daviddoji/18065
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

link 0.30000000000000004 example

Browse Source
This commit is contained in:
Steven G. Johnson 2023-05-15 14:10:06 -04:00
parent 8d14eb5120
commit 245bc6befd
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@ -404,4 +404,4 @@ In **floating-point** arithmetic, we store both an integer coefficient and an ex
Went through some simple definitions and examples in Julia (see notebook above), illustrating the basic ideas and a few interesting tidbits. In particular, we looked at **error accumulation** during long calculations (e.g. summation), as well as examples of [catastrophic cancellation](https://en.wikipedia.org/wiki/Loss_of_significance) and how it can sometimes be avoided by rearranging a calculation.
**Further reading:** [Trefethen & Bau's *Numerical Linear Algebra*](https://people.maths.ox.ac.uk/trefethen/text.html), lecture 13. [What Every Computer Scientist Should Know About Floating Point Arithmetic](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.22.6768) (David Goldberg, ACM 1991). William Kahan, [How Java's floating-point hurts everyone everywhere](http://www.cs.berkeley.edu/~wkahan/JAVAhurt.pdf) (2004): contains a nice discussion of floating-point myths and misconceptions. A brief but useful summary can be found in [this Julia-focused floating-point overview](https://discourse.julialang.org/t/psa-floating-point-arithmetic/8678) by Prof. John Gibson. Because many programmers never learn how floating-point arithmetic actually works, there are [many common myths](https://github.com/mitmath/18335/blob/spring21/notes/fp-myths.pdf) about its behavior.
**Further reading:** [Trefethen & Bau's *Numerical Linear Algebra*](https://people.maths.ox.ac.uk/trefethen/text.html), lecture 13. [What Every Computer Scientist Should Know About Floating Point Arithmetic](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.22.6768) (David Goldberg, ACM 1991). William Kahan, [How Java's floating-point hurts everyone everywhere](http://www.cs.berkeley.edu/~wkahan/JAVAhurt.pdf) (2004): contains a nice discussion of floating-point myths and misconceptions. A brief but useful summary can be found in [this Julia-focused floating-point overview](https://discourse.julialang.org/t/psa-floating-point-arithmetic/8678) by Prof. John Gibson. Because many programmers never learn how floating-point arithmetic actually works, there are [many common myths](https://github.com/mitmath/18335/blob/spring21/notes/fp-myths.pdf) about its behavior. (An infamous example is `0.1 + 0.2` giving `0.30000000000000004`, which people are puzzled by so frequently it has led to a web site [https://0.30000000000000004.com/](https://0.30000000000000004.com/)!)