2331 lines
1.9 MiB
2331 lines
1.9 MiB
<!DOCTYPE html>
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<!-- Created by pdf2htmlEX (https://github.com/pdf2htmlEX/pdf2htmlEX) -->
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<html xmlns="http://www.w3.org/1999/xhtml">
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<head>
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<meta charset="utf-8"/>
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<meta name="generator" content="pdf2htmlEX"/>
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<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"/>
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<style type="text/css">
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/*!
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* Base CSS for pdf2htmlEX
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* Copyright 2012,2013 Lu Wang <coolwanglu@gmail.com>
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* https://github.com/pdf2htmlEX/pdf2htmlEX/blob/master/share/LICENSE
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*/#sidebar{position:absolute;top:0;left:0;bottom:0;width:250px;padding:0;margin:0;overflow:auto}#page-container{position:absolute;top:0;left:0;margin:0;padding:0;border:0}@media screen{#sidebar.opened+#page-container{left:250px}#page-container{bottom:0;right:0;overflow:auto}.loading-indicator{display:none}.loading-indicator.active{display:block;position:absolute;width:64px;height:64px;top:50%;left:50%;margin-top:-32px;margin-left:-32px}.loading-indicator img{position:absolute;top:0;left:0;bottom:0;right:0}}@media print{@page{margin:0}html{margin:0}body{margin:0;-webkit-print-color-adjust:exact}#sidebar{display:none}#page-container{width:auto;height:auto;overflow:visible;background-color:transparent}.d{display:none}}.pf{position:relative;background-color:white;overflow:hidden;margin:0;border:0}.pc{position:absolute;border:0;padding:0;margin:0;top:0;left:0;width:100%;height:100%;overflow:hidden;display:block;transform-origin:0 0;-ms-transform-origin:0 0;-webkit-transform-origin:0 0}.pc.opened{display:block}.bf{position:absolute;border:0;margin:0;top:0;bottom:0;width:100%;height:100%;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;user-select:none}.bi{position:absolute;border:0;margin:0;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;user-select:none}@media print{.pf{margin:0;box-shadow:none;page-break-after:always;page-break-inside:avoid}@-moz-document url-prefix(){.pf{overflow:visible;border:1px solid #fff}.pc{overflow:visible}}}.c{position:absolute;border:0;padding:0;margin:0;overflow:hidden;display:block}.t{position:absolute;white-space:pre;font-size:1px;transform-origin:0 100%;-ms-transform-origin:0 100%;-webkit-transform-origin:0 100%;unicode-bidi:bidi-override;-moz-font-feature-settings:"liga" 0}.t:after{content:''}.t:before{content:'';display:inline-block}.t span{position:relative;unicode-bidi:bidi-override}._{display:inline-block;color:transparent;z-index:-1}::selection{background:rgba(127,255,255,0.4)}::-moz-selection{background:rgba(127,255,255,0.4)}.pi{display:none}.d{position:absolute;transform-origin:0 100%;-ms-transform-origin:0 100%;-webkit-transform-origin:0 100%}.it{border:0;background-color:rgba(255,255,255,0.0)}.ir:hover{cursor:pointer}</style>
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<style type="text/css">
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/*!
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* Fancy styles for pdf2htmlEX
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* Copyright 2012,2013 Lu Wang <coolwanglu@gmail.com>
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* https://github.com/pdf2htmlEX/pdf2htmlEX/blob/master/share/LICENSE
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*/@keyframes fadein{from{opacity:0}to{opacity:1}}@-webkit-keyframes fadein{from{opacity:0}to{opacity:1}}@keyframes swing{0{transform:rotate(0)}10%{transform:rotate(0)}90%{transform:rotate(720deg)}100%{transform:rotate(720deg)}}@-webkit-keyframes swing{0{-webkit-transform:rotate(0)}10%{-webkit-transform:rotate(0)}90%{-webkit-transform:rotate(720deg)}100%{-webkit-transform:rotate(720deg)}}@media screen{#sidebar{background-color:#2f3236;background-image:url("data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSI0IiBoZWlnaHQ9IjQiPgo8cmVjdCB3aWR0aD0iNCIgaGVpZ2h0PSI0IiBmaWxsPSIjNDAzYzNmIj48L3JlY3Q+CjxwYXRoIGQ9Ik0wIDBMNCA0Wk00IDBMMCA0WiIgc3Ryb2tlLXdpZHRoPSIxIiBzdHJva2U9IiMxZTI5MmQiPjwvcGF0aD4KPC9zdmc+")}#outline{font-family:Georgia,Times,"Times New Roman",serif;font-size:13px;margin:2em 1em}#outline ul{padding:0}#outline li{list-style-type:none;margin:1em 0}#outline li>ul{margin-left:1em}#outline a,#outline a:visited,#outline a:hover,#outline a:active{line-height:1.2;color:#e8e8e8;text-overflow:ellipsis;white-space:nowrap;text-decoration:none;display:block;overflow:hidden;outline:0}#outline a:hover{color:#0cf}#page-container{background-color:#9e9e9e;background-image:url("data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSI1IiBoZWlnaHQ9IjUiPgo8cmVjdCB3aWR0aD0iNSIgaGVpZ2h0PSI1IiBmaWxsPSIjOWU5ZTllIj48L3JlY3Q+CjxwYXRoIGQ9Ik0wIDVMNSAwWk02IDRMNCA2Wk0tMSAxTDEgLTFaIiBzdHJva2U9IiM4ODgiIHN0cm9rZS13aWR0aD0iMSI+PC9wYXRoPgo8L3N2Zz4=");-webkit-transition:left 500ms;transition:left 500ms}.pf{margin:13px auto;box-shadow:1px 1px 3px 1px #333;border-collapse:separate}.pc.opened{-webkit-animation:fadein 100ms;animation:fadein 100ms}.loading-indicator.active{-webkit-animation:swing 1.5s ease-in-out .01s infinite alternate none;animation:swing 1.5s ease-in-out .01s infinite alternate none}.checked{background:no-repeat url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAYAAADEtGw7AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH3goQDSYgDiGofgAAAslJREFUOMvtlM9LFGEYx7/vvOPM6ywuuyPFihWFBUsdNnA6KLIh+QPx4KWExULdHQ/9A9EfUodYmATDYg/iRewQzklFWxcEBcGgEplDkDtI6sw4PzrIbrOuedBb9MALD7zv+3m+z4/3Bf7bZS2bzQIAcrmcMDExcTeXy10DAFVVAQDksgFUVZ1ljD3yfd+0LOuFpmnvVVW9GHhkZAQcxwkNDQ2FSCQyRMgJxnVdy7KstKZpn7nwha6urqqfTqfPBAJAuVymlNLXoigOhfd5nmeiKL5TVTV+lmIKwAOA7u5u6Lped2BsbOwjY6yf4zgQQkAIAcedaPR9H67r3uYBQFEUFItFtLe332lpaVkUBOHK3t5eRtf1DwAwODiIubk5DA8PM8bYW1EU+wEgCIJqsCAIQAiB7/u253k2BQDDMJBKpa4mEon5eDx+UxAESJL0uK2t7XosFlvSdf0QAEmlUnlRFJ9Waho2Qghc1/U9z3uWz+eX+Wr+lL6SZfleEAQIggA8z6OpqSknimIvYyybSCReMsZ6TislhCAIAti2Dc/zejVNWwCAavN8339j27YbTg0AGGM3WltbP4WhlRWq6Q/btrs1TVsYHx+vNgqKoqBUKn2NRqPFxsbGJzzP05puUlpt0ukyOI6z7zjOwNTU1OLo6CgmJyf/gA3DgKIoWF1d/cIY24/FYgOU0pp0z/Ityzo8Pj5OTk9PbwHA+vp6zWghDC+VSiuRSOQgGo32UErJ38CO42wdHR09LBQK3zKZDDY2NupmFmF4R0cHVlZWlmRZ/iVJUn9FeWWcCCE4ODjYtG27Z2Zm5juAOmgdGAB2d3cBADs7O8uSJN2SZfl+WKlpmpumaT6Yn58vn/fs6XmbhmHMNjc3tzDGFI7jYJrm5vb29sDa2trPC/9aiqJUy5pOp4f6+vqeJ5PJBAB0dnZe/t8NBajx/z37Df5OGX8d13xzAAAAAElFTkSuQmCC)}}</style>
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<style type="text/css">
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.ff0{font-family:sans-serif;visibility:hidden;}
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/*
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Copyright 2012 Mozilla Foundation
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Copyright 2013 Lu Wang <coolwanglu@gmail.com>
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Apachine License Version 2.0
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*/
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(function(){function b(a,b,e,f){var c=(a.className||"").split(/\s+/g);""===c[0]&&c.shift();var d=c.indexOf(b);0>d&&e&&c.push(b);0<=d&&f&&c.splice(d,1);a.className=c.join(" ");return 0<=d}if(!("classList"in document.createElement("div"))){var e={add:function(a){b(this.element,a,!0,!1)},contains:function(a){return b(this.element,a,!1,!1)},remove:function(a){b(this.element,a,!1,!0)},toggle:function(a){b(this.element,a,!0,!0)}};Object.defineProperty(HTMLElement.prototype,"classList",{get:function(){if(this._classList)return this._classList;
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(function(){/*
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pdf2htmlEX.js: Core UI functions for pdf2htmlEX
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Copyright 2012,2013 Lu Wang <coolwanglu@gmail.com> and other contributors
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https://github.com/pdf2htmlEX/pdf2htmlEX/blob/master/share/LICENSE
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*/
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pdf2htmlEX.Viewer=Viewer;})();
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try{
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pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({});
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</script>
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<title></title>
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</head>
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<body>
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<div id="sidebar">
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<div id="outline">
|
||
<ul><li><a class="l" href="#pf5" data-dest-detail='[5,"XYZ",28.346,255.118,null]'>Integral Data Types</a><ul><li><a class="l" href="#pfa" data-dest-detail='[10,"XYZ",28.346,212.159,null]'>Fixed Width Integers</a></li><li><a class="l" href="#pfd" data-dest-detail='[13,"XYZ",28.346,228.21,null]'>size_t and ptrdiff_t</a></li><li><a class="l" href="#pfe" data-dest-detail='[14,"XYZ",28.346,204.571,null]'>Signed/Unsigned Integer Characteristics</a></li><li><a class="l" href="#pf14" data-dest-detail='[20,"XYZ",28.346,228.21,null]'>Promotion, Truncation</a></li><li><a class="l" href="#pf18" data-dest-detail='[24,"XYZ",28.346,228.21,null]'>Undefined Behavior</a></li></ul></li><li><a class="l" href="#pf20" data-dest-detail='[32,"XYZ",28.346,255.118,null]'>Floating-point Types and Arithmetic</a><ul><li><a class="l" href="#pf21" data-dest-detail='[33,"XYZ",28.346,228.21,null]'>IEEE Floating-point Standard and Other Representations</a></li><li><a class="l" href="#pf2a" data-dest-detail='[42,"XYZ",28.346,217.069,null]'>Normal/Denormal Values</a></li><li><a class="l" href="#pf2c" data-dest-detail='[44,"XYZ",28.346,228.21,null]'>Infinity ()</a></li><li><a class="l" href="#pf2e" data-dest-detail='[46,"XYZ",28.346,228.21,null]'>Not a Number (NaN)</a></li><li><a class="l" href="#pf30" data-dest-detail='[48,"XYZ",28.346,186.503,null]'>Machine Epsilon</a></li><li><a class="l" href="#pf31" data-dest-detail='[49,"XYZ",28.346,228.21,null]'>Units at the Last Place (ULP)</a></li><li><a class="l" href="#pf33" data-dest-detail='[51,"XYZ",28.346,228.21,null]'>Cheatsheet</a></li><li><a class="l" href="#pf36" data-dest-detail='[54,"XYZ",28.346,228.21,null]'>Limits and Useful Functions</a></li></ul></li><li><a class="l" href="#pf38" data-dest-detail='[56,"XYZ",28.346,255.118,null]'>tmp</a><ul><li><a class="l" href="#pf38" data-dest-detail='[56,"XYZ",28.346,203.183,null]'>Arithmetic Properties</a></li><li><a class="l" href="#pf3b" data-dest-detail='[59,"XYZ",28.346,228.21,null]'>Special Values Behavior</a></li><li><a class="l" href="#pf3c" data-dest-detail='[60,"XYZ",28.346,228.21,null]'>Floating-Point Undefined Behavior</a></li><li><a class="l" href="#pf3d" data-dest-detail='[61,"XYZ",28.346,228.21,null]'>Detect Floating-point Errors </a></li></ul></li><li><a class="l" href="#pf3f" data-dest-detail='[63,"XYZ",28.346,255.118,null]'>Floating-point Issues</a><ul><li><a class="l" href="#pf45" data-dest-detail='[69,"XYZ",28.346,214.682,null]'>Catastrophic Cancellation</a></li><li><a class="l" href="#pf4a" data-dest-detail='[74,"XYZ",28.346,228.21,null]'>Floating-point Comparison</a></li></ul></li></ul></div>
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</div>
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<div id="page-container">
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<div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">Mo<span class="_ _0"></span>dern<span class="_ _1"> </span>C++</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">Programming</div><div class="t m0 x2 h3 y3 ff2 fs1 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span>Basic<span class="_ _3"> </span>Concepts<span class="_ _3"> </span>I<span class="_ _0"></span>I</div><div class="t m0 x3 h4 y4 ff2 fs2 fc0 sc0 ls0 ws0">Integral<span class="_ _4"> </span>and<span class="_ _4"> </span>Flo<span class="_ _5"></span>a<span class="_ _6"></span>ting-point<span class="_ _4"> </span>Types</div><div class="t m0 x1 h5 y5 ff3 fs3 fc0 sc0 ls0 ws0">F<span class="_ _5"></span>ederico<span class="_ _7"> </span>Busato</div><div class="t m0 x4 h6 y6 ff4 fs4 fc0 sc0 ls0 ws0">2024-03-29</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">T<span class="_ _6"></span>able<span class="_ _8"> </span>of<span class="_ _8"> </span>Contents</div><div class="t m0 x6 h8 y8 ff1 fs4 fc2 sc0 ls0 ws0">1<span class="_ _9"> </span><span class="fs2 fc0">Integral<span class="_ _4"> </span>Data<span class="_ _a"> </span>T<span class="_ _b"></span>yp<span class="_ _c"></span>es</span></div><div class="t m0 x7 h6 y9 ff4 fs4 fc0 sc0 ls0 ws0">Fixed<span class="_ _d"> </span>Width<span class="_ _d"> </span>Integers</div><div class="t m0 x7 h6 ya ff5 fs4 fc0 sc0 ls0 ws0">size<span class="_ _7"> </span>t<span class="_ _d"> </span><span class="ff4">and<span class="_ _d"> </span></span>ptrdiff<span class="_ _e"> </span>t</div><div class="t m0 x7 h6 yb ff4 fs4 fc0 sc0 ls0 ws0">Signed/Unsigned<span class="_ _d"> </span>Integer<span class="_ _d"> </span>Cha<span class="_ _5"></span>racteristics</div><div class="t m0 x7 h6 yc ff4 fs4 fc0 sc0 ls0 ws0">Promotion,<span class="_ _d"> </span>T<span class="_ _6"></span>runcation</div><div class="t m0 x7 h6 yd ff4 fs4 fc0 sc0 ls0 ws0">Undefined<span class="_ _d"> </span>Behavio<span class="_ _5"></span>r</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">1/77</div><a class="l" href="#pf5" data-dest-detail='[5,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:47.076000px;bottom:158.775000px;width:133.371000px;height:14.745000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfa" data-dest-detail='[10,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:140.425000px;width:89.110000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfd" data-dest-detail='[13,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:121.002000px;width:99.243000px;height:11.068000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfe" data-dest-detail='[14,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:101.466000px;width:168.383000px;height:11.955000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf14" data-dest-detail='[20,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:83.508000px;width:96.803000px;height:10.156000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf18" data-dest-detail='[24,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:65.550000px;width:83.036000px;height:8.911000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">T<span class="_ _b"></span>able<span class="_ _f"> </span>of<span class="_ _8"> </span>Contents</div><div class="t m0 x6 h8 yf ff1 fs4 fc2 sc0 ls0 ws0">2<span class="_ _9"> </span><span class="fs2 fc0">Floating-p<span class="_ _c"></span>oint<span class="_ _a"> </span>T<span class="_ _b"></span>yp<span class="_ _c"></span>es<span class="_ _4"> </span>and<span class="_ _a"> </span>Arithmetic</span></div><div class="t m0 x7 h6 y10 ff4 fs4 fc0 sc0 ls0 ws0">IEEE<span class="_ _d"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>Standa<span class="_ _5"></span>rd<span class="_ _d"> </span>and<span class="_ _d"> </span>Other<span class="_ _d"> </span>Rep<span class="_ _5"></span>resentations</div><div class="t m0 x7 h6 y11 ff4 fs4 fc0 sc0 ls0 ws0">No<span class="_ _5"></span>rmal/Denormal<span class="_ _d"> </span>V<span class="_ _5"></span>alues</div><div class="t m0 x7 h6 y12 ff4 fs4 fc0 sc0 ls0 ws0">Infinit<span class="_ _5"></span>y<span class="_ _d"> </span>(<span class="ff7">∞</span>)</div><div class="t m0 x7 h6 y13 ff4 fs4 fc0 sc0 ls0 ws0">Not<span class="_ _d"> </span>a<span class="_ _d"> </span>Numb<span class="_ _c"></span>er<span class="_ _d"> </span>(<span class="ff5">NaN</span>)</div><div class="t m0 x7 h6 y14 ff4 fs4 fc0 sc0 ls0 ws0">Machine<span class="_ _d"> </span>Epsilon</div><div class="t m0 x7 h6 y15 ff4 fs4 fc0 sc0 ls0 ws0">Units<span class="_ _d"> </span>at<span class="_ _d"> </span>the<span class="_ _d"> </span>Last<span class="_ _d"> </span>Place<span class="_ _d"> </span>(<span class="ff5">ULP</span>)</div><div class="t m0 x7 h6 y16 ff4 fs4 fc0 sc0 ls0 ws0">Cheatsheet</div><div class="t m0 x7 h6 y17 ff4 fs4 fc0 sc0 ls0 ws0">Limits<span class="_ _d"> </span>and<span class="_ _d"> </span>Useful<span class="_ _d"> </span>F<span class="_ _5"></span>unctions</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">2/77</div><a class="l" href="#pf20" data-dest-detail='[32,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:47.076000px;bottom:190.569000px;width:241.683000px;height:14.744000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf21" data-dest-detail='[33,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:172.218000px;width:239.531000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf2a" data-dest-detail='[42,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:152.462000px;width:107.430000px;height:11.955000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf2c" data-dest-detail='[44,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:133.259000px;width:51.722000px;height:11.955000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf2e" data-dest-detail='[46,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:114.056000px;width:89.192000px;height:11.955000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf30" data-dest-detail='[48,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:95.406000px;width:70.153000px;height:10.849000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf31" data-dest-detail='[49,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:75.650000px;width:125.377000px;height:11.955000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf33" data-dest-detail='[51,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:58.938000px;width:47.737000px;height:8.911000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf36" data-dest-detail='[54,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:39.735000px;width:118.237000px;height:8.911000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf4" class="pf w0 h0" data-page-no="4"><div class="pc pc4 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">T<span class="_ _b"></span>able<span class="_ _f"> </span>of<span class="_ _8"> </span>Contents</div><div class="t m0 x7 h6 y18 ff4 fs4 fc0 sc0 ls0 ws0">Arithmetic<span class="_ _d"> </span>Prop<span class="_ _c"></span>erties</div><div class="t m0 x7 h6 y19 ff4 fs4 fc0 sc0 ls0 ws0">Sp<span class="_ _c"></span>ecial<span class="_ _d"> </span>V<span class="_ _5"></span>alues<span class="_ _d"> </span>Behavio<span class="_ _5"></span>r</div><div class="t m0 x7 h6 y1a ff4 fs4 fc0 sc0 ls0 ws0">Floating-P<span class="_ _5"></span>oint<span class="_ _d"> </span>Undefined<span class="_ _d"> </span>Behavior</div><div class="t m0 x7 h6 y1b ff4 fs4 fc0 sc0 ls0 ws0">Detect<span class="_ _d"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>Erro<span class="_ _5"></span>rs</div><div class="t m0 x9 ha y1c ff8 fs6 fc0 sc0 ls0 ws0">⋆</div><div class="t m0 x6 h8 y1d ff1 fs4 fc2 sc0 ls0 ws0">3<span class="_ _9"> </span><span class="fs2 fc0">Floating-p<span class="_ _c"></span>oint<span class="_ _a"> </span>Issues</span></div><div class="t m0 x7 h6 y1e ff4 fs4 fc0 sc0 ls0 ws0">Catastrophic<span class="_ _d"> </span>Cancellation</div><div class="t m0 x7 h6 y1f ff4 fs4 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>Compa<span class="_ _5"></span>rison</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">3/77</div><a class="l" href="#pf38" data-dest-detail='[56,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:179.782000px;width:91.463000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3b" data-dest-detail='[59,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:160.579000px;width:101.011000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3c" data-dest-detail='[60,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:141.376000px;width:145.801000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3d" data-dest-detail='[61,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:122.173000px;width:130.441000px;height:12.349000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3f" data-dest-detail='[63,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:47.076000px;bottom:91.149000px;width:137.937000px;height:14.745000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf45" data-dest-detail='[69,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:72.799000px;width:108.565000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf4a" data-dest-detail='[74,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:49.490000px;bottom:53.596000px;width:112.744000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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||
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D2TtZRybNu2rWwinognEul0xjBMTdNcLtPr9ZmmKTXZ1Ni8avXqirKyu1nuMzM798Mf/rDvypWmhvpNG9fX1K2QmiHlreee3qFN7ypYpcyk02/u2VNQXOJyuVILcyPj4/68wsaGhurKck2KeHR+eHTcymYtJfLzwiMjI1LK+dmZRDozMjqenxd2pG663AV5wXQqGQ6Hp6cmU6m04XIPDY/6/YGtO3eUFRcGfF6hVDw6d6nnSrigqKaywtDl7S7F7V720sevReoS2VTi2KEDxzrOVa9sevyRhyvKSllZBYBIBfAPlWXZX/jSF91u88Chw6X5eUXFxcFg0OX2aFJIqRmGYTvK5TJsWzl2VknN63Y5ji2l7nK70qm0lMLQNaGUkCKTdTKZVDaTlZqWzWYzmXQikZqZmbFsJxAIFhcXmoZuK7Fjx672tWtvN7DqOM6LL7+yf/9bRfl5D91/78qWVnH90NFlyXW7Q03Fktv6juOIO+6TKpQ6eux4uLCoIBR4+YXnt9+z+2r/lVBevq6yxaXl5RUVQimhhJAilUwYpuvi+XP+YHhhYX5gaDgSDhYW5O9761A2kw6HQllbNa5p0zKJlQ0r3zpwUHOys/Ox9nXtl/v6rw4MPvDIY20tDbomNCkH+vsOHz/1wCOPFoYDudesaZrjOIvzAW4eTF2yY6u29AlLr4bjOEopXTjHD7z5zAuv17Ws/dd//Edej5u/5ACIVAD/wIyNT/zgmR/Y2cz5i52RcLCosDgcDrpcbpfb1DVd0w1D14UUbrdbKSWVozRdarrtKCtrpbPZTDptZbPeQGBldUVVRZnjOPMLC7HoQnRhYT4ay2ateCKZyWQymXQymU4kk8pRmq573G6v37958+bmpub8SP5ieSqlei5f/trXv+Ey9Pa1rTt33uPx+5eecX837+jdjqdOTk6ahnnm1PFQQZHfHwoHvGNjowvRmMcXyMvLq6yo6Oq8aAltTWur29SVEFKp/itXCgqLZmamBgYGZuZjoYBvfn5uZmo6k7XCkfxgMOQPBgxhD4+MlpSWD/ZfnpuP+oMhXyDg9fk3bdqcHw66TSOdSiipKcfqunx13do1QjniLmbZipum1d7yOUqITHy+49ix19861LZp64c/8PhvzvkLAIhUAPg5pmZmvvnNrxumu6PjRPPK+vyCQn8waJiuYMBvmC7T0BKpTCKRjMUT09MziWQilUmno7FkIpHKZtPppJW1NeHopsvrcWuGu7iocGVTc3NTY11dXUHY71jZ6Nz01Mzs2Nj47NxcLJ5QjhONJeKJRDQaTSUTLpcrkpfnD4Z27rq3taVlcnr6//l//5uuaU0ra5944olQON8RQsob8vR2A6K3S7o7jLBef1zatj0xPhJNZEqLCi5eOFdRVTM8Ota4csWxo0dqalZkMinT45scHqhvbq0oL01lbLfLEEpqmjiwb89C0iopyh8bGdmydbudjg+Njh45dsrn99XV1Z3qOL1x65byiH9qIbUQW/Ca+qnT59e2t13qvGQGQo899EBRQb5UtmNbfX294zOxxubm4kieEI64/Zaui6PCt3yPN3/hOI6Tiu/f+8beQyd33v/Qx5960njPdgcDQKQCwK/G8MjIM8/8cHpmZnhwsH5FjT+Uf3VoRGSTHq9vfHLKMAyhVNayhbKFEobpEkLpmmYpoUvNtm2325XJWraVWdW4orFpVVl5RSAYFMqJxWKT09Nj4xOxeDwvkl9bXb2itjocDlnp1Pz83MzM9MT4+PTcfCwWT6VSC9GYZWWV0C3bTiZSFSWFW7dtWdO2TtP1X34y5c8dklwMX9u2kol4V3dPY1OLyqYvdHY5SkTyC+pqa+Zmps6dv1hSXh7Jywv6PL09Pd5wftPKekPXHceKLixMToyf7+x+4MEHgz6vlc2OjwwNjYzue+tAS8uqnbt25eXljQz29/ZdOXv2woc+9OThg2/NzCfyCwodpQpLylqaGspKCjXlXL3SF4vOZ3RvQX6kprLibrYsuPOfLj3ZVQgRnZ3a+8brZy71PfDgw48+9AAHqwIgUgH8JnIc57kXXhgeGhgYGMykknUr6pJZdeTQwYjfk19SPjE97XV7pZTZbMYRIjcRUkhNCKFrUghhK+F2uYRSPrfxsY99tGXNBiFyE0ZzS3mufR2LLnR1nT97+lRvX7/H6w2E8lbW19XVrWior80L+mOx6Njo6PGOMx2nzji2XVNddd/ue5tbVklNFzc22C98mujPTdWlf6qE0KRUSs1MT2cdNTM53t/Xl7CcluYWj8uIRmMramsmpqYSyWQqEe+7OvjoI49YtiqIhG0rE4tFw3n5136UEkI5sdhCIJgnZG5D08XfIB3bikbnjx891j84Ul5VpZSam4/ee//9Jfl5uq4Jx5pfWAgEw7Ztmaap3TR+/K6ydem35L62ktGTx4+/vu/twsraP/rMpwsL8vksACBSAfymSGcyX/7Kl/xeT8eZC6bmrGppjmbkvjdfX1lZapneeDTmcrndbrcUKhqP61JquuEolUmn/D6/4zhZx1G2beh6WXHBH/zBHwbzi4USi6uackt/hBRC5fbyVJrUBgd633jj9a6uS8pRhqG7XO7i8srmxsZodOH48WORYHDTpvZ7731Ad7nErZZGLc2s2x0ZerszRcXtTyIVS4Ybl52bGluY7zhztrm5ORWLHjr0tu4Nbt6ytbK0+Pnnn5Omt7Qokp9fMDo8FMorWLtmtZRSKWfx51vZzPD4dHVlmbxdDSsllZqZnnhzz5tdPVda17YtzM6UVFVvWL++MC8khJJSnjtzKhApLCgoDvrcuQtw59v6S9/a4sqqpQmrrq+0Uo5jZ5KH9u15/cCx4uoVf/TZT5eXFPOhAECkAvg1S6ZST3/rG8l0uru7pzgvVFZVdXVksuPIwfoVNZrLn06ns5mMabps5WhSU0K5TFc2m7Ud29B0y7Y0Tctms44SlWUln/nMZwpLKt9JSZkbKxTq+mDq9RU813JqYnzk4vlzZ8+eHh2bVI4lNb0wP791VfO27duKisuEUOKu7++/szD/Lp4mhJifX3B7fW5Tv/ON8ncSVkghRSIWvXylv6ik7Orl7umZGVtztbc2HztyKG2LSEFBdWVlJpNORKMjk9Otq9c01tdpUgghJsZGDh050tCytqVhhdR0KdRtcllmU4mBq1dPnT4tTbffH5ienvaF8nbu2F6QF5RCzEyO9/X3x9L2rh07dHm3B2Xd7n3lYvz6F46UMjozdfTIkdPnOxtWrXny8ceKGFUFiFQiFcCvS1d39xuvvTw5PTM8NLRmVVMov+jipd7ezgvta1ePTM0Lx1FKGYYhhCOlns1mHEdpum7oRiyZMDTN7XJJKS3Laqir+kef+L1QXuEts0lqUjk3jmUKpYRQStnKOXHy1OsvPZ+fF26or7l39+5wXoES6najpzfn491nmRAim826THNoZGxkZPhK32WvL7D7/vv9Xo8U6u43CpgcH42nsj6vZ3x0JBCO2FZ2enomk4pNzsVbV7VEowt+n+/cqY5QQdFDDz6oSaGUsrPZWCLeebGzvLKysqLCNAznxsVbi29UCGVnM5OTU2++8XrKVlbWiiWS9z34YElRUWlxgSZENpsxTLcQt3jjv8AFeSdYc//kKGVlTp04dvDgYeENfebTn66rqWJXVYBIBYC/V3v3H7h4rmNyZm5o8Oq69nbNcJ270Nnfe2nzxo2WMGKxaCKZ1DU9kUzomub3By0ra9tWJps1DDM3J9XUpWGYa1tWfvx3P+OIa0eMLs4fVc4t7kfnhlcd4SipDQ0NfePpp/2mUVGS/8RjjxSWlCshlp5uuvTI0GUptvQE0dutfL/xCVIKNT83Ozo1Mzc55khDSC0S9u99c2/b+k2rVrWGAt6lp6TeMv6u/WQhLdsautp3trN78+atMxMjw6Nj/lB+c33N0UNvF1asWFlX2dvb29iyOuj3S7l0uZK0rOzo2PipM+ceeeQRt6mJGyeJvvPihXQc++LZkwePnFjdtm5yYtw0Tc0d2Lljm99t3PIuv7jVXNtbXpxbbnGQG/IW4tq+qkKInnMnvvvMs+684n/1J/+0pqKczwtApALAe04pdebcuUNv7x8aGV+Ym1mzepUjzUPHjsemxpuam9NZJxAMud0e27bS6bRl2UKoTCaTTKUsy5JCSCG8Pr8mlRBq68b2+x5+0nR5bnnsk1JqcRhVSunkxk+luDo4tP/AgaErVypLi9rXtm7YtPnmxftLp4rezTu65SOLL2NsbNSy7L/4qy9u3Lhp29bNc3Ozbpd55MjR1WvWjo0MSU0vLa9avXqVqevLfuHS+anL+tWxrXPnzmVs4XGb0dmZoZHRytr6pqamgMfovXzFNHVHybKKylDAJ5f8qHQi3nGqY3RsorKuoaa6sqQw/5a1nfsGy8r29nRfvHBxeGxSCeELR7Zv3VJcWFAQybvlYOq7vVA3vymVm46hlKNUMjZ3eO+brx/u+Gd/8s83tq3hgwMQqQDwHnKU+urffU1YyYvdvdKx17Y2xzLOvn0HvIaob2odGBgoKirxeNy6ruu6kUolbdt2uz1CKMdxFhYWNCnjiYSUUpPi8Yd23/PQB2xbCXnt/24Op8UBVKWUI5SQ2iuvv3Hu9Cm/x9W2quH++x+Qhit3tOkt96VfXPFz5xHT2yXX0tcwMTb67W9+0x0M5efnP/XBD1zuu5JOZwxdGx6b2rxx3UsvPO/2+h58+LH8SFiKO624WnY2VTaTNkyXEiKTWHjrwMGNW3fkhQLjY6NdvX1KiYL8PKkZq5qbpSblknkLtpU5uP/N+ZRTXFK2rr3N1IS4cUGYECIeixlun6nLbCp+6K19g1ML9XXVJ06e2bZjh2VZ69e1e1zGLTP6Dvf9b/m4k/sJueO4csUsRG4HVkNYX/nil870DHzv6W9onKcKEKkA8B6xbftnz/1sdmqiq+eKKZ2mpoZ4xnnjjTeriyKB/ML5aMIwjEgkXzmOZVu5pEql0i6XGY3Hg36/aZq5msmkkxvXrd31wKO67hJC2I6jLz3R9HqtLl0plcpkjp082XHyZDYZX9vatGXThuLSciG1paebLluZ/m7f3S0LbGZmdm4hmkmnE4l4KBgYGegP5uWXlpWXlZZOTo6PT06NjwzX1TfUVFdd6u5WjhUIhjXTXVlWIu56ZwCxZH3V4rKwTDrVfakrkJdfWlw0MDDg8gaqKytuXDXlzM/NjoyOxePJ+pUNPp/X7TKvVaNtjY6NX7hwobvn8tZd9zbU1QR8numJsSNHjmqm6+KFi5GCog9/9CP54eAdNjG4m2u1ODVWLk6QENfma+QW/ivHuXTqyFe/+9M//dM/Xbu6lU8QQKQCwK/e5PT0T370w2Qme/r06brK8toVKwZGJw+9/db6Na2JrFKOI4UyDJfP789ms7quK6UsyxJCGKYphdB0Q9Oklc16DO2hhx5oWNWe+7GW4yRSCeU4QX9A07RcpL2TQULZjtNx5szhgwezqfiqxpVbN28sr6xRN219essE/IU71VFiaHi0urJ88OqVV19+MW2pktKS4uKSXbt2idxgoaYtLCxc6e8PhsKGrktlz88vaKbL1GU4nFdcXLIQjYZDoaWbSf0CiayUsm37tVde9gXDpmmWlZVVV9cszilQSjmO4zhOT9cFdyCyorZaCJFMxE90nElGZztOnS4oLnO7jJKyCiX1LZs3hgKByeGrIxPTq1avdpnXtt+3HZXbrfZdXaV3YnRxwuz1Nl38InehhJ355le+eH5o5ut//SXJYCrw2xSp+uc//3kuBID32sjo6A+++7QjxKmOjo1rWqpqai729O97/dV7t22enI/bluM4TjAYNN2eXJhqmubx+hzlSCkNXdd13RFKk1IK58NPfbC+sVVoUgihhMpks16X2+Vy65qeW7P/zt77UszFYn/zt3/bd6kzEvJ/7MMf2LZtuy8YlppcOoAqbloDtPTxWwbrnR8fHBr56l9/KeTzXLzUs37dug0bNxUXRA4dfHv3Aw8FAn4hpSZlOpM1df3E0SIF7WMAACAASURBVKNKSstRAZ8rmc5kU4lVq1YFg+FEIv7MD79veHzhcNjQdXn7l7T0Vvstn6BpWmNj4+jQ1Ynp2fHJqUQsqhuuoN+fWyWmaZqu68UlpZFInhBiaKD/0uX+TCa9or6+fd36VDxqGOaZjhPj4+MDg0OFpeXFJWXl5aW6fm3cenR48KXX3ywoKvH7fLlZE7eM+5uvqmVZud8ulhSqEIv7hgmlVO4sA0dqNRUlhw8ebl27Lj+Sx0cJ+C2h6zqRCuC9pZQ6ePjwgbfejCZSly51t69ZVVhacanv6rmOY/fu2jUbT2ua5na7TUP6A0Hbsk3TZZpmboappum5W9ia1EzD9BjaIw8/XNewKjeB0rKdrG2buialZui6o5ysldWkJqVQSk3Pz7/2xhuvvfJKQdC3eUP7ww89VFhcJnKTV++4w9TN7mYAL9e4may1d+/eRHT+E5/8vYHBwUQyHo/HZ+ejdfUrt+/Y4ff7pZRzc/OdnRdPnz4ldHNV6+rY3MzI8FAgFEmnUoXFxZmsdanr4ukz59e2tcXmZ2fn5icmJ4uLi+/8ehYr8DaZKKtrav0uw84k5xPpgkior/+qUDIQCIilE3ClyGazUxNjpjdYUlw4OtA/ODFTX1uVzWT8/kBJaemV3u75WGx+PhbKyzN1LR6d7zh6eGxqJuj3Hj9xoqKqxjQNeXd/JXL1vOwtLL7+d/6zQUophC8Unhq6evJC1z07d/CBAn57IpXb/QDeQ7Zt//RnP12Ym+m81JuIzbetXSNM74FDRzPzk02ta6dnZlxuj5XNetxmeVmZZctkKpXJpG3bNk1T03WP25PNZlwut2VbRXmBJ558yh+KCCmUElnLylpZwzANXZNSZrLZ3itXovMLuqF5Pd5z58/39/bmh4Pr21s3btrqcnsWB+uWHhl1u/q88/TKWy78dxznjTfesNLp2pUNRUVFP37mhw0NDeOTkz6f3+s2B4dGPve5z+ZGEA/s36eZrlQi4fZ60+n0qlWr80KBVDIZyc/XTTObTl0dGJyani7Iz++9fFnXjZUraq9e7W/fuCUSCt4QcLdPwNs+Qam52emzp08XltdWVxSPjo0HgqHSsjLh2O+UrnIGrg7kFxUnE7GBkfGyovzxiclEMjk/N5fNpLu7LycSiUhRyeNPPFZRVqYL+9yZ0z5/4MzZ8xXV1Zs2bkolY5pu+rweccuFbLd6kTdtEyZzq/tz84+FFMpRM8NX/sufffGf/cm/3LZpPR8r4LcBc1IBvLeF+vVvfF3T5LHjJ0IB39o1q22h/ez5l007tWbdhtHxCU0aui4T8bjPHygqLMralqkbSijLsm3HDvj98XhcCOHz+72G/N1//BmXxy+kUkpkbcuybU1Kl2EIKZWjnnvppaH+y488eP/3fvxsJpkoLCpurCl75NHHPf5A7mDPZYdC5U5MvXnx/rJOvfPJn9c3UhUjw0MXLvXmhfwnjh0bGR78wAee7LzUm0pEP/WpT/V0X9JNV0vLKsM0Fm9rX7ncfebMed0017a1O1Y2FouuXrNWCNHT3TU3vxAI5VWVl1wZGM4LBQ+8td/l8T344IORvLAm5aXevqaVK5wlm0YtfWHXzoC91Qqwm8tVCjE6Onqpp8fn8zU0tYQDvqWHlwqlui91Zh2RSaUiBYWnTh5vaV092Ndz4uQpw+1ra28bHxudi6U/+tEPF+VHhLJ03ZgcHR6ZjRlO+sSZCzt27FhRXblsWPQOWx8s/pFzbaNWsWwFlRDqG1/+wuGz3T/6/neWDcECeL9GKrf7Abwn4onEt57+phTOyY5TJYWRlpaWlCVe37uvwOeqWdk4NjZhmi7Lti3b9vu9ZaVlSghd1zUp3W63rhuOY2ua7vP5DMOMBLxPfvApfzgiNSWEyFqW5di6ppm6lpvfmbHtZ37w/WAwdKGrxxBq7arGR++/d9O2nabLlSudZbeSl9bb7dz9HICFhfloPJFJJXTDWL+ufduOXSc7TgV8Xn/A33fl6r33PVBaWqrp+jsTL5Xqvty/ds3q2pqaF557dnp2bsOmrVJqZ8+eqaquLSstefXlFxcS6TVr25VtRSKRyrKSK/39ff0DU1OTXrfZ1Xu5sKDQMPQ7v86b3++yP1VSzkxNTk2MF5aUTY6PRmNxry9g6HpuLy8pZUFBUcDrdnk8ZzuO1jasMpQ1MjmzfuOGsrLSidHhdNYOhwKdXV1CM7K2E/D7pVBHDh3KpFJSM0ZHRjRNyy8o1HVtcbj0lptVLabq0hkL6vp6/9wf5uZ+eDRnYGh4Pp5avaqFFVTA+x63+wG8J+YXok8//XWXy3306PGaipKGxpVTC+mXXnm1ujCvoLxqYSEmhGMaZiIed7s9RcWFbpdbCWlZ2UwmY7rcQjku02XbtpCiIBz4+O9+Smi5teTSUU4qnZKaIRzb43JJTXMclchmv/zFL6psOuj37di2cf3GLYtZeucB0Ts/vuye/s0DloshmEomp6amJqemCouKx0eHy8vLXn319Y0bNzY2NZmm+U4XKiWltK3sf/j8v69uWP3hD31IF1Y6Gf/K3379kQcfyC8unZ2eLC2vKinKt7OZr/7N37S0bdi9a/vQYP98NJGXF0nEY46SbWtalRBKCctxDE3ecu3XnbcpXfoes5nMQiw+MjTg8vqzqYTh8TetXCmEszR/U8mk6XJrmhSOdfToUUfqIyOjPrc+s5AqLso/d/q0o5mbt+/YtK7d69LHhgfnorHJyan6xqbJkcGZhHXv9s1i2YlWNx3otWyv2aWvOTe2qhxH2tm/+cs/O3a+O630v/ubr5QUFui6zmcNeL9iJBXAr974xOSPf/zDaDx1uuNUVUXJiobGwfHZ/W/uaamr9OYVRBdiHrcnt7jJ5XbrhhEIBJRSmq5LIV1udzaTFkKk0ilN02rKCh//0EcM0yM1IaRwlMpkM0JIx7HdLldPf///9Z/+0/T09Ntv7fcYcsv6tscfe7R2xUp5fffTu3WbpFs2zrcYVZqmLRunNAwjGAyGQqHurk5PIOT1BtKZdE3timAouOyVxOJxyxbjY6MXTp949qc/DkUia9vWrairmZqa6unpLijIn50cO3zk2Lr1G9avXxfye0YnJhsbW9wuw7KdeDxWWVnh8XrGx8cPHnir7+pAIpkK50VMQ7+7d3mLObi6rvu8Xrdpdl08Pz41U1iQPzc7k8xYwSXTJAzj+lGoUquqqnaZhlSO6fY2N63sPH9OaGZRcbHH1E93dIzNzNfV15eUlHi93pG+7r6RqQfuuze3QdUNA6W3nw28dL3UtXhdnKgqZVkk0NnTl0jGf/LcS0eOHZ+enFxRX+92ufjQAe8/jKQC+FVSSh04ePDcmY6FaPxqf/+qlia3z3/u4qXu82e2btk8G01KTc8dJuR2uaSmpZLJcF4oEAhqup5bY5PJZHVD1zXNtqyd2ze3rdviSCGv70FvZS3LcTQpDd24dPnyF7/wV5UlhYUFhY0NKzZs2BCO5P/a7wJLpWZmZ+fm5vquDhQVRGzbqW9oDPp9i7e5M+nU/r1vtqxur6ood8QNR1v1dF8aGR4JRQpampuz2fTg4FD9ypWObaeT8YHh0Zqqyrn5BSVUKh6PLsx19fQ1NTdbqcT4xPiu3Q8W5OeJn7fea/HfkVh2UJYQ0YX5EydONjY0RAqK/F5PIhEdHh7VTXdVVZWhLx9LFkJIIbJZa2xsNBZPxhbmAqHgm6++mnZkJBI2THdpWdmGjRvzAv7ciQo/91/K0jm+atnI6pJn5Gam/vTpr+07djqRThcWFQ719p7v7v3Cl778oQ88wXlUwPsMC6cA/Mo4jvPVv/uqY2VHJqaGrvZv27Q+FCk4ePLc5bMnHn3ssctXR3TdcLvdsVjUth3TNHL7dHo9Hl3XlRJ+v0/TdcuypBCaJresX7tx231SCkdev02sRDKTkUKYun7s9JmXX3i+qrS4MOJ/5OHHwvmF6sYYuvFufm6Z+J1u9y/7RiE1oRzxi80TcJRlW6PDQ8dOdmzcsNFlaprpKS4syO2lJaVUyskttxLXRjc1JYTtKEPXpVCzs9OWZcejC0rKcCh8sfNiy+r2SDh05uQRfyiSF8l3m/rA8IiuVGNTs6bJdNZ2u8x0OhWNxQvzI0JoUlt+W3/ZgqobpzQ4r770wnwi29bavGfPnvbN21e3tob9HiFlNpM+d+5cXUNLXtC3LHDF9YMAZqYmTE8gHPRNjY+9+eZeze2ZnJisb2hUVkr3he/buV2TQtxx4dTiT16cYpH7BddPC7s2zq2uH5c6crnzi3/79LnzZ9O25nNpXd2XDV0rraz6ype/tHXjBj6GAJEKADfIZLPPPffs3Ox0Z1dPPLbQvrbVG4y8ffTk2NXeDRs3zcwtuF0ur9eXyWQsy8pms+lUMi8vUlhUaNvKtiyllG7obo/Htu1MKrlz6+a1G7dKTVNL9jCyLNtynMHBwf379s9OT9VUlm7bsrmufqW44wqhXHneYS+km575Tjj9MhdEKZVOpy6cv9C+bv34+Oj0zOyKujqv17vspU5PTX35y18pLysNBvyJVDqcX/jBJ5+YHB81XJ6B/iupjOXzemamJ1evXV9YmD90tT+eSDY1NyvbHpsYt5VIxaJ79ry5dt2GTCbV1tbW093T0rra7/NKoW6ZgLf8T4vxoYHRyanh0XGvx1NcVOBorvY1qxYvx/DwUDQWLyopi4SDy37m0q+UUspxus6djqatyz2Xrg6O7rj3vu1bNhq69nMv1LJhXXn9QWfpr1DXxlilsr/6V395/lLP/oOH4/GElEJKTTd0l8v18U/83v/33/6rztp/gEgFgJyJyannn/9ZIpHsOHW6qrSwsbExpbQXnnu+MOyvqKyZjyfdbo9ylBKOYZiGYaSSScu2/D6fx+c3dMMwdKVEKp3SDcOU6sNPfaiwtEpq8p1CVUop2dnTc/jQwdjCQk1Fyfr2NXX1DVIzlg6e/kJZuey75C+fp7eUTqfm5uYt2y4uKjIMY/Ftvf7S8/sPH/+v//k/246ja1o8tuD1B6SUjm0nk8m+vsv73zrY1Ny8ZevWkN+rcu/2+gijUGpsbCyVTvdf6dMN03Ecn9/fe6mzsKyqqaGhuqribiJ18W3Pzc70dF9K2XLzpk1C2C7TJaWIxxMer1cTYmZ6cnJmvqikJBIKLV6fm+/JKyWUYw1evWJr7twhq3ff9Deks1KL/2LU8lR1+s6d+u5PXzx3uuPU+U5NXhum1XXd4/X95GfPbV7fxkcSeH9EKgunAPxSLvX07H3jFdtRhw8fbm2sr1mxIiPMn/702ZWVpcGCkkQq4/O6XS53Op02Xa5cTzi2o+l6Xl4kl2u2Zef+98gQzlMf/EBxWa3UrxWqlNJxlOU4r7yx5+SRQ0GvZ3N76wMPPZRfWKJp2k3ncMpbHhkq7rCflNSEUOI2Z42Kd3Ms6p2/0TCMQCAQDPhFblGXEo5QUoiS4tLvf++7xRVVVZXluSNeX37l1dfe2NPXf7W4pGzlypVBnzkxPpq1HE034tH5K/39oVDYNIzcTw6GQolU2u1xu93e2amxvr7+++5/qOdSZ2lZaTSWCAaDy3YnkFImkmmXy5WbcrD0Hbk9nrKKqsqKMuVYb+190zE8o4N989FExrK8Pr/f7y8sLJgcGxocHi0sLl5+ntU7S8qklFokvzCSF76bi3Pz9VxaqDfvrpD7LQWFBccOHfL4Az29l23HEUpomhRClFZU/1+f/3dMTgXeHzgWFcAvpae39+0D++diiRMnTq5uaapZUT88OffTHz+zorzYDISFo6SQSim325PNZCwrK5Swbce2LY/H43G7s9msZVkul0sIWVyQ9/jjTxSWVilt6Ybz0nHskfGJn/3oh7VVFY88dF9Tc6vQtF/dAqlbDi7KX3Rc9o6/6drsWBmLxc5duNDZ1RWNxsoqKp949GHHtgoKCqUQ//7/+LeXu7uCofCubVtOHjvkaGZr6+qa6pp0Ovn2W3vnosmWltZQwH/61ElL6H5/4HJP19jYRCQvz+f15RUUlZWV9vb2VFdXTUxOFRQWJmLRbDbr9nikEEo5E2Njf/7nfzY0NPTiiy+mLFVTXb34Hhe3kdU0LZPJFOVH+vuvTM7GhGNblu32+Lwel1IinBfJC4cGBq7OLUSDwaB24+6zy3aVusVl/fkTM2582k2nDyjlCKGdOXHk8IlTofzCPJe4MjhiOyqUFy4vr/hf/vRP161ZzacSIFIB/LY7dOToyeNHRidnjx491L56VWlZeUbpzz/3fPuKCn9xhZW1DNOVtaxgMOx2u2zHyaQzumHYli2UnZ9fmJtxmFs1VRj2PPHkR0J5hUIKTS7dUEkuxGJf/uIXDU00N67csH6jus3gnBCaeDcDotczSL/lSOrtRlh/7k++m8HCL3/xCxMTE7oUExNj3/ve99o376iqKM+F2XM/+fG//y//vbqssLZ+Zdu69SXFRUoo0+WO5Bc2NjbE5ucGB66WlpcH/d6nv/GNZCbb1rauorysr6+v/8qViZm5utoat9tdkBc+dvL0zu3bg8Gg2+3OrRo7evDtf/kv/oVSyrIsX8A/Mzby9e/8oKm5pSASXnxhuZOcTNP0+oOVZaUnjh6ZW5j3B0IFRYUdxw6fPHthVUuLrmv5kUjQ77148YLh9vm8HnHj9lKLP+fmx28+92tJvt9widT1Y1FvSGClpJCdp4999etPBwoKH9+9fc/et4bHp7wez7337Kisrf34R58qKijkgwkQqQB+eymlXnnttSuXL42MTV7pvbRuzeq8/EKfzzc2OdN17vSO3fdNTEx5vT6hhOM4ynGSyUTu+yzLTmfSRUWFHq/Xcex0Ku3z+Rrrqx557Em3L6CESCQSJ051xOPRdCodDoYcR3X19Jw4tL+xqXl1S1NRcamQN+fptRd1x5d8u8U06l0+/suSUvved769ccuW2Pzc5Mzc+va1/+k//odHHn3U43ErIVbU1nzrW9/adc/9oaA/N5/he99++i/+/M9Pnjhx6tyFrdu319XUulxG16Weiuqa6cnx8+fPZYW+uqVJ02R3Z6fQtMKiIsdxGhtWhkIhIaWUmrKtZ77/vT//i7/89Gf/8F/+q3+tCbWqpWV4ZHjFirrzZzpOn71YU1fn83mX38HX9bVr2/LzwhNjoyePHnb5w2taW4MB3+zsTCKV9fn8ZaWliejsyOiYbrjcbtey3LybzbDu8LfLWTqJVikhpRJCOdbbe159+vs/LqmqfWDH5vGR4WdfeEXoxpZt24ojobKKys2btuSFw3w8ASIVwG8p23aee+H5yYmxEx2nZ6YmNqxfl19Q5HKZlmXrmhgdH19ZV7sQS1jZrGXbLpcrt/jb7XYnEkmfzxcKBtwen2EYhmEEAv7mhhW7dj+sm26l1OWrAy+99EIkEolFY53nz527cMGR8ujhQ+Mjg3V19Tu2bTXd7iW1967u+KvfhEuXC6+1a1cfPHQ4HInMzs5MT0/ZlrXznvv8Pq+UsqC4dPfue7xez6lTpzTD1KT2w29/c9WGbX/0T/7g5JGDw6PjO3Zs13VdKufihQux6PyOe+5LxxdmZueS6ex9u3cH/d5EPJFOZ3w+//jEeCKVCvh9L//0h9/6zvdXr12bTaW+8KWv/NEf//Fg/xVHypU11bGFhUQicfjgW8c7zmzatFG/cSW+UioUzqupqauorDA10dPTPT45vTA71dXZGU1lykuLff5gfn5+PDo/Nj5hOSI3qrr4Tn+BKRnvnJt641UTSmWT8W/87VeffW3f+vXrm6pL+geHZiYnj565+OgHntza3nL6XFdbe9vDDz7IcakAkQrgt9Tc/MLXv/ZVoew9+w64dLGmtcXjC2iaJoQyTJcuxfjMQjY2l19UnLXsZDJp27auabqhK0d53C4pZSS/wDAMqWlej7uxtnLrzvulrikhRifG56JRj66U0Pv6+jShxoYGIgVFb7+1v7F5VUV5Uevq1VJqywr13dx8l3dYWSWuPeFu5wm828eXPiEYCm/ZvLkgL5QfCm7dvuMTn/ikz+fJ3SLPbagkpSwvK5+empibma5tbBnovfjtb38nnsruvv/B6qoKKWUgGGpubGpe1fq3f/2VtvUbersvtaxqzQuF/IFAMBhMpdJjI4PjkzOrVzV1dnU1t214aPeOfXv31zS1luYHfvyTZ7du31FeUZGMzp2/dLnn4rnxqbmHH3+8YUVdbvnRsvcipfT6fIVFJSXFRXMTI/MpZ8fm9VPT0+lUOmM5fp/P5/MV5OcrK2O63IuteeeLc9v/0pBy8Xypd+7zO0o41tNf+7u3Dh//5Kc+XRZy9Q+Oun3ei2fPlNU1bd+wenhwwBuJ3HvPjvq6ej6hwPspUtmCCsDdGhsff/75n6Uz9tW+y+FwsLS4UJouXTcd21ZCeDxuKbWjJ053nz+98777F+ZjuT3kpZSWlVVKuFxmQX6+y+1Jp9NCOVs3b2xbv1UJx1FiYmb6uWef9ZpG1srW1jcYUglN16WYi6f3vPDT9Zu2rGttbNu45ZcbJrvd9lLy+u6c4u9nwPX6mUpL8vg2LzcWi3Z2Xkxl7IqKypqqCl031JLtnzKplJCi+1JXKmOtW7dO142LF87bSlZVVkihdMMM+H093d1C1w3TDHi9b7/52ukLXfkFhbHowgsvvlhYWhHymL5Q3v/2b/7tyhW18i5ecyaddrndubmhtm0dObBXCxZv29i2rE1v+Y93d03UO4dOXT8TdXps+Hvf/d657su779mZ79YGx6cMl8vtMk91nG5Z3Wro+vz8vDcQ/PSnP1teVsaHFHjfYJ9UAHfZEOLl117rv9wlhPbsS69tW7Xi33z+88msMz4+NjY6Eo8nHMexHTE0MfOjZ56pL8sPF1dqUnMcJzdA6HZ7NF1fmJ+rqKx0u92aVNs2b2pc1S6kUlLE48mTHSdTybjHH3JpynJU76WLqbQ9MjpcGA4lU6mqqsqnPvhkOL/gvXlzi2v51R1b9j1J1aXrgm535eOx6Pnz56prV5SVlix9/tz0xMjkXHVlZTAYnBwf6Th9xjDdfo/LH86bGBurb2yqLi+dmZ2LRPI0qU1PT8xH44FA4OAbr7z25lupdOpSd8/v/v7n/vBznzENPfdKpKaJ25flzQ0qpVSOszjqefNbuMtOXVqouS+uVbxyTh099N1nfpLK2g/u3pmKLSzEElJqUtOiM9OeUJ6hCVsp03S1rml7/LEnuNUPvM8ildv9AH6+1/bsmZ0ac7k8LperuaE2EsmfnZ2urqmprKqpqqqpqKgI54VPnO38wXe+VVtSkF9a4XF7lBBKCa/Pm0olbds2DKNuRa1SIp2MP/HYIzUrW67FoRAu06ytrqmqqjZM4619e/OLSy3LvtjVdebY4dbWVXmRSCTgXbdp880368W1jVSdX+bm+/VV/GrZPe67+MZf+Dde+8dl57gufpFOpyYnxgPBkFBKSulyu6uqqoLBwLKidRz7+LFjkxNjnd09a9va3YYWj85Nzsa2b9nSee5MdU3tvv371q5do2maEsrr8+fnRaLzs6Gisn/8u5+00ol//E/++AOPPmTouqZpvb29wXDe8NU+ty9gGJqQN0xOveWWBXe+XMuec4en5ZJULvmWazukCvH2Gy//6NmXDH/oY489MD0xPhdLaIbhOI4uxcDETDjoSyTT/oB/y5btDz30MIUKvM9wux/Az5HJZF974/XpiWHDdOuGYdu2nUmXlZaUlpUvLMwH/d66lU3hSEEymfzKX/+1aRhdl7p9Xr9SSmq6lU07SpqmKaU0DN3rcUXC4fseeKi8olpJkc5kUqlEXigvNwlROY6jRDyZ+Ouv/s0br7zcf7n3/nt3FpeV19bVP/bgPVUrGu/wIm+5sdE/OIvjjt2XulKpdNZW1dVVhQUFS9+W4zjR6ILjqOGhId0whodHNCkmJyYKyio3tq91mYZSQjfMgwf2eQPh6sryC51dzc0tZWUlhp7b2Esm4rHxyUmPx1dcXKRd3yrhwJ5Xf/bia098+B9tbGuJxhLl5eW6FM7d3b5fevHv/Jzb/dHiGKrtOLnb/VKoQ3v3fP9nLzbU1zXX10yPj80l0pomHdsWUlqWncpk3C5XKBx68skPNTY28zkF3n8YSQVwJ47j/N3X/k4XjpKalbXGJqaGBoeHRkaGRsYmJiY8HrOmti6VShu69Hr9+fn/P3vvGVzXmeb5PW846eYA3IucCIAgSJAEs0hRmVKH6aAO6jCzO57q3Zpx6Kkde+zd8m6t0zqU7XFtecbrsd0zndQKLXUrZ4nKzAkkSBA5X6Sb40nv+/rDASCIACGqu2e6Wzy/D6yLw3PeE4AL/O8T/k8klS+llpYwxrphYgSaqjAOpmGalilLkkrgwc9/vq6xDRAIAddHhrFZmZpfDPh9hFCOYGhs7L/4i3/x2gvP5bMZQtCuXT0+f9Dv9dx93/0I4VXzKdgoPLlha84/TkD01zxw9ctVtReNVgX8vrffeHVufl72+KLhsLNd1/UPT5zcurXLo2nziwsNjU3lUqG+oaFn566uznZZlimVFEVhtjmfmBkaGimWK51bO3/x5OO2QJIsBwN+ACHJcjgUkikeGRmmkqqpCkIomy88/PVvVEdD5VJ5ZGR4cWnhWv9VbzDs1dS1Ed/1t7B6zWul6nob1Js1Ti0n9tc8BSEEMPvlp5946vmX9x863NVUM59IFA0LQDDOkRACoUpZ9wcDhNCHv/atzs5O933q4vKZxI2kuri43BTDMF585eV8JsmAjI2OJxKzjDFKiKNaCCEEg8ej7dyxvXv7dtO2y4WCFoy+9eZbxUIRY4QRppLEOS+XS17N4/cqX//Gt6prGgCAgxgaGamKhm0uMpmMYPbU7Fz/5b6B/steVSaylk6nF2Ym/vk/+x4jytJc4p577tyxaw8h5HZ47KtBR87YxPgYonJrS7NlWSCEaeh/83/+0qRa5AAAIABJREFU++ujU9/5wz+6/567Ukvzzz77/B9/709l+rEVECCE0MjIcH1D44XzZ2M1tZcuXqirb4xEIpFwpLoqIlYkZiaVLOlGOBz1qPLs7IxpGFOzc21b2hRZ0VTF5lyRJI/Hs1aGws1rTzcMpm4eZ71hTQHAzMrTj/3stbc/6NzWvXdHx3wiUTIs5/MSQghjxLkolit+rycYCn//z//CfZ+6uHxWcRunXFxcNub60NB7b7/pD/inEotXr1wRggMgSqkQgiAECDsjNAGAEoIx2rd399m+AVFM77/rvr6+yx7NAwAYY8GFEGznto57jn1B1XwCABAkUylNlRmH8YnxSqXy6M8e++D4G1/+0hcZEOAWwpKiqtl08msPHCZaAKne/qvXAn7fgw8ei8VrxWf9ya9XcpZpXOq7rGoev8/X3Ny0MJd44qc/GU0sPvLt7+7dud2wWSjgc/ZktvXiiy9ev369pqaGylp7e9uO7Tuu9V9eWFxSVYUDdHRua2lqKFcqHlVbrQPNpJaK5Uo0Wu31eN58/dXO7T2RcJhzJjjXNI9tGu++88623n3NdfH1VyjWuu7f2u3cTKFyIQqpxcceffTCwPCDx45FVDwyPskAMAjOQQhBCeacZQslv99PKP3j/+h7jQ0N7lvVxeUzLFLddL+Li8vHpQPAiZMnr14+7/f7GIcz5y/aprliXgkAAiHEOQNAQgghgDNmMz4zM3v06JG//cGPm+tiZcPSVI0xRgjBGB/Y03P/F75GqIzQsi5aSqevXLuWTCUnp2f/h//2vxm9fo0xKx6Lh0IhTCR/MOgNRxcmx7719S/nMumx4eF9u3dWGHr7+HFJIjW1dfCbG1L6u5Du33D72gIGKtH6+vpL588Ggv5Tp89u7dp+9O67G2uqxsbHe3bu9KjK6oFPPPrjdNHo6dmx/+Ad+/fsvHz+3ONP/eKRb38HCdbU2n75/LlAKJLPpJeSybnFpWg0gjFGAB6vLxgMLywkFlPZ3t27FFXLZ9OBUMTn0cql4vkLFzweT0dnByV4w0tdzebDJ/mh3uzeneLX5Ozk3/zN/319IvGdR77mIXxoeJQDIFguUcWUIELTqTSRZE1VZEX9/Oc+71r3u7h8hnHN/F1cXD6uUIV47fXXFhNTsuJBGJcNe/D6ACAEgq8IJ8QYW55vDwgjcJw7bduuq4kvJNNmueAPRf1ej+CC2ebObZ33HPsCQhgBiJV2/lAg0NDQMDk7+9/96//a0ktOPqcqGtm9Z18mlz937uzx11/FFF+6dIXIcm1tjV4uEmG3dm47der01OREY0ODqmm3eDu/jzpmrfgTK66hWzo68tlMvLZ+fGwkWyz37Ny5Y8d25+aEEKVyWZbk46++vOfQkbDP89Zrr4xPz99z330KWP/X3/3ku9/9rkRQuVyyGatvbFQUtf/SxSv913bs6EHLFaEiGAj6PNpScokLiMXjGGB+Zqrv6gBG5M6jd9I1w6icC9s8gLq656392PHB/r6f/OyJ2aX0V7/8BbuYGR6bFAAC0HJTHSCMMXA+Pj1TV1cnhPjaI9+pjkbdN6yLiytSXVxcbgvyxeLrr7+Wy2W4EJZlMs4ZZ2OjYxiE4BwhQEIAQhhjjDACxAWHZY0jAKC5sXF0clql2OMLyLLkVeV77rrz8L0PYkwchYqEM9MJBAiMMGB8+sy5zNKCaZpCiOmZ2Q8/+OD69YHF+TmCSaVcKurm6MTU5MRE19aO7q4Oo1RobWmSVO9LL72sV8qxWMzxDfhEtfdb0a+/5vobyrtwJOr3em1mhwMBw7T0clEAppTmMpmFZCqbTu7ed+Dpp56M1TV98YtfHB+88j/9j/+zAaScz99z3/2aprS0tEbCoWI+//PHf1bf2n748GGKEaUfFbQSSv3+AAFILi1WDDOdTEbjtbt39dxwL5vEp2/xu7C6IOdcMPvlZ3/x2NPPReK1X7z/aG5pYTIxz2F5+hYAYIx0XccY5bJZrPqCPs0fjn7x8593g6guLq5IdXFxuS3IZNLP/PLnxWL5wsW+q/1XU8mUEBwEL5u8VMiJZSmKnLipcJL+jDPOHNd1TZYi8dqrfRei0Wh1dZXP433ooQe39uyF5WGjAAIEiEKpNDY6HIvFueDpbG58dDgaCi4sLJim5WgSZtsYIQDI5wuFQiGTyWbzhRNnL5iVykMPPdB34SKy9T379x9/54PrA/3t7e2qpq1vP4ffRrr/hi+dgl34zdUJrC4bDoc9Xm8quThwfbCkGz6/3+fzhwOBUrm8tLS4d/+BxZmpn/z4h/PJVLQqsnP33j//F3+hSk7Pmbjaf7WppW3/vr0Ls5Pn+q7lc5m6hoa1UVIAoJLk8wckgvLFYn1Do0TJ+ntZ/XI1qrqhwt7EbGHVeer153/50lsfHL7n/jt3tU+Ojk4vLAFaFqgIIUIJAiAIASbzc/ONjQ3Mtv7gS1+NV1e771kXF1ekuri4fPYpl8vPPPsLWZbOXbhom0bn1g6vP3Ty1BmfqnR0bCmW9HK5LAQHcHpYOOdCCGHblnO4RKXeXTv7rw4oBNc1NntU5fAdd2zdvuujEU4COALOuaqqp8+dy6cXdcumkvL+e+9IGGpqaizLrFR0xhgACAGEYI/Hc/jo3cWKnlxayhcKoxNT1/qvtTXU7t2za3J8vLGx0efzHz/+DggWi8UxoZ/V8sSbWWsFAsHqqigCrlcq586eqa6pjVXHA0F/MZ8LVdfcc+89Dx574MiRO3t2bKcEIwT9ly+OTczolYo3ECiXis1bOqIBDWM8Pj5uCYiGwzcM2SKURqNVlJDNn+vNHvutfDsqxfzzTz726rsnduzo3tpYPT0xOZNMO59/luUyIUIIzhgTAoOYS2WFaTQ01H/+83+wqptdXFxckeri4vKZZXBk5LWXX+AcXnntzXDQf2D/vmhV7Hz/YHpuxhcIVgV9ew4cpFRaSiZty8IYMcZXyiVBCFFXW3Po4L7xyZlMOhmvqfV7vV/5yle2dO0UK+MyGefvnzr5f/xv/+sTj/749ddf3btrx4HDd0fD0UKp9NbrrxMkZErq6up9Pu/i4hLnPBqN+H0+IURHVzdmVlNz69jYmGVZs/OL/QMDqqodPnzILGYLuVzvvv2vv/nu6OhQS3OD5vFuou1uPZL6iRrrHzoEuxqb3HxckzOJKhAILS4kEnPzwWCQYxr0+yJVVX6vaptGYmGprr4eIQSA5ubnCManTp+59777MBYXL5wzbNi6tbO+ri6TSm3p6HRiqZ/2UjdRqDeMV1i7oPNfzCj/8Ad/9+HZi60dW4/s2T56fTCRyXHOnf0xxoQQQIgxzoVACBcyGUPXhyfG27fuuPPwHe7b1sXldhCprgWVi8ttzbWBgXNnThqmderkydaW5ra2lrzO33rruMSM3r17ijpbXJgLBgOhgD8cDhoWy2azpVIZBJckihAKBoOVciWVTnGBIpHqUMD7wLEH65u2rD1F2dCffe651197ZfT6Vc7sztbmHzz6FMJkZmHxv/+3/9qvUiEExkgIUSgUK7peHY0cOXzoqedenRgd8Xm1zq5uDnjw+vXZ6UlZlvw+771HDh27646tWzsSqZwkawvp3ODQ0P59e44cvUuiMvzmIqq/3UFW66taN5nntLS0ZBq6zbiqeeKxmKFXsrlcPB4HQJapp5LJC31Xdu/emctmp2YSR++8kzE2Pz128kL/t775DVmiv+Yj2vz1jYcAlHOZJx5//GL/4JEjdzTXRieGhxOpLCxPqAWMMSYECQaAmeCCCypJ1y5fOXD3vfnExPe+/5fNja7zlIvLZx/XgsrF5fZFCPHGW2+ODF1LLCz1X7nSu6unc2vnUq70zC+f3tpcH6iqYQIQIn5/ABA2LD63sJjNZCsVXZKoKsuWzRCQTDaPCKVUrq6KNjfWfe3r3wpGYgAACOYWFzLZtGEa4UBge3f3l7705UNH747F4oFw9PDhw4Cwbhrvvfs2BqAUU0IRIE3TZEnya+qffe+PDx++wxYikysMDFyjBNo6Omtra+fnFvKFwvjU9LkrV1VJOnxof8CnERB1DY2LS+kPP3jf61Gj0Sj6DeWC11db/mNq01s/NULI4/EEg2HB2BOPPXr23Pmm1i3xeNxZgBDq8wdampsK+fz46HDZsGOR0OnTp2ub2w8f3C9R6dd/Sje82FTOioG+83/39z+cmF344uceCKv46tXrqUJJCAFO7B0jjAkwmyPEBeeMI4TMUnFifqmlsS5WU3fffQ+4xlMuLrcDbrrfxeU2hXP+wx//EHFrcHRqemx4355dtQ2N14Ynnvnl08fuOlLhVJEVLhAhWNd1QgjnXNM0TdMUVRPMVj1+RfUQSkOhUKWiU0mqCgUe/uZ3iaQuixUBfq8v4A8updPjk+PhYECSlOpotLd3zx2HjyCEAaBiGB+cPAmW7sxIopQqqmKZpk9Tjxw+6AsEe3t3v/nWO1s7tw4PD48OD3W0d+za3WuY1vxcQteNq4PDUxOTRw7ui8erFIr0cqWprf2ll15OJZc6OjoQxps3pH9aR09Yk4iHX7v/aZMDN+xS2tArYPXAlYgvqJoWj9fu3r3rF089mc0Xm1taCV6+YIxxIBCyjMrY1GxDfZ3FeDQSeuqJJzy+QHV1lRPD/LQ9XpsI1g2/5EJMD1394U8en17MPPLwl6hVujIwXDZNzrlz1wgjhDBnzBn6wBkXAAjB0Mio5g/U1NZ///t/7lajuri4ItXFxeUzSyabe+7ZX0oEj4yNp5cWdu7qqYrVnLlw5fgbrx0+sI8hSZVlhDGAwCuixOv1MMYYYxhjRdU4t22bM8ZM05JluaWp7g++9LCk3OhdigCC/kAkUjU5M0UwCEAIAGPstG6blvX+++8BMx0v96aG+rqmllQyGQz49+3ZhajMGL/U15fNpKpjNYFA4NrAQCqZ3Lt3rz8USSQSum7MLSWPv3+Kgujq7o5Gw5nFha1dXUvJ9Llz54IBfzgccoKh65/Aamv5p3puv8XerE902lqVqqFQSNM0j8eTyaQVVfX7fABiVdhVxeJdne2Vcim5uHh14Ho4HFI8/pp49eryt36P61v4N5+byjnvO/XBY08/hxTPt776BWwU+64O6rYtHJ0NgBHCBDufoAAQF4IxhkBghMdHx3bs3vuv/vIvZVl2378uLrePSHVrUl1cbi+uXR84f/akAHzqzLmI37Nz104ie95+94PFmfE9Bw6l01lN8xBCbMu2bVtSZABkGjqllBBCCLUsS5Ikxx6IMWab5tEjB/fdcffNShBXxZNl27l83maWbVuhQMjr9RqW9b//1V8Vk3OmbYEQ0er4j3/8aKlQiEWD777xHFH9+VL5r/79XwMXCEEuX7A4ZLPZ5OKiJMmtba3ZbP7ypYuSRLweT1tzwx9+4yt3HNyTLxmZfAnJnouXLodDgXvuvbe2vvETdddvt/b01vk05vkIIbBtKzGbGBwc6N7RWxOvWhN5BaNSevqpp/YeuadrS/OG369f4WKcLWvV/+oWq1J87umnjp88X9/Y+NA9h+emJobGp23GuBAYoWXzXUw4Z5wLIThCiHMOnFNJAoB4ffN/8md/6ipUF5fbCrcm1cXl9uKDkycHrl7WTfbeO+9u39bR0dkpsPTsiy8lp8YOHbkrmcqoqlop63pFd5yAJFmWCKGSJITAGDPGZYkSQiiVJIoZFwf37T5w5D5YbVZCH/37sf50jDDGXo/H6/GqqjK3sLC4OB+JVsXr6kZGx4BZlJJUJnvl8hUAQARXh4Jbt3Ulc5n+vqsChCzLXo+GQKiaJzEzY1nG3Nz8zp4dTW3tQ0ND5XI5Vyyd77vCGTt69E4MvJLPbu3aWjHsN954E7jV1NxyQ+ocPp65Xu+0+g83FnWtHNxQHX6iVr5Zy/zHtwsAwBirsuT1BUuFnEA4n8/6fAFnsC2lcs+u3VWRIKyzL4VfadjshoFV53Uxm/p//sN/ONc/tLO393Bvd3Zx/srgKGcMhECEODFU5zMP59xxOgMAxBkHhAnp3Xvge3/yJ2uHDri4uNwOuOl+F5fbBSHEa2+8Pj5yPZMtnDp9amt7a2trmyDKL595jlqV/XccLpR0jIngglBKJQqAdN0wTcO27WXBgTECZFkmQiA4t0zj7sMHeg8chfXt9AgQQuAMQV0ZM4UQEkhgBATTUDDo8fqXlhb9Pl/P7t2Li0tGuTSdmE/Mzuzp3fnXf/03dz70pZ89+ctrFy9YzFYUD8aAEZJlWZWpJEuKolhAlhbm/F7tyJGjNuOJ2ZmKbgyPTZw8ebq5oXb33j255AIG2Nm772Jf/8TYSDwW83g8sEaS3pDu/x0ZoLr2wtZf4a+wIJXkgN/n9wcunDnx/smzLa0tmqpgjGF5nNM/1A/b6i0U0os/+fGjU4uZfXt7e7dtyS7OXxoY4pyvnF4ghAAhxhhwzhkTQghATnkAwvjgwcPf/MY3kNsq5eJyW4pUN93v4nJbKNSXX3mpXMhOzi2eP316/97e9vYtDMuPPfFUVMW1rZ3FQl7VfJwzy7J8Xh+hhFJqGIZt287MUo+mliu6pnkcb3W/Rzl27Fhrx/bVwJsQQji1jwIQdpQWAELgSCuEkACBHKklAJDgwrZty7YURTUt67133378sceP3rH3u3/8z0+dOfNv/82/mZuZ0is6Z+zokYN79+4p64bgDAAs206msxKls3OLC3MzbR1dkUhEotKrr7xs6BVFkaOR0B8+/KU/+qffzWfSc0tp1RMYmpgZGx05duz+ffsPCMBrBc/a0UfrxeImL259+3oBerMdbuY5dcOeNzvjeiG7ZgdAIHTTHBkZ7d62bfUka9Xkrd/j2mOdp7f+LpzNej75t3/7g7HE4lf+4PPYrkyNjiUyWcY4whgjBEIgjEFwLkAAYpxjwZkQGGHOGUboyD33f+Phh933r4vL7YkkSa5IdXH5jMM5f/W1VzLp5PDo5OjQQG/v7qam5lzJ+OUzz9SF/fVbttqWTSlljFEqCcFt22aMSxJVVYUzrhsGpdQyTY9HA0QwBgzi0MEDO3sPio/rIQBA5KaXgYQQCH801kiAMwvA+YcLYZpWJpP54Y9+9OTPflosFGzbFpwLLjDBO3u6Dx++A0AgAMu2BReWbeeLJd3kfX19Xk3ZtWuXrKgXL14aGxmSZcnv9+3f0fWdb329vbWpUKrkKxbD8rWB63V18aN33RMKR25IrP/jh1E3POPmEvZW1lwvZD/aAiBg1YoUNjn1pzoRbGSP6iw1MtD/zDPPJ5Lph7/6ZQ2Zk+OTw5MzgnO+vBsiSAgBfKWtCtbUsALArt17vve9f+bGUF1cXJHq4uLy2WR+YeHVV17kQkyOjfu9WkNTo+oLXr42/OHbb+zt6VaCVY7AoIQKEKZpqqpGCLYsy7IsVVGFWI53MtvGGAvBg17t6488Eo01fCRNECCEnPikQDdVOQihoZHRzNJ8z85dmuYFQOCE8DgwzgrF0t/98EevvPxSNpXMZ9KWZSEEnAvOuW0zhJAk0YceeqCrs93QdcaFbVuc81Q2BwKls7lrV681NNR1b++xbfvMmTNziRlFkoKh4J0H9vzRt77e1to8t5jSLZYrWecvXdq9q+fo0btUTVsbL/zHEUPrq05viGX+mivDTepEfwXp+SuI1DXbxcXTHz797Msmkr547G6F6xf7rmZLZcEFExwB4oIDIIKAcS4A+PI43OWQNue8ubXtv/ov/6WrUF1cbnOR6takurh8Zrl85crpk+9bHE6dPtcWC/zZ97/fsqXjxPkrLz/79J2HD5ZsHI1ECJEECMsyg8GgoqiMMX/ATzDlnFNJYozZzEYIS5QKAJ/Pt2f3zvZtu5blCAJwJlgiLFZqT8FxthQrlakrykkIEQlHOKDrgwMAQAlSJBWWj0FDExOnT58u5AsIYYSQPxikkkyIkxZGAoDZbPD60Mzs7LbubYRgSVIopZJENVUtFPLbtu+YmV3ov3Kpo729e/sO02Kzs7O2ZU3Nzp09d76jubFnZ49h6kjww0eOvPPeiZHh681NjZrmgY28P9c1IW38YsPt6yXv8vab7L/+kE1OtNao9QaZuN7AFW5hnOmGw0vh08+M/fi98NPvvvXi6+96wlX/5CvHwKqcOHMhV6owzp2oudOTJzjjK3FTzjkXgnGBEOJC1NQ2/Kt/+a9cP1QXl9sct3HKxeUzy5X+K5cvnZNkWQgwTTOVzgYVXB2PyZovFvYHIjG9YjiJFEooRsg0TEIJY8wyTMsyQXCEsG7oBGNVUQklPp/PYmz/3l5/MLp6FryqmdByBh9gOaO8PgqGEQr6g6FwZGFpaWkpuZSc93g8siwjjCanZ1Jzs42tLYauS4pHUTVCiawoCIBSatu2o35z2fxcItHd3UUIsSzL5/NSiYaCwUI+H/D7Pb5AX9/FxfnEocNH6hsa0slUJput6OapC33ziUR7a0tDQ21ierq1pYkq2quvvWFbejwepzcfufSrRfJuxet+w8DnDbrzFlfesA71Vq7zV4jdbpLod+CW8fpLL7538hyR1Qfu3Fcu5M5e6MsVy1xwBMDFclmyU+XhOKFyITgXjHGnuDUarXr4q18OBAMIIUKI+0Z2cXFFqouLy2cHzvkrr76SmJ0mlCJMZYk21MXvv+9eT7i6Uil3drTv3rO/sbFR9XpsxkvFoizLAAhhrCiSLMs2YwJA1w2EgBLKmKWpKqyE6zpamgKR6o8kEcYr/ftrdBK+aec4AqQoSk1VrLa2jgkxNDykamqxVJqcnj5+/Pipd48/cN99kVgsm8sjTDwej6yoCCPsOAsAAELZbD4eq4rF44CQomoSlWRZ9vm9siQxZsXjtRbjl86fBc7vfeBYMByZTyQy2ezoxNQ7H57yacrOXTslsCiIqqqqpWT6lVdelmW5rrbWGYK1oSi8FR+AWywYWC8oN9Gjn7jmWqW7CmzkqPXrK9RPtmgFmJsa/9GPfnzx2nD3zp1H9myfn5k+c+FysWIIEMD5ctUpAHwUOuWMC865Yz6lKMqhQwf39O5CgiWXFhbnE1SSvD6/+452cXFFqouLy2cBxtgP/u7/VWWqqBpCCISwGOeMFwt5WSJen0/Xdb2Uj4ZDHe2dHk3VLaZXdJ/fAwKKxZJt2xhjr6b5/F6MMOcCAFm2BSBM0/R4PJFwMF7X6JwLryhUhB2xBSsTODdNHyOBMBIgAr5AY32jYVsTk5MDg8MTY6MXzp7ZtbOnqaFhS1tLNl8ol3XN43Xko+CO8ScSAJqqbmlrkSQZYwSYYIwpIZRgTVMFtwEgFI1PTEwkZiZramr27j84O5PIZNJ6Re8fGLp6qW/Xzp76+hqzlK+UK3ccOfzKq28sLs5vaWujVL5B7cGaIaWrbJiG/sRxqTcIU7gFU1LnRKtSdcOV1+vR9d1Xt1ioAJ9UaQA3n+AqOM8tzvx/f/+TsenE5x56sDbsLWZSZy9dsTgXgq8UhyAniModkepEUFcEK0bozqNH6+tiCJY7vLgQhXxuYW6mKlbjhlRdXFyR6uLi8vuNrutPPPlYwO+TFQUhhEDYtl0uFWzGOOe2bafSmWKhIFGpXKmkU0uqJEWqY6lUMp3KOBpCURQAKBaLggvAmBDitLkgQH6/37IshYi2ju5l7YId6YEErFqwO/+x0km+XswBQoA/OhyBpqg1NXXDo6P9Vy5PT4wd2LdP9volTBob6okkLS0uCRBUkhxnTUmWQXBFkbdt2yYrskQljIAQCiCoLCNAhBBFlizLbGluzmTzs9PTAGL/vn2BYGhuLlEslpayubMX+oKq3LNzR3V1dHR4uGfX7nyhfPz4W6oixWI18PEBoZvEPjcJUt5KXv5WlC5sWjywuYPVrR/4K7O8juBTo4M/e/zpgsG++fCXAwrOLC2cuXTV5ss9+6tOVSsK1XnFOec2Y0IIVdMOHzkSj4ZW2/yd3D8GwQUsLcwFgiFJkt0+KheX202kujM8XFw+I5iW+dOf/igQ8Hu93lJZHxkdn5wYr+i6EMBsmxBCCYpGo3t29RiWrUikoaHxQv91Y2Fi2767ZqZfkSh33J1kRfZ4vLZleQJeJHgynQUhAFAmk/H7A8lkZtn7FK2MNnJCdyAAlkOpy6KEOxHWj4f0BCBwKhNXDwQEyDRN0zQBECZEL5WQR8MIdXW0x2tqzp46lc1mvT6/EMI0dM3rY1z4fB4hkABEqAzcxpgIIbjKASFAlFJ5bHJyS2sLlqUT775rVModXd0tLS0vPP98sZgfmZj66x8+fuLM+e//p3/Ws71rbn6hMRbas6f3iSefSszNHTv2IKYSxnhDi9C1cc0NpeqGgdINrVhhI9Oo1UEDsKmR6g0dVBvuv+GlfqINKqyJxW5+4OqLK+dPP/38q6ls/vPH7pHBHhwYGJ6YZms+pKwqVGeilOAChLA5F5wLzhEmB/fvCwd9hmVhhJzoLGaIEG4JQogAIQavXW5sbovF69y3uYvL7aVT3Uiqi8tngNGxseef+2UkHKKSPD6VuHjx0mwiYRiGoxAIIVwIm/FCsTgyNr6QmAsHA6Vypboq/OQLbxQTY7GGFss0/X4vlSiRJMs0CKXZTIbZnFKiqioC8Hg0y7IMw+jqaJFU37JMdf5ZqY2ENTM5V77+2HWun3NkWXY6tdh3dWBw4CoC0bunlxCq6xWEMcXIqyptbVswlbLZLMJYUhSEMHB7//79CBPAgARIVAIABIJQQgihhCAEVZEIwtjUK40trbOJxPWB/mhV9Z49e1SPL5NOFovFmbmF/qsDBKGu7m4AMTE82LWteymVfu/d93xerbo6BuvqO2/GrXhIrVtk48XXt/x/zMwVAH4ThlmbXOqnWhkBXLtw5qlnXkwVKt955OshjV66cGFido6JGyX1anp/RaYKbtuCcypJvb27w0E/ElxwDpyLtW6paCUoj1A+n6t28/4uLreVQnXT/S4unwEu91+5cPaU6vFgQi/BEgaVAAAgAElEQVT2X7/S16dXKkIIWZI456tCxxn2JATkC8WRsfFI0Icwam5r/3f/y191b2lWVA0AIYQ5Y5QS22KUUkKprCh6pWLblsfjFUIgQr0yjjW0LEua1UJTBB8TpmgDhQqr5qgrKrZU1l9++cVMKo0J9mieqngtxmRxfu7q4HA+tRSpihEEqqrU18bbtmxJZXLMZggBs+2777yDAwYhEEKYEIwxYMS5oIRiDIRQKkmKRBRVZbZVE49X19T3X+6bGB+3TH1ubiGfK1R0Q2C0mMld7uvf0tLQs6Mr4PNIlLS1t586depy3+VQKBAKRz6tHLzl/fENtvqb1J6u16/rj/p1tOanVbTOFr1UePGZp1996/1ITd23v/p5oRdPnDg1n86u7o4R4pwLzhnnXABnjDEmhOCccca5EMFgaP/+vQGfx5GuALDs9A/AVgZlcQHOIAhAkFycq61rdJP+Li6uSHVxcfk9QAjx9z/+0fz0hD8QIITqpnXiww8xAAKBEJYkidkMVtwrEUJO/xECMC17aX5uW1cXJmRgaLSQTUWqqkPhSDqdFkIomlYulyuVsmVZyBmgjFCxWFQVRVZVZlQ6tu1YVkJ4xX/qozpUsdwpjwAAcS4sm3EhGFtu6BYgnLoAJODspT6/RytXyonZ2d5duwzGl5aWfvHzJ/OZ5LVrA4Vcuqt7B0KCcyFRadfunRzw4sICINTaVNfU3Cy4oJLEGSMEy5LEbMZss6W5UaLEME0AIITKFAsQ+WymXC5OTc9OTU5Zlo0QaB5NliSbMSag/+qAVcj37t8Xq45evnC+tbUtUh174fmXVBnXNTSIj0obPtJ/t+Itumk9gLiZweomKzvBVPTxzq1bb9W6YcsnNk5tdiXMfuynP+kfmqhratzV0ez3KO+9fyKVKwDAaijU6Zly2qTEcne/4JxzxgFAUZS9e3bJlDixVQBwbKpWPuYIR7YSQoTga3rERCAYdt/4Li6uSHVxcfmdhjH+zDNPW0bZ5w9SWcaEDIyML84nECyPRnf0AVnWAYBAYExgZdi6bphtLU1EkofGpoqphfrGFoyxpnkECNtmpq4rikIplWSlVCoBAkWSEUaUYEPXu7q6CJUBwJk0tVxYulqAuqw0AAlkc7ZeWHMhBAiMcFN9vaJq27ZtNyyrXC5TghLzi4mZmVwuJ7hIptMT4yPBQCASiRJCEEB9bU19c/P8/Py5cxexsDs6OyybIYwYYwiBaRqDg0M//OFPz5w5F49Xx6qrbMYxQhhTj0c1LXtifNK2mc/nPfa5z2Wz2UqlrOu6rutEkmaWMkPXrrc2NXR3deTzufRScv/+fR+evjA4cLUqGgkGg7feanQzF/pbd4PaUFYuB003GiiFbtKmtv4s6zX0Jx51Y6krgF7MPff0U5cGRuuaWw737mBG+Z33P0zli85OTvDe+SETAhhbyfE7QpVzEODz+3f2bFckIoRAa3qqAMApWYWPhZqd+8aE4HK5VFNbv6FfmIuLiytSXVxcficYHRt78smfYYw0VaOUMpth4JOJpdTSIsGIcy4AGLORk0J12pWEYNzJtzqaFfbs6rEEfvPN49GQv71zW7lcoZQAINMwZFnhnGFH7YKQZNlRErbNGIe66rA/XP2xTP/Ky7VZfiacC9lQ/QDjXAjh83olShobmsqG0VRXY3F+9/0PyB6vUal889vfidY1Hn/rreHr16qrqyUqAaCAR9u2fbvmD7777vsn3n+/paGuKlZTqVRM07Yt89nnXpyZnslkshcuXEokEp1bWn1+p3wW+wP+6ZmEPxhobmurVCq7e3tDkejszGy5Uq6UK6ZpZovFsxcuzc3OtbS21dXFC+lkY2OdLfD5C33pdLImHpdlZRPZt15TfioZesP2W59uKoSAtXWrn2QscMO1faIJwA1XMnb96k8efeLqyORdR48c2tU1NzXx4ZkLJd1Yexa20qHv+KCyZasp5nw+qqmp2bG9S5ao4Ms/H8sKVax8flq5KSds7ISxMUIYAcJYlhXXPNXFxRWpLi4uv6PMLy6+/PwzgVAIIeQMm6SUmpZl2mx2ekoIwETijGGEAYHg3EkQO3/2V4VAfbyqu6fn+ujke8ffuP+++7GkhCNBSqkQiGDilK9yLhhjBBPLNIlEVVVBhFimrpeKHV3dy3lnAStW+6uCBoET3ltJ2t602hKtBAER1FRXB8KRWHWse9u2TL6wtbVx34FDoXC4rat78PrQO8ffbGqqDwRDGBMEUBuv7tzRc/XqteeeewG4tXffXssyl5LJ48ffYbbtnCKVSp88dTYaDjY3N3HOMcK1tfFsoWTqJc55JlcgGD3w4EOzs7O5TKZcqZiGIQCSueLFS31hn3f/gV6PTNJLSwcPHbx0+erJE6eqq8LRaBQtO29tbKS6efL9BovTta9X10Hok3uq1r64wU517SVt+NhvxdJ1deWP6VTBr144+4tnX5qYTz781S/VBZXZifFT5y9b/CP7MQFgWZZzDLeZAGCcgePfz7gAFIlEu7e2L392WjkXZxyjj8LBjiQVgDBCCGNwFCrBGBNMMCU0Eq12fwm4uLgi1cXF5XeRH/3oR6ome1VF1TyKqgrObGZTQoMB/+xi0tArK0JNCO4MolxOpXLGhUCU4IDfc/8D9yWzpRefe6Zn29aqmgZVVagkmRbXDR1AMCZUVcGYIASSRDGhlmUihGRJ0jwe07LKhWxNTS0m1GnuRwKYszxfrkSs6LpuGJsMHf1IfsGyg5UA5PV6CSELCwt79u4bHR6+/4Fjo0PX9x06jKn00nPPZ9LJhvo6QikgJGPUvWuXonk+/ODE2TOnGxvqU+nM+XPnb1j7+uBIpVLuaG8jlGqqWlsT41xksznGuGmaiZnJ7u7tXn8gMTNjWZZpWqZlAUIjY+MLs3Nd3duamxsSM9PNjY3xeM2HJ08XC7lYPC5JMtw8wLl5s/8tepT+Og1bn9j+/yv0HnHGPjj+xktvvle2+Ne//Lmwh06Ojp65PMBWGp6caGipVMIYY0y4EJytWE5xwRgDgOrqWFdnG0bLgx9gtZnPKWdGILhY9jBDiGCCCHGGo2JnUUwIwYah1zU0u78EXFxckeri4vI7h23bJz54NxKtwhjbzBaMUUoBQKKUYFzf0Di3lDbKJYwRBwECccEBgHOBkAAQCEHA73vw2P0c4IUXXoqGgu1dPbIsUVkWnMkSyecLum6oiuIUEjLOVEXRvJ5SqVwulQAQxrhSMUvlcv+VyyG/GgxVCQAOYjXJ64gPQogj5mDTRpzVYkS+Iq0wRp3t7V6fnxB6+dKF++69t62tzRcIRuK1pz54/8ypU9u2dUlUwphIBNfU1Xdu237t6rV33n5ncnKqXK6sOrMiTDChgrPZ2fnTZ851drUF/CEAiEar/D7PwuICt3SESSZf9Pu9d9//4PjYaLFY0Cu6aRoCwUI6f/Hc+Vg02rKlzavgxbnEXfc+cOrM+VOnTtXGq0LhyNpbgHX9T+sjrJu4lq5XkOunBtxKhcDaU683Pf3EvqgNrwEAkECn33vrzQ/OLSRTj3zlC14JzU6Mnbs6uPq9dvxuS4WipCgSpZyx1TpUIQRnDAGqravb1tmGkbM/FsLpoxIAgB13WC4IwYAwIU4IFRMnlkqIo1NX1aorUl1cXJHq4uLyO8fc/MKDDz3UVBcPR6NCCMs0TcuihMqyhDAmhACIro4t/nC4VNEt0xLcdqx8EAJKSLSq6uD+PYcOHsgWSj9/+hkCvLltC8aIEsmyLIkSJpAQXFU1IbiiyI5cME2jUq5omhoIhpltW5YFIJhtE0pmpmcSM5MSAY8/gPCna2fBCCOEbxZZpJTEYrHOrVs9Xq9HU2tj1T6/v2lLR6lceen554GzmnhM1TQEgDHa3dsLsjY+OmJbFkIYI0wkWXC+nDrG2Gb80sUrqiq3tLaAYIqi1sZjumnlcnlKcEU3luZnduzcTSRlcWFON0zDMBnnDNDla4O5dHpLW1t1NLg4l9i2ras6XvvOO+9n0qlYdZWiqBvqxZtt2UQO/gpToD6x1PU3MFlKCLNSevOV5989ecEbCH7jCw9IyJ4YHbo4MMzWLM45NwyTUEopXQ6hrnRKCS4Aobr6+rbWRoSAMS4EYOQ4oq6qcBBCYKcCGiGMMCEYEHKCp4hQgjChhGBCCMKYVMdrXcNUF5fbQaQi0zTdB+Hi8nvBhctX/vA730mnkn/6T769+9AhzeMBAUXdYpZBMXZGhiJMCcHMthRZNpgwdb1cLjMufB7F49EIlebm5ucWls6eOVMTCR06fCgcqx+bmBLM1jQVEGa2ZZqWk7LHGBGCy2Wdc0EIsW3L5/MSSgzD4oxTShwhq+umbVttrc0Hjtzl8Xhv/XZuxQN/LaVyeXR8Ymo2ceH8ubdeftnSi9/85iPNWzpsyzIMAyGYW0qdeP+9ibHRQi5nmgYIQJgghEKhgKZpi0tJ27IDPs9DDz3Q2dlRruiWaRaKxfHJqWQqQwglklxdVVVdXdV3qW92eoJKUsDvC4dDwWCoNhr6wrF7dvZstywrsZiKVNfOJXOX+87fcccdu3r3EELXq8z1E6Fu0I7ru5c+6ta/eYzzVgToJit/CnUKAELkM6nHH/3Z4MRMXWPjscN7zFLhxOlzTiP/alGBzVg2m/P5fBjjFWPU5f48xjjGZOvWzupI0Jkr4VzUcp5/5apWAqeYYCdsSjAh1NG8sowRkiRJolSSKKVUkqQ9+4+4bqkuLp95JElyI6kuLr8HCCF+8viTr7z+ZrgqNjp0vbY60rWjx+vxUEo8qpOXByYExoRxRgjFGDMhJAyyLHm9WigYwBjbFptJzL3yymu2UQkGw5lCsZDJfOGBO/cdujNdLKfmE7Isy4rCGJckCWOkyLSim1QiEkWqqjLGAZBlWgRjhJEzwpQQwmyb2TyXy17rvzo5fA0LO1Ydl6iMMaaEYIQJxhRjxxz1ZiLsVsxHTcPIl0peTfEGAm1bt+XyxVdefJ4CD0erCEKWbXtUeXt3tycQvt5/hbPl9ikq0YDfF4tVtTY3LSbTFV2/eu26YNaOHd2macqyFI1GEEByaREQGKaVSqW3d3fVNTZPjI8Zul7RLdu2bSEGRqdGRsb27u7hnDFTTy3O3//QF55/4cWR4eGWpkZF8+CbZO1vFkzdvONqdT7qJv3+Gz60Gw7ZcIVPbJxy+uyNQvpnP/3Z4MTs/sN33rGzwyzkjn9wKluq8I8bFximVSiWPB5NLI+V4qsKVQjo6GiPRYMrmX3kRL4BYadxatX/FGOMABGC0bJOpY5UJRhLlDpfU7qc7q+tb3JFqovLZx433e/i8nsA5/wHP/pJYm5eU2TdMOYSc36F7tqzt1QqSJLEOF9OkmKMECIYEwwYYYyAcbAZQwhxzjEhi+n8yXff/pM/+afdPbvi8VhtXR1DZGRoSGGVnds7m7d0AqG5XI5zpsgUYWKatiQRzrjH663opuZRBeOyLAEIWZYliTp5GEmWOWMCwOvVKoY9N78wOnzNMsuhYJBKH3k2rXRH/eqYppnN55ltU4wRRo2Njb5Q5P333h0fHozFqgmVbdt2vFSbtrSn0plCLgeAJImGQ0GPR/Npam28mgMU8sWp6dlrA9ebG+tDoTCzWSDgj0TCpXK5Ui6D4EuptETp7t492Vw+m04ZhmHZluCsVNEvXxmojVe1t7dVRwKJyfFde/YzQY6//Zbfo1VVV2+inDYpPF1brvoxvSjE6lDQGz6x3OIT+3WU3OTI9cce//nkfOrQwb2dDVGjkHvnxOmibqy9Ti6EEKJQKHo8GsZYLPtJccEFZ5xQaWtXZzwauaH0VohlL1VY9ZZa/syDKZWccCollFAnnkqc8Cql1BGphBDXKtXFxRWpLi4uvxO8+MZbb7/9TjqdEbZdV18/NT1bzmUPHjqoapqmaZQQ07QBQJYlBAghJ2a5/CdcVRXgHDDiHF5+4+18cvGPvvnwrj17W1rbqqLRYDCAKJ2eX+y/0m9X8u31Vbv37Vc9/nQuX8znJUmyTMvr9+VzOUIIZ5xSbNu23+81LVuSKKXEZlwiy6LFUcmY0FJZn5icGhsdnpudCPg8Xl/Qad7+qOZweTzqpxap+UKRMcYZkyUqK7KmeXbu2Vcolp9/9rliLtPQUE+IhIBFQsHevXsjNXUL8/N6pYwxVhVZlqhhWpNTM7bNEELFYvlSX38qudTS0qSqqixLNfEYwjifzdiM65VKKpXa1rW1rWPrwvxcIZ8vFYuGaZiMDQyPDQ4MVoVDtXU1eqmgSHjv3n1nzvedOnEiGPBFo1U3XPbaJP4NIcxN5ObNMv6/gTLTTRFC2Ib+7puvvXr8/en55AP33dUQ9c9NTZ4431c2rLUXwDkHhIQQuWzO49G4cKx5GefcZozKcs/2beGAd9WSfzXZz5d9/sWKQsUII6d7n1JCqdMBSCQnu0/IsmKlBGNMJam9c5umed1fCy4urkh1cXH57TMzO3fy/Xe9wZBp2blMem5+vphN3XX3USpRm3HOBbMthLBt2wBCkijBmHHhTAqlhADCQoDfq95715GDd93z/gcnU4nJhrqahqbWurpaWdEAY5/PNz2XHB4ZzS4kurZu2bd3n6BKJrWICDV1Q1NVSaamYXp9XkmSs7kCsxnBYFrMNE1NlSglhiXyubzHo6iqYpqWJMsCkKEbk5OTViUXCYeopAECjBACRDAmCANCBOHNjVQ/lu43zVK5tDy1CBACkFUF21Y4Ejl4970nP/zg6pXLnR1thBCEBEZQXxPfd/BQMp1eSMyahkkkZXp2XgBIMnUckYSAVDp78WJfV0d7MBSyLCsYCMSqo5l0ulQqIkwKxVKxkLv73nsTibl8PmeYtqEbjFll3ey7NmhVKgfvOFBbWzM/O1NfV9PY1vnC8y+kkwvNzU10xdYAbmKev3Ho9IYdPj5fCjaaGgU3LwOAm9sCbNbdL8QLzzx99vL1xVT6P//z/9gj9OFrVy8OjlqMr1YOrJkOJRhj5XJZURXOuKLIlmkxzhHGO7Zv93lVuKH8AFa8ppx7BwCEnIipEyJ16kMolQgCIkkEYypJlFCyUqlaW9sQjlS5XVMuLq5IdXFx+Z1A1bQnn/5FbmleU9Wr1wYmx4Ztm91911GMwOf3W5ZlmNaK1HAcnRwbSkQpcUZMIoQsm+m6HvV7evfuA9l7/vz55Mx4wO9rbmmrra2VFJVQQmU5lc2Pj4zo+XRzQ83Wrm5J0YrFIrNM22aUEsO0hWCqqkqSBELIskQIQQhblkUo8Xg002KWZTv+/6Zp6rqBANKZ/MjIUDq5qMnE6/MjjB23AYwQRphigjEG+ITMNOc8k8uZpgmOL6vgQgjEOaJUluR8Lnvg0B1LqdSrL78sERyLxwkhGAMluHvbNiRrumnmcgWbWY6+oZQ6z0pwwbnou3KF2VZzU4MQgDGprq7GhJaKRdu2bA7z8ws7enpq6uoX5+f1SqVi2JZl2pzPzC+OjY411tW2d3bo5WIundzdu2d+KX3mzOlIJBQKbTBifn3SfxPW6s5bDIL+Ovl9IYRl6K+/9OKZS1d10/jeH36zkk1OT0xeuD7KxceavfhyUFQwxvO5PGBsm0ZbU325VNYty+P19uzY4feq8JGoBbFihipgOYCKABxh6tSoYIwppU7UlFDqtPJLkuToU0qdHciWjm3Smg8ALi4urkh1cXH5bWJZ9hvH35SpVCkVZFVLLiXL5dLXH7xbi7fMTo57NdWpCsUECc4olRz/VIIEILw6OV2WJM6FaVnCNuPx+PYdPSZRz507W0wmGurra+saq2IxVdMABEd0eHxy8No1q5Trbm/q2t5jEy2fz9oWE0JUymVJIvl8ngtRFQ5UdENRZF23ZInajDHLAADN40Fo2coqlU4LzhhHmUx6fHxiany4trbG4/Fx4Ug0EAAYEMYIAXIasgCBM0sVoY9ifoVi0TBNwBgEFyAQgFP/iDFCGHs0T0XX27a017duefWll9LJpY62VsAEIyxRtKW1NRqvTaZSAjAgpGgewRkllDGG8LKEmk3M9/df3du705HdwYC/OlqVzWZ0XWdCZDMpEOL+Bx4YGRnR9YphWLlMJp1OT07PHn/vA5nbR44erYrF0kuLQb+vrX3rkz9/yjIqjQ0Njr3AqiR1dORqz9DNppU6fUvOlvXSc8M+J9jIePVW4tOrL/RS/slHf9I/PCmo9MePfLmcS40MDp4fGOE3XOSKpmWMM8bS6TSldHEuMb2wpGoeRVF7tnf7VEmI1ZsCR+IiAEKwc0rHGNXxPUUIU7qc2CeESpQ68nSlDpVijDGhhJCmli2BQMj9heDi4opUFxeX3xVsxl977XVmGxhj4Ky+rjYcrfrw1NnGkHzojsMGR/lcLhDwY0IcLySMsUSJJEm6aRMEhEoyJYwxZtuEEF03TKNi6ZWqcKC9sytXsS/3Xcwl5+pra+saGuLxWkkiiqpiKk/PLwxdH/QQsbWjta2tDTDVDUOiRAju9fkJQvlixTBMhLAkS0JwJLjX51MUxaiUsulkNptllhEMBiOhYLy6yuf3C0zTudzw4ODi3LSmSL5A6GP57BtS2wBCLLfXMNvWTQMBrEmEA8bOZHdEMMIYFFnmli0AmhvqJifGr1y+omlqVXWUMYEwDvr9W9o7CoUiYMJsmzGGMVJkhXPhSEYhhGlZF/suezW1vr6OcSHJJBKNIoBKuWzZtsVgLpHYt2+vompjo6PxmlrV411YXBQAfdeGpifGt3ZsaWlttfVyLpveu2//wNDYhfPna+PV/kBwbaJ8QwP/tRHTtfIUbq35adUK4FcOtRayqad+/vTI1LzX5/vy/UesUv7SpcuDUwmx9sLWTGpwWvht28pmc7GqiC8YUhQtEg717NiuynStvRRCwIXAaDnVLwAcpbo8RIoSQohEKUaIUEoxIXQ1erqS5aeEYBwIBJta2t2mfheX20qkuj6pLi6/6zDO/+w/+/N8atH5m8+5YMwWAOWyvjA78/CxOx/88lc51ZaSKYoFoRQhwJhi7MS9EMHYMk1MiG3bnAtZIhgBIVSSqM+jxWIxbzCaSmeGrvV7FdLesTXe0FLR9ZnE3NTUZDqVTCeTerHYUB/ftXt3IFI9PjM/MHA9s7SgaVqxrDu9UKqm2jYbGx2dmZmMhEM+j6eqOlYbq/J5PbHqqqbmtmA0alo2ty3DMqdm5oZGJ3KpZENdvKOzs6GpTVI0EIBWNZCj5UDY3PGFZzZjQgjLshhjtm2ZlmWZlm1bFcO0TNOyTMMwDdPUdd3WK8lsvlLR+8+dnJkc72xtbu7oisbiCECWJUKlxFL63NnzszPTxULeqRkwdV03DNu2l53nhQgFA/fff9eWttZ8sSxAlEvlyanphaWkJKvFQt7UK7Zty6r2yLe+Mzg0ePrEh4auV0VD0VDwc8fu+6NvfyMQCg5cH9G8AUvAO+99GK+O3HXPPdGq2A1B09+g3lrbm/WJ/qk3npfzqbHBl147PjI5e2D/3q1NscXE7NmL/RXLWiuXxbI2XRmCyjnjPJfN5iuVA729ARklssXOLW0AYtWKyzkEO8FUwVdrGDBCmBBMMEZ4pdyUOul+jLEkSbIsY4ycHipCKMaIErJt+27N4/ZLubjcRrg+qS4uvwdghN54+51SPuukuRFGGBMESKJkdHImkco+99wLjSH1oQfuLTCiF3KSrGjq8rwlzpjNGDjWVISA4IwxIQBjEELoplUsFEuFrN/r2dq9A2v+CxcvZebGa2viNbUNDQ0NwVAEQKhebzpfOn/mbDmXbqyLH9i3p6qmYX5xye/zgGCaz1spV86fO7e0OBePxc6cPfv+h6f6r15bSCazhWKpYhayGb1UqKmNV8Vqo9HqcDgUDvo5kYaHRsbHx0cGr0UjwUAowlerFRFaFjoIHHMigvFHE4kAnEwxOAIIIQzw/7P3prGVpfd55//dznL3jZc7WSSrSBarWFtXVW/qlrqlVkuyZcmWlXgce2JjJoGDwSDAIBhkBghmMBgg3waTCTBAHCOAE8uWbNmSJbW6W91q9VZd+76yWCSL+728+3buWd5lPrz3sstaHNjJAJZ1fh+qmuzqy1v33oN+zvP+/8/DKEYIKwQYI+55PPBzuXxuZPzi5StOpTg4mGempRQgpDKJ6OzcoXKtqaBXIR+JRgPffSK1FLmed//Bw+Je6eSJRR5wZrBMOp1MJDbWVgghEdvOZLNKgdNujo6MfOKFTxaLxWJxr9Zorjxe//D9DyfHRo8enk2lE4+WHnzms59d29j+4ds/HB7KZbIDT+rIn5WT+lNdz5/MW/3J//ZnHff/2IM8+chKqXs3rnz3tbc2doqvfOZT+Sgt72xfvHHHDfiTulYBCCF7ulMIIaWQUgqxs7OdSqU73Y4k1uzBKYyRUkr1B0/1c1IKdL6EHo7GCOk5VIyQVqiUEEIwowYhxDAMgvun/5TqlSpCyPzhRTsSC23UkJBfNCc1FKkhIT8HvPvBuUa13IuTxD0NhxAGJFvtDkLo6p3777z9o6ypjh476XGoVau2ZUoldQi6yZg+n+3tSFMGgHSEqhDC9fxmo9F12ulEZObgbADGrVs3K7sb8WhkaGh4cGg4EomaJovEE4VybXX5UaWwk0tGjp04xqyoF4ibN25cvXKl3W6urT3e3dl54YXn/7vf/W//2e/9k1c/+8rxxSNTByZHRsfGxscYM5ESAedSysF8Pp1MeELU6nU/EOtra8WddaVEIpkglCEApAWVljr6i/5fHhBGqFeZqQBjBIRgBb3GIoSxbdsIYy5lIpmcXTxBZfCd195oNhtDg3nLtDAChNChmSnCjGqtHvi+VIoQSjCWUvZUsFJKQbVWW3m0OjIylMlkpeCmaY6MjkxMjA8M5Aby+cGhoY31jY3NraGh/NzcHDXMnZ0dzkWt1b5w6QoSwcKRI+OTE48e3I9HIocOL7z+xg/Lpb3B/IBl2crYJW4AACAASURBVP9ZW/SnJvn/pEX65BTB3+jjtP+w965feeOdc5s7Oy+99KnxgcTag/s3Hz32/6pClT0nVel8UymEVFIp8H2/WCoPDuZHR0ZnpiYwKAWgXz6diatA/xVAL/TrlxYTjHuBU4RSpn8jhGGsj/txbzoV6x4IggnJ54dzA0OhQg0J+QUUqeFxf0jIzwH/+v/6NzcvfQQI9jPM9QGsEKLreru7xUazZZkGpSQXj3zhpec+9eoXPGw6rQYgwJgQTCglXsCl4IxghTAGxaXkXFBKkVKIYBEEkYhtm8bg0FAyla21u6sPH/hOa/bgzOiBGYnI3l5xa2urXC6VyrVGeS9mG5FIFFHj1oPlSxcubG9tfvXXvvTpVz4DgO7cu7/+eL1Wb+iQf0qwaZrZVGJqcuLYscWxiclSudpuVEem5i5evV7YXO84Xc6lZRmg5OH52aPHTsbiKfVXNsqVVIpr/05KzrkQQorA9wMuhO8HQRDoU38e+J7v+77v+X61Ui0WC/fu3E0PDN66dnV3a+OXv/DKkSNHCGWWZQFAu+tduHLz/t07PAg8tysE97qu73s9P7Xb1T/94PTEFz7/WV8oJQXnQkkZcN5stSKRmOP6N65fSyQSr7z6Ocfp3rpx7dbNG9FIxLTMqeH8b/7GV7/867/uC/VoaUlIVW11b9++vXB49ulnno3G4k9Kxic3n37s179ezv7tPk5KKa/d/OHbP7h5f6Xr8y//8qvEa965fffB4y31xFAsAAip9ASqHsEQvUopqaTinLs+n50/NDaYxwiUAkC9p4QRFlJghBUABu3bQ79yAlHGSH8cFRNCCaMUM8Z0iD/GxNg/5ac0lclNz8yFCjUk5BeQ8Lg/JOTngxt37m+sLqN+uGQ/Hx3r/5GnU6lkMlGpVLrdriLGrYcrr333tZE4+8znvuBwqJT2CMVKAcFYSuX5PsFYgcIIcyE919HGmmFaUsqA83qt7nWatmXOHprNj07euHt/7f6NmG2OjE8NDY2k0mnToIlUuu2Kc5evvfHG6zeuX6tWKv/qf/kXn3jxha2d3W9957X1ja12x5FSKgUIYanA94OW013fLly7dj0dt4eGh9b3alsPbk3MLmxsrIMCz3OZYVCCOt3uvfv3nGYpPzhIqdG3jBEGQDqzChAgRDBSQLQ5RwgmRLurCDAhqDf1aFuGGY0N5Qc6jcqpM0+bkeh3//J7pcLO7OwhPTjACD40NTEwOr689BBhjBA2TFMKHkskDYN5bhcAAEG12rh5++7c9EQmm3NdD2EMCJmGIXggAv/Z5z+xvbN758bVer3+0mc+Ozs3++DBg1az2fWDKzdvl7c3nn3umbGJCadZb1TKr37+8+99eOHGjWvTU1ORaGxfpD5pnf7YgOmTZaf7JuuThujPikGFn73dL3znm9/81vLj7d3i3j/+ja9g3l2+e+fO6qb6qxmoelMKAQghFICUQkktUZVSSiK8cHhubDCvp4gB9FxxzzkFPUuBQPV9cIR7/ql+dxglmFBGDUIxo/tL/ZQQiklvVjWdyc0cOhwq1JCQX1gnNRSpISE/B/hBcOnyBZAKYQQf1zUp0CfjgCglAwMD0Wi0Uql4XmDY1tL6zp/+ydcjwnn2maeRESlXawQkZUyvVyNMKKOgABOynwek29WFEF0/6DpOu9VgSM3NHkrmxx4+Wt1dXYqaNJcfHhoeSaVSQsHjrcLSvbuB5/3r/+NfTR86dOfBozfefFsI0S8Twr0DX0AYE4yxVFJIuL/0yDbI7OzB7/7g3QP5RMPlvusQaiBAyFSpZMYV/l6p+XD5QdBtZbNZyozekf8Tig4AY6LHVfvV7wRjAIoACO2JIkIs03r3nbd+9NZbleLuqadO5YbHtnYK58+dGx8dSSZTmBBQMpOIHZiZqTdarusapmlYlt7oB9DRnoAABQG/eetep92aPTgl+5JMW4OFwu7k+BgxInvlUrtRbTdbL3/ms81WZ3t7y/X8nb3Sufc/SEStM88+l07Hl+7emZ+dzWQH3n77R27XyecH+qmf6ieF5o8d9/8sPfo39VOL2+t/9md/sfp4y4wlfv1XPue1qnfv3r+3ttUTn0+4rVKLVSG1hwqgpJRCKqUkAJo9NDOYy6D+1n//Ce8/JR2G2ptOwRhpTdpbkyKUEMIo6+Wi9pf4KaGEYP0rxnh2/miY2x8SEorUkJCQv9MU90rnP3hfgdLSTPVDRhGgnu0FCmNkmlY+n2WGlcuk7EgkkU7dW9v+t//2/x2N4lc/97lSO2hUKzHb0vLG7TqEUoNRxgwuhOt6psEUAoQgCLjreb4ftNrtruNELWNudg7ZiavXrxcfP8xl06lM3uXinbffKJeKiWj0l77waqDQd157U0nef24YYwxKEYwxhv38JQAklFpafnRwagIZ9p/8p/947OSpZrMVtY1UImZF0p1uW3JJDVTYK9fr7aUHdygK0pksoVTrHq3RkVaIAJhShAARoq06BYhhpM1Og5Jz77339huvB5y3Wq07168fObJw4vRpx5d/+a1vE6SmDkyYti0ET8Zix44e4YCrlSoPfMO0GDMI0fodSyl1k2uhWFp+tHL27CmMdCkoKKUYM3zPtWzzqafOnPvwI9dpD+QHJsbGDs4vbK6vdx1nZ6905cr1Zrn47NnTY5MTALJRrZ45+/R7H350987dmelpy7Z+qv35Y9bpTzUUf1LI/jVOqgJolPf+7JvfKpRqw2NjrzyzSECeO3d+bbug+rmm+48ppMIYKdlb7e/ZqEpJJQFgenpmKJ9F+1JZKYVQbwpVAUJYKUAY6SIJ3IubwnogmjCDYMKooRejdCAqIUTv9iGMGSUY49nDi7YdCa/9kJBQpIaEhPydptZofvDBezoHXu2n3Guj72N50RMjEduilGCMQQECNT45eW1p7Y3vfGc0ZT11+kyj67dbLUYw7h2mg1LaCENSSkqZEIL0hAJRCvzAb7bbrXotnYzNzS/QSPLu3bsba4/+8jvf+uiDD9Ox6Kdf/tTk9PROqXbnzh39XLSF1pNZAEpKUEgqrS71fg0xsBoaHllde2wbBjMtx3GpZTCGKDG9wFMcx2OxgAdCqo2NjeX7d9xOM5PNUWr2HgUUQohgBKAQJnodCiP08TYVRlcvX/7mN/4ElESAlFJcyuWHD7AUZ599LhJPXr585e6dO6OD+XQmIyWnBA8P5hOZbL3REr0NKgwI61Ue6Gcwdbvu5StXbYNNHJjUPfUYIUAgOa9W9haOHLFjqQ8+eO/x43WkxPETJ2qNZrlckUrdX1798Nz5bCJ6eGF+IJ/bWH20MD9vx+I//OE7IHkup1U4PCku/7OJqn8zlNpeX/3+6z9Y29w5cuzYmSMzBmMXL1xc3dxFGO+P//ZX8nWjlB5BFVIKqf9ZKULo7KGDwwPZj59KXykjhHTL1Me3EDppCqHexh4htFcppXfVsEEpoaS3LEXJfkrqydPPmaYVXvghIaFIDUVqSMjfdQLOX3/rbQKSEAxKIYS12lN65K8XZqR3qDECUKAQwggUwlhIQTEyorFr9x79xV98O23C888+A0akVm+CEgohKRUlWEqpEAIlMcaUEC5BSqGU0rlCAeeNer3rtCMGOXBgMpkb3NwtWxR/6Ve/dOr0aUrp6ub2xtrj/iTC/nG/Rsre8gzCBCsplFKMkfzQiEnIXrmUSKYxJvF4outxyzSE5AqhTssxGFOAhOBCyr1S6dHDe/XKLqUkHk8QTHX+FCCM9T5Zb+sfEYwAwYVzH/35N76GEAghEcZCSoSQ67pbW1sP7tw8dHDmhU+9dP369UqtbppWLJ5QAIL72VT88PwcorRWb2CCCaYKEDMMSnAvQwkjqdTa483bt24fnD1kGAz6M5gE426ng0B2u27ge4XiHufBl37113ID+d1CoVatNlvtd89dvHX12tTE2NGjC67Tkr579Njxh4/WPvrovGUa6Uzm/6fTbSX4+Q/ee+e9j1Y3dz736stTQ6luu/X9N36wtVeRvdHRng0qAaRUPUEqpZBCKbWvUE3LOjw/l07GtYuMAPbvlKQCpdDHA7agevYpRpRRSghljPQEKdOC1fgrc6hapmJCyImnnvmxfK6QkJBQpIaEhPwdBWP83ddew0oqpbBe8Ef7xhX0W5h6ckkB6HnQXugoAkBICEEQRGLR+2s7/8///W9GE8bnXv2Mh6xSYSdi2wgBwQQjJIQApRCAYRgIEDMY54JgxIVEgDgX7U7HabcED6bGh4+fOJZMJnX1ZbPjPXzwoO/ZaWMXY6SNU8AYKcAEE72CQzAZGx5idqS6V2i0nWw2a9k2JsQyDcs0g0BahkEpCzjHSkbi8ZrTIoggpXYKpaWHD5fv3xkcSMcSSQCEkUKgu6iU7P1I+NY3vvbmG68DUpRRHQmAMeZc6LHLIAhWlpfLxUK1UikUCplMemRkTAouuEAYY5DDgwOj4wd2C0UAZds2IVQqwAgopVr1AoIgEJVyeX5uFnrjmCD7efWxaCSeTM0tHNlYXy/s7hAEL7388vZuoVAo+p5Xa7Xe/eB8DIlTZ05nMqmNR8tD+dz80ePf/vZ3isXdg9PTzDCe9FPhic2qn/V9BYD+muN+UJfOvXfuyp3llUdf+cqXMxaGwP3u6293/EBJoftpAUBI1b/zgV6jlJJSSCWVkEqBikSiJ48dMRnrfcwUYIyklICQAn2yDxhhJBXCWD87HXSKCaGUItxzTCmjGMBgjFJKGcX6+7SnUGcPL5qmHV7yISEhoUgNCfk5uVYx/sHb73DP1UalNg97Q6mA9nWhntj8sfRMbWrqcEpACEsxOT1z9f6jb33zz6nXfOHFFz1g1WrZZBQRbDCm+hXtaN8KQ4gZhh9wQhCmlHPRdT3P96QQAOD7XAGKRu2bd5e4jrTr/eRefZRemep1aYJUSkolz549XdrbW1lbO3L0CGVGLBYFJQmmCBQmxHO9IAhASYQwKD/CTNNgmFFfBATACfyH95d2th67nWa33QoCz3XazXp1bXnpwe0b3/z6Hz9aXeWCgwLDMDHBPAh4wJVSuN+zGQR+tVp1vQCBKhb3Bgcy6WxOKiAESwWgVMSkMzNTjbbT6XQoZZQSBYgwAymFMeKBAATtVvvYsaMIYV34qV9rPYZLKVGBt3B08eHDR/V6LR6PTU/PjE9O7pXKrWaz2WzdXl5dvnfvwPjYsVOneBB0mvXjxxbrjdaHH52P2FY6k/6pVmL/x/w4P3P7XYHXbf/orR9cvnm/63u/81u/YSlvZ33trQ8uuFzo9C5KaF/RglIghVC6K1aPoCqlpX0kEjl6eI5S0l/c1x5q7xOmQwD0FDIiREcuYIJRX4HSXs8pxZgw1i887TWfYj2cSgmZPbwYiyXC6z0kJATCnNSQkJ8juq73h1/72rl339GllHvlSj6bRpRqrSCF7NmrvblPBQBK9pzV/vaL9siUdhPtSKTtuO1a9VOnj371H/0WZ9Ficddm1DQNKaWUChBQQvQ2N6MU+iEAPaMUQCnFObcsU5tx9x5tvfHGG9x1dE87Jrjv9uH9zXylFKX0heeeyQ3k3vvRu4Zp5YdGkqmkaZkIsOu5sXg84LxaqSNQlDGD4na7FY9FPe4jCRjTcr2JVNBuOalkfK9UVQrarSaADHzfFwEPuBSiXq8LzgMeYEz0yG293uBBQBnzPU8IUa3VgyDQr1IimRJC/N4//SeGaekuJEYxoRSUlIDL9fbVazdKpZKU0nU6rVZTBD7ngdvt8oD/yhc/n0wmAEAIKYXQkk4ILoVEGHWcbjqdZoZ57qML2dzA6aee4oLvbO9cuHDedx1K6Wg++5tf/dWv/NqXzUjk8eZOcacwMnXoR+++ZzD26quv5IdH/guylxQCtLe9/sZbP3q8tWtHo59/6Tkm3Pv37l+590gq1Wm3fS5s26aUaNWplJL9qCm9wy9UT6zmctlDM9OEIB3qL/vGrfb1pV6I690O9UZS9d2Nbo6gjPYipwgh/cN+Sp/8jRCMTzz1DMbhLn9ISEiPMCc1JOTn53Kl9PSpk0ePn7h6/UajXrt24/b6+tro8JBl2wih/UNbpZSSgBBSEhCGXnhlz2vrOXE630cIgUAmU8lS2/93v/8H43H66i/9kitxpbyXiMcNg0kFPOCUUmYwL+AGo9pbZQbTQ4pKCMoYM5hSSnCeikXnDy883i46nfa+Pu13DgHGWEqJEP7cKy+PjY3cuHlTcj49v+h0OrZt2nbE9TyEsOd5PODJVLLbdSnGQkrLNIUQnhtQQjpemyHqc98ymOt6mFArYtq25XQdpZDBDMfrEoSZYSQTcWbb3XbHNA3GmJRSKCU4lwo6ThcACcG15v7n//O/3NktLB5dAF09RalWbJQxKWXEtg7OTJcbbd9zCTVAKUKZ1EMRCE1NTZimiTGRUqh9N7J/zk4IcbvdSqn06U+/vLW189EH7/pczR46ePKpU6srK+12hyu4cffBxQuXDoyNnDp9ZjCfWV5++PyzzwqA737vdUbR0OAQ7k+p/tSyU71Lr8cdECAEivt+p1nfK+zeuXX93fcvbBVKyLQ//8mzhgounL9wa2VTAbSaLaEgnUoKITFGspePKgF0p1SvZEq/yYNDg7MHZyhBesJY6nkApRQAQdDLwu1PI/QLpRBjvVbT3jwq7YUlMNrbk6I9H5XqGehTZ57fL6oICQkJCZ3UkJCfS5RSX//zb//+7//7RrV09uln262G53Utg0mpxZWSQuoAIG2y6qJKvWWllNRStTdbCaBABb4fj8WLlaop/F/5wiuf/9KvlZpOp1GL2CamlPsBYUQKxXmgD2gBIYyxNmUxxnqAEROsk95dn69sFVaWHxUKRa/bkUIQDIZhZjLZibGhmZnp4s5OrdG4cf3m2bOnP/nJF0pNf2dnG3EXMO26npIqEJIHgQJglCgpKAEeBJTRZrNt2xHf9ygzQKlmq0UYbTVajFHXc1ptD0RgmaxUqeSzWcftYowLpUq1VGKGyaXotDott8nAcLvdjuMEvi+lJIS++uorTz//otdpYYwwIUIIQohWbAgh3w8AADP2eHP3xo2b9Vo18H3Og67TkTx44RPPpZJxjEkQBHr4oSfgpFSgBBc6Gz/gfGh4pO24165ctk1zeGRk8dSZW9evXbp4XnCey6YTicQvv/zCb/zWP0plMuurq0IiZETeP3fesoxXPvPywOAw9MXo/qdAChF4XsfpdFrNdrtdq9fbbafRaBSLxU7H9XmAqdF1OkePHTu7eMh32h+89/5qsao97c2t7fHxMSGE5/k6LlcppcMK+pOovWqpXC47e3AG99NPlVQKgZQ6GAswgFQKY7Ifk6XX+rUspYRgQjEhOg0V9/NQWW8OlVBKASFKyLETZ/p5sSEhISEfO6mhSA0J+fnj3KUr/+EP/iASiermJC7F1tYWUUEsGuVaawilehXqUodWPtFmJAGQUhIAlALZzzPyPTeVzlQbbae087/9i//h2Cc/t7S64bUq6VRSISS4EFJhjJGSEpBtMp8rHngGY8xgQirfDxjFAZdUh4ti7LhB1w8wAtM0Y7bBOW802+c/Ov/w4cPRiSkFUNnbXZyZ+Mo//Acslrl8816zVvY7LUSoAOT7AcG42WzZBolGrHa7TZkhOFcAhFJKcKfdIZS22t1yqYRAMYNhi/lthzKT+931ja1kKrVXK/tONxaJ1ptNIYXBjFazVavVPNczTaPrdLvdrm1bADA/N/uJT75sW4ZhUCkVIGww2mo7tmU4XQ+URBgTQhxPvvPeB1LKvcIOxrhRq509fWIwl5VScCkkF3K/7F5KhJDUsg9A17lapnHk2Ilv/Ok3MUYnFxeEwqncwJ994+ue6wKogWx6cnjo//zf/9eZ2VnP8+7evjM1t3Bnae3ihQvPP3dm4fCCHYm6XadWrVRKe+VypVSpNtudVqvDhRCAy3vFF547m85kuecG7draTokS/HindOTw7Keff+qdN996uL2nnVE/CFzXi8WiXteVoCgzEIDqpUxJLvTdh5RKDQ4MTE8fwHqqWCqdkID6hrwCIKAkIEL0mhQQLfMxUEp1cj8iVAtSwzD0aQBltJ/VTyijBOND80fDOdSQkJCfKlLD4/6QkJ8/CsXixUuXlVIGYwiAUhqLxRU1Xc8VnBsG6+X8ax2qAJBCCIOS+4+gRwf15CIAYAQIE9/3CZLJ3MAb753/4O03Dx8YPjS/0HQ8p93SU4MYYUwI55xzoUDZtsWFwAiojuzX9UIESymllBgjkxHbYiajSkpA6OHyyo2rV37nd3/3+PHF6QOTQ8PDDcffWH1kIX5k/tDo+IRhxxptp1Gru67re74U3KQQBL5hUIyJ53kAYDAaBNzzPCkVMwzdcZRIxDBB3BcKSYJILJYIQCRtmxJDKIkpkQI85fuOL5iMxGPcF4ZBhZCO05VKlcqVRw+XMulUKpWilCophRBKSlCSMaLjl1rt9sbao7Onn+JKtVodBYpSOpBLRyIRglEQ8H2fG/WiZ/uNC0rpOQcuxNbmxpEjR4aGR370o/fqzeaxhfnpQ3OUsWKhGARBtdE4f+GS06wvLCxMHjy0+uCeDNz5I0cvXr5x5eq1a1evXbtx88rVazfvPkgPDO3sFtqt1uGD05VSYX5mslpvKCWpcCvFgutzw2CWZUUtc2Iod/HS1dXdkj7BRwh1Ok40YgOAVGCYBvQGkHuxUwC9hanRkZGZ6QME9QdGlFK9Y/1eOxbSCWe4N9lBCMYIkV5iP6GUYqpDZgmlRC9QEd0p1d+iwhifPP2cYZhh8WlISMhPEm73h4T8XFKpNd597z3LMFrtNqigXK2ajEYjkVgsLonhOI4fBJbJoJdN1U8vReqJJlUM0FMdAPoAX/9RJIVACBAz3zt/5c0335jMxE+ePiuAOE4HQHHO9XYLJRgh0pM+GOufgkAhTLQAAqUM09ACCBAKguCNH34o2rXf/Z3fPjAzOzg4lIjH0pk0s+zN3dKtGze8Vn1sILlweD6ZyXU9j2GVTsalUrZl2XaUGczzPCGF7jtNpZKAkMmoQjyXyVqWZZqmYVhIgUIQjUYjpmlE7EgsGgS+9APHc5EgGKNkLBmxo9RmQdcXgsdy8ZgVdZyuVHJzc1MKns1kKGMIISFBioAxRijBGLqO+/Wvf/32zZtHD88vLC66nh8Eolqrc7+biMcQRgHnCGMhhHapZS9cVPb7wbTRiNutluO0Tz112rSst95+q9VqP//8c7Ozc47r7e7seH5w896DD3707mg++9SZ05lMxmk3FuZmsRKra6uZRCwIfJDBzFA2CHzhOru7u4lUqtlsBb7fbLe3ipXVnb2tQuH+8uNrt+4uPVrxg6Dlev1OKKSU8nyfEEYIRhj3Q/r7J/xSSaUoZXOzh0aH8tAP1RI6QleLcOg9FMEIADDGBCNKCcJYn+DjngallOlGCMr6XzHKev2nH29K4VChhoSEhCI1JOTvD/lcdnOvsrm5sb1TfOetH5RL5cuXLsZtIzuQNxiLxuLUMIt7RZNixgy97I8xSCmFkHrbvqebYL8gHgEojLGWs5RSAMWFyGZzH1y7+0f//t+dnp88dub5vVqTu45lmZxzy7L8wBecCyH0Nj9GiJmmkFIEgR43FEJgTHREKsbozImjwzOHl+/fRn47N5BPZwfyA7lINGZaRiSeLDda167fqhd3ZmcmT544Hk1lK5WSbVLDMAkhAeeGaQqhCMGMUc9zCaYKIRUITEgkGkWAEFYmM7rcD7yAYCyVbNVaYxMTNa+DMXYch1JCQLkBT6USkViEe16n3iYECyEGBvMGMzqOs7KyMpDLJhMJjJGQSnBBKFVS+r733nsflsuVGzduZBLRs08/Y0Uimxtbm9u764/XRoaHMKZCiF7ugVQBF9s7O+++9/7jx+t2xI7F47Tf3QoAlUolmYgdWTx+f2l59eH9Vqf9wgsvDo0M37l9u9PpuAH/8MLFx0sPTj51amZuwfPcP/rDP7Qti2DQdwX3Hq6s7xaLLc8NhNNu319Z3dja2d3dLRR26tVKqVRqN+tut5NJp4eGBvtZ/XrwVLZazWg0AgAYoSDgSkklP47rB0BHjxxOJ+IIFEJYcgEACEAiIAhEP9Ssd6uDMQboreeTXscppQwTSggllGFCTEoIpQZjH1dOEUIwXjxxhlIWXsshISGhSA0J+XsFQujZ06c++clPvvvhR92uW9jdUQpaXffR0n3bNFKpJKU0nckJbLRaLSG4bZkAPX1DCN4vfH8yJV4n0vdLARBCiFHqep6BYWB84q33Lz68fnF2YvDAofmOx7vdrh49DQKupGCUEUp4EHAeSCm190ZwL2ReTx7oHKqZiZG5w4v1jrd0745w28lUOpPOxhNJ2zIt08jk8q2ut/zgfqO0O5RLzx85yqxYx+l0nTbnHJRklHDOlZSmYUoRxCKWZZkIkFKCMcNzvWQyYZu2L7xiuXz14mVGycsvPH/ixKnC9h4mWIA0LNvljugGbte1ErZBWLPZGh4ZVgpS6RQmpN1qXrx4OZWMZzMZygyMkO8HQeCXK5XzH12QUiCE98pl3/dmDkwODA23Op1SsfRw6aFhsHg8rhUqAHAp7ty5W6/VPc/f3S0QQpKJBKVUvyaEENdxuk57bna20WyVSyUlBWPsxFOnW61OuVTqON3NYunG9esHJ0YPHpq5cunSjeX17WKpsFfeLpR2i3vFwm6lsL21sb69s91utTjXiVpI59Hqt3B6ZjoSsZU+0FdKKVWv15KpNEKon4Uq95tPtWw9NHsom05Ar3BKB/XruAiQvfkFXa+FCMYYI4wQIQRh1DvIp5RQhnFv7NRgvUV+jHuVUhijZCJ59PhpQmh4IYeEhIQiNSTk7ycRy5qZnnY8Lzc4FLfJF7/4xdjg2Mrq6vUrl4XvZjOZqG0nkikzEqs3miLwIrYNAFLqyVSly0tV/0i3r07xflEV7gULIT8IXM8rifjJdAAAIABJREFUlGvXbt+79P67EQhOnDguiNloNCxGTcNkpuX7PkJIe2oBF0ophEEIpQOGpBQBF0HAfd9T3M8PZMcnp+vt7v3bN2qlwkA2kx8cyQ/kotFoJBaLRKMdXyw9eFgtbA5mEvMLR3NDo1yidruFENbFoXqj3HE93/NdzyWERKNRhLHvus1GQwQ8CKSQ8Jff/s7a2tqBkcGWFzh+mxiMKLAjESSlaRpYocJOYfLgpBJqfHLCsi2/625t7QwO5YcHBt5++4e5bDYWi3EuXd9fXVm7d/cuQlj30PoSqtVKKhFbPHo0mcuXK+W1tcc7O9u2bUVsWyrVaDRu376ro1illMXi3k6hEI/Hk4mEUgoUEEI4F+VSMZvNzEzPLC0tra4sjwwPzcxMj05OFXZ3O+3Obqny/ofn/vQb3/zw/OWVtdWtzc1isVjaK9aqtVKpXCrXavVGvd5sNptOpyul0G+xjiawI9GD01PQj8aVUjYazWg8rneepJSCc6l6UwlKQSQaWVw8ko5H+wt2IPufFQQfB18hBBgBwUQPMGBCMMGEEMYYoZQQ7ZhiSpmhj/n1UKouPyU4kUjOHj4WHvGHhISEIjUk5O85w4P55555ulyp/Ddf/fLTZ5+aPHCg2XFS+eGNze0bVy4lE7FEPGoYZiqZFNjY3NqOGJQZhupv9PcWp/TqlB5bfaJhFQARhBBGIJVS4DqdVDrjCnn/4aPXv//6kfHcM594sVDvOM0aY1QB+J6PCeZcJhNxBcr3OSGYMUNIvY8jDUaFVG4QtNstr9seHxmePHS4G8g7t6679UIik8vm8tlM2o5EAaF0KuErfP3WnerW43w6fmj2UH5sqtZoBl6XMRYEARciFrHi8TgzjFjEwhgnkwndN4AQTmbiBjUPHTuxMHuw4nTdjpPL5pOxmNNxMMJCyI7qtOudQ/MHW9XmgbkpO252O15xZ5cH/IVnn/7wowt2NLq+sVGvVicmxwDQrdt3Nzc3TcvChESjUaUUpobrdrud1vDQ4MTUTKfrNhuNR8urQeAP5PM3b96q1xtPqDvwPX9jYzPgwdBQXt8lAIDn+xST+fnZocEhROiVS5fu3X/w7LPPHjl6tFyuVCuVZruzvrXTbLsAIIQQQnLOFUDX9QPfl1IJIYJAOI7TarVa7TYCoJS0251sLjc4OCB0MJYQXIhmsxmJRnSxgxapoEDo6DJQxxaPxiJWv8YWSz1q3Ku07W/XKaUDJfA+lPQUKsZ6CLUXLkWwlqaUst4hPyUY4/kjx0MPNSQkJBSpISG/EJiG8ezZM5OT06Zp2AYdGchKwWPxRDyTv3P7zuPVFYPgeDxmmNZALu9yUa/VMSjDMJV2UgEQwnofptesqnpaFSGsQGqVFXDedTqxRAJjomMwP7p07fy7PxxJReYXT7Rc3+06sWgUADFKPN/X0QEKQAiBkMIYBwEHQEIIikkQcMCo23WF5+Sy6dEDB11B1h7er5V2I5aVyQ3mMmnLjhoU5wZynsSPVh9vP17JxMzFxcVsfsQNAsGDWCwacGEyygxTm4Wu6wIgw2BSSgSEmHRieMSOxVKpFI2wQHAMipqEUcoso1GoxWIW52J4cHhkbCgWiZZ2S7u7uy995sWlpWUWjUajkXqtvlso3Lt7b2x8zIxEu15AGUskk6YdicbjAOAH3PV5s9WO29bs3Fwyk213OqW9vZ3tnZ3dAvRvBnTnlj6OL5erhUIxnx8wTVMq5fuBZZufffmlz7366Vg06rg+F2Ll0XJhd2dwML+xvtFstoXgSimMEQDiXEipfD/gQQBKglKUEqUURkgBBAFvNFqxZMr1vFOnThmUQD+T3/f9gAvTMJWUQnBQ+5WnoJSaPjiVz6QQKKmgPxwAUsn9hoie3Y4RQQh6jVIIY0wpxZgwSvV+FKaMEGJ+vDdFaG+bn8TjicXjZ8JNqZCQkFCkhoT8YoEQsuxIxI4YBhkcyOWSscD3zHhqYGT8wvkLqyuPRkeGLMuORqOJdKbpBHuFnXQiDoAQAEZI6e5UQLhno/bUlZY+GCM/EO12J5VK9HqkAIhhdgJx8fqtSx+8++KphemF4zuFPQLcjkR4EDBGARQlSAgJChBGlFIpJEIoCAJCiBAyCAKpoNPpSK8zmM+NHjjkBurunVvdWjGby6UyuXg8iZlBsUokk57CN27eLW6sjOQS84cX8qOTjuMIzpWSBONYLGZHIhgTUMIwrXgigQCcbuB1XQWCYmViQwFEojEhZbXSqNeqpd3C3KFDiND5o3NW1CxU9h7cfrB4bK62V+34wYHx8ZbTadabK6trjLGlBw8OTIydPHNWIColmJaFMbEsW0nJOReCtxwXKz6Uz49OTXVdr16v+X6AEEaIYEJ1NBcCQJiAUt2uu7GxGYvHMum053mGabzw/LPpRHxm+sDYyJDjuBhDpdaIRSPrjx97no8QUlIIIQEjKZQUAmPEGAOEDdPIZrNdx4X+Jtzs4YVTx4/kstl8LtPbhVJKStlstW3b0klYGGMphP63CKEjCwsj+WyvSlcp0duy6rnA+zUCWiXrOVS8v8tPCKUEEUooIwRT1gtG1b8zxjDGjFKM0NFjp/dHWkNCQkJCkRoS8osFZSyZTMdi0UQiPpTPDaTiQvCxqYOEWVcvXqiV91KppG1HsqlEZmCoVK132i3TYJiQ3qY/KOgtbus1f9VvZYeAi26nnUqn+1EAgBFgTAzDcAPxndfefHDz2qmjh4cnpxttV3JfSIExQQCEsn4nq6JUnxAjzgUoxQxDgQq48Hy/0Wxwt50fyI5PzjS7/tLSUrO8m06ns9mBVCZrWlHLYLF4zAnk8spao7gdj1oHD85E4smAC8dxDEaEEEHgE0zqjcZecU8qxQxDIEwwRYQBwtlUmvOu3+02mzUQamxitNP1nn76VNy2G/XW7at3GCG5bG6vXFk4uaAI3l7bWFlZs0zTNM0gCJYfrdar5aNHj0QSCc/ztQOpu6+EEL7ndV3P972IZc1MTwFlAEApM0zDtAxdE6oAYaJHfrFUsLW102o1oxHbsqzPfOoFwzQxJrlM6vXvfq/WbJ08+dT4+MRgfmBt7bGO/dJvUywe+/QXfvnIqTOjk1OLp56KRexHy8vQb53FGC8uHh7IppWUtm0ppfbFaKPRiESi7Vbz1Ilj7Var63lKKTsSOTw3m0nFQXcQ9N4oQIAwRgAgpSJ4f79OB5Wh3iQqIQTjXoVU70yfEYL1GGrPZCWEEpIfHJk/cjyUpyEhIaFIDQn5hQYhZNuRTGZgID+Uy6Unxoby6ZhtGomBIU/iu3fv7G1vJuLxRDyeyWQy2YFaq1NvNChShmki2O+BhycSVQFABQFvNRvpTBoAPm4d0jkAGJmRWMf1v/fWu29868/HsvHDR44qbDbqdQy9B+vnH3EAhDFBGGOC9WwoD3jABefC9YNatRq4ncH8wPTMQWInHi4tlbZXLYMODA5mc/lkKhWPx1KpVMvjS0uP1pfvZ+L24fnZ4bFJhQ0hRLvV8n1PCO4FvNnsOO12q1Zqt9vddisIvKhFlx486rQ7lmFJpAbzw8+cPRWLxJqd5uWLV8vlyvETR3Z3i2dfOtttB6v3llZWHgshcrmMbrOXQpQrlUcPHyRs8+DBg9QwOp0OKKVD7BUgP/A7TrfTbnu+P3NgcnJqWiiwIlHLsqOxBCbENDRU25BSykartbW9yyj5ja9+GQGAktW94jsfXuh63tjoaDIR297e3iuVXc9TAKBAASwcO3Hm9Olmux2LJ1Lp9Fe/+hW3WV1bW5dSIQSnn3766PxsrVaLRCKUUl15JZXiXHQchzF6/dr1oVym1mpzIfP5wYX5QxHL7KnTnkZFuly3l60LvTBUjBHGCAFo3UkJoYwRSiljhq5AJZgxyhijVBuphFDCKB0cHBmfnA4VakhISChSQ0JCelLVMIxUOpvN5qLRyNBgPhm1QIns0Cg2rB+88XqzVp4YHWGWnU4mcvnBpuOW9woD6aQAAFB9QaED+pECxIXfbLYymczHagMhpSQoqUBLVUwQDE5M/uD9C3/8H/5gdiT7zIsvVVqu77QMgwEoSnAkGgUEUipCMAIkBDcMhgnRVa4YgZAq4Nz33G6nk4hYB6ZnWDz76NGj3bXlWMRMDwxlM5lYPGGYLJmMUyv6YHn10b076Zg5NjaWSsYr1dryw4dXrl5bX988c/aM47mDuTxWot2obRcK9UpdUpTIZKYPTJ85eWJkZFhJ2eXu1sbO3bv3PvnpTyzfWTr9wpk4Saw+Wnm8vrGxsTU+PtrbKxJCKCmEcF13Y2OjVNg9eGAync012x3OOSCsC+sDzj3PDwLfdbvpRHxy6oDvBwGXhmEww1CAGCWYGggEJpgQCqCUglarPZKKHTx0UCq1fP/B7YcrAKC4f+XKla1CsVarCiG0diSEpLPZhblD9UYDU5ZKxA5OjlkUvfv+OUrIcy+8cOLInBS8WCymsxkEoIOlpAKn25VSlkuljutjZhGMx8fHZqYmGO49rOqf7isAqRRCAEr1osgQINTzgDHBRB/0M0aIXpAyCCVML+8zRsnH5VKYUErw/ELooYaEhIQiNSQk5CekKmNGOp2NJ5KJRHxkOJ+wjYDziZm5dte/dPlSq17N53OMGalEMhJP7pZrrtOxLQuTXsepfhwFMhDQaTZS6bSWrjoLQAHooioARAhWAO12Jx61c0OjH1y59aM3vndkamx6dr7ry67jEIwVKNxbIur1Z3p+4PsBwYgQrBTow2KCESbUdd1OqxGP2uMTk1Y8tb61U95ep4QkUqlUKhOLxU3TTCUTLBJb29heW17a2thc39is1JuJRCIaizXrtY7jesATidTg6Pj83Pzhw3NH5g8fGBsbGkgblmVQLKXaKRQ+OPfh7MzM5vrG4ZOL2VTu0eb6/Tv3b9+6Ozo6rHewpBC6uV5vygsh2u32Xqk0NDSYzuYkIM/z9FoUxlgIHgTc94N6q4Mlnzo4k0ilXN9HCEw7YpqmlBJhihCgXnsC+AH/8NLVm1evTY0Nr6yu7dWanY7jc+H7frlUbjRanIv9N3Tx+Mmx8fFOx7Ft2+86UYvdu3XTTsRM0zx5YhGBqlZrPhfJRFwqJaQCAMl5q9WKx2K/+du/fWzuYLFcHh2fODAxhBQSur9VSi1PuZAAuvwBEEK6kUyb3ghhSjAhOu6UYB2J2o/mZ7SXkUr0EhXBhJC5+SMHpmfDyzAkJORvLVKR7/vhCxES8vcepVS9XqlUysXd7ceP1+88WCk32qVy9d71K+lE/Oji0XgqC6A8Lnd2trudZioWMS2r35kpHTfY2Vg7NDundMgnIARI9ecYlVKEMCmFEEJ/LaSIJ1LVao27zm/+6i+98oVfbnq8WimbjNgRmwsBUur2IkBIBJwLwRg1DMYIsS1TSgiE4L6nAGLRSCKRSCQzra63s7XltusjIyODo+OYsG7XqVRr7WbN9z2n67qe73Y92zIZo1IBY3pokgHIIBAYKUaJ7/uddntnZ3dtc/3+3aW1xxtHjy0ErnfoyOyB0al7yw/Of3Dh0sXLg0P5RDzGeeB6gQgCn4sgCGRvTUpEo9GnTh4nlFLKzFgSiLG5udl1HKQtR4x9t4sJYYymk4mJ8dFIPFUslR+vrgoheOB7nseDwPc93+067XbAA8EFAJgGzWUyB6YOCKWSySSlpNVsraw93tzckkLHQAEl5Jmnz6TS6cuXLztOd3hw4OjiUcuyypXq1OS4lLLRbNm2hRDSa/uScy54pVLNZjOJWNTpdA7NzafiUW3iyn4TFUZIKRBSq+H+OIe+CdGn/Bgz1iuLwnr8lDI9e8r6i/w9/YopISg85Q8JCfkvhDEWitSQkF8sarVyqVQs7u6ur69fv7vcDtSjBw9uX7tyfPHwwtET+vgeEbq6vt6qFMZHR4RSAOB6/uPVlUOzs71cVQVajEol9295taBVCOkQI6kU99yBwaHN7d3a1vr/9D/+0y/+w9/crXZKuxupVFIIIYVAGAWB1rUSExKN2ARjgjFg4rmufhgEQBBELDM9MJxKprqBuHf3drdemp2dzY/NYEJc1223mtVqqdVs6konSgnGhHNfBAIJv9lslcuVzY2New8e7mxsrBdKtUbDD7htmcOD+fHx0WPPnD67eGJ9Z/vtN9/+/mtvRqOR8YkxrSM9LxBCeH4gpfR9X8fbHz9+LJ1K6lJQahjMsKQRrVaqpWIBIQwIMCYUo263axjMtq2RocGZ6em2F9y8dbvbakpEJA9ctyul7LSagec4na4fBAAghGCMvfD803Yk0s8TVQEX5z4832y1QIFSCmGk0xcwQU+dfurgwQMgZNtxBnM5qVS73bFtS0iJFAghhBSci1q9nkomlVKHjy4MJBMIlJBSy1AdRKX1KCiQSu535Go/FWFEMNFutz7QRxhjQg3GsC4/ZUTHTOl4VELp0NDo6PiB8FoLCQkJRWpISMjfDM4D1+1ubq7v7u7cvH3vwcrm/fv3V+7dSibiC/NzIxPTOsWdK7S1vRU4zVQizqXa2Fifnp7WKg0B6luqoJSSUlFKpZQ9WQOglBQ6blMKgnE0ntje3YtA8KVfevVzX/rVesdv1su2bRGMhZQE61wkZJsGJhSBQoC8IPD9AGFEMZZKYYRMg9l2JJFIRuPJluPt7mxKt53NDQwMDmNqdDutYnG3srdXLe9trG/slavFQrFcKVdqjWKx2Gi1HdcXUiKErEh0cHhkYCA3OjYxMz0yPTk1NJCt1Oq3bt38T//xj8uV2uzsDAAIzn3fd11PCOH7QcD16Kw8eHB6YmIcgSKYQO/0mxDKkBltd5zdnR3P80FJhAmhTHJfATCC8/mBidFRatlbhb3CbsHrdrtOB5T0PNftdtvNuu8HABAEgWEYn37pRWYwhLDOfxVKYkAPlpZWV9c5F9C/URgcHv7Ui8/FY9HdQiERj0dsW0rZdhxKqM6O0iq/3XYUUolEYn52NhWP7CtRnX4q+o2pBGNASGdWIYQIIYCQAmAYA8aMYMqYdlF1bj+hlOoAf51FpXP9KR0YGJo4MBNeZSEhIaFIDQkJ+dtL1Uajtrm5/s75G9//zrfbleLUxPjd1a16ufjsM2eHRycUYIyRy+XSg/vc61TL5ZPHFwETLgSADtAEJYUCpBRQQoTonUn3nValFJJS6L57yf2xA1PLy6uqXf2X//z3zrzyxeXHW16rZpoGpgQhBAoMgxmMKoS9rqOk4koRQgzGpFKB73POLdO0LNsyjVwuZ9iJVsdZWl4ubqy2dtcrtfqVazfvLK/VO47FWCRiB4FfqTUUoHgqM3FganpqcvHkU5PjI+lEPBWPSN/1fD8IAs5FEARrmzt//EdfO3/+0uLiYYQx5zwIAt/zfM/3Ax5wHgSBUiqTSR9fPAoYY0IIQgRjyihlhkEJItTzpTCjG6urTqctBWempRT4rgOgTNOKRiLDQ4MTY6NdCVevXu+0Wr7nem631aj5nhcEAedcKZVIxD/x/DN9m1Pqg3ellAh4sVRaWVmt1RoI4bn52Rc/8ayUgiK08nh9bGwUAFyn2/V9znksGgEApUBK4fmBYVqnTi1GDAMpJaTaLz5VPcEK8ETvqVKSUarTUTECyhgoZRgGoUyf9ms/lfVCUqmO60cYE0IOLxyLxhLhxRUSEhKK1JCQkP8KUnVja/P6rTs7G48z+aG33vuosld8eP8+kd7C4YWhkVFEGEKo0XaWlh5U9goDmeTE+BgzTCklgJJKSamkFIyx3hK6AgRa+vTmGntzrUpJKQ1GmWkXCsVshP2z//4fHznzfK3ZqlZKJiOWaVh2FCMkpew4jpACI4wxlkrqOUfAGAAsxgihgFDEtuPJlGFFC3vlN99889Klix9duEgJnRgfGxsfzw0M5HK5/NBgPpvNZlKMEiW5EiLwPSF1S6ggBAsugoDvFgrf/f5rr333B6NjI+lUMuA88P0g4K7nBn7gB9z3fSEEIeTs06djtg2YAAJDbw0Ryhg1GNPdS44vnUBUavXKXlEKCQgJwRGAEJIxYllWKpWenhgjprXyeHNrc93ruk6n3Wk1uo6DMRZCjI6NHl2YV1IqUFJCPwtMcSHbrebW1raQMpFInDx50jSoNne1J1ppV9utTjySCFwvEolQQoSUUkpmmAuH55LxqJL6TemFTSGEpFRCyf28BQCF+vtyRB/rY7RvFVNKESaMEoyxwRj5+PsEY0QIOTR3JJlMh9dUSEhIKFJDQkL+qyGl2NsrdrrdP//eD5ZuXfUECiSsPHxQLe4cnps9ODuPCQNMJMbFvdLq8pLyncmJ8Vg8yQNfSCGlNJjhBz6o/YnVfqgR6AUeBdA7WUZKCSmSyfRepar+v/buPMzK6s4T+Fne7b733tpv7dTCviOCu0aicYsmJiYmGhOzd9JZ7Nixk0k6mWTixI4dEzt2HB2JC4oiCIIgCIogCIJsUlJQUFBQVFFF7cvd7/u+55z549wqnL27R9PJ5PtJnjyKqHCBPF9+57dkEjffcM0tn70tLXkqPhwyKTOsnO/5vpBS6s4BxpmSyjA4N0yiBKX5w0f6ZLxlGI7jSEJTmVwmm1OEcKqIkoQQKWUQ+NwwCSEi8JXI74qSQuQ8X0kRCCGlHIrHX1q1ZsULqysqK2trK33f9/1ABEEul8tmczldbvV9KeXcubOqKqsMzgklepO9bVuUUG5zh1v69pJlWYFQg6OpRNbv6+sfHR4iJB82pRRCBI4TsmyntqqiuqZGELrrrV1dHaeVDHI5j1ISBMHkSZPq62qklFKqsRkmKaUSIkilkslkijNWVFo6ubFBCBEEASFECdk50n0i1X3l/AsLvXDbiVN6LSshpLikdOa0SdxgVFElpV4vNbYXNX9ZSilJKWWM6+Sqt/czzgw9JWXk96LysTGp/JYpwzANTll+wn/K1JnRgiJMSgHA+xhSsYIKAAilLBKJFkSjUxrrLNsqjjomY260qKZxctPBpv173y4pKiguKjYZjUYjExoaC8sqd2x/MzUyWFNdKcfGwGW+UDd2EEApvdhIt1Dmz2lSSikjlPqex4msnzx1/5ETTz++eFZNyXkLLvCpNdDfL4WglOpKp678mYbBGDO5wRjVu1ulFFIoxrlUKpvz0umMDl2M5DtlKSGWZXPOpQhM03RshzBOCBNSSklsi+uTUel0pvndwy+vfyVWWVlZGZMikPpKk5SB7weB0AlVCNHYUD+hod7iBqGEc8O0bNs0DcPgEe4Qy7ItzrllWcwwHJsXFBQwQkKuKxQZGR5WUlKqV+KzVCrle348Ee/tH6itrppQX68IGezv1zNKldXV0Ug44oZUPuhLSnWtWga+n8vlRBCYlllQUFhYUKCDZuAHZsTKxPxL62bNrplRVlLS19efTGUM04yVlc2cMZUahAgi87v6x7Kp7sYg+UtS4//RvwHQ1VNL7zs1DCu/YcrkepbfMvnYllTD4KWlsekz54VCLhIqALyPsCcVAM5hjEci0YkTJ9bVNVRWlJUVRaWfK6usLiwtbznS0nHyuG3b0UiEEhV2QyPxRNPBgydOnAzZVlFxoWmaUoqxVtX89D8hSh+lIu+9T0Upo7rhkScTCYuT4vKqTTv2bVz3UoR6c+fMlYYzPDoasgxCqJSSUsZNgzE2vvxKKaUzkpIyCHy91dP3cgZj+dvwShGiglzW97KpRMJLjDiOU1ZRVRAtNCyHEJXL5RjnnNGOjs51617O5nIV5TEphFBKBPmEKqTQDalSypLS4rlzZuUP1RuGZVqWYdiu6ZiWzSzDskzH5LZlmAZ3DEq4afLCQjdkW5RZ4Ug4m8v5vs8o9X2fUhYEfjaTcUKhyljsyLsHZkyfXhSrTCQSFVWV5WVFSspw2B1/x9fhUiqVzWVzuaxSyrLt4qIi27KCIFCKVNRUTpnY2FhYEyssZ4wxQgsKCkZG47W11ZOnNjJFpJIG40xJKfXZW0ooJZQSRcY+LcU5V4QwSvS6U8b1UVODjV2W4vr3CaalJ/lN3d7AOed8xqx5nHP88gGA9z2k4rkfAP4XpBRdZ04PDg22tZ083NJ6dnC0q+vs3rd21JYVTp42o7qu8Z3mw2+9sUUX4jhns2dMnTJ1qm48DYTQqXTsoV+jhBBKmd4HoKfLpZJEESElkbKwuGhgOJEY6Lvpqks/8alPWUWx/r4+In3HdZVUZn5zvEGJopRJKUQQDA0Odp46GU8khe8l0pn46GgikUin01lfpDM5xphhWiHXjUbDBZHIlZdd+OHrP84NUwTByMhgMj7a2tr65JNPNx9pqaiqtAye83zf9zzPD4Igm80Gvp9KZTLZrGEYl116cdh1GeeWZRmcGw63mKWvgHJucJtzyg1mUE4IJSblhFCmcxulPX2DvUPx06c7BgcHpZREESECKWVjY2OsuOC5pUtd17319s/nchmmglQu09t1dmBgoK6uzrJtKaWUkiglpUilUplMhhASiUQn1NW6ts0No6GhviAaJmS8AZhIJYkkiioiiGKSKMIU1WsNdOTVJ6SkkHSsLq1/cAyDU0I5o/pgFOP6fKvJOTdNgxCiH/hNblBKdBG1pDQ2cdI0FFAB4INg6v/rAQD4HzDGayc0xmKVhYWFE2prTp/u2HvwcCY+6IpsZqTfr6otKS4qKCyIRKOZdCYIvGMnTs2aMzsIAimoXmyUX+pJ6HuqqoZSQt/aVIpQSgxm6IZIyVginuDSmzJt6paDxx958lPfuPMz37n7+wMe62g7VhwNUcrz81iKCD/t+cHh5uaNGzaNpNJuJFo1oaEgEq6YPGdSYWFxQbSkuIAyM+oYtmMP9vfv2r07UF5r6/HKsp1T511gOeHSssqiopIXV658863dc+fO8byclIQQovSJJiE4pVkhAyEopVOmTg6HXdOyOWO2Zdq2rZfY27bDLW6Y3CAG54wYxFCcUKabZk2DCSU45fW1FaUlxcLzCouKT544LomyLDtAdtPoAAAgAElEQVSTSRUVFcZHR4QQilJucO5Rzk2XKMJoT29fe3vnJZdeWBCN5nJCKel7nud5Igjy0/SMS8KmTpoUdm1Kqf5mE6kIpUxRfXtWEWVQQ0ghz/0+geg6KiGE5nt7KSFEHw3Tdej8Sn7D5JxxbuY3TunNU5xahsGY7gfmJaWxhsYpSKgA8MHBcz8A/K9RSg3TLC4ujZVXhEJOZXlpfW11cXl5fWOj5wchx5k657xQpNC0nFA4SolqrKtl3JBCsPyxVEro+Lu/jjJ629H4PBBRSunT8PpfRznPZLOOySZNndF84vSKZcvCKnvBwvPNSFEinpQyMAyulMqkM3v37V/z0sul5eW33f65RR9edOzdA1x4V1952dRJDbGSgsJopCjqOo7t5TI7d2wbHYl3tJ2KuO7AyOhoX1e0sCCXSY0M9v/mN7+rmVBLqfJ8nzMWCF8IoaeRgsAP/CCTzVZUxKZPmWzZjmWajm05jm1ZluM4pmtblunYtmM6hsVNwzL0NJFpmJwZnFHGDMZ1H6rrWLHS4sAPIgUFvlDJRNwJuRXlse4znWc6O6vr6hobGqkKlBLpTLb7zJmkl4nOLcs5QcLOFTI3yPqBENlsVq/6j0SiRUWFkydPLIi6782eUgn9gq/7BDilfhDo0Sj9GStCxi7aEl1P1XdZub53qrfxG6ahe205N03T1Bv89YM/56apy6tGfePkyqoawzDxywQAPqiEOnbRBADgf8uy7ClTZpSUlFVVVaWSyXQu+Lsf/iQSMuvq6qdPamiorzvd0XmGG91ne8pisf7BoUNN7y44b3ZJWbkfBJTSIAjIe97988v+laL0XBmOMapzlVJUKZVOJcKOWVY38/FVGx/+w9N/f9fXPvKJW7uHU4nRIds2Dx0+svblVwzT/NJXv1hSVLJt+46DR1pTiVGm1Oe+/EXKTUKEkIIzdrTlaBCoM52dZZVVwrDj6ezew60FZRVtx44eamqSjBmG4fk+kUIpQ7e8KkIqKyuDIDh+/EQ0Ep43d07IdUOOY3LOQkbIDBmcGxHbUoZpcNM0Kef6vpROfEopxhihjCilt+Tr72U04s6fO6PrbL9BlBtyBgcHGSX9/f2EsrraCalk3DJYEPiJZLw3PVS6qPaj5y0yudGZ6EqMpmLxwq6T3XoQjZtmJBKdPG1iYTg89mESpZRQghMeUMEkJbreTAilVA/zS6LY2LO+IoRSxmj+cBXjnFHKGGWcW6ZJKDM4Z/nrUYxybupzUozqGMsYmz5zrhuOooYKAB94TkUlFQD+JVw3XFYWKygs4rbbOzKayuReWbdOpEb1IfjSWGxwNNnWerynp2dgcMiXVCrl2qZp2vqCETm3Ll6PT5H/PraysZIqpZQRQhhlqVQyVlp0vL2jrbv/ZMvhCWXRKVOnDcbTy5Yvd2z79s/d1lBXf/xYa2lJ0eWXXzYyMtrb11dVXV1eXq5PehJC4om4ULIgWjCjsW5CTXUilRwcHGxvazvZ0bX7YHNJaUkghJIy5+Uo50IEvh+k05nLL1p4oq09kUzNnDm9PFZmOYZjOZZth2zHCjmhcMhmpmVZpmXZtmPqyqNpGpwZpm0YpmkYjJv66Zwzrs93Mc6JFAVRt7yigihFucE5H00kcrnclGnTGGNKieH46NGBtvKFtR+bv2hKQX3MKqyIxGIFRRXlserq2sJoUWlZaePEyfNmzyiMhPXiA6ryqwyIIpRQRhglRCoiCcmPmuU/a0LyC6Yoo4wzHVkpZ8zUY1Kcm6aZ3zBlmnrplKbrqnrOnxvGzNnzQ24ECRUAPvCEisEpAPjXUkq9+sb25avWHD/aUh01397fpJS0Xbe6qrpqQv3Z3v72kyfmzZ5phdzR0cRQ75lZs2cLIYJAyHxtcWzGZyy86nLj2BeO/2ukXmfVeuJUdXV1tKCQUlrm8kUfvrKzZ2DqpIbps+d42ezeffvTw0ORkP36ljd6RuLfueu7UyZP0o/sQhKT0/7e3p7ursHBod7eXk+IlubDJRXlx1pai8vKlFK+7/u+n0qnbcvyvFwumystixVEQ/v2vlNWHltw/nzHti3TtB3bcCzHsizTME1HHwI19Zu4YYxla50Hxy5FUSaFkFLPkBE9JabG9se2d/UfbW2NFhR2dp4xTdOgQTwRP0XPzj9v9oLaeaVmhKpzO/eVlIoQpYfz6bnqqRo7qMAokVLpj09PrTFChF6JSqg69zsBohThjBLKOCO64msanFGq3/f1KVdD96Fyzrm+dMr1n1VU1lbVTDBNC78EAOCPAHtSAeBfjVI6ubHhuquvGsl6oxlfUT6tNmYaRnv76TNnuubNml41ocF1w0oGvpSnTp6cUFujCLEsU7+m6y1UerfSeHLSe6soJYRwQqQeOtd/tbCgoH9gsLenu7CwIC34seMnLpw9dUJ9XV9Pr2kamZx/qPXkH55ZdvxU+6xZs6+99iO27UgpDcMgStq2XVRU1NN95tlnl51q7+CUzZg7r7WlJVJYxCiTUkghAiG8XI4bXG99uvryizs7u8729s2eObM8FnMc27RM2wmFbce2bccOOY5t67ZU07Qsi48zDM4NZhiUMaZfyBnVf0Qp1bmZUmoaBlGqtCg6ZVLjhKoKzllPX69pmA3zJ8ybOWNGbFqpFaVKUV18HW8e1dv2GVNKUcakUlQpxg2iRH4zrW7vJYSPBVNKqSLnCth6PRfnjBLGOTUMgzGmT3nphMoNkxuGaXDDyJ+RsvJLpvIz/tNmzkWHGAD80aCSCgD/T4ZGRh9+fEnLoYM9Z7unV5U0nzjFCJ01d24g6fDwcDydaT54YNGVHwqCQCppGIbBeRCIQAQ6lUqpxt+NlSKMjddT1Vh5NV96zPmir7eHKFJeWWk7oYrC8GUXzp8yc1Y8laurrRpOZl/ZuOHCBQsnNtSlkolsJjMaj2dSqVw6pbzssVOdb+7Zn0mlZk+f+m7zkfKamkg4IoQfCCUCP5PNJpPJUCiUy+V83wuZ1tm+/poJtRcuON9xbMMxTdOKOCHTNE3Lsi3bNE09RcTyg+/5S6J6Tp685ztAFNELuZRSQkqilFJKinPbZIWUhNChkTg3zEjIyoiMwxwphRr7XpNzG/il/rzOtfTqVlS97UtH/rGNX1JKzqjIT/yP91owznUfBWUsH1LzY/uMsXN9qNw0OWPc5IzlD04ZlNLzFlysT1IBAPxx4CwqALwPhuOJ9Zs2b3p1U3dnR8xh8VSK2SHHjWZy3oF9e6+9elHO8/MJShHGGaNUERIEIh+3xm/Jj63+l0qS9/Sw6sZLqaQQYmh4xMt5xSXFJSVlNJe8+cbrGhoaLNc9dOTYwf37BkfiA729yUwm8LyevsGRRLKstDgeT2RzuSAQtm1feulF0UhESCmCwA+ECPxEIu75vmWamWwuk05nc15VZeUVl19iWbYVtkPcsmwrFHJM0zZNwzItbuQrj/oRXD/yM6bTqb6wpZQiihK95TT/LK+IlEKK/BJZmT+Uml9fqqTMT5bpK6V6gb+UuqlUZ00pJdU5N/8VlT5zSsa+RCrFKNUHAHS3hD5KS/WclO721TcMlNLFUr21X+/k11VVHVWNsfjNDWPy1JmFhcX4SQ4ACKkA8Oeq42zPI394qrOjo/3UycKQ6ThO1pdNB/ZfteiyIBBS5ouC+QBKqGWZfhAEUhBJdH+qUoRSriOZUoQxRsZqipSysXF5JaXqGRhOjgzGYqWFRcXVVdXtrUcHBwdOd/dlcjklVaSgYNa886OFBcUlZaWxsoKw+/gjDydGh+fMnlVfP0EIEQQyEIHn+cLLjSQSSgpuGLlsLpvJKEVuuOG6wrIi0zDDlmPalmXmN0+ZpmXqsSgd6xgllHLOiKKUMyUl41wpRfMlYialVGMhVREipJRCSBEoqSilUskgEDqGKikpY8L31XuOlwaB4IwGUnJKAqkMRoVUY3+DEEJQSnVdVgSBzvS6XssoEZJQmt/4NXbrVO+bIpZpEaI45wbjzLI4Y4Zh6HYC0zQZpYbBTdMklHLG5px3AZpQAQAhFQD+7ClFOrq6nlr2Qtuxlmwyns1lT7e3z509Q0o1VgukUklCGCFSKaUrkkEQ5OOnUpxxQqkQQg+vjxUaBWWcEEUpU0qv9Fd60z4hhCpVUVHRNzTyblPT8OBAKBS662/vqaqsGE6mU4nEpEmTbIM988yz776z7/LLL1My8APh+0Hg+0HgeZ4/NDRsGEwRGvi+7/tXLrqyprrKNEzLMh3Hsm3Hth3LsgzTtEzDNM2xKipljJVXVAeBH40W2I6Ty2YppSE3LIQYGR7qH+gNu+FkKknGc6qSQkglZfCe8Krf6KWS+iNS+qiA/jBFfg+/kkIRSpQUUnFdK1UyyH99Qcae/vU/kxIipGTnOlOZrqNyvbyWUs4NyzAoY5SxsZqwfvDnRv4aKi8tKauurQ+5YfyUBgCEVAD4/8qxk+33/+af+np7aqorpZdNxkcIIYToQXWlpCJjK6gUJSY3DM48L9DLqiilQsjxjlX94i1l/i+9997quWduQnzfL4mVDyfSxw4fuvHjN7vRwmhBYW1NVXVF7MSxln/81a8uufgi0zCEFL4vcrmsfuvP5rK9vf1hN0QozWYyM2fOWLhgATOpbdim7biObVu2ZZuObXNDJ1T9JM4qKqsrKmv+z1VGpVQQ+Llcrrena2hoQBc+pRRCSKKU5/tKz4flx/SJ/vJ8iXSsaCyVYrp/QASCUCJlICUlxJfKYNQLBMm3q4r8jQT9t1Cq065O0/m3fm4YlDLDYIZBKeXnQiobS95Md6FOnzEnHCnAT2MAQEgFgP8PSanS2UwqlfjnRx8/efQQGXu41zc81Vh75fh0lGkYlLEgCPTNJKLyjQFEjS1fOrf9X1FKpVT6/VpKXUSUepjd84NMJjNp8pSZc+dNndjQ1dG+aePGcCTiuiHf94NA5DzP93zP9wPfy+WyXd29RYVRKaXjODd9/EbXtS3Dti3bcRzHsS3bsS3TtkzDMLlhlFdUlZXFwv/KVfb6O55KJYcG+nzfGxrqV1IJIfS3WeZ7V4metMp/LlIRQvTXkYpQJYNAUEoDIchYB2v+9iyRlDIpgrFOVUUpVVISxohSlDGDMUJZfrrfMDnnjHO9Z0CXhDljhsEpYwY3yiuqsWcKABBSAeAvQiKZXLJsxf69b3upuJ49J2NFUMr03fn85lSppN6IpAjx/UAvGVXnjlWRsSNKY4urCGH5Qfn8/0iZf/vOZLK9PT3JeJxy45KLL4hEwkEgfM/z/MD3vZzn+Z7neV4mm+0521NcXMQYveb666rLy/PHTkMhy7JDrmtbhn76Ly6NTZw4VbfJ/j/KZFKelztx7Ih6b5vtmOA9f6ykrq1KKSWRQigipVBSiXNlZKln/tXYMlVdeR6/dKVnpRijlOkYqhef5gusBtPTUvkp/qkz5oRxSgoAEFIB4C9Kz8DQH5Y80/LuOyTIyfxqe0n17DqjOpLpI0lCCMu0LMvMZLNMqUApIqUkdLxLdaw5VRFCCGNESUYNpQQhVMhgfELL8zzOqGU75WUlhBDf972cl/N83/c8z8t6OS/nZbPZoYFBN+xeffXVjRMnOHbIsW3bdsJh1zQtx3Fs0ygrr6hvmPRBFBf7ersTifjw8CAhRAmh9Ku90v27KhBSKqmEpJQQIQKppJRUSV/mY60UQimpVyXkB/qlJIQwSqRSXF9n1e/7+UWt+tBpfqsU54wzmt/ajxkpAEBIBYC/WIqQnt6+x5546sSxw8L39KyQDp3j56YUUXq4iiplWhZjzPN9IcTYqiX1nl2qRKdVQsjYl+i9Tvq1XPm+RwgJOU55rEwKmcvlsp7neb7ve7lcNplMSqlSyeTA4PCiKz904cULbMMKh0OO7YRc13Ec27Jsx2lonFReXvXBFRd11I7Hhwf6+4aHBsbWS8kgCPLfZSFkfsRKBVJKIQkhurNVn6HS/xwdzamS42VUvb6fMcYoo4yONZwywzAZpZzR/J9yo7auMfZBfh8BABBSAeDPw9BofMOrm1/ftCGXSekxd0L0DFE+tymlKKF6OEo3AEghvCDIN2u+pzl1/GzV2GHV/LiRVMrzPM6Z64RKS4u9nOf5fjqT1WXUTCadyWQD30skUhPq6z/60etCth1ynHDYdd2w49i2bVuWNX3G7D/mitBMJkUUSSTiZzpP6fVVQorx536hlBKCEEKUDIQaXxkwvjdVEkKU0oVVSinLn6nS91rz9VJKqWFwzvT9Kh6JFkycPB0FVABASAUAOOdoW/uKVS8ebT5IhK/H2yml+bEqvfc/P69O9LUq27Ky2ayQUkql54DGb6tKQhkhjFG9DkBJGQjheR7nPOKGCgsLPS+XyeaymWzge5lcLp1Oe7lcNpudM//8hQvmupZtO07IccKRqOvYjmPbtnPe+Rf+e6U33/eam/YRQqTeBaADqt4eKwUlMtBjVkoGQhG9HjWf0PM3EVj+yBQjhBgGJ5TmD0xRpXtSKaXTZsxx0YEKAAipAAD/MyFly/GTz7+w/OSxo0QGOprq7VQ6req+VUUUIYRRyrlBKfUDX+hOTfLfBSzKGMlfW5WBEEHgc84j4XA0HM5ks9lsLpvNZHK5bCaj/1vX0PChK65wHCMSjoZCjuuG3bAbchzLtmfNmheJRP8dPxldHu08fXKgv0cIoZTSUTXfAyClDuuEKKEf+ikdny/LL+/X9eZ8PKWcM73Sv6CgsKauEQNSAICQCgDwf4+qR1qPP/HU0z1nTjJFZH6BvdRrU8fvM41HMcdxGKWpdGa8J1UpqS8r6a8ghBBSSCG4YYZDITfkpNLpbC6XyWazmXQu56USCcOyPnrTjSWlBa5hhyMRN+S6Ydd13ZDjzPj3TqjvlUzGjx9tLigsHh4a0EdQdVqV+Y9J5tfJEqrG0i0b29bFOSeUcMYJIZxzwti06bMjWIAKAAipAAD/clnP2/fOu+tf2dDR1qp0oVDqNkv1P39lSqllmjqrCSHU+Ow/oYpKJZXn+0IEpmlGXNcwjHQqnfNyqXQ6k8lk0hml5FVXXzWhpsa2LdcNhcNh13VDoZDruucvuOhPrUdTHwUYHhoYHhpIJhPj96vUuc9HN+PqnVyUUN2Tmr+GSimNRKN19ZNxQQoAEFIBAP7tgayp5ejql9aebG0JctnxqEpIfq5KV1Xz91IpNQzD4DyX8/XXkEpRoqSUnufrImLYDUkps9lcJptJpVLpVMrzcldcccXkSRNDju26bsgNRyJhNxSyHWfBwov/xKeIMumUkGJooL+/v0cRPVymCKVKSl0+1Zu8CCFlscqSspjrhhnj+HkFAAipAADvS1QlTUePPfbY4pG+rrEZqnMXqvTsPyH5k1SMMssyc553rslSkayXCwJhWVbItvxA5DLpZDqdSacz6VRlVc01118VMh0n5ITD0bAbikbClu3MmXven9dTuBBicKA3HI6k0ymllO/lyitrcrlsKBTmHMEUABBSAQA+GJls7q19+zesf7m74zRR4txVVTp+/5MRQhRRjm1nc7n8OzchUspMLksUMQzDti0vl0umUplMJpmIW5Z93Q3XVpaXO04o7Lqu6+q1U7PnzEOzJgAAQioAwL+UVOpUx5nnV606fHC/DHyiN9sTkl9ZTwil1DAMKaSUSq/2l1Km0xmplGUapmFkstl0KpVMJilj1117TXmsLBKJ6HwadkOO41x08RXvy71TAABASAWAv7CoKtXru/aseWnN4JnTRApF9I5UfaGeSkocy/I9X++kklKm0mlKCDcMgxvJZCKVSqaSyUsuuXTarCkROxyNRnVCDTnO7LnzUUMFAEBIBQD4t/MD8ebbe9esXtnX3anGTqUSQiiltmkJJXUzgJQqnUkrqfRtpZHRkVQiEYuVXXfdteFwOBKJFBQUhEJOrKx82vSZuLcEAICQCgDwPsjkvDWbNm/esDY1MiyVHJ+msi3LNIxAiCAQiVQyvyxUiMHhId/zP/axG2uqq6LRqJ7md93Qwgsuw0J7AACEVACA99NoIvnsyhff2fN2fKSfEiqlZJQRSmzLUkrFE0mppJIy8IOR+Mjll142deqU4qKiSCTsuqG6usb6holIqAAACKkAAB8IPwi27Ny1+dVNne2nGJF6WVU2m/NzWSEVJcrz/RkzZixcuKCosKCgoMB13Tlz57tYaw8AgJAKAPBBk0rt2HPgyScfyybjTJF0JpvzPCWEVNJ13Vtu+WQsVhZ23alTplVUVuPjAgBASAUA+ONJpjNv7Nz16qaNnaeOe54XBMIJhT56ww0XLjy/qqq6vLwSe6YAABBSAQD+fUgpW0+2x+OjlmlOmzI55Dj4TAAAEFIBAAAAAN6HkIrHLwAAAAD4k4OQCgAAAAAIqQAAAAAACKkAAAAAgJAKAAAAAICQCgAAAAAIqQAAAAAACKkAAAAAgJAKAAAAAICQCgAAAACAkAoAAAAACKkAAAAAAAipAAAAAICQCgAAAACAkAoAAAAACKkAAAAAAAipAAAAAICQCgAAAACAkAoAAAAAgJAKAAAAAAipAAAAAAAIqQAAAACAkAoAAAAAgJAKAAAAAAipAAAAAAAIqQAAAAAACKkAAAAAgJAKAAAAAICQCgAAAAAIqQAAAAAACKkAAAAAgJAKAAAAAICQCgAAAAAIqQAAAAAACKkAAAAAAAipAAAAAICQCgAAAACAkAoAAAAACKkAAAAAAAipAAAAAICQCgAAAACAkAoAAAAAgJAKAAAAAAipAAAAAAAIqQAAAACAkAoAAAAAgJAKAAAAAAipAAAAAAAIqQAAAACAkAoAAAAAgJAKAAAAAICQCgAAAAAIqQAAAAAACKkAAAAAgJAKAAAAAICQCgAAAAB/QYw/l29oJpu9/vYv4AcM4M/LttUv4EMAAIB/A+p5Hj4FAAAAAPjTYZomnvsBAAAA4E8OQioAAAAAIKQCAAAAACCkAgAAAABCKgAAAAAAQioAAAAAIKQCAAAAACCkAgAAAABCKgAAAAAAQioAAAAAAEIqAAAAACCkAgAAAAAgpAIAAAAAQioAAAAAAEIqAAAAACCkAgAAAAAgpAIAAAAAQioAAAAAAEIqAAAAAABCKgAAAAAgpAIAAAAAIKQCAAAAAEIqAAAAAABCKgAAAAAgpAIAAAAAIKQCAAAAACCkAgAAAABCKgAAAAAAQioAAAAAIKQCAAAAACCkAgAAAABCKgAAAAAAQioAAAAAIKQCAAAAAPxJMUb/ofFP51vTf80f8EMCAAAA8BduxiXX8z+8kfzFG/FfvxF330jctGi9e+/f3vyhjaH7vnfLFa/Z9//NrZdtsR747m2XbjMe/M4dF+/gD33rzot20Yf/+ssX7CGPfuNrC/fLxX/1jfMPiie+9q35h/wlX/3uvCPe0i9/b+6x7LIvfX/2icyKO38w61Rq1Rd+NKMjueaOn0zviq/73M+m9oxuuO0XU/qHN332l5OGhjbf+quJowNbP/3rhmTqSePRYHnyab7YXxl/lj6RWz36PFmSXTv8glyaXj/0oliW2jjwkr8i8Vr/y96q+JbeV7JrRrb1vJpZN7yj+/XUhsFdXW8kNw3s6Xwzvrlvf8dbo1t7D7a/Pbz97KFT+4Z2dh9pe2dg95ljJ97t39t5ovVw74HTp44d7Wlq72g53t18suvIya6Wtp7m052tx/sPneloax1qOtvefnT0YN+pzpbkgcG27sOZ/SMnepu9vYnWgXfFnvSx4SayO9cSf4fvCo6kDlg7VXN2X2gHO+TvjWw3m+Tbhducg3R3ydbwAeOt2JaC/fbOys3Fe903a14r2xPdXrepYnfRG40bq3eVbp28YcLO8tenrW/YUbV55rpJ22tfnbN26rb6TeetmbF14isLVs/eMmXDhavmbZ7+8iUrz39t1rrLV1ywae5LVy6/eOP8NVctu2zDwhevee5D6y9adf3SD6+79IUbn/nI2itWfHzJdWsWPf/Jpz66+upln37iY6uuffazj39i5Q1LP7f4UytuevoLj31m+c1LvvTo7ctuefKrj3z+uVuf/KvyL065bcI3Y1+ZfEftt0u/PvHO6rtKvtn45aq7i75d/7WKewrvqvtG+Q+jd9d+q+zHkXtqvlv6U/eHVd8r/nnox5XfL7rX/mn5Dwrus34e+1H0fuPe0p+EH+D3lfzMfZDeX/QL5yHyQOEv7Yflg9FfmY+KhyK/Nhb7D7u/ZU94j4Z+R5dkF9u/V0szT1iPyGWpJcZjwYrkUv64vyq+jD6VWzO6gjyTXTe8Sj6X3jC0RixPbRpY569MbO7f4K2Ob+3dlF07sr1nc2b98M7uramNg7u7tidfG9jbuTO+pe9Ax+7Rbb1N7XuHd5xtPnVgaFd3S1vTwJ4zrSea+/d3trW29B483X6stedQe2dLW/eRk91H2ruOtfU2d3aeOD5wqLvjVOtwU297x9H4wYFTXS2pA8NtPYez++Mn+pv9vanWoXflnuyx0Sa6229JvmPskkcyB+ydtNnb5+4wDom90e12E3m7aJt7kO8u3Ro9YL1VvqVof2hn1ebSvZE3a18r31O4vX5T1e6SNyZurN0V2zplQ/3Oytenr5+4o2bzrHVTtte9Onft9G2Nm+avmbV18isLV8/dMm3DRavmb5758qUrF742Z90VKy7adN5Li5ZfunHBmquXXbHhwhevfW7R+ktW3bD06nWXv3DTM9euvXLFzUtuWHPV87c8ddPqa5bd+sTNq65/9rbHb1l549I7Ft+64uNP3/nYbcs/ueTLj96x7NNPfu3RO6d9pv4b5V+acvuEb8W+Ovnztd8t/auJX6z+XslfN36l6vtF36n/esUPCv+m7pvlP4r+be23y34S+buau0p/5v6HqruLfxH6+8p7in5p/8fyHxb8yvpPsR9Hf23859Kfhn/L/6Hk5+7v6D8W3ev8nvym8D77EflP0fvNx8Q/Rx4wHvf/i/sge8r7r56ROzsAAAaqSURBVKGH6DPZP9gPq+cyT1qPyuWpp43Fwcrks/wJf3X8ebokt3b0BbI0u374RbksvXHoJbEi9drAy/6qxJb+V7w18W29r2bXjezoeT2zYXhX9xupTYN7ut5Mbh7Y3/lWfGvfwY63R7f3HmrfN7zz7JFT7wzt7j7W9u7A3jMnThzuP9B5qvVob9PpjmPHe5rbu1pOdrec7Dlyuqu1rb/5TGfb8aFDZzvaW0eb+to7jyYPDp7qbskcGGnrPeztT5wYaBZ7063D75I9uWPxJr47aEm9Y+1SR7IHQjtZs78vssM8JPcWbnea6Nsl28IHjd2xrQUH7LcqtxTvd3fWbC7bG32z7rWKPUXbGzdV7y59Y/LGCbvKt07b0LCz6vWZ6yftqN08Z93U7fWvnrd2xraJmxasmb11yisXrp63ZfqGS1adv3nWy5evvOC1ueuuXHHxpvkvXbX8so0L11yz7EMbLnrx+uc+vP7SVTcu/ci6K174+DPXrV204pNLPrrm6uc//dTHVl+77LNPfGLVDc9+7vFPrbxp6RcWf2bFzU9/6bHbl9+y5KuPfv75Wxu+XvnFabfVf7P8K1PumPDt2Ncn31l7V+k3J365+u6Sbzd+reqeorvqv1Hxw8K7675V/uPoPbXfLftp5Ic13yv9ufvjqu8X3xv6aeUPiu6zf17+o4L7rXtjP4k+YNxX+rPwg/z+kl+4D9EHin7pPEweLPyV/ah8KPprc7F4OPJb4wn/Ufd3bIm3OPR7ujT7hP2IWpZZYj0mV6SWGo8Hq5LL+FP+mvgK+kxu3egq8lx2w/AauTy9aWidWJnaPLDBX53Y2r/JWxvf3rs5u35kZ8/WzMbh3d3bU68N7u3amdwycKBzd3xbX1PH3tEdvc3tB4Z3nW051TS0p7u1rXlg/5m2Ey39BzvbW1t7D53uPNbWc6S9u6W9+9jJ3iOdXSfaBpq7O08dHz7U29HRGm8aaO86mjo4fKqnJXsg3tZ/2N+fOjHULPdmW0ffpXv8Y8kmY7dsybxj76JHvAPuTqNZ7IvusA+RvUXb3Sb+dum26EFrd/nWogOht6q2lO6P7KzdXL638M3616r2lGyfuKl2d+yNKRvrd1Vunb5h4s6a12etn7KjbvPcddO3N746f+2sbZM3LVwzd+u0Vy5aPX/LzA2Xrlq4ec7LV6y86LXz1i1acemmBS9dvfyKjReuuXbZog2XvHjDc1evv3zVTUuvXXflCzc/c8Paq1bcsuSmNdc8f+tTN6++ftltT9yy6sZn73j81pUfX3rn4ttWfPLpLz92x/JPP/21qi9M/0zDNyq/NO32+m+Vf3XK5yd8N/ZXk79Y+73Sv574lervl3yn8etVPyj6m/pvVvyo8G/rvl3+k+jf1d5V9rPIf6i5u/QX7t9X3VP8y9B/rPxh0a/s/1T+44JfW/859tPob41/KP15+Hf8H0vudX9Pf1N0n/MI+afC++3H5D9HHzAfF/8l8qDxlP9f3YfYM94fQg/T57JP2o+q5ZmnrcVyZepZ44lgdfJ5vsRfG3+BLs2tH32RLMtuHH5Jrki/NvSyWJXaMvCKvyaxrf9Vb118R+/r2Q0ju3reyGwa3tP9Zmrz4P6ut5JbBw52vh3f3neoY9/ozt4j7e8M7z577NS7Q3u7T7QdHjhw5tSJo/1NnR2tx3ubT3cdO9nT0t7Tcrq79WT/kTNdbW1DzWc724+PHurr6GxNNg22dx/NHBw51dviHUi0DRwW+9MnhpvJ3lxr/F2+JziWarJ2q5bsO6Fd7Ih/ILLTbJb7Cnc4h+jeku3hJuPt2LaCg/buyq3FB9y3araU7Y/urNtcsbfozcbXqveUbp+8acLu8jembWzYVbV15oZJO2tfn7N+6o76zeetm7F94qsL1s7eNmXThWvmbZ3+yiWrz98ya8Plqy7YPPflK1de/Nr8dVetuGzTwpeuWf6hjRetuX7Zhzdc+uKNz31k/RWrPr70unWLXvjkMx9de/WKTy/52Jprn//sU59YfcOyzz3xqVU3PfuFxz+z8ualX1p8+4pbnv7q4s/PvHXi16u+OP22hm9WfmXaHfXfLv/6lDsn3BX75uQv195d+u2JX6u+p+Suxm9U/bDo7vpvVfy48J6675b/NPrD2u+V/Tzy45rvl97r/rTqB8X3hX5e+aOi++17y39S8IB1X+xn0QeN+0t/EX6IP1DyS/dh+mDRr5xHyUOFv7YXy4ejvzWfEI9Gfmcs8Re7v2dLvSdCj9Bl2SX2Y2pFZqn1uFx1+h/b/xv63bhawvFNpQAAAABJRU5ErkJggg=="/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">A<span