37 citations · 94 across the 3 of their papers we have counts for
4 papers
Pathways: Asynchronous Distributed Dataflow for ML
Paul Barham, Aakanksha Chowdhery, Jeff Dean +13
We present the design of a new large scale orchestration layer for accelerators. Our system, Pathways, is explicitly designed to enable exploration of new systems and ML research i…
Equality Saturation for Tensor Graph Superoptimization
Yichen Yang, Phitchaya Mangpo Phothilimtha, Yisu Remy Wang +3
One of the major optimizations employed in deep learning frameworks is graph rewriting. Production frameworks rely on heuristics to decide if rewrite rules should be applied and in…
Transferable Graph Optimizers for ML Compilers
Yanqi Zhou, Sudip Roy, Amirali Abdolrashidi +9
Most compilers for machine learning (ML) frameworks need to solve many correlated optimization problems to generate efficient machine code. Current ML compilers rely on heuristics…
GDP: Generalized Device Placement for Dataflow Graphs
Yanqi Zhou, Sudip Roy, Amirali Abdolrashidi +8
Runtime and scalability of large neural networks can be significantly affected by the placement of operations in their dataflow graphs on suitable devices. With increasingly comple…