Biosequence Similarity Search on the Mercury System

Authors:
Praveen Krishnamurthy;Jeremy Buhler;Roger Chamberlain;Mark Franklin;Kwame Gyang;Arpith Jacob;Joseph Lancaster
Affiliations:
Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA;Department of Computer Science and Engineering, Washington University, St. Louis, USA
Venue:
Journal of VLSI Signal Processing Systems
Year:
2007

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Abstract

Biosequence similarity search is an important application in modern molecular biology. Search algorithms aim to identify sets of sequences whose extensional similarity suggests a common evolutionary origin or function. The most widely used similarity search tool for biosequences is BLAST, a program designed to compare query sequences to a database. Here, we present the design of BLASTN, the version of BLAST that searches DNA sequences, on the Mercury system, an architecture that supports high-volume, high-throughput data movement off a data store and into reconfigurable hardware. An important component of application deployment on the Mercury system is the functional decomposition of the application onto both the reconfigurable hardware and the traditional processor. Both the Mercury BLASTN application design and its performance analysis are described.