algorithmic-efficiency
algorithmic-efficiency copied to clipboard
MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
Results
62
algorithmic-efficiency issues
Sort by
recently updated
recently updated
newest added
The submission_runner_test.py test appears that is not currently included in the CI test suite.
🧪 Test
Some workloads e.g. Criteo1TB spent 75% of the total runtime time on evaluations. We should re-analyze and potentially reconfigure the intervals.