SWPS3 - Fast multi-threaded vectorized Smith-Waterman for IBM Cell/B.E. and ×86/SSE2

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Abstract

Background. We present swps3, a vectorized implementation of the Smith-Waterman local alignment algorithm optimized for both the Cell/BE and ×86 architectures. The paper describes swps3 and compares its performances with several other implementations. Findings. Our benchmarking results show that swps3 is currently the fastest implementation of a vectorized Smith-Waterman on the Cell/BE, outperforming the only other known implementation by a factor of at least 4: on a Playstation 3, it achieves up to 8.0 billion cell-updates per second (GCUPS). Using the SSE2 instruction set, a quad-core Intel Pentium can reach 15.7 GCUPS. We also show that swps3 on this CPU is faster than a recent GPU implementation. Finally, we note that under some circumstances, alignments are computed at roughly the same speed as BLAST, a heuristic method. Conclusion. The Cell/BE can be a powerful platform to align biological sequences. Besides, the performance gap between exact and heuristic methods has almost disappeared, especially for long protein sequences. © 2008 Szalkowski et al; licensee BioMed Central Ltd.

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Szalkowski, A., Ledergerber, C., Krähenbühl, P., & Dessimoz, C. (2008). SWPS3 - Fast multi-threaded vectorized Smith-Waterman for IBM Cell/B.E. and ×86/SSE2. BMC Research Notes, 1. https://doi.org/10.1186/1756-0500-1-107

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