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Need workaround to support multiprocess CUDA tensor sharing on Jetson Platforms #60401

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shmsong opened this issue Jun 21, 2021 · 1 comment
Open

Need workaround to support multiprocess CUDA tensor sharing on Jetson Platforms #60401

shmsong opened this issue Jun 21, 2021 · 1 comment
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feature A request for a proper, new feature. module: multiprocessing Related to torch.multiprocessing triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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@shmsong
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shmsong commented Jun 21, 2021

馃殌 Feature

A different method for sharing CUDA Tensors across processes on Jetson platforms is needed.

CUDA unified addressing based IPC functionality isn't yet supported on Tegra platforms

https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DEVICE.html#group__CUDART__DEVICE_1g8a37f7dfafaca652391d0758b3667539

and current implementation of THPStorage depends on it, making existing dataloader implementations not compatible on Jetson.

Motivation

Current data loader test cannot pass without the requested feature. Setting multiprocessing.sharing_strategy only affects CPU tensors and doesn't go around this problem.

$ python test_dataloader.py -v -k test_multiprocessing_contexts

gives

cuda runtime error (801) : operation not supported
@VitalyFedyunin VitalyFedyunin added feature A request for a proper, new feature. module: multiprocessing Related to torch.multiprocessing triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module labels Jun 24, 2021
@rahulswa08
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Is this issue resolved? Does any pytorch version support multiprocessing on Jetson platform?

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feature A request for a proper, new feature. module: multiprocessing Related to torch.multiprocessing triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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