Submitted by PresentGrapefruit451 t3_zcy55l in MachineLearning
Due to additional cache will there be significant improvement in timing to run medium scale ML training programs?
Comments
PresentGrapefruit451 OP t1_iyzemhl wrote
I thought so cause more l3 cache can keep more cpu instructions and for preprocessing and data loading stages fast cpu processing might be of help. Though not sure if the improvement will be significant.
ang_mo_uncle t1_iyznlge wrote
If anything, marginally. https://www.techpowerup.com/review/amd-ryzen-7-5800x3d/9.html
AnnualDegree99 t1_iyzpxid wrote
Wouldn't you be using a GPU to train your model, that would be probably hundreds of times faster?
PresentGrapefruit451 OP t1_iz0avfh wrote
Yes thats there, i am asking in regards to pre processing by CPU.
PresentGrapefruit451 OP t1_iz0awjz wrote
[deleted] t1_iz1bude wrote
PeterIanStaker t1_iz268nu wrote
If you're training neural networks, I'm not sure - I would wait for reviews of the 7950x3d (though in this case, you should almost always prefer a mid-tier GPU like a 3060ti)
If you're doing something like random forests or SVM, you're going to find yourself limited by SSD or even RAM speed loooooong before the difference between a 7950x3d and 7950x ever becomes relevant.
PresentGrapefruit451 OP t1_iz3a2h1 wrote
I am mainly looking for retraining models inception, yolo, etc. Using tenserflow and keras.
PeterIanStaker t1_iz3gh0k wrote
In that case don’t even worry about cpu, really you’d be fine with a 5600x equivalent. If the 7950x3d winds up being better value for money then fine, but otherwise your limiting factor will be your gpu, if not your data pipeline.
PresentGrapefruit451 OP t1_iz4acpz wrote
Thanks much Peter for the advise!
pommedeterresautee t1_iyza0g2 wrote
I know very little about CPUs, but wondering why do you think more cache would help?
Intuitively I would think it would be the case if training was for most of the time memory bandwidth limited but the issue with CPUs (vs GPUs) is that during training, model is computed bounded.