Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
권호 표지
DOI QR코드

DOI QR Code

Probabilistic Power-saving Scheduling of a Real-time Parallel Task on Discrete DVFS-enabled Multi-core Processors

이산적 DVFS 멀티코어 프로세서 상에서 실시간 병렬 작업을 위한 확률적 저전력 스케쥴링

  • Lee, Wan Yeon (Dept. of Computer Science, Dongduk Women's University)
  • 이완연 (동덕여자대학교 컴퓨터학과)
  • Received : 2012.12.11
  • Accepted : 2013.01.01
  • Published : 2013.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose a power-efficient scheduling scheme that stochastically minimizes the power consumption of a real-time parallel task while meeting the deadline on multicore processors. The proposed scheme applies the parallel processing that executes a task on multiple cores concurrently, and activates a part of all available cores with unused cores powered off, in order to save power consumption. It is proved that the proposed scheme minimizes the mean power consumption of a real-time parallel task with probabilistic computation amount on DVFS-enabled multicore processors with a finite set of discrete clock frequencies. Evaluation shows that the proposed scheme saves up to 81% power consumption of the previous method.

본 논문에서는 멀티코어 프로세서에서 단일 실시간 병렬 작업의 데드라인을 만족하면서 전력 소모량의 확률적 기대 값을 최소화하는 스케쥴링 기법을 제안하였다. 제안된 기법에서는 단일 작업을 여러 개의 코어들 상에서 동시에 수행하는 병렬 처리 기법을 적용하였고, 전체 코어들 중에서 일부의 코어들만을 사용하고 나머지 코어들의 전원을 소등하여 전력 소모량을 줄였다. 또한 한정된 개수의 이산적 클락 주파수 값들을 가지는 DVFS 기반 멀티코어 프로세서에 대해서, 확률적 계산량 모델을 가진 실시간 병렬 작업의 데드라인을 만족하면서 전력 소모량의 확률적 기대 값을 최소화함을 수학적으로 증명하였다. 성능평가 실험에서, 제안된 기법이 기존 방법의 전력소모량을 최대 81%까지 감소시킴을 확인하였다.

Keywords

References

  1. Semiconductor Industry Association (SIA), International Technology Roadmap for Semiconductors: 2005 Edition, http://www.itrs.net.
  2. L. Benini, A. Bogliolo, and G. Micheli, "A survey of design techniques for system-level dynamic power management,'' IEEE Trans. VLSI Syst., vol. 8, no. 3, pp. 299-316, 2000. https://doi.org/10.1109/92.845896
  3. R. Xu, C. Xi, R. Melhem, and D. Moss, ''Practical PACE for embedded systems,'' ACM Int'l Conf. Embedded Software, 2005, pp. 54-63.
  4. C. Yang, J. Chen, and T. Kuo, ''An approximation algorithm for energy-efficient scheduling on a chip multiprocessor,'' Design, Automation and Test in Europe Conf., 2005, pp. 468-473.
  5. H. Aydin and Q. Yang, ''Energy-aware partitioning for multiprocessor real-time systems,'' Int'l Parallel Distributed Processing Symp., 2003, p. 113.2.
  6. A. Andrei, P. Eles, Z. Peng, M. T. Schmitz, and B. Hashimi, ''Energy optimization of multiprocessor systems on chip by voltage selection,'' IEEE Trans. VLSI Syst., vol. 15, no. 3, pp. 262-275, 2007. https://doi.org/10.1109/TVLSI.2007.891101
  7. E. Seo, J. Jeong, S. Park, and J. Lee, ''Energy efficient scheduling of real-time tasks on multicore processors,'' IEEE Trans. Parallel Distrib. Syst., vol. 19, no. 11, pp. 1540-1552, 2008. https://doi.org/10.1109/TPDS.2008.104
  8. C. Xian, Y. Lu, and Z. Li, ''Energy-aware scheduling for real-time multiprocessor systems with uncertain task execution time," Design Automation Conf., pp. 664-669, 2007.
  9. H. Pack, J. Yeo and W. Lee, ''Energy-efficient multi-core scheduling for real-time video processing,'' Journal of the Korea Society of Computer and Information, vol. 16, no. 6, pp. 11-20, 2011. https://doi.org/10.9708/jksci.2011.16.6.011
  10. W. Lee, ''Power-efficient scheduling of periodic real-time tasks on lightly loaded multcore processors,'' Journal of the Korea Society of Computer and Information, vol. 17, no. 8, pp. 11-19, 2012.
  11. W. Lee and K. Kim, ''Energy-saving stochastic scheduling of a real-time parallel task with varying computation amount on multi-core processors,'' IEICE Trans. Fundamentals, vol. E94-A, no. 2, pp. 842-845, 2011. https://doi.org/10.1587/transfun.E94.A.842
  12. D. Luenberger, Linear and Nonlinear Programming, Addison-Wesley, 1984.