[
https://issues.apache.org/jira/browse/MATH-375?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12892134#action_12892134
]
Luc Maisonobe commented on MATH-375:
------------------------------------
I finally found some time to look at this proposal.
It is very impressive and I really want to include it.
As the code is rather long and has been developed outside of the Apache
Software Foundation, could you send a signed Software Grant to the foundation
(see [http://www.apache.org/licenses/#grants]) ? As you will see, the softaware
grant is simply a license you grant, the intellectual property remains yours.
The best way would be to have it sent by fax or by mail with a detached gpg
signature. Please refer to this Jira issue and the attached patch you already
submitted.
Thanks a lot for this contribution.
> 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.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
