{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:09Z","timestamp":1750220709993,"version":"3.41.0"},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T00:00:00Z","timestamp":1575417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMETRICS Perform. Eval. Rev."],"published-print":{"date-parts":[[2019,12,4]]},"abstract":"<jats:p>Nearly all modern data centers serve workloads which are capable of exploiting parallelism. When a job parallelizes across multiple servers it will complete more quickly, but jobs receive diminishing returns from being allocated additional servers. Because allocating multiple servers to a single job is inefficient, it is unclear how best to share a fixed number of servers between many parallelizable jobs. In this paper, we provide the first closed form expression for the optimal allocation of servers to jobs. Specifically, we specify the number of servers that should be allocated to each job at every moment in time. Our solution is a combination of favoring small jobs (as in SRPT scheduling) while still ensuring high system efficiency. We call our scheduling policy high-efficiency SRPT (heSRPT).<\/jats:p>","DOI":"10.1145\/3374888.3374896","type":"journal-article","created":{"date-parts":[[2019,12,5]],"date-time":"2019-12-05T14:07:24Z","timestamp":1575554844000},"page":"18-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["heSRPT"],"prefix":"10.1145","volume":"47","author":[{"given":"Benjamin","family":"Berg","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rein","family":"Vesilo","sequence":"additional","affiliation":[{"name":"Macquarie University, Macquarie Park, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mor","family":"Harchol-Balter","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,12,4]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"265","volume-title":"OSDI","volume":"16","author":"Abadi M.","year":"2016","unstructured":"M. Abadi , P. Barham , J. Chen , Z. Chen , A. Davis , J. Dean , M. Devin , S. Ghemawat , G. Irving , M. Isard , : a system for large-scale machine learning . In OSDI , volume 16 , pages 265 -- 283 , 2016 . M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard, et al. Tensorflow: a system for large-scale machine learning. In OSDI, volume 16, pages 265--283, 2016."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2935764.2935782"},{"key":"e_1_2_1_3_1","volume-title":"Towards optimality in parallel scheduling. ACM POMACS (SIGMETRICS), 1(2):40:1 -- 40:30","author":"Berg B.","year":"2018","unstructured":"B. Berg , J.P. Dorsman , and M. Harchol-Balter . Towards optimality in parallel scheduling. ACM POMACS (SIGMETRICS), 1(2):40:1 -- 40:30 , 2018 . B. Berg, J.P. Dorsman, and M. Harchol-Balter. Towards optimality in parallel scheduling. ACM POMACS (SIGMETRICS), 1(2):40:1 -- 40:30, 2018."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-3975(99)00186-3"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/1496770.1496845"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/MC.2008.209","article-title":"Amdahl's law in the multicore era","volume":"41","author":"Hill M. D.","year":"2008","unstructured":"M. D. Hill and M. R. Marty . Amdahl's law in the multicore era . Computer , 41 : 33 -- 38 , 2008 . M. D. Hill and M. R. Marty. Amdahl's law in the multicore era. Computer, 41:33--38, 2008.","journal-title":"Computer"},{"key":"e_1_2_1_7_1","volume-title":"Competitively scheduling tasks with intermediate parallelizability. ACM Transactions on Parallel Computing (TOPC), 3(1):4","author":"Im Sungjin","year":"2016","unstructured":"Sungjin Im , Benjamin Moseley , Kirk Pruhs , and Eric Torng . Competitively scheduling tasks with intermediate parallelizability. ACM Transactions on Parallel Computing (TOPC), 3(1):4 , 2016 . Sungjin Im, Benjamin Moseley, Kirk Pruhs, and Eric Torng. Competitively scheduling tasks with intermediate parallelizability. ACM Transactions on Parallel Computing (TOPC), 3(1):4, 2016."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MASCOTS.2018.00037"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3053277.3053279","article-title":"A multicore benchmark suite with network stacks and SPLASH-2X","volume":"44","author":"Zhan X.","year":"2017","unstructured":"X. Zhan , Y. Bao , C. Bienia , and K. Li. PARSEC3.0 : A multicore benchmark suite with network stacks and SPLASH-2X . ACM SIGARCH Computer Architecture News , 44 : 1 -- 16 , 2017 . X. Zhan, Y. Bao, C. Bienia, and K. Li. PARSEC3.0: A multicore benchmark suite with network stacks and SPLASH-2X. ACM SIGARCH Computer Architecture News, 44:1--16, 2017.","journal-title":"ACM SIGARCH Computer Architecture News"}],"container-title":["ACM SIGMETRICS Performance Evaluation Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3374888.3374896","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3374888.3374896","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:33:08Z","timestamp":1750199588000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3374888.3374896"}},"subtitle":["Optimal Scheduling of Parallel Jobs with Known Sizes"],"short-title":[],"issued":{"date-parts":[[2019,12,4]]},"references-count":9,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,12,4]]}},"alternative-id":["10.1145\/3374888.3374896"],"URL":"https:\/\/doi.org\/10.1145\/3374888.3374896","relation":{},"ISSN":["0163-5999"],"issn-type":[{"type":"print","value":"0163-5999"}],"subject":[],"published":{"date-parts":[[2019,12,4]]},"assertion":[{"value":"2019-12-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}