Palirria: accurate on-line parallelism estimation for adaptive work-stealing
2015 (English)In: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634Article in journal (Refereed) Published
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.
multicore, parallel, scheduler, workload, runtime, task, adaptive, resource management, load balancing, work-stealing
Research subject Computer Science
IdentifiersURN: urn:nbn:se:kth:diva-175460DOI: 10.1002/cpe.3630ISI: 000369832200020ScopusID: 2-s2.0-84956796768OAI: oai:DiVA.org:kth-175460DiVA: diva2:861125
QC 201603072015-10-152015-10-152016-03-19Bibliographically approved