Performance and Energy Trade-Offs for Parallel Applications on Heterogeneous Multi-Processing Systems

A. M. Coutinho Demetrios, Daniele De Sensi, Arthur Francisco Lorenzon, Kyriakos Georgiou, Jose Nunez-Yanez, Kerstin Eder and Samuel Xavier- de-Souza
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A. M. Coutinho Demetrios: Instituto Federal do Rio Grande do Norte, Pau dos Ferros 59900-000, Brazil
Daniele De Sensi: Computer Science Department, Università di Pisa, 56127 Pisa, Italy
Arthur Francisco Lorenzon: Computer Science Department, Universidade Federal de Pampa, Alegrete 97546-550, Brazil
Kyriakos Georgiou: Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK
Jose Nunez-Yanez: Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK
Kerstin Eder: Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK
Samuel Xavier- de-Souza: Department of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte, Natal 59078-970, Brazil

Energies, 2020, vol. 13, issue 9, 1-24

Abstract: This work proposes a methodology to find performance and energy trade-offs for parallel applications running on Heterogeneous Multi-Processing systems with a single instruction-set architecture. These offer flexibility in the form of different core types and voltage and frequency pairings, defining a vast design space to explore. Therefore, for a given application, choosing a configuration that optimizes the performance and energy consumption is not straightforward. Our method proposes novel analytical models for performance and power consumption whose parameters can be fitted using only a few strategically sampled offline measurements. These models are then used to estimate an application’s performance and energy consumption for the whole configuration space. In turn, these offline predictions define the choice of estimated Pareto-optimal configurations of the model, which are used to inform the selection of the configuration that the application should be executed on. The methodology was validated on an ODROID-XU3 board for eight programs from the PARSEC Benchmark, Phoronix Test Suite and Rodinia applications. The generated Pareto-optimal configuration space represented a 99% reduction of the universe of all available configurations. Energy savings of up to 59.77%, 61.38% and 17.7% were observed when compared to the performance, ondemand and powersave Linux governors, respectively, with higher or similar performance.

Keywords: heterogeneous multi-processing; energy efficiency; power model; Pareto frontier (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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