Modeling Universal Globally Adaptive Load-Balanced Routing

Mollah, Md Atiqul; Wang, Wenqi; Faizian, Peyman; Rahman, MD Shafayat; Yuan, Xin; Pakin, Scott; Lang, Michael

doi:10.1145/3349620

Title: Modeling Universal Globally Adaptive Load-Balanced Routing

Journal Article · Tue Sep 10 00:00:00 EDT 2019 · ACM Transactions on Parallel Computing

DOI:https://doi.org/10.1145/3349620· OSTI ID:1565855

Mollah, Md Atiqul ^[1]; Wang, Wenqi ^[2]; Faizian, Peyman ^[3]; Rahman, MD Shafayat ^[2]; Yuan, Xin ^[2];

^[4];

^[4]

Oakland Univ., Rochester, MI (United States)
Florida State Univ., Tallahassee, FL (United States)
Univ. of North Florida, Jacksonville, FL (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Universal globally adaptive load-balanced (UGAL) routing has been proposed for various interconnection networks and has been deployed in a number of current-generation supercomputers. Although UGAL-based schemes have been extensively studied, most existing results are based on either simulation or measurement. Without a theoretical understanding of UGAL, multiple questions remain: For which traffic patterns is UGAL most suited? Furthermore, what determines the performance of the UGAL-based scheme on a particular network configuration? Here, we develop a set of throughput models for UGALbased on linear programming. We show that the throughput models are valid across the torus, Dragonfly, and Slim Fly network topologies. Finally, we identify a robust model that can accurately and efficiently predict UGAL throughput for a set of representative traffic patterns across different topologies. Our models not only provide a mechanism to predict UGAL performance on large-scale interconnection networks but also reveal the inner working of UGAL and further our understanding of this type of routing.

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Research Organization:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Office of Defense Programs (DP)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1565855

Report Number(s):: LA-UR-18-28331

Journal Information:: ACM Transactions on Parallel Computing, Vol. 6, Issue 2; ISSN 2329-4949

Publisher:: Association for Computing MachineryCopyright Statement

Country of Publication:: United States

Language:: English

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