Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems

Shivashis Saha, Ying Lu, Jitender S. Deogun

Research output: Contribution to conferencePaper

22 Citations (Scopus)

Abstract

Next-generation multi-core multiprocessor real-time systems consume less energy at the cost of increased power density. This increase in power-density results in high heat density and may affect the reliability and performance of real-time systems. Thus, incorporating maximum temperature constraints in scheduling of real-time task sets is an important challenge. This paper investigates thermal-constrained energy-aware partitioning of periodic real-time tasks in heterogeneous multi-core multiprocessor systems. We adopt a power model which considers the impact of temperature and voltage on a processor's static power consumption. Two types of thermal models are used to respectively capture negligible and non-negligible amount of heat transfer among cores. We develop a novel genetic-algorithm based approach to solve the heterogeneous multi-core multiprocessor partitioning problem. Extensive simulations were performed to validate the effectiveness of the approach. Experimental results show that integrating a worst-fit based partitioning heuristic with the genetic algorithm can significantly reduce the total energy consumption of a heterogeneous multi-core multiprocessor real-time system.

Original languageEnglish (US)
Pages41-50
Number of pages10
DOIs
StatePublished - Nov 19 2012
Event18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012 - Seoul, Korea, Republic of
Duration: Aug 19 2012Aug 22 2012

Conference

Conference18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012
CountryKorea, Republic of
CitySeoul
Period8/19/128/22/12

Fingerprint

Real time systems
Genetic algorithms
Electric power utilization
Energy utilization
Scheduling
Heat transfer
Temperature
Electric potential
Hot Temperature

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition

Cite this

Saha, S., Lu, Y., & Deogun, J. S. (2012). Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems. 41-50. Paper presented at 18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012, Seoul, Korea, Republic of. https://doi.org/10.1109/RTCSA.2012.15

Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems. / Saha, Shivashis; Lu, Ying; Deogun, Jitender S.

2012. 41-50 Paper presented at 18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012, Seoul, Korea, Republic of.

Research output: Contribution to conferencePaper

Saha, S, Lu, Y & Deogun, JS 2012, 'Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems', Paper presented at 18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012, Seoul, Korea, Republic of, 8/19/12 - 8/22/12 pp. 41-50. https://doi.org/10.1109/RTCSA.2012.15
Saha S, Lu Y, Deogun JS. Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems. 2012. Paper presented at 18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012, Seoul, Korea, Republic of. https://doi.org/10.1109/RTCSA.2012.15
Saha, Shivashis ; Lu, Ying ; Deogun, Jitender S. / Thermal-constrained energy-aware partitioning for heterogeneous multi-core multiprocessor real-time systems. Paper presented at 18th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2012, Seoul, Korea, Republic of.10 p.
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