class="_ _8"> </span>Firmwa<span class="_ _5"></span>re<span class="_ _7"> </span>Bug</div><div class="t m0 x7 hb y21 ff9 fs7 fc0 sc0 ls0 ws0">“Certain<span class="_ _f"> </span>SSDs<span class="_ _f"> </span>have<span class="_ _f"> </span>a<span class="_ _f"> </span>firmwa<span class="_ _5"></span>re<span class="_ _f"> </span>bug<span class="_ _f"> </span>causing<span class="_ _f"> </span>them<span class="_ _f"> </span>to<span class="_ _f"> </span>irrecoverably<span class="_ _f"> </span>fail<span class="_ _f"> </span>after</div><div class="t m0 x7 hb y22 ff9 fs7 fc0 sc0 ls0 ws0">exactly<span class="_ _a"> </span>32,768<span class="_ _f"> </span>hours<span class="_ _a"> </span>of<span class="_ _f"> </span>op<span class="_ _c"></span>eration.<span class="_ _11"> </span>SSDs<span class="_ _a"> </span>that<span class="_ _f"> </span>w<span class="_ _5"></span>ere<span class="_ _a"> </span>put<span class="_ _f"> </span>into<span class="_ _a"> </span>service<span class="_ _f"> </span>at<span class="_ _a"> </span>the</div><div class="t m0 x7 hb y23 ff9 fs7 fc0 sc0 ls0 ws0">same<span class="_ _e"> </span>time<span class="_ _e"> </span>will<span class="_ _e"> </span>fail<span class="_ _e"> </span>simultaneously<span class="_ _6"></span>,<span class="_ _e"> </span>so<span class="_ _e"> </span>RAID<span class="_ _e"> </span>won’t<span class="_ _d"> </span>help”</div><div class="t m0 x1 hc y24 ffa fs4 fc0 sc0 ls0 ws0">HPE<span class="_ _a"> </span>SAS<span class="_ _4"> </span>Solid<span class="_ _a"> </span>State<span class="_ _a"> </span>Drives<span class="_ _4"> </span>-<span class="_ _a"> </span>Critical<span class="_ _4"> </span>Firmware<span class="_ _a"> </span>Upgrade</div><div class="t m0 xb hd y25 ffb fs8 fc3 sc0 ls0 ws0">Via<span class="_ _d"> </span><span class="ffc">twitter.com/martinkl/status/1202235877520482306?s=19</span></div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">4/77</div><a class="l" href="https://support.hpe.com/hpsc/doc/public/display?docId=emr_na-a00092491en_us"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:146.167000px;width:284.433000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://twitter.com/martinkl/status/1202235877520482306?s=19"><div class="d m1" style="border-style:none;position:absolute;left:50.580000px;bottom:3.064000px;width:246.774000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Overflo<span class="_ _5"></span>w<span class="_ _8"> </span>Implementations</div><div class="t m0 x1 h6 y26 ff4 fs4 fc0 sc0 ls0 ws0">Note:<span class="_ _8"> </span>Computing<span class="_ _d"> </span>the<span class="_ _d"> </span>average<span class="_ _d"> </span>in<span class="_ _d"> </span>the<span class="_ _d"> </span>right<span class="_ _d"> </span>wa<span class="_ _5"></span>y<span class="_ _d"> </span>is<span class="_ _d"> </span>not<span class="_ _d"> </span>trivial,<span class="_ _d"> </span>see<span class="_ _d"> </span><span class="ffa">On<span class="_ _a"> </span>finding<span class="_ _4"> </span>the<span class="_ _a"> </span>average</span></div><div class="t m0 x1 hc y27 ffa fs4 fc0 sc0 ls0 ws0">of<span class="_ _a"> </span>two<span class="_ _4"> </span>unsigned<span class="_ _a"> </span>integers<span class="_ _a"> </span>without<span class="_ _4"> </span>overflow</div><div class="t m0 x1 h6 y28 ff4 fs4 fc0 sc0 ls0 ws0">related<span class="_ _d"> </span>op<span class="_ _c"></span>erations:<span class="_ _8"> </span>ceiling<span class="_ _d"> </span>division,<span class="_ _d"> </span>rounding<span class="_ _d"> </span>division</div><div class="t m0 xb he y29 ffc fs8 fc3 sc0 ls0 ws0">ai.googleblog.com/2006/06/extra-extra-read-all-about-it-nearly.html</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">5/77</div><a class="l" href="https://devblogs.microsoft.com/oldnewthing/20220207-00/?p=106223"><div class="d m1" style="border-style:none;position:absolute;left:296.119000px;bottom:53.751000px;width:130.074000px;height:11.125000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://devblogs.microsoft.com/oldnewthing/20220207-00/?p=106223"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:40.003000px;width:221.668000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://ai.googleblog.com/2006/06/extra-extra-read-all-about-it-nearly.html"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:-0.338000px;width:317.385000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">P<span class="_ _5"></span>otentially<span class="_ _8"> </span>Catastrophic<span class="_ _f"> </span>F<span class="_ _5"></span>ailure</div><div class="t m0 xa hb y2a ff4 fs7 fc0 sc0 ls0 ws0">51<span class="_ _12"> </span><span class="ff9">da<span class="_ _5"></span>ys<span class="_ _7"> </span><span class="ff4">=<span class="_ _12"> </span>51<span class="_"> </span><span class="ff7">·<span class="_ _13"></span></span>24<span class="_"> </span><span class="ff7">·<span class="_ _13"></span></span>60<span class="_"> </span><span class="ff7">·<span class="_ _13"></span></span>60<span class="_"> </span><span class="ff7">·<span class="_ _13"></span></span>1000<span class="_ _12"> </span>=<span class="_ _12"> </span>4<span class="_ _14"> </span>406<span class="_ _14"> </span>400<span class="_ _14"> </span>000<span class="_ _12"> </span></span>ms</span></div><div class="t m0 xb he y2b ffc fs8 fc3 sc0 ls0 ws0">Boeing<span class="_ _f"> </span>787s<span class="_ _f"> </span>must<span class="_ _a"> </span>be<span class="_ _f"> </span>turned<span class="_ _f"> </span>off<span class="_ _f"> </span>and<span class="_ _a"> </span>on<span class="_ _f"> </span>every<span class="_ _f"> </span>51<span class="_ _f"> </span>days<span class="_ _a"> </span>to<span class="_ _8"> </span>prevent<span class="_ _a"> </span>‘misleading<span class="_ _f"> </span>data’</div><div class="t m0 x1 he y2c ffc fs8 fc3 sc0 ls0 ws0">being<span class="_ _f"> </span>shown<span class="_ _f"> </span>to<span class="_ _a"> </span>pilots</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">6/77</div><a class="l" href="https://www.theregister.co.uk/2020/04/02/boeing_787_power_cycle_51_days_stale_data/"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:17.174000px;width:391.471000px;height:11.656000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://www.theregister.co.uk/2020/04/02/boeing_787_power_cycle_51_days_stale_data/"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:2.783000px;width:100.847000px;height:11.154000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">C++<span class="_ _8"> </span>Data<span class="_ _f"> </span>Mo<span class="_ _c"></span>del</div><div class="t m0 xc hb y2d ff1 fs7 fc0 sc0 ls0 ws0">Mo<span class="_ _c"></span>del/Bits<span class="_ _15"> </span>OS<span class="_ _16"> </span><span class="ff5">short<span class="_ _17"> </span>int<span class="_ _17"> </span>long<span class="_ _17"> </span>long<span class="_ _18"> </span>long<span class="_ _17"> </span>pointer</span></div><div class="t m0 xb hb y2e ffa fs7 fc0 sc0 ls0 ws0">ILP32<span class="_ _19"> </span><span class="ff4">Windo<span class="_ _5"></span>ws/Unix<span class="_ _e"> </span>32-bi<span class="fc5 sc0">t</span><span class="_ _1a"> </span>16<span class="_ _1b"> </span>32<span class="_ _1c"> </span>32<span class="_ _16"> </span>64<span class="_ _1d"> </span>32</span></div><div class="t m0 xb hb y2f ff5 fs7 fc4 sc0 ls0 ws0">LLP64<span class="_ _19"> </span><span class="ff4 fc0">Windo<span class="_ _5"></span>ws<span class="_ _e"> </span>64-bit<span class="_ _1e"> </span>16<span class="_ _1b"> </span>32<span class="_ _1c"> </span>32<span class="_ _16"> </span>64<span class="_ _1d"> </span>64</span></div><div class="t m0 xd hb y30 ff5 fs7 fc4 sc0 ls0 ws0">LP64<span class="_ _1f"> </span><span class="ff4 fc0">Linux<span class="_ _e"> </span>64-bit<span class="_ _20"> </span>16<span class="_ _1b"> </span>32<span class="_ _1c"> </span>64<span class="_ _16"> </span>64<span class="_ _1d"> </span>64</span></div><div class="t m0 xe hb y31 ffa fs7 fc0 sc0 ls0 ws0">char<span class="_ _21"> </span><span class="ff4">is<span class="_ _e"> </span>alw<span class="_ _5"></span>a<span class="_ _5"></span>ys<span class="_ _e"> </span>1<span class="_ _e"> </span>byte</span></div><div class="t m0 x1 h6 y32 ff1 fs4 fc0 sc0 ls0 ws0">LP32<span class="_ _d"> </span><span class="ff4">Windo<span class="_ _5"></span>ws<span class="_ _d"> </span>16-bit<span class="_ _d"> </span>APIs<span class="_ _d"> </span>(no<span class="_ _d"> </span>more<span class="_ _12"> </span>used)</span></div><div class="t m0 xb he y33 ffc fs8 fc3 sc0 ls0 ws0">C++<span class="_ _f"> </span>Fundamental<span class="_ _f"> </span>types</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">7/77</div><a class="l" href="https://en.cppreference.com/w/cpp/language/types"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:1.522000px;width:100.847000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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5l/8Ja2TEOmNPtBqmV5NLUoGTg8trQxf9O6cx/7OMm0pqO6hmhw9Llw0y3b9oWGvxrMpOJzF7x389p3CrOXDR8pXNM5mSm/nQnfOP8zky5s23fynQe71kwtqqQHjv6s47Mb7twd6v/x50+sOr04s+yzbaXw2aatpexQCD3pf3vp+K4t26amJoaaWvfkfjQxsftfJ9PfHRo9FmabQ9y155/yqe8OjR4Ps80h3lCdToTZ5hCvr07Ph9nmEN9cnV4Is80hvunsdGQkzHSEeF11Gg0zHSFeW52OhJmOEN9YncbCTEeIb6hOR8NMR4ivr07HwkxHiNdUp+NhpiPEq6vTiTDTEeJvVKfnw0xHiFdVpxfCTEeIrzs7jY2E6c4QX1udRsN0Z4ivqU5HwnRniFdWp7Ew3Rnir1eno2G6M8QrqtOxMN0Z4s7qdDxMd4b46up0Ikx3hviq6vR8mO4M8ZVnp6MnwtSaEC89Ow0fCcV19/VmKpMtswNz2epTng9Ta0K8pDqNhqmbd69PzWbaU2GiYTCbql4fC1Przl6vzxSmmg41VB8YOro8X1x9/6bs6YaDTbUnvxCm1oR48dlp5PmQXH/PpubKwVR9dR1HQ3HdPd3Zif9IV1c2NNKWr3SFuL02tucrXSFuq97heEjW9d2e/vxVR0fDbNefbysVf9TaePbK4bFQWv8XXfUfZQ+2NtTusjhf6Qpxa3U8sjw/d2PfeLa5etexkGzo214ZSKovMzTWli/dunM8W73lyJGQdN2zrXl/MV274ZJ8pSvELbVxab7SFeJc9V0dC8UNfxmHT8rPNNXXnrEsX+kKcXNt7MhXukLcVBsvy1e6QpytjZfnK10hbqyNy/OVrhDX3sxoW77cHeLqnUdOhOS2vs3TA3XVxR8+Fkob7+8+czpqz0wWBxprKxhtz5e7Q7yousYXQvHWXbfur/2rodHF+XJ3iKPqwyOhuCXumcwlYebzsx8eDcXNcc9kLmRmzzn5wydCaWNvTyGU2gfrak89Hop39PbMZicGUtWzHB4LxU07t6UPFutqr7kkX+4OcaZ6lGNhtvv+W+sqmVIyUPuEDB29LF+84/4t6dOTn9U3pJPPFzN09PJ8cWP1kZb64nkfxY588Zv3b0mfTk/WnXt9dGm+3B3i2imOLsuXu0NcXc7IsZB0926faPz32qmNHA3J5r6+J+vnqu/gRCjeuXN9KA3P5Wq36MiXu0NcfYGR0ZD07OgZn3uqqfaJHQnJ1ge29M8uqv2Dy/Ll7hCH2nh5vtwd4kptXJ4vd4e4XPugtuXndoR4bs//AkxUXUDnco8QAAAAAElFTkSuQmCC"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Fixed<span class="_ _8"> </span>Width<span class="_ _f"> </span>Integers<span class="_ _22"> </span>1/3</div><div class="t m0 xe hf y34 ff5 fs7 fc1 sc0 ls0 ws0">int*<span class="_ _7"> </span>t<span class="_ _8"> </span><cstdint></div><div class="t m0 xe hb y35 ff4 fs7 fc0 sc0 ls0 ws0">C++<span class="_ _e"> </span>p<span class="_ _5"></span>rovides<span class="_ _e"> </span>fixed<span class="_ _e"> </span>width<span class="_ _e"> </span>integer<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>es.</div><div class="t m0 xe hb y36 ff4 fs7 fc0 sc0 ls0 ws0">They<span class="_ _e"> </span>have<span class="_ _e"> </span>the<span class="_ _e"> </span>same<span class="_ _e"> </span>size<span class="_ _e"> </span>on<span class="_ _e"> </span>any<span class="_ _e"> </span>a<span class="_ _5"></span>rchitecture:</div><div class="t m0 xe hb y37 ff4 fs7 fc6 sc0 ls0 ws0">int8<span class="_ _7"> </span>t<span class="fc0">,<span class="_ _e"> </span></span>uint8<span class="_ _7"> </span>t</div><div class="t m0 xe hb y38 ff4 fs7 fc6 sc0 ls0 ws0">int16<span class="_ _7"> </span>t<span class="fc0">,<span class="_ _e"> </span></span>uint16<span class="_ _7"> </span>t</div><div class="t m0 xe hb y39 ff4 fs7 fc6 sc0 ls0 ws0">int32<span class="_ _7"> </span>t<span class="fc0">,<span class="_ _e"> </span></span>uint32<span class="_ _7"> </span>t</div><div class="t m0 xe hb y3a ff4 fs7 fc6 sc0 ls0 ws0">int64<span class="_ _7"> </span>t<span class="fc0">,<span class="_ _e"> </span></span>uint64<span class="_ _7"> </span>t</div><div class="t m0 x1 hb y3b ff9 fs7 fc0 sc0 ls0 ws0">Go<span class="_ _c"></span>od<span class="_ _e"> </span>practice<span class="_ _c"></span><span class="ff4">:<span class="_ _a"> </span>Prefer<span class="_ _d"> </span>fixed-width<span class="_ _e"> </span>integers<span class="_ _e"> </span>instead<span class="_ _e"> </span>of<span class="_ _e"> </span>native<span class="_ _e"> </span>types.<span class="_ _3"> </span><span class="ffa">int<span class="_ _21"> </span></span>and</span></div><div class="t m0 xe hb y3c ffa fs7 fc0 sc0 ls0 ws0">unsigned<span class="_ _21"> </span><span class="ff4">can<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _d"> </span>directly<span class="_ _e"> </span>used<span class="_ _e"> </span>as<span class="_ _e"> </span>they<span class="_ _e"> </span>are<span class="_ _d"> </span>widely<span class="_ _e"> </span>accepted<span class="_ _e"> </span>by<span class="_ _d"> </span>C++<span class="_ _e"> </span>data<span class="_ _7"> </span>mo<span class="_ _c"></span>dels</span></div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">8/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Fixed<span class="_ _8"> </span>Width<span class="_ _f"> </span>Integers<span class="_ _22"> </span>2/3</div><div class="t m0 xe hb y3d ffa fs7 fc0 sc0 ls0 ws0">int*<span class="_ _7"> </span>t<span class="_ _21"> </span><span class="ff4">types<span class="_ _e"> </span>are<span class="_ _d"> </span>not<span class="_ _e"> </span>“real”<span class="_ _e"> </span>types,<span class="_ _7"> </span>they<span class="_ _e"> </span>a<span class="_ _5"></span>re<span class="_ _e"> </span>merely<span class="_ _e"> </span><span class="ff9">t<span class="_ _5"></span>yp<span class="_ _c"></span>edefs<span class="_ _8"> </span><span class="ff4">to<span class="_ _e"> </span>approp<span class="_ _5"></span>riate</span></span></span></div><div class="t m0 x1 hb y3e ff4 fs7 fc0 sc0 ls0 ws0">fundamental<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>es</div><div class="t m0 x1 hb y3f ff4 fs7 fc0 sc0 ls0 ws0">C++<span class="_ _e"> </span>standa<span class="_ _5"></span>rd<span class="_ _e"> </span>do<span class="_ _c"></span>es<span class="_ _d"> </span>not<span class="_ _e"> </span>ensure<span class="_ _e"> </span>a<span class="_ _e"> </span>one-to-one<span class="_ _e"> </span>mapping:</div><div class="t m0 xb hb y40 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">There<span class="_ _e"> </span>a<span class="_ _5"></span>re<span class="_ _e"> </span><span class="ff1">five<span class="_ _e"> </span></span>distinct<span class="_ _e"> </span><span class="ff9">fundamental<span class="_ _e"> </span>types<span class="_ _f"> </span></span>(<span class="_ _12"> </span><span class="ffa">char<span class="_ _12"> </span></span>,<span class="_ _21"> </span><span class="ffa">short<span class="_ _12"> </span></span>,<span class="_ _21"> </span><span class="ffa">int<span class="_ _12"> </span></span>,<span class="_ _21"> </span><span class="ffa">long<span class="_ _12"> </span></span>,</span></div><div class="t m0 xf hb y41 ffa fs7 fc0 sc0 ls0 ws0">long<span class="_ _18"> </span>long<span class="_ _12"> </span><span class="ff4">)</span></div><div class="t m0 xb hb y42 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">There<span class="_ _e"> </span>a<span class="_ _5"></span>re<span class="_ _e"> </span><span class="ff1">four<span class="_ _21"> </span><span class="ffa">int*<span class="_ _8"> </span>t<span class="_ _21"> </span><span class="ff9">overloads<span class="_ _f"> </span></span></span></span>(<span class="_ _12"> </span><span class="ffa">int8<span class="_ _7"> </span>t<span class="_ _12"> </span></span>,<span class="_ _21"> </span><span class="ffa">int16<span class="_ _8"> </span>t<span class="_ _12"> </span></span>,<span class="_ _21"> </span><span class="ffa">int32<span class="_ _7"> </span>t<span class="_ _12"> </span></span>,<span class="_ _e"> </span>and</span></div><div class="t m0 xf hb y43 ffa fs7 fc0 sc0 ls0 ws0">int64<span class="_ _7"> </span>t<span class="_ _12"> </span><span class="ff4">)</span></div><div class="t m0 xb he y44 ffc fs8 fc3 sc0 ls0 ws0">ithare.com/c-on-using-int<span class="_ _d"> </span>t-as-overload-and-template-parameters</div><div class="t m0 x8 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">9/77</div><a class="l" href="http://ithare.com/c-on-using-int_t-as-overload-and-template-parameters/"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:2.656000px;width:297.237000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Fixed<span class="_ _8"> </span>Width<span class="_ _f"> </span>Integers<span class="_ _22"> </span>3/3</div><div class="t m0 x1 hb y45 ff4 fs7 fc0 sc0 ls0 ws0">W<span class="_ _5"></span>a<span class="_ _5"></span>rning:<span class="_ _a"> </span>I/O<span class="_ _d"> </span>Stream<span class="_ _e"> </span>interprets<span class="_ _21"> </span><span class="ffa">uint8<span class="_ _7"> </span>t<span class="_ _21"> </span></span>and<span class="_ _21"> </span><span class="ffa">int8<span class="_ _8"> </span>t<span class="_ _21"> </span></span>as<span class="_ _21"> </span><span class="ffa">char<span class="_ _21"> </span></span>and<span class="_ _d"> </span>not<span class="_ _7"> </span>as<span class="_ _e"> </span>integer</div><div class="t m0 x1 hb y46 ff4 fs7 fc0 sc0 ls0 ws0">values</div><div class="t m0 xe he y47 ff5 fs8 fc7 sc0 ls0 ws0">int8_t<span class="_ _f"> </span><span class="ffc fc0">var;</span></div><div class="t m0 xe he y48 ffc fs8 fc0 sc0 ls0 ws0">cin<span class="_ _f"> </span><span class="fc8">>><span class="_ _f"> </span></span>var;<span class="_ _23"> </span><span class="ffe fc9">//<span class="_ _f"> </span>read<span class="_ _f"> </span><span class="fff">'</span>2<span class="fff">'</span></span></div><div class="t m0 xe he y49 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>var;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span><span class="fff">'</span>2<span class="fff">'</span></span></div><div class="t m0 xe he y4a ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">a<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>var<span class="_ _f"> </span><span class="fc8">*<span class="_ _f"> </span>2</span>;</span></div><div class="t m0 xe he y4b ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>a;<span class="_ _24"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span><span class="fff">'</span>100<span class="fff">'<span class="_ _a"> </span></span>!!</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">10/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff5 fs3 fc1 sc0 ls0 ws0">size<span class="_ _f"> </span>t<span class="_ _8"> </span><span class="ff1">and<span class="_ _8"> </span></span>ptrdiff<span class="_ _f"> </span>t</div><div class="t m0 xe hf y4c ff5 fs7 fc1 sc0 ls0 ws0">size<span class="_ _7"> </span>t<span class="_ _8"> </span>ptrdiff<span class="_ _7"> </span>t<span class="_ _8"> </span><cstddef></div><div class="t m0 x6 hb y4d ff5 fs7 fc0 sc0 ls0 ws0">size<span class="_ _7"> </span>t<span class="_ _21"> </span><span class="ff4">and<span class="_ _21"> </span></span>ptrdiff<span class="_ _8"> </span>t<span class="_ _21"> </span><span class="ff4">are<span class="_ _d"> </span><span class="ff9">aliases<span class="_ _f"> </span></span>data<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>es<span class="_ _d"> </span>capable<span class="_ _e"> </span>of<span class="_ _e"> </span>storing<span class="_ _e"> </span>the<span class="_ _e"> </span>biggest</span></div><div class="t m0 xe hb y4e ff4 fs7 fc0 sc0 ls0 ws0">rep<span class="_ _5"></span>resentable<span class="_ _e"> </span>value<span class="_ _e"> </span>on<span class="_ _e"> </span>the<span class="_ _e"> </span>current<span class="_ _e"> </span>a<span class="_ _5"></span>rchitecture</div><div class="t m0 xb hb y4f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _11"> </span><span class="ff5">size<span class="_ _7"> </span>t<span class="_ _21"> </span><span class="ff4">is<span class="_ _e"> </span>an<span class="_ _e"> </span>unsigned<span class="_ _e"> </span>integer<span class="_ _e"> </span>type<span class="_ _e"> </span>(of<span class="_ _e"> </span>at<span class="_ _e"> </span>least<span class="_ _e"> </span>16-bit)</span></span></div><div class="t m0 xb hb y50 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _11"> </span><span class="ff5">ptrdiff<span class="_ _7"> </span>t<span class="_ _21"> </span><span class="ff4">is<span class="_ _e"> </span>the<span class="_ _e"> </span>signed<span class="_ _e"> </span>version<span class="_ _e"> </span>of<span class="_ _21"> </span><span class="ffa">size<span class="_ _8"> </span>t<span class="_ _21"> </span></span>commonly<span class="_ _e"> </span>used<span class="_ _e"> </span>for<span class="_ _d"> </span>computing</span></span></div><div class="t m0 x7 hb y51 ff4 fs7 fc0 sc0 ls0 ws0">p<span class="_ _c"></span>ointer<span class="_ _d"> </span>differences</div><div class="t m0 xb hb y52 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _11"> </span><span class="ff5">size<span class="_ _7"> </span>t<span class="_ _21"> </span><span class="ff4">is<span class="_ _e"> </span>the<span class="_ _e"> </span>return<span class="_ _e"> </span>type<span class="_ _e"> </span>of<span class="_ _f"> </span><span class="ffa fc4">sizeof()<span class="_ _e"> </span></span>and<span class="_ _e"> </span>commonly<span class="_ _e"> </span>used<span class="_ _e"> </span>to<span class="_ _e"> </span>rep<span class="_ _5"></span>resent<span class="_ _e"> </span>size</span></span></div><div class="t m0 x7 hb y53 ff4 fs7 fc0 sc0 ls0 ws0">measures</div><div class="t m0 xb hb y54 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _11"> </span><span class="ff5">size<span class="_ _7"> </span>t<span class="_ _12"> </span><span class="ff4">/<span class="_ _12"> </span></span>ptrdiff<span class="_ _8"> </span>t<span class="_ _21"> </span><span class="ff4">a<span class="_ _5"></span>re<span class="_ _e"> </span>4<span class="_ _e"> </span>b<span class="_ _5"></span>ytes<span class="_ _e"> </span>on<span class="_ _e"> </span>32-bit<span class="_ _e"> </span>architectures,<span class="_ _d"> </span>and<span class="_ _e"> </span>8<span class="_ _e"> </span>bytes<span class="_ _d"> </span>on<span class="_ _e"> </span>64-bit</span></span></div><div class="t m0 x7 hb y55 ff4 fs7 fc0 sc0 ls0 ws0">a<span class="_ _5"></span>rchitectures</div><div class="t m0 xb hb y56 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4 fc6">C++23<span class="_ _e"> </span><span class="fc0">adds<span class="_ _21"> </span><span class="ffa">uz<span class="_ _12"> </span></span>/<span class="_ _12"> </span><span class="ffa">UZ<span class="_ _21"> </span></span>literals<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _21"> </span><span class="ff5">size<span class="_ _7"> </span>t<span class="_ _12"> </span></span>,<span class="_ _e"> </span>and<span class="_ _21"> </span><span class="ffa">z<span class="_ _12"> </span></span>/<span class="_ _12"> </span><span class="ffa">Z<span class="_ _21"> </span></span>for<span class="_ _21"> </span><span class="ff5">ptrdiff<span class="_ _7"> </span>t</span></span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">11/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Signed/Unsigned<span class="_ _8"> </span>Integer<span class="_ _f"> </span>Cha<span class="_ _5"></span>racteristics</div><div class="t m0 x1 hb y57 ff5 fs7 fc0 sc0 ls0 ws0">Signed<span class="_ _e"> </span><span class="ff4">and<span class="_ _e"> </span></span>Unsigned<span class="_ _e"> </span><span class="ff4">integers<span class="_ _e"> </span>use<span class="_ _e"> </span>the<span class="_ _e"> </span>same<span class="_ _e"> </span>ha<span class="_ _5"></span>rdwa<span class="_ _5"></span>re<span class="_ _d"> </span>for<span class="_ _d"> </span>their<span class="_ _e"> </span>op<span class="_ _c"></span>erations,<span class="_ _e"> </span>but<span class="_ _e"> </span>they</span></div><div class="t m0 x1 hb y58 ff4 fs7 fc0 sc0 ls0 ws0">have<span class="_ _e"> </span>very<span class="_ _e"> </span>different<span class="_ _e"> </span>semantic</div><div class="t m0 x1 hb y59 ff4 fs7 fc0 sc0 ls0 ws0">Basic<span class="_ _e"> </span>concepts:</div><div class="t m0 x11 hb y5a ff1 fs7 fc0 sc0 ls0 ws0">Overflo<span class="_ _5"></span>w<span class="_ _4"> </span><span class="ff4">The<span class="_ _e"> </span>result<span class="_ _e"> </span>of<span class="_ _e"> </span>an<span class="_ _e"> </span>arithmetic<span class="_ _d"> </span>op<span class="_ _c"></span>eration<span class="_ _e"> </span>exceeds<span class="_ _e"> </span>the<span class="_ _e"> </span>w<span class="_ _5"></span>o<span class="_ _5"></span>rd<span class="_ _e"> </span>length,<span class="_ _e"> </span>namely</span></div><div class="t m0 x12 hb y5b ff4 fs7 fc0 sc0 ls0 ws0">the<span class="_ _e"> </span>p<span class="_ _c"></span>ositive/negative<span class="_ _d"> </span>the<span class="_ _e"> </span>largest<span class="_ _d"> </span>values</div><div class="t m0 xe hb y5c ff1 fs7 fc0 sc0 ls0 ws0">W<span class="_ _5"></span>rapa<span class="_ _5"></span>round<span class="_ _4"> </span><span class="ff4">The<span class="_ _e"> </span>result<span class="_ _e"> </span>of<span class="_ _e"> </span>an<span class="_ _e"> </span>a<span class="_ _5"></span>rithmetic<span class="_ _e"> </span>op<span class="_ _c"></span>eration<span class="_ _e"> </span>is<span class="_ _e"> </span>reduced<span class="_ _e"> </span>mo<span class="_ _c"></span>dulo<span class="_ _d"> </span>2</span></div><div class="t m0 x13 h10 y5d ff10 fs5 fc0 sc0 ls0 ws0">N</div><div class="t m0 x14 hb y5c ff4 fs7 fc0 sc0 ls0 ws0">where<span class="_ _e"> </span><span class="ff9">N<span class="_ _f"> </span></span>is</div><div class="t m0 x12 hb y5e ff4 fs7 fc0 sc0 ls0 ws0">the<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>of<span class="_ _e"> </span>bits<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>wo<span class="_ _5"></span>rd</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">12/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Signed<span class="_ _8"> </span>Integer</div><div class="t m0 xb hb y5f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Rep<span class="_ _5"></span>resent<span class="_ _e"> </span>p<span class="_ _c"></span>ositive,<span class="_ _d"> </span>negative,<span class="_ _7"> </span>and<span class="_ _e"> </span>zero<span class="_ _e"> </span>values<span class="_ _e"> </span>(<span class="_ _5"></span><span class="ff11">Z</span></span></div><div class="t m0 x15 h11 y60 ff11 fs7 fc0 sc0 ls0 ws0">Z</div><div class="t m0 x15 hb y5f ff11 fs7 fc0 sc0 ls0 ws0">Z<span class="ff4">)</span></div><div class="t m0 x7 hb y61 ff4 fs7 fc0 sc0 ls0 ws0">Rep<span class="_ _5"></span>resent<span class="_ _e"> </span>the<span class="_ _e"> </span>human<span class="_ _e"> </span>intuition<span class="_ _e"> </span>of<span class="_ _e"> </span>numb<span class="_ _c"></span>ers</div><div class="t m0 x7 hb y62 ff4 fs7 fc0 sc0 ls0 ws0">Mo<span class="_ _5"></span>re<span class="_ _e"> </span>negative<span class="_ _e"> </span>values<span class="_ _e"> </span>(2</div><div class="t m0 x16 h9 y63 ff6 fs5 fc0 sc0 ls0 ws0">31</div><div class="t m0 x17 hb y62 ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">1)<span class="_ _e"> </span>than<span class="_ _e"> </span>p<span class="_ _c"></span>ositive<span class="_ _e"> </span>(2</span></div><div class="t m0 x18 h9 y63 ff6 fs5 fc0 sc0 ls0 ws0">31</div><div class="t m0 x19 hb y62 ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">2)</span></div><div class="t m0 x1a h6 y64 ff4 fs4 fc0 sc0 ls0 ws0">Even<span class="_ _d"> </span>multiply<span class="_ _6"></span>,<span class="_ _d"> </span>division,<span class="_ _d"> </span>and<span class="_ _d"> </span>mo<span class="_ _c"></span>dulo<span class="_ _d"> </span>b<span class="_ _5"></span>y<span class="_ _d"> </span>-1<span class="_ _d"> </span>can<span class="_ _d"> </span>fail</div><div class="t m0 x7 hb y65 ff9 fs7 fc0 sc0 ls0 ws0">Overflo<span class="_ _5"></span>w/underflo<span class="_ _5"></span>w<span class="_ _e"> </span>semantic<span class="_ _f"> </span><span class="ff7">→<span class="_ _e"> </span><span class="ff4">undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></span></div><div class="t m0 x1a h6 y66 ff4 fs4 fc0 sc0 ls0 ws0">P<span class="_ _5"></span>ossible<span class="_ _d"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r:<span class="_ _8"> </span>overflow:<span class="_ _8"> </span>(2</div><div class="t m0 x1b h12 y67 ff6 fs6 fc0 sc0 ls0 ws0">31</div><div class="t m0 x1c h6 y66 ff7 fs4 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">1)<span class="_"> </span>+<span class="_ _14"> </span>1<span class="_ _12"> </span></span>→<span class="_ _25"> </span><span class="ff9">min</span></div><div class="t m0 x1d h6 y68 ff4 fs4 fc0 sc0 ls0 ws0">underflo<span class="_ _5"></span>w:<span class="_ _8"> </span><span class="ff7">−</span>2</div><div class="t m0 x1e h12 y69 ff6 fs6 fc0 sc0 ls0 ws0">31</div><div class="t m0 x1f h6 y68 ff7 fs4 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">1<span class="_ _25"> </span></span>→<span class="_ _25"> </span><span class="ff9">max</span></div><div class="t m0 x7 hb y6a ff4 fs7 fc0 sc0 ls0 ws0">Bit-wise<span class="_ _e"> </span>op<span class="_ _c"></span>erations<span class="_ _d"> </span>are<span class="_ _d"> </span>implementation-defined</div><div class="t m0 x20 h6 y6b ff4 fs4 fc0 sc0 ls0 ws0">e.g.<span class="_ _8"> </span>signed<span class="_ _d"> </span>shift<span class="_ _d"> </span><span class="ff7">→<span class="_ _d"> </span></span>undefined<span class="_ _d"> </span>b<span class="_ _c"></span>ehavior</div><div class="t m0 xb hb y6c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Prop<span class="_ _c"></span>erties<span class="_ _0"></span><span class="ff4">:<span class="_ _f"> </span>commutative,<span class="_ _7"> </span>reflexive,<span class="_ _e"> </span>not<span class="_ _e"> </span>asso<span class="_ _c"></span>ciative<span class="_ _d"> </span>(overflow/underflo<span class="_ _5"></span>w)</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">13/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf10" class="pf w0 h0" data-page-no="10"><div class="pc pc10 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Unsigned<span class="_ _8"> </span>Integer</div><div class="t m0 xb hb y6d ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Rep<span class="_ _5"></span>resent<span class="_ _e"> </span>only<span class="_ _e"> </span><span class="ff9">non-negative<span class="_ _8"> </span></span>values<span class="_ _e"> </span>(<span class="_ _5"></span><span class="ff11">N</span></span></div><div class="t m0 x21 h11 y6e ff11 fs7 fc0 sc0 ls0 ws0">N</div><div class="t m0 x21 hb y6d ff11 fs7 fc0 sc0 ls0 ws0">N<span class="ff4">)</span></div><div class="t m0 xb hb y6f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Discontinuit<span class="_ _5"></span>y<span class="_ _e"> </span>in<span class="_ _e"> </span>0,<span class="_ _e"> </span>2</span></div><div class="t m0 x22 h9 y70 ff6 fs5 fc0 sc0 ls0 ws0">32</div><div class="t m0 x23 hb y6f ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">1</span></div><div class="t m0 x7 hb y71 ff4 fs7 fc0 sc0 ls0 ws0">W<span class="_ _5"></span>rapa<span class="_ _5"></span>round<span class="_ _e"> </span>semantic<span class="_ _e"> </span><span class="ff7">→<span class="_ _e"> </span></span>well-defined<span class="_ _d"> </span>(mo<span class="_ _c"></span>dulo<span class="_ _e"> </span>2</div><div class="t m0 x24 h9 y72 ff6 fs5 fc0 sc0 ls0 ws0">32</div><div class="t m0 x25 hb y71 ff4 fs7 fc0 sc0 ls0 ws0">)</div><div class="t m0 x7 hb y73 ff4 fs7 fc0 sc0 ls0 ws0">Bit-wise<span class="_ _e"> </span>op<span class="_ _c"></span>erations<span class="_ _d"> </span>are<span class="_ _d"> </span>well-defined</div><div class="t m0 xb hb y74 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Prop<span class="_ _c"></span>erties<span class="_ _0"></span><span class="ff4">:<span class="_ _f"> </span>commutative,<span class="_ _7"> </span>reflexive,<span class="_ _e"> </span>asso<span class="_ _c"></span>ciative</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">14/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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ToUekL03do0Ewo9IeqtTSdCoSdEPbXpZCj0hOi+2nQqFHpCdG9tOh0KPSG65+Y0cyrkV4do2c1p4ngorX1+MFHNtS2MLqZrp5wO+dUh6qpNUyH/xL71sYVEZyxkG8fSsdrx6ZBfe/N4KjGXbz7aWHthfGZlprTqwOb09cbDzfWTz4T86hAtvTlNng7FR/dsbqkejqVq65gJpbV7+tPZf4zXVjY+2ZGp9oWosz52Zqp9IeqoXeFkKK4dfib+1V2npsJC3+8PlUuvtzfdPHJsOpTX/2Ff6ov04fbG+lWWZqp9IWqvjcdXZhYfH55Nt9SuOh2KG4a3V0eLtduMT3dkyk/tmk3XLjl5PBT79gy1HCrF6xfsylT7QtRWH5dlqn0haq29qxOhtOGPovBl5Uhzqn7G8ky1L0Qt9bE7U+0LUXN9XJGp9oUoXR/vylT7QtRUH1dmqn0hqr+ZqY5MpT9EtStPngrFp4e3FEYbaos/diKUNx7ov3E92ZnIlUab6iuY6sxU+kO0pLbGM6H01O6nDtX/anxqaabSH6Jk7eXJUNoaDeRai2H+q2c/MRVKW6KBXGtILNzy5I+dCuWNgwNzodw51lA/9WQobRocWEhnR2O1ZzkxHUqbdw3FD5ca6vfsylT6Q5SoPcrpsNB/4KmGaqJcHK1/QsZnVmRKmw5sjV/PXUs1xotfLWZ85q5MaWPtlbZU6baPYnem9OyBrfHr8VzDrcenlmUq/SGqP8Wp5ZlKf4hqy5k8EYr9g9uzTf9Qf2qTM6G4ZXj4jdRi7R2cCqXv7VofyhOLrfVLdGcq/SGq3WByKhQHdgzMLr7ZXP/ETobithe2jiwsqf/BikylP0ShPt6VqfSHqFofV2Yq/SGq1D+oHZnFHSFa3P8fvHkN0AGAI4EAAAAASUVORK5CYII="/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">When<span class="_ _8"> </span>Use<span class="_ _f"> </span>Signed/Unsigned<span class="_ _8"> </span>Integer?<span class="_ _26"> </span>1/2</div><div class="t m0 x1 hb y75 ff4 fs7 fc0 sc0 ls0 ws0">Go<span class="_ _c"></span>ogle<span class="_ _d"> </span>Style<span class="_ _d"> </span>Guide</div><div class="t m0 x26 hb y76 ff4 fs7 fc0 sc0 ls0 ws0">Because<span class="_ _e"> </span>of<span class="_ _e"> </span>histo<span class="_ _5"></span>rical<span class="_ _e"> </span>accident,<span class="_ _e"> </span>the<span class="_ _e"> </span>C++<span class="_ _e"> </span>standa<span class="_ _5"></span>rd<span class="_ _e"> </span>also<span class="_ _e"> </span>uses<span class="_ _e"> </span>unsigned<span class="_ _e"> </span>integers<span class="_ _e"> </span>to</div><div class="t m0 x26 hb y77 ff4 fs7 fc0 sc0 ls0 ws0">rep<span class="_ _5"></span>resent<span class="_ _e"> </span>the<span class="_ _d"> </span>size<span class="_ _e"> </span>of<span class="_ _e"> </span>containers<span class="_ _e"> </span>-<span class="_ _e"> </span>many<span class="_ _d"> </span>memb<span class="_ _c"></span>ers<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _d"> </span>standards<span class="_ _d"> </span>b<span class="_ _c"></span>o<span class="_ _c"></span>dy<span class="_ _d"> </span>b<span class="_ _c"></span>elieve<span class="_ _e"> </span>this</div><div class="t m0 x26 hb y78 ff4 fs7 fc0 sc0 ls0 ws0">to<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _d"> </span>a<span class="_ _e"> </span>mistake,<span class="_ _d"> </span>but<span class="_ _e"> </span>it<span class="_ _e"> </span>is<span class="_ _e"> </span>effectively<span class="_ _e"> </span>imp<span class="_ _c"></span>ossible<span class="_ _e"> </span>to<span class="_ _e"> </span>fix<span class="_ _e"> </span>at<span class="_ _e"> </span>this<span class="_ _e"> </span>p<span class="_ _c"></span>oint</div><div class="t m0 x1 hb y79 ff1 fs7 fc0 sc0 ls0 ws0">Solution:<span class="_ _a"> </span><span class="ff4">use<span class="_ _21"> </span><span class="ffa fc4">int64<span class="_ _e"> </span>t</span></span></div><div class="t m0 x1 hb y7a ff1 fs7 fc0 sc0 ls0 ws0">max<span class="_ _7"> </span>value:<span class="_ _a"> </span><span class="ff4">2</span></div><div class="t m0 x27 h9 y7b ff6 fs5 fc0 sc0 ls0 ws0">63</div><div class="t m0 x28 hb y7a ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">1<span class="_ _e"> </span>=<span class="_ _e"> </span>9,223,372,036,854,775,807<span class="_ _e"> </span>or</span></div><div class="t m0 x1d hb y7c ff4 fs7 fc0 sc0 ls0 ws0">9<span class="_ _e"> </span>quintillion<span class="_ _e"> </span>(9<span class="_ _e"> </span>billion<span class="_ _e"> </span>of<span class="_ _e"> </span>billion),</div><div class="t m0 x1d hb y7d ff4 fs7 fc0 sc0 ls0 ws0">ab<span class="_ _c"></span>out<span class="_ _d"> </span>292<span class="_ _e"> </span>yea<span class="_ _5"></span>rs<span class="_ _d"> </span>in<span class="_ _e"> </span>nanoseconds,</div><div class="t m0 x1d hb y7e ff4 fs7 fc0 sc0 ls0 ws0">9<span class="_ _e"> </span>million<span class="_ _e"> </span>terab<span class="_ _5"></span>ytes</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">15/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">When<span class="_ _8"> </span>Use<span class="_ _f"> </span>Signed/Unsigned<span class="_ _8"> </span>Integer?<span class="_ _26"> </span>2/2</div><div class="t m0 x1 hb y7f ff9 fs7 fc0 sc0 ls0 ws0">When<span class="_ _e"> </span>use<span class="_ _e"> </span><span class="ffe">signed<span class="_ _e"> </span></span>integer?</div><div class="t m0 xb hb y80 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">if<span class="_ _e"> </span>it<span class="_ _e"> </span>can<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _d"> </span>mixed<span class="_ _e"> </span>with<span class="_ _e"> </span>negative<span class="_ _e"> </span>values,<span class="_ _e"> </span>e.g.<span class="_ _a"> </span>subtracting<span class="_ _e"> </span>b<span class="_ _5"></span>yte<span class="_ _e"> </span>sizes</span></div><div class="t m0 xb hb y81 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">p<span class="_ _5"></span>refer<span class="_ _e"> </span>expressing<span class="_ _d"> </span>non-negative<span class="_ _e"> </span>values<span class="_ _e"> </span>with<span class="_ _e"> </span>signed<span class="_ _e"> </span>integer<span class="_ _e"> </span>and<span class="_ _e"> </span>assertions</span></div><div class="t m0 xb hb y82 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">optimization<span class="_ _e"> </span>purp<span class="_ _c"></span>oses,<span class="_ _d"> </span>e.g.