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https://issues.apache.org/jira/browse/MATH-375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12877132#action_12877132
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William Rossi commented on MATH-375:
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I'm not as well versed in these copyright issues I as I should be, but my
understanding is that as the copyright holder of the dfp library, I could
dual license it. In any event, dfp is not required by the software, its
only used in the supporting test cases.
Which also why I whould be hesitant to assign copyright to ASF, if I were
to do that and ASF decides not to persue the project then I'm left with
nothing. By maintaining the copyright, I can issue licenses to other
parties as I see fit.
The ASF software grant agreement doesn't ask me to assign copyright to
ASF, but to mearly agree to specific license terms.
> 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
> Attachments: 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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