1k citations · 1.3k across the 6 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024★ 4 cited
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…
cs.LG2021★ 5 cited
Automap: Towards Ergonomic Automated Parallelism for ML Models
Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis +8
The rapid rise in demand for training large neural network architectures has brought into focus the need for partitioning strategies, for example by using data, model, or pipeline…