37 citations · 39 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Dynamic Control Flow in Large-Scale Machine Learning
Yuan Yu, Martín Abadi, Paul Barham +12
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcem…
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi, Ashish Agarwal, Paul Barham +37
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…
Falkirk Wheel: Rollback Recovery for Dataflow Systems
Michael Isard, Martín Abadi
We present a new model for rollback recovery in distributed dataflow systems. We explain existing rollback schemes by assigning a logical time to each event such as a message deliv…