<span class="_ _a"> </span>exploit<span class="_ _e"> </span>undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _d"> </span>for<span class="_ _d"> </span>overflow<span class="_ _d"> </span>or<span class="_ _e"> </span>in<span class="_ _e"> </span>loops</span></div><div class="t m0 x1 hb y83 ff9 fs7 fc0 sc0 ls0 ws0">When<span class="_ _e"> </span>use<span class="_ _e"> </span><span class="ffe">unsigned<span class="_ _e"> </span></span>integer?</div><div class="t m0 xb hb y84 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">if<span class="_ _e"> </span>the<span class="_ _e"> </span>quantit<span class="_ _5"></span>y<span class="_ _e"> </span>can<span class="_ _e"> </span>never<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>mixed<span class="_ _e"> </span>with<span class="_ _e"> </span>negative<span class="_ _e"> </span>values<span class="_ _e"> </span>(?)</span></div><div class="t m0 xb hb y85 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">bitmask<span class="_ _e"> </span>values</span></div><div class="t m0 xb hb y86 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">optimization<span class="_ _e"> </span>purp<span class="_ _c"></span>oses,<span class="_ _d"> </span>e.g.<span class="_ _a"> </span>division,<span class="_ _e"> </span>mo<span class="_ _c"></span>dulo</span></div><div class="t m0 xb hb y87 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">safet<span class="_ _5"></span>y-critical<span class="_ _e"> </span>system,<span class="_ _e"> </span>signed<span class="_ _e"> </span>integer<span class="_ _e"> </span>overflow<span class="_ _d"> </span>could<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>“non-deterministic”</span></div><div class="t m0 xb hd y88 ffc fs8 fc3 sc0 ls0 ws0">Subscripts<span class="_ _f"> </span>and<span class="_ _f"> </span>sizes<span class="_ _a"> </span>should<span class="_ _f"> </span>be<span class="_ _f"> </span>signed<span class="ffb">,<span class="_ _12"> </span><span class="ff12">Bjarne<span class="_ _25"> </span>Stroustrup</span></span></div><div class="t m0 x6 hd y89 ffc fs8 fc3 sc0 ls0 ws0">Don’t<span class="_ _f"> </span>add<span class="_ _f"> </span>to<span class="_ _a"> </span>the<span class="_ _f"> </span>signed/unsigned<span class="_ _f"> </span>mess<span class="ffb">,<span class="_ _12"> </span><span class="ff12">Bjarne<span class="_ _25"> </span>Stroustrup</span></span></div><div class="t m0 x6 hd y8a ffc fs8 fc3 sc0 ls0 ws0">Integer<span class="_ _f"> </span>Type<span class="_ _f"> </span>Selection<span class="_ _a"> </span>in<span class="_ _f"> </span>C++:<span class="_ _27"> </span>in<span class="_ _f"> </span>Safe,<span class="_ _f"> </span>Secure<span class="_ _a"> </span>and<span class="_ _f"> </span>Correct<span class="_ _f"> </span>Code<span class="ffb">,<span class="_ _12"> </span><span class="ff12">Rob<span class="_ _c"></span>ert<span class="_ _12"> </span>C.<span class="_ _12"> </span>Seacord</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">16/77</div><a class="l" href="http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2019/p1428r0.pdf"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:25.482000px;width:176.165000px;height:11.656000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2019/p1491r0.pdf"><div class="d m1" style="border-style:none;position:absolute;left:34.324000px;bottom:13.875000px;width:176.164000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://github.com/boostcon/cppnow_presentations_2023/blob/main/cppnow_slides/Integer_type_selection.pdf"><div class="d m1" style="border-style:none;position:absolute;left:34.324000px;bottom:0.481000px;width:303.262000px;height:12.000000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Arithmetic<span class="_ _8"> </span>T<span class="_ _6"></span>yp<span class="_ _c"></span>e<span class="_ _8"> </span>Limits</div><div class="t m0 x1 hb y8b ff4 fs7 fc0 sc0 ls0 ws0">Query<span class="_ _e"> </span>p<span class="_ _5"></span>rop<span class="_ _c"></span>erties<span class="_ _d"> </span>of<span class="_ _e"> </span>arithmetic<span class="_ _d"> </span>types<span class="_ _e"> </span>in<span class="_ _e"> </span><span class="fc6">C++11</span>:</div><div class="t m0 xe he y8c ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><limits></span></div><div class="t m0 xe hd y8d ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><<span class="ff5 fc7">int</span>>::</span>max();<span class="_ _29"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ffb">2</span></span></div><div class="t m0 x29 h13 y8e ff6 fs9 fc9 sc0 ls0 ws0">31</div><div class="t m0 x2a hd y8d ff13 fs8 fc9 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ffb">1</span></div><div class="t m0 xe hd y8f ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><<span class="ff5 fc7">uint16_t</span>>::</span>max();<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ffb">65<span class="ff14">,<span class="_ _14"> </span></span>535</span></span></div><div class="t m0 xe hd y90 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><<span class="ff5 fc7">int</span>>::</span>min();<span class="_ _29"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ff13">−<span class="ffb">2</span></span></span></div><div class="t m0 x2b h13 y91 ff6 fs9 fc9 sc0 ls0 ws0">31</div><div class="t m0 xe hd y92 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><<span class="ff5 fc7">unsigned</span>>::</span>min();<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ffb">0</span></span></div><div class="t m0 x1 h6 y93 ff4 fs4 fc0 sc0 ls0 ws0">*<span class="_ _d"> </span>this<span class="_ _d"> </span>syntax<span class="_ _d"> </span>will<span class="_ _d"> </span>b<span class="_ _c"></span>e<span class="_ _12"> </span>explained<span class="_ _d"> </span>in<span class="_ _d"> </span>the<span class="_ _d"> </span>next<span class="_ _d"> </span>lectures</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">17/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Promotion<span class="_ _8"> </span>and<span class="_ _f"> </span>T<span class="_ _b"></span>runcation</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">Promotion<span class="_ _e"> </span><span class="ff4">to<span class="_ _e"> </span>a<span class="_ _e"> </span>la<span class="_ _5"></span>rger<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="_ _e"> </span>k<span class="_ _5"></span>eeps<span class="_ _e"> </span>the<span class="_ _e"> </span>sign</span></div><div class="t m0 xe h10 y94 ff5 fs5 fc7 sc0 ls0 ws0">int16_t<span class="_ _8"> </span><span class="ff15 fc0">x<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>-1</span>;</span></div><div class="t m0 xe h10 y95 ff5 fs5 fc7 sc0 ls0 ws0">int<span class="_ _2a"> </span><span class="ff15 fc0">y<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span></span>x;<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>sign<span class="_ _7"> </span>extend</span></span></div><div class="t m0 xe h10 y96 ff15 fs5 fc0 sc0 ls0 ws0">cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>y;<span class="_ _2a"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>-1</span></div><div class="t m0 x1 hb y97 ff1 fs7 fc0 sc0 ls0 ws0">T<span class="_ _6"></span>runcation<span class="_ _e"> </span><span class="ff4">to<span class="_ _e"> </span>a<span class="_ _e"> </span>smaller<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="_ _d"> </span>is<span class="_ _e"> </span>implemented<span class="_ _e"> </span>as<span class="_ _e"> </span>a<span class="_ _e"> </span>mo<span class="_ _c"></span>dulo<span class="_ _e"> </span>op<span class="_ _c"></span>eration<span class="_ _e"> </span>with<span class="_ _e"> </span>resp<span class="_ _c"></span>ect<span class="_ _d"> </span>to</span></div><div class="t m0 x1 hb y98 ff4 fs7 fc0 sc0 ls0 ws0">the<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>of<span class="_ _e"> </span>bits<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>smaller<span class="_ _e"> </span>type</div><div class="t m0 xe h10 y99 ff5 fs5 fc7 sc0 ls0 ws0">int<span class="_ _2a"> </span><span class="ff15 fc0">x<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>65537</span>;<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>2ˆ16<span class="_ _7"> </span>+<span class="_ _8"> </span>1</span></span></div><div class="t m0 xe h10 y9a ff5 fs5 fc7 sc0 ls0 ws0">int16_t<span class="_ _8"> </span><span class="ff15 fc0">y<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span></span>x;<span class="_ _2a"> </span><span class="ffe fc9">//<span class="_ _8"> </span>x<span class="_ _7"> </span>%<span class="_ _8"> </span>2ˆ16</span></span></div><div class="t m0 xe h10 y9b ff15 fs5 fc0 sc0 ls0 ws0">cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>y;<span class="_ _1e"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>1</span></div><div class="t m0 xe h10 y9c ff5 fs5 fc7 sc0 ls0 ws0">int<span class="_ _2a"> </span><span class="ff15 fc0">z<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>32769</span>;<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>2ˆ15<span class="_ _7"> </span>+<span class="_ _8"> </span>1<span class="_ _8"> </span>(does<span class="_ _8"> </span>not<span class="_ _8"> </span>fit<span class="_ _8"> </span>in<span class="_ _8"> </span>a<span class="_ _7"> </span>int16_t)</span></span></div><div class="t m0 xe h10 y9d ff5 fs5 fc7 sc0 ls0 ws0">int16_t<span class="_ _8"> </span><span class="ff15 fc0">w<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span></span>z;<span class="_ _2a"> </span><span class="ffe fc9">//<span class="_ _8"> </span>(int16_t)<span class="_ _7"> </span>(x<span class="_ _8"> </span>%<span class="_ _8"> </span>2ˆ16<span class="_ _8"> </span>=<span class="_ _8"> </span>32769)</span></span></div><div class="t m0 xe h10 y9e ff15 fs5 fc0 sc0 ls0 ws0">cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>w;<span class="_ _1e"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>-32767</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">18/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf15" class="pf w0 h0" data-page-no="15"><div class="pc pc15 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Mixing<span class="_ _8"> </span>Signed/Unsigned<span class="_ _f"> </span>Erro<span class="_ _5"></span>rs<span class="_ _2b"> </span>1/3</div><div class="t m0 xe he y9f ff5 fs8 fc7 sc0 ls0 ws0">unsigned<span class="_ _f"> </span><span class="ffc fc0">a<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>10</span>;<span class="_ _1"> </span><span class="ffe fc9">//<span class="_ _a"> </span>array<span class="_ _f"> </span>is<span class="_ _f"> </span>small</span></span></div><div class="t m0 xe he ya0 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _29"> </span><span class="ffc fc0">b<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>-1</span>;</span></div><div class="t m0 xe he ya1 ffc fs8 fc0 sc0 ls0 ws0">array[<span class="fc8">10ull<span class="_ _f"> </span>+<span class="_ _f"> </span></span>a<span class="_ _a"> </span><span class="fc8">*<span class="_ _f"> </span></span>b]<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>0</span>;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>?</span></div><div class="t m0 x1 h14 ya2 ff16 fs8 fc0 sc0 ls0 ws0"><span class="fc5 sc0">A</span></div><div class="t m0 xd hd ya2 ffb fs8 fc0 sc0 ls0 ws0">Segmentation<span class="_ _12"> </span>fault!</div><div class="t m0 xe he ya3 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc4">f<span class="fc0">(</span></span>int<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>unsigned<span class="_ _f"> </span><span class="ffc fc0">b,<span class="_ _f"> </span></span>int<span class="ffc fc8">*<span class="_ _f"> </span><span class="fc0">array)<span class="_ _a"> </span>{<span class="_ _1"> </span><span class="ffe fc9">//<span class="_ _a"> </span>array<span class="_ _8"> </span>is<span class="_ _a"> </span>small</span></span></span></div><div class="t m0 x7 he ya4 ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(a<span class="_ _f"> </span><span class="fc8">><span class="_ _a"> </span></span>b)</span></div><div class="t m0 x2c he ya5 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc0">array[a<span class="_ _f"> </span><span class="fc8">-<span class="_ _a"> </span></span>b];<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>?</span></span></div><div class="t m0 x7 he ya6 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc8">0<span class="fc0">;</span></span></div><div class="t m0 xe he ya7 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x1 h14 ya8 ff16 fs8 fc0 sc0 ls0 ws0"><span class="fc5 sc0">A</span></div><div class="t m0 xd hd ya8 ffb fs8 fc0 sc0 ls0 ws0">Segmentation<span class="_ _12"> </span>fault<span class="_ _12"> </span>for<span class="_ _18"> </span><span class="ffc">a<span class="_ _a"> </span><span class="ff17"><<span class="_ _8"> </span></span>0<span class="_ _12"> </span></span>!</div><div class="t m0 xe he ya9 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>v.size()<span class="_ _f"> </span>return<span class="_ _a"> </span>unsigned</div><div class="t m0 xe he yaa ff5 fs8 fcb sc0 ls0 ws0">for<span class="_ _f"> </span><span class="ffc fc0">(</span><span class="fc7">size_t<span class="_ _f"> </span><span class="ffc fc0">i<span class="_ _a"> </span><span class="fc8">=<span class="_ _f"> </span>0</span>;<span class="_ _f"> </span>i<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span></span>v.size()<span class="_ _f"> </span><span class="fc8">-<span class="_ _f"> </span>1</span>;<span class="_ _f"> </span>i<span class="fc8">++</span>)</span></span></div><div class="t m0 x7 he yab ffc fs8 fc0 sc0 ls0 ws0">array[i]<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>3</span>;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>?</span></div><div class="t m0 x1 h14 yac ff16 fs8 fc0 sc0 ls0 ws0"><span class="fc5 sc0">A</span></div><div class="t m0 xd hd yac ffb fs8 fc0 sc0 ls0 ws0">Segmentation<span class="_ _12"> </span>fault<span class="_ _12"> </span>for<span class="_ _18"> </span><span class="ffc">v.size()<span class="_ _a"> </span>==<span class="_ _8"> </span>0<span class="_ _12"> </span></span>!</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">19/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
|
||
<div id="pf16" class="pf w0 h0" data-page-no="16"><div class="pc pc16 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA4wAAAH/CAIAAACTgcSzAAAACXBIWXMAABYlAAAWJQFJUiTwAAAQuklEQVR42u3Y3XNTd37A4Z8sCcmy5RdeTOgmwd68kwQIOC+QYDgxNjjDAiXQtN1eJjvT9qb/RW97t51OJr1Ih3QaJ7OkbA2xg21s3rMvTTe7hGQgnU02pCTIlpFsS7LUC6QNdHrR2WlnSPd57r7nHJ/z0znHM585sfuefjYAAMAd45Oz003uAgAAdxqRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgDAb8VKpZK7AADAnSOZTPqSCgDAHUekAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEA+P2V+BatdW5uzgMDAPjdZLPZb9FqfUkFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAPD7J1YqldwFAADuHMlk0pdUAADuOCIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAA/PcS36K1zs3NeWAAAL+bbDb7LVqtL6kAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAA8L8kViqV3AUAAO4cyWTSl1QAAO44IhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAD4H0nM/nWPu8C32rWBV90EAPj/5JEtu2OdfxVyfxNCeKBn//rW2c7ne2K/yjavPzH1brw5f/eKzat6un9+8t2eJ7felyotHf3XsY7qskuF2S3f23FvU6Kt9HF+Wc9Hwx9s3f3lx+WD3bXZ+ImfnOhIXSp8sW3H3nuzc+1z8eGlVeHaVwdX5pLtncd+NLUxPJA4uPJaefn9J3JfD8bjb4XMrkSoTrw6Mb/lhf1PxRevF1uOnx/riC0t1eLx1MymHeHTH4f05v6etpXpSv6tYnLn+CfnH/8sH4teWnHjRvq995btXZib311LVcfjIXxee+b9mfIDS+HjQm1DWzXxi8sjlfzQ/v33lJoSxfzw0qrw75d6l9+4eGFp1fqOxAedna2js49szv7qJ3OP9N67pi0kkmfe/uLhhy6//wfP7xz/zexDl358Od/f3XujPdk+e/FK++6o843J0T/qPbCUWCqPzLXcvrbRkXXpEA+hvrQ33h35s+/tS7198erm7IUPVx7ckz49Or5t9+6RmepA9nilumW8miyfeK2Sf6F/aO2xtsqBG0fm06E5v2eukgrxtzoyO2cSY+3FgeErM5uzF+a+s3f9kcuF/jXJjjDxw4n8cy8cuJQsDgwnMy+mjtRm++eaO0fTszcXFhZCsmmodixe7F9MdoR3Qhj44cToN5cpFl88tqIwMPzZtY3h5/esGoqtqISvmwuJdzrao1hs+fC1UtQcW7FQLiXKx88druZf6B94/+OOAxtmKk2jV74e6lmxUC4lmt/J3Lh5mcbSP6rs2pwozKd7CpXXv/yP257Y0t5Hl7e+eelo495c+PuxW372bGJvRykZy7xVngvJpoHhamJPLXM0VXwxXZkdTmRCS2lg+PNP1leS85m2q4vZXfdkj38We/queOZcU2Zw+HphT+3UaxP5p9c+tvjJV8Wuq7H4ytz8L5OFZ4e2V2PN64qxVNurH1ReXv9hudpTasq0Jycu/eL+29/rTGVfa2g9dvmD/7I9Ob+3uhTLtB0pxvZf+LS69e5U5eLPRr+7bl9raP06VTj87ucv17fd23Pw+IXhgSiEVH985Nep7es/b6l0vjEfDh5/f3hgR6gs7bw725ov/Gh+dk820VmMXY1nw2vptpfK+fFq9tBsy7LYZ7O/3dGZvnV67cQHXZs39XeM1GZ3pZpfP33xle3rL4X8g+/825GdG/s7RmKx/WNfF3alml8/nf5+/1JiqTw+NZGuLlt8/oln8plsOvPOwleDh89ffWXgOzdmxz/N7P4/+D/75dDTt17r07/c9uBHhdjqM1euPnrbLX2vc+62417qu6+l9fPCjW+O/JfoyVuPmP3+1o54y+Rvyi+szZfGOhdv3Rf/89UhubZ8MdGxojYcX9yTTRydDYOHz//6LzbdV2j6MJl4dP749OjOJwcPn8+9/GRHIp2oLH4Ra1uTLC4rjZyYWtmc27jh1n3XSon2eLIpnRydfC9sfHLwcEj/6WgiFt264Fe2r78yt7h6/OTc/d2FRPVyIjx8+zsTnxs8fP7Ky73ristq8ZHpn3Zdf+y5AyH1tz9746GZ5YlV1wcr4fq2nZXMWAj98X98//TeHYPFYn6spf1g9s18/sA/FOI/GJs8FRZbQ9R78O9ysR+MTZ4Oi60h2lyfzoTF1hBtqk9nw2JriJ6oT+fCYmuINt6cTk6Eha4QbahPk2GhK0Tr69PJsNAVosfr01RY6ArRY/VpOix0hejR+nQqLHSFaF19Oh0WukL0SH06Exa6QvRwfTobFrpC9FB9OhcWukL04M1paiLMd4fogfo0Gea7Q3R/fToZ5rtDdF99mgrz3SH6bn2aDvPdIeqpT6fCfHeIuuvT6TDfHaK19elMmO8O0b316WyY7w7RPTen6TOhuC5EK29O4ydDecOLA4laoW1xZClTP+RsKK4L0Yr6NBmKTxzYFFtMdMZCPj2aidW3T4XihpvbU4m5YsvxdH3H2PSaXPmRQ9syM+mjLY2Dz4XiuhAtvzlNnA2lR/dta60djaXq65gO5Q37+jL5f47XVzY20ZGr9YaoszF25mq9Ieqon+F0KG0Yeib+zVUnJ8Ni7x8OVspvtjff3HJiKlQ2/XFv6svM0fZ04yzLc7XeELXXx5NrckuPD81mWutnnQqlzUO7aiOl+mXGpjpylaf2zGbqp5w4GUq9+wZbj5TjjROuyNV6Q9TWGFfmar0hytZ/1alQ3vwnUfiqeqwl1ThiVa7WG6LWxtiVq/WGqKUxrs7VekOUaYx35Wq9IWpujGtytd4QNX7MZEeu2hei+pknzoTS00Pb50ea6os/cSpUthzquzGT7EwUyiPNjRVMduaqfSFaVl/juVB+au9TRxp/NTa5PFftC1GyvnsilHdE/YVsKSx88+zHJ0N5e9RfyIbE4i1P/sSZUNky0D8XKp2jTY1DT4fy1oH+xUx+JFZ/luNTobxtz2D8aLmpcc0VuWpfiBL1RzkVFvsOPdVUS1RKI403ZGx6da689dCO+EzheiodL32zmLHpu3LlLfU9banyba9iV6787KEd8Zl4oenW7ZMrc9W+EDWe4uSqXLUvRPXlTJwKpb6BXfnmf2o8tYnpUNo+NPRWaqn+C86E8nN7NoXK+FK2cYquXLUvRPULTEyGUv/u/tmlt1sab+xEKO18acfw4rLGH6zOVftCFBrjXblqX4hqjXFNrtoXomrjRe3ILe0O0dLB/wTaG/mY9b+heQAAAABJRU5ErkJggg=="/><div class="t m0 x5 h15 y7 ff1 fs3 fc1 sc0 ls0 ws0">Mixing<span class="_ _8"> </span>Signed/Unsigned<span class="_ _f"> </span>Erro<span class="_ _5"></span>rs<span class="_ _2c"> </span><span class="ff18"><span class="_ _8"> </span></span>2/3</div><div class="t m0 x1 hb yad ff4 fs7 fc0 sc0 ls0 ws0">Easy<span class="_ _e"> </span>case:</div><div class="t m0 xe he yae ff5 fs8 fc7 sc0 ls0 ws0">unsigned<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>32</span>;<span class="_ _2d"> </span><span class="ffe fc9">//<span class="_ _f"> </span>x<span class="_ _f"> </span>can<span class="_ _a"> </span>be<span class="_ _f"> </span>also<span class="_ _f"> </span>a<span class="_ _f"> </span>pointer</span></span></div><div class="t m0 xe he yaf ffc fs8 fc0 sc0 ls0 ws0">x<span class="_ _2e"> </span><span class="fc8">+=<span class="_ _f"> </span>2u<span class="_ _f"> </span>-<span class="_ _a"> </span>4</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>2u<span class="_ _f"> </span>-<span class="_ _a"> </span>4<span class="_ _f"> </span>=<span class="_ _f"> </span>2<span class="_ _f"> </span>+<span class="_ _a"> </span>(2ˆ32<span class="_ _8"> </span>-<span class="_ _a"> </span>4)</span></div><div class="t m0 x2d he yb0 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _2f"> </span>=<span class="_ _f"> </span>2ˆ32<span class="_ _f"> </span>-<span class="_ _a"> </span>2</div><div class="t m0 x2d he yb1 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>(32<span class="_ _f"> </span>+<span class="_ _a"> </span>(2ˆ32<span class="_ _f"> </span>-<span class="_ _f"> </span>2))<span class="_ _f"> </span>%<span class="_ _a"> </span>2ˆ32</div><div class="t m0 xe he yb2 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>x;<span class="_ _30"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>30<span class="_ _a"> </span>(as<span class="_ _f"> </span>expected)</span></div><div class="t m0 x1 hb yb3 ff1 fs7 fc0 sc0 ls0 ws0">What<span class="_ _7"> </span>ab<span class="_ _c"></span>out<span class="_ _7"> </span>the<span class="_ _7"> </span>following<span class="_ _e"> </span>co<span class="_ _c"></span>de?</div><div class="t m0 xe he yb4 ff5 fs8 fc7 sc0 ls0 ws0">uint64_t<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>32</span>;<span class="_ _2d"> </span><span class="ffe fc9">//<span class="_ _f"> </span>x<span class="_ _f"> </span>can<span class="_ _a"> </span>be<span class="_ _f"> </span>also<span class="_ _f"> </span>a<span class="_ _f"> </span>pointer</span></span></div><div class="t m0 xe he yb5 ffc fs8 fc0 sc0 ls0 ws0">x<span class="_ _2e"> </span><span class="fc8">+=<span class="_ _f"> </span>2u<span class="_ _f"> </span>-<span class="_ _a"> </span>4</span>;</div><div class="t m0 xe he yb6 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>x;</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">20/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf17" class="pf w0 h0" data-page-no="17"><div class="pc pc17 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h15 y7 ff1 fs3 fc1 sc0 ls0 ws0">Mixing<span class="_ _8"> </span>Signed/Unsigned<span class="_ _f"> </span>Erro<span class="_ _5"></span>rs<span class="_ _2c"> </span><span class="ff18"><span class="_ _8"> </span></span>3/3</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">A<span class="_ _7"> </span>real-wo<span class="_ _5"></span>rld<span class="_ _e"> </span>case:</div><div class="t m0 xe he yb7 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>allocate<span class="_ _f"> </span>a<span class="_ _a"> </span>zero<span class="fff">₫<span class="_ _f"> </span></span>rtx<span class="_ _f"> </span>vector<span class="_ _27"> </span>of<span class="_ _f"> </span>N<span class="_ _a"> </span>elements</div><div class="t m0 xe he yb8 ffe fs8 fc9 sc0 ls0 ws0">//</div><div class="t m0 xe he yb9 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>sizeof(struct<span class="_ _f"> </span>rtvec_def)<span class="_ _a"> </span>==<span class="_ _f"> </span>16</div><div class="t m0 xe he yba ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>sizeof(rtunion)<span class="_ _f"> </span>==<span class="_ _a"> </span>8</div><div class="t m0 xe he ybb ffc fs8 fc0 sc0 ls0 ws0">rtvec<span class="_ _f"> </span><span class="fc4">rtvec_alloca</span>(<span class="ff5 fc7">int<span class="_ _f"> </span></span>n)<span class="_ _a"> </span>{</div><div class="t m0 x7 he ybc ffc fs8 fc0 sc0 ls0 ws0">rtvec<span class="_ _f"> </span>rt;</div><div class="t m0 x7 he ybd ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">i;</span></div><div class="t m0 x7 he ybe ffc fs8 fc0 sc0 ls0 ws0">rt<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span></span>(rtvec)obstack_alloc(</div><div class="t m0 x2c he ybf ffc fs8 fc0 sc0 ls0 ws0">rtl_obstack,</div><div class="t m0 x2c he yc0 ff5 fs8 fcb sc0 ls0 ws0">sizeof<span class="ffc fc0">(</span>struct<span class="_ _f"> </span><span class="fc4">rtvec_def<span class="ffc fc0">)<span class="_ _f"> </span><span class="fc8">+<span class="_ _a"> </span></span>((n<span class="_ _f"> </span><span class="fc8">-<span class="_ _f"> </span>1</span>)<span class="_ _f"> </span><span class="fc8">*<span class="_ _a"> </span></span></span></span>sizeof<span class="ffc fc0">(rtunion)));</span></div><div class="t m0 xe he yc1 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _27"> </span>...</div><div class="t m0 x7 he yc2 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc0">rt;</span></div><div class="t m0 xe he yc3 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 xb he yc4 ffc fs8 fc3 sc0 ls0 ws0">Garbage<span class="_ _f"> </span>In,<span class="_ _f"> </span>Garbage<span class="_ _a"> </span>Out:<span class="_ _1"> </span>Arguing<span class="_ _a"> </span>about<span class="_ _f"> </span>Undefined<span class="_ _f"> </span>Behavior<span class="_ _f"> </span>with<span class="_ _a"> </span>Nasal<span class="_ _8"> </span>Daemons,</div><div class="t m0 x26 he yc5 ffc fs8 fc3 sc0 ls0 ws0">Chandler<span class="_ _f"> </span>Carruth,<span class="_ _f"> </span>CppCon<span class="_ _a"> </span>2016</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">21/77</div><a class="l" href="https://www.youtube.com/watch?v=yG1OZ69H_-o"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:12.281000px;width:391.471000px;height:11.656000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://www.youtube.com/watch?v=yG1OZ69H_-o"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:-2.110000px;width:148.468000px;height:11.153000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf18" class="pf w0 h0" data-page-no="18"><div class="pc pc18 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _31"> </span>1/7</div><div class="t m0 x1 hb yc6 ff4 fs7 fc0 sc0 ls0 ws0">The<span class="_ _e"> </span>C++<span class="_ _e"> </span>standa<span class="_ _5"></span>rd<span class="_ _e"> </span>do<span class="_ _c"></span>es<span class="_ _d"> </span>not<span class="_ _e"> </span>prescribe<span class="_ _e"> </span>any<span class="_ _e"> </span>sp<span class="_ _c"></span>ecific<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _e"> </span>(undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r)<span class="_ _d"> </span>for</div><div class="t m0 x1 hb yc7 ff4 fs7 fc0 sc0 ls0 ws0">several<span class="_ _e"> </span>integer/unsigned<span class="_ _e"> </span>a<span class="_ _5"></span>rithmetic<span class="_ _e"> </span>op<span class="_ _c"></span>erations</div><div class="t m0 xb hb yc8 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Signed<span class="_ _e"> </span>integer<span class="_ _e"> </span>overflo<span class="_ _5"></span>w/underflow</span></div><div class="t m0 xf he yc9 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span></span>int<span class="ffc fc8">>::<span class="fc0">max()<span class="_ _f"> </span></span>+<span class="_ _f"> </span>20<span class="fc0">;</span></span></div><div class="t m0 xb hb yca ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Mo<span class="_ _5"></span>re<span class="_ _e"> </span>negative<span class="_ _e"> </span>values<span class="_ _e"> </span>than<span class="_ _e"> </span>p<span class="_ _c"></span>ositive</span></div><div class="t m0 xf he ycb ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span></span>int<span class="ffc fc8">>::<span class="fc0">max()<span class="_ _f"> </span></span>*<span class="_ _f"> </span>-1<span class="fc0">;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _27"> </span>(2ˆ31<span class="_ _a"> </span>-1)<span class="_ _f"> </span>*<span class="_ _f"> </span>-1</span></span></span></div><div class="t m0 xf he ycc ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>x;<span class="_ _32"> </span><span class="ffe fc9">//<span class="_ _27"> </span>-2ˆ31<span class="_ _f"> </span>+1<span class="_ _a"> </span>ok</span></div><div class="t m0 xf he ycd ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">y<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span></span>int<span class="ffc fc8">>::<span class="fc0">min()<span class="_ _f"> </span></span>*<span class="_ _f"> </span>-1<span class="fc0">;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _a"> </span>-2ˆ31<span class="_ _f"> </span>*<span class="_ _f"> </span>-1</span></span></span></div><div class="t m0 xf he yce ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>y;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>hard<span class="_ _f"> </span>to<span class="_ _f"> </span>see<span class="_ _a"> </span>in<span class="_ _f"> </span>complex<span class="_ _f"> </span>examples<span class="_ _f"> </span>//<span class="_ _a"> </span>2ˆ31<span class="_ _8"> </span>overflow!!</span></div><div class="t m0 xb he ycf ffc fs8 fc3 sc0 ls0 ws0">The<span class="_ _f"> </span>Usual<span class="_ _f"> </span>Arithmetic<span class="_ _a"> </span>Confusions</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">22/77</div><a class="l" href="https://shafik.github.io/c++/2021/12/30/usual_arithmetic_confusions.html"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:4.295000px;width:147.920000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf19" class="pf w0 h0" data-page-no="19"><div class="pc pc19 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _31"> </span>2/7</div><div class="t m0 xb hb y5f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Initialize<span class="_ _8"> </span><span class="ff4">an<span class="_ _e"> </span>integer<span class="_ _e"> </span>with<span class="_ _e"> </span>a<span class="_ _e"> </span>value<span class="_ _e"> </span>la<span class="_ _5"></span>rger<span class="_ _e"> </span>than<span class="_ _e"> </span>its<span class="_ _e"> </span>range<span class="_ _e"> </span>is<span class="_ _e"> </span>undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></span></div><div class="t m0 xf he yd0 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">z<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>3000000000</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="fcc">undefined<span class="_ _f"> </span>behavior!!</span></span></span></div><div class="t m0 x26 hd yd1 ff19 fs8 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff12">Bitwise<span class="_ _25"> </span>op<span class="_ _c"></span>erations<span class="_ _e"> </span><span class="ffb">on<span class="_ _12"> </span>signed<span class="_ _12"> </span>integer<span class="_ _12"> </span>types<span class="_ _12"> </span>is<span class="_ _d"> </span>undefined<span class="_ _12"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></span></div><div class="t m0 xf he yd2 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc0">y<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>1<span class="_ _f"> </span><<<span class="_ _f"> </span>12</span>;<span class="_ _33"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="fcc">undefined<span class="_ _f"> </span>behavior!!</span></span></span></div><div class="t m0 xb hb yd3 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Shift<span class="_ _8"> </span><span class="ff4">la<span class="_ _5"></span>rger<span class="_ _d"> </span>than<span class="_ _d"> </span>#bits<span class="_ _e"> </span>of<span class="_ _d"> </span>the<span class="_ _d"> </span>data<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="_ _12"> </span>is<span class="_ _e"> </span>undefined<span class="_ _d"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _d"> </span>even<span class="_ _d"> </span>for<span class="_ _d"> </span><span class="ff5">unsigned</span></span></span></div><div class="t m0 xf he yd4 ff5 fs8 fc7 sc0 ls0 ws0">unsigned<span class="_ _f"> </span><span class="ffc fc0">y<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>1u<span class="_ _f"> </span><<<span class="_ _f"> </span>32u</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _a"> </span><span class="fcc">undefined<span class="_ _f"> </span>behavior!!</span></span></span></div><div class="t m0 xb hb yd5 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _d"> </span>in<span class="_ _7"> </span>implicit<span class="_ _e"> </span>conversion</span></div><div class="t m0 xf he yd6 ff5 fs8 fc7 sc0 ls0 ws0">uint16_t<span class="_ _f"> </span><span class="ffc fc0">a<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>65535</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>0xFFFF</span></span></div><div class="t m0 xf he yd7 ff5 fs8 fc7 sc0 ls0 ws0">uint16_t<span class="_ _f"> </span><span class="ffc fc0">b<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>65535</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>0xFFFF<span class="_ _34"> </span>expected:<span class="_ _f"> </span>4<span class="fff">'</span>294<span class="fff">'</span>836<span class="fff">'</span>225</span></span></div><div class="t m0 xf he yd8 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(a<span class="_ _a"> </span><span class="fc8">*<span class="_ _f"> </span></span>b);<span class="_ _33"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span><span class="fff">'</span>-131071<span class="fff">'<span class="_ _f"> </span></span><span class="fcc">undefined<span class="_ _a"> </span>behavior!!<span class="_ _f"> </span></span>(int<span class="_ _f"> </span>overflow)</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">23/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf1a" class="pf w0 h0" data-page-no="1a"><div class="pc pc1a w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _8"> </span>-<span class="_ _8"> </span>Signed<span class="_ _8"> </span>Overflow<span class="_ _8"> </span>Example<span class="_ _8"> </span>1<span class="_ _35"> </span>3/7</div><div class="t m0 xe he yd9 ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><climits></span></div><div class="t m0 xe he yda ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><cstdio></span></div><div class="t m0 xe he ydb ff5 fs8 fc7 sc0 ls0 ws0">void<span class="_ _f"> </span><span class="ffc fc4">f<span class="fc0">(</span></span>int<span class="ffc fc8">*<span class="_ _f"> </span><span class="fc0">ptr,<span class="_ _a"> </span></span></span>int<span class="_ _f"> </span><span class="ffc fc0">pos)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he ydc ffc fs8 fc0 sc0 ls0 ws0">pos<span class="fc8">++</span>;</div><div class="t m0 x7 he ydd ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(pos<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span>0</span>)<span class="_ _33"> </span><span class="ffe fc9">//<span class="_ _8"> </span><--<span class="_ _a"> </span>the<span class="_ _f"> </span>compiler<span class="_ _f"> </span>could<span class="_ _f"> </span>assume<span class="_ _a"> </span>that<span class="_ _f"> </span>signed<span class="_ _f"> </span>overflow<span class="_ _f"> </span>never</span></span></div><div class="t m0 x2c he yde ff5 fs8 fcb sc0 ls0 ws0">return<span class="ffc fc0">;<span class="_ _2d"> </span><span class="ffe fc9">//<span class="_ _36"> </span>happen<span class="_ _f"> </span>and<span class="_ _f"> </span>"simplify"<span class="_ _a"> </span>the<span class="_ _f"> </span>condition<span class="_ _f"> </span>to<span class="_ _f"> </span>check</span></span></div><div class="t m0 x7 he ydf ffc fs8 fc0 sc0 ls0 ws0">ptr[pos]<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>0</span>;</div><div class="t m0 xe he ye0 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 xe he ye1 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc4">main<span class="fc0">()<span class="_ _f"> </span>{<span class="_ _37"> </span><span class="ffe fc9">//<span class="_ _f"> </span>the<span class="_ _f"> </span>code<span class="_ _a"> </span>compiled<span class="_ _f"> </span>with<span class="_ _f"> </span>optimizations,<span class="_ _f"> </span>e.g.<span class="_ _a"> </span>-O3</span></span></span></div><div class="t m0 x7 he ye2 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="ffc fc8">*<span class="_ _f"> </span><span class="fc0">tmp<span class="_ _f"> </span></span>=<span class="_ _a"> </span></span><span class="fcb">new<span class="_ _f"> </span></span>int<span class="ffc fc0">[<span class="fc8">10</span>];<span class="_ _27"> </span><span class="ffe fc9">//<span class="_ _f"> </span>leads<span class="_ _f"> </span>to<span class="_ _a"> </span>segmentation<span class="_ _f"> </span>faults<span class="_ _f"> </span>with<span class="_ _f"> </span>clang,<span class="_ _a"> </span>while</span></span></div><div class="t m0 x7 he ye3 ffc fs8 fc0 sc0 ls0 ws0">f(tmp,<span class="_ _f"> </span>INT_MAX);<span class="_ _2e"> </span><span class="ffe fc9">//<span class="_ _f"> </span>it<span class="_ _a"> </span>terminates<span class="_ _f"> </span>correctly<span class="_ _f"> </span>with<span class="_ _f"> </span>gcc</span></div><div class="t m0 x7 he ye4 ffc fs8 fc0 sc0 ls0 ws0">printf(<span class="fcd">"%d<span class="ff5 fce">\n</span>"</span>,<span class="_ _f"> </span>tmp[<span class="fc8">0</span>]);</div><div class="t m0 xe he ye5 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">24/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf1b" class="pf w0 h0" data-page-no="1b"><div class="pc pc1b w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _8"> </span>-<span class="_ _8"> </span>Signed<span class="_ _8"> </span>Overflow<span class="_ _8"> </span>Example<span class="_ _8"> </span>2<span class="_ _35"> </span>4/7</div><div class="t m0 x1 hd ye6 ffc fs8 fc0 sc0 ls0 ws0">s/open.c<span class="_ _12"> </span><span class="ffb">of<span class="_ _12"> </span>the<span class="_ _12"> </span>Linux<span class="_ _12"> </span>kernel</span></div><div class="t m0 xe he ye7 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc4">do_fallocate<span class="fc0">(...,<span class="_ _f"> </span>loff_t<span class="_ _a"> </span>offset,<span class="_ _f"> </span>loff_t<span class="_ _f"> </span>len)<span class="_ _f"> </span>{</span></span></div><div class="t m0 x7 he ye8 ffc fs8 fc0 sc0 ls0 ws0">inode<span class="_ _f"> </span><span class="fc8">*</span>inode<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>...;</div><div class="t m0 x7 he ye9 ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(offset<span class="_ _f"> </span><<span class="_ _a"> </span>0<span class="_ _f"> </span>||<span class="_ _f"> </span>len<span class="_ _f"> </span><=<span class="_ _a"> </span>0)</span></div><div class="t m0 x2c he yea ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc8">-<span class="fc0">EINVAL;</span></span></div><div class="t m0 x7 he yeb ffe fs8 fc9 sc0 ls0 ws0">/*<span class="_ _f"> </span>Check<span class="_ _f"> </span>for<span class="_ _a"> </span>wrap<span class="_ _f"> </span>through<span class="_ _f"> </span>zero<span class="_ _f"> </span>too<span class="_ _a"> </span>*/</div><div class="t m0 x7 he yec ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">((offset<span class="_ _f"> </span><span class="fc8">+<span class="_ _a"> </span></span>len<span class="_ _f"> </span><span class="fc8">><span class="_ _f"> </span></span>inode<span class="fc8">-></span>i_sb<span class="fc8">-></span>s_maxbytes)<span class="_ _f"> </span><span class="fc8">||<span class="_ _a"> </span></span>(offset<span class="_ _f"> </span>+<span class="_ _f"> </span>len<span class="_ _f"> </span><<span class="_ _a"> </span>0))</span></div><div class="t m0 x2c he yed ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc8">-<span class="fc0">EFBIG;<span class="_ _36"> </span><span class="ffe fc9">//<span class="_ _f"> </span>the<span class="_ _f"> </span>compiler<span class="_ _a"> </span>is<span class="_ _f"> </span>able<span class="_ _f"> </span>to<span class="_ _f"> </span>infer<span class="_ _a"> </span>that<span class="_ _8"> </span>both<span class="_ _a"> </span><span class="fff">'</span>offset<span class="fff">'<span class="_ _f"> </span></span>and</span></span></span></div><div class="t m0 x7 he yee ffc fs8 fc0 sc0 ls0 ws0">...<span class="_ _38"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="fff">'</span>len<span class="fff">'<span class="_ _f"> </span></span>are<span class="_ _a"> </span>non-negative<span class="_ _f"> </span>and<span class="_ _f"> </span>can<span class="_ _f"> </span>eliminate<span class="_ _a"> </span>this<span class="_ _f"> </span>check,</span></div><div class="t m0 xe he yef ffc fs8 fc0 sc0 ls0 ws0">}<span class="_ _39"> </span><span class="ffe fc9">//<span class="_ _f"> </span>without<span class="_ _f"> </span>verify<span class="_ _a"> </span>integer<span class="_ _f"> </span>overflow</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">25/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _8"> </span>-<span class="_ _8"> </span>Division<span class="_ _8"> </span>by<span class="_ _8"> </span>Zero<span class="_ _8"> </span>Example<span class="_ _3a"> </span>5/7</div><div class="t m0 x1 hd yf0 ffc fs8 fc0 sc0 ls0 ws0">src/backend/utils/adt/int8.c<span class="_ _12"> </span><span class="ffb">of<span class="_ _12"> </span>PostgreSQL</span></div><div class="t m0 xe he yf1 ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(arg2<span class="_ _f"> </span><span class="fc8">==<span class="_ _a"> </span>0</span>)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he yf2 ffc fs8 fc0 sc0 ls0 ws0">ereport(ERROR,<span class="_ _f"> </span>(errcode(ERRCODE_DIVISION_BY_ZERO),<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _a"> </span>the<span class="_ _f"> </span>compiler<span class="_ _f"> </span>is<span class="_ _f"> </span>not<span class="_ _a"> </span>aware</span></div><div class="t m0 x2e he yf3 ffc fs8 fc0 sc0 ls0 ws0">errmsg(<span class="fcd">"division<span class="_ _f"> </span>by<span class="_ _f"> </span>zero"</span>)));<span class="_ _3b"> </span><span class="ffe fc9">//<span class="_ _f"> </span>that<span class="_ _f"> </span>this<span class="_ _a"> </span>function</span></div><div class="t m0 xe he yf4 ffc fs8 fc0 sc0 ls0 ws0">}<span class="_ _3c"> </span><span class="ffe fc9">//<span class="_ _f"> </span>doesn<span class="fff">'</span>t<span class="_ _f"> </span>return</span></div><div class="t m0 xe he yf5 ffe fs8 fc9 sc0 ls0 ws0">/*<span class="_ _f"> </span>No<span class="_ _f"> </span>overflow<span class="_ _a"> </span>is<span class="_ _f"> </span>possible<span class="_ _f"> </span>*/</div><div class="t m0 xe he yf6 ffc fs8 fc0 sc0 ls0 ws0">PG_RETURN_INT32((int32)<span class="_ _f"> </span>arg1<span class="_ _f"> </span><span class="fc8">/<span class="_ _a"> </span></span>arg2);<span class="_ _1"> </span><span class="ffe fc9">//<span class="_ _a"> </span>the<span class="_ _f"> </span>compiler<span class="_ _f"> </span>assumes<span class="_ _f"> </span>that<span class="_ _a"> </span>the<span class="_ _8"> </span>divisor<span class="_ _a"> </span>is</span></div><div class="t m0 x2f he yf7 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>non-zero<span class="_ _f"> </span>and<span class="_ _a"> </span>can<span class="_ _f"> </span>move<span class="_ _f"> </span>this<span class="_ _f"> </span>statement<span class="_ _a"> </span>on</div><div class="t m0 x2f he yf8 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>the<span class="_ _f"> </span>top<span class="_ _23"> </span>(always<span class="_ _f"> </span>executed)</div><div class="t m0 xb he yf9 ffc fs8 fc3 sc0 ls0 ws0">Undefined<span class="_ _f"> </span>Behavior:<span class="_ _27"> </span>What<span class="_ _a"> </span>Happened<span class="_ _8"> </span>to<span class="_ _a"> </span>My<span class="_ _f"> </span>Code?</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">26/77</div><a class="l" href="https://cs.stanford.edu/~zhihao/papers/apsys12.pdf"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:2.861000px;width:218.531000px;height:13.444000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _8"> </span>-<span class="_ _8"> </span>Implicit<span class="_ _8"> </span>Overflow<span class="_ _8"> </span>Example<span class="_ _3d"> </span>6/7</div><div class="t m0 x1 hb yfa ff9 fs7 fc0 sc0 ls0 ws0">Even<span class="_ _e"> </span>w<span class="_ _5"></span>o<span class="_ _5"></span>rse<span class="_ _e"> </span>example:</div><div class="t m0 xe he yfb ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><iostream></span></div><div class="t m0 xe he yfc ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _f"> </span><span class="ffc fc4">main<span class="fc0">()<span class="_ _f"> </span>{</span></span></div><div class="t m0 x7 he yfd ff5 fs8 fcb sc0 ls0 ws0">for<span class="_ _f"> </span><span class="ffc fc0">(</span><span class="fc7">int<span class="_ _f"> </span><span class="ffc fc0">i<span class="_ _a"> </span><span class="fc8">=<span class="_ _f"> </span>0</span>;<span class="_ _f"> </span>i<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span>4</span>;<span class="_ _f"> </span><span class="fc8">++</span>i)</span></span></div><div class="t m0 x2c he yfe ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>i<span class="_ _a"> </span><span class="fc8">*<span class="_ _f"> </span>1000000000<span class="_ _f"> </span><<<span class="_ _f"> </span></span>std<span class="fc8">::</span>endl;</div><div class="t m0 xe he yff ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 xe he y100 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>with<span class="_ _f"> </span>optimizations,<span class="_ _a"> </span>it<span class="_ _f"> </span>is<span class="_ _f"> </span>an<span class="_ _f"> </span>infinite<span class="_ _a"> </span>loop</div><div class="t m0 xe he y101 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>--><span class="_ _f"> </span>1000000000<span class="_ _a"> </span>*<span class="_ _f"> </span>i<span class="_ _f"> </span>><span class="_ _f"> </span>INT_MAX</div><div class="t m0 xe he y102 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span><span class="fcc">undefined<span class="_ _f"> </span>behavior!!