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Initial Formulation of Why Disallowing Same Program Co-schedules Improves Performance
Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för data-, elektro- och lantmäteriteknik.ORCID-id: 0000-0001-7232-0079
Högskolan Väst, Institutionen för ingenjörsvetenskap, Avdelningen för data-, elektro- och lantmäteriteknik.ORCID-id: 0000-0003-0589-8086
2017 (engelsk)Inngår i: Co-Scheduling of HPC Applications / [ed] Carsten Trinitis, Josef Weidendorfer, Netherlands: IOS Press, 2017, 1, s. 95-113Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Co-scheduling processes on different cores in the same server might leadto excessive slowdowns if they use the same shared resource, like a memory bus. Ifpossible, processes with a high shared resource use should be allocated to differentserver nodes to avoid contention, thus avoiding slowdown. This article proposesthe more general principle that twins, i.e. several instances of the same program,should be allocated to different server nodes. The rational for this is that instancesof the same program use the same resources and they are more likely to be eitherlow or high resource users. High resource users should obviously not be combined,but a bit non-intuitively, it is also shown that low resource users should also notbe combined in order to not miss out on better scheduling opportunities. This isverified using both a probabilistic argument as well as experimentally using tenprograms from the NAS parallel benchmark suite running on two different systems.By using the simple rule of forbidding these terrible twins, the average slowdownis shown to decrease from 6.6% down to 5.9% for System A and from 9.5% to8.3% for System B. Furthermore, the worst case slowdown is lowered from 12.7%to 9.0% and 19.5% to 13% for systems A and B, respectively. Thus, indicating aconsiderable improvement despite the rule being program agnostic and having noinformation about any program’s resource usage or slowdown behavior.

sted, utgiver, år, opplag, sider
Netherlands: IOS Press, 2017, 1. s. 95-113
Serie
Advances in parallel Computing, ISSN 0927-5452, E-ISSN 1879-808X ; 28
Emneord [en]
Co-scheduling; Scheduling; Allocation; Multicore; Slowdown; Cluster; Cloud
HSV kategori
Forskningsprogram
TEKNIK, Datateknik
Identifikatorer
URN: urn:nbn:se:hv:diva-10619DOI: 10.3233/978-1-61499-730-6-95ISBN: 978-1-61499-729-0 (tryckt)ISBN: 978-1-61499-730-6 (digital)OAI: oai:DiVA.org:hv-10619DiVA, id: diva2:1066740
Tilgjengelig fra: 2017-01-19 Laget: 2017-01-19 Sist oppdatert: 2019-01-04bibliografisk kontrollert

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