Parallel pattern identification in biological sequences on clusters

This paper presents a low communication overhead parallel algorithm for pattern matching in biological sequences. Given such a sequence of length n and a pattern of length m, we conclude an algorithm with five computation/communication phases, each requiring O(n) computation time and only O(p) message units. The low communication overhead of the algorithm is essential to achieving reasonable speedups on clusters, where the interprocessor communication latency is usually higher Previous parallel implementations use straightforward domain decomposition based on existing sequential algorithms and rely on parallel machines with low-latency interconnection network and fast hardware support for processor synchronization.