Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
A Programmable Processor for Approximate String Matching with High Throughput Rate
ASAP '00 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures, and Processors
BLAST
Biosequence Similarity Search on the Mercury System
ASAP '04 Proceedings of the Application-Specific Systems, Architectures and Processors, 15th IEEE International Conference
Single Pass, BLAST-Like, Approximate String Matching on FPGAs
FCCM '06 Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Families of FPGA-based accelerators for approximate string matching
Microprocessors & Microsystems
FPGA-accelerated seed generation in Mercury BLASTP
FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Mercury BLASTP: Accelerating Protein Sequence Alignment
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Massively Parallelized DNA Motif Search on the Reconfigurable Hardware Platform COPACOBANA
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Fast and accurate NCBI BLASTP: acceleration with multiphase FPGA-based prefiltering
Proceedings of the 24th ACM International Conference on Supercomputing
CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
FPGA-based hardware acceleration for local complexity analysis of massive genomