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by augment_me
28 days ago
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As someone who works in the field, the blog is nice but it has a lot of CODEX fingerprints on it, and it's also very specific to the size of the model in question in a way that is not explicit from the blog until the very last section. In general, for some reason CODEX loves CUDA-streams, it's the first optimization it goes for every time when writing GPU kernels. However in many cases this is not a bottleneck, it happens to be so here because the model in the blog is small (2.4ms FW-pass is tiny, and 9B params sit on a single GPU). Large models are closer to 30-40ms. The CPU-GPU sync is 1-2ms, when working on larger MoE models the scheduling of tokens in this way is much less important than for example scheduling of computation/communication or kernel optimization. I wish the blog would state this at the start with the premise of what has been done, or show that this is indeed the bottleneck with some benchmarking. Otherwise is kind of overselling things imo. |
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If you scroll down to the section titled "A cost model for the bubble", you will find both benchmark results and us saying, "you get back anywhere from a few percent to a third; more the faster your accelerator/model is".