Parallelization Methods for Edge Extraction Applied to Chip Multiprocessor Clusters

As the parallel computing technologies become mature, many computationally intensive and/or data intensive algorithms could be improved with parallelization methods. In this paper, we improve the performance of the edge extraction algorithmic program by parallelizing the sequential algorithm. We altogether propose three parallelization methods based on chip multiprocessor (CMP) clusters. The OpenMP-based method is investigated for the shared memory model and thus it is applied to single CMP node, while the three MPI-based methods are investigated for the message passing model and thus they are applied to CMP-clusters. Massive experiments verify that the parallelization methods proposed in this paper are all effective and efficient.