Cody Blakeney Notes Value of PyTorch Matmul Precision Setting
Arcee AI researcher shared experience with a specific torch configuration on social media.
TLDR
Cody Blakeney leads research at Arcee AI after serving as data research lead at MosaicML on models including DBRX and MPT plus a visiting researcher role at Meta. In a post he stated that the advice to consider setting torch.set_float32_matmul_precision to high proved worth following because it delivered better performance. Blakeney holds a PhD in computer science. The remark draws on his direct work with the configuration during model development and training. No further details on the scale of gains or exact workloads appear in the post itself.
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