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a99332eb25
This PR enhances offline tuning to support multi-GPUs. High-level description of algorithm: - Duplicate GEMMs are first eliminated - GEMMs are distributed to multi-GPUs for tuning - Results are gathered into a file with `_full` in the filename Also adding support for GemmAndBias and ScaledGemm Pull Request resolved: https://github.com/pytorch/pytorch/pull/139673 Approved by: https://github.com/jeffdaily, https://github.com/hongxiayang
36 lines
970 B
ReStructuredText
36 lines
970 B
ReStructuredText
.. currentmodule:: torch.cuda.tunable
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TunableOp
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=========
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.. note::
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This is a prototype feature, which means it is at an early stage
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for feedback and testing, and its components are subject to change.
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Overview
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--------
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.. automodule:: torch.cuda.tunable
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API Reference
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-------------
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.. autofunction:: enable
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.. autofunction:: is_enabled
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.. autofunction:: tuning_enable
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.. autofunction:: tuning_is_enabled
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.. autofunction:: record_untuned_enable
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.. autofunction:: record_untuned_is_enabled
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.. autofunction:: set_max_tuning_duration
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.. autofunction:: get_max_tuning_duration
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.. autofunction:: set_max_tuning_iterations
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.. autofunction:: get_max_tuning_iterations
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.. autofunction:: set_filename
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.. autofunction:: get_filename
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.. autofunction:: get_results
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.. autofunction:: get_validators
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.. autofunction:: write_file_on_exit
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.. autofunction:: write_file
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.. autofunction:: read_file
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.. autofunction:: tune_gemm_in_file
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.. autofunction:: mgpu_tune_gemm_in_file
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