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On Fine-Grained Runtime Power Budgeting for Networks-on-Chip Systems
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2016 (English)In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 9, 2780-2793 p.Article in journal (Refereed) Published
Abstract [en]

Power budgeting is an essential aspect of networks-on-chip (NoC) to meet the power constraint for on-chip communications while assuring the best possible overall system performance. For simplicity and ease of implementation, existing NoC power budgeting schemes treat all the individual routers uniformly when allocating power to them. However, such homogeneous power budgeting schemes ignore the fact that the workloads of different NoC routers may vary significantly, and thus may provide excess power to routers with low workloads, whereas insufficient power to those with high workloads. In this paper, we formulate the NoC power budgeting problem in order to optimize the network performance over a power budget through per-router frequency scaling. We take into account of heterogeneous workloads across different routers as imposed by variations in traffic. Correspondingly, we propose a fine-grained solution using an agile algorithm with low time complexity. Frequency of each router is set individually according to its contribution to the average network latency while meeting the power budget. Experimental results have confirmed that with fairly low runtime and hardware overhead, the proposed scheme can help save up to 50 percent application execution time when compared with the latest proposed methods.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016. Vol. 65, no 9, 2780-2793 p.
Keyword [en]
Energy-aware systems, power management, parallel systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-194279DOI: 10.1109/TC.2015.2506565ISI: 000384130500008ScopusID: 2-s2.0-84982124673OAI: diva2:1040773

QC 20161028

Available from: 2016-10-28 Created: 2016-10-21 Last updated: 2016-11-01Bibliographically approved

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Daneshtalab, Masoud
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Electronics and Embedded Systems
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