DOI:
Abstract:
Homology detection in large data bases is probably the most time consuming operation in molecular genetic computing systems. Moreover, the progresses made all around the world concerning the mapping and sequencing of the genome of Homo Sapiens and other species have increased the size of data bases exponentially. Therefore even the best workstation would not be able to reach the scanning speed required. In order to answer this need we propose an algorithm, A2R2, and its implementation on a massively parallel system. Basically, two kinds of algorithms are used to search in molecular genetic data bases. The first kind is based on dynamic programming and the second on word processing, A2R2 belongs to the second kind. The structure of the motif (pattern) searched by A2R2 can support those from Fast, Blast and Flash algorithms. After a short presentation of the reconfigurable hardware concept and technology used in our massively parallel accelerator we present the A2R2 implementation. This parallel implementation outperforms any kind of previously published genetic data base scanning hardware or algorithms. We report up to 25 million nucleotides per scanning seconds as our best results.