Sumanth Hegde
@sumanthrh
Post-training @anyscalecompute. Prev - @UCSanDiego, @C3_AI, @iitmadras. Machine Learning and Systems. Intensity is all you need.
加入 February 2016
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And now for the second problem - scaling to large models. Here, we applied some tried and tested ideas:
1. PP-local and EP-local gather: Avoid redundant gather across PP groups, avoid gathering EP layers to avoid OOMs
2. Pipelined execution: Pipeline all-gather on the trainer, the weight transfer and the post-process on the inference side
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