A Comparative Evaluation of Latency-Aware Energy Optimization Approaches in Many-Core Systems

Esper K, Wildermann S, Teich J (2021)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2021

Pages Range: 1:1--1:12

Conference Proceedings Title: Proceedings of the Workshop on Next Generation Real-Time Embedded Systems (NG-RES), OASICS Vol. 87

Event location: Budapest HU

ISBN: 978-3-95977-178-8

URI: https://drops.dagstuhl.de/opus/volltexte/2021/13477

DOI: 10.4230/OASIcs.NG-RES.2021.1

Open Access Link: https://drops.dagstuhl.de/opus/volltexte/2021/13477

Abstract

Many applications vary a lot in execution time depending on their workload. A prominent example is image processing applications, where the execution time is dependent on the content or the size of the processed input images. An interesting case is when these applications have quality-of-service requirements such as soft deadlines, that they should meet as good as possible. A further complicated case is when such applications have one or even multiple further objectives to optimize like, e.g., energy consumption.
Approaches that dynamically adapt the processing resources to application needs under multiple optimization goals and constraints can be characterized into the application-specific and feedback-based techniques. Whereas application-specific approaches typically statically use an offline stage to determine the best configuration for each known workload, feedback-based approaches, using, e.g., control theory, adapt the system without the need of knowing the effect of workload on these goals.
In this paper, we evaluate a state-of-the-art approach of each of the two categories and compare them for image processing applications in terms of energy consumption and number of deadline misses on a given many-core architecture. In addition, we propose a second feedback-based approach that is based on finite state machines (FSMs). The obtained results suggest that whereas the state-of-the-art application-specific approach is able to meet a specified latency deadline whenever possible while consuming the least amount of energy, it requires a perfect characterization of the workload on a given many-core system. If such knowledge is not available, the feedback-based approaches have their strengths in achieving comparable energy savings, but missing deadlines more often.

Authors with CRIS profile

Khalil Esper Sonderforschungsbereich/Transregio 89 Invasives Rechnen Stefan Wildermann Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design) Jürgen Teich Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)

Related research project(s)

Basics of Invasive Computing (A01) (SFB/TRR 89 InvasIC (A01)) DFG SFB/Transregio 89 "Invasive Computing" (TRR 89) July 1, 2010 - Dec. 31, 2022

How to cite

APA:

Esper, K., Wildermann, S., & Teich, J. (2021). A Comparative Evaluation of Latency-Aware Energy Optimization Approaches in Many-Core Systems. In Proceedings of the Workshop on Next Generation Real-Time Embedded Systems (NG-RES), OASICS Vol. 87 (pp. 1:1--1:12). Budapest, HU.

MLA:

Esper, Khalil, Stefan Wildermann, and Jürgen Teich. "A Comparative Evaluation of Latency-Aware Energy Optimization Approaches in Many-Core Systems." Proceedings of the Workshop on Next Generation Real-Time Embedded Systems (NG-RES), Budapest 2021. 1:1--1:12.

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