SWAPHI: Smith-waterman protein database search on Xeon Phi coprocessors

The maximal sensitivity of the Smith-Waterman algorithm has enabled its wide use in biological sequence database search. Unfortunately, the high sensitivity comes at the expense of quadratic time complexity, which makes the algorithm computationally demanding for big databases. In this paper, we present SWAPHI, the first parallelized algorithm employing the emerging Xeon Phis to accelerate Smith-Waterman protein database search. SWAPHI is designed based on the scale-and-vectorize approach, i.e. it boosts alignment speed by effectively utilizing both the coarse-grained parallelism from the many co-processing cores (scale) and the fine-grained parallelism from 512-bit wide single instruction multiple data (SIMD) vectors per core (vectorize). By searching against the large UniProtKB/TrEMBL protein database, SWAPHI achieves a performance of up to 58.8 billion cell updates per second (GCUPS) on a single Xeon Phi and up to 228.4 GCUPS on four Xeon Phis. Moreover, SWAPHI using four Xeon Phis is superior to both SWIPE on 16 highend CPU cores and BLAST+ on 8 cores, with the maximum speedup of 1.52 and 1.86, respectively. SWAPHI is freely available at http://swaphi.sourceforge.net.