PiP-MColl: Process-in-Process-based Multi-object MPI Collectives-Reference-Cited by-同舟云学术

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

Published:2023-10-31 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Cluster Computing (CLUSTER)
language:
Short-container-title:

Author:

Huang Jiajun¹,Ouyang Kaiming²,Zhai Yujia¹,Liu Jinyang¹,Si Min³,Raffenetti Ken⁴,Zhou Hui⁴,Hori Atsushi⁵,Chen Zizhong¹,Guo Yanfei⁴,Thakur Rajeev⁴

Affiliation:

1. University of California,Riverside

2. NVIDIA Corporation

3. Meta Platforms, Inc.

4. Argonne National Laboratory

5. National Institute of Informatics

Funder

U.S. Department of Energy

Office of Science

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10319881/10319941/10319969.pdf?arnumber=10319969

Reference24 articles.

1. Contention-Aware Kernel-Assisted MPI Collectives for Multi-/Many-Core Systems

2. Optimization of Collective Reduction Operations

3. Kernel Assisted Collective Intra-node MPI Communication among Multi-Core and Many-Core CPUs

4. Optimization of Collective Communication Operations in MPICH

5. Designing Efficient Shared Address Space Reduction Collectives for Multi-/Many-cores

Cited by 1 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. POSTER: Optimizing Collective Communications with Error-bounded Lossy Compression for GPU Clusters;Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming;2024-02-20

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