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In the past few years, cluster computing has been accepted widely as parallel platform because of its high performance at an affordable cost. To maximize the use of available resources, resource monitoring for cluster computing is required. The resource information collected can be used by any parallel applications, i.e. parallel motion estimation, for handling variation of available resources in typical time-sharing computers. Therefore, the computing load can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using MPI programming model to achieve efficient parallel motion estimation. Results show the effectiveness of our method in which the faster parallel execution time can be achieved.
Control, Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on (Volume:3 )
Date of Conference: 2-5 Dec. 2002