</span></div><div class="t m0 xe he y103 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>the<span class="_ _f"> </span>compiler<span class="_ _a"> </span>translates<span class="_ _f"> </span>the<span class="_ _f"> </span>multiplication<span class="_ _f"> </span>constant<span class="_ _a"> </span>into<span class="_ _f"> </span>an<span class="_ _f"> </span>addition</div><div class="t m0 xb he y104 ffc fs8 fc3 sc0 ls0 ws0">Why<span class="_ _f"> </span>does<span class="_ _f"> </span>this<span class="_ _a"> </span>loop<span class="_ _f"> </span>produce<span class="_ _f"> </span>undefined<span class="_ _f"> </span>behavior?</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">27/77</div><a class="l" href="https://stackoverflow.com/questions/24296571/why-does-this-loop-produce-warning-iteration-3u-invokes-undefined-behavior-an/24297811#24297811"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:0.617000px;width:218.531000px;height:13.444000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h15 y7 ff1 fs3 fc1 sc0 ls0 ws0">Undefined<span class="_ _8"> </span>Behavior<span class="_ _8"> </span>-<span class="_ _8"> </span>Common<span class="_ _8"> </span>Lo<span class="_ _c"></span>ops<span class="_ _3e"> </span><span class="ff18"><span class="_ _8"> </span></span>7/7</div><div class="t m0 x1 hb y105 ff1 fs7 fc0 sc0 ls0 ws0">Is<span class="_ _7"> </span>the<span class="_ _7"> </span>following<span class="_ _e"> </span>lo<span class="_ _c"></span>op<span class="_ _7"> </span>safe?</div><div class="t m0 xe he y106 ff5 fs8 fc7 sc0 ls0 ws0">void<span class="_ _f"> </span><span class="ffc fc4">f<span class="fc0">(</span></span>int<span class="_ _f"> </span><span class="ffc fc0">size)<span class="_ _a"> </span>{</span></div><div class="t m0 x7 he y107 ff5 fs8 fcb sc0 ls0 ws0">for<span class="_ _f"> </span><span class="ffc fc0">(</span><span class="fc7">int<span class="_ _f"> </span><span class="ffc fc0">i<span class="_ _a"> </span><span class="fc8">=<span class="_ _f"> </span>1</span>;<span class="_ _f"> </span>i<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span></span>size;<span class="_ _f"> </span>i<span class="_ _f"> </span><span class="fc8">+=<span class="_ _f"> </span>2</span>)</span></span></div><div class="t m0 x2c he y108 ffc fs8 fc0 sc0 ls0 ws0">...</div><div class="t m0 xe he y109 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 xb hb y10a ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">What<span class="_ _e"> </span>happ<span class="_ _c"></span>ens<span class="_ _d"> </span>if<span class="_ _21"> </span><span class="ffa">size<span class="_ _21"> </span></span>is<span class="_ _e"> </span>equal<span class="_ _e"> </span>to<span class="_ _21"> </span><span class="ffa">INT<span class="_ _8"> </span>MAX<span class="_ _12"> </span></span>?</span></div><div class="t m0 xb hb y10b ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Ho<span class="_ _5"></span>w<span class="_ _e"> </span>to<span class="_ _e"> </span>make<span class="_ _d"> </span>the<span class="_ _e"> </span>previous<span class="_ _d"> </span>lo<span class="_ _c"></span>op<span class="_ _e"> </span>safe?</span></div><div class="t m0 xb hb y10c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _11"> </span><span class="ffa">i<span class="_ _18"> </span>>=<span class="_ _18"> </span>0<span class="_ _18"> </span>&&<span class="_ _18"> </span>i<span class="_ _18"> </span><<span class="_ _18"> </span>size<span class="_ _21"> </span><span class="ff4">is<span class="_ _e"> </span>not<span class="_ _e"> </span>the<span class="_ _e"> </span>solution<span class="_ _e"> </span>b<span class="_ _c"></span>ecause<span class="_ _d"> </span>of<span class="_ _e"> </span><span class="ff9">undefined<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _a"> </span><span class="ff4">of</span></span></span></span></div><div class="t m0 x7 hb y10d ff4 fs7 fc0 sc0 ls0 ws0">signed<span class="_ _e"> </span>overflo<span class="_ _5"></span>w</div><div class="t m0 xb hb y10e ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Can<span class="_ _e"> </span>w<span class="_ _5"></span>e<span class="_ _e"> </span>generalize<span class="_ _e"> </span>the<span class="_ _e"> </span>solution<span class="_ _e"> </span>when<span class="_ _e"> </span>the<span class="_ _e"> </span>increment<span class="_ _e"> </span>is<span class="_ _21"> </span><span class="ffa">i<span class="_ _18"> </span>+=<span class="_ _18"> </span>step<span class="_ _12"> </span></span>?</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">28/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Overflo<span class="_ _5"></span>w<span class="_ _8"> </span>/<span class="_ _f"> </span>Underflo<span class="_ _5"></span>w</div><div class="t m0 x1 hb y10f ff4 fs7 fc0 sc0 ls0 ws0">Detecting<span class="_ _e"> </span>wrapa<span class="_ _5"></span>round<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span>unsigned<span class="_ _e"> </span>integral<span class="_ _e"> </span>types<span class="_ _e"> </span>is<span class="_ _e"> </span><span class="ff1">not<span class="_ _7"> </span>trivial</span></div><div class="t m0 xe he y110 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>some<span class="_ _f"> </span>examples</div><div class="t m0 xe he y111 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc4">is_add_overflow<span class="fc0">(</span></span>unsigned<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>unsigned<span class="_ _f"> </span><span class="ffc fc0">b)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he y112 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc0">(a<span class="_ _f"> </span><span class="fc8">+<span class="_ _a"> </span></span>b)<span class="_ _f"> </span><span class="fc8"><<span class="_ _f"> </span></span>a<span class="_ _f"> </span><span class="fc8">||<span class="_ _a"> </span></span>(a<span class="_ _f"> </span><span class="fc8">+<span class="_ _f"> </span></span>b)<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span></span>b;</span></div><div class="t m0 xe he y113 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 xe he y114 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc4">is_mul_overflow<span class="fc0">(</span></span>unsigned<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>unsigned<span class="_ _f"> </span><span class="ffc fc0">b)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he y115 ff5 fs8 fc7 sc0 ls0 ws0">unsigned<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>a<span class="_ _f"> </span><span class="fc8">*<span class="_ _f"> </span></span>b;</span></div><div class="t m0 x7 he y116 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc0">a<span class="_ _f"> </span><span class="fc8">!=<span class="_ _a"> </span>0<span class="_ _f"> </span>&&<span class="_ _f"> </span></span>(x<span class="_ _f"> </span><span class="fc8">/<span class="_ _a"> </span></span>a)<span class="_ _f"> </span><span class="fc8">!=<span class="_ _f"> </span></span>b;</span></div><div class="t m0 xe he y117 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x1 hb y118 ff4 fs7 fc0 sc0 ls0 ws0">Detecting<span class="_ _e"> </span>overflo<span class="_ _5"></span>w/underflo<span class="_ _5"></span>w<span class="_ _e"> </span>for<span class="_ _d"> </span>signed<span class="_ _e"> </span>integral<span class="_ _e"> </span>types<span class="_ _e"> </span>is<span class="_ _e"> </span>even<span class="_ _e"> </span>harder<span class="_ _d"> </span>and<span class="_ _e"> </span>must<span class="_ _e"> </span>b<span class="_ _c"></span>e</div><div class="t m0 x1 hb y119 ff4 fs7 fc0 sc0 ls0 ws0">check<span class="_ _5"></span>ed<span class="_ _e"> </span>b<span class="_ _c"></span>efo<span class="_ _5"></span>re<span class="_ _d"> </span>p<span class="_ _c"></span>erforming<span class="_ _d"> </span>the<span class="_ _e"> </span>op<span class="_ _c"></span>eration</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">29/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 xa h2 y11a ff1 fs0 fc0 sc0 ls0 ws0">Floating-p<span class="_ _0"></span>oint<span class="_ _1"> </span>T<span class="_ _10"></span>yp<span class="_ _0"></span>es</div><div class="t m0 xa h2 y11b ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>Arithmetic</div><a class="l" href="#pf20" data-dest-detail='[32,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:105.775000px;bottom:149.618000px;width:241.993000px;height:24.025000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf20" data-dest-detail='[32,"XYZ",27.346,256.118,null]'><div class="d m1" style="border-style:none;position:absolute;left:105.775000px;bottom:120.066000px;width:172.196000px;height:19.206000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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KI+TYfCk/s3xhYTXbGQS49nYvXjM6Gw/ubxVGK+0HIsXT8xMbsmW3704JbM9fSRlsbFZ0NhbYiW35ymzoTSY3u3tNaOxFL1dcyG8vq9A5ncf8TrK5uY6szW+kPU1Ri7srX+EHXW73AqlNaPPBv/9qnT02Gx//vDlfKbHc03jxyfCZWNf9Gf+ipzpCPduMvybK0/RB318cSa7NITI3OZ1vpdZ0Kpb2RHbaxUf8zETGe28vTuuUz9llMnQql/73Dr4XK8ccMV2Vp/iNob48psrT9EbfVfdTKU+/4yCl9Xj7akGlesytb6Q9TaGLuztf4QtTTG1dlaf4gyjfGubK0/RM2NcU221h+ixo+Z7sxWB0JUv/PU6VB6ZmRrcaypvvjjJ0Nl08GBG9eTXYl8eay5sYLprmx1IETL6ms8G8pP73n6cONPTUwvz1YHQpSsn54K5W3RYL6tFBa+ffeT06G8NRrMt4XE4i1v/vjpUNk0NDgfKl3jTY1LT4Xy5qHBxUxuLFZ/l5Mzobxl93D8SLmp8cwV2epAiBL1VzkTFgcOPt1US1RKY40vZGJ2dba8+eC2+PX8tVQ6Xvp2MROzd2XLm+pn2lPl2z7F7mz5uYPb4tfj+aZbj0+vzFYHQtR4i9OrstWBENWXM3UylAaGduSa/73x1qZmQ2nryMhbqaX6Lzgdys/v3hgqk0ttjVt0Z6sDIao/YGo6lAZ3Ds4tvd3S+GKnQmn7S9tGF5c1/sDqbHUgRKEx3pWtDoSo1hjXZKsDIao2PtTO7NLOEC0d+F9qOfya1WTZ+wAAAABJRU5ErkJggg=="/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">IEEE<span class="_ _8"> </span>Floating-Point<span class="_ _8"> </span>Standa<span class="_ _5"></span>rd</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">IEEE754<span class="_ _e"> </span><span class="ff4">is<span class="_ _e"> </span>the<span class="_ _e"> </span>technical<span class="_ _e"> </span>standa<span class="_ _5"></span>rd<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _e"> </span>a<span class="_ _5"></span>rithmetic</span></div><div class="t m0 x1 hb y11c ff4 fs7 fc0 sc0 ls0 ws0">The<span class="_ _e"> </span>standa<span class="_ _5"></span>rd<span class="_ _e"> </span>defines<span class="_ _e"> </span>the<span class="_ _e"> </span>bina<span class="_ _5"></span>ry<span class="_ _e"> </span>format,<span class="_ _d"> </span>op<span class="_ _c"></span>erations<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r,<span class="_ _d"> </span>rounding<span class="_ _e"> </span>rules,<span class="_ _e"> </span>exception</div><div class="t m0 x1 hb y11d ff4 fs7 fc0 sc0 ls0 ws0">handling,<span class="_ _e"> </span>etc.</div><div class="t m0 x11 h6 y11e ff9 fs4 fc0 sc0 ls0 ws0">First<span class="_ _d"> </span>Release<span class="_ _28"> </span><span class="ff4">:<span class="_ _8"> </span>1985</span></div><div class="t m0 x26 h6 y11f ff9 fs4 fc0 sc0 ls0 ws0">Second<span class="_ _d"> </span>Release<span class="_ _28"> </span><span class="ff4">:<span class="_ _8"> </span>2008.<span class="_ _f"> </span>A<span class="_ _5"></span>dd<span class="_ _d"> </span>16-bit,<span class="_ _d"> </span>128-bit,<span class="_ _d"> </span>256-bit<span class="_ _d"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _12"> </span>types</span></div><div class="t m0 x30 h6 y120 ff9 fs4 fc0 sc0 ls0 ws0">Third<span class="_ _d"> </span>Release<span class="_ _28"> </span><span class="ff4">:<span class="_ _8"> </span>2019.<span class="_ _f"> </span>Sp<span class="_ _c"></span>ecify<span class="_ _d"> </span><span class="ffa">min/max<span class="_ _d"> </span></span>behavior</span></div><div class="t m0 x31 h6 y121 ff4 fs4 fc0 sc0 ls0 ws0">see<span class="_ _4"> </span><span class="ffa">The<span class="_ _a"> </span>IEEE<span class="_ _4"> </span>Standard<span class="_ _a"> </span>754:<span class="_ _3f"> </span>One<span class="_ _a"> </span>for<span class="_ _4"> </span>the<span class="_ _a"> </span>History<span class="_ _a"> </span>Books</span></div><div class="t m0 x1 hb y122 ff4 fs7 fc0 sc0 ls0 ws0">IEEE754<span class="_ _e"> </span>technical<span class="_ _e"> </span>do<span class="_ _c"></span>cument:</div><div class="t m0 x1 hc y123 ffa fs4 fc0 sc0 ls0 ws0">754-2019<span class="_ _a"> </span>-<span class="_ _4"> </span>IEEE<span class="_ _a"> </span>Standard<span class="_ _a"> </span>for<span class="_ _4"> </span>Floating-Point<span class="_ _a"> </span>Arithmetic</div><div class="t m0 x1 hb y124 ff4 fs7 fc0 sc0 ls0 ws0">In<span class="_ _e"> </span>general,<span class="_ _e"> </span><span class="ff1">C/C++<span class="_ _7"> </span>adopts<span class="_ _7"> </span>IEEE754<span class="_ _8"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _e"> </span>standard</span>:</div><div class="t m0 x1 hc y125 ffa fs4 fc0 sc0 ls0 ws0">en.cppreference.com/w/cpp/types/numeric<span class="_ _e"> </span>limits/is<span class="_ _7"> </span>iec559</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">30/77</div><a class="l" href="https://www.computer.org/csdl/magazine/co/2019/12/08909942/1f8KFWxbTCU"><div class="d m1" style="border-style:none;position:absolute;left:107.051000px;bottom:104.407000px;width:258.281000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://ieeexplore.ieee.org/document/8766229"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:62.310000px;width:284.433000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://en.cppreference.com/w/cpp/types/numeric_limits/is_iec559"><div class="d m1" style="border-style:none;position:absolute;left:27.350000px;bottom:20.712000px;width:291.964000px;height:11.125000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">32/64-bit<span class="_ _8"> </span>Floating-Point</div><div class="t m0 x1 hb y126 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">IEEE754<span class="_ _7"> </span>Single-precision<span class="_ _d"> </span><span class="ff4">(32-bit)<span class="_ _21"> </span><span class="ffa">float</span></span></span></div><div class="t m0 x12 hb y127 ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y128 ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x33 hb y127 ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _d"> </span><span class="ff4">(or<span class="_ _d"> </span>base)</span></div><div class="t m0 x1b h16 y128 ffa fs7 fc0 sc0 ls0 ws0">8-bit</div><div class="t m0 x34 hb y127 ff1 fs7 fc0 sc0 ls0 ws0">Mantissa<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span>significant)</span></div><div class="t m0 x35 h16 y128 ffa fs7 fc0 sc0 ls0 ws0">23-bit</div><div class="t m0 x1 hb y129 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">IEEE754<span class="_ _7"> </span>Double-precision<span class="_ _d"> </span><span class="ff4">(64-bit)<span class="_ _21"> </span><span class="ffa">double</span></span></span></div><div class="t m0 x12 hb y12a ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y12b ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x33 hb y12a ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _d"> </span><span class="ff4">(or<span class="_ _d"> </span>base)</span></div><div class="t m0 x36 h16 y12b ffa fs7 fc0 sc0 ls0 ws0">11-bit</div><div class="t m0 x34 hb y12a ff1 fs7 fc0 sc0 ls0 ws0">Mantissa<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span>significant)</span></div><div class="t m0 x35 h16 y12b ffa fs7 fc0 sc0 ls0 ws0">52-bit</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">31/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">128/256-bit<span class="_ _8"> </span>Floating-Point</div><div class="t m0 x1 hb y12c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">IEEE754<span class="_ _7"> </span>Quad-Precision<span class="_ _e"> </span><span class="ff4">(128-bit)<span class="_ _21"> </span><span class="ffa">std::float128<span class="_ _21"> </span></span><span class="fc6">C++23</span></span></span></div><div class="t m0 x12 hb y12d ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y12e ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x33 hb y12d ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _d"> </span><span class="ff4">(or<span class="_ _d"> </span>base)</span></div><div class="t m0 x36 h16 y12e ffa fs7 fc0 sc0 ls0 ws0">15-bit</div><div class="t m0 x34 hb y12d ff1 fs7 fc0 sc0 ls0 ws0">Mantissa<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span>significant)</span></div><div class="t m0 x37 h16 y12e ffa fs7 fc0 sc0 ls0 ws0">112-bit</div><div class="t m0 x1 hb y12f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">IEEE754<span class="_ _7"> </span>Octuple-Precision<span class="_ _e"> </span><span class="ff4">(256-bit)<span class="_ _e"> </span>(not<span class="_ _e"> </span>standardized<span class="_ _d"> </span>in<span class="_ _e"> </span>C++)</span></span></div><div class="t m0 x12 hb y130 ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y131 ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x33 hb y130 ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _d"> </span><span class="ff4">(or<span class="_ _d"> </span>base)</span></div><div class="t m0 x36 h16 y131 ffa fs7 fc0 sc0 ls0 ws0">19-bit</div><div class="t m0 x34 hb y130 ff1 fs7 fc0 sc0 ls0 ws0">Mantissa<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span>significant)</span></div><div class="t m0 x37 h16 y131 ffa fs7 fc0 sc0 ls0 ws0">236-bit</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">32/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">16-bit<span class="_ _8"> </span>Floating-Point</div><div class="t m0 x1 hb y132 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">IEEE754<span class="_ _7"> </span>16-bit<span class="_ _7"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _e"> </span><span class="ff4">(<span class="_ _12"> </span><span class="ffa">std::binary16<span class="_ _12"> </span></span>)<span class="_ _e"> </span><span class="fc6">C++23<span class="_ _e"> </span></span><span class="ff7">→<span class="_ _e"> </span></span>GPU,<span class="_ _e"> </span>Arm7</span></span></div><div class="t m0 x12 hb y133 ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y134 ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x38 hb y133 ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent</div><div class="t m0 x1b h16 y134 ffa fs7 fc0 sc0 ls0 ws0">5-bit</div><div class="t m0 x39 hb y133 ff1 fs7 fc0 sc0 ls0 ws0">Mantissa</div><div class="t m0 x35 h16 y134 ffa fs7 fc0 sc0 ls0 ws0">10-bit</div><div class="t m0 x1 hb y135 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff1">Go<span class="_ _c"></span>ogle<span class="_ _7"> </span>16-bit<span class="_ _7"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _e"> </span><span class="ff4">(<span class="_ _12"> </span><span class="ffa">std::bfloat16<span class="_ _25"> </span></span>)<span class="_ _e"> </span><span class="fc6">C++23<span class="_ _e"> </span></span><span class="ff7">→<span class="_ _e"> </span></span>TPU,<span class="_ _e"> </span>GPU,<span class="_ _e"> </span>Arm8</span></span></div><div class="t m0 x12 hb y136 ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y137 ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x38 hb y136 ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent</div><div class="t m0 x1b h16 y137 ffa fs7 fc0 sc0 ls0 ws0">8-bit</div><div class="t m0 x39 hb y136 ff1 fs7 fc0 sc0 ls0 ws0">Mantissa</div><div class="t m0 x3a h16 y137 ffa fs7 fc0 sc0 ls0 ws0">7-bit</div><div class="t m0 xb he y138 ffc fs8 fc3 sc0 ls0 ws0">half-precision-arithmetic-fp16-versus-bfloat16</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">33/77</div><a class="l" href="https://nickhigham.wordpress.com/2018/12/03/half-precision-arithmetic-fp16-versus-bfloat16/"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:0.627000px;width:218.531000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">8-bit<span class="_ _8"> </span>Floating-Point<span class="_ _8"> </span>(Non-Standa<span class="_ _5"></span>rdized<span class="_ _8"> </span>in<span class="_ _8"> </span>C++/IEEE)</div><div class="t m0 x1 hb y139 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _21"> </span><span class="ffa">E4M3</span></div><div class="t m0 x12 hb y13a ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y13b ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x38 hb y13a ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent</div><div class="t m0 x1b h16 y13b ffa fs7 fc0 sc0 ls0 ws0">4-bit</div><div class="t m0 x39 hb y13a ff1 fs7 fc0 sc0 ls0 ws0">Mantissa</div><div class="t m0 x3a h16 y13b ffa fs7 fc0 sc0 ls0 ws0">3-bit</div><div class="t m0 x1 hb y13c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _21"> </span><span class="ffa">E5M2</span></div><div class="t m0 x12 hb y13d ff1 fs7 fc0 sc0 ls0 ws0">Sign</div><div class="t m0 x32 h16 y13e ffa fs7 fc0 sc0 ls0 ws0">1-bit</div><div class="t m0 x38 hb y13d ff1 fs7 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent</div><div class="t m0 x1b h16 y13e ffa fs7 fc0 sc0 ls0 ws0">5-bit</div><div class="t m0 x39 hb y13d ff1 fs7 fc0 sc0 ls0 ws0">Mantissa</div><div class="t m0 x3a h16 y13e ffa fs7 fc0 sc0 ls0 ws0">2-bit</div><div class="t m0 x26 hd y13f ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">Floating<span class="_ _f"> </span>Point<span class="_ _a"> </span>Formats<span class="_ _8"> </span>for<span class="_ _a"> </span>Machine<span class="_ _f"> </span>Learning<span class="ffb">,<span class="_ _12"> </span><span class="ff12">IEEE<span class="_ _12"> </span>draft</span></span></span></div><div class="t m0 x26 hd y140 ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">FP8<span class="_ _f"> </span>Formats<span class="_ _a"> </span>for<span class="_ _8"> </span>Deep<span class="_ _a"> </span>Learning<span class="ffb">,<span class="_ _25"> </span><span class="ff12">Intel,<span class="_ _12"> </span>Nvidia,<span class="_ _d"> </span>Arm</span></span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">34/77</div><a class="l" href="https://github.com/P3109/Public/blob/main/Shared%20Reports/P3109%20WG%20Interim%20report.pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:19.136000px;width:251.453000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://arxiv.org/pdf/2209.05433.pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:4.541000px;width:213.468000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Other<span class="_ _8"> </span>Real<span class="_ _f"> </span>V<span class="_ _5"></span>alue<span class="_ _8"> </span>Rep<span class="_ _5"></span>resentations<span class="_ _8"> </span>(Non-standardized<span class="_ _8"> </span>in<span class="_ _8"> </span>C++/IEEE)<span class="_ _40"> </span>1/2</div><div class="t m0 xb hb y141 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">T<span class="_ _6"></span>enso<span class="_ _5"></span>rFloat-32<span class="_ _7"> </span>(TF32)<span class="_ _e"> </span><span class="ff4">Sp<span class="_ _c"></span>ecialized<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>format<span class="_ _d"> </span>for<span class="_ _d"> </span>deep<span class="_ _e"> </span>learning</span></span></div><div class="t m0 x7 hb y142 ff4 fs7 fc0 sc0 ls0 ws0">applications</div><div class="t m0 xb hb y143 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">P<span class="_ _5"></span>osit<span class="_ _d"> </span><span class="ff4">(John<span class="_ _e"> </span>Gustafson,<span class="_ _e"> </span>2017),<span class="_ _e"> </span>also<span class="_ _d"> </span>called<span class="_ _e"> </span><span class="ff9">unum<span class="_ _e"> </span>I<span class="_ _c"></span>II<span class="_ _f"> </span></span>(<span class="ff9">universal<span class="_ _d"> </span>numb<span class="_ _c"></span>er<span class="_ _41"></span></span>),<span class="_ _d"> </span>represents</span></span></div><div class="t m0 x7 hb y144 ff4 fs7 fc0 sc0 ls0 ws0">floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>values<span class="_ _e"> </span>with<span class="_ _e"> </span><span class="ff9">variable-width<span class="_ _e"> </span></span>of<span class="_ _e"> </span>exp<span class="_ _c"></span>onent<span class="_ _e"> </span>and<span class="_ _e"> </span>mantissa.</div><div class="t m0 x7 hb y145 ff4 fs7 fc0 sc0 ls0 ws0">It<span class="_ _e"> </span>is<span class="_ _e"> </span>implemented<span class="_ _e"> </span>in<span class="_ _e"> </span>exp<span class="_ _c"></span>erimental<span class="_ _d"> </span>platforms</div><div class="t m0 x26 hd y146 ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">NVIDIA<span class="_ _f"> </span>Hopper<span class="_ _a"> </span>Architecture<span class="_ _8"> </span>In-Depth</span></div><div class="t m0 x26 hd y147 ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">Beating<span class="_ _f"> </span>Floating<span class="_ _a"> </span>Point<span class="_ _8"> </span>at<span class="_ _a"> </span>its<span class="_ _f"> </span>Own<span class="_ _f"> </span>Game:<span class="_ _27"> </span>Posit<span class="_ _f"> </span>Arithmetic</span></div><div class="t m0 x26 hd y148 ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">Posits,<span class="_ _f"> </span>a<span class="_ _a"> </span>New<span class="_ _8"> </span>Kind<span class="_ _a"> </span>of<span class="_ _f"> </span>Number,<span class="_ _f"> </span>Improves<span class="_ _f"> </span>the<span class="_ _a"> </span>Math<span class="_ _f"> </span>of<span class="_ _f"> </span>AI</span></div><div class="t m0 x26 hd y149 ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">Comparing<span class="_ _f"> </span>posit<span class="_ _a"> </span>and<span class="_ _8"> </span>IEEE-754<span class="_ _a"> </span>hardware<span class="_ _f"> </span>cost</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">35/77</div><a class="l" href="https://developer.nvidia.com/blog/nvidia-hopper-architecture-in-depth/"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:41.755000px;width:166.750000px;height:9.366000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.johngustafson.net/pdfs/BeatingFloatingPoint.pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:29.153000px;width:270.311000px;height:9.365000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://spectrum.ieee.org/floating-point-numbers-posits-processor"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:16.550000px;width:251.482000px;height:9.365000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://hal.archives-ouvertes.fr/hal-03195756v3/document"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:3.947000px;width:199.701000px;height:9.366000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Other<span class="_ _8"> </span>Real<span class="_ _f"> </span>V<span class="_ _5"></span>alue<span class="_ _8"> </span>Rep<span class="_ _5"></span>resentations<span class="_ _8"> </span>(Non-standardized<span class="_ _8"> </span>in<span class="_ _8"> </span>C++/IEEE)<span class="_ _40"> </span>2/2</div><div class="t m0 xb hb y141 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Microscaling<span class="_ _7"> </span>Fo<span class="_ _5"></span>rmats<span class="_ _e"> </span>(MX)<span class="_ _e"> </span><span class="ff4">Sp<span class="_ _c"></span>ecification<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span>low-p<span class="_ _5"></span>recision<span class="_ _d"> </span>floating-p<span class="_ _c"></span>oint</span></span></div><div class="t m0 x7 hb y142 ff4 fs7 fc0 sc0 ls0 ws0">fo<span class="_ _5"></span>rmats<span class="_ _e"> </span>defined<span class="_ _e"> </span>b<span class="_ _5"></span>y<span class="_ _e"> </span>AMD,<span class="_ _e"> </span>Arm,<span class="_ _e"> </span>Intel,<span class="_ _e"> </span>Meta,<span class="_ _e"> </span>Microsoft,<span class="_ _e"> </span>NVIDIA,<span class="_ _e"> </span>and<span class="_ _e"> </span>Qualcomm.</div><div class="t m0 x7 hb y14a ff4 fs7 fc0 sc0 ls0 ws0">It<span class="_ _e"> </span>includes<span class="_ _e"> </span>FP8,<span class="_ _e"> </span>FP6,<span class="_ _e"> </span>FP4,<span class="_ _e"> </span>(MX)INT8</div><div class="t m0 xb hb y144 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Fixed-p<span class="_ _c"></span>oint<span class="_ _e"> </span><span class="ff4">rep<span class="_ _5"></span>resentation<span class="_ _e"> </span>has<span class="_ _e"> </span>a<span class="_ _e"> </span>fixed<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>of<span class="_ _e"> </span>digits<span class="_ _e"> </span>after<span class="_ _e"> </span>the<span class="_ _e"> </span>radix<span class="_ _e"> </span>p<span class="_ _c"></span>oint</span></span></div><div class="t m0 x7 hb y145 ff4 fs7 fc0 sc0 ls0 ws0">(decimal<span class="_ _d"> </span>p<span class="_ _c"></span>oint).<span class="_ _f"> </span>The<span class="_ _e"> </span>gaps<span class="_ _d"> </span>b<span class="_ _c"></span>et<span class="_ _5"></span>ween<span class="_ _12"> </span>adjacent<span class="_ _e"> </span>numb<span class="_ _c"></span>ers<span class="_ _d"> </span>a<span class="_ _5"></span>re<span class="_ _d"> </span>alwa<span class="_ _5"></span>ys<span class="_ _d"> </span>equal.<span class="_ _a"> </span>The<span class="_ _12"> </span>range</div><div class="t m0 x7 hb y14b ff4 fs7 fc0 sc0 ls0 ws0">of<span class="_ _e"> </span>their<span class="_ _e"> </span>values<span class="_ _e"> </span>is<span class="_ _e"> </span>significantly<span class="_ _e"> </span>limited<span class="_ _e"> </span>compa<span class="_ _5"></span>red<span class="_ _e"> </span>to<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>numb<span class="_ _c"></span>ers.</div><div class="t m0 x7 hb y14c ff4 fs7 fc0 sc0 ls0 ws0">It<span class="_ _e"> </span>is<span class="_ _e"> </span>widely<span class="_ _e"> </span>used<span class="_ _e"> </span>on<span class="_ _e"> </span>emb<span class="_ _c"></span>edded<span class="_ _d"> </span>systems</div><div class="t m0 x26 hd y14d ff19 fs8 fc3 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffc">OCP<span class="_ _f"> </span>Microscaling<span class="_ _a"> </span>Formats<span class="_ _8"> </span>(MX)<span class="_ _a"> </span>Specification</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">36/77</div><a class="l" href="https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:4.615000px;width:204.408000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf28" class="pf w0 h0" data-page-no="28"><div class="pc pc28 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Rep<span class="_ _5"></span>resentation<span class="_ _42"> </span>1/2</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _7"> </span>numb<span class="_ _c"></span>er<span class="ff4">:</span></div><div class="t m0 xb hb y14e ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Radix<span class="_ _f"> </span><span class="ff4">(or<span class="_ _d"> </span>base):<span class="_ _a"> </span><span class="ff1a">β</span></span></span></div><div class="t m0 xb hb y81 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Precision<span class="_ _e"> </span><span class="ff4">(or<span class="_ _d"> </span>digits):<span class="_ _a"> </span></span>p</span></div><div class="t m0 xb hb y14f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Exp<span class="_ _c"></span>onent<span class="_ _8"> </span><span class="ff4">(magnitude):<span class="_ _a"> </span></span>e</span></div><div class="t m0 xb hb y150 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Mantissa<span class="_ _c"></span><span class="ff4">:<span class="_ _f"> </span></span>M</span></div><div class="t m0 x1 hb y151 ff9 fs7 fc0 sc0 ls0 ws0">n<span class="_ _12"> </span><span class="ff4">=<span class="_ _43"> </span></span>M</div><div class="t m0 x11 h17 y152 ff1b fs4 fc0 sc0 ls0 ws0">|{z}</div><div class="t m0 x1a h10 y153 ff10 fs5 fc0 sc0 ls0 ws0">p</div><div class="t m0 x2c hb y151 ff7 fs7 fc0 sc0 ls0 ws0">×<span class="ff1a">β</span></div><div class="t m0 x3b h10 y154 ff10 fs5 fc0 sc0 ls0 ws0">e</div><div class="t m0 x3c hb y151 ff7 fs7 fc0 sc0 ls0 ws0">→<span class="_ _44"> </span><span class="ff4">IEEE754:<span class="_ _a"> </span>1<span class="ff1a">.<span class="ff9">M<span class="_ _12"> </span></span></span></span>×<span class="_ _13"> </span><span class="ff4">2</span></div><div class="t m0 x3d h10 y154 ff10 fs5 fc0 sc0 ls0 ws0">e</div><div class="t m0 xe he y155 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _27"> </span><span class="ffc fc0">f1<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>1.3f</span>;<span class="_ _45"> </span><span class="ffe fc9">//<span class="_ _f"> </span>1.3</span></span></div><div class="t m0 xe hd y156 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _27"> </span><span class="ffc fc0">f2<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>1.1e2f</span>;<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _a"> </span><span class="ffb">1<span class="ff14">.</span>1<span class="_ _14"> </span><span class="ff13">·<span class="_ _13"> </span></span>10</span></span></span></div><div class="t m0 x3e h13 y157 ff6 fs9 fc9 sc0 ls0 ws0">2</div><div class="t m0 xe hd y158 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _27"> </span><span class="ffc fc0">f3<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>3.7E4f</span>;<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _a"> </span><span class="ffb">3<span class="ff14">.</span>7<span class="_ _14"> </span><span class="ff13">·<span class="_ _13"> </span></span>10</span></span></span></div><div class="t m0 x3e h13 y159 ff6 fs9 fc9 sc0 ls0 ws0">4</div><div class="t m0 xe he y15a ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _27"> </span><span class="ffc fc0">f4<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>.3f</span>;<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _f"> </span>0.3</span></span></div><div class="t m0 xe he y15b ff5 fs8 fc7 sc0 ls0 ws0">double<span class="_ _f"> </span><span class="ffc fc0">d1<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>1.3</span>;<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _f"> </span>without<span class="_ _a"> </span>"f"</span></span></div><div class="t m0 xe hd y15c ff5 fs8 fc7 sc0 ls0 ws0">double<span class="_ _f"> </span><span class="ffc fc0">d2<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>5E3</span>;<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ffb">5<span class="_"> </span><span class="ff13">·<span class="_ _13"> </span></span>10</span></span></span></div><div class="t m0 x16 h13 y15d ff6 fs9 fc9 sc0 ls0 ws0">3</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">37/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf29" class="pf w0 h0" data-page-no="29"><div class="pc pc29 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Rep<span class="_ _5"></span>resentation<span class="_ _42"> </span>2/2</div><div class="t m0 xe hb y4c ff1 fs7 fc1 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _7"> </span>Bias</div><div class="t m0 xe hb y15e ff4 fs7 fc0 sc0 ls0 ws0">In<span class="_ _d"> </span>IEEE754<span class="_ _e"> </span>floating<span class="_ _d"> </span>p<span class="_ _c"></span>oint<span class="_ _d"> </span>numb<span class="_ _c"></span>ers,<span class="_ _e"> </span>the<span class="_ _d"> </span>exp<span class="_ _c"></span>onent<span class="_ _d"> </span>value<span class="_ _e"> </span>is<span class="_ _d"> </span>offset<span class="_ _e"> </span>from<span class="_ _e"> </span>the<span class="_ _d"> </span>actual<span class="_ _e"> </span>value</div><div class="t m0 xe hb y15f ff4 fs7 fc0 sc0 ls0 ws0">b<span class="_ _5"></span>y<span class="_ _e"> </span>the<span class="_ _e"> </span><span class="ff1">exp<span class="_ _c"></span>onent<span class="_ _7"> </span>bias</span></div><div class="t m0 x26 h6 y160 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">The<span class="_ _d"> </span>exp<span class="_ _c"></span>onent<span class="_ _12"> </span>is<span class="_ _d"> </span>stored<span class="_ _12"> </span>as<span class="_ _d"> </span>an<span class="_ _d"> </span>unsigned<span class="_ _d"> </span>value<span class="_ _d"> </span>suitable<span class="_ _d"> </span>for<span class="_ _12"> </span>comparison</span></div><div class="t m0 x26 h6 y161 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Floating<span class="_ _d"> </span>p<span class="_ _c"></span>oint<span class="_ _12"> </span>values<span class="_ _d"> </span>are<span class="_ _12"> </span>lexicographic<span class="_ _d"> </span>ordered</span></div><div class="t m0 x26 h6 y162 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Fo<span class="_ _5"></span>r<span class="_ _12"> </span>a<span class="_ _d"> </span>single-precision<span class="_ _12"> </span>numb<span class="_ _c"></span>er,<span class="_ _12"> </span>the<span class="_ _d"> </span>exp<span class="_ _c"></span>onent<span class="_ _d"> </span>is<span class="_ _d"> </span>stored<span class="_ _12"> </span>in<span class="_ _d"> </span>the<span class="_ _d"> </span>range<span class="_ _d"> </span>[1<span class="ff1a">,<span class="_ _14"> </span></span>254]<span class="_ _d"> </span>(0<span class="_ _d"> </span>and<span class="_ _d"> </span>255</span></div><div class="t m0 x7 h6 y163 ff4 fs4 fc0 sc0 ls0 ws0">have<span class="_ _d"> </span>sp<span class="_ _c"></span>ecial<span class="_ _12"> </span>meanings),<span class="_ _d"> </span>and<span class="_ _d"> </span>is<span class="_ _d"> </span>biased<span class="_ _d"> </span>by<span class="_ _12"> </span>subtracting<span class="_ _d"> </span>127<span class="_ _d"> </span>to<span class="_ _d"> </span>get<span class="_ _d"> </span>an<span class="_ _d"> </span>exp<span class="_ _c"></span>onent<span class="_ _d"> </span>value<span class="_ _d"> </span>in<span class="_ _d"> </span>the</div><div class="t m0 x7 h6 y164 ff4 fs4 fc0 sc0 ls0 ws0">range<span class="_ _d"> </span>[<span class="ff7">−</span>126<span class="ff1a">,<span class="_ _14"> </span></span>+127]</div><div class="t m0 x2e hc y165 ffa fs4 fc0 sc0 ls0 ws0">0<span class="_ _47"> </span>10000111<span class="_ _48"> </span>11000000000000000000000</div><div class="t m0 x2e h6 y166 ffa fs4 fc0 sc0 ls0 ws0">+<span class="_ _1b"> </span><span class="ff4">2</span></div><div class="t m0 x3f h12 y167 ff6 fs6 fc0 sc0 ls0 ws0">(135<span class="ff1c">−</span>127)</div><div class="t m0 x40 h6 y166 ff4 fs4 fc0 sc0 ls0 ws0">=<span class="_ _25"> </span>2</div><div class="t m0 x41 h12 y167 ff6 fs6 fc0 sc0 ls0 ws0">8</div><div class="t m0 x2f h12 y168 ff6 fs6 fc0 sc0 ls0 ws0">1</div><div class="t m0 x42 h12 y169 ff6 fs6 fc0 sc0 ls0 ws0">2</div><div class="t m0 x21 h18 y16a ff6 fsa fc0 sc0 ls0 ws0">1</div><div class="t m0 x43 h6 y166 ff4 fs4 fc0 sc0 ls0 ws0">+</div><div class="t m0 x44 h12 y168 ff6 fs6 fc0 sc0 ls0 ws0">1</div><div class="t m0 x45 h12 y169 ff6 fs6 fc0 sc0 ls0 ws0">2</div><div class="t m0 x2b h18 y16a ff6 fsa fc0 sc0 ls0 ws0">2</div><div class="t m0 x46 h6 y166 ff4 fs4 fc0 sc0 ls0 ws0">=<span class="_ _25"> </span>0<span class="ff1a">.</span>5<span class="_ _41"></span>+<span class="_ _0"></span>0<span class="ff1a">.</span>25<span class="_ _12"> </span>=<span class="_ _25"> </span>0<span class="ff1a">.</span>75</div><div class="t m0 x47 ha y16b ff10 fs6 fc0 sc0 ls0 ws0">normal</div><div class="t m0 x48 h6 y16c ff7 fs4 fc0 sc0 ls0 ws0">→</div><div class="t m0 x49 h6 y166 ff4 fs4 fc0 sc0 ls0 ws0">1<span class="ff1a">.</span>75</div><div class="t m0 x4a h6 y16d ff4 fs4 fc0 sc0 ls0 ws0">+1<span class="ff1a">.</span>75<span class="_"> </span><span class="ff7">∗<span class="_ _13"></span></span>2</div><div class="t m0 x4b h12 y16e ff6 fs6 fc0 sc0 ls0 ws0">8</div><div class="t m0 x45 h6 y16d ff4 fs4 fc0 sc0 ls0 ws0">=<span class="_ _25"> </span>448<span class="ff1a">.</span>0</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">38/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf2a" class="pf w0 h0" data-page-no="2a"><div class="pc pc2a w0 h0"><img class="bi x0 y0 w1 h1" alt="" 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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Normal/Deno<span class="_ _5"></span>rmal<span class="_ _49"> </span>1/2</div><div class="t m0 xe hb y16f ff1 fs7 fc1 sc0 ls0 ws0">No<span class="_ _5"></span>rmal<span class="_ _7"> </span>numb<span class="_ _c"></span>er</div><div class="t m0 xe hb y170 ff4 fs7 fc0 sc0 ls0 ws0">A<span class="_ _e"> </span><span class="ff1">no<span class="_ _5"></span>rmal<span class="_ _e"> </span><span class="ff4">numb<span class="_ _c"></span>er<span class="_ _d"> </span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>floating<span class="_ _e"> </span>p<span class="_ _c"></span>oint<span class="_ _e"> </span>value<span class="_ _e"> </span>that<span class="_ _e"> </span>can<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>rep<span class="_ _5"></span>resented<span class="_ _e"> </span>with<span class="_ _e"> </span><span class="ff9">at<span class="_ _e"> </span>least<span class="_ _e"> </span>one</span></span></span></div><div class="t m0 xe hb y171 ff9 fs7 fc0 sc0 ls0 ws0">bit<span class="_ _e"> </span>set<span class="_ _e"> </span>in<span class="_ _e"> </span>the<span class="_ _e"> </span>exp<span class="_ _c"></span>onent<span class="_ _8"> </span><span class="ff4">or<span class="_ _d"> </span>the<span class="_ _e"> </span>mantissa<span class="_ _e"> </span>has<span class="_ _e"> </span>all<span class="_ _e"> </span>0s</span></div><div class="t m0 xe hb y172 ff1 fs7 fc1 sc0 ls0 ws0">Deno<span class="_ _5"></span>rmal<span class="_ _7"> </span>numb<span class="_ _c"></span>er</div><div class="t m0 xe hb y173 ff1 fs7 fc0 sc0 ls0 ws0">Deno<span class="_ _5"></span>rmal<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span>subno<span class="_ _5"></span>rmal)<span class="_ _e"> </span>numb<span class="_ _c"></span>ers<span class="_ _e"> </span>fill<span class="_ _e"> </span>the<span class="_ _e"> </span>underflo<span class="_ _5"></span>w<span class="_ _e"> </span>gap<span class="_ _e"> </span>a<span class="_ _5"></span>round<span class="_ _e"> </span>zero<span class="_ _e"> </span>in</span></div><div class="t m0 xe hb y174 ff4 fs7 fc0 sc0 ls0 ws0">floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>arithmetic.