# Again on reaching optimal parallel scaling

**URL:** <https://discourse.julialang.org/t/again-on-reaching-optimal-parallel-scaling/73203>\
**Category:** Performance\
**Tags:** parallel\
**Created:** [December 16, 2021, 2:40pm UTC](https://discourse.julialang.org/t/again-on-reaching-optimal-parallel-scaling/73203 "2021-12-16T14:40:57Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![carstenbauer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/carstenbauer/32/4981_2.png) [@carstenbauer](https://discourse.julialang.org/u/carstenbauer)\
**Post date:** [December 16, 2021, 7:08pm UTC](https://discourse.julialang.org/t/again-on-reaching-optimal-parallel-scaling/73203/5 "2021-12-16T19:08:51Z")

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> [@tkf](#):
>
> Another way to profile the program is to look at the performance counters using [GitHub - JuliaPerf/LinuxPerf.jl](https://github.com/JuliaPerf/LinuxPerf.jl) (or just `perf stat` command) if you use Linux.

FWIW, there also is [GitHub - JuliaPerf/LIKWID.jl: Julia wrapper for the performance monitoring and benchmarking suite LIKWID.](https://github.com/JuliaPerf/LIKWID.jl) which has at least _some_ documentation. 🙂

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