Efficiency of Shared-Memory Multiprocessors for a Genetic Sequence Similarity Search Algorithm
Ed Huai-hsin, Elizabeth Shoop, John V. Carlis, Ernest F. Retzel, John Riedl · 1997
Molecular biologists who conduct large-scale genetic sequencing projects are producing an ever-increasing amount of sequence data. GenBank, the primary repository for DNA sequence data is doubling in size every 1.3 years. Keeping pace with the analysis of this data is a difficult task. One of the most successful techniques for analyzing genetic data is sequence similarity analysis---the comparison of unknown sequences against known sequences kept in databases. As biologists gather more sequence data, sequence similarity algorithms are more and more useful, but take longer and longer to run. BLAST is one of the most popular sequence similarity algorithms in use today, but its running time is proportional to the size of the database. Sequence similarity analysis using BLAST is becoming a bottleneck. Shared-Memory Multiprocessors (SMPs) may offer performance that scales with the growth of the genetic databases. This paper analyzes the performance of BLAST on SMPs, to improve our theoretic...