<span class="_ _f"> </span>Any<span class="_ _e"> </span>non-zero<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _e"> </span>with<span class="_ _e"> </span>magnitude<span class="_ _e"> </span>smaller<span class="_ _e"> </span>than<span class="_ _e"> </span>the</div><div class="t m0 xe hb y175 ff4 fs7 fc0 sc0 ls0 ws0">smallest<span class="_ _e"> </span>no<span class="_ _5"></span>rmal<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>is<span class="_ _e"> </span>denormal</div><div class="t m0 xe hb y176 ff4 fs7 fc0 sc0 ls0 ws0">A<span class="_ _e"> </span><span class="ff1">deno<span class="_ _5"></span>rmal<span class="_ _e"> </span><span class="ff4">numb<span class="_ _c"></span>er<span class="_ _d"> </span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>floating<span class="_ _e"> </span>p<span class="_ _c"></span>oint<span class="_ _e"> </span>value<span class="_ _e"> </span>that<span class="_ _e"> </span>can<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>rep<span class="_ _5"></span>resented<span class="_ _e"> </span>with<span class="_ _e"> </span><span class="ff9">all<span class="_ _e"> </span>0s<span class="_ _e"> </span>in</span></span></span></div><div class="t m0 xe hb y177 ff9 fs7 fc0 sc0 ls0 ws0">the<span class="_ _e"> </span>exp<span class="_ _c"></span>onent<span class="ff4">,<span class="_ _d"> </span>but<span class="_ _e"> </span>the<span class="_ _e"> </span>mantissa<span class="_ _e"> </span>is<span class="_ _e"> </span>non-zero</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">39/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Normal/Deno<span class="_ _5"></span>rmal<span class="_ _49"> </span>2/2</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">Why<span class="_ _7"> </span>denormal<span class="_ _e"> </span>numb<span class="_ _c"></span>ers<span class="_ _7"> </span>make<span class="_ _e"> </span>sense:<span class="_ _4a"> </span><span class="ff4">(<span class="ff7">↓<span class="_ _e"> </span></span>no<span class="_ _5"></span>rmal<span class="_ _e"> </span>numb<span class="_ _c"></span>ers)</span></div><div class="t m0 x1 hb y178 ff1 fs7 fc0 sc0 ls0 ws0">The<span class="_ _7"> </span>problem:<span class="_ _f"> </span><span class="ff4">distance<span class="_ _e"> </span>values<span class="_ _e"> </span>from<span class="_ _e"> </span>zero<span class="_ _4b"> </span>(<span class="ff7">↓<span class="_ _e"> </span></span>deno<span class="_ _5"></span>rmal<span class="_ _e"> </span>numb<span class="_ _c"></span>ers)</span></div><div class="t m0 xb he y179 ffc fs8 fc3 sc0 ls0 ws0">Floating-point<span class="_ _f"> </span>representation,<span class="_ _f"> </span>by<span class="_ _a"> </span>Carl<span class="_ _f"> </span>Burch</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">40/77</div><a class="l" href="http://www.cburch.com/books/float/index.html"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:0.115000px;width:209.116000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA4wAAAH/CAIAAACTgcSzAAAACXBIWXMAABYlAAAWJQFJUiTwAAARNElEQVR42u3Z3XNU533A8We1u6y00uqFF2Eav0jxK9gGDPILOAiOhQRiCFAMddv00s5M2z+kt71Lp+NxL9zBnVp2g0sqY8lIQrzjNKkbB4w94E5MjIvNohW7knZXu71gN4a4uclMJsL+fO5+5xzOefY5y8x3VrH7n342AADAgvHxqWMNdgEAgIVGpAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAA8BuxYrFoFwAAWDiSyaRfUgEAWHBEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAD8lsQdtNaVmyIvDADg93NucuwOWq1fUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgDAN1usWCzeKWudnp72wgAAfj+ZTOZOWWoymfRLKgAAC45IBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgDA7xIrFot2AQCAhSOZTPolFQCABUekAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQCAP6yELYD/1/T09MJZTCaT8UYA+FbxSyoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAA+OOKFYtFuwAAwMKRTCb9kgoAwIIjUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAA8LskbAHfMOXy/OPR1q8fPzc5ZnMA4E4RKxaLdgEAgIUjmUz6cz8AAAuOSAUAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAEQqAAAiFQAARCoAAHe2hC34Nlu5Kfr6wXOTY3bmG69cnn882urtewUAC1asWCzaBQAAFo5kMunP/QAALDgiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAIFIBABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCAIBIBQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgAAIhUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBgAUjYAvh2KszMrB/Y8fXj5ybHbA4Af3SxYrFoFwAAWDiSyaQ/9wMAsOCIVAAARCoAAIhUAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAAAQqQAAiFQAABCpAACIVAAAEKkAAIhUAAAQqQAAiFQAABCpAAAgUgEAEKkAACBSAQAQqQAAIFIBABCpAAAgUgEAQKQCACBSAQBApAIAIFIBAECkAgAgUgEAQKQCACBSAQBApAIAgEgFAECkAgCASAUAQKQCAIBIBQBApAIAgEgFAACRCgCASAUAAJEKAIBIBQAAkQoAgEgFAACRCgCASAUAAJEKAAAiFQAAkQoAACIVAACRCgAAIhUAAJEKAAAiFQAARCoAACIVAABEKgAAIhUAAEQqAAAiFQAARCoAACIVAABEKgAAiFQAAEQqAACIVAAARCoAAIhUAABEKgAAiFQAAKhJTP1dt10AWMiu9r9sE4BvlZUbticeyl7O/n0I4cHuPatbpjqe646dyzStPjL5Trwpd/eS9cu6u35+9J3uJzfenyrOH/qv0fbKogv5qQ3f33JvQ6K1+FFuUfeHQ+9v3P75R6V9XdWp+JGfHmlPXch/tmnLrnsz023T8aH5ZeHqF/uWZpNtHW//eHJteDCxb+nV0uIHjmS/HIjH3wjpbYlQGX95fGbDjj1PxeeuFZoPnxltj83PV+Px1PV1W8InPwmN6/u6W5c2lnNvFJJbxz4+8/inuVj0wpIbNxrffXfRrtnpme3VVGUsHsLl6jPvXS89OB8+ylfXtFYSv7g4XM4N7tlzT7EhUcgNzS8L/3OhZ/GN82fnl61uT7zf0dEyMrVyfebcT6dX9ty7ojUkkiff/OyRhy++9yfPbR379dTDF35yMdfX1XOjLdk2df5S2/ao47WJkT/r2TufmC8NTzffvraR4VWNIR5CbWmvvTP8V9/fnXrz/JX1mbMfLN23s/HEyNim7duHr1f6M4fLlQ1jlWTpyCvl3I6+wfvebi3vvXFwpjE05XZOl1Mh/kZ7euv1xGhboX/o0vX1mbPT39m1+uDFfN+KZHsY/9F47ns79l5IFvqHkunnUwerU33TTR0jjVM3FxZmQ7JhsPp2vNA3l2wPb4XQ/6Pxka8eUyg8//aSfP/Qp1fXhp/fs2wwtqQcvmzKJ95qb4tiscVDV4tRU2zJbKmYKB0+faCS29HX/95H7XvXXC83jFz6crB7yWypmGh6K33j5mPqS/+wvG19Ij/T2J0vv/r5/972xuZ3Pbq45fULh+p7c/afRm/52FOJXe3FZCz9Rmk6JBv6hyqJndX0oVTh+cby1FAiHZqL/UOXP15dTs6kW6/MZbbdkzn8aezpu+Lp0w3pgaFr+Z3V46+M556+77G5j78odF6JxZdmZ36ZzD87uLkSa1pViKVaX36//OLqD0qV7mJDui05fuEXD9z+vU6Xd7eElrcvvv9bx5MzuyrzsXTrwUJsz9lPKhvvTpXP/2zku6t2t4SWL1P5A+9cfrF27N7ufYfPDvVHIaT64sO/Sm1efbm53PHaTNh3+L2h/i2hPL/17kxLLv/jmamdmURHIXYlngmvNLa+UMqNVTL7p5oXxT6d+s2JjsZbp1eOvN+5fl1f+3B1aluq6dUT51/avPpCyD301n8f3Lq2r304Ftsz+mV+W6rp1RONP+ibT8yXxibHGyuL5p574plcOtOYfmv2i4EDZ6681P+dG1Njn6S3/wH+n/1y8Olbn/XJ32566MN8bPnJS1cevW1L3+2Yvu26F3rvb265nL/x1ZX/ET156xVTP9jYHm+e+HVpx3254mjH3K3n4n+9PCTvK51PtC+pDsXndmYSh6bCwIEzv/qbdffnGz5IJh6dOXxsZOuTAwfOZF98sj3RmCjPfRZrXZEsLCoOH5lc2pRdu+bWc1eLibZ4sqExOTLxblj75MCB0PiXI4lYdOuCX9q8+tL03PKxo9MPdOUTlYuJ8Mjt35n49MCBM5de7FlVWFSNDx/7z85rj31vb0j9w89ee/j64sSyawPlcG3T1nJ6NIS++L+8d2LXloFCITfa3LYv83out/ef8/Efjk4cD3MtIerZ94/Z2A9HJ06EuZYQ3Xj35nQyzLWEaF3t3Kkw1xKiJ2rT6TDXEqK1N6ej42G2M0RratNEmO0M0eradDTMdobo8do0GWY7Q/RYbToWZjtD9GhtOh5mO0O0qjadCLOdIVpZm06G2c4QPVKbToXZzhA9XJtOh9nOED10c5ocDzNdIXqwNk2Ema4QPVCbjoaZrhDdX5smw0xXiL5bm46Fma4Qddem42GmK0RdtelEmOkK0X216WSY6QrRvbXpVJjpCtE9N6djJ0NhVYiW3pzGjobSmuf7E9V869zwfLp2yalQWBWiJbVpIhSe2LsuNpfoiIVc40g6Vjs+GQprbh5PJaYLzYcbaydGj63Illbu35S+3niouX7x6VBYFaLFN6fxU6H46O5NLdVDsVRtHcdCac3u3nTu3+O1lY2Ot2erPSHqqI8d2WpPiNprdzgRimsGn4l/9dSJiTDX86cD5dLrbU03jxyZDOV1f96T+jx9qK2xfpfF2WpPiNpq49EV2fnHB6fSLbW7Tobi+sFt1eFi7TGjk+3Z8lM7p9K1W44fDcWe3QMtB0vx+g2XZKs9IWqtj0uz1Z4QZWqf6ngorf+LKHxRebs5Vb9iWbbaE6KW+tiZrfaEqLk+Ls9We0KUro93Zas9IWqqjyuy1Z4Q1T/MRHu20hui2p3HT4bi04ObZ4Ybaos/cjyUN+zvvXE92ZHIl4ab6iuY6MhWekO0qLbG06H01K6nDtb/1ejE4mylN0TJ2unxUNoS9eUzxTD71bsfmwilzVFfPhMSc7e8+SMnQ3lDf990KHeMNNQvPRFKG/v75tK54VjtXY5NhtKmnQPxQ6WG+jOXZCu9IUrUXuVkmOvd/1RDNVEuDte/IaPHlmdLG/dviV/PX0s1xotfLWb02F3Z0obamdZU6bavYme29Oz+LfHr8XzDrccnlmYrvSGqv8WJZdlKb4hqyxk/Hoq9/dtyTf9af2vjx0Jx8+DgG6n52ic4GUrf27kulMfmM/VbdGYrvSGqPWB8IhT7tvdNzb/ZXP/Gjofi1he2DM0tqv+D5dlKb4hCfbwrW+kNUbU+rshWekNUqX9R27Pz20P0b/v+DxSEJfVZhiTDAAAAAElFTkSuQmCC"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Infinit<span class="_ _5"></span>y<span class="_ _8"> </span><span class="ff7">∞<span class="_ _4c"> </span></span>1/2</div><div class="t m0 xe hb y17a ff1 fs7 fc1 sc0 ls0 ws0">Infinit<span class="_ _5"></span>y</div><div class="t m0 xe hb y17b ff4 fs7 fc0 sc0 ls0 ws0">In<span class="_ _e"> </span>the<span class="_ _e"> </span>IEEE754<span class="_ _e"> </span>standa<span class="_ _5"></span>rd,<span class="_ _e"> </span><span class="ff5">inf<span class="_ _e"> </span></span>(infinit<span class="_ _5"></span>y<span class="_ _e"> </span>value)<span class="_ _e"> </span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>numeric<span class="_ _e"> </span>data<span class="_ _e"> </span>type<span class="_ _e"> </span>value<span class="_ _e"> </span>that</div><div class="t m0 xe hb y17c ff4 fs7 fc0 sc0 ls0 ws0">exceeds<span class="_ _e"> </span>the<span class="_ _e"> </span>maximum<span class="_ _e"> </span>(o<span class="_ _5"></span>r<span class="_ _e"> </span>minimum)<span class="_ _e"> </span>rep<span class="_ _5"></span>resentable<span class="_ _e"> </span>value</div><div class="t m0 x1 hb y17d ff4 fs7 fc0 sc0 ls0 ws0">Op<span class="_ _c"></span>erations<span class="_ _d"> </span>generating<span class="_ _21"> </span><span class="ff5">inf<span class="_ _12"> </span></span>:</div><div class="t m0 xb hb y17e ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±∞<span class="_ _13"> </span>·<span class="_ _25"> </span>±∞</span></div><div class="t m0 xb hb y17f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±∞<span class="_ _13"> </span>·<span class="_ _25"> </span>±<span class="ffa">finite<span class="_ _7"> </span>value</span></span></div><div class="t m0 xb hb y180 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">finite<span class="_ _8"> </span>value<span class="_ _25"> </span><span class="ff9">op<span class="_ _e"> </span></span>finite<span class="_ _8"> </span>value<span class="_ _12"> </span><span class="ff1a">><span class="_ _12"> </span></span>max<span class="_ _7"> </span>value</span></div><div class="t m0 xb hb y181 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">finite<span class="_ _e"> </span>value<span class="_ _e"> </span><span class="ff1a">/<span class="_ _13"> </span><span class="ff7">±<span class="_ _25"> </span><span class="ff4">0</span></span></span></span></div><div class="t m0 x1 hb y182 ff4 fs7 fc0 sc0 ls0 ws0">There<span class="_ _e"> </span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>single<span class="_ _e"> </span>rep<span class="_ _5"></span>resentation<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span><span class="ffa">+inf<span class="_ _e"> </span></span>and<span class="_ _e"> </span><span class="ffa">-inf</span></div><div class="t m0 x1 hb y183 ff4 fs7 fc0 sc0 ls0 ws0">Compa<span class="_ _5"></span>rison:<span class="_ _a"> </span><span class="ffa">(inf<span class="_ _4"> </span>==<span class="_ _18"> </span>finite<span class="_ _8"> </span>value)<span class="_ _e"> </span><span class="ff7">→<span class="_ _e"> </span></span>false</span></div><div class="t m0 x2e hb y184 ffa fs7 fc0 sc0 ls0 ws0">(<span class="ff7">±</span>inf<span class="_ _18"> </span>==<span class="_ _18"> </span><span class="ff7">±</span>inf)<span class="_ _4d"> </span><span class="ff7">→<span class="_ _e"> </span></span>true</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">41/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Infinit<span class="_ _5"></span>y<span class="_ _4e"> </span>2/2</div><div class="t m0 xe he y185 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>5.0<span class="_ _a"> </span>/<span class="_ _f"> </span>0.0</span>;<span class="_ _2d"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _a"> </span>"inf"</span></div><div class="t m0 xe he y186 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>-5.0<span class="_ _a"> </span>/<span class="_ _f"> </span>0.0</span>;<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _a"> </span>print<span class="_ _f"> </span>"-inf"</span></div><div class="t m0 xe he y187 ff5 fs8 fcb sc0 ls0 ws0">auto<span class="_ _f"> </span><span class="ffc fc0">inf<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span></span><span class="fc7">float<span class="ffc fc8">>::<span class="fc0">infinity;</span></span></span></div><div class="t m0 xe he y188 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">-0.0<span class="_ _a"> </span>==<span class="_ _f"> </span>0.0</span>);<span class="_ _4f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>true,<span class="_ _f"> </span>0<span class="_ _a"> </span>==<span class="_ _f"> </span>0</span></div><div class="t m0 xe he y189 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>((<span class="fc8">5.0f<span class="_ _a"> </span>/<span class="_ _f"> </span></span>inf)<span class="_ _f"> </span><span class="fc8">==<span class="_ _f"> </span></span>((<span class="fc8">-5.0f<span class="_ _a"> </span>/<span class="_ _f"> </span></span>inf));<span class="_ _27"> </span><span class="ffe fc9">//<span class="_ _f"> </span>true,<span class="_ _f"> </span>0<span class="_ _a"> </span>==<span class="_ _f"> </span>0</span></div><div class="t m0 xe he y18a ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">10e40f</span>)<span class="_ _a"> </span><span class="fc8">==<span class="_ _f"> </span></span>(<span class="fc8">10e40f<span class="_ _f"> </span>+<span class="_ _f"> </span>9999999.0f</span>);<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>true,<span class="_ _f"> </span>inf<span class="_ _f"> </span>==<span class="_ _a"> </span>inf</span></div><div class="t m0 xe he y18b ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">10e40</span>)<span class="_ _23"> </span><span class="fc8">==<span class="_ _f"> </span></span>(<span class="fc8">10e40f<span class="_ _f"> </span>+<span class="_ _a"> </span>9999999.0f</span>);<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>false,<span class="_ _f"> </span>10e40<span class="_ _a"> </span>!=<span class="_ _f"> </span>inf</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">42/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Not<span class="_ _8"> </span>a<span class="_ _f"> </span>Numb<span class="_ _c"></span>er<span class="_ _8"> </span>(NaN)<span class="_ _50"> </span>1/2</div><div class="t m0 xe hb y18c ff1 fs7 fc1 sc0 ls0 ws0">NaN</div><div class="t m0 xe hb y18d ff4 fs7 fc0 sc0 ls0 ws0">In<span class="_ _e"> </span>the<span class="_ _e"> </span>IEEE754<span class="_ _e"> </span>standa<span class="_ _5"></span>rd,<span class="_ _e"> </span><span class="ff5">NaN<span class="_ _e"> </span></span>(not<span class="_ _e"> </span>a<span class="_ _e"> </span>numb<span class="_ _c"></span>er)<span class="_ _d"> </span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>numeric<span class="_ _7"> </span>data<span class="_ _e"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="_ _d"> </span>value</div><div class="t m0 xe hb y18e ff4 fs7 fc0 sc0 ls0 ws0">rep<span class="_ _5"></span>resenting<span class="_ _e"> </span>an<span class="_ _e"> </span>undefined<span class="_ _e"> </span>o<span class="_ _5"></span>r<span class="_ _e"> </span>non-representable<span class="_ _d"> </span>value</div><div class="t m0 x1 hb y18f ff4 fs7 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>op<span class="_ _c"></span>erations<span class="_ _e"> </span>generating<span class="_ _21"> </span><span class="ff5">NaN<span class="_ _12"> </span></span>:</div><div class="t m0 x26 h6 y190 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Op<span class="_ _c"></span>erations<span class="_ _12"> </span>with<span class="_ _d"> </span>a<span class="_ _d"> </span><span class="ffa">NaN<span class="_ _d"> </span></span>as<span class="_ _d"> </span>at<span class="_ _d"> </span>least<span class="_ _d"> </span>one<span class="_ _d"> </span>op<span class="_ _c"></span>erand</span></div><div class="t m0 x26 h6 y191 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±∞<span class="_ _13"> </span>·<span class="_ _13"> </span>∓∞<span class="_ _12"> </span><span class="ff4">,<span class="_ _d"> </span>0<span class="_"> </span></span>·<span class="_ _13"> </span>∞</span></div><div class="t m0 x26 h6 y192 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">0<span class="ff1a">/</span>0<span class="ff1a">,<span class="_ _14"> </span><span class="ff7">∞</span>/<span class="ff7">∞</span></span></span></div><div class="t m0 x26 h6 y193 ffd fs4 fc0 sc0 ls0 ws0">•</div><div class="t m0 x7 h6 y194 ff7 fs4 fc0 sc0 ls0 ws0">√</div><div class="t m0 x20 h6 y193 ff9 fs4 fc0 sc0 ls0 ws0">x<span class="_ _51"></span><span class="ff4">,<span class="_ _d"> </span>log(</span>x<span class="_ _51"></span><span class="ff4">)<span class="_ _d"> </span>for<span class="_ _12"> </span></span>x<span class="_ _7"> </span><span class="ff1a"><<span class="_ _25"> </span><span class="ff4">0</span></span></div><div class="t m0 x26 h6 y195 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">sin</span></div><div class="t m0 x4c h12 y196 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">1</span></div><div class="t m0 x4d h6 y195 ff4 fs4 fc0 sc0 ls0 ws0">(<span class="ff9">x<span class="_ _51"></span></span>)<span class="ff1a">,<span class="_ _14"> </span></span>cos</div><div class="t m0 x28 h12 y197 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">1</span></div><div class="t m0 x4e h6 y195 ff4 fs4 fc0 sc0 ls0 ws0">(<span class="ff9">x<span class="_ _51"></span></span>)<span class="_ _d"> </span>fo<span class="_ _5"></span>r<span class="_ _d"> </span><span class="ff9">x<span class="_ _e"> </span><span class="ff1a"><<span class="_ _12"> </span><span class="ff7">−</span></span></span>1<span class="_ _25"> </span><span class="ff9">o<span class="_ _5"></span>r<span class="_ _7"> </span>x<span class="_ _e"> </span><span class="ff1a">><span class="_ _25"> </span><span class="ff4">1</span></span></span></div><div class="t m0 x1 hb y198 ff4 fs7 fc0 sc0 ls0 ws0">Compa<span class="_ _5"></span>rison:<span class="_ _a"> </span><span class="ffa">(NaN<span class="_ _4"> </span>==<span class="_ _18"> </span>x)<span class="_ _24"> </span><span class="ff7">→<span class="_ _e"> </span></span>false</span>,<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span>every<span class="_ _e"> </span><span class="ffa">x</span></div><div class="t m0 x2e hb y199 ffa fs7 fc0 sc0 ls0 ws0">(NaN<span class="_ _18"> </span>==<span class="_ _18"> </span>NaN)<span class="_ _e"> </span><span class="ff7">→<span class="_ _e"> </span></span>false</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">43/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Not<span class="_ _8"> </span>a<span class="_ _f"> </span>Numb<span class="_ _c"></span>er<span class="_ _8"> </span>(NaN)<span class="_ _50"> </span>2/2</div><div class="t m0 x1 hb y19a ff4 fs7 fc0 sc0 ls0 ws0">There<span class="_ _e"> </span>a<span class="_ _5"></span>re<span class="_ _e"> </span>many<span class="_ _e"> </span>rep<span class="_ _5"></span>resentations<span class="_ _e"> </span>for<span class="_ _d"> </span><span class="ffa">NaN<span class="_ _e"> </span></span>(e.g.<span class="_ _a"> </span>2</div><div class="t m0 x46 h9 y19b ff6 fs5 fc0 sc0 ls0 ws0">24</div><div class="t m0 x4f hb y19a ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">2<span class="_ _e"> </span>for<span class="_ _e"> </span><span class="ffa">float</span>)</span></div><div class="t m0 x1 hb y19c ff4 fs7 fc0 sc0 ls0 ws0">The<span class="_ _e"> </span>sp<span class="_ _c"></span>ecific<span class="_ _d"> </span>(bitwise)<span class="_ _d"> </span><span class="ffa">NaN<span class="_ _e"> </span></span>value<span class="_ _e"> </span>returned<span class="_ _e"> </span>by<span class="_ _d"> </span>an<span class="_ _e"> </span>op<span class="_ _c"></span>eration<span class="_ _e"> </span>is<span class="_ _e"> </span>implementation/compiler</div><div class="t m0 x1 hb y19d ff4 fs7 fc0 sc0 ls0 ws0">sp<span class="_ _c"></span>ecific</div><div class="t m0 xe he y19e ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>0<span class="_ _a"> </span>/<span class="_ _f"> </span>0</span>;<span class="_ _2e"> </span><span class="ffe fc9">//<span class="_ _f"> </span>undefined<span class="_ _f"> </span>behavior</span></div><div class="t m0 xe he y19f ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>0.0<span class="_ _a"> </span>/<span class="_ _f"> </span>0.0</span>;<span class="_ _2d"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _a"> </span>"nan"<span class="_ _f"> </span>or<span class="_ _f"> </span>"-nan"</span></div><div class="t m0 xb he y1a0 ffc fs8 fc3 sc0 ls0 ws0">quiet<span class="_ _d"> </span>NaN</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">44/77</div><a class="l" href="https://en.cppreference.com/w/cpp/types/numeric_limits/quiet_NaN"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:2.018000px;width:43.041000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Machine<span class="_ _8"> </span>Epsilon</div><div class="t m0 xe hb y1a1 ff1 fs7 fc1 sc0 ls0 ws0">Machine<span class="_ _7"> </span>epsilon</div><div class="t m0 xe hb y1a2 ff1 fs7 fc0 sc0 ls0 ws0">Machine<span class="_ _7"> </span>epsilon<span class="_ _12"> </span><span class="ff1a">ε</span></div><div class="t m0 x50 hb y1a3 ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x50 hb y1a2 ff1a fs7 fc0 sc0 ls0 ws0">ε<span class="_ _e"> </span><span class="ff4">(o<span class="_ _5"></span>r<span class="_ _e"> </span><span class="ff9">machine<span class="_ _e"> </span>accuracy<span class="_ _51"></span></span>)<span class="_ _e"> </span>is<span class="_ _e"> </span>defined<span class="_ _e"> </span>to<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>the<span class="_ _e"> </span>smallest<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>that</span></div><div class="t m0 xe hb y1a4 ff4 fs7 fc0 sc0 ls0 ws0">can<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _d"> </span>added<span class="_ _e"> </span>to<span class="_ _e"> </span>1<span class="ff1a">.</span>0<span class="_ _e"> </span>to<span class="_ _e"> </span>give<span class="_ _e"> </span>a<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _e"> </span>other<span class="_ _e"> </span>than<span class="_ _e"> </span>one</div><div class="t m0 x1 h6 y1a5 ff4 fs4 fc0 sc0 ls0 ws0">IEEE<span class="_ _d"> </span>754<span class="_ _d"> </span>Single<span class="_ _d"> </span>p<span class="_ _5"></span>recision<span class="_ _d"> </span>:<span class="_ _7"> </span><span class="ff1a">ε</span></div><div class="t m0 x51 h6 y1a6 ff1a fs4 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x51 h6 y1a5 ff1a fs4 fc0 sc0 ls0 ws0">ε<span class="_ _25"> </span><span class="ff4">=<span class="_ _25"> </span>2</span></div><div class="t m0 x3e h12 y1a7 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">23</span></div><div class="t m0 x52 h6 y1a5 ff7 fs4 fc0 sc0 ls0 ws0">≈<span class="_ _25"> </span><span class="ff4">1<span class="ff1a">.</span>19209<span class="_"> </span></span>∗<span class="_ _13"></span><span class="ff4">10</span></div><div class="t m0 x53 h12 y1a7 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">7</span></div><div class="t m0 x1 h6 y1a8 ff4 fs4 fc0 sc0 ls0 ws0">IEEE<span class="_ _d"> </span>754<span class="_ _d"> </span>Double<span class="_ _d"> </span>p<span class="_ _5"></span>recision<span class="_ _d"> </span>:<span class="_ _7"> </span><span class="ff1a">ε</span></div><div class="t m0 x54 h6 y1a9 ff1a fs4 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x54 h6 y1a8 ff1a fs4 fc0 sc0 ls0 ws0">ε<span class="_ _25"> </span><span class="ff4">=<span class="_ _25"> </span>2</span></div><div class="t m0 x9 h12 y1aa ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">52</span></div><div class="t m0 x55 h6 y1a8 ff7 fs4 fc0 sc0 ls0 ws0">≈<span class="_ _25"> </span><span class="ff4">2<span class="ff1a">.</span>22045<span class="_"> </span></span>∗<span class="_ _13"></span><span class="ff4">10</span></div><div class="t m0 x56 h12 y1aa ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">16</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">45/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf31" class="pf w0 h0" data-page-no="31"><div class="pc pc31 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Units<span class="_ _8"> </span>at<span class="_ _f"> </span>the<span class="_ _8"> </span>Last<span class="_ _8"> </span>Place<span class="_ _f"> </span>(<span class="ff5">ULP</span>)</div><div class="t m0 xe hb y1ab ff1 fs7 fc1 sc0 ls0 ws0">ULP</div><div class="t m0 xe hb y1ac ff1 fs7 fc0 sc0 ls0 ws0">Units<span class="_ _7"> </span>at<span class="_ _7"> </span>the<span class="_ _8"> </span>Last<span class="_ _7"> </span>Place<span class="_ _e"> </span><span class="ff4">is<span class="_ _e"> </span>the<span class="_ _e"> </span>gap<span class="_ _e"> </span>b<span class="_ _c"></span>et<span class="_ _5"></span>w<span class="_ _5"></span>een<span class="_ _e"> </span>consecutive<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>numb<span class="_ _c"></span>ers</span></div><div class="t m0 x57 hb y1ad ff9 fs7 fc0 sc0 ls0 ws0">ULP<span class="_ _0"></span><span class="ff4">(</span>p<span class="_ _c"></span><span class="ff1a">,<span class="_ _14"> </span></span>e<span class="_ _0"></span><span class="ff4">)<span class="_ _12"> </span>=<span class="_ _12"> </span><span class="ff1a">β</span></span></div><div class="t m0 x58 h9 y1ae ff10 fs5 fc0 sc0 ls0 ws0">e<span class="_ _c"></span><span class="ff1d">−<span class="ff6">(</span></span>p<span class="_ _c"></span><span class="ff1d">−<span class="ff6">1)</span></span></div><div class="t m0 x55 hb y1ad ff7 fs7 fc0 sc0 ls0 ws0">→<span class="_ _12"> </span><span class="ff4">2</span></div><div class="t m0 x3d h9 y1ae ff10 fs5 fc0 sc0 ls0 ws0">e<span class="_ _c"></span><span class="ff1d">−<span class="ff6">(</span></span>p<span class="_ _c"></span><span class="ff1d">−<span class="ff6">1)</span></span></div><div class="t m0 x1 hb y1af ff4 fs7 fc0 sc0 ls0 ws0">Example:</div><div class="t m0 x59 hb y1b0 ff1a fs7 fc0 sc0 ls0 ws0">β<span class="_ _e"> </span><span class="ff4">=<span class="_ _12"> </span>10</span>,<span class="_ _f"> </span><span class="ff9">p<span class="_ _e"> </span><span class="ff4">=<span class="_ _12"> </span>3</span></span></div><div class="t m0 x59 hb y1b1 ff1a fs7 fc0 sc0 ls0 ws0">π<span class="_ _d"> </span><span class="ff4">=<span class="_ _12"> </span>3</span>.<span class="ff4">1415926</span>...<span class="_ _12"> </span><span class="ff7">→<span class="_ _12"> </span><span class="ff9">x<span class="_ _8"> </span><span class="ff4">=<span class="_ _12"> </span>3</span></span></span>.<span class="ff4">14<span class="_"> </span><span class="ff7">×<span class="_ _13"></span></span>10</span></div><div class="t m0 x3d h9 y1b2 ff6 fs5 fc0 sc0 ls0 ws0">0</div><div class="t m0 x59 hb y1b3 ff9 fs7 fc0 sc0 ls0 ws0">ULP<span class="_ _0"></span><span class="ff4">(3<span class="ff1a">,<span class="_ _14"> </span></span>0)<span class="_ _12"> </span>=<span class="_ _12"> </span>10</span></div><div class="t m0 x5a h9 y1b4 ff1d fs5 fc0 sc0 ls0 ws0">−<span class="ff6">2</span></div><div class="t m0 x1d hb y1b3 ff4 fs7 fc0 sc0 ls0 ws0">=<span class="_ _12"> </span>0<span class="ff1a">.</span>01</div><div class="t m0 x1 hb y1b5 ff4 fs7 fc0 sc0 ls0 ws0">Relation<span class="_ _e"> </span>with<span class="_ _12"> </span><span class="ff1a">ε</span></div><div class="t m0 x27 hb y1b6 ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x27 hb y1b5 ff1a fs7 fc0 sc0 ls0 ws0">ε<span class="ff4">:</span></div><div class="t m0 xb hb y1b7 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _a"> </span><span class="ff1a">ε</span></div><div class="t m0 x7 hb y1b8 ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x7 hb y1b7 ff1a fs7 fc0 sc0 ls0 ws0">ε<span class="_ _12"> </span><span class="ff4">=<span class="_ _12"> </span><span class="ff9">ULP</span>(<span class="ff9">p<span class="_ _c"></span></span></span>,<span class="_ _14"> </span><span class="ff4">0)</span></div><div class="t m0 xb hb y1b9 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">ULP</span></div><div class="t m0 x5b h10 y1ba ff10 fs5 fc0 sc0 ls0 ws0">x</div><div class="t m0 x5c hb y1b9 ff4 fs7 fc0 sc0 ls0 ws0">=<span class="_"> </span><span class="ff1a">ε</span></div><div class="t m0 x31 hb y1bb ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x31 hb y1b9 ff1a fs7 fc0 sc0 ls0 ws0">ε<span class="_ _13"> </span><span class="ff7">∗<span class="_ _25"> </span></span>β</div><div class="t m0 x5d h9 y1bc ff10 fs5 fc0 sc0 ls0 ws0">e<span class="_ _c"></span><span class="ff6">(</span>x<span class="_ _0"></span><span class="ff6">)</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">46/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf32" class="pf w0 h0" data-page-no="32"><div class="pc pc32 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-P<span class="_ _5"></span>oint<span class="_ _8"> </span>Represent<span class="_ _5"></span>ation<span class="_ _8"> </span>of<span class="_ _f"> </span>a<span class="_ _8"> </span>Real<span class="_ _f"> </span>Numb<span class="_ _c"></span>er</div><div class="t m0 x1 hb y1bd ff4 fs7 fc0 sc0 ls0 ws0">The<span class="_ _e"> </span>machine<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>representation<span class="_ _d"> </span><span class="ff1">fl(<span class="ff9">x<span class="_ _41"></span></span>)<span class="_ _e"> </span></span>of<span class="_ _e"> </span>a<span class="_ _e"> </span><span class="ff9">real<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _f"> </span>x<span class="_ _a"> </span></span>is<span class="_ _d"> </span>expressed<span class="_ _d"> </span>as</div><div class="t m0 x1 hb y1be ff9 fs7 fc0 sc0 ls0 ws0">fl<span class="_"> </span><span class="ff4">(</span>x<span class="_ _41"></span><span class="ff4">)<span class="_ _12"> </span>=<span class="_ _12"> </span></span>x<span class="_ _12"> </span><span class="ff4">(1<span class="_"> </span>+<span class="_ _13"> </span><span class="ff1a">δ<span class="_ _c"></span></span>),<span class="_ _e"> </span>where<span class="_ _e"> </span><span class="ff1a">δ<span class="_ _7"> </span></span>is<span class="_ _e"> </span>a<span class="_ _e"> </span>small<span class="_ _e"> </span>constant</span></div><div class="t m0 x1 hb y1bf ff4 fs7 fc0 sc0 ls0 ws0">The<span class="_ _e"> </span>app<span class="_ _5"></span>ro<span class="_ _5"></span>ximation<span class="_ _e"> </span>of<span class="_ _e"> </span>a<span class="_ _e"> </span><span class="ff9">real<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _f"> </span>x<span class="_ _a"> </span></span>has<span class="_ _d"> </span>the<span class="_ _e"> </span>following<span class="_ _d"> </span>properties:</div><div class="t m0 x1 hb y1c0 ff1e fs7 fc0 sc0 ls0 ws0">Absolute<span class="_ _7"> </span>Error<span class="_ _0"></span><span class="ff4">:<span class="_ _a"> </span><span class="ff7">|<span class="ff9">fl<span class="_ _0"></span></span></span>(<span class="ff9">x<span class="_ _41"></span></span>)<span class="_"> </span><span class="ff7">−<span class="_ _13"></span><span class="ff9">x<span class="_ _51"></span></span>|<span class="_ _12"> </span>≤</span></span></div><div class="t m0 x5e hb y1c1 ff4 fs7 fc0 sc0 ls0 ws0">1</div><div class="t m0 x5e hb y1c2 ff4 fs7 fc0 sc0 ls0 ws0">2</div><div class="t m0 x41 hb y1c0 ff7 fs7 fc0 sc0 ls0 ws0">·<span class="_ _13"> </span><span class="ff9">ULP</span></div><div class="t m0 x1f h10 y1c3 ff10 fs5 fc0 sc0 ls0 ws0">x</div><div class="t m0 x1 hb y1c4 ff1e fs7 fc0 sc0 ls0 ws0">Relative<span class="_ _7"> </span>Error<span class="_ _0"></span><span class="ff4">:</span></div><div class="t m0 xa h17 y1c5 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 xa h17 y1c6 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 xa h17 y1c7 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 xa h17 y1c8 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x5f hb y1c9 ff9 fs7 fc0 sc0 ls0 ws0">fl<span class="_"> </span><span class="ff4">(</span>x<span class="_ _41"></span><span class="ff4">)<span class="_"> </span><span class="ff7">−<span class="_ _13"></span></span></span>x</div><div class="t m0 x3f hb y1ca ff9 fs7 fc0 sc0 ls0 ws0">x</div><div class="t m0 x23 h17 y1c5 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x23 h17 y1c6 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x23 h17 y1c7 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x23 h17 y1c8 ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x60 hb y1c4 ff7 fs7 fc0 sc0 ls0 ws0">≤</div><div class="t m0 x38 hb y1c9 ff4 fs7 fc0 sc0 ls0 ws0">1</div><div class="t m0 x38 hb y1ca ff4 fs7 fc0 sc0 ls0 ws0">2</div><div class="t m0 x1b hb y1c4 ff7 fs7 fc0 sc0 ls0 ws0">·<span class="_ _14"></span><span class="ff1a">ε</span></div><div class="t m0 x61 hb y1cb ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x61 hb y1c4 ff1a fs7 fc0 sc0 ls0 ws0">ε</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">47/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Cheatsheet<span class="_ _52"> </span>1/3</div><div class="t m0 x26 h6 y1cc ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">NaN<span class="_ _d"> </span><span class="ff4">(mantissa<span class="_ _d"> </span><span class="ff7"></span>=<span class="_ _25"> </span>0)</span></span></div><div class="t m0 x50 hc y1cd ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">11111111<span class="_ _1e"> </span>***********************</span></div><div class="t m0 x26 h6 y1ce ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±<span class="_ _d"> </span><span class="ff4">infinity</span></span></div><div class="t m0 x50 hc y1cf ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">11111111<span class="_ _1e"> </span>00000000000000000000000</span></div><div class="t m0 x26 h6 y1d0 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Low<span class="_ _5"></span>est/La<span class="_ _5"></span>rgest<span class="_ _12"> </span>(<span class="ff7">±</span>3<span class="ff1a">.</span>40282<span class="_"> </span><span class="ff7">∗<span class="_ _13"> </span></span>10</span></div><div class="t m0 x36 h12 y1d1 ff6 fs6 fc0 sc0 ls0 ws0">+38</div><div class="t m0 x1c h6 y1d0 ff4 fs4 fc0 sc0 ls0 ws0">)</div><div class="t m0 x50 hc y1d2 ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">11111110<span class="_ _1e"> </span>11111111111111111111111</span></div><div class="t m0 x26 h6 y1d3 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Minimum<span class="_ _d"> </span>(normal)<span class="_ _12"> </span>(<span class="ff7">±</span>1<span class="ff1a">.</span>17549<span class="_"> </span><span class="ff7">∗<span class="_ _13"></span></span>10</span></div><div class="t m0 x1e h12 y1d4 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">38</span></div><div class="t m0 x62 h6 y1d3 ff4 fs4 fc0 sc0 ls0 ws0">)</div><div class="t m0 x50 hc y1d5 ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">00000001<span class="_ _1e"> </span>00000000000000000000000</span></div><div class="t m0 x26 h6 y1d6 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Denormal<span class="_ _12"> </span>numb<span class="_ _c"></span>er<span class="_ _12"> </span>(<span class="ff1a"><<span class="_ _25"> </span></span>2</span></div><div class="t m0 x63 h12 y1d7 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">126</span></div><div class="t m0 x40 h6 y1d6 ff4 fs4 fc0 sc0 ls0 ws0">)(minimum:<span class="_ _8"> </span>1<span class="ff1a">.</span>4<span class="_"> </span><span class="ff7">∗<span class="_ _13"> </span></span>10</div><div class="t m0 x56 h12 y1d7 ff1c fs6 fc0 sc0 ls0 ws0">−<span class="ff6">45</span></div><div class="t m0 x64 h6 y1d6 ff4 fs4 fc0 sc0 ls0 ws0">)</div><div class="t m0 x50 hc y1d8 ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">00000000<span class="_ _1e"> </span>***********************</span></div><div class="t m0 x26 h6 y1d9 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±<span class="ff4">0</span></span></div><div class="t m0 x50 hc y1da ff1f fs4 fc0 sc0 ls0 ws0">∗<span class="_ _53"> </span><span class="ffa">00000000<span class="_ _1e"> </span>00000000000000000000000</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">48/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf34" class="pf w0 h0" data-page-no="34"><div class="pc pc34 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Cheatsheet<span class="_ _52"> </span>2/3</div><div class="t m0 x58 h19 y1db ff5 fs4 fc0 sc0 ls0 ws0">E4M3<span class="_ _54"> </span>E5M2<span class="_ _54"> </span>half</div><div class="t m0 x65 hd y1dc ff1 fs8 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _55"> </span><span class="ffb">4<span class="_ _12"> </span>[0*-14]<span class="_ _12"> </span>(no<span class="_ _12"> </span>inf<span class="_ _0"></span>)<span class="_ _56"> </span>5-bit<span class="_ _12"> </span>[0*-30]</span></div><div class="t m0 x65 hd y1dd ff1 fs8 fc0 sc0 ls0 ws0">Bias<span class="_ _57"> </span><span class="ffb">7<span class="_ _58"> </span>15</span></div><div class="t m0 x65 hd y1de ff1 fs8 fc0 sc0 ls0 ws0">Mantissa<span class="_ _54"> </span><span class="ffb">4-bit<span class="_ _59"> </span>2-bit<span class="_ _5a"> </span>10-bit</span></div><div class="t m0 x65 hd y1df ff1 fs8 fc0 sc0 ls0 ws0">La<span class="_ _5"></span>rgest<span class="_ _12"> </span><span class="ffb">(<span class="ff13">±</span>)</span></div><div class="t m0 x63 hd y1e0 ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>75<span class="_"> </span><span class="ff13">∗<span class="_ _14"> </span></span>2</div><div class="t m0 x66 h13 y1e1 ff6 fs9 fc0 sc0 ls0 ws0">8</div><div class="t m0 x67 hd y1e2 ffb fs8 fc0 sc0 ls0 ws0">448</div><div class="t m0 x68 hd y1e3 ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>75<span class="_"> </span><span class="ff13">∗<span class="_ _14"> </span></span>2</div><div class="t m0 x24 h13 y1e4 ff6 fs9 fc0 sc0 ls0 ws0">15</div><div class="t m0 x53 hd y1e5 ffb fs8 fc0 sc0 ls0 ws0">57<span class="ff14">,<span class="_ _14"> </span></span>344</div><div class="t m0 x69 hd y1e3 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x6a h13 y1e4 ff6 fs9 fc0 sc0 ls0 ws0">16</div><div class="t m0 x6b hd y1e5 ffb fs8 fc0 sc0 ls0 ws0">65<span class="ff14">,<span class="_ _14"> </span></span>536</div><div class="t m0 x65 hd y1e6 ff1 fs8 fc0 sc0 ls0 ws0">Smallest<span class="_ _12"> </span><span class="ffb">(<span class="ff13">±</span>)</span></div><div class="t m0 x67 hd y1e7 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x60 h13 y1e8 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">6</span></div><div class="t m0 x6c hd y1e9 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>015625</div><div class="t m0 x6d hd y1e7 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x37 h13 y1e8 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">14</span></div><div class="t m0 x6e hd y1e9 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>00006</div><div class="t m0 x65 hd y1ea ff1 fs8 fc0 sc0 ls0 ws0">Smallest<span class="_ _d"> </span>Deno<span class="_ _5"></span>rmal</div><div class="t m0 x67 hd y1eb ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x60 h13 y1ec ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">9</span></div><div class="t m0 x51 hd y1ed ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>001953125</div><div class="t m0 x56 hd y1eb ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x6f h13 y1ec ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">16</span></div><div class="t m0 x44 hd y1ed ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>5258<span class="_"> </span><span class="ff13">∗<span class="_ _14"> </span></span>10</div><div class="t m0 x19 h13 y1ee ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">5</span></div><div class="t m0 x70 hd y1eb ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x71 h13 y1ec ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">24</span></div><div class="t m0 x72 hd y1ed ffb fs8 fc0 sc0 ls0 ws0">6<span class="ff14">.</span>0<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x73 h13 y1ee ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">8</span></div><div class="t m0 x65 hd y1ef ff1 fs8 fc0 sc0 ls0 ws0">Epsilon</div><div class="t m0 x67 hd y1f0 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x60 h13 y1f1 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">4</span></div><div class="t m0 x33 hd y1f2 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>0625</div><div class="t m0 x4f hd y1f0 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x74 h13 y1f1 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">2</span></div><div class="t m0 x56 hd y1f2 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>25</div><div class="t m0 x70 hd y1f0 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x71 h13 y1f1 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">10</span></div><div class="t m0 x75 hd y1f2 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>00098</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf35" class="pf w0 h0" data-page-no="35"><div class="pc pc35 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Cheatsheet<span class="_ _52"> </span>3/3</div><div class="t m0 x22 h19 y1f3 ff5 fs4 fc0 sc0 ls0 ws0">bfloat16<span class="_ _5b"> </span>float<span class="_ _5c"> </span>double</div><div class="t m0 x65 hd y1f4 ff1 fs8 fc0 sc0 ls0 ws0">Exp<span class="_ _c"></span>onent<span class="_ _5d"> </span><span class="ffb">8-bit<span class="_ _12"> </span>[0*-254]<span class="_ _5e"> </span>11-bit<span class="_ _12"> </span>[0*-2046]</span></div><div class="t m0 x65 hd y1f5 ff1 fs8 fc0 sc0 ls0 ws0">Bias<span class="_ _5f"> </span><span class="ffb">127<span class="_ _60"> </span>1023</span></div><div class="t m0 x65 hd y1f6 ff1 fs8 fc0 sc0 ls0 ws0">Mantissa<span class="_ _54"> </span><span class="ffb">7-bit<span class="_ _5a"> </span>23-bit<span class="_ _61"> </span>52-bit</span></div><div class="t m0 x65 hd y1f7 ff1 fs8 fc0 sc0 ls0 ws0">La<span class="_ _5"></span>rgest<span class="_ _12"> </span><span class="ffb">(<span class="ff13">±</span>)</span></div><div class="t m0 x76 hd y1f8 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x77 h13 y1f9 ff6 fs9 fc0 sc0 ls0 ws0">128</div><div class="t m0 x78 hd y1fa ffb fs8 fc0 sc0 ls0 ws0">3<span class="ff14">.</span>4<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x4b h13 y1fb ff6 fs9 fc0 sc0 ls0 ws0">38</div><div class="t m0 x70 hd y1f8 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x71 h13 y1f9 ff6 fs9 fc0 sc0 ls0 ws0">1024</div><div class="t m0 x72 hd y1fa ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>8<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x73 h13 y1fb ff6 fs9 fc0 sc0 ls0 ws0">308</div><div class="t m0 x65 hd y1fc ff1 fs8 fc0 sc0 ls0 ws0">Smallest<span class="_ _12"> </span><span class="ffb">(<span class="ff13">±</span>)</span></div><div class="t m0 x79 hd y1fd ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x3d h13 y1fe ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">126</span></div><div class="t m0 x7a hd y1ff ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>2<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x43 h13 y200 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">38</span></div><div class="t m0 x7b hd y1fd ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x49 h13 y1fe ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">1022</span></div><div class="t m0 x7c hd y1ff ffb fs8 fc0 sc0 ls0 ws0">2<span class="ff14">.</span>2<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x13 h13 y200 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">308</span></div><div class="t m0 x65 hd y201 ff1 fs8 fc0 sc0 ls0 ws0">Smallest<span class="_ _d"> </span>Deno<span class="_ _5"></span>rmal<span class="_ _2e"> </span><span class="ffb">/</span></div><div class="t m0 x7d hd y202 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x4f h13 y203 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">149</span></div><div class="t m0 x7e hd y204 ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>4<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x34 h13 y205 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">45</span></div><div class="t m0 x7b hd y202 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x49 h13 y203 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">1074</span></div><div class="t m0 x7c hd y204 ffb fs8 fc0 sc0 ls0 ws0">4<span class="ff14">.</span>9<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x13 h13 y205 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">324</span></div><div class="t m0 x65 hd y206 ff1 fs8 fc0 sc0 ls0 ws0">Epsilon</div><div class="t m0 x67 hd y207 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x60 h13 y208 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">7</span></div><div class="t m0 x33 hd y209 ffb fs8 fc0 sc0 ls0 ws0">0<span class="ff14">.</span>0078</div><div class="t m0 x56 hd y207 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x6f h13 y208 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">23</span></div><div class="t m0 x68 hd y209 ffb fs8 fc0 sc0 ls0 ws0">1<span class="ff14">.</span>2<span class="_"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x7f h13 y20a ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">7</span></div><div class="t m0 x70 hd y207 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x71 h13 y208 ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">52</span></div><div class="t m0 x80 hd y209 ffb fs8 fc0 sc0 ls0 ws0">2<span class="ff14">.