[core][distributed] fix ray worker rank assignment #6235
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andoorve
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Jul 9, 2024
| # the machine boundaries. We need to make sure that workers in the | ||
| # same node are assigned consecutive ranks. | ||
| # examples: | ||
| # [('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [0]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [0]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [1]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [2]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [3]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [1]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [2]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [3])] # noqa |
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Are we guaranteed that the GPU IDs for a given node will be in strictly increasing order?
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I don't think so. this is not needed, either. the CUDA_VISIBLE_DEVICES is ",".join(map(str, node_gpus[node_id])), and local rank is node_workers[node_id].index(rank), as long as these two are consistent, it should be fine.
node_gpus[node_id]: list of gpu ids for each worker in this node
node_workers[node_id]: list of worker ranks for each worker in this node
andoorve
approved these changes
Jul 9, 2024
andoorve
reviewed
Jul 9, 2024
| # [('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [0]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [0]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [1]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [2]), ('dfaad7adfdae57a694cc74490db45bd112c9f31243523e43ddc2e7f0', [3]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [1]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [2]), ('852a09a13c7503ef126d7c828454c741494b1be33a8627a5206604d9', [3])] # noqa | ||
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| # initialize worker ranks with -1 (unassigned) | ||
| worker_ranks = [-1 for x in worker_node_and_gpu_ids] |
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You can do this simply by using python sort/sorted, but this can be very unreadable.
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I wish ray can sort by node & GPU id for me :( but it cannot
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Signed-off-by: Alvant <alvasian@yandex.ru>
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looks like ray does not guarantee the ranks align with machine boundary. when this happens, tensor parallel will happen across machines, which will bring terrible performance.