A Million-Fold Speed Improvement in Genomic Repeats Detection

This paper presents a novel, parallel algorithm for generating top alignments. Top alignments are used for finding internal repeats in biological sequences like proteins and genes. Our algorithm replaces an older, sequential algorithm (Repro), which was prohibitively slow for sequence lengths higher than 2000. The new algorithm is an order of magnitude faster (O(n3) rather than O(n4)). The paper presents a three-level parallel implementation of the algorithm: using SIMD multimedia extensions found on present-day processors (a novel technique that can be used to parallelize any application that performs many sequence alignments), using shared-memory parallelism, and using distributed-memory parallelism. It allows processing the longest known proteins (nearly 35000 amino acids). We show exceptionally high speed improvements: between 548 and 889 on a cluster of 64 dual-processor machines, compared to the new sequential algorithm. Especially for long sequences, extreme speed improvements over the old algorithm are obtained.