Whole Genome Comparison using Commodity Workstations

—Whole genome comparison consists of comparing or aligning two genome sequences in the hope that analogous functional or physical characteristics may be observed. Sequence comparison is done via a number of slow rigorous algorithms, or faster heuristic approaches. However, due to the large size of genomic sequences, the capacity of current software is limited. In this work, we design a parallel-distributed system for the Smith-Waterman dynamic programming sequence comparison algorithm. We use subword parallelism to speedup sequence to sequence comparison using Streaming SIMD Extensions (SSE) on Intel Pentium processors. We compare two approaches, one requiring explicit data dependency handling and the other built to automatically handle dependencies. We achieve a speedup of 10-30 and establish the optimum conditions for each approach. We then implement a scalable and fault-tolerant distributed version of the genome comparison process on a network of workstations based on a static work allocation algorithm. We achieve speeds upwards of 8000 MCUPS on 64 workstations, one of the fastest implementations of the Smith-Waterman algorithm.