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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Bibliographic Details
Published inAsia-Pacific Conference on Circuits and Systems Vol. 1; pp. 207 - 210 vol.1
Main Authors Gunawan, T.S., Cai Wen Tong
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Application software
Computer applications
Computerized monitoring
Concurrent computing
Costs
High performance computing
Load management
Motion estimation
Parallel programming
Time sharing computer systems
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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.
ISBN:9780780376908
0780376900
DOI:10.1109/APCCAS.2002.1114938