# Making @benchmark outputs statistically meaningful, and actionable

**URL:** <https://discourse.julialang.org/t/making-benchmark-outputs-statistically-meaningful-and-actionable/104256>\
**Category:** Profiling\
**Tags:** benchmark, benchmarktools\
**Created:** [September 26, 2023, 11:38am UTC](https://discourse.julialang.org/t/making-benchmark-outputs-statistically-meaningful-and-actionable/104256 "2023-09-26T11:38:25Z")\
**Posts on this page:** 1\
**Showing post:** 121

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**Author:** ![nsajko](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nsajko/32/221187_2.png) [@nsajko](https://discourse.julialang.org/u/nsajko)\
**Post date:** [October 1, 2023, 7:51pm UTC](https://discourse.julialang.org/t/making-benchmark-outputs-statistically-meaningful-and-actionable/104256/121 "2023-10-01T19:51:10Z")

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AFAIK PGO for Julia user code is a relevant topic. Were Julia to gain profile-guided recompilation as an option for Julia packages, as mentioned [here](https://discourse.julialang.org/t/has-pgo-for-re-compiling-methods-been-considered/97426), `BenchmarkTools` could presumably stay simple, because LLVM would take care of the complexity. That is, `BenchmarkTools` would just need to recompile with PGO, which should (when enough PGO-based optimizations are implemented) ensure that some of the issues mentioned here don’t matter.

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