Re: [PATCH v3 0/2]: perf: reduce data loss when profiling highly parallel CPU bound workloads

Alexey Budankov
2018-08-28T11:58:33Z

Hi Andi,

On 28.08.2018 11:59, Jiri Olsa wrote:
> On Mon, Aug 27, 2018 at 08:03:21PM +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
>>
>> Data loss metrics is the ratio lost_time/elapsed_time where
>> lost_time is the sum of time intervals containing PERF_RECORD_LOST
>> records and elapsed_time is the elapsed application run time
>> under profiling.
>
> I like the idea and I think it's good direction to go, but could
> you please share some from perf stat or whatever you used to meassure
> the new performance?

Is it ok to share VTune GUI screenshots I sent you the last time
to demonstrate the advantage of AIO trace streaming?

Thanks,
Alexey

>
> thanks,
> jirka
>