Scheduling Task-parallel Applications in Dynamically Asymmetric Environments
Paper i proceeding, 2020

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.

Task scheduling

Interference awareness



Jing Chen

Chalmers, Data- och informationsteknik, Datorteknik

Pirah Noor Soomro

Chalmers, Data- och informationsteknik, Datorteknik

Mustafa Abduljabbar

Chalmers, Data- och informationsteknik, Datorteknik

Madhavan Manivannan

Chalmers, Data- och informationsteknik, Datorteknik

Miquel Pericas

Chalmers, Data- och informationsteknik, Datorteknik

ACM International Conference Proceeding Series

9781450388689 (ISBN)

49th International Conference on Parallel Processing, ICPP Workshops 2020
Virtual, Online, Canada,

Low-energy toolset for heterogeneous computing (LEGaTO)

Europeiska kommissionen (EU) (EC/H2020/780681), 2018-02-01 -- 2021-01-31.



Datavetenskap (datalogi)




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