<div dir="ltr"><br><div class="gmail_extra"><br><br><div class="gmail_quote">On Tue, Jan 7, 2014 at 11:06 AM, Tobias Grosser <span dir="ltr"><<a href="mailto:tobias@grosser.es" target="_blank">tobias@grosser.es</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">Hi,<br>
<br>
I would like to announce a new set of LNT -O3 performance testers.<br>
<br>
In a discussion titled "Question about results reliability in LNT infrustructure" Anton suggested that one way to get statistically reliable test results from the LNT infrastructure is to use a larger sample size (5-10) as well as a more robust statistical test (Wilcoxon/Mann-Whitney). Another requirement to make the performance results we get from our testers useful is to have a per-commit performance run.<br>
<br>
I would like to announce that I set up 4 identical machines* that publicly report LNT results for 'clang -O3' at:<br>
<br>
<a href="http://llvm.org/perf/db_default/v4/nts/machine/34" target="_blank">http://llvm.org/perf/db_<u></u>default/v4/nts/machine/34</a><br>
<br>
We currently catch in average groups of 3-5 commits. As most commits obviously do not impact performance this seems to be enough to track down performance regressions/changes easily.<br></blockquote><div><br></div><div>If possible, I think it would be a good idea to filter out commits that don't affect code generation. This would allow machine resources to be better used.</div>
<div><br></div><div>Is there some way we can easily filter commits based on whether they affect code generation or not? Would it be reliable enough to check if the commit touches any of our integration tests?</div><div><br>
</div><div>As a rough estimate:</div><div><br></div><div><div>sean:~/pg/llvm/llvm % git log --oneline --since='1 month ago' | wc -l</div><div>706</div><div>sean:~/pg/llvm/llvm % git log --oneline --since='1 month ago' ./test | wc -l</div>
<div>317</div></div><div><br></div><div>So it seems like if this is reasonable we can effectively double our performance testing coverage by filtering like this.</div><div><br></div><div>-- Sean Silva</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
The results that have been reported so far seem to provide sufficient information to catch performance changes. Specifically, when setting the aggregation function to median, most runs are shown to not impact performance:<br>
<br>
e.g: <a href="http://llvm.org/perf/db_default/v4/nts/19939?num_comparison_runs=10&test_filter=&test_min_value_filter=&aggregation_fn=median&compare_to=19934&submit=Update" target="_blank">http://llvm.org/perf/db_<u></u>default/v4/nts/19939?num_<u></u>comparison_runs=10&test_<u></u>filter=&test_min_value_filter=<u></u>&aggregation_fn=median&<u></u>compare_to=19934&submit=Update</a><br>
<br>
We still have a couple of runs that report performance differences, but where looking at the performance graph of the changed test cases makes it very clear that those are false positives due to test case noise.<br>
<br>
Here comes the point of this mail. I am currently not sure when I find time to improve the LNT infrastructure to take advantage of the data provided. So in case someone else would like to have a look and e.g. add the Wilcoxon/Mann-Whitney test this would be highly appreciated.<br>
<br>
I also have a couple of more machines. Hence, if the LNT infrastructure is in place we can use them to increase the reliability of the results even more.<br>
<br>
Cheers,<br>
Tobias<br>
<br>
* Also have sufficiently close performance characteristics when running LNT tests for the same version<br>
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</blockquote></div><br></div></div>