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https://issues.apache.org/jira/browse/MATH-375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12902899#action_12902899
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Luc Maisonobe commented on MATH-375:
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Thanks for the fix.
I think we will probably start with all missing functions implemented with a
call to the corresponding Math function, This would allow people to simply do
global search and replace for Math to FastMath and have a working setup.
>From my personal use, the higher priorities functions to be implemented with
>fast and accurate versions would be first asin, acos, then cbrt and later
>sinh, cosh, tanh.
For functions like nextUp, signum and the likes, we could use our own bit
twiddling (we should also probably move MathUtil.nextAfter in the FastMath
class too).
I still did not see the grant registered in Apache foundation files, did you
sent it already ?
> Elementary functions in JDK are slower than necessary and not as accurate as
> they could be.
> -------------------------------------------------------------------------------------------
>
> Key: MATH-375
> URL: https://issues.apache.org/jira/browse/MATH-375
> Project: Commons Math
> Issue Type: New Feature
> Environment: JDK 1.4 - 1.6
> Reporter: William Rossi
> Fix For: 2.2
>
> Attachments: atanpatch.txt.gz, FastMath.tar.gz
>
>
> I would like to contribute improved versions on exp(), log(), pow(), etc. to
> the project. Please refer to this discussion thread
> http://markmail.org/message/zyeoguw6gwtofm62.
> I have developed over the past year a set of elementary functions similar to
> those in java.lang.Math, but with the following characteristics:
> * Higher performance.
> * Better accuracy. Results are accurate to slightly more that +/- 0.5 ULP.
> * Pure Java. The standard Math class is impleneted via JNI, and thus takes a
> performance hit.
> Note that some functions such as exp are nearly twice as fast in my
> implementation. I've seen it 3 times faster on different processors. The
> preformance varies by the relative speed of calculation vs memory lookups.
> The functions are implemented as tables of values in extra precision (approx
> 70 bits), and then interpolated with a minimax polynomial.
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