Acme: A Research Framework for Distributed Reinforcement Learning. - Matt Hoffman 001; Bobak Shahriari; John Aslanides; Gabriel Barth-Maron; Feryal M. P. Behbahani; Tamara Norman; Abbas Abdolmaleki; Albin Cassirer; Fan Yang; Kate Baumli; Sarah Henderson; Alexander Novikov 001; et al. (CoRR, 2020)

Automap: Towards Ergonomic Automated Parallelism for ML Models. - Michael Schaarschmidt; Dominik Grewe; Dimitrios Vytiniotis; Adam Paszke; Georg Stefan Schmid; Tamara Norman; James Molloy; Jonathan Godwin; Norman Alexander Rink; Vinod Nair; Dan Belov (CoRR, 2021)

Synthesizing Optimal Parallelism Placement and Reduction Strategies on Hierarchical Systems for Deep Learning. - Ningning Xie; Tamara Norman; Dominik Grewe; Dimitrios Vytiniotis (MLSys, 2022)

Automatic Discovery of Composite SPMD Partitioning Strategies in PartIR. - Sami Alabed; Dominik Grewe; Juliana Franco; Bart Chrzaszcz; Tom Natan; Tamara Norman; Norman A. Rink; Dimitrios Vytiniotis; Michael Schaarschmidt (CoRR, 2022)

PartIR: Composing SPMD Partitioning Strategies for Machine Learning. - Sami Alabed; Bart Chrzaszcz; Juliana Franco; Dominik Grewe; Dougal Maclaurin; James Molloy; Tom Natan; Tamara Norman; Xiaoyue Pan; Adam Paszke; Norman A. Rink; Michael Schaarschmidt; et al. (CoRR, 2024)

PartIR: Composing SPMD Partitioning Strategies for Machine Learning. - Sami Alabed; Daniel Belov; Bart Chrzaszcz; Juliana Franco; Dominik Grewe; Dougal Maclaurin; James Molloy; Tom Natan; Tamara Norman; Xiaoyue Pan; Adam Paszke; Norman A. Rink; et al. (ASPLOS (1), 2025)