Abstract
This paper discusses and evaluates parallel implementations of a segmentation algorithm based on the Split-and-Merge approach. The solution has been conceived for a multiprocessor using the Single Program Multiple Data (SPMD) programming model and executions have been carried out on a Cray-T3E system. Our main goal is to describe our experiences in solving the region growing problem, which is representative of a class of non-uniform problems, characterized by a behavior that is data dependent. Since this problem exhibits unpredictable load fluctuations, it requires the use of load-balancing schemes to achieve efficient parallel solutions. We also propose and analyze several strategies for the selection of region identifiers and their influence on execution time and load distribution.
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