</span>2<span class="_ _14"> </span><span class="ff13">·<span class="_ _14"> </span></span>10</div><div class="t m0 x81 h13 y20a ff20 fs9 fc0 sc0 ls0 ws0">−<span class="ff6">16</span></div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf36" class="pf w0 h0" data-page-no="36"><div class="pc pc36 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Limits</div><div class="t m0 xe he yd9 ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><limits></span></div><div class="t m0 xe he yda ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>T:<span class="_ _f"> </span>float<span class="_ _a"> </span>or<span class="_ _f"> </span>double</div><div class="t m0 xe he ydb ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">max</span></span>();<span class="_ _62"> </span><span class="ffe fc9">//<span class="_ _f"> </span>largest<span class="_ _f"> </span>value</span></div><div class="t m0 xe he ydd ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">lowest</span></span>();<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _a"> </span>lowest<span class="_ _f"> </span>value<span class="_ _f"> </span>(C++11)</span></div><div class="t m0 xe he ydf ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">min</span></span>();<span class="_ _62"> </span><span class="ffe fc9">//<span class="_ _f"> </span>smallest<span class="_ _f"> </span>value</span></div><div class="t m0 xe he y20b ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">denorm<span class="_ _d"> </span>min</span></span>()<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _a"> </span>smallest<span class="_ _f"> </span>(denormal)<span class="_ _f"> </span>value</span></div><div class="t m0 xe he ye2 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">epsilon</span></span>();<span class="_ _45"> </span><span class="ffe fc9">//<span class="_ _a"> </span>epsilon<span class="_ _f"> </span>value</span></div><div class="t m0 xe he ye4 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">infinity</span></span>()<span class="_ _45"> </span><span class="ffe fc9">//<span class="_ _a"> </span><span class="ff21">infinity</span></span></div><div class="t m0 xe he y20c ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span>T<span class="fc8">>::<span class="fc4">quiet<span class="_ _d"> </span>NaN</span></span>()<span class="_ _27"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ff21">NaN</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">53/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf37" class="pf w0 h0" data-page-no="37"><div class="pc pc37 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>-<span class="_ _8"> </span>Useful<span class="_ _f"> </span>F<span class="_ _5"></span>unctions</div><div class="t m0 xe he y20d ffe fs8 fca sc0 ls0 ws0">#<span class="_ _14"> </span>include<span class="_ _28"> </span><span class="fc9"><cmath><span class="_ _28"> </span>//<span class="_ _a"> </span>C++11</span></div><div class="t m0 xe he y20e ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc0">std<span class="fc8">::<span class="fc4">isnan</span></span>(T<span class="_ _f"> </span>value)<span class="_ _36"> </span><span class="ffe fc9">//<span class="_ _f"> </span>check<span class="_ _a"> </span>if<span class="_ _f"> </span>value<span class="_ _f"> </span>is<span class="_ _f"> </span>NaN</span></span></div><div class="t m0 xe he y20f ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc0">std<span class="fc8">::<span class="fc4">isinf</span></span>(T<span class="_ _f"> </span>value)<span class="_ _36"> </span><span class="ffe fc9">//<span class="_ _f"> </span>check<span class="_ _a"> </span>if<span class="_ _f"> </span>value<span class="_ _f"> </span>is<span class="_ _f"> </span><span class="ff13">±</span>infinity</span></span></div><div class="t m0 xe he y210 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc0">std<span class="fc8">::<span class="fc4">isfinite</span></span>(T<span class="_ _f"> </span>value)<span class="_ _23"> </span><span class="ffe fc9">//<span class="_ _f"> </span>check<span class="_ _f"> </span>if<span class="_ _a"> </span>value<span class="_ _f"> </span>is<span class="_ _f"> </span>not<span class="_ _f"> </span>NaN</span></span></div><div class="t m0 x3e he y211 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>and<span class="_ _f"> </span>not<span class="_ _a"> </span><span class="ff13">±</span>infinity</div><div class="t m0 xe he y212 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc0">std<span class="fc8">::<span class="fc4">isnormal</span></span>(T<span class="_ _f"> </span>value);<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>check<span class="_ _f"> </span>if<span class="_ _f"> </span>value<span class="_ _a"> </span>is<span class="_ _f"> </span>Normal</span></span></div><div class="t m0 xe hd y213 ffc fs8 fc0 sc0 ls0 ws0">T<span class="_ _46"> </span>std<span class="fc8">::<span class="fc4">ldexp</span></span>(T<span class="_ _a"> </span>x,<span class="_ _f"> </span>p)<span class="_ _29"> </span><span class="ffe fc9">//<span class="_ _f"> </span>exponent<span class="_ _f"> </span>shift<span class="_ _a"> </span><span class="ff12">x<span class="_ _25"> </span><span class="ff13">∗<span class="_ _13"> </span><span class="ffb">2</span></span></span></span></div><div class="t m0 x24 h1a y214 ff10 fs9 fc9 sc0 ls0 ws0">p</div><div class="t m0 xe he y215 ff5 fs8 fc7 sc0 ls0 ws0">int<span class="_ _27"> </span><span class="ffc fc0">std<span class="fc8">::<span class="fc4">ilogb</span></span>(T<span class="_ _f"> </span>value)<span class="_ _36"> </span><span class="ffe fc9">//<span class="_ _f"> </span>extracts<span class="_ _f"> </span>the<span class="_ _a"> </span>exponent<span class="_ _f"> </span>of<span class="_ _f"> </span>value</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">54/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf38" class="pf w0 h0" data-page-no="38"><div class="pc pc38 w0 h0"><img class="bi x0 y0 w1 h1" alt="" 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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Arithmetic<span class="_ _8"> </span>Prop<span class="_ _c"></span>erties<span class="_ _63"> </span>1/3</div><div class="t m0 x1 hb y216 ff4 fs7 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>op<span class="_ _c"></span>erations<span class="_ _e"> </span>are<span class="_ _d"> </span>written</div><div class="t m0 xb hb y217 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">⊕<span class="_ _e"> </span><span class="ff4">addition</span></span></div><div class="t m0 xb hb y218 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">⊖<span class="_ _e"> </span><span class="ff4">subtraction</span></span></div><div class="t m0 xb hb y219 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">⊗<span class="_ _e"> </span><span class="ff4">multiplication</span></span></div><div class="t m0 xb hb y21a ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">⊘<span class="_ _e"> </span><span class="ff4">division</span></span></div><div class="t m0 x1 hb y21b ff7 fs7 fc0 sc0 ls0 ws0">⊙<span class="_ _12"> </span>∈<span class="_ _12"> </span>{⊕<span class="ff1a">,<span class="_ _14"> </span></span>⊖<span class="ff1a">,<span class="_ _14"> </span></span>⊗<span class="ff1a">,<span class="_ _14"> </span></span>⊘}</div><div class="t m0 x1 hb y21c ff9 fs7 fc0 sc0 ls0 ws0">op<span class="_ _d"> </span><span class="ff7">∈<span class="_ _12"> </span>{<span class="ff4">+<span class="ff1a">,<span class="_ _14"> </span></span></span>−<span class="ff1a">,<span class="_ _13"> </span></span>∗<span class="ff1a">,<span class="_ _14"> </span>/</span>}<span class="_ _d"> </span><span class="ff4">denotes<span class="_ _e"> </span>exact<span class="_ _e"> </span>precision<span class="_ _d"> </span>op<span class="_ _c"></span>erations</span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">55/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Arithmetic<span class="_ _8"> </span>Prop<span class="_ _c"></span>erties<span class="_ _63"> </span>2/3</div><div class="t m0 x82 hb y5f ff9 fs7 fc0 sc0 ls0 ws0">(P1)<span class="_ _18"> </span><span class="ff4">In<span class="_ _e"> </span>general,<span class="_ _e"> </span></span>a<span class="_ _12"> </span>op<span class="_ _e"> </span>b<span class="_ _e"> </span><span class="ff7"><span class="ff4">=<span class="_ _12"> </span></span></span>a<span class="_"> </span><span class="ff7">⊙<span class="_ _13"> </span></span>b</div><div class="t m0 x82 hb y21d ff9 fs7 fc0 sc0 ls0 ws0">(P2)<span class="_ _18"> </span><span class="ff1">Not<span class="_ _7"> </span>Reflexive<span class="_ _e"> </span></span>a<span class="_ _d"> </span><span class="ff7"><span class="ff4">=<span class="_ _12"> </span></span></span>a</div><div class="t m0 x20 hb y21e ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Reflexive<span class="_ _8"> </span><span class="ff4">without<span class="_ _e"> </span><span class="ffa">NaN</span></span></span></div><div class="t m0 x82 hb y21f ff9 fs7 fc0 sc0 ls0 ws0">(P3)<span class="_ _18"> </span><span class="ff1">Not<span class="_ _7"> </span>Commutative<span class="_ _e"> </span></span>a<span class="_"> </span><span class="ff7">⊙<span class="_ _25"> </span></span>b<span class="_ _d"> </span><span class="ff7"><span class="ff4">=<span class="_ _12"> </span></span></span>b<span class="_ _25"> </span><span class="ff7">⊙<span class="_ _25"> </span></span>a</div><div class="t m0 x20 hb y220 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">Commutative<span class="_ _8"> </span><span class="ff4">without<span class="_ _e"> </span><span class="ffa">NaN<span class="_ _e"> </span></span>(<span class="ffa">NaN<span class="_ _e"> </span><span class="ff7"></span></span>=<span class="_ _e"> </span><span class="ffa">NaN</span>)</span></span></div><div class="t m0 x82 hb y221 ff9 fs7 fc0 sc0 ls0 ws0">(P4)<span class="_ _18"> </span><span class="ff4">In<span class="_ _e"> </span>general,<span class="_ _e"> </span><span class="ff1">Not<span class="_ _7"> </span>Asso<span class="_ _c"></span>ciative<span class="_ _e"> </span></span>(</span>a<span class="_"> </span><span class="ff7">⊙<span class="_ _13"> </span></span>b<span class="_ _0"></span><span class="ff4">)<span class="_ _13"> </span><span class="ff7">⊙<span class="_ _25"> </span></span></span>c<span class="_ _e"> </span><span class="ff7"><span class="ff4">=<span class="_ _12"> </span></span></span>a<span class="_"> </span><span class="ff7">⊙<span class="_ _25"> </span><span class="ff4">(</span></span>b<span class="_"> </span><span class="ff7">⊙<span class="_ _25"> </span></span>c<span class="_ _0"></span><span class="ff4">)</span></div><div class="t m0 x20 hb y222 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">even<span class="_ _e"> </span>excluding<span class="_ _e"> </span><span class="ffa">NaN<span class="_ _e"> </span></span>and<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span></span>in<span class="_ _e"> </span>intermediate<span class="_ _e"> </span>computations</span></div><div class="t m0 x82 hb y223 ff9 fs7 fc0 sc0 ls0 ws0">(P5)<span class="_ _18"> </span><span class="ff4">In<span class="_ _e"> </span>general,<span class="_ _e"> </span><span class="ff1">Not<span class="_ _7"> </span>Distributive<span class="_ _e"> </span></span>(</span>a<span class="_"> </span><span class="ff7">⊕<span class="_ _25"> </span></span>b<span class="_ _c"></span><span class="ff4">)<span class="_ _13"> </span><span class="ff7">⊗<span class="_ _13"> </span></span></span>c<span class="_ _8"> </span><span class="ff7"><span class="ff4">=<span class="_ _25"> </span>(</span></span>a<span class="_ _25"> </span><span class="ff7">⊗<span class="_ _25"> </span></span>c<span class="_ _0"></span><span class="ff4">)<span class="_"> </span><span class="ff7">⊕<span class="_ _13"></span></span>(</span>b<span class="_ _25"> </span><span class="ff7">⊗<span class="_ _25"> </span></span>c<span class="_ _0"></span><span class="ff4">)</span></div><div class="t m0 x20 hb y224 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">even<span class="_ _e"> </span>excluding<span class="_ _e"> </span><span class="ffa">NaN<span class="_ _e"> </span></span>and<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span></span>in<span class="_ _e"> </span>intermediate<span class="_ _e"> </span>computations</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">56/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Arithmetic<span class="_ _8"> </span>Prop<span class="_ _c"></span>erties<span class="_ _63"> </span>3/3</div><div class="t m0 x82 hb y225 ff9 fs7 fc0 sc0 ls0 ws0">(P6)<span class="_ _18"> </span><span class="ff1">Identit<span class="_ _5"></span>y<span class="_ _7"> </span>on<span class="_ _7"> </span>op<span class="_ _c"></span>erations<span class="_ _7"> </span>is<span class="_ _8"> </span>not<span class="_ _7"> </span>ensured</span></div><div class="t m0 x20 hb y226 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">(<span class="ff9">a<span class="_"> </span><span class="ff7">⊖<span class="_ _25"> </span></span>b<span class="_ _c"></span></span>)<span class="_ _13"> </span><span class="ff7">⊕<span class="_ _13"> </span><span class="ff9">b<span class="_ _e"> </span></span></span>=<span class="_ _12"> </span><span class="ff9">a</span></span></div><div class="t m0 x20 hb y227 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">(<span class="ff9">a<span class="_"> </span><span class="ff7">⊘<span class="_ _25"> </span></span>b<span class="_ _c"></span></span>)<span class="_ _13"> </span><span class="ff7">⊗<span class="_ _13"> </span><span class="ff9">b<span class="_ _e"> </span></span></span>=<span class="_ _12"> </span><span class="ff9">a</span></span></div><div class="t m0 x82 hb y228 ff9 fs7 fc0 sc0 ls0 ws0">(P7)<span class="_ _18"> </span><span class="ff1">Overflo<span class="_ _5"></span>w/Underflo<span class="_ _5"></span>w<span class="_ _e"> </span><span class="ff4">Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>has</span></span></div><div class="t m0 x7e hb y229 ff9 fs7 fc0 sc0 ls0 ws0">“saturation”<span class="_ _f"> </span><span class="ff4">values<span class="_ _e"> </span><span class="ffa">inf,<span class="_ _18"> </span>-inf</span></span></div><div class="t m0 x20 hb y22a ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">as<span class="_ _e"> </span>opp<span class="_ _c"></span>osite<span class="_ _d"> </span>to<span class="_ _e"> </span>integer<span class="_ _e"> </span>arithmetic<span class="_ _d"> </span>with<span class="_ _7"> </span>wrap-a<span class="_ _5"></span>round<span class="_ _e"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">57/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Sp<span class="_ _c"></span>ecial<span class="_ _8"> </span>V<span class="_ _5"></span>alues<span class="_ _8"> </span>Behavior</div><div class="t m0 x7 hb y22b ff1 fs7 fc0 sc0 ls0 ws0">Zero<span class="_ _7"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</div><div class="t m0 x20 hb y22c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff9">a<span class="_"> </span><span class="ff7">⊘<span class="_ _25"> </span><span class="ff4">0<span class="_ _d"> </span><span class="ffa">=<span class="_ _18"> </span>inf</span>,<span class="_ _e"> </span></span></span>a<span class="_ _d"> </span><span class="ff7">∈<span class="_ _12"> </span>{</span>finite<span class="_ _12"> </span><span class="ff7">−<span class="_ _13"> </span><span class="ff4">0</span>}<span class="_ _44"> </span><span class="ffb fs8">[IEEE-764],<span class="_ _12"> </span>undefined<span class="_ _12"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _12"> </span>in<span class="_ _12"> </span>C++</span></span></span></div><div class="t m0 x20 hb y22d ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">0<span class="_"> </span><span class="ff7">⊘<span class="_ _13"></span></span>0,<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span><span class="ff7">⊘<span class="_ _12"> </span></span></span>0<span class="_ _e"> </span><span class="ffa">=<span class="_ _18"> </span>NaN<span class="_ _19"> </span><span class="ffb fs8">[IEEE-764],<span class="_ _12"> </span>undefined<span class="_ _12"> </span>b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r<span class="_ _12"> </span>in<span class="_ _12"> </span>C++</span></span></span></div><div class="t m0 x20 hb y22e ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">0<span class="_ _12"> </span><span class="ff7">⊗<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span>=<span class="_ _18"> </span>NaN</span></span></span></div><div class="t m0 x20 hb y22f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">+0<span class="_ _18"> </span>=<span class="_ _18"> </span>-0<span class="_ _21"> </span><span class="ff4">but<span class="_ _e"> </span>they<span class="_ _e"> </span>have<span class="_ _e"> </span>a<span class="_ _e"> </span>different<span class="_ _e"> </span>binary<span class="_ _d"> </span>representation</span></span></div><div class="t m0 x7 hb y230 ff5 fs7 fc0 sc0 ls0 ws0">Inf<span class="_ _7"> </span><span class="ff1">b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></div><div class="t m0 x20 hb y231 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">inf<span class="_ _e"> </span><span class="ff7">⊙<span class="_ _12"> </span><span class="ff9">a<span class="_ _7"> </span></span></span>=<span class="_ _18"> </span>inf<span class="ff4">,<span class="_ _e"> </span><span class="ff9">a<span class="_ _d"> </span><span class="ff7">∈<span class="_ _12"> </span>{</span>finite<span class="_ _12"> </span><span class="ff7">−<span class="_ _13"> </span></span></span>0<span class="ff7">}</span></span></span></div><div class="t m0 x20 hb y232 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">inf<span class="_ _e"> </span><span class="ff7">⊕⊗<span class="_ _e"> </span></span>inf<span class="_ _e"> </span>=<span class="_ _18"> </span>inf</span></div><div class="t m0 x20 hb y233 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">inf<span class="_ _e"> </span><span class="ff7">⊖⊘<span class="_ _e"> </span></span>inf<span class="_ _e"> </span>=<span class="_ _18"> </span>NaN</span></div><div class="t m0 x20 hb y234 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span></span>⊙<span class="_ _12"> </span>∓<span class="_ _e"> </span><span class="ffa">inf<span class="_ _e"> </span>=<span class="_ _18"> </span>NaN</span></span></div><div class="t m0 x20 hb y235 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff7">±<span class="_ _e"> </span><span class="ffa">inf<span class="_ _18"> </span>=<span class="_ _e"> </span></span>±<span class="_ _e"> </span><span class="ffa">inf</span></span></div><div class="t m0 x7 hb y236 ff5 fs7 fc0 sc0 ls0 ws0">NaN<span class="_ _7"> </span><span class="ff1">b<span class="_ _c"></span>ehavio<span class="_ _5"></span>r</span></div><div class="t m0 x20 hb y237 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">NaN<span class="_ _e"> </span><span class="ff7">⊙<span class="_ _12"> </span><span class="ff9">a<span class="_ _7"> </span></span></span>=<span class="_ _18"> </span>NaN</span></div><div class="t m0 x20 hb y238 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">NaN<span class="_ _e"> </span><span class="ff7"><span class="ff4">=<span class="_ _12"> </span><span class="ff9">a</span></span></span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">58/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-P<span class="_ _5"></span>oint<span class="_ _8"> </span>Undefined<span class="_ _f"> </span>Behavio<span class="_ _5"></span>r</div><div class="t m0 xb hb y5f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Division<span class="_ _7"> </span>by<span class="_ _e"> </span>zero</span></div><div class="t m0 x7 h6 y239 ff4 fs4 fc0 sc0 ls0 ws0">e.g.,<span class="_ _64"> </span>10</div><div class="t m0 x3b h12 y23a ff6 fs6 fc0 sc0 ls0 ws0">8</div><div class="t m0 x2e h6 y239 ff1a fs4 fc0 sc0 ls0 ws0">/<span class="ff4">0</span>.<span class="ff4">0</span></div><div class="t m0 xb hb y23b ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Conversion<span class="_ _7"> </span>to<span class="_ _7"> </span>a<span class="_ _8"> </span>na<span class="_ _5"></span>rro<span class="_ _5"></span>w<span class="_ _5"></span>er<span class="_ _7"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _7"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="ff4">:</span></span></div><div class="t m0 x7 h6 y23c ff4 fs4 fc0 sc0 ls0 ws0">e.g.,<span class="_ _64"> </span>0<span class="ff1a">.</span>1<span class="_ _a"> </span><span class="ffa">double<span class="_ _4"> </span><span class="ff7">→<span class="_ _a"> </span></span>float</span></div><div class="t m0 xb hb y23d ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Conversion<span class="_ _7"> </span>from<span class="_ _7"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _7"> </span>to<span class="_ _8"> </span>integer<span class="ff4">:</span></span></div><div class="t m0 x7 hb y23e ff4 fs7 fc0 sc0 ls0 ws0">e.g.,</div><div class="t m0 x83 h6 y23f ff4 fs4 fc0 sc0 ls0 ws0">10</div><div class="t m0 x57 h12 y240 ff6 fs6 fc0 sc0 ls0 ws0">8</div><div class="t m0 x32 h6 y23f ffa fs4 fc0 sc0 ls0 ws0">float<span class="_ _a"> </span><span class="ff7">→<span class="_ _4"> </span></span>int</div><div class="t m0 xb hb y68 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Op<span class="_ _c"></span>erations<span class="_ _7"> </span>on<span class="_ _7"> </span>signaling<span class="_ _7"> </span>NaNs<span class="ff4">:<span class="_ _a"> </span>Arithmetic<span class="_ _e"> </span>op<span class="_ _c"></span>erations<span class="_ _d"> </span>that<span class="_ _e"> </span>cause<span class="_ _e"> </span>an<span class="_ _e"> </span>“invalid</span></span></div><div class="t m0 x7 hb y241 ff4 fs7 fc0 sc0 ls0 ws0">op<span class="_ _c"></span>eration”<span class="_ _d"> </span>exception<span class="_ _e"> </span>to<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>signaled</div><div class="t m0 x7 hb y242 ff4 fs7 fc0 sc0 ls0 ws0">e.g.,<span class="_ _21"> </span><span class="ffa fs4">inf<span class="_ _a"> </span>-<span class="_ _4"> </span>inf</span></div><div class="t m0 xb hb y243 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Inco<span class="_ _5"></span>rrectly<span class="_ _7"> </span>assuming<span class="_ _7"> </span>IEEE-754<span class="_ _8"> </span>compliance<span class="_ _7"> </span>for<span class="_ _e"> </span>all<span class="_ _7"> </span>platforms<span class="ff4">:</span></span></div><div class="t m0 x7 hb y244 ff4 fs7 fc0 sc0 ls0 ws0">e.g.,<span class="_ _e"> </span><span class="fs4">Some<span class="_ _d"> </span>emb<span class="_ _c"></span>edded<span class="_ _12"> </span>Linux<span class="_ _d"> </span>distribution<span class="_ _d"> </span>on<span class="_ _d"> </span>ARM</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">59/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Detect<span class="_ _8"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Errors</div><div class="t m0 x17 h1b y245 ff22 fs5 fc1 sc0 ls0 ws0">⋆</div><div class="t m0 x84 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">1/2</div><div class="t m0 x1 hb y7f ff4 fs7 fc6 sc0 ls0 ws0">C++11<span class="_ _e"> </span><span class="fc0">allo<span class="_ _5"></span>ws<span class="_ _e"> </span>determining<span class="_ _e"> </span>if<span class="_ _e"> </span>a<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>exceptional<span class="_ _e"> </span>condition<span class="_ _e"> </span>has<span class="_ _e"> </span>o<span class="_ _c"></span>ccurred<span class="_ _e"> </span>by</span></div><div class="t m0 x1 hb y246 ff4 fs7 fc0 sc0 ls0 ws0">using<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>exception<span class="_ _e"> </span>facilities<span class="_ _e"> </span>provided<span class="_ _d"> </span>in<span class="_ _21"> </span><span class="ff23"><<span class="ff5">cfenv</span>></span></div><div class="t m0 xe he y247 ffe fs8 fca sc0 ls0 ws0">#include<span class="_ _28"> </span><span class="fc9"><cfenv></span></div><div class="t m0 xe he y248 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>MACRO</div><div class="t m0 xe he y249 ffc fs8 fc0 sc0 ls0 ws0">FE_DIVBYZERO<span class="_ _27"> </span><span class="ffe fc9">//<span class="_ _f"> </span>division<span class="_ _a"> </span>by<span class="_ _8"> </span>zero</span></div><div class="t m0 xe he y24a ffc fs8 fc0 sc0 ls0 ws0">FE_INEXACT<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _a"> </span>rounding<span class="_ _f"> </span>error</span></div><div class="t m0 xe he y24b ffc fs8 fc0 sc0 ls0 ws0">FE_INVALID<span class="_ _46"> </span><span class="ffe fc9">//<span class="_ _a"> </span>invalid<span class="_ _f"> </span>operation,<span class="_ _f"> </span>i.e.<span class="_ _f"> </span>NaN</span></div><div class="t m0 xe he y24c ffc fs8 fc0 sc0 ls0 ws0">FE_OVERFLOW<span class="_ _45"> </span><span class="ffe fc9">//<span class="_ _a"> </span>overflow<span class="_ _f"> </span>(reach<span class="_ _f"> </span>saturation<span class="_ _f"> </span>value<span class="_ _a"> </span>+inf)</span></div><div class="t m0 xe he y24d ffc fs8 fc0 sc0 ls0 ws0">FE_UNDERFLOW<span class="_ _27"> </span><span class="ffe fc9">//<span class="_ _f"> </span>underflow<span class="_ _27"> </span>(reach<span class="_ _a"> </span>saturation<span class="_ _f"> </span>value<span class="_ _f"> </span>-inf)</span></div><div class="t m0 xe he y24e ffc fs8 fc0 sc0 ls0 ws0">FE_ALL_EXCEPT<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>all<span class="_ _a"> </span>exceptions</span></div><div class="t m0 xe he y24f ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>functions</div><div class="t m0 xe he y250 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>feclearexcept(FE_ALL_EXCEPT);<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>clear<span class="_ _a"> </span>exception<span class="_ _f"> </span>status</span></div><div class="t m0 xe he y251 ffc fs8 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>fetestexcept(<span class="fc8"><</span>macro<span class="fc8">></span>);<span class="_ _2f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>returns<span class="_ _f"> </span>a<span class="_ _a"> </span>value<span class="_ _f"> </span>!=<span class="_ _f"> </span>0<span class="_ _f"> </span>if<span class="_ _a"> </span>an</span></div><div class="t m0 x7a he y252 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>exception<span class="_ _f"> </span>has<span class="_ _a"> </span>been<span class="_ _f"> </span>detected</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">60/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Detect<span class="_ _8"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Errors</div><div class="t m0 x17 h1b y245 ff22 fs5 fc1 sc0 ls0 ws0">⋆</div><div class="t m0 x84 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">2/2</div><div class="t m0 xe h10 y253 ffe fs5 fca sc0 ls0 ws0">#include<span class="_ _4"> </span><span class="fc9"><cfenv><span class="_ _65"> </span>//<span class="_ _8"> </span>floating<span class="_ _7"> </span>point<span class="_ _8"> </span>exceptions</span></div><div class="t m0 xe h10 y254 ffe fs5 fca sc0 ls0 ws0">#include<span class="_ _4"> </span><span class="fc9"><iostream></span></div><div class="t m0 xe h10 y255 ffe fs5 fca sc0 ls0 ws0">#pragma<span class="_ _8"> </span>STDC<span class="_ _7"> </span>FENV_ACCESS<span class="_ _8"> </span>ON<span class="_ _18"> </span><span class="fc9">//<span class="_ _8"> </span>tell<span class="_ _8"> </span>the<span class="_ _7"> </span>compiler<span class="_ _8"> </span>to<span class="_ _8"> </span>manipulate<span class="_ _8"> </span>the<span class="_ _8"> </span>floating-point</span></div><div class="t m0 x54 h10 y256 ffe fs5 fc9 sc0 ls0 ws0">//<span class="_ _8"> </span>environment<span class="_ _7"> </span>(not<span class="_ _8"> </span>supported<span class="_ _8"> </span>by<span class="_ _8"> </span>all<span class="_ _8"> </span>compilers)</div><div class="t m0 x54 h10 y257 ffe fs5 fc9 sc0 ls0 ws0">//<span class="_ _8"> </span>gcc:<span class="_ _7"> </span>yes,<span class="_ _8"> </span>clang:<span class="_ _8"> </span>no</div><div class="t m0 xe h10 y258 ff5 fs5 fc7 sc0 ls0 ws0">int<span class="_ _8"> </span><span class="ff15 fc4">main<span class="fc0">()<span class="_ _8"> </span>{</span></span></div><div class="t m0 x11 h10 y259 ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>feclearexcept(FE_ALL_EXCEPT);<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>clear</span></div><div class="t m0 x11 h10 y25a ff5 fs5 fcb sc0 ls0 ws0">auto<span class="_ _8"> </span><span class="ff15 fc0">x<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>1.0<span class="_ _8"> </span>/<span class="_ _8"> </span>0.0</span>;<span class="_ _66"> </span><span class="ffe fc9">//<span class="_ _8"> </span>all<span class="_ _7"> </span>compilers</span></span></div><div class="t m0 x11 h10 y25b ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>(<span class="ff5 fc7">bool</span>)<span class="_ _8"> </span>std<span class="fc8">::</span>fetestexcept(FE_DIVBYZERO);<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>true</span></div><div class="t m0 x11 h10 y25c ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>feclearexcept(FE_ALL_EXCEPT);<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>clear</span></div><div class="t m0 x11 h10 y25d ff5 fs5 fcb sc0 ls0 ws0">auto<span class="_ _8"> </span><span class="ff15 fc0">x2<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>0.0<span class="_ _8"> </span>/<span class="_ _8"> </span>0.0</span>;<span class="_ _67"> </span><span class="ffe fc9">//<span class="_ _8"> </span>all<span class="_ _7"> </span>compilers</span></span></div><div class="t m0 x11 h10 y25e ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>(<span class="ff5 fc7">bool</span>)<span class="_ _11"> </span>std<span class="fc8">::</span>fetestexcept(FE_INVALID);<span class="_ _11"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>true</span></div><div class="t m0 x11 h10 y25f ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>feclearexcept(FE_ALL_EXCEPT);<span class="_ _8"> </span><span class="ffe fc9">//<span class="_ _8"> </span>clear</span></div><div class="t m0 x11 h10 y260 ff5 fs5 fcb sc0 ls0 ws0">auto<span class="_ _8"> </span><span class="ff15 fc0">x4<span class="_ _8"> </span><span class="fc8">=<span class="_ _8"> </span>1e38f<span class="_ _8"> </span>*<span class="_ _8"> </span>10</span>;<span class="_ _68"> </span><span class="ffe fc9">//<span class="_ _8"> </span>gcc:<span class="_ _7"> </span>ok</span></span></div><div class="t m0 x11 h10 y261 ff15 fs5 fc0 sc0 ls0 ws0">std<span class="fc8">::</span>cout<span class="_ _8"> </span><span class="fc8"><<<span class="_ _8"> </span></span>std<span class="fc8">::</span>fetestexcept(FE_OVERFLOW);<span class="_ _1e"> </span><span class="ffe fc9">//<span class="_ _8"> </span>print<span class="_ _7"> </span>true</span></div><div class="t m0 xe h10 y262 ff15 fs5 fc0 sc0 ls0 ws0">}</div><div class="t m0 xb hd y263 ffb fs8 fc3 sc0 ls0 ws0">see<span class="_ _12"> </span><span class="ffc">What<span class="_ _f"> </span>is<span class="_ _a"> </span>the<span class="_ _8"> </span>difference<span class="_ _a"> </span>between<span class="_ _f"> </span>quiet<span class="_ _f"> </span>NaN<span class="_ _f"> </span>and<span class="_ _a"> </span>signaling<span class="_ _f"> </span>NaN?</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">61/77</div><a class="l" href="https://stackoverflow.com/questions/18118408/what-is-the-difference-between-quiet-nan-and-signaling-nan"><div class="d m1" style="border-style:none;position:absolute;left:49.518000px;bottom:-0.698000px;width:279.726000px;height:13.445000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Some<span class="_ _8"> </span>Examples...<span class="_ _69"> </span>1/4</div><div class="t m0 x1 hb y264 ff1 fs7 fc0 sc0 ls0 ws0">Ariene<span class="_ _8"> </span>5:<span class="_ _4"> </span><span class="ff4">data<span class="_ _8"> </span>conversion<span class="_ _7"> </span>from<span class="_ _7"> </span>64-bit</span></div><div class="t m0 x1 hb y265 ff4 fs7 fc0 sc0 ls0 ws0">floating<span class="_ _d"> </span>p<span class="_ _c"></span>oint<span class="_ _e"> </span>value<span class="_ _d"> </span>to<span class="_ _e"> </span>16-bit<span class="_ _d"> </span>signed<span class="_ _e"> </span>in-</div><div class="t m0 x1 hb y266 ff4 fs7 fc0 sc0 ls0 ws0">teger<span class="_ _e"> </span><span class="ff7">→<span class="_ _e"> </span><span class="ff24">$<span class="ff9">137<span class="_ _e"> </span>million</span></span></span></div><div class="t m0 x85 hb y267 ff1 fs7 fc0 sc0 ls0 ws0">P<span class="_ _5"></span>atriot<span class="_ _a"> </span>Missile:<span class="_ _43"> </span><span class="ff4">small<span class="_ _f"> </span>chopping<span class="_ _f"> </span>erro<span class="_ _5"></span>r</span></div><div class="t m0 x85 hb y268 ff4 fs7 fc0 sc0 ls0 ws0">at<span class="_ _e"> </span>each<span class="_ _e"> </span>op<span class="_ _c"></span>eration,<span class="_ _d"> </span>100<span class="_ _e"> </span>hours<span class="_ _e"> </span>activity</div><div class="t m0 x85 hb y269 ff7 fs7 fc0 sc0 ls0 ws0">→<span class="_ _e"> </span><span class="ff9">28<span class="_ _e"> </span>deaths</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">62/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf41" class="pf w0 h0" data-page-no="41"><div class="pc pc41 w0 h0"><img class="bi x0 y0 w1 h1" alt="" 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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Some<span class="_ _8"> </span>Examples...<span class="_ _69"> </span>2/4</div><div class="t m0 x1 hb y26a ff1 fs7 fc0 sc0 ls0 ws0">Integer<span class="_ _7"> </span>type<span class="_ _7"> </span>is<span class="_ _8"> </span>mo<span class="_ _5"></span>re<span class="_ _7"> </span>accurate<span class="_ _7"> </span>than<span class="_ _7"> </span>floating<span class="_ _8"> </span>t<span class="_ _5"></span>yp<span class="_ _c"></span>e<span class="_ _7"> </span>fo<span class="_ _5"></span>r<span class="_ _7"> </span>large<span class="_ _e"> </span>numb<span class="_ _c"></span>ers</div><div class="t m0 xe he y26b ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>16777217</span>;<span class="_ _6a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>16777217</span></div><div class="t m0 xe he y26c ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="ff5 fc7">int</span>)<span class="_ _a"> </span><span class="fc8">16777217.0f</span>;<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span><span class="fcc">16777216!!</span></span></div><div class="t m0 xe he y26d ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="ff5 fc7">int</span>)<span class="_ _a"> </span><span class="fc8">16777217.0</span>;<span class="_ _1"> </span><span class="ffe fc9">//<span class="_ _a"> </span>print<span class="_ _f"> </span>16777217,<span class="_ _f"> </span>double<span class="_ _f"> </span>ok</span></div><div class="t m0 x1 hb y26e ff5 fs7 fc0 sc0 ls0 ws0">float<span class="_ _7"> </span><span class="ff1">numb<span class="_ _c"></span>ers<span class="_ _7"> </span>are<span class="_ _e"> </span>different<span class="_ _7"> </span>from<span class="_ _8"> </span></span>double<span class="_ _7"> </span><span class="ff1">numb<span class="_ _c"></span>ers</span></div><div class="t m0 xe he y26f ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">1.1<span class="_ _a"> </span>!=<span class="_ _f"> </span>1.1f</span>);<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _a"> </span>true<span class="_ _f"> </span>!!!</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">63/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Some<span class="_ _8"> </span>Examples...<span class="_ _69"> </span>3/4</div><div class="t m0 x1 hb y270 ff1 fs7 fc0 sc0 ls0 ws0">The<span class="_ _7"> </span>floating<span class="_ _7"> </span>p<span class="_ _c"></span>oint<span class="_ _7"> </span>precision<span class="_ _e"> </span>is<span class="_ _8"> </span>finite!</div><div class="t m0 xe he y271 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>setprecision(<span class="fc8">20</span>);</div><div class="t m0 xe he y272 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>3.33333333f</span>;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span><span class="fcc">3.333333254!!</span></span></div><div class="t m0 xe he y273 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>3.33333333</span>;<span class="_ _23"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>3.333333333</span></div><div class="t m0 xe he y274 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">0.1<span class="_ _a"> </span>+<span class="_ _f"> </span>0.1<span class="_ _f"> </span>+<span class="_ _f"> </span>0.1<span class="_ _a"> </span>+<span class="_ _f"> </span>0.1<span class="_ _f"> </span>+<span class="_ _f"> </span>0.1<span class="_ _a"> </span>+<span class="_ _8"> </span>0.1</span>);<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>0.59999999999999998</span></div><div class="t m0 x1 hb y275 ff1 fs7 fc0 sc0 ls0 ws0">Floating<span class="_ _7"> </span>p<span class="_ _c"></span>oint<span class="_ _7"> </span>arithmetic<span class="_ _e"> </span>is<span class="_ _7"> </span>not<span class="_ _8"> </span>asso<span class="_ _c"></span>ciative</div><div class="t m0 xe he y276 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span>0.1<span class="_ _a"> </span>+<span class="_ _f"> </span></span>(<span class="fc8">0.2<span class="_ _f"> </span>+<span class="_ _f"> </span>0.3</span>)<span class="_ _a"> </span><span class="fc8">==<span class="_ _f"> </span></span>(<span class="fc8">0.1<span class="_ _f"> </span>+<span class="_ _f"> </span>0.2</span>)<span class="_ _a"> </span><span class="fc8">+<span class="_ _8"> </span>0.3</span>;<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>false</span></div><div class="t m0 x1 hb y277 ff4 fs7 fc0 sc0 ls0 ws0">IEEE754<span class="_ _e"> </span>Floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>computation<span class="_ _e"> </span>guarantees<span class="_ _d"> </span>to<span class="_ _e"> </span>produce<span class="_ _e"> </span><span class="ff1">deterministic<span class="_ _e"> </span></span>output,</div><div class="t m0 x1 hb y278 ff4 fs7 fc0 sc0 ls0 ws0">namely<span class="_ _d"> </span>the<span class="_ _e"> </span>exact<span class="_ _d"> </span>bitwise<span class="_ _12"> </span>value<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _d"> </span>each<span class="_ _e"> </span>run,<span class="_ _d"> </span>if<span class="_ _e"> </span>and<span class="_ _e"> </span>only<span class="_ _e"> </span>if<span class="_ _e"> </span>the<span class="_ _d"> </span><span class="ff1">o<span class="_ _5"></span>rder<span class="_ _e"> </span>of<span class="_ _7"> </span>the<span class="_ _7"> </span>op<span class="_ _c"></span>erations</span></div><div class="t m0 x1 hb y279 ff1 fs7 fc0 sc0 ls0 ws0">is<span class="_ _7"> </span>alwa<span class="_ _5"></span>ys<span class="_ _e"> </span>the<span class="_ _7"> </span>same</div><div class="t m0 x1 hb y27a ff7 fs7 fc0 sc0 ls0 ws0">→<span class="_ _e"> </span><span class="ff9">same<span class="_ _e"> </span>result<span class="_ _e"> </span>on<span class="_ _e"> </span>any<span class="_ _e"> </span>machine<span class="_ _e"> </span>and<span class="_ _e"> </span>fo<span class="_ _5"></span>r<span class="_ _e"> </span>all<span class="_ _e"> </span>runs</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">64/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Some<span class="_ _8"> </span>Examples...<span class="_ _69"> </span>4/4</div><div class="t m0 x1a hb y27b ff9 fs7 fc0 sc0 ls0 ws0">“Using<span class="_ _e"> </span>a<span class="_ _e"> </span>double-p<span class="_ _5"></span>recision<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _e"> </span>value,<span class="_ _e"> </span>w<span class="_ _5"></span>e<span class="_ _e"> </span>can<span class="_ _e"> </span>rep<span class="_ _5"></span>resent<span class="_ _e"> </span>easily<span class="_ _e"> </span>the</div><div class="t m0 xd hb y27c ff9 fs7 fc0 sc0 ls0 ws0">numb<span class="_ _c"></span>er<span class="_ _d"> </span>of<span class="_ _e"> </span>atoms<span class="_ _e"> </span>in<span class="_ _e"> </span>the<span class="_ _e"> </span>universe.</div><div class="t m0 x1a hb y27d ff9 fs7 fc0 sc0 ls0 ws0">If<span class="_ _8"> </span>your<span class="_ _8"> </span>soft<span class="_ _5"></span>w<span class="_ _5"></span>a<span class="_ _5"></span>re<span class="_ _8"> </span>ever<span class="_ _f"> </span>p<span class="_ _5"></span>ro<span class="_ _c"></span>duces<span class="_ _8"> </span>a<span class="_ _8"> </span>numb<span class="_ _c"></span>er<span class="_ _8"> </span>so<span class="_ _8"> </span>large<span class="_ _8"> </span>that<span class="_ _8"> </span>it<span class="_ _f"> </span>will<span class="_ _8"> </span>not<span class="_ _8"> </span>fit<span class="_ _f"> </span>in<span class="_ _8"> </span>a</div><div class="t m0 xd hb y27e ff9 fs7 fc0 sc0 ls0 ws0">double-p<span class="_ _5"></span>recision<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>value,<span class="_ _e"> </span>chances<span class="_ _e"> </span>are<span class="_ _d"> </span>go<span class="_ _c"></span>o<span class="_ _c"></span>d<span class="_ _e"> </span>that<span class="_ _e"> </span>y<span class="_ _5"></span>ou<span class="_ _e"> </span>have<span class="_ _e"> </span>a<span class="_ _e"> </span>bug”</div><div class="t m0 x86 hb y27f ff1e fs7 fc0 sc0 ls0 ws0">Daniel<span class="_ _7"> </span>Lemire<span class="ff9">,<span class="_ _e"> </span>Prof.<span class="_ _a"> </span>at<span class="_ _d"> </span>the<span class="_ _e"> </span>University<span class="_ _d"> </span>of<span class="_ _e"> </span>Queb<span class="_ _c"></span>ec</span></div><div class="t m0 x1a hb y280 ff9 fs7 fc0 sc0 ls0 ws0">“<span class="_ _e"> </span>NASA<span class="_ _e"> </span>uses<span class="_ _e"> </span>just<span class="_ _e"> </span>15<span class="_ _e"> </span>digits<span class="_ _e"> </span>of<span class="_ _e"> </span><span class="ff1a">π<span class="_ _7"> </span></span>to<span class="_ _e"> </span>calculate<span class="_ _e"> </span>interplanetary<span class="_ _d"> </span>travel.</div><div class="t m0 xd hb y281 ff9 fs7 fc0 sc0 ls0 ws0">With<span class="_ _12"> </span>40<span class="_ _12"> </span>digits,<span class="_ _d"> </span>you<span class="_ _12"> </span>could<span class="_ _12"> </span>calculate<span class="_ _12"> </span>the<span class="_ _d"> </span>circumference<span class="_ _12"> </span>of<span class="_ _d"> </span>a<span class="_ _12"> </span>circle<span class="_ _12"> </span>the<span class="_ _d"> </span>size<span class="_ _12"> </span>of<span class="_ _d"> </span>the</div><div class="t m0 xd hb y282 ff9 fs7 fc0 sc0 ls0 ws0">visible<span class="_ _7"> </span>universe<span class="_ _7"> </span>with<span class="_ _7"> </span>an<span class="_ _7"> </span>accuracy<span class="_ _7"> </span>that<span class="_ _7"> </span>w<span class="_ _5"></span>ould<span class="_ _7"> </span>fall<span class="_ _7"> </span>by<span class="_ _e"> </span>less<span class="_ _7"> </span>than<span class="_ _7"> </span>the<span class="_ _7"> </span>diameter<span class="_ _7"> </span>of</div><div class="t m0 xd hb y283 ff9 fs7 fc0 sc0 ls0 ws0">a<span class="_ _e"> </span>single<span class="_ _e"> </span>hydrogen<span class="_ _e"> </span>atom”</div><div class="t m0 x37 hb y284 ff1e fs7 fc0 sc0 ls0 ws0">Latest<span class="_ _7"> </span>in<span class="_ _7"> </span>space<span class="ff9">,<span class="_ _e"> </span>T<span class="_ _6"></span>witter</span></div><div class="t m0 xb he y285 ffc fs8 fc3 sc0 ls0 ws0">Number<span class="_ _f"> </span>of<span class="_ _f"> </span>atoms<span class="_ _a"> </span>in<span class="_ _f"> </span>the<span class="_ _f"> </span>universe<span class="_ _f"> </span>versus<span class="_ _a"> </span>floating-point<span class="_ _f"> </span>values</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">65/77</div><a class="l" href="https://lemire.me/blog/2020/03/15/number-of-atoms-in-the-universe-versus-floating-point-values/"><div class="d m1" style="border-style:none;position:absolute;left:34.722000px;bottom:6.801000px;width:284.433000px;height:13.444000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf44" class="pf w0 h0" data-page-no="44"><div class="pc pc44 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Algo<span class="_ _5"></span>rithms</div><div class="t m0 x1 hb y7f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff5">addition<span class="_ _7"> </span><span class="ff1">algorithm<span class="_ _d"> </span><span class="ff4">(simplified):</span></span></span></div><div class="t m0 x87 hd y286 ffb fs8 fc0 sc0 ls0 ws0">(1)<span class="_ _4"> </span>Compare<span class="_ _25"> </span>the<span class="_ _12"> </span>exp<span class="_ _c"></span>onents<span class="_ _12"> </span>of<span class="_ _12"> </span>the<span class="_ _12"> </span>tw<span class="_ _5"></span>o<span class="_ _12"> </span>numbers.