high performance computing on graphics processing units: hgpu.org

Bioinformatics is the field of science which applies computer science and information technology to the problems of biological science. One of the most useful applications of bioinformatics is sequence analysis. Sequence analysis, which is the process of subjecting a DNA, RNA to any wide range of analytical approaches, involves methodologies like sequence alignment and searches against biological databases. For the analysis DNA sequences are stored in databases for easy retrieval and comparison. Frequency of pattern occurrence in database may predict the intensity of the disease. When the sequence database is huge, matching a pattern is very time consuming task. This fact leads to the need of utilizing latest complex and expensive hardware like GPU. In this paper, we propose a Parallel string matching algorithm using CUDA (Compute Unified Device Architecture). The focus of the research is the design and implementation of an algorithm by utilizing GPU cores optimally. Our algorithms finds correct matches and experimental results show very high performance gain over the sequential approach.