Response-Time Analysis for Non-Preemptive Periodic Moldable Gang Tasks

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3 Citaten (Scopus)
53 Downloads (Pure)

Samenvatting

Gang scheduling has long been adopted by the high-performance computing community as a way to reduce the synchronization overhead between related threads. It allows for several threads to execute in lock steps without suffering from long busy-wait periods or be penalized by large context-switch overheads. When combined with non-preemptive execution, gang scheduling significantly reduces the execution time of threads that work on the same data by decreasing the number of memory transactions required to load or store the data. In this work, we focus on two main types of gang tasks: rigid and moldable. A moldable gang task has a presumed known minimum and maximum number of cores on which it can be executed at runtime, while a rigid gang task always executes on the same number of cores. This work presents the first response-time analysis for non-preemptive moldable gang tasks. Our analysis is based on the notion of schedule abstraction; a new approach for response-time analysis with the promise of high accuracy. Our experiments on periodic rigid gang tasks show that our analysis is 4.9 times more successful in identifying schedulable tasks than the existing utilization-based test for rigid gang tasks.

Originele taal-2Engels
Titel34th Euromicro Conference on Real-Time Systems, ECRTS 2022
RedacteurenMartina Maggio
Plaats van productieDagstuhl
UitgeverijSchloss Dagstuhl - Leibniz-Zentrum für Informatik
Pagina's12:1-12:22
Aantal pagina's22
ISBN van elektronische versie978-3-95977-239-6
DOI's
StatusGepubliceerd - 28 jun. 2022
Evenement34th Euromicro Conference on Real-Time Systems, ECRTS 2022 - Modena, Italië
Duur: 5 jul. 20228 jul. 2022

Publicatie series

NaamLeibniz International Proceedings in Informatics, LIPIcs
Volume231
ISSN van geprinte versie1868-8969

Congres

Congres34th Euromicro Conference on Real-Time Systems, ECRTS 2022
Land/RegioItalië
StadModena
Periode5/07/228/07/22

Bibliografische nota

Funding Information:
Funding Joan Marcè i Igual: This work was made with the support of the NWO SAM-FMS project (project number 17931) as a part of the MASCOT program. Mitra Nasri: This work was made with the support of the EU ECSEL Joint Undertaking under grant agreement no 101007260 (project TRANSACT).

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