# Recommended env variables for most performant parallel/multithreading?

**URL:** <https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631>\
**Category:** Performance\
**Tags:** question\
**Created:** [June 24, 2019, 10:50pm UTC](https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631 "2019-06-24T22:50:13Z")\
**Posts on this page:** 4\
**Page:** 1

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**Author:** ![alvrg](https://avatars.discourse-cdn.com/v4/letter/a/eb8c5e/32.png) [@alvrg](https://discourse.julialang.org/u/alvrg)\
**Post date:** [June 24, 2019, 10:50pm UTC](https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631/1 "2019-06-24T22:50:13Z")

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Hi all, I have two questions.

1. What are the recommended values of the env variables (`JULIA_NUM_THREADS`, `MKL/OPENBLAS_NUM_THREADS`, …) if I want to speed up my code using `Threads.@threads`?

2. To what should I set those variables (the former ones plus `addprocs(x)`) if, instead, I would like to use `@distributed` or `pmap` to get more performance?

The heaviest parts of my scripts usually involve diagonalizing very large Hermitian matrices and/or BLAS operations. Also (3.), is there any possibility to mix multithreading code within parallel loops and still improve performance, or should I avoid using multithreading when I am already using parallel and vice-verse?

For more information, the Julia version I am using is

```julia
>>> versioninfo()

Julia Version 1.1.0
Commit 80516ca202* (2019-01-21 21:24 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: Intel(R) Xeon(R) W-2145 CPU @ 3.70GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, skylake)
Environment:
  JULIA_NUM_THREADS = 12

```

Searching for `W-2145 CPU @ 3.70GHz` I reached [this page](https://ark.intel.com/content/www/us/en/ark/products/126707/intel-xeon-w-2145-processor-11m-cache-3-70-ghz.html), where it says I have 8 cores and 16 threads. Should the answer for 1. be `JULIA_NUM_THREADS=16` and the answer for 2. be `addprocs(8)`? What about `MKL/OPENBLAS_NUM_THREADS`?

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**Author:** ![jeff.bezanson](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jeff.bezanson/32/48_2.png) [@jeff.bezanson](https://discourse.julialang.org/u/jeff.bezanson)\
**Post date:** [June 24, 2019, 11:02pm UTC](https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631/2 "2019-06-24T23:02:41Z")

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You’ll want the total number of threads in use to be 16, so for example `addprocs(8)` and `JULIA_NUM_THREADS=2` (this is the number of threads used by `@threads` within a single process). I would also set the number of BLAS threads to the same value as JULIA\_NUM\_THREADS. However, if you call BLAS within a `@threads` loop the CPU will probably be over-subscribed, so I would try to avoid that.

EDIT: If you happen to have a case where it makes sense to call BLAS inside a `@threads` loop, then you should set the number of BLAS threads to 1.

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**Author:** ![alvrg](https://avatars.discourse-cdn.com/v4/letter/a/eb8c5e/32.png) [@alvrg](https://discourse.julialang.org/u/alvrg)\
**Post date:** [June 25, 2019, 9:29am UTC](https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631/3 "2019-06-25T09:29:58Z")

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Thanks! I didn’t know that `JULIA_NUM_THREADS` was the number of threads used within a single process.

With BLAS threads do you mean that I should set both `BLAS.set_num_threads()` and `MKL_NUM_THREADS` to be equivalent to `JULIA_NUM_THREADS`, or that `BLAS.set_num_threads(Threads.nthreads())` works for every BLAS and MKL/OpenBLAS operation?

One more question, if I only want to use multithreading and not parallel, I should set `JULIA_NUM_THREADS=16`, am I right?

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<div class="post-metadata">

**Author:** ![jeff.bezanson](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jeff.bezanson/32/48_2.png) [@jeff.bezanson](https://discourse.julialang.org/u/jeff.bezanson)\
**Post date:** [June 25, 2019, 3:00pm UTC](https://discourse.julialang.org/t/recommended-env-variables-for-most-performant-parallel-multithreading/25631/4 "2019-06-25T15:00:39Z")

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> [@alvrg](#):
>
> `BLAS.set_num_threads(Threads.nthreads())` works for every BLAS and MKL/OpenBLAS operation?

I believe it should, yes.

> [@alvrg](#):
>
> One more question, if I only want to use multithreading and not parallel, I should set `JULIA_NUM_THREADS=16` , am I right?

Yes.