Sep 20 – 24, 2021
US/Pacific timezone

Adding features to perf using BPF

Sep 21, 2021, 8:00 AM
Refereed Track/Virtual-Room (LPC Virtual)

Refereed Track/Virtual-Room

LPC Virtual

LPC Refereed Track (Closed) LPC Refereed Track


Arnaldo Carvalho de Melo (Red Hat Inc.) Song Liu Namhyung Kim


The availability of BPF allows the improvement of preexisting perf features or the
addition of new ones without requiring kernel changes.

The first use of BPF to augment perf is to use BPF programs to profile other BPF
programs with 'perf stat', this is already upstream and set the stage for
further uses. This provides functionality similar to 'bpftool prog profile' while reusing
lots of 'perf stat' features that were developed and improved by the perf tooling

Then we had bperf, to share hardware performance counters, aggregate data in BPF
maps that then get read by 'perf stat' as if it was a normal perf event that then reuses
all the perf tooling features.

Some improvements, such as scaling cgroups perf monitoring were first attempted by
modifying the kernel. But after several attempts, one is being made using BPF with
encouraging results. It works by hooking into cgroup scheduling and doing aggregation
that is made available to 'perf stat' via bperf.

Such use of BPF for aggregating information in the kernel instead of changing the perf
subsystem was well received by a perf kernel maintainer, which is encouraging.

Future work will use BPF to enable perf_events when some specific trigger condition
takes place, so that only a window determined by two probes gets sampled.

Also being considered is the conversion of some perf subcommands that analyze tracepoints
like perf sched/lock/etc to use BPF to aggregate things in the kernel instead of passing
vast amounts of data for aggregation in userspace while keeping the existing, familiar
tooling interface.

This shows how the perf and BPF communities are working together to improve Linux tooling,
provide ways to scale profiling and to improve observability of BPF programs, it is
expected that by presenting this talk we get suggestions for further improvements.

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Primary authors

Arnaldo Carvalho de Melo (Red Hat Inc.) Song Liu


Namhyung Kim

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