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[ROCm] Tunableop record untuned #128813

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@jfactory07 jfactory07 commented Jun 17, 2024

When enable tunableop, It is easy to have OOM since APP usually needs large video memory size, such as running a LLM for inference. So we need a offline mode to tune the GEMMs. This PR provide an offline mode for tunableOp:

  • record untuned GEMMs to file.

  • a python API named tune_gemm_in_file is added to read the untuned file and tune the GEMMs in file

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang

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pytorch-bot bot commented Jun 17, 2024

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/128813

Note: Links to docs will display an error until the docs builds have been completed.

✅ No Failures

As of commit 1892821 with merge base b40a033 (image):
💚 Looks good so far! There are no failures yet. 💚

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@pytorch-bot pytorch-bot bot added the module: rocm AMD GPU support for Pytorch label Jun 17, 2024
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@jfactory07 jfactory07 marked this pull request as ready for review June 17, 2024 06:39
@jfactory07 jfactory07 requested a review from eqy as a code owner June 17, 2024 06:39
@mikaylagawarecki mikaylagawarecki added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Jun 17, 2024
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