Competitive Two-Level Adaptive Scheduling Using Resource Augmentation

  • Authors:

  • Hongyang Sun;Yangjie Cao;Wen-Jing Hsu

  • Affiliations:

  • School of Computer Engineering, Nanyang Technological University, Singapore 639798;School of Electronic and Information Engineering, Xi'an Jiaotong University, Shanxi, P.R. China 710049;School of Computer Engineering, Nanyang Technological University, Singapore 639798

  • Venue:
  • Job Scheduling Strategies for Parallel Processing
  • Year:
  • 2009

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Abstract

As multi-core processors proliferate, it has become more important than ever to ensure efficient execution of parallel jobs on multiprocessor systems. In this paper, we study the problem of scheduling parallel jobs with arbitrary release time on multiprocessors while minimizing the jobs' mean response time. We focus on non-clairvoyant scheduling schemes that adaptively reallocate processors based on periodic feedbacks from the individual jobs. Since it is known that no deterministic non-clairvoyant algorithm is competitive for this problem, we focus on resource augmentation analysis, and show that two adaptive algorithms, Agdeq and Abgdeq, achieve competitive performance using O(1) times faster processors than the adversary. These results are obtained through a general framework for analyzing the mean response time of any two-level adaptive scheduler. Our simulation results verify the effectiveness of Agdeq and Abgdeq by evaluating their performances over a wide range of workloads consisting of synthetic parallel jobs with different parallelism characteristics.