Parallel Tiled Codes Implementing the Smith-Waterman Alignment Algorithm for Two and Three Sequences.

Abstract

The Smith-Waterman (SW) algorithm explores all the possible alignments between two or more sequences and as a result it returns the optimal local alignment. However, the computational cost of this algorithm is very high, and the exponential growth of computation makes SW unrealistic for searching similarities in large sets of sequences. Fortunately, the dynamic programming kernel of the SW algorithm involves mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. This allows us to apply polyhedral compilation techniques to optimize the studied SW dense array code. In this article, we present an approach to generate efficient SW implementations for two and three sequences by using the transitive closure of a dependence graph and loop skewing. Generated programs are represented with parallel tiled loop nests, which expose significantly higher performance than that of programs obtained with closely related compilers. The approach is able to tile all loops of original loop nests as opposed to well-known affine transformation techniques. Furthermore, it allows for code optimization of three-sequence alignment. Such a code cannot be generated by means of state-of-the-art automatic optimizing compilers. We demonstrate that an under-approximation of transitive closure (instead of exact transitive closure) can be used to generate valid parallel tiled code. This considerably reduces the computational complexity of the approach. Generated codes were run on cores of a modern Intel multiprocessor and they expose high speedup and good scalability on this platform.