Yandex 开源 yaFSDP：多 GPU 训练 LLM 提速 26%
Yandex 开源的 yaFSDP 直接对比 PyTorch FSDP：256 张 A100 训练 Llama 3 70B 快了约 26%。原理是把通信和计算重叠起来，减少 GPU 空转。自己搭训练集群、跑大参数模型的团队可以直接试试。
Yandex 开源了一个用于多 GPU 大模型训练的工具 yaFSDP。在其公布的示例中，用 256 张 A100 GPU 训练 Llama 3 70B，比 PyTorch FSDP 配置节省约 26% 的训练时间。
该工具的核心优化在于内存复用与通信重叠：它在 GPU 执行其他计算的同时传输模型数据，减少通信等待造成的空闲，从而提升整体训练吞吐。
对于需要自建训练集群的团队来说，这是一个可以在不增加硬件投入的情况下缩短训练周期的选项，尤其适合大规模参数模型的预训练或微调场景。
This is an open-source tool for training large language models across multiple GPUs.
It's pretty efficient:
It reuses memory and transfers model data while your GPUs run other calculations, making training much faster.
Yandex published an example where training Llama 3 70B on 256 A100 GPUs took about 26% less time than with a PyTorch FSDP setup.
This report is categorized under AITOP's "Products" desk. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include yaFSDP, Yandex, Llama 3, PyTorch.
Source attribution: curated from Ate-a-Pi (@svpino).
