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Palirria: accurate on-line parallelism estimation for adaptive work-stealing
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. (Multicore Center)ORCID iD: 0000-0002-7860-6593
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. SICS Swedish Institute of Computer Science, Sweden. (Multicore Center)ORCID iD: 0000-0002-9637-2065
2015 (English)In: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634Article in journal (Refereed) Published
Abstract [en]

We present Palirria, a self-adapting work-stealing scheduling method for nested fork/join parallelism that can be used to estimate the number of utilizable workers and self-adapt accordingly. The estimation mechanism is optimized for accuracy, minimizing the requested resources without degrading performance. We implemented Palirria for both the Linux and Barrelfish operating systems and evaluated it on two platforms: a 48-core Non-Uniform Memory Access (NUMA) multiprocessor and a simulated 32-core system. Compared with state-of-the-art, we observed higher accuracy in estimating resource requirements. This leads to improved resource utilization and performance on par or better to executing with fixed resource allotments.

Place, publisher, year, edition, pages
John Wiley & Sons, 2015.
Keyword [en]
multicore, parallel, scheduler, workload, runtime, task, adaptive, resource management, load balancing, work-stealing
National Category
Computer Systems
Research subject
Computer Science
URN: urn:nbn:se:kth:diva-175460DOI: 10.1002/cpe.3630ISI: 000369832200020ScopusID: 2-s2.0-84956796768OAI: diva2:861125

QC 20160307

Available from: 2015-10-15 Created: 2015-10-15 Last updated: 2016-03-19Bibliographically approved

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Varisteas, GeorgiosBrorsson, Mats
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