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@tkoskela
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I've added thread pinning opimizations (thanks to @giordano) that could improve performance on Archer2. I would like to test the performance with

  • 8 ranks per node, 16 threads per rank
  • 16 ranks per node, 8 threads per rank
  • 32 ranks per node, 4 threads per rank

@tkoskela tkoskela requested a review from DanGiles January 27, 2023 16:32
@giordano giordano changed the title Tk/thread pinning Add thread pinning optimization Jan 27, 2023
Comment on lines +8 to +26
comm = MPI.COMM_WORLD
mpi_size = MPI.Comm_size(comm)
my_rank = MPI.Comm_rank(comm)

cores_per_numa = 16
threads_per_rank = Threads.nthreads()
ranks_per_numa = div(cores_per_numa, threads_per_rank)

# Pin threads so that threads of a MPI rank will be pinned to cores with
# contiguous IDs. This will ensure that
# - When running 16 or less threads per rank, all threads will be pinned to the same
# NUMA region as their master (sharing a memory controller within Infinity fabric)
# - When running 8 or less threads per rank, all threads will be pinned to the same
# Core Complex Die
# - When running 4 or less threads per rank, all threads will be pinned to the same
# Core Complex (sharing a L3 cache)

my_numa, my_id_in_numa = divrem(my_rank, ranks_per_numa) .+ (1, 0)
pinthreads( numa( my_numa, 1:Threads.nthreads() ) .+ threads_per_rank .* my_id_in_numa )
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With ThreadPinning v0.7.3 you can use simply pinthreads(:affinitymask)

@matt-graham
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I think the failed CI jobs on nightly build here may have been due to the same upstream problems that were causing issues in #236 (comment) but we've now exceeded the 30 day window for being able to re-run workflows.

This otherwise looks good to merge to me other than @giordano's suggestion above to use pinthreads(:affinitymask). Not sure if there is any other way to trigger a new workflow run than pushing a new commit to this branch as we don't have a workflow_dispatch trigger specified to allow running manually.

Also just noticed this is set to merge in to scaling_archer2 branch - as the extra/weak_scaling/run_particleda.jl script currently on master hasn't been updated for the changes in #232 and so doesn't run, it would probably be worth merging both those changes and those here in to master?

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3 participants