Resource monitoring for cluster computing with application to parallel motion estimation
In recent years, cluster computing has been accepted widely as a parallel platform because of its high performance at an affordable cost. To make the best use of the cluster computing resources, a resource monitoring program is needed. The information collected can be used by any parallel applicatio...
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Published in | Asia-Pacific Conference on Circuits and Systems Vol. 1; pp. 207 - 210 vol.1 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
2002
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Subjects | |
Online Access | Get full text |
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Summary: | In recent years, cluster computing has been accepted widely as a parallel platform because of its high performance at an affordable cost. To make the best use of the cluster computing resources, a resource monitoring program is needed. The information collected can be used by any parallel application, i.e. parallel motion estimation, for handling load variation in typical time-sharing computers. Therefore, the parallel workload can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using the MPI programming model and its application to parallel motion estimation. Results show the effectiveness of our method in which a faster parallel execution time can be achieved. |
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ISBN: | 9780780376908 0780376900 |
DOI: | 10.1109/APCCAS.2002.1114938 |