All-reduce Operations
All-Reduce Operations is a collective communication primitive in distributed memory programming that belongs to the class of reduction operations and is distinguished by its requirement to compute a global reduction (such as sum, max, or product) of data across all processing elements and then distribute the resulting value to every participant in the system.
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22
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2017–2026
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An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives
Benjamin Klenk, Nan Jiang, Greg Thorson et al. · 2020 · 64 citations
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce
Xupeng Miao, Xiaonan Nie, Yingxia Shao et al. · 2021 · 61 citations
How to scale distributed deep learning?
Peter Jin, Qiaochu Yuan, Forrest Iandola et al. · arXiv (Cornell University) · 2016 · 53 citations · Full text
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Peking University
Beijing, China
2 h-index
6 publications
342 citations

King Abdullah University of Science and Technology
Jeddah, Saudi Arabia
2 h-index
2 publications
111 citations
Tencent (China)
Shenzhen, China
1 h-index
1 publications
61 citations
University of California, Santa Barbara
Santa Barbara, United States
1 h-index
1 publications
40 citations
University of Vienna
Vienna, Austria
1 h-index
3 publications
36 citations
Yonsei University
Seoul, South Korea
1 h-index
1 publications
21 citations
Texas A&M University
College Station, United States
1 h-index
5 publications
200 citations

City University of Hong Kong
Hong Kong, Hong Kong
1 h-index
2 publications
74 citations
1–8 of 22
1 publications · 34 citations
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1 publications · 74 citations
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TOPC · 1 publications · 14 citations
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1 publications · 24 citations
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1 publications · 12 citations
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