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Recently, we open-sourced YaFSDP, Yandex’s tool for efficient distributed training of LLMs.
Recently, we open-sourced YaFSDP, Yandex’s tool for efficient distributed training of LLMs.
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Here are some of the key ideas used in YaFSDP to provide speedup and memory savings over FSDP:
Here are some of the key ideas used in YaFSDP to provide speedup and memory savings over FSDP:
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• Allocate and utilize just two buffers throughout the transformer for all collected weights to circumvent the torch memory allocator;
• Allocate and utilize just two buffers throughout the transformer for all collected weights to circumvent the torch memory allocator;
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• Gather small normalization layers at the beginning of the iteration and average the gradients only at the end;
• Gather small normalization layers at the beginning of the iteration and average the gradients only at the end;
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• Move gradient division to the very end of the backward pass.
• Move gradient division to the very end of the backward pass.
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To learn more about how YaFSDP works, check out our latest blog post: 
To learn more about how YaFSDP works, check out our latest blog post: 
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https://medium.com/yandex/yafsdp-a-tool-for-faster-llm-training-and-optimized-gpu-utilization-is-no-632b7539f5b3
https://medium.com/yandex/yafsdp-a-tool-for-faster-llm-training-and-optimized-gpu-utilization-is-no-632b7539f5b3
Recently, we open-sourced YaFSDP, Yandex’s tool for efficient distributed training of LLMs.

Here are some of the key ideas used in YaFSDP to provide speedup and memory savings over FSDP:
• Allocate and utilize just two buffers throughout the transformer for all collected weights to circumvent the torch memory allocator;
• Gather small normalization layers at the beginning of the iteration and average the gradients only at the end;
• Move gradient division to the very end of the backward pass.

To learn more about how YaFSDP works, check out our latest blog post: https://medium.com/yandex/yafsdp-a-tool-for-faster-llm-training-and-optimized-gpu-utilization-is-no-632b7539f5b3
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