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PyTorch 2.15 tackles the 'one bad GPU' problem
ML admins will be happy to learn that one bad GPU may no longer mean starting an entire training job from scratch.
Summary
ML admins will be happy to learn that one bad GPU may no longer mean starting an entire training job from scratch. The latest 2.15 release of PyTorch includes a rewritten backend for Nvidia's Collective Communications Library (NCCL), designed to improve fault diagnosis and recovery when GPUs work together. This latest feature shows how its creators continue to advance the software from being a tool for researchers to being a cornerstone in production AI work.
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