TCCL: Co-optimizing Collective Communication and Traffic Routing for GPU-centric Clusters

Author:

Li Baojia1ORCID,Wang Xiaoliang2ORCID,Wang Jingzhu1ORCID,Liu Yifan2ORCID,Gong Yuanyuan1ORCID,Lu Hao1ORCID,Dang Weizhen1ORCID,Zhang Weifeng1ORCID,Huang Xiaojie1ORCID,Chen Mingzhuo1ORCID,Chen Jie1ORCID,He Chunzhi1ORCID,Liu Yadong1ORCID,Hu Xiaoyuan1ORCID,Liu Chen1ORCID,Ji Xuefeng1ORCID,Xia Yinben1ORCID,Li Xiang1ORCID,He Zekun1ORCID,Wang Yachen1ORCID,Zou Xianneng1ORCID

Affiliation:

1. Tencent

2. Nanjing University

Publisher

ACM

Reference12 articles.

1. 2017. NVIDIA Collective Communication Library (NCCL). https://developer.nvidia.com/nccl. (2017).

2. 2023. Collective Communications Library with various primitives for multi-machine training. https://github.com/facebookincubator/gloo. (Jan. 2023).

3. MSCCLang: Microsoft Collective Communication Language

4. ACCL: Architecting Highly Scalable Distributed Training Systems With Highly Efficient Collective Communication Library

5. Yixiao Gao, Qiang Li, Lingbo Tang, Yongqing Xi, Pengcheng Zhang, Wenwen Peng, Bo Li, Yaohui Wu, Shaozong Liu, Lei Yan, et al. 2021. When cloud storage meets RDMA. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI). 519--533.

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