All-to-All Broadcast Algorithm in Galaxyfly Networks

Hongbin Zhuang, Jou-Ming Chang, Xiao-Yan Li (), Fangying Song and Qinying Lin
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Hongbin Zhuang: College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
Jou-Ming Chang: Institute of Information and Decision Sciences, National Taipei University of Business, Taipei 10051, Taiwan
Xiao-Yan Li: College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
Fangying Song: School of Mathematics and Statistics, Fuzhou University, Fuzhou 350108, China
Qinying Lin: College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China

Mathematics, 2023, vol. 11, issue 11, 1-14

Abstract: The design of interconnection networks is a fundamental aspect of high-performance computing (HPC) systems. Among the available topologies, the Galaxyfly network stands out as a low-diameter and flexible-radix network for HPC applications. Given the paramount importance of collective communication in HPC performance, in this paper, we present two different all-to-all broadcast algorithms for the Galaxyfly network, which adhere to the supernode-first rule and the router-first rule, respectively. Our performance evaluation validates their effectiveness and shows that the first algorithm has a higher degree of utilization of network channels, and that the second algorithm can significantly reduce the average time for routers to collect packets from the supernode.

Keywords: Galaxyfly network; all-to-all broadcast; interconnection network; algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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