[LLVMdev] Proposal: change LNT’s regression detection algorithm and how it is used to reduce false positives

[Kristof Beyls]

Sounds like a great idea!

 

From: llvmdev-bounces at cs.uiuc.edu [mailto:llvmdev-bounces at cs.uiuc.edu] On Behalf Of Smith, Kevin B
Sent: 20 May 2015 23:54
To: Sean Silva; Chris Matthews
Cc: LLVM Developers Mailing List
Subject: Re: [LLVMdev] Proposal: change LNT’s regression detection algorithm and how it is used to reduce false positives

 

Ø  Also, we can trivially eliminate running the regression detection algorithm if the binary hasn't changed.

 

Strongly agree.  Internal performance regression testing for Intel compiler uses this method to help eliminate noise. It is

a great first line method to greatly cut down on developer time wasted chasing phantoms.

 

Kevin Smith

 

From: llvmdev-bounces at cs.uiuc.edu [mailto:llvmdev-bounces at cs.uiuc.edu] On Behalf Of Sean Silva
Sent: Wednesday, May 20, 2015 3:31 PM
To: Chris Matthews
Cc: LLVM Developers Mailing List
Subject: Re: [LLVMdev] Proposal: change LNT’s regression detection algorithm and how it is used to reduce false positives

 

I found an interesting datapoint:

 

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.

 

Also, we can trivially eliminate running the regression detection algorithm if the binary hasn't changed.

 

-- Sean Silva

 

On Mon, May 18, 2015 at 9:02 PM, Chris Matthews <chris.matthews at apple.com> wrote:

The reruns flag already does that.  It helps a bit, but only as long as the the benchmark is flagged as regressed.

 

 

On May 18, 2015, at 8:28 PM, Sean Silva <chisophugis at gmail.com> wrote:

 

 

 

On Mon, May 18, 2015 at 11:24 AM, Mikhail Zolotukhin <mzolotukhin at apple.com> wrote:

Hi Chris and others!

 

I totally support any work in this direction.

 

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:)

 

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.

 

Why not just start out with only a few samples, then collect more for benchmarks that appear to have changed?

 

-- Sean Silva

 

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.

 

Thanks,

Michael

 

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