GSPMD automatically infers tensor partitioning from limited user annotations to parallelize single-device ML programs across thousands of TPUs, reporting 50-62% utilization for up to trillion-parameter models.
Train ML models on large images and 3D volumes with spatial partitioning on Cloud TPUs
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GSPMD: General and Scalable Parallelization for ML Computation Graphs
GSPMD automatically infers tensor partitioning from limited user annotations to parallelize single-device ML programs across thousands of TPUs, reporting 50-62% utilization for up to trillion-parameter models.