# CPU utilization in parallel computing

**URL:** https://discourse.julialang.org/t/cpu-utilization-in-parallel-computing/26320
**Category:** Julia at Scale
**Created:** [July 13, 2019, 1:54pm UTC](https://discourse.julialang.org/t/cpu-utilization-in-parallel-computing/26320 "2019-07-13T13:54:41Z")
**Posts on this page:** 2
**Page:** 1

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### Author: ![FujiwaraTakumiEH](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/fujiwaratakumieh/32/37975_2.png) [@FujiwaraTakumiEH](https://discourse.julialang.org/u/FujiwaraTakumiEH)
#### Post date: [July 13, 2019, 1:54pm UTC](https://discourse.julialang.org/t/cpu-utilization-in-parallel-computing/26320/1 "2019-07-13T13:54:41Z")

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When using `@distributed` parallel code, if the amount of data needed to be manipulated is large, will CPU utilization reach 100%, which can be used as a basis for successful parallel？ (of course, direct test runtime is more accurate)

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### Author: ![Tamas\_Papp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tamas_papp/32/25949_2.png) [@Tamas\_Papp](https://discourse.julialang.org/u/Tamas_Papp)
#### Post date: [July 13, 2019, 2:32pm UTC](https://discourse.julialang.org/t/cpu-utilization-in-parallel-computing/26320/2 "2019-07-13T14:32:07Z")

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This depends on your task and whether it is CPU-bound, the details of the hardware setup, how the data is accessed, and a lot of other details.