Earticle

초록

영어

Improving the energy efficiency of high performance clusters has become important research issue. We proposed a new algorithm that reduces energy consumption of precedence constrained parallel tasks in power-scalable clusters. To reduce energy consumption without increasing the schedule length, our algorithm reclaims both static and dynamic slack time and employs different frequency adjusting techniques in different slack time. The optimal frequency is obtained through analyzing the precedence constraints of parallel tasks. We conducted extensive experiments to compare the proposed algorithm with two other existing algorithms, simulation results show that the proposed algorithm can get better energy efficiency without increasing the make span.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Computational Model
  3.1. Task Model
  3.2. Energy Model
 4. Two-Phase Frequency Scaling
  4.1. First Phase Frequency Scaling
  4.2. Second Phase Frequency Scaling
  4.3. Energy Aware Scheduling Algorithm
 5. Experimental Evaluation
  5.1. Impact of ECR and LCR
  5.2. Overall Energy Efficiency
 6. Conclusion and Future Work
 Acknowledgement
 References

키워드

저자

• Aihua Liang [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China ]
• Jun Liang [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China ]
• Jiazheng Yuan [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605