By Topic

Fair and Efficient Online Adaptive Scheduling for Multiple Sets of Parallel Applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hongyang Sun ; Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore ; Yangjie Cao ; Wen-Jing Hsu

Both fairness and efficiency are crucial measures for the performance of parallel applications on multiprocessor systems. In this paper, we study online adaptive scheduling for multiple sets of such applications, where each set may contain one or more jobs with time-varying parallelism profile. This scenario arises naturally when dealing with several applications submitted simultaneously by different users in a large parallel system, where both user-level fairness and system-wide efficiency are important concerns. To achieve fairness, we use the equipartitioning algorithm, which evenly splits the available processors among the active job sets at any time. For efficiency, we apply a feedback-driven adaptive scheduler, which periodically adjusts the processor allocations within each set by consciously exploiting the jobs' execution history. We show that our algorithm is competitive for the objective of minimizing the set response time. For sufficiently large jobs, this theoretical result improves upon an existing algorithm that provides only fairness but lacks efficiency. Furthermore, we conduct simulations to empirically evaluate our algorithm, and the results confirm its improved performance using malleable workloads consisting of a wide range of parallelism variation structures.

Published in:

Parallel and Distributed Systems (ICPADS), 2011 IEEE 17th International Conference on

Date of Conference:

7-9 Dec. 2011