activity
20142026
most citedPathways: Asynchronous Distributed Dataflow for ML

37 citations · 109 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

Compressed Recurrent Feedback in Tsetlin Machines: A Reproducible Boolean-FSM Study

Ankit Kumar, Utkarsh Raj, Rishad Shafik +1

Sequential inference on small devices requires a model to retain useful history without repeatedly processing a long input record. A Recurrent Tsetlin Machine (RTM) provides this m…

cs.LG2022★ 8 cited

Neural Architecture Search using Property Guided Synthesis

Charles Jin, Phitchaya Mangpo Phothilimthana, Sudip Roy

In the past few years, neural architecture search (NAS) has become an increasingly important tool within the deep learning community. Despite the many recent successes of NAS, howe…

cs.DC2022★ 37 cited

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…

cs.LG2021★ 3 cited

A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules

Xinfeng Xie, Prakash Prabhu, Ulysse Beaugnon +6

Multi-Chip-Modules (MCMs) reduce the design and fabrication cost of machine learning (ML) accelerators while delivering performance and energy efficiency on par with a monolithic l…

cs.AI2021★ 32 cited

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…

cs.LG2020

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…

cs.LG2019★ 25 cited

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…

cs.DB2014★ 4 cited

The Homeostasis Protocol: Avoiding Transaction Coordination Through Program Analysis

Sudip Roy, Lucja Kot, Gabriel Bender +5

Datastores today rely on distribution and replication to achieve improved performance and fault-tolerance. But correctness of many applications depends on strong consistency proper…