PipeDream

Author:

Narayanan Deepak1,Harlap Aaron2,Phanishayee Amar3,Seshadri Vivek3,Devanur Nikhil R.3,Ganger Gregory R.4,Gibbons Phillip B.4,Zaharia Matei5

Affiliation:

1. Microsoft Research and Stanford University

2. Microsoft Research and Carnegie Mellon University

3. Microsoft Research

4. Carnegie Mellon University

5. Stanford University

Publisher

ACM

Reference57 articles.

1. 2019. Gloo. https://github.com/facebookincubator/gloo. 2019. Gloo. https://github.com/facebookincubator/gloo.

2. 2019. MLPerf. https://www.mlperf.org/. 2019. MLPerf. https://www.mlperf.org/.

3. 2019. NCCL. https://developer.nvidia.com/nccl. 2019. NCCL. https://developer.nvidia.com/nccl.

4. 2019. NVLink. https://www.nvidia.com/en-us/data-center/nvlink/. 2019. NVLink. https://www.nvidia.com/en-us/data-center/nvlink/.

5. 2019. PyTorch. https://github.com/pytorch/pytorch. 2019. PyTorch. https://github.com/pytorch/pytorch.

Cited by 306 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. APapo: An asynchronous parallel optimization method for DNN models;Future Generation Computer Systems;2024-03

2. Fedcs: Efficient communication scheduling in decentralized federated learning;Information Fusion;2024-02

3. Adaptive partitioning and efficient scheduling for distributed DNN training in heterogeneous IoT environment;Computer Communications;2024-02

4. AshPipe: Asynchronous Hybrid Pipeline Parallel for DNN Training;Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region;2024-01-18

5. Security of NVMe Offloaded Data in Large-Scale Machine Learning;Computer Security – ESORICS 2023;2024

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