distributed training

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication ICLR 2022 Quantized Training of Gradient Boosting Decision Trees NeurIPS 2022 ResIST: Layer-wise decomposition of ResNets for distributed training UAI 2022 SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training NeurIPS 2022 Secure Distributed Training at Scale ICML 2022 Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NeurIPS 2022 Shifted compression framework: generalizations and improvements UAI 2022 solo-learn: A Library of Self-supervised Methods for Visual Representation Learning JMLR 2022 Survey on Efficient Training of Large Neural Networks IJCAI 2022 TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training NeurIPS 2022 Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations ICLR 2022 Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization OSDI 2022 Unlocking the Power of Inline Floating-Point Operations on Programmable Switches NSDI 2022 VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement NeurIPS 2022 WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU JMLR 2022 1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021 Accelerating Gossip SGD with Periodic Global Averaging ICML 2021 Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees AAAI 2021 Communication Efficient SGD via Gradient Sampling With Bayes Prior CVPR 2021 Constrained Robust Submodular Partitioning NeurIPS 2021 Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data ICML 2021 Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads OSDI 2021 EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback NeurIPS 2021 Error Compensated Distributed SGD Can Be Accelerated NeurIPS 2021 Fast Training Method for Stochastic Compositional Optimization Problems NeurIPS 2021