POSTER: Optimizing Collective Communications with Error-bounded Lossy Compression for GPU Clusters-Reference-Cited by-同舟云学术

POSTER: Optimizing Collective Communications with Error-bounded Lossy Compression for GPU Clusters

Published:2024-02-20 Issue: Volume: Page:454-456
ISSN:
Container-title:Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
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Author:

Huang Jiajun¹^ORCID,Di Sheng²^ORCID,Yu Xiaodong³^ORCID,Zhai Yujia⁴^ORCID,Liu Jinyang¹^ORCID,Huang Yafan⁵^ORCID,Raffenetti Ken⁶^ORCID,Zhou Hui⁶^ORCID,Zhao Kai⁷^ORCID,Chen Zizhong¹^ORCID,Cappello Franck²^ORCID,Guo Yanfei⁶^ORCID,Thakur Rajeev²^ORCID

Affiliation:

1. University of California, Riverside, Riverside, USA

2. Argonne National Laboratory, Lemont, United States of America

3. Stevens Institute of Technology, Hoboken, United States of America

4. University of California, Riverside, Riverside, United States of America

5. The University of Iowa, Iowa City, United States of America

6. Argonne National Laboratory, Lemont, USA

7. Florida State University, Tallahassee, USA

Funder

NSF (National Science Foundation)

DOE U.S. Department of Energy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627535.3638467

Reference13 articles.

1. Optimization of MPI collective communication on BlueGene/L systems

2. Fast Error-Bounded Lossy HPC Data Compression with SZ

3. Jiajun Huang Sheng Di Xiaodong Yu Yujia Zhai Zhaorui Zhang Jinyang Liu Xiaoyi Lu Ken Raffenetti Hui Zhou Kai Zhao Zizhong Chen Franck Cappello Yanfei Guo and Rajeev Thakur. 2023. An Optimized Error-controlled MPI Collective Framework Integrated with Lossy Compression. arXiv:2304.03890 [cs.DC]

4. Accelerating MPI Collectives with Process-in-Process-based Multi-object Techniques

5. PiP-MColl: Process-in-Process-based Multi-object MPI Collectives