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Dynamic adaptation to available resources for parallel computing in an autonomous network of workstations

Dynamic adaptation to available resources for parallel computing in an autonomous network of... Networks of workstations (NOWs), which are generally composed of autonomous compute elements networked together, are an attractive parallel computing platform since they offer high performance at low cost. The autonomous nature of the environment, however, often results in inefficient utilization due to load imbalances caused by three primary factors: 1) unequal load (compute or communication) assignment to equally-powerful compute nodes, 2) unequal resources at compute nodes, and 3) multiprogramming. These load imbalances result in idle waiting time on cooperating processes that need to synchronize or communicate data. Additional waiting time may result due to local scheduling decisions in a multiprogrammed environment. In this paper, we present a combined approach of compile-time analysis, run-time load distribution, and operating system scheduler cooperation for improved utilization of available resources in an autonomous NOW. The techniques we propose allow efficient resource utilization by taking into consideration all three causes of load imbalance in addition to locality of access in the process of load distribution. The resulting adaptive load distribution and cooperative scheduling system allows applications to take advantage of parallel resources when available by providing better performance than when the loaded resources are not used at all. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGPLAN Notices Association for Computing Machinery

Dynamic adaptation to available resources for parallel computing in an autonomous network of workstations

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2001 by ACM Inc.
ISSN
0362-1340
DOI
10.1145/568014.379572
Publisher site
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Abstract

Networks of workstations (NOWs), which are generally composed of autonomous compute elements networked together, are an attractive parallel computing platform since they offer high performance at low cost. The autonomous nature of the environment, however, often results in inefficient utilization due to load imbalances caused by three primary factors: 1) unequal load (compute or communication) assignment to equally-powerful compute nodes, 2) unequal resources at compute nodes, and 3) multiprogramming. These load imbalances result in idle waiting time on cooperating processes that need to synchronize or communicate data. Additional waiting time may result due to local scheduling decisions in a multiprogrammed environment. In this paper, we present a combined approach of compile-time analysis, run-time load distribution, and operating system scheduler cooperation for improved utilization of available resources in an autonomous NOW. The techniques we propose allow efficient resource utilization by taking into consideration all three causes of load imbalance in addition to locality of access in the process of load distribution. The resulting adaptive load distribution and cooperative scheduling system allows applications to take advantage of parallel resources when available by providing better performance than when the loaded resources are not used at all.

Journal

ACM SIGPLAN Notices – Association for Computing Machinery

Published: Jul 1, 2001

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