# Julia under rosetta 2 on mac m1: threading/scheduling issues with openblas?

**URL:** https://discourse.julialang.org/t/julia-under-rosetta-2-on-mac-m1-threading-scheduling-issues-with-openblas/72087
**Category:** Internals & Design
**Tags:** mac-m1
**Created:** [November 25, 2021, 10:50pm UTC](https://discourse.julialang.org/t/julia-under-rosetta-2-on-mac-m1-threading-scheduling-issues-with-openblas/72087 "2021-11-25T22:50:24Z")
**Posts on this page:** 3
**Page:** 1

<div class="post-metadata">

### Author: ![Egwene\_al\_Vere](https://avatars.discourse-cdn.com/v4/letter/e/df788c/32.png) [@Egwene\_al\_Vere](https://discourse.julialang.org/u/Egwene_al_Vere)
#### Post date: [November 25, 2021, 10:50pm UTC](https://discourse.julialang.org/t/julia-under-rosetta-2-on-mac-m1-threading-scheduling-issues-with-openblas/72087/1 "2021-11-25T22:50:24Z")

</div>

Not sure where is the best place to post this: I noticed that with julia (x86) running under rosetta translation, for codes that heavily uses linear algebra, the performance can be 7-10 times slower with default (8) vs single-threaded openblas. It’s hard to get a minimum example, but a somewhat simple example is listed at the end of this post. Tested on Julia 1.70 rc3. My guess is the process may run in the slow efficiency core along with the fast performance core, causing a lot of wait/locks:

Looking into this further, it looks like by default, BLAS set thread to 8. When setting thread to 1, the code can be quite faster:

Default (`BLAS.get_num_threads()` returns 8)  
1.024 s (11007 allocations: 6.04 MiB)

whereas setting BLAS thread to 1 `BLAS.set_num_threads(1)`, the code runs  
170.692 ms (11007 allocations: 6.04 MiB)

As a comparison, the native arm m1 1.7 build gives  
55.083 ms (11007 allocations: 6.04 MiB)

It looks like under the default 8 threads, 2 would run in the slower efficiency core (maybe then causing wait?)

 ![Screen Shot 2021-11-25 at 12.05.41 PM](https://global.discourse-cdn.com/julialang/original/3X/b/1/b1d8111ae77c87ff42f96a26282fd6d21f6983b3.png)

whereas in the 1-threaded openblas case, the peak is not very discernible

 ![Screen Shot 2021-11-25 at 12.17.20 PM copy](https://global.discourse-cdn.com/julialang/original/3X/f/d/fd8d6b39dec1da5ee119d7c7f66815b16456e62f.png)

And in vs code, `@profview` shows the majority time would be on wait/lock (the tiny silver at the rightmost is the actual calculations with linear algebra codes)

 ![Screen Shot 2021-11-25 at 5.28.52 PM](https://global.discourse-cdn.com/julialang/original/3X/1/9/192f94cb4509eb5123e737c5cd687e9b01e6bb74.png)

Example:

```julia
using BenchmarkTools, LinearAlgebra
using ExponentialUtilities

function loop_ex(n, m)
    c = zeros(ComplexF64, n, n)
    cache = ExponentialUtilities.alloc_mem(c, ExpMethodHigham2005())
    for i = 1:m
        a = rand(ComplexF64, n, n)
        b = exponential!(a, ExpMethodHigham2005(a), cache)
        mul!(c, b, b, 1, 1)
    end
    c
end

@btime loop_ex(17, 1000)

```

Is there a way to force julia to run only in performance core by setting the correct qos? Should this be reported to github? Thanks!

–  
edit: might be relevant: [pr](https://github.com/JuliaLang/julia/pull/42099)

---

<div class="post-metadata">

### Author: ![gbaraldi](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/gbaraldi/32/22101_2.png) [@gbaraldi](https://discourse.julialang.org/u/gbaraldi)
#### Post date: [November 26, 2021, 1:36am UTC](https://discourse.julialang.org/t/julia-under-rosetta-2-on-mac-m1-threading-scheduling-issues-with-openblas/72087/2 "2021-11-26T01:36:54Z")

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I set this on the normal m1, I imagine for the higher performance ones you just change the number and I don’t have issues. The scheduler then uses the high performance cores mostly

```nohighlight
export OMP_NUM_THREADS=4
export JULIA_NUM_THREADS=4
export OPENBLAS_NUM_THREADS=4

```

---

<div class="post-metadata">

### Author: ![goerch](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/goerch/32/29122_2.png) [@goerch](https://discourse.julialang.org/u/goerch)
#### Post date: [November 26, 2021, 4:07am UTC](https://discourse.julialang.org/t/julia-under-rosetta-2-on-mac-m1-threading-scheduling-issues-with-openblas/72087/3 "2021-11-26T04:07:13Z")

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I’m not sure this is a platform specific problem.

```julia
versioninfo()
println(BLAS.get_config())
println(BLAS.get_num_threads())
@btime loop_ex(17, 1000)
BLAS.set_num_threads(1)
println(BLAS.get_num_threads())
@btime loop_ex(17, 1000)

```

yields

```julia
Julia Version 1.7.0-rc3
Commit 3348de4ea6 (2021-11-15 08:22 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: Intel(R) Core(TM) i7-10710U CPU @ 1.10GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
Environment:
  JULIA_NUM_THREADS = 6
LBTConfig([ILP64] libopenblas64_.dll)
8
  457.824 ms (11007 allocations: 6.04 MiB)
1
  36.553 ms (11007 allocations: 6.04 MiB)

```

and

```julia
Julia Version 1.7.0-rc3
Commit 3348de4ea6 (2021-11-15 08:22 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: Intel(R) Core(TM) i7-10710U CPU @ 1.10GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
Environment:
  JULIA_NUM_THREADS = 6
LBTConfig([ILP64] mkl_rt.1.dll)
1
  36.639 ms (11007 allocations: 6.04 MiB)
1
  36.577 ms (11007 allocations: 6.04 MiB)

```

here.