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Add sum reduction operator to TritonBench #2282

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Add sum reduction operator to TritonBench #2282

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Commits on Jun 6, 2024

  1. Add sum reduction operator to TritonBench (pytorch#2282) 

    Summary:

Add a Triton reduction kernel for the `sum` operator where `dim=None` to TritonBench, following the [TritonBench guide](https://fb.workplace.com/notes/953949486404240). This implementation works for all matrices being reduced to a scalar value.

To measure accuracy of Triton reduction kernel, add accuracy metric to sum kernel in TritonBench in order to test accuracy of Triton implementation against baseline PyTorch implementation, referencing [`torchbenchmark/operators/gemm/operator.py`](https://www.internalfb.com/code/fbsource/[767bb6faa353685b84f08a39f36fdcf6ca170c85]/fbcode/pytorch/benchmark/torchbenchmark/operators/gemm/operator.py?lines=236). Reset output registers per run of the Triton kernel for accurate Triton output.

To measure performance of the Triton reduction kernel against PyTorch, add gbps metric, referencing [`torchbenchmark/operators/vector_add/operator.py`](https://www.internalfb.com/code/fbsource/[858eda681c7618f9427ba55cef8d4aba712cb26e]/fbcode/pytorch/benchmark/torchbenchmark/operators/vector_add/operator.py?lines=19).

Referenced the existing [vector_add](https://www.internalfb.com/code/fbsource/fbcode/pytorch/benchmark/torchbenchmark/operators/vector_add/) and [grouped_gemm](https://www.internalfb.com/code/fbsource/fbcode/pytorch/benchmark/torchbenchmark/operators/grouped_gemm/) TritonBench operators as frameworks for implementation.

See the [TritonBench Operator Coverage Tracker](https://docs.google.com/spreadsheets/d/1091POOPSPsUnlNVEKaz2X_DQXdIwFv-fGOH_g9by-Zo/edit#gid=0) for current operator coverage in TritonBench.

Reviewed By: xuzhao9, davidberard98

Differential Revision: D58048782
    @jananisriram @facebook-github-bot
    jananisriram authored and facebook-github-bot committed Jun 6, 2024
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