Model
Digital Document
Publisher
Florida Atlantic University
Description
Many image processing applications can exploit high degree of data locality and parallelism to improve performance. Customized massively parallel computing hardware provides expensive but the most efficient solution as far as performance is concerned. Now-a-days high bandwidth network with high performance workstations are becoming economical and are widely available. Hence, better performance-to-cost ratio can be achieved by implementing message passing paradigm of parallel processing. Parallel edge detector was developed using message passing interfaces on cluster of workstations. This thesis discussed performance evaluation in terms of execution time, speedup, and efficiency for tasks with different computational intensities. Effects of sequential I/O component and load balancing are also discussed.
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