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PyTorch 分布式训练底层原理与 DDP 实战指南
深度学习模型参数量和训练数据集的爆炸式增长,以 Llama 3.1 为例:4050 亿参数、15.6 万亿 token 的训练量,如果仅靠单 GPU可能需要数百年才能跑完,或者根本无法加载模型。 并行计算(Parallelism)通过将训练任务分发到多个 GPU(单机多卡或多机多卡),并利用 ...
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