ME News reports that on April 8 (UTC+8), the PyTorch team recently evaluated and improved the performance of LayerNorm and RMSNorm, two fundamental normalization methods, when used with torch.compile on NVIDIA H100 and B200 GPUs. The goal was to achieve near state-of-the-art performance at the individual kernel level while enabling automatic fusion. The official announcement includes a link to more detailed information. (Source: InFoQ)
PyTorch optimizes LayerNorm and RMSNorm performance on H100 and B200 GPUs
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Summary
PyTorch announced a project optimizing LayerNorm and RMSNorm performance on NVIDIA H100 and B200 GPUs. Using torch.compile, the team enhanced per-kernel efficiency and enabled automatic fusion. This update is part of ongoing developments from the deep learning community. More details are available on the official blog.
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