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Saving Energy by Means of Dynamic Load Management in Embedded Multicore Systems
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1276-3609
Fraunhofer Institute for Embedded Systems and Communication Technologies ESK, Germany.
University of Applied Sciences Munich, Germany.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6132-7945
2014 (English)In: Proceedings of the 9th IEEE International Symposium on Industrial Embedded Systems, SIES 2014, 2014, p. 11-20Conference paper, Published paper (Refereed)
Abstract [en]

Load balancing is widely used to optimize response times and throughput of software systems. When considering embedded systems, however, additional optimization goals like energy consumption become relevant. In this paper, we explore the use of load balancing in embedded multicore applications. We present extensions to three prominent load balancing schemes, enabling them to dynamically scale the number of active cores. We integrated the algorithms in a proprietary operating system targeting multicore embedded systems. Our evaluation, which is based on a telecommunication (VoIP) scenario, shows that a significant reduction in energy consumption is possible.

Place, publisher, year, edition, pages
2014. p. 11-20
Keywords [en]
Load BalancingMulticoreMultikernelDistributed Systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-25176DOI: 10.1109/SIES.2014.6871180ISI: 000345746200002Scopus ID: 2-s2.0-84906667174ISBN: 9781479940233 (print)OAI: oai:DiVA.org:mdh-25176DiVA, id: diva2:722501
Conference
9th IEEE International SIES SIES'14, 18-20 Jun 2014, Pisa, Italy
Projects
PREMISE - Predictable Multicore SystemsAvailable from: 2014-06-09 Created: 2014-06-05 Last updated: 2015-10-05Bibliographically approved
In thesis
1. Efficient Resource Management for Many-Core based Industrial Real-Time Systems
Open this publication in new window or tab >>Efficient Resource Management for Many-Core based Industrial Real-Time Systems
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The increased complexity of today’s industrial embedded systems stands inneed for more computational power while most systems must adhere to a restrictedenergy consumption, either to prolong the battery lifetime or to reduceoperational costs. The many-core processor is therefore a natural fit. Due tothe simple architecture of the compute cores, and therefore their good analyzability,such processors are additionally well suited for real-time applications.In our research, we focus on two particular problems which need to be addressedin order to pave the way into the many-core era. The first area is powerand thermal aware execution frameworks, where we present different energyaware extensions to well known load balancing algorithms, allowing them todynamically scale the number of active cores depending on their workload.In contrast, an additional framework is presented which balances workloadsto minimize temperature gradients on the die. The second line of works focuseson industrial standards in the face of massively parallel platforms, wherewe address the automotive and automation domain. We present an executionframework for IEC 61131-3 applications, allowing the consolidation of severalIEC 61131-3 applications on the same platform. Additionally, we discussseveral architectural options for the AUTOSAR software architecture on suchmassively parallel platforms.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2015
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 221
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-29290 (URN)978-91-7485-237-0 (ISBN)
Presentation
2015-11-06, Gamma, Västerås, 09:30 (English)
Opponent
Supervisors
Projects
PREMISE
Funder
Knowledge Foundation, 16286Knowledge Foundation, 16256
Available from: 2015-10-05 Created: 2015-10-02 Last updated: 2015-10-26Bibliographically approved

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Becker, MatthiasNolte, Thomas

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