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cs.LG2025
TOAST: Fast and scalable auto-partitioning based on principled static analysis
Sami Alabed, Dominik Grewe, Norman Alexander Rink +5
Partitioning large machine learning models across distributed accelerator systems is a complex process, requiring a series of interdependent decisions that are further complicated…
cs.LG2024
PartIR: Composing SPMD Partitioning Strategies for Machine Learning
Sami Alabed, Daniel Belov, Bart Chrzaszcz +14
Training of modern large neural networks (NN) requires a combination of parallelization strategies encompassing data, model, or optimizer sharding. When strategies increase in comp…