Re: [PATCH v14 0/3]: perf: reduce data loss when profiling highly parallel CPU bound workloads

[Jiri Olsa]

On Thu, Oct 25, 2018 at 10:59:36AM +0300, Alexey Budankov wrote:
> Hi,
> 
> On 15.10.2018 13:17, Jiri Olsa wrote:
> > On Mon, Oct 15, 2018 at 09:26:09AM +0300, Alexey Budankov wrote:
> >>
> >> Currently in record mode the tool implements trace writing serially. 
> >> The algorithm loops over mapped per-cpu data buffers and stores 
> >> ready data chunks into a trace file using write() system call.
> >>
> >> At some circumstances the kernel may lack free space in a buffer 
> >> because the other buffer's half is not yet written to disk due to 
> >> some other buffer's data writing by the tool at the moment.
> >>
> >> Thus serial trace writing implementation may cause the kernel 
> >> to loose profiling data and that is what observed when profiling 
> >> highly parallel CPU bound workloads on machines with big number 
> >> of cores.
> >>
> >> Experiment with profiling matrix multiplication code executing 128 
> >> threads on Intel Xeon Phi (KNM) with 272 cores, like below,
> >> demonstrates data loss metrics value of 98%:
> >>
> >> /usr/bin/time perf record -o /tmp/perf-ser.data -a -N -B -T -R -g \
> >>     --call-graph dwarf,1024 --user-regs=IP,SP,BP --switch-events \
> >>     -e cycles,instructions,ref-cycles,software/period=1,name=cs,config=0x3/Duk -- \
> >>     matrix.gcc
> > 
> > I ran above on 24 cpu server and could not see the gain,
> > but I guess I'd need much bigger server to see that
> > 
> > anyway, the code is now nicely separated, and given the
> > advertised results below I have no objections
> > 
> > Reviewed-by: Jiri Olsa <jolsa@xxxxxxxxxx>
> 
> Is the plan Jiri mentioned earlier to have it as a stand alone patch kit 
> or upstream the changes into mainline?

I haven't heard from Arnaldo yet, but I'd like to have this merged in

jirka