Modeling universal globally adaptive load-balanced routing
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? In addition, what determines the performance of the UGAL-based scheme on a particular network configuration? In this work, 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 innerworking of UGAL and further our understanding of this type of routing.
ACM Transactions on Parallel Computing
Digital Object Identifier (DOI)
Mollah, M.A., Wang, W., Faizian, P., Rahman, M.S., Yuan, X., Pakin, S., Lang, M. (2019) Modeling universal globally adaptive load-balanced routing. ACM Transactions on Parallel Computing, 6(2), 9.