RE: [PATCH V2 0/5] event synthesization multithreading for perf record
From: Liang, Kan
Date: Fri Oct 20 2017 - 16:19:24 EST
>
> * kan.liang@xxxxxxxxx <kan.liang@xxxxxxxxx> wrote:
>
> > From: Kan Liang <Kan.liang@xxxxxxxxx>
> >
> > The event synthesization multithreading is introduced in ("perf top
> > optimization") https://lkml.org/lkml/2017/9/29/269
> > But it was not enabled for perf record. Because the process function
> > process_synthesized_event was not multithreading friendly.
> >
> > The patch series temporarily stores the process result in per-thread
> > file, which make the processing in parallel. Then it dumps the file
> > one by one to the perf.data at the end of event synthesization.
> >
> > The source code is also available at
> > https://github.com/kliang2/perf.git perf_record_opt
> >
> > Usually, the event synthesization only happens once on either start or end.
> > With the snapshotting code, we synthesize events multiple times, once
> > per each new perf.data file. Both of the cases are verified.
> >
> > Here are the latency test result on Knights Mill and Skylake server
> >
> > The workload is to compile Linux kernel as below "sudo nice make
> > -j$(grep -c '^processor' /proc/cpuinfo)"
> > Then, "sudo perf record -e cycles -a -- sleep 1"
> >
> > The latency is the time cost of __machine__synthesize_threads or its
> > multithreading replacement, record__multithread_synthesize.
> >
> > - Latency on Knights Mill (272 CPUs)
> >
> > Original(s) With patch(s) Speedup
> > 12.74 5.54 2.3X
> >
> > - Latency on Skylake server (192 CPUs)
> >
> > Original(s) With patch(s) Speedup
> > 0.36 0.25 1.47X
>
> Btw., just as an interesting experiment, could you try to measure how it
> performs to create just the per-CPU files, and *not* dump them into a single
> file?
>
Sure, please find the experiment result in the cover letter of V3 patch series.
Thanks,
Kan
> I.e. how much faster will it get if the serialization at the end is avoided?
>
> Of course nothing can read such per-CPU files yet, so this is just for scalability
> measurement.
>
> Thanks,
>
> Ingo