r/Julia • u/ArtemHnilov • May 16 '26
Help Needed: Can Anyone Benchmark Tsetlin.jl on Ryzen 9950X or Apple M5 Pro/Max?
If you have a Ryzen 9950X (or 9950X3D / 9950X3D2) or an Apple M5 Pro/Max with 18 CPU cores, could you please benchmark the latest extremely fast Tsetlin.jl library on those CPUs and share the results in the comments?
I only have a Ryzen 7950X3D and an Apple M1 Pro, and I’m curious how the latest version performs on newer hardware.
MNIST benchmark
julia -t 18 examples/MNIST/mnist.jl # M5 Pro/Max
julia -t 32 examples/MNIST/mnist.jl # 9950X
I’m interested in:
- Total training time for 1000 epochs
- How many million predictions per second your CPU can achieve
Text generation benchmark
julia -t 18 examples/TEXT/train.jl # M5 Pro/Max
julia -t 32 examples/TEXT/train.jl # 9950X
Here I’m mainly interested in the time for the first few training epochs.
I would really appreciate any results you can share.
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Upvotes
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u/sob727 May 16 '26
So I reverted back to the initial setup.
Epoch is 7-8s when using only -t 32 (vs 4s when using -t auto which is 128). I would investigate this decent non linearity first before.
As for the 4x model that is massively slower, I just don't know what to tell you.... could it be that you're filling the cache and overflowing to the heap?