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Fix bug of multi-GPU train nn.Graph extra mem cost in rank 0 #5930
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chengtbf
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liujuncheng,
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August 17, 2021 15:16
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liujuncheng
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Aug 18, 2021
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August 18, 2021 02:54
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修复 多卡(多进程)训练 nn.Graph 时,rank 0 上会多占用很多显存的 BUG。
BUG 的原因是我们在 cudaMallocHost 的时候没有指定 device id,那么每个进程都会默认指定 device 0,此时虽然申请的是 host pinned memory,但是也会在相应的进程上创建 device 0 的 CUDA context。 CUDA context 是进程内概念,各个 rank 之间不共享, 每个 context 至少占用 300MiB - 500MiB 的显存。
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