Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy

Ying Li; Jianwei Niu; Meikang Qiu; Xiang Long

doi:10.1109/HPCC-CSS-ICESS.2015.126

Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy

Ying Li
, Jianwei Niu
, Meikang Qiu
, Xiang Long

School of Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

The main challenge for embedded real-time systems, especially for mobile devices, is the trade-off between system performance and energy efficiency. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures, we propose an Accelerated Search algorithm based on dynamic programming to obtain a combination of various task schemes which can be completed in a given time with a confidence probability by consuming the minimum possible energy. We adopt a DAG (Directed Acyclic Graph) to represent the precedent relation between tasks and develop a Minimum-Energy Model to find the optimal tasks assignment. The heterogeneous multi-core architectures can execute tasks under different voltage level with DVFS which leads to different execution time and different consumption energy. The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6%).

Original language	English
Title of host publication	Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	577-582
Number of pages	6
ISBN (Electronic)	9781479989362
DOIs	https://doi.org/10.1109/HPCC-CSS-ICESS.2015.126
State	Published - 23 Nov 2015
Event	17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015 - New York, United States Duration: 24 Aug 2015 → 26 Aug 2015

Publication series

Name	Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015

Conference

Conference	17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015
Country/Territory	United States
City	New York
Period	24/08/15 → 26/08/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Heterogeneous multi-core real-time system
Minimum energy
Probability statistics
Tasks assignment

Access to Document

10.1109/HPCC-CSS-ICESS.2015.126

Cite this

Li, Y., Niu, J., Qiu, M., & Long, X. (2015). Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy. In Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015 (pp. 577-582). Article 7336220 (Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPCC-CSS-ICESS.2015.126

Li, Ying ; Niu, Jianwei ; Qiu, Meikang et al. / Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy. Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 577-582 (Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015).

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title = "Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy",

abstract = "The main challenge for embedded real-time systems, especially for mobile devices, is the trade-off between system performance and energy efficiency. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures, we propose an Accelerated Search algorithm based on dynamic programming to obtain a combination of various task schemes which can be completed in a given time with a confidence probability by consuming the minimum possible energy. We adopt a DAG (Directed Acyclic Graph) to represent the precedent relation between tasks and develop a Minimum-Energy Model to find the optimal tasks assignment. The heterogeneous multi-core architectures can execute tasks under different voltage level with DVFS which leads to different execution time and different consumption energy. The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6\%).",

keywords = "Heterogeneous multi-core real-time system, Minimum energy, Probability statistics, Tasks assignment",

author = "Ying Li and Jianwei Niu and Meikang Qiu and Xiang Long",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015 ; Conference date: 24-08-2015 Through 26-08-2015",

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doi = "10.1109/HPCC-CSS-ICESS.2015.126",

language = "英语",

series = "Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "577--582",

booktitle = "Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015",

address = "美国",

}

Li, Y , Niu, J, Qiu, M & Long, X 2015, Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy. in Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015., 7336220, Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015, Institute of Electrical and Electronics Engineers Inc., pp. 577-582, 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015, New York, United States, 24/08/15. https://doi.org/10.1109/HPCC-CSS-ICESS.2015.126

Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy. / Li, Ying ; Niu, Jianwei; Qiu, Meikang et al.
Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 577-582 7336220 (Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy

AU - Li, Ying

AU - Niu, Jianwei

AU - Qiu, Meikang

AU - Long, Xiang

PY - 2015/11/23

Y1 - 2015/11/23

N2 - The main challenge for embedded real-time systems, especially for mobile devices, is the trade-off between system performance and energy efficiency. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures, we propose an Accelerated Search algorithm based on dynamic programming to obtain a combination of various task schemes which can be completed in a given time with a confidence probability by consuming the minimum possible energy. We adopt a DAG (Directed Acyclic Graph) to represent the precedent relation between tasks and develop a Minimum-Energy Model to find the optimal tasks assignment. The heterogeneous multi-core architectures can execute tasks under different voltage level with DVFS which leads to different execution time and different consumption energy. The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6%).

AB - The main challenge for embedded real-time systems, especially for mobile devices, is the trade-off between system performance and energy efficiency. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures, we propose an Accelerated Search algorithm based on dynamic programming to obtain a combination of various task schemes which can be completed in a given time with a confidence probability by consuming the minimum possible energy. We adopt a DAG (Directed Acyclic Graph) to represent the precedent relation between tasks and develop a Minimum-Energy Model to find the optimal tasks assignment. The heterogeneous multi-core architectures can execute tasks under different voltage level with DVFS which leads to different execution time and different consumption energy. The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6%).

KW - Heterogeneous multi-core real-time system

KW - Minimum energy

KW - Probability statistics

KW - Tasks assignment

UR - https://www.scopus.com/pages/publications/84961700404

U2 - 10.1109/HPCC-CSS-ICESS.2015.126

DO - 10.1109/HPCC-CSS-ICESS.2015.126

M3 - 会议稿件

AN - SCOPUS:84961700404

T3 - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015

SP - 577

EP - 582

BT - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015

Y2 - 24 August 2015 through 26 August 2015

ER -

Li Y , Niu J, Qiu M, Long X. Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy. In Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 577-582. 7336220. (Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015). doi: 10.1109/HPCC-CSS-ICESS.2015.126

Optimizing tasks assignment on heterogeneous multi-core real-time systems with minimum energy

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this