<span class="_ _8"> </span>Shift<span class="_ _12"> </span>the<span class="_ _12"> </span>smaller<span class="_ _12"> </span>numb<span class="_ _c"></span>er<span class="_ _12"> </span>to<span class="_ _12"> </span>the<span class="_ _12"> </span>right<span class="_ _12"> </span>until<span class="_ _d"> </span>its</div><div class="t m0 x7 hd y287 ffb fs8 fc0 sc0 ls0 ws0">exp<span class="_ _c"></span>onent<span class="_ _25"> </span>would<span class="_ _12"> </span>match<span class="_ _12"> </span>the<span class="_ _12"> </span>larger<span class="_ _25"> </span>exp<span class="_ _c"></span>onent</div><div class="t m0 x87 hd y288 ffb fs8 fc0 sc0 ls0 ws0">(2)<span class="_ _4"> </span>Add<span class="_ _25"> </span>the<span class="_ _12"> </span>mantissa</div><div class="t m0 x87 hd y289 ffb fs8 fc0 sc0 ls0 ws0">(3)<span class="_ _4"> </span>Normalize<span class="_ _25"> </span>the<span class="_ _12"> </span>sum<span class="_ _12"> </span>if<span class="_ _12"> </span>needed<span class="_ _d"> </span>(shift<span class="_ _12"> </span>right/left<span class="_ _12"> </span>the<span class="_ _12"> </span>exp<span class="_ _c"></span>onent<span class="_ _12"> </span>b<span class="_ _5"></span>y<span class="_ _12"> </span>1)</div><div class="t m0 x1 hb y28a ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff5">multiplication<span class="_ _7"> </span><span class="ff1">algorithm<span class="_ _d"> </span><span class="ff4">(simplified):</span></span></span></div><div class="t m0 x87 hd y28b ffb fs8 fc0 sc0 ls0 ws0">(1)<span class="_ _4"> </span>Multiplication<span class="_ _12"> </span>of<span class="_ _12"> </span>mantissas.<span class="_ _8"> </span>The<span class="_ _12"> </span>numb<span class="_ _c"></span>er<span class="_ _25"> </span>of<span class="_ _12"> </span>bits<span class="_ _d"> </span>of<span class="_ _12"> </span>the<span class="_ _12"> </span>result<span class="_ _12"> </span>is<span class="_ _12"> </span>twice<span class="_ _25"> </span>the<span class="_ _d"> </span>size<span class="_ _12"> </span>of<span class="_ _12"> </span>the<span class="_ _12"> </span>op<span class="_ _c"></span>erands</div><div class="t m0 x7 hd y28c ffb fs8 fc0 sc0 ls0 ws0">(46<span class="_"> </span>+<span class="_ _14"> </span>2<span class="_ _12"> </span>bits,<span class="_ _12"> </span>with<span class="_ _12"> </span>+2<span class="_ _d"> </span>fo<span class="_ _5"></span>r<span class="_ _12"> </span>implicit<span class="_ _12"> </span>normalization)</div><div class="t m0 x87 hd y28d ffb fs8 fc0 sc0 ls0 ws0">(2)<span class="_ _4"> </span>Normalize<span class="_ _25"> </span>the<span class="_ _12"> </span>product<span class="_ _12"> </span>if<span class="_ _12"> </span>needed<span class="_ _d"> </span>(shift<span class="_ _12"> </span>right/left<span class="_ _12"> </span>the<span class="_ _12"> </span>exp<span class="_ _c"></span>onent<span class="_ _12"> </span>b<span class="_ _5"></span>y<span class="_ _12"> </span>1)</div><div class="t m0 x87 hd y28e ffb fs8 fc0 sc0 ls0 ws0">(3)<span class="_ _4"> </span>Addition<span class="_ _25"> </span>of<span class="_ _12"> </span>the<span class="_ _12"> </span>exp<span class="_ _c"></span>onents</div><div class="t m0 x1 hb y28f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _e"> </span><span class="ff5">fused<span class="_ _18"> </span>multiply-add<span class="_ _e"> </span><span class="ff4">(<span class="ffa">fma</span>):</span></span></div><div class="t m0 x26 hd y290 ff19 fs8 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffb">Recent<span class="_ _12"> </span>architectures<span class="_ _25"> </span>(also<span class="_ _12"> </span>GPUs)<span class="_ _12"> </span>provide<span class="_ _12"> </span><span class="ffc">fma<span class="_ _12"> </span></span>to<span class="_ _12"> </span>compute<span class="_ _12"> </span>addition<span class="_ _12"> </span>and<span class="_ _12"> </span>multiplication<span class="_ _d"> </span>in<span class="_ _12"> </span>a<span class="_ _12"> </span>single</span></div><div class="t m0 x7 hd y291 ffb fs8 fc0 sc0 ls0 ws0">instruction<span class="_ _12"> </span>(p<span class="_ _c"></span>erfo<span class="_ _5"></span>rmed<span class="_ _12"> </span>b<span class="_ _5"></span>y<span class="_ _12"> </span>the<span class="_ _12"> </span>compiler<span class="_ _12"> </span>in<span class="_ _12"> </span>most<span class="_ _d"> </span>cases)</div><div class="t m0 x26 hd y292 ff19 fs8 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffb">The<span class="_ _12"> </span>rounding<span class="_ _12"> </span>error<span class="_ _25"> </span>of<span class="_ _12"> </span><span class="ff12">fma<span class="_ _c"></span></span>(<span class="ff12">x<span class="_ _0"></span><span class="ff14">,<span class="_ _14"> </span></span>y<span class="_ _0"></span><span class="ff14">,<span class="_ _14"> </span></span>z<span class="_ _c"></span></span>)<span class="_ _12"> </span>is<span class="_ _d"> </span>less<span class="_ _12"> </span>than<span class="_ _12"> </span>(<span class="ff12">x<span class="_ _12"> </span><span class="ff13">⊗<span class="_ _13"> </span></span>y<span class="_ _0"></span></span>)<span class="_"> </span><span class="ff13">⊕<span class="_ _14"> </span><span class="ff12">z</span></span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">66/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _8"> </span>Cancellation<span class="_ _6b"> </span>1/5</div><div class="t m0 xe hb y293 ff1 fs7 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _7"> </span>Cancellation</div><div class="t m0 xe hb y294 ff1 fs7 fc0 sc0 ls0 ws0">Catastrophic<span class="_ _7"> </span>cancellation<span class="_ _e"> </span><span class="ff4">(or<span class="_ _d"> </span><span class="ff9">loss<span class="_ _e"> </span>of<span class="_ _e"> </span>significance<span class="_ _0"></span></span>)<span class="_ _e"> </span>refers<span class="_ _e"> </span>to<span class="_ _e"> </span>loss<span class="_ _e"> </span>of<span class="_ _e"> </span>relevant</span></div><div class="t m0 xe hb y295 ff4 fs7 fc0 sc0 ls0 ws0">info<span class="_ _5"></span>rmation<span class="_ _e"> </span>in<span class="_ _e"> </span>a<span class="_ _e"> </span>floating-p<span class="_ _c"></span>oint<span class="_ _d"> </span>computation<span class="_ _e"> </span>that<span class="_ _e"> </span>cannot<span class="_ _e"> </span>b<span class="_ _c"></span>e<span class="_ _e"> </span>revered</div><div class="t m0 x1 hb y296 ff4 fs7 fc0 sc0 ls0 ws0">T<span class="_ _6"></span>w<span class="_ _5"></span>o<span class="_ _e"> </span>cases:</div><div class="t m0 x82 hb y297 ff9 fs7 fc0 sc0 ls0 ws0">(C1)<span class="_ _18"> </span><span class="ff1">a<span class="_ _13"> </span><span class="ff7">±<span class="_ _25"> </span></span>b<span class="ff4">,<span class="_ _d"> </span>where<span class="_ _e"> </span></span>a<span class="_ _12"> </span><span class="ff7">≫<span class="_ _12"> </span></span>b<span class="_ _e"> </span><span class="ff4">or<span class="_ _d"> </span></span>b<span class="_ _12"> </span><span class="ff7">≫<span class="_ _12"> </span></span>a<span class="ff4">.<span class="_ _a"> </span>The<span class="_ _e"> </span>value<span class="_ _e"> </span>(o<span class="_ _5"></span>r<span class="_ _e"> </span>pa<span class="_ _5"></span>rt<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>value)<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>smaller</span></span></div><div class="t m0 x7 hb y298 ff4 fs7 fc0 sc0 ls0 ws0">numb<span class="_ _c"></span>er<span class="_ _d"> </span>is<span class="_ _e"> </span>lost</div><div class="t m0 x82 hb y299 ff9 fs7 fc0 sc0 ls0 ws0">(C2)<span class="_ _18"> </span><span class="ff1">a<span class="_ _13"> </span><span class="ff7">−<span class="_ _25"> </span></span>b<span class="ff4">,<span class="_ _d"> </span>where<span class="_ _e"> </span></span>a<span class="ff1a">,<span class="_ _14"> </span></span>b<span class="_ _e"> </span><span class="ff4">are<span class="_ _d"> </span>appro<span class="_ _5"></span>ximation<span class="_ _d"> </span>of<span class="_ _7"> </span>exact<span class="_ _e"> </span>values<span class="_ _e"> </span>and<span class="_ _e"> </span><span class="ff1">a<span class="_"> </span><span class="ff7">≈<span class="_ _12"> </span></span>b</span>,<span class="_ _e"> </span>namely<span class="_ _e"> </span>a<span class="_ _e"> </span>loss<span class="_ _e"> </span>of</span></span></div><div class="t m0 x7 hb y29a ff4 fs7 fc0 sc0 ls0 ws0">p<span class="_ _5"></span>recision<span class="_ _e"> </span>in<span class="_ _e"> </span>b<span class="_ _c"></span>oth<span class="_ _d"> </span><span class="ff1">a<span class="_ _e"> </span></span>and<span class="_ _e"> </span><span class="ff1">b</span>.<span class="_ _a"> </span><span class="ff1">a<span class="_ _13"> </span><span class="ff7">−<span class="_ _25"> </span></span>b<span class="_ _d"> </span></span>cancels<span class="_ _e"> </span>most<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>relevant<span class="_ _e"> </span>part<span class="_ _d"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>result</div><div class="t m0 x7 hb y29b ff4 fs7 fc0 sc0 ls0 ws0">b<span class="_ _c"></span>ecause<span class="_ _d"> </span><span class="ff1">a<span class="_ _12"> </span><span class="ff7">≈<span class="_ _12"> </span></span>b</span>.<span class="_ _a"> </span>It<span class="_ _e"> </span>implies<span class="_ _e"> </span>a<span class="_ _e"> </span><span class="ff9">small<span class="_ _e"> </span>absolute<span class="_ _e"> </span>erro<span class="_ _5"></span>r<span class="_ _f"> </span><span class="ff4">but<span class="_ _e"> </span>a<span class="_ _e"> </span></span>large<span class="_ _e"> </span>relative<span class="_ _e"> </span>erro<span class="_ _5"></span>r</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">67/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _8"> </span>Cancellation<span class="_ _f"> </span><span class="fs4">(case<span class="_ _e"> </span>1)<span class="_ _8"> </span></span>-<span class="_ _f"> </span>Granula<span class="_ _5"></span>rit<span class="_ _5"></span>y<span class="_ _6c"> </span>2/5</div><div class="t m0 x88 h6 y29c ff1 fs4 fcc sc0 ls0 ws0">Intersection<span class="_ _e"> </span><span class="ff4 fc0">=<span class="_ _25"> </span>16<span class="ff1a">,<span class="_ _14"> </span></span>777<span class="ff1a">,<span class="_ _14"> </span></span>216<span class="_"> </span>=<span class="_ _25"> </span>2</span></div><div class="t m0 x89 h12 y29d ff6 fs6 fc0 sc0 ls0 ws0">24</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">68/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _8"> </span>Cancellation<span class="_ _f"> </span><span class="fs4">(case<span class="_ _e"> </span>1)<span class="_ _6d"> </span></span>3/5</div><div class="t m0 x1 h5 y29e ff3 fs3 fc0 sc0 ls0 ws0">Ho<span class="_ _5"></span>w<span class="_ _7"> </span>many<span class="_ _7"> </span>iterations<span class="_ _7"> </span>p<span class="_ _c"></span>erfo<span class="_ _5"></span>rms<span class="_ _e"> </span>the<span class="_ _7"> </span>following<span class="_ _e"> </span>co<span class="_ _c"></span>de?</div><div class="t m0 xe h16 y29f ff5 fs7 fcb sc0 ls0 ws0">while<span class="_ _18"> </span><span class="ffa fc0">(x<span class="_ _18"> </span><span class="fc8">><span class="_ _18"> </span>0</span>)</span></div><div class="t m0 x1a h16 y2a0 ffa fs7 fc0 sc0 ls0 ws0">x<span class="_ _18"> </span><span class="fc8">=<span class="_ _18"> </span></span>x<span class="_ _18"> </span><span class="fc8">-<span class="_ _18"> </span></span>y;</div><div class="t m0 x1 hb y2a1 ff4 fs7 fc0 sc0 ls0 ws0">Ho<span class="_ _5"></span>w<span class="_ _e"> </span>many<span class="_ _e"> </span>iterations?</div><div class="t m0 xe he y2a2 ffc fs8 fc0 sc0 ls0 ws0">float:<span class="_ _27"> </span>x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>10</span>,<span class="fc8">000</span>,<span class="fc8">000<span class="_ _45"> </span></span>y<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>1<span class="_ _36"> </span>-><span class="_ _f"> </span>10</span>,<span class="fc8">000</span>,<span class="fc8">000</span></div><div class="t m0 xe he y2a3 ffc fs8 fc0 sc0 ls0 ws0">float:<span class="_ _27"> </span>x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>30</span>,<span class="fc8">000</span>,<span class="fc8">000<span class="_ _45"> </span></span>y<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>1<span class="_ _36"> </span>-><span class="_ _f"> </span></span>does<span class="_ _a"> </span><span class="ff5 fcb">not<span class="_ _f"> </span></span>terminate</div><div class="t m0 xe he y2a4 ffc fs8 fc0 sc0 ls0 ws0">float:<span class="_ _27"> </span>x<span class="_ _f"> </span><span class="fc8">=<span class="_ _33"> </span>200</span>,<span class="fc8">000<span class="_ _24"> </span></span>y<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>0.001<span class="_ _f"> </span>-><span class="_ _a"> </span></span>does<span class="_ _f"> </span><span class="ff5 fcb">not<span class="_ _f"> </span></span>terminate</div><div class="t m0 xe he y2a5 ffc fs8 fc0 sc0 ls0 ws0">bfloat:<span class="_ _f"> </span>x<span class="_ _f"> </span><span class="fc8">=<span class="_ _2f"> </span>256<span class="_ _24"> </span></span>y<span class="_ _f"> </span><span class="fc8">=<span class="_ _f"> </span>1<span class="_ _36"> </span>-><span class="_ _f"> </span></span>does<span class="_ _a"> </span><span class="ff5 fcb">not<span class="_ _f"> </span></span>terminate<span class="_ _f"> </span><span class="fc8">!!</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">69/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _8"> </span>Cancellation<span class="_ _f"> </span><span class="fs4">(case<span class="_ _e"> </span>1)<span class="_ _6d"> </span></span>4/5</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _7"> </span>increment</div><div class="t m0 xe he y2a6 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _f"> </span><span class="ffc fc0">x<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span>0.0f</span>;</span></div><div class="t m0 xe he y2a7 ff5 fs8 fcb sc0 ls0 ws0">for<span class="_ _f"> </span><span class="ffc fc0">(</span><span class="fc7">int<span class="_ _f"> </span><span class="ffc fc0">i<span class="_ _a"> </span><span class="fc8">=<span class="_ _f"> </span>0</span>;<span class="_ _f"> </span>i<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span>20000000</span>;<span class="_ _f"> </span>i<span class="fc8">++</span>)</span></span></div><div class="t m0 xe he y2a8 ffc fs8 fc0 sc0 ls0 ws0">x<span class="_ _f"> </span><span class="fc8">+=<span class="_ _f"> </span>1.0f</span>;</div><div class="t m0 x1 hb y2a9 ff4 fs7 fc0 sc0 ls0 ws0">What<span class="_ _e"> </span>is<span class="_ _e"> </span>the<span class="_ _e"> </span>value<span class="_ _e"> </span>of<span class="_ _21"> </span><span class="ff5">x<span class="_ _21"> </span></span>at<span class="_ _e"> </span>the<span class="_ _e"> </span>end<span class="_ _e"> </span>of<span class="_ _e"> </span>the<span class="_ _e"> </span>lo<span class="_ _c"></span>op?</div><div class="t m0 x1 hb y2aa ff1 fs7 fc0 sc0 ls0 ws0">Ceiling<span class="_ _7"> </span>division</div><div class="t m0 xa h17 y2ab ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 x4e hb y2ac ff9 fs7 fc0 sc0 ls0 ws0">a</div><div class="t m0 x5d hb y2ad ff9 fs7 fc0 sc0 ls0 ws0">b</div><div class="t m0 x8a h17 y2ab ff1b fs4 fc0 sc0 ls0 ws0"></div><div class="t m0 xe hc y2ae ffe fs4 fc9 sc0 ls0 ws0">//<span class="_ _6e"> </span>std::ceil((float)<span class="_ _a"> </span>101<span class="_ _4"> </span>/<span class="_ _a"> </span>2.0f)<span class="_ _a"> </span>-><span class="_ _4"> </span>50.5f<span class="_ _a"> </span>-><span class="_ _4"> </span>51</div><div class="t m0 xe hc y2af ff5 fs4 fc7 sc0 ls0 ws0">float<span class="_ _a"> </span><span class="ffa fc0">x<span class="_ _4"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>ceil((</span>float<span class="ffa fc0">)<span class="_ _a"> </span><span class="fc8">20000001<span class="_ _4"> </span>/<span class="_ _a"> </span>2.0f</span>);</span></div><div class="t m0 x1 hb y2b0 ff4 fs7 fc0 sc0 ls0 ws0">What<span class="_ _e"> </span>is<span class="_ _e"> </span>the<span class="_ _e"> </span>value<span class="_ _e"> </span>of<span class="_ _21"> </span><span class="ff5">x<span class="_ _12"> </span></span>?</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">70/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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<div id="pf49" class="pf w0 h0" data-page-no="49"><div class="pc pc49 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Catastrophic<span class="_ _8"> </span>Cancellation<span class="_ _f"> </span><span class="fs4">(case<span class="_ _e"> </span>2)<span class="_ _6d"> </span></span>5/5</div><div class="t m0 x1 hb y7f ff4 fs7 fc0 sc0 ls0 ws0">Let’s<span class="_ _e"> </span>solve<span class="_ _e"> </span>a<span class="_ _e"> </span>quadratic<span class="_ _e"> </span>equation:</div><div class="t m0 x17 hb y2b1 ff9 fs7 fc0 sc0 ls0 ws0">x</div><div class="t m0 x66 h9 y2b2 ff6 fs5 fc0 sc0 ls0 ws0">1<span class="ff25">,</span>2</div><div class="t m0 x86 hb y2b1 ff4 fs7 fc0 sc0 ls0 ws0">=</div><div class="t m0 x8b hb y2b3 ff7 fs7 fc0 sc0 ls0 ws0">−<span class="ff9">b<span class="_ _25"> </span></span>±</div><div class="t m0 x8c hb y2b4 ff7 fs7 fc0 sc0 ls0 ws0">√</div><div class="t m0 x7e hb y2b3 ff9 fs7 fc0 sc0 ls0 ws0">b</div><div class="t m0 x53 h9 y2b5 ff6 fs5 fc0 sc0 ls0 ws0">2</div><div class="t m0 x8d hb y2b3 ff7 fs7 fc0 sc0 ls0 ws0">−<span class="_ _13"> </span><span class="ff4">4<span class="ff9">ac</span></span></div><div class="t m0 x2b hb y2b6 ff4 fs7 fc0 sc0 ls0 ws0">2<span class="ff9">a</span></div><div class="t m0 x1 hb y2b7 ff9 fs7 fc0 sc0 ls0 ws0">x</div><div class="t m0 x6 h9 y2b8 ff6 fs5 fc0 sc0 ls0 ws0">2</div><div class="t m0 x65 hb y2b7 ff4 fs7 fc0 sc0 ls0 ws0">+<span class="_"> </span>5000<span class="ff9">x<span class="_ _d"> </span></span>+<span class="_"> </span>0<span class="ff1a">.</span>25</div><div class="t m0 xe he y2b9 ffc fs8 fc0 sc0 ls0 ws0">(<span class="fc8">-5000<span class="_ _f"> </span>+<span class="_ _f"> </span></span>std<span class="fc8">::</span>sqrt(<span class="fc8">5000.0f<span class="_ _a"> </span>*<span class="_ _f"> </span>5000.0f<span class="_ _f"> </span>-<span class="_ _f"> </span>4.0f<span class="_ _a"> </span>*<span class="_ _f"> </span>1.0f<span class="_ _f"> </span>*<span class="_ _f"> </span>0.25f</span>))<span class="_ _a"> </span><span class="fc8">/<span class="_ _8"> </span>2<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ff21">x2</span></span></span></div><div class="t m0 xe he y2ba ffc fs8 fc0 sc0 ls0 ws0">(<span class="fc8">-5000<span class="_ _f"> </span>+<span class="_ _f"> </span></span>std<span class="fc8">::</span>sqrt(<span class="fc8">25000000.0f<span class="_ _a"> </span>-<span class="_ _f"> </span>1.0f</span>))<span class="_ _f"> </span><span class="fc8">/<span class="_ _f"> </span>2<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>catastrophic<span class="_ _f"> </span>cancellation<span class="_ _f"> </span>(C1)</span></span></div><div class="t m0 xe he y2bb ffc fs8 fc0 sc0 ls0 ws0">(<span class="fc8">-5000<span class="_ _f"> </span>+<span class="_ _f"> </span></span>std<span class="fc8">::</span>sqrt(<span class="fc8">25000000.0f</span>))<span class="_ _a"> </span><span class="fc8">/<span class="_ _f"> </span>2</span></div><div class="t m0 xe he y2bc ffc fs8 fc0 sc0 ls0 ws0">(<span class="fc8">-5000<span class="_ _f"> </span>+<span class="_ _f"> </span>5000</span>)<span class="_ _a"> </span><span class="fc8">/<span class="_ _f"> </span>2<span class="_ _f"> </span>=<span class="_ _f"> </span>0<span class="_ _6f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>catastrophic<span class="_ _f"> </span>cancellation<span class="_ _a"> </span>(C2)</span></span></div><div class="t m0 xe he y2bd ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>correct<span class="_ _f"> </span>result:<span class="_ _a"> </span>0.00005!!</div><div class="t m0 x1 hb y2be ff9 fs7 fc0 sc0 ls0 ws0">relative<span class="_ _e"> </span>erro<span class="_ _5"></span>r<span class="_ _51"></span><span class="ff4">:</span></div><div class="t m0 x3 hb y2bf ff7 fs7 fc0 sc0 ls0 ws0">|<span class="ff4">0<span class="_"> </span></span>−<span class="_ _13"></span><span class="ff4">0<span class="ff1a">.</span>00005</span>|</div><div class="t m0 x8e hb y2c0 ff4 fs7 fc0 sc0 ls0 ws0">0<span class="ff1a">.</span>00005</div><div class="t m0 x60 hb y2be ff4 fs7 fc0 sc0 ls0 ws0">=<span class="_ _e"> </span><span class="fcc">100%</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">71/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Compa<span class="_ _5"></span>rison<span class="_ _70"> </span>1/3</div><div class="t m0 x1 hb y2c1 ff1 fs7 fc0 sc0 ls0 ws0">The<span class="_ _7"> </span>problem</div><div class="t m0 xe he y2c2 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">0.11f<span class="_ _a"> </span>+<span class="_ _f"> </span>0.11f<span class="_ _f"> </span><<span class="_ _f"> </span>0.22f</span>);<span class="_ _a"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _f"> </span>true!!</span></div><div class="t m0 xe he y2c3 ffc fs8 fc0 sc0 ls0 ws0">cout<span class="_ _f"> </span><span class="fc8"><<<span class="_ _f"> </span></span>(<span class="fc8">0.1f<span class="_ _a"> </span>+<span class="_ _f"> </span>0.1f<span class="_ _f"> </span>><span class="_ _f"> </span>0.2f</span>);<span class="_ _33"> </span><span class="ffe fc9">//<span class="_ _f"> </span>print<span class="_ _a"> </span>true!!</span></div><div class="t m0 x1 hb y2c4 ff4 fs7 fc0 sc0 ls0 ws0">Do<span class="_ _e"> </span>not<span class="_ _e"> </span>use<span class="_ _e"> </span>absolute<span class="_ _e"> </span>erro<span class="_ _5"></span>r<span class="_ _e"> </span>ma<span class="_ _5"></span>rgins!!</div><div class="t m0 xe he y2c5 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc4">areFloatNearlyEqual<span class="fc0">(</span></span>float<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>float<span class="_ _f"> </span><span class="ffc fc0">b)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he y2c6 ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(std<span class="fc8">::</span>abs(a<span class="_ _f"> </span><span class="fc8">-<span class="_ _a"> </span></span>b)<span class="_ _f"> </span><span class="fc8"><<span class="_ _f"> </span></span>epsilon);<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _a"> </span>epsilon<span class="_ _f"> </span>is<span class="_ _f"> </span>fixed<span class="_ _f"> </span>by<span class="_ _a"> </span>the<span class="_ _8"> </span>user</span></span></div><div class="t m0 x2c he y2c7 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">true<span class="fc0">;</span></span></div><div class="t m0 x7 he y2c8 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">false<span class="fc0">;</span></span></div><div class="t m0 xe he y2c9 ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x1 h6 y2ca ff4 fs4 fc0 sc0 ls0 ws0">Problems:</div><div class="t m0 x26 h6 ya9 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Fixed<span class="_ _d"> </span><span class="ffa">epsilon<span class="_ _d"> </span></span>“lo<span class="_ _c"></span>oks<span class="_ _12"> </span>small”<span class="_ _d"> </span>but<span class="_ _d"> </span>it<span class="_ _d"> </span>could<span class="_ _d"> </span>b<span class="_ _c"></span>e<span class="_ _d"> </span>to<span class="_ _c"></span>o<span class="_ _12"> </span>large<span class="_ _12"> </span>when<span class="_ _d"> </span>the<span class="_ _d"> </span>numb<span class="_ _c"></span>ers<span class="_ _d"> </span>b<span class="_ _c"></span>eing<span class="_ _12"> </span>compared</span></div><div class="t m0 x7 h6 y2cb ff4 fs4 fc0 sc0 ls0 ws0">a<span class="_ _5"></span>re<span class="_ _d"> </span>very<span class="_ _d"> </span>small</div><div class="t m0 x26 h6 y2cc ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">If<span class="_ _d"> </span>the<span class="_ _12"> </span>compared<span class="_ _12"> </span>numb<span class="_ _c"></span>ers<span class="_ _12"> </span>are<span class="_ _12"> </span>very<span class="_ _d"> </span>large,<span class="_ _12"> </span>the<span class="_ _12"> </span><span class="ffa">epsilon<span class="_ _d"> </span></span>could<span class="_ _d"> </span>end<span class="_ _d"> </span>up<span class="_ _12"> </span>b<span class="_ _c"></span>eing<span class="_ _d"> </span>smaller<span class="_ _12"> </span>than<span class="_ _d"> </span>the</span></div><div class="t m0 x7 h6 y2cd ff4 fs4 fc0 sc0 ls0 ws0">smallest<span class="_ _d"> </span>rounding<span class="_ _d"> </span>erro<span class="_ _5"></span>r,<span class="_ _d"> </span>so<span class="_ _d"> </span>that<span class="_ _d"> </span>the<span class="_ _d"> </span>comparison<span class="_ _12"> </span>alwa<span class="_ _5"></span>ys<span class="_ _12"> </span>returns<span class="_ _d"> </span><span class="ffa">false</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">72/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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src="data:image/png;base64,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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Compa<span class="_ _5"></span>rison<span class="_ _70"> </span>2/3</div><div class="t m0 x1 hb y7f ff1 fs7 fc0 sc0 ls0 ws0">Solution:<span class="_ _a"> </span><span class="ff4">Use<span class="_ _d"> </span>relative<span class="_ _e"> </span>error</span></div><div class="t m0 x17 h9 y2ce ff1d fs5 fc0 sc0 ls0 ws0">|<span class="ff10">a</span>−<span class="ff10">b<span class="_ _c"></span></span>|</div><div class="t m0 x66 h10 y2cf ff10 fs5 fc0 sc0 ls0 ws0">b</div><div class="t m0 x1c hb y7f ff1a fs7 fc0 sc0 ls0 ws0"><<span class="_ _12"> </span>ε</div><div class="t m0 xe he yb7 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc4">areFloatNearlyEqual<span class="fc0">(</span></span>float<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>float<span class="_ _f"> </span><span class="ffc fc0">b)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he yb8 ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(std<span class="fc8">::</span>abs(a<span class="_ _f"> </span><span class="fc8">-<span class="_ _a"> </span></span>b)<span class="_ _f"> </span><span class="fc8">/<span class="_ _f"> </span></span>b<span class="_ _f"> </span><span class="fc8"><<span class="_ _a"> </span></span>epsilon);<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>epsilon<span class="_ _f"> </span>is<span class="_ _a"> </span>fixed</span></span></div><div class="t m0 x2c he yb9 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">true<span class="fc0">;</span></span></div><div class="t m0 x7 he yba ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">false<span class="fc0">;</span></span></div><div class="t m0 xe he ybb ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x1 h6 y2d0 ff4 fs4 fc0 sc0 ls0 ws0">Problems:</div><div class="t m0 x26 h6 y2d1 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff5">a=0,<span class="_ _a"> </span>b=0<span class="_ _8"> </span><span class="ff4">The<span class="_ _8"> </span>division<span class="_ _7"> </span>is<span class="_ _8"> </span>evaluated<span class="_ _8"> </span>as<span class="_ _8"> </span><span class="ffa">0.0/0.0<span class="_ _7"> </span></span>and<span class="_ _8"> </span>the<span class="_ _8"> </span>whole<span class="_ _8"> </span><span class="ffa">if<span class="_ _7"> </span></span>statement<span class="_ _8"> </span>is<span class="_ _8"> </span><span class="ffa">(nan<span class="_ _a"> </span><</span></span></span></div><div class="t m0 x7 h6 y2d2 ffa fs4 fc0 sc0 ls0 ws0">espilon)<span class="_ _d"> </span><span class="ff4">which<span class="_ _d"> </span>alw<span class="_ _5"></span>ays<span class="_ _12"> </span>returns<span class="_ _d"> </span><span class="ffa">false</span></span></div><div class="t m0 x26 h6 y2d3 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff5">b=0<span class="_ _f"> </span><span class="ff4">The<span class="_ _f"> </span>division<span class="_ _8"> </span>is<span class="_ _f"> </span>evaluated<span class="_ _f"> </span>as<span class="_ _f"> </span><span class="ffa">abs(a)/0.0<span class="_ _f"> </span></span>and<span class="_ _f"> </span>the<span class="_ _f"> </span>whole<span class="_ _f"> </span><span class="ffa">if<span class="_ _8"> </span></span>statement<span class="_ _f"> </span>is<span class="_ _f"> </span><span class="ffa">(+inf<span class="_ _4"> </span><</span></span></span></div><div class="t m0 x7 h6 y2d4 ffa fs4 fc0 sc0 ls0 ws0">espilon)<span class="_ _d"> </span><span class="ff4">which<span class="_ _d"> </span>alw<span class="_ _5"></span>ays<span class="_ _12"> </span>returns<span class="_ _d"> </span><span class="ffa">false</span></span></div><div class="t m0 x26 h6 y2d5 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff5">a<span class="_ _a"> </span>and<span class="_ _4"> </span>b<span class="_ _a"> </span>very<span class="_ _4"> </span>small.<span class="_ _43"> </span><span class="ff4">The<span class="_ _7"> </span>result<span class="_ _8"> </span>should<span class="_ _8"> </span>b<span class="_ _c"></span>e<span class="_ _7"> </span><span class="ffa">true<span class="_ _8"> </span></span>but<span class="_ _8"> </span>the<span class="_ _8"> </span>division<span class="_ _7"> </span>by<span class="_ _8"> </span><span class="ffa">b<span class="_ _8"> </span></span>ma<span class="_ _5"></span>y<span class="_ _8"> </span>p<span class="_ _5"></span>ro<span class="_ _c"></span>duces</span></span></div><div class="t m0 x7 h6 y2d6 ff4 fs4 fc0 sc0 ls0 ws0">wrong<span class="_ _d"> </span>results</div><div class="t m0 x26 h6 y2d7 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff5">It<span class="_ _a"> </span>is<span class="_ _4"> </span>not<span class="_ _a"> </span>commutative.<span class="_ _f"> </span><span class="ff4">W<span class="_ _5"></span>e<span class="_ _d"> </span>alw<span class="_ _5"></span>ays<span class="_ _12"> </span>divide<span class="_ _d"> </span>by<span class="_ _12"> </span><span class="ffa">b</span></span></span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">73/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _8"> </span>Compa<span class="_ _5"></span>rison<span class="_ _70"> </span>3/3</div><div class="t m0 x1 hb y7f ff4 fs7 fc0 sc0 ls0 ws0">P<span class="_ _5"></span>ossible<span class="_ _e"> </span>solution:</div><div class="t m0 x8f h9 y2ce ff1d fs5 fc0 sc0 ls0 ws0">|<span class="ff10">a</span>−<span class="ff10">b<span class="_ _c"></span></span>|</div><div class="t m0 x5a h9 y2d8 ff6 fs5 fc0 sc0 ls0 ws0">max(<span class="ff1d">|<span class="ff10">a<span class="_ _c"></span></span>|<span class="ff25">,</span>|<span class="ff10">b<span class="_ _c"></span></span>|</span>)</div><div class="t m0 x90 hb y7f ff1a fs7 fc0 sc0 ls0 ws0"><<span class="_ _12"> </span>ε</div><div class="t m0 xe he yb7 ff5 fs8 fc7 sc0 ls0 ws0">bool<span class="_ _f"> </span><span class="ffc fc4">areFloatNearlyEqual<span class="fc0">(</span></span>float<span class="_ _f"> </span><span class="ffc fc0">a,<span class="_ _a"> </span></span>float<span class="_ _f"> </span><span class="ffc fc0">b)<span class="_ _f"> </span>{</span></div><div class="t m0 x7 he yb8 ff5 fs8 fcb sc0 ls0 ws0">constexpr<span class="_ _f"> </span><span class="fc7">float<span class="_ _f"> </span><span class="ffc fc0">normal_min<span class="_ _36"> </span><span class="fc8">=<span class="_ _f"> </span></span>std<span class="fc8">::</span>numeric_limits<span class="fc8"><</span></span>float<span class="ffc fc8">>::<span class="fc0">min();</span></span></span></div><div class="t m0 x7 he yb9 ff5 fs8 fcb sc0 ls0 ws0">constexpr<span class="_ _f"> </span><span class="fc7">float<span class="_ _f"> </span><span class="ffc fc0">relative_error<span class="_ _a"> </span><span class="fc8">=<span class="_ _f"> </span><</span>user_defined<span class="fc8">></span></span></span></div><div class="t m0 x7 hd ybb ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(<span class="fc8">!</span>std<span class="fc8">::</span>isfinite(a)<span class="_ _f"> </span><span class="fc8">||<span class="_ _a"> </span>!</span>isfinite(b))<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span><span class="ff12">a<span class="_ _25"> </span><span class="ffb">=<span class="_ _25"> </span><span class="ff13">±∞<span class="ff14">,<span class="_ _41"> </span></span></span></span>NaN<span class="_ _4"> </span></span>or<span class="_ _a"> </span><span class="ff12">b<span class="_ _25"> </span><span class="ffb">=<span class="_ _25"> </span><span class="ff13">±∞<span class="ff14">,<span class="_ _41"> </span></span></span></span>NaN</span></span></span></div><div class="t m0 x2c he ybc ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">false<span class="fc0">;</span></span></div><div class="t m0 x7 he ybd ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _f"> </span><span class="ffc fc0">diff<span class="_ _27"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>abs(a<span class="_ _8"> </span><span class="fc8">-<span class="_ _a"> </span></span>b);</span></div><div class="t m0 x7 he y2d9 ffe fs8 fc9 sc0 ls0 ws0">//<span class="_ _f"> </span>if<span class="_ _f"> </span>"a"<span class="_ _a"> </span>and<span class="_ _f"> </span>"b"<span class="_ _f"> </span>are<span class="_ _f"> </span>near<span class="_ _a"> </span>to<span class="_ _f"> </span>zero,<span class="_ _f"> </span>the<span class="_ _f"> </span>relative<span class="_ _a"> </span>error<span class="_ _8"> </span>is<span class="_ _a"> </span>less<span class="_ _f"> </span>effective</div><div class="t m0 x7 he ybf ff5 fs8 fcb sc0 ls0 ws0">if<span class="_ _f"> </span><span class="ffc fc0">(diff<span class="_ _f"> </span><span class="fc8"><=<span class="_ _a"> </span></span>normal_min)<span class="_ _f"> </span><span class="ffe fc9">//<span class="_ _f"> </span>or<span class="_ _f"> </span>also:<span class="_ _a"> </span>user_epsilon<span class="_ _f"> </span>*<span class="_ _27"> </span>normal_min</span></span></div><div class="t m0 x2c he yc0 ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc">true<span class="fc0">;</span></span></div><div class="t m0 x7 he yc2 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _f"> </span><span class="ffc fc0">abs_a<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>abs(a);</span></div><div class="t m0 x7 he yc3 ff5 fs8 fc7 sc0 ls0 ws0">float<span class="_ _f"> </span><span class="ffc fc0">abs_b<span class="_ _f"> </span><span class="fc8">=<span class="_ _a"> </span></span>std<span class="fc8">::</span>abs(b);</span></div><div class="t m0 x7 he y2da ff5 fs8 fcb sc0 ls0 ws0">return<span class="_ _f"> </span><span class="ffc fc0">(diff<span class="_ _f"> </span><span class="fc8">/<span class="_ _a"> </span></span>std<span class="fc8">::</span>max(abs_a,<span class="_ _f"> </span>abs_b))<span class="_ _f"> </span><span class="fc8"><=<span class="_ _f"> </span></span>relative_error;</span></div><div class="t m0 xe he y2db ffc fs8 fc0 sc0 ls0 ws0">}</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">74/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">Minimize<span class="_ _8"> </span>Error<span class="_ _8"> </span>Propagation<span class="_ _8"> </span>-<span class="_ _8"> </span>Summary</div><div class="t m0 xb hb y5f ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Prefer<span class="_ _e"> </span><span class="ff1">multiplication/division<span class="_ _e"> </span></span>rather<span class="_ _e"> </span>than<span class="_ _e"> </span>addition/subtraction</span></div><div class="t m0 xb hb y2dc ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">T<span class="_ _6"></span>ry<span class="_ _e"> </span>to<span class="_ _e"> </span>reorganize<span class="_ _d"> </span>the<span class="_ _e"> </span>computation<span class="_ _e"> </span>to<span class="_ _e"> </span><span class="ff1">keep<span class="_ _e"> </span>near<span class="_ _d"> </span></span>numb<span class="_ _c"></span>ers<span class="_ _e"> </span>with<span class="_ _e"> </span>the<span class="_ _e"> </span>same<span class="_ _e"> </span>scale</span></div><div class="t m0 x7 hb y2dd ff4 fs7 fc0 sc0 ls0 ws0">(e.g.<span class="_ _a"> </span>so<span class="_ _5"></span>rting<span class="_ _d"> </span>numb<span class="_ _c"></span>ers)</div><div class="t m0 xb hb y2de ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Consider<span class="_ _e"> </span><span class="ff1">putting<span class="_ _8"> </span>a<span class="_ _7"> </span>zero<span class="_ _e"> </span></span>very<span class="_ _e"> </span>small<span class="_ _e"> </span>numb<span class="_ _c"></span>er<span class="_ _d"> </span>(under<span class="_ _e"> </span>a<span class="_ _e"> </span>threshold).<span class="_ _a"> </span>Common</span></div><div class="t m0 x7 hb y2df ff4 fs7 fc0 sc0 ls0 ws0">application:<span class="_ _a"> </span>iterative<span class="_ _d"> </span>algorithms</div><div class="t m0 xb hb y2e0 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Scale<span class="_ _e"> </span>b<span class="_ _5"></span>y<span class="_ _e"> </span>a<span class="_ _e"> </span><span class="ff1">p<span class="_ _c"></span>o<span class="_ _5"></span>w<span class="_ _5"></span>er<span class="_ _7"> </span>of<span class="_ _7"> </span>tw<span class="_ _5"></span>o<span class="_ _d"> </span><span class="ff4">is<span class="_ _e"> </span>safe</span></span></span></div><div class="t m0 xb hb y14c ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff1">Switch<span class="_ _7"> </span>to<span class="_ _7"> </span>log<span class="_ _8"> </span>scale<span class="ff4">.<span class="_ _f"> </span>Multiplication<span class="_ _7"> </span>b<span class="_ _c"></span>ecomes<span class="_ _d"> </span>Add,<span class="_ _d"> </span>and<span class="_ _e"> </span>Division<span class="_ _e"> </span>b<span class="_ _c"></span>ecomes</span></span></div><div class="t m0 x7 hb y2e1 ff4 fs7 fc0 sc0 ls0 ws0">Subtraction</div><div class="t m0 xb hb y2e2 ffd fs7 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ff4">Use<span class="_ _e"> </span>a<span class="_ _e"> </span><span class="ff1">comp<span class="_ _c"></span>ensation<span class="_ _7"> </span>algo<span class="_ _5"></span>rithm<span class="_ _e"> </span><span class="ff4">lik<span class="_ _5"></span>e<span class="_ _e"> </span>Kahan<span class="_ _e"> </span>summation,<span class="_ _e"> </span>Dekker’s<span class="_ _d"> </span>FastT<span class="_ _b"></span>woSum,</span></span></span></div><div class="t m0 x7 hb y2e3 ff4 fs7 fc0 sc0 ls0 ws0">R<span class="_ _5"></span>ump’s<span class="_ _e"> </span>A<span class="_ _5"></span>ccSum</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">75/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">References</div><div class="t m0 x1 hb y2e4 ff1 fs7 fc0 sc0 ls0 ws0">Suggest<span class="_ _7"> </span>readings<span class="ff4">:</span></div><div class="t m0 x26 h6 y2e5 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">What<span class="_ _a"> </span>Every<span class="_ _4"> </span>Computer<span class="_ _a"> </span>Scientist<span class="_ _4"> </span>Should<span class="_ _a"> </span>Know<span class="_ _a"> </span>About<span class="_ _4"> </span>Floating-Point<span class="_ _a"> </span>Arithmetic</span></div><div class="t m0 x26 h6 y2e6 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Do<span class="_ _a"> </span>Developers<span class="_ _4"> </span>Understand<span class="_ _a"> </span>IEEE<span class="_ _4"> </span>Floating<span class="_ _a"> </span>Point?</span></div><div class="t m0 x26 h6 y2e7 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Yet<span class="_ _a"> </span>another<span class="_ _4"> </span>floating<span class="_ _a"> </span>point<span class="_ _4"> </span>tutorial</span></div><div class="t m0 x26 h6 y2e8 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Unavoidable<span class="_ _a"> </span>Errors<span class="_ _4"> </span>in<span class="_ _a"> </span>Computing</span></div><div class="t m0 x1 hb y2e9 ff1 fs7 fc0 sc0 ls0 ws0">Floating-p<span class="_ _c"></span>oint<span class="_ _7"> </span>Compa<span class="_ _5"></span>rison<span class="_ _7"> </span>readings<span class="ff4">:</span></div><div class="t m0 x26 h6 y2ea ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">The<span class="_ _a"> </span>Floating-Point<span class="_ _4"> </span>Guide<span class="_ _a"> </span>-<span class="_ _4"> </span>Comparison</span></div><div class="t m0 x26 h6 y2eb ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Comparing<span class="_ _a"> </span>Floating<span class="_ _4"> </span>Point<span class="_ _a"> </span>Numbers,<span class="_ _4"> </span>2012<span class="_ _a"> </span>Edition</span></div><div class="t m0 x26 h6 y2ec ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Some<span class="_ _a"> </span>comments<span class="_ _4"> </span>on<span class="_ _a"> </span>approximately<span class="_ _4"> </span>equal<span class="_ _a"> </span>FP<span class="_ _a"> </span>comparisons</span></div><div class="t m0 x26 h6 y2ed ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Comparing<span class="_ _a"> </span>Floating-Point<span class="_ _4"> </span>Numbers<span class="_ _a"> </span>Is<span class="_ _4"> </span>Tricky</span></div><div class="t m0 x1 hb y2ee ff1 fs7 fc0 sc0 ls0 ws0">Floating<span class="_ _7"> </span>p<span class="_ _c"></span>oint<span class="_ _7"> </span>to<span class="_ _c"></span>ols<span class="ff4">:</span></div><div class="t m0 x26 h6 y2ef ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">IEEE754<span class="_ _a"> </span>visualization/converter</span></div><div class="t m0 x26 h6 y2f0 ffd fs4 fc0 sc0 ls0 ws0">•<span class="_ _4"> </span><span class="ffa">Find<span class="_ _a"> </span>and<span class="_ _4"> </span>fix<span class="_ _a"> </span>floating-point<span class="_ _4"> </span>problems</span></div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">76/77</div><a class="l" href="docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:192.243000px;width:383.810000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://pdinda.org/Papers/ipdps18.pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:176.502000px;width:237.360000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://wordsandbuttons.online/yet_another_floating_point_tutorial.html"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:160.762000px;width:185.056000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.physics.udel.edu/~bnikolic/teaching/phys660/PDF/unavoidable_errors.pdf"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:145.021000px;width:164.134000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://floating-point-gui.de/errors/comparison"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:107.721000px;width:195.517000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:91.980000px;width:242.590000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://marc-b-reynolds.github.io/math/2019/05/14/FloatCmp.html"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:76.239000px;width:273.972000px;height:10.174000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://bitbashing.io/comparing-floats.html"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:60.498000px;width:221.669000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.h-schmidt.net/FloatConverter/IEEE754.html"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:24.585000px;width:164.134000px;height:9.738000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://herbie.uwplse.org/"><div class="d m1" style="border-style:none;position:absolute;left:49.168000px;bottom:7.457000px;width:190.286000px;height:10.175000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x5 h7 y7 ff1 fs3 fc1 sc0 ls0 ws0">On<span class="_ _8"> </span>Floating-Point</div><div class="t m0 x10 h9 ye ff6 fs5 fc0 sc0 ls0 ws0">77/77</div></div><div class="pi" data-data='{"ctm":[1.000000,0.000000,0.000000,1.000000,0.000000,0.000000]}'></div></div>
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