<div dir="ltr">Update: in that same block of 10,000 LLVM/Clang revisions, this the number of distinct SHA1 hashes for the binaries of the following benchmarks:<div><br></div><div><div><div>7<span class="" style="white-space:pre"> </span>MultiSource/Applications/aha/aha</div><div>2<span class="" style="white-space:pre"> </span>MultiSource/Benchmarks/BitBench/drop3/drop3</div><div>10<span class="" style="white-space:pre"> </span>MultiSource/Benchmarks/BitBench/five11/five11</div><div>7<span class="" style="white-space:pre"> </span>MultiSource/Benchmarks/BitBench/uudecode/uudecode</div><div>3<span class="" style="white-space:pre"> </span>MultiSource/Benchmarks/BitBench/uuencode/uuencode</div><div>5<span class="" style="white-space:pre"> </span>MultiSource/Benchmarks/Trimaran/enc-rc4/rc4</div><div>11<span class="" style="white-space:pre"> </span>SingleSource/Benchmarks/BenchmarkGame/n-body</div><div>2<span class="" style="white-space:pre"> </span>SingleSource/Benchmarks/Shootout/ackermann</div></div><div><br></div><div>Let me know if there are any specific benchmarks you would like me to test.</div></div><div><br></div><div>-- Sean Silva</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, May 20, 2015 at 3:31 PM, Sean Silva <span dir="ltr"><<a href="mailto:chisophugis@gmail.com" target="_blank">chisophugis@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">I found an interesting datapoint:<div><br><div>In the last 10,000 revisions of LLVM+Clang, only 10 revisions actually caused the binary of MultiSource/Benchmarks/BitBench/five11 to change. So if just store a hash of the binary in the database, we should be able to pool all samples we have collected while the binary is the the same as it currently is, which will let us use significantly more datapoints for the reference.</div><div><br></div><div>Also, we can trivially eliminate running the regression detection algorithm if the binary hasn't changed.</div><span class="HOEnZb"><font color="#888888"><div><br></div><div>-- Sean Silva</div></font></span></div></div><div class="HOEnZb"><div class="h5"><div class="gmail_extra"><br><div class="gmail_quote">On Mon, May 18, 2015 at 9:02 PM, Chris Matthews <span dir="ltr"><<a href="mailto:chris.matthews@apple.com" target="_blank">chris.matthews@apple.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word">The reruns flag already does that. It helps a bit, but only as long as the the benchmark is flagged as regressed.<div><br></div><div><br><div><blockquote type="cite"><div><div><div>On May 18, 2015, at 8:28 PM, Sean Silva <<a href="mailto:chisophugis@gmail.com" target="_blank">chisophugis@gmail.com</a>> wrote:</div><br></div></div><div><div><div><div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote">On Mon, May 18, 2015 at 11:24 AM, Mikhail Zolotukhin <span dir="ltr"><<a href="mailto:mzolotukhin@apple.com" target="_blank">mzolotukhin@apple.com</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"><div style="word-wrap:break-word">Hi Chris and others!<div><br></div><div>I totally support any work in this direction.</div><div><br></div><div>In the current state LNT’s regression detection system is too noisy, which makes it almost impossible to use in some cases. If after each run a developer gets a dozen of ‘regressions’, none of which happens to be real, he/she won’t care about such reports after a while. We clearly need to filter out as much noise as we can - and as it turns out even simplest techniques could help here. For example, the technique I used (which you mentioned earlier) takes ~15 lines of code to implement and filters out almost all noise in our internal data-sets. It’d be really cool to have something more scientifically-proven though:)</div><div><br></div><div>One thing to add from me - I think we should try to do our best in assumption that we don’t have enough samples. Of course, the more data we have - the better, but in many cases we can’t (or we don’t want) to increase number os samples, since it dramatically increases testing time.</div></div></blockquote><div><br></div><div><span style="font-size:13px">Why not just start out with only a few samples, then collect more for benchmarks that appear to have changed?</span></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"><div style="word-wrap:break-word"><div> That’s not to discourage anyone from increasing number of samples, or adding techniques relying on a significant number of samples, but rather to try mining as many ‘samples’ as possible from the data we have - e.g. I absolutely agree with your idea to pass more than 1 previous run.</div><div><br></div><div>Thanks,</div><div>Michael</div><div><br></div></div></blockquote></div></div></div></div></div><span>
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