How to correctly install Julia in Renoir platform?

New to Julia
1

I am using a laptop with AMD Renoir CPU, the operating system is Manjaro under WSL2. Under a simple performance test there appears to be a major performance problem:

julia> versioninfo()

Julia Version 1.4.2
Commit 44fa15b150* (2020-05-23 18:35 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: AMD Ryzen 5 4600HS with Radeon Graphics
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-8.0.1 (ORCJIT, znver1)

julia> using LinearAlgebra

julia> LinearAlgebra.versioninfo()
BLAS: libopenblas (OpenBLAS 0.3.10 NO_LAPACK NO_LAPACKE DYNAMIC_ARCH NO_AFFINITY USE_OPENMP Prescott MAX_THREADS=64)
LAPACK: liblapack

I assume that it is recognized as a Prescott CPU and the performance does not surprise me:

julia> peakflops(10_000)
7.764909084542572e10

For a 6c12t processor it should not be right as my 7200U laptop has about 5e10 on battery. To add it gives basically same result in the Windows version of Julia.

I tried also to download from GitHub and compile it myself. With a naive compilation it gives:

julia> versioninfo()
Julia Version 1.6.0-DEV.531
Commit 3dc49ca18d (2020-07-24 05:37 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: AMD Ryzen 5 4600HS with Radeon Graphics
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-9.0.1 (ORCJIT, btver1)

julia> using LinearAlgebra

julia> LinearAlgebra.versioninfo()
BLAS: libopenblas (OpenBLAS 0.3.9  USE64BITINT DYNAMIC_ARCH NO_AFFINITY Prescott MAX_THREADS=32)
LAPACK: libopenblas64_

julia> peakflops(10_000)
5.056306894529036e10

To make things worse now the LLVM is even Bristol Ridge arch. I may be able to solve the part of OpenBLAS but the LLVM is confusing. Since I am pretty much a starter and using Julia as a learning tool instead of coping with compilation first, how should I fix the performance problem and have the hardware recognized correctly? BTW, I would expect step-to-step procedures since I suppose it is not only me but many other users new to Julia.

To add: This thread reported a similar Prescott problem. However, I suppose MKL to be a not acceptable solution for Zen CPUs and the “Prescott” should have an easy debug mode to override.

Update: I reinstalled and reconfigured the libopenblas from AUR, now the system Julia has:

julia> LinearAlgebra.versioninfo()
BLAS: libopenblas (OpenBLAS 0.3.10 NO_AFFINITY USE_OPENMP ZEN MAX_THREADS=12)
LAPACK: liblapack

julia> peakflops(10_000)
1.9276897177522015e11

It now saves me from the annoyance and enables me to focus on actual coding and real problems. However, I still suggest there being problems since I tried editing Make.user too and it didn’t work at all.

2

Did you ever check how many threads BLAS was using? It is possible that you were not fully utilizing your CPU on your first tests. For example, I get about 5.7e10 with only 1 thread, but like 2.4e11 with 6 threads.

See this discussion

1 Like
4

I checked, no problem there and they are normal. Seems it is a problem of OpenBLAS not recognizing the CPU and falling back to Pentium 4 settings. I would hope though this shouldn’t be solved by recompilation like what I did latter.

5

I am also having the same issue on a Ryzen 7 4700U.

6

I made an issue to track this: https://github.com/JuliaLang/julia/issues/36826

1 Like
7

To follow up, a patch was merged for LLVM to detect Renoir as znver2 which will be in 1.6.

For OpenBLAS, a patch was also merged, but in the meantime the architecture can be selected with an environment variable: OPENBLAS_CORETYPE=ZEN.

julia> LinearAlgebra.versioninfo()
BLAS: libopenblas (OpenBLAS 0.3.5  USE64BITINT DYNAMIC_ARCH NO_AFFINITY Zen MAX_THREADS=32)
LAPACK: libopenblas64_
1 Like