Task Partitioning and Load Balancing Strategy for Matrix Applications on Distributed System
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| Title | Task Partitioning and Load Balancing Strategy for Matrix Applications on Distributed System |
| Authors | |
| Abstract | In this paper, we present a load-balancing strategy (Adaptive Load Balancing strategy) for data parallel applications to balance the work load effectively on a distributed system. We study its impact on computation-hungry matrix multiplication application. The ALB strategy enhances the performance with features such as intelligent node selection, pre-task assignment, adaptive task sizing and buffer allocation, and load balancing. The ALB strategy exhibits reduced nodes idle time and inter process communication time, and improved speed up as compared to Run Time task Scheduling strategy. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2013-03-01 |
| Source | Journal of Computers Vol 8, No 3 (2013): Special Issue: Parallel Computing |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |