De(con)struction of the lazy-F loop: improving performance of Smith Waterman alignment

TL;DR

This paper presents an optimized Smith-Waterman algorithm that enhances the lazy-F loop heuristic, achieving superior asymptotic performance and practical efficiency through loop transformations and elimination.

Contribution

It introduces a series of transformations that improve lazy-F loop performance and eliminates the loop entirely, setting a new standard for scan-based SW algorithms.

Findings

Achieves asymptotic performance of O(n/p+log(p))

Demonstrates practical efficiency improvements

Eliminates the lazy-F loop for better performance

Abstract

Striped variation of the Smith-Waterman algorithm is known as extremely efficient and easily adaptable for the SIMD architectures. However, the potential for improvement has not been exhausted yet. The popular Lazy-F loop heuristic requires additional memory access operations, and the worst-case performance of the loop could be as bad as the nonvectorized version. We demonstrate the progression of the lazy-F loop transformations that improve the loop performance, and ultimately eliminate the loop completely. Our algorithm achieves the best asymptotic performance of all scan-based SW algorithms O(n/p+log(p)), and is very efficient in practice.