A Scalable Approach for Partially Local Federated Learning
General and Scalable Parallelization for Neural Networks
Massively Parallel Graph Computation: From Theory to Practice
Massively Large-Scale Distributed Reinforcement Learning with Menger
Yet More Google Compute Cluster Trace Data
Balanced Partitioning and Hierarchical Clustering at Scale
Introducing the TensorFlow Research Cloud
Google at USENIX Symposium on Operating Systems Design and Implementation (OSDI ‘10)
