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#4242 turned on "grid traversal factor" which is a good thing. However, it exposed a bug in how we limit that factor to prevent overrun in case the swizzled axis has fewer tiles than the factor. This led to a regression from 58% to 35% geomean perf compared to eager on H200.
This PR swaps the axes used to compute the number of swizzled tiles and takes us from a geomean of 35% to 65% on benchmarks/python/test_matmul.py on H200.
The change in the calculation of swizzled_tiles may have unintended consequences on performance or correctness. Ensure that this change does not introduce any edge cases or regressions.
The added memory check in the benchmark tests is a good practice to prevent OOM errors. Ensure that the threshold of 20GiB is appropriate and that no important test cases are being skipped unnecessarily.
if (m*k+n*k+m*n) *2>20* (2**30):
pytest.skip("Case takes more than 20GiB. Skipping to avoid OOM")
The added memory check in the benchmark tests is a good practice to prevent OOM errors. Ensure that the threshold of 20GiB is appropriate and that no important test cases are being skipped unnecessarily.
if (m*k+n*k+m*n) *2>20* (2**30):
pytest.skip("Case takes more than 20GiB. Skipping to avoid OOM")
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Limiting mem use to 20GB. This is conservative but we don't expect problem sizes bigger than this for DL at this time, and it prevents OOM on most devices.
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#4242 turned on "grid traversal factor" which is a good thing. However, it exposed a bug in how we limit that factor to prevent overrun in case the swizzled axis has fewer tiles than the factor. This led to a regression from 58% to 35% geomean perf compared to eager on H200.
This PR swaps the axes used to compute the number of swizzled tiles and takes us from a geomean of 35% to 65% on
benchmarks/python/test_matmul.pyon H200.