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Coordinated managem...
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Nejat, Mehrzad,1989Chalmers tekniska högskola,Chalmers University of Technology
(author)
Coordinated management of DVFS and cache partitioning under QoS constraints to save energy in multi-core systems
- Article/chapterEnglish2020
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Elsevier BV,2020
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LIBRIS-ID:oai:research.chalmers.se:4c8f27e4-2e85-455c-a808-baf7742a2ded
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https://research.chalmers.se/publication/517599URI
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https://doi.org/10.1016/j.jpdc.2020.05.006DOI
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Language:English
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Summary in:English
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Subject category:art swepub-publicationtype
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Notes
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Reducing the energy expended to carry out a computational task is important. In this work, we explore the prospects of meeting Quality-of-Service requirements of tasks on a multi-core system while adjusting resources to expend a minimum of energy. This paper considers, for the first time, a QoS-driven coordinated resource management algorithm (RMA) that dynamically adjusts the size of the per-core last-level cache partitions and the per-core voltage–frequency settings to save energy while respecting QoS requirements of every application in multi-programmed workloads run on multi-core systems. It does so by doing configuration-space exploration across the spectrum of LLC partition sizes and Dynamic Voltage–Frequency Scaling (DVFS) settings at runtime at negligible overhead. We show that the energy of 4-core and 8-core systems can be reduced by up to 18% and 14%, respectively, compared to a baseline with even distribution of cache resources and a fixed mid-range core voltage–frequency setting. The energy savings can potentially reach 29% if the QoS targets are relaxed to 40% longer execution time.
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Manivannan, Madhavan,1986Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)madhavan
(author)
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Pericas, Miquel,1979Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)miquelp
(author)
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Stenström, Per,1957Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)pers
(author)
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Chalmers tekniska högskola
(creator_code:org_t)
Related titles
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In:Journal of Parallel and Distributed Computing: Elsevier BV144, s. 246-2591096-08480743-7315
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