Scheduling Task-parallel Applications in Dynamically Asymmetric Environments release_xspjxhx6hrhajkzxpvypa6kmyu

by Jing Chen, Pirah Noor Soomro, Mustafa Abduljabbar, Madhavan Manivannan, Miquel Pericas

Released as a article .

2020  

Abstract

Shared resource interference is observed by applications as dynamic performance asymmetry. Prior art has developed approaches to reduce the impact of performance asymmetry mainly at the operating system and architectural levels. In this work, we study how application-level scheduling techniques can leverage moldability (i.e. flexibility to work as either single-threaded or multithreaded task) and explicit knowledge on task criticality to handle scenarios in which system performance is not only unknown but also changing over time. Our proposed task scheduler dynamically learns the performance characteristics of the underlying platform and uses this knowledge to devise better schedules aware of dynamic performance asymmetry, hence reducing the impact of interference. Our evaluation shows that both criticality-aware scheduling and parallelism tuning are effective schemes to address interference in both shared and distributed memory applications
In text/plain format

Archived Files and Locations

application/pdf  868.8 kB
file_p3dcz2hktbgrvd3g62zvy4tcom
arxiv.org (repository)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article
Stage   submitted
Date   2020-09-22
Version   v2
Language   en ?
arXiv  2009.00915v2
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 28ee80ba-0700-409d-a575-8f9c8abda072
API URL: JSON