Adaptive Distributed Computing through Competition

• Main Author: SHUM, Kam Hong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 1996
• Subjects: Adaptive Parallelism; Scheduling; Parallel Computing; Workstation Clusters; Competition; Auction; load balancing; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1057; http://dx.doi.org/10.1109/CDS.1996.509365
• Institution: Singapore Management University

In this paper, a framework for supporting adaptive execution of parallel applications in networks of workstations is presented. The framework is comprised of two levels of competition. At the first level, the tasks of each application are partitioned into grains. The grains race one another until all their tasks are finished. The turn-around time of an application can be shortened by sharing the tasks of the heavily loaded grains with the neighboring grains. At the second level, a prototype system called Comedians has been developed, which enables competition among applications for workstations by mechanisms of auction and bidding. The objectives of the Comedians system are to maximize the speedup of individual parallel applications and, at the same time, to allocate workstations efficiently and fairly to the applications. Unlike all related work, this paper suggests an integrated solution to both the issues of adaptive parallelism and parallel application scheduling in a multi-user environment. The experimental results demonstrate the effectiveness of the support for adaptive parallelism and the dynamics of competition among parallel applications.