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From "Luc Maisonobe (JIRA)" <>
Subject [jira] Commented: (MATH-375) Elementary functions in JDK are slower than necessary and not as accurate as they could be.
Date Sat, 28 Aug 2010 09:15:56 GMT


Luc Maisonobe commented on MATH-375:

OK, then I'll simply raise the threshold a bit.

Offering dfp under a compatible license would help the project. The answer from our legal
team concerning this toic can be found here: [].
Here is the appropriate quote concerning LGPL from the previous link,:

The LGPL is ineligible primarily due to the restrictions it places on larger works, violating
the third license criterion. Therefore, LGPL-licensed works must not be included in Apache

If you consider offering dfp on a dual license, would you also consider integrating it into
commons-math too ? It would be a very nice addition I think.

> Elementary functions in JDK are slower than necessary and not as accurate as they could
> -------------------------------------------------------------------------------------------
>                 Key: MATH-375
>                 URL:
>             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
> 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
> 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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