Using Analytical Models to Load Balancing in a Heterogeneous Network of Computers
An effective workload distribution has a prime rule on reducing the total execution time of a parallel application on heterogeneous environments, such as computational grids and heterogeneous clusters. Several methods have been proposed in the literature by many researchers in the last decade. This...
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Published in | Parallel Computing Technologies pp. 559 - 568 |
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Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | An effective workload distribution has a prime rule on reducing the total execution time of a parallel application on heterogeneous environments, such as computational grids and heterogeneous clusters. Several methods have been proposed in the literature by many researchers in the last decade. This paper presents two approaches to workload distribution based on analytical models developed to performance prediction of parallel applications, named PEMPIs VRP (Vector of Relative Performances). The workload is distributed based on relative performance ratios, obtained by these models. In this work, we present two schemes, static and dynamic, in a research middleware for a heterogeneous network of computers. In the experimental tests we evaluated and compared them using two MPI applications. The results show that, using the VRP’s dynamic strategy, we can reduce the imbalance, among the execution time of the processes, in relation to average time from 25% to near of 5%. |
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ISBN: | 9783540739395 3540739394 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-540-73940-1_56 |