Mac mini M4 pro vs AMD Ryzen 9 9950X for Linear Algebra?

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Here is an update for anyone who comes into this thread by chance. I ended up with the 9950X and built an Ubuntu PC with it. I am happy with it so far as a “personal server” staying behind SSH and wired to a switch. With a decent CPU cooler, it stays silent when staying idle and only makes some noise when running something like y-cruncher that pushes the CPU to the maximum load.

Some quick benchmark following the post here:

julia> versioninfo()
Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 32 × AMD Ryzen 9 9950X 16-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, generic)
Threads: 16 default, 0 interactive, 8 GC (on 32 virtual cores)
Environment:
  JULIA_NUM_THREADS = 16

julia> using LinearAlgebra

julia> N=449*10*2;

julia> A = rand(N,N); B = rand(N,N); C = similar(A);

julia> 2e-9N^3 / @elapsed mul!(C,A,B)
# First Run 1268.744956058828

julia> 2e-9N^3 / @elapsed mul!(C,A,B)
1736.538226330524

julia> 2e-9N^3 / @elapsed mul!(C,A,B)
1729.8860585152077

Ignoring the very first run affected by compile time, I got 1.7 TFLOPS, which is much better than the 0.35 TFLOPS I got on my current laptop.

Additional info for the PC build:

  • Default settings for CPU without tweaking anything in BIOS
  • Corsair DDR5 RAM 96GB running at 6000MHz via XMP profile and 1:1 ratio with controller
  • Ubuntu 24.10
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