Re: [PATCH] perf jevents: Limit the number of JSON reading workers

[Ian Rogers]

On Thu, Sep 17, 2026 at 3:00 AM Sandipan Das <sandipan.das@xxxxxxx> wrote:
>
> The ProcessPoolExecutor is created without max_workers, so
> concurrent.futures defaults to one worker per CPU and forks all of them
> when the first task is submitted. Each worker costs the parent a few
> file descriptors. For systems with high core-count processors like the
> AMD EPYC 9996, the pool can easily exhaust RLIMIT_NOFILE as seen below.
>
>   File ".../multiprocessing/popen_fork.py", line 65, in _launch
>     child_r, parent_w = os.pipe()
>   OSError: [Errno 24] Too many open files
>
> The error is reported, but jevents.py does not exit. The workers that
> did start stay blocked waiting for work and are never joined, so the
> build eventually hangs. Other targets keep building in the meantime,
> leaving the traceback several lines above the point where the build
> stalls.
>
> Limit the pool instead of sizing it against the descriptor limit, which
> would mean relying on how many descriptors concurrent.futures needs for
> each worker. At least for recent AMD EPYC processors, reading the JSON
> files does not need many workers to be fast and things typically stop
> scaling beyond 32 workers. Hence, a small upper bound keeps the speedup
> and stays well inside any usable limit.
>
> Fixes: eaab2eb09dc2 ("perf pmu-events: Parallelize JSON and metric pre-computation in jevents.py")
> Signed-off-by: Sandipan Das <sandipan.das@xxxxxxx>

Reviewed-by: Ian Rogers <irogers@xxxxxxxxxx>

Thanks,
Ian

> ---
>  tools/perf/pmu-events/jevents.py | 11 ++++++++++-
>  1 file changed, 10 insertions(+), 1 deletion(-)
>
> diff --git a/tools/perf/pmu-events/jevents.py b/tools/perf/pmu-events/jevents.py
> index 860027bb71b2..d81fe6757915 100755
> --- a/tools/perf/pmu-events/jevents.py
> +++ b/tools/perf/pmu-events/jevents.py
> @@ -1450,6 +1450,13 @@ const char *describe_metricgroup(const char *group)
>  }
>  """)
>
> +# Upper bound on the number of workers reading JSON files in parallel.
> +_max_parallel_workers = 32
> +
> +def _parallel_worker_count(num_tasks: int) -> int:
> +  return max(1, min(getattr(os, 'process_cpu_count', os.cpu_count)() or 1,
> +                    _max_parallel_workers, num_tasks))
> +
>  def _parallel_read_json_events(task: Tuple[str, str]) -> Tuple[str, str, Sequence[JsonEvent]]:
>    path, topic = task
>    return path, topic, _read_json_events_impl(path, topic)
> @@ -1549,7 +1556,9 @@ struct pmu_table_entry {
>      preprocess_arch_std_files(arch_path)
>      ftw(arch_path, [], collect_json)
>
> -  with concurrent.futures.ProcessPoolExecutor(initializer=_init_worker, initargs=(_arch_std_events,)) as executor:
> +  with concurrent.futures.ProcessPoolExecutor(max_workers=_parallel_worker_count(len(tasks)),
> +                                              initializer=_init_worker,
> +                                              initargs=(_arch_std_events,)) as executor:
>      for path, topic, events in executor.map(_parallel_read_json_events, tasks):
>        _json_cache[(path, topic)] = events
>
> --
> 2.53.0
>