Change search
ReferencesLink to record
Permanent link

Direct link
A pareto-optimal runtime power budgeting scheme for many-core systems
Show others and affiliations
2016 (English)In: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436Article in journal (Refereed) Epub ahead of printText
Abstract [en]

Due to the ever-escalating power consumption, a significant proportion of the future many-core chips is mandatory to be switched off to meet the power budgets. This trend has brought up a paradigm shift from conventional low-power to power budgeting designs, where performance optimization needs to be performed under a tight power budget constraint. There are two key issues to be considered when moving this new design paradigm forward. Firstly, with per-core frequency scaling, the number of frequency combinations of the cores grows exponentially. As more cores are integrated onto a chip, it becomes more challenging to achieve the optimal performance over a given power budget. Secondly, the power budgets of many-core system might undergo a rapid fluctuation. Consequently, the power budgeting scheme needs to be prompt to make appropriate changes to track such power budget variation. This paper is aiming at resolving the problem of optimizing overall performance over a power budget using frequency scaling technique. To solve the problem efficiently at runtime, we propose a parallel dynamic programming network, in which the Pareto-optimal solutions can be obtained using linear time complexity. Experimental results have confirmed that the proposed approach can reduce the execution time by 45% when compared to other existing methods. The runtime overhead and hardware cost of the proposed approach are reasonably small, such as the average area and power consumption are less than 1% of the whole network-on-chip. This paper demonstrates an effective formulation for delivering Pareto-optimal solutions for power budgeting in future many-core systems.

Place, publisher, year, edition, pages
Elsevier, 2016.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-186726DOI: 10.1016/j.micpro.2016.03.006OAI: oai:DiVA.org:kth-186726DiVA: diva2:928533
Note

QCR 20160516

Available from: 2016-05-16 Created: 2016-05-13 Last updated: 2016-05-16Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Daneshtalab, Masoud
By organisation
Electronics and Embedded Systems
In the same journal
Microprocessors and microsystems
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 4 hits
ReferencesLink to record
Permanent link

Direct link