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SubjectRe: [PATCH v2 0/3] perf-stat: share hardware PMCs with BPF
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On March 18, 2021 6:14:34 PM GMT-03:00, Jiri Olsa <jolsa@redhat.com> wrote:
>On Thu, Mar 18, 2021 at 03:52:51AM +0000, Song Liu wrote:
>>
>>
>> > On Mar 17, 2021, at 6:11 AM, Arnaldo Carvalho de Melo
><acme@kernel.org> wrote:
>> >
>> > Em Wed, Mar 17, 2021 at 02:29:28PM +0900, Namhyung Kim escreveu:
>> >> Hi Song,
>> >>
>> >> On Wed, Mar 17, 2021 at 6:18 AM Song Liu <songliubraving@fb.com>
>wrote:
>> >>>
>> >>> perf uses performance monitoring counters (PMCs) to monitor
>system
>> >>> performance. The PMCs are limited hardware resources. For
>example,
>> >>> Intel CPUs have 3x fixed PMCs and 4x programmable PMCs per cpu.
>> >>>
>> >>> Modern data center systems use these PMCs in many different ways:
>> >>> system level monitoring, (maybe nested) container level
>monitoring, per
>> >>> process monitoring, profiling (in sample mode), etc. In some
>cases,
>> >>> there are more active perf_events than available hardware PMCs.
>To allow
>> >>> all perf_events to have a chance to run, it is necessary to do
>expensive
>> >>> time multiplexing of events.
>> >>>
>> >>> On the other hand, many monitoring tools count the common metrics
>(cycles,
>> >>> instructions). It is a waste to have multiple tools create
>multiple
>> >>> perf_events of "cycles" and occupy multiple PMCs.
>> >>
>> >> Right, it'd be really helpful when the PMCs are frequently or
>mostly shared.
>> >> But it'd also increase the overhead for uncontended cases as BPF
>programs
>> >> need to run on every context switch. Depending on the workload,
>it may
>> >> cause a non-negligible performance impact. So users should be
>aware of it.
>> >
>> > Would be interesting to, humm, measure both cases to have a firm
>number
>> > of the impact, how many instructions are added when sharing using
>> > --bpf-counters?
>> >
>> > I.e. compare the "expensive time multiplexing of events" with its
>> > avoidance by using --bpf-counters.
>> >
>> > Song, have you perfmormed such measurements?
>>
>> I have got some measurements with perf-bench-sched-messaging:
>>
>> The system: x86_64 with 23 cores (46 HT)
>>
>> The perf-stat command:
>> perf stat -e
>cycles,cycles,instructions,instructions,ref-cycles,ref-cycles <target,
>etc.>
>>
>> The benchmark command and output:
>> ./perf bench sched messaging -g 40 -l 50000 -t
>> # Running 'sched/messaging' benchmark:
>> # 20 sender and receiver threads per group
>> # 40 groups == 1600 threads run
>> Total time: 10X.XXX [sec]
>>
>>
>> I use the "Total time" as measurement, so smaller number is better.
>>
>> For each condition, I run the command 5 times, and took the median of
>
>> "Total time".
>>
>> Baseline (no perf-stat) 104.873 [sec]
>> # global
>> perf stat -a 107.887 [sec]
>> perf stat -a --bpf-counters 106.071 [sec]
>> # per task
>> perf stat 106.314 [sec]
>> perf stat --bpf-counters 105.965 [sec]
>> # per cpu
>> perf stat -C 1,3,5 107.063 [sec]
>> perf stat -C 1,3,5 --bpf-counters 106.406 [sec]
>
>I can't see why it's actualy faster than normal perf ;-)
>would be worth to find out

Isn't this all about contended cases?

>
>jirka
>
>>
>> From the data, --bpf-counters is slightly better than the regular
>event
>> for all targets. I noticed that the results are not very stable.
>There
>> are a couple 108.xx runs in some of the conditions (w/ and w/o
>> --bpf-counters).
>>
>>
>> I also measured the average runtime of the BPF programs, with
>>
>> sysctl kernel.bpf_stats_enabled=1
>>
>> For each event, if we have one leader and two followers, the total
>run
>> time is about 340ns. IOW, 340ns for two perf-stat reading
>instructions,
>> 340ns for two perf-stat reading cycles, etc.
>>
>> Thanks,
>> Song
>>

--
Sent from my Android device with K-9 Mail. Please excuse my brevity.

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