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Improving all-reduce collective operations for imbalanced process arrival patterns

Abstract

Two new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example for machine learning are provided. The results of the experiments were described and analyzed, showing that the proposed solution has high scalability and improved performance in comparison with the usually used ring and Rabenseifner algorithms.

Citations

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Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
JOURNAL OF SUPERCOMPUTING no. 74, pages 3071 - 3092,
ISSN: 0920-8542
Language:
English
Publication year:
2018
Bibliographic description:
Proficz J.: Improving all-reduce collective operations for imbalanced process arrival patterns// JOURNAL OF SUPERCOMPUTING. -Vol. 74, iss. 7 (2018), s.3071-3092
DOI:
Digital Object Identifier (open in new tab) 10.1007/s11227-018-2356-z
Bibliography: test
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Verified by:
Gdańsk University of Technology

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