[Core][Distributed] use cpu/gloo to initialize pynccl #4248
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zhuohan123
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LGTM! Left some small comments.
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| current_device = torch.cuda.current_device() | ||
| try: | ||
| torch.cuda.set_device(device) | ||
| NCCL_CHECK( | ||
| _c_ncclCommInitRank(ctypes.byref(self.comm), self.world_size, | ||
| self.unique_id, self.rank)) | ||
| self.stream = torch.cuda.Stream() | ||
| finally: | ||
| torch.cuda.set_device(current_device) |
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Why do we need a try...finally block here? Can the program continue to run when there is an exception in the try block?
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It can, but I think it would be better for a function to be pure, i.e. don't implicitly modify some global state.
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nccl initialization requires broadcasting a unique id, which lives in cpu memory. previously, we only have one
ncclbackend process group, so we have to move the unique id to gpu, broadcast it, and then move it back to cpu.After #3904 , we always have a cpu/gloo backend, so we don't need to move the unique id around. We can just broadcast it in cpu memory.