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Add new model: simple_gpt_tp_manual #1969

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@xmfan xmfan commented Oct 7, 2023

Similar to simple_gpt, but instead of using the DTensor API to apply Tensor Parallelism (TP), we use the manual weights sharding implementation and directly functional collectives. 2 main reasons it is beneficial to add this:

  1. DTensor + compile is not ready yet
  2. DTensor has a CPU overhead, and adding this less overhead model will help us track the improvement/regression

Tests:

in benchmark/
python test.py -k "test_simple_gpt_manual_tp_"

in pytorch/
PYTHONPATH=benchmark/ python pytorch/benchmarks/dynamo/torchbench.py --float16 -dcuda --inference --backend=inductor --multiprocess --performance --only simple_gpt_tp_manual

@xmfan xmfan force-pushed the xmfan/simple_gpt_manual_tp branch from 5b068d7 to 320111e Compare October 7, 2023 01:01
@xmfan xmfan temporarily deployed to docker-s3-upload October 7, 2023 01:02 — with GitHub Actions Inactive
@xmfan xmfan temporarily deployed to docker-s3-upload October 7, 2023 01:02 — with GitHub Actions Inactive
@xmfan xmfan temporarily deployed to docker-s3-upload October 9, 2023 22:15 — with GitHub Actions Inactive
@xmfan xmfan temporarily deployed to docker-s3-upload October 9, 2023 22:15 — with GitHub Actions Inactive
@xmfan xmfan marked this pull request as ready for review October 9, 2023 22:41
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@xmfan has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

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@xmfan merged this pull request in cdd87f0.

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3 participants