{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:33Z","timestamp":1750220853789,"version":"3.41.0"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2019,6,30]],"date-time":"2019-06-30T00:00:00Z","timestamp":1561852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Advanced Simulation and Computing"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Parallel Comput."],"published-print":{"date-parts":[[2019,6,30]]},"abstract":"<jats:p>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 inner working of UGAL and further our understanding of this type of routing.<\/jats:p>","DOI":"10.1145\/3349620","type":"journal-article","created":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T12:47:00Z","timestamp":1567514820000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Modeling Universal Globally Adaptive Load-Balanced Routing"],"prefix":"10.1145","volume":"6","author":[{"given":"Md Atiqul","family":"Mollah","sequence":"first","affiliation":[{"name":"Oakland University, Rochester, Michigan"}]},{"given":"Wenqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Florida State University, Tallahassee, Florida"}]},{"given":"Peyman","family":"Faizian","sequence":"additional","affiliation":[{"name":"University of North Florida, Jacksonville, Florida"}]},{"given":"MD Shafayat","family":"Rahman","sequence":"additional","affiliation":[{"name":"Florida State University, Tallahassee, Florida"}]},{"given":"Xin","family":"Yuan","sequence":"additional","affiliation":[{"name":"Florida State University, Tallahassee, Florida"}]},{"given":"Scott","family":"Pakin","sequence":"additional","affiliation":[{"name":"Los Alamos National Laboratory, Los Alamos, New Mexico"}]},{"given":"Michael","family":"Lang","sequence":"additional","affiliation":[{"name":"Los Alamos National Laboratory, Los Alamos, New Mexico"}]}],"member":"320","published-online":{"date-parts":[[2019,8,30]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.5555\/2388996.2389136"},{"doi-asserted-by":"publisher","key":"e_1_2_1_2_1","DOI":"10.1109\/SC.2014.34"},{"unstructured":"Arjun Singh. 2005. Load-Balanced Routing in Interconnection Networks. Ph.D. Dissertation. Stanford University.  Arjun Singh. 2005. Load-Balanced Routing in Interconnection Networks. Ph.D. Dissertation. 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