Date:   Thu, 18 Mar 2021 03:52:51 +0000
From:   Song Liu <songliubraving@...com>
To:     Arnaldo Carvalho de Melo <acme@...nel.org>
CC:     Namhyung Kim <namhyung@...nel.org>,
        linux-kernel <linux-kernel@...r.kernel.org>,
        Kernel Team <Kernel-team@...com>,
        "Arnaldo Carvalho de Melo" <acme@...hat.com>,
        Jiri Olsa <jolsa@...nel.org>
Subject: Re: [PATCH v2 0/3] perf-stat: share hardware PMCs with BPF



> On Mar 17, 2021, at 6:11 AM, Arnaldo Carvalho de Melo <acme@...nel.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@...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]

>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

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