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Low-complexity run-time management of concurrent workloads for energy-efficient multi-core systems

Lookup NU author(s): Ali Aalsaud, Dr Fei Xia, Dr Ashur Rafiev, Dr Rishad Shafik, Professor Alexander Romanovsky, Professor Alex Yakovlev

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Contemporary embedded systems may execute multiple applications, potentially concurrently on heterogeneous platforms, with different system workloads (CPU- or memory-intensive or both) leading to different power signatures. This makes finding the most energy-efficient system configuration for each type of workload scenario extremely challenging. This paper proposes a novel run-time optimization approach aiming for maximum power normalized performance under such circumstances. Based on experimenting with PARSEC applications on an Odroid XU-3 and Intel Core i7 platforms, we model power normalized performance (in terms of instruction per second (IPS)/Watt) through multivariate linear regression (MLR). We derive run-time control methods to exploit the models in different ways, trading off optimization results with control overheads. We demonstrate low-cost and low-complexity run-time algorithms that continuously adapt system configuration to improve the IPS/Watt by up to 139% compared to existing approaches


Publication metadata

Author(s): Aalsaud A, Xia F, Rafiev A, Shafik R, Romanovsky A, Yakovlev A

Publication type: Article

Publication status: Published

Journal: Journal of Low Power Electronics and Applications

Year: 2020

Volume: 10

Issue: 3

Print publication date: 25/08/2020

Online publication date: 25/08/2020

Acceptance date: 10/08/2020

Date deposited: 25/08/2020

ISSN (electronic): 2079-9268

Publisher: MDPI

URL: https://doi.org/10.3390/jlpea10030025

DOI: 10.3390/jlpea10030025


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