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https://issues.apache.org/jira/browse/MATH-650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13206181#comment-13206181
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Gilles commented on MATH-650:
-----------------------------
{quote}
I'm surprised though that binary files take longer to load than litteral. I
should have thought that reading a presumably longer table, and parsing a
presumably larger number of octets for each double would result in a longer
loading time. I must have missed something.
{quote}
Thank you for asking! ;)
I also raised this puzzling point on the ML, after having implemented the
resource loading approach following a suggestion by Ted Dunning, who also had
hinted that it would be faster.
Nobody came up with an explanation about why the implementation is indeed
slower. I'd have said that
* either there is a bug in my implementation (in the sense that is not done
correctly to get the best performance from this approach) and it would nice and
useful to find what is wrong there,
* or the loading of big literal arrays is faster and it would be interesting to
know why, in order to rectify the conventional wisdom that had us believe
otherwise.
> FastMath has static code which slows the first access to FastMath
> -----------------------------------------------------------------
>
> Key: MATH-650
> URL: https://issues.apache.org/jira/browse/MATH-650
> Project: Commons Math
> Issue Type: Improvement
> Affects Versions: Nightly Builds
> Environment: Android 2.3 (Dalvik VM with JIT)
> Reporter: Alexis Robert
> Priority: Minor
> Fix For: 3.0
>
> Attachments: FastMathLoadCheck.java, LucTestPerformance.java
>
>
> Working on an Android application using Orekit, I've discovered that a simple
> FastMath.floor() takes about 4 to 5 secs on a 1GHz Nexus One phone (only the
> first time it's called). I've launched the Android profiling tool (traceview)
> and the problem seems to be linked with the static portion of FastMath code
> named "// Initialize tables"
> The timing resulted in :
> - FastMath.slowexp (40.8%)
> - FastMath.expint (39.2%)
> \- FastMath.quadmult() (95.6% of expint)
> - FastMath.slowlog (18.2%)
> Hoping that would help
> Thanks!
> Alexis Robert
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