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https://issues.apache.org/jira/browse/MATH-375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12903808#action_12903808
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Luc Maisonobe commented on MATH-375:
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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:
[http://www.apache.org/legal/resolved.html#category-a]. Here is the appropriate
quote concerning LGPL from the previous link,:
{quote}
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 products.
{quote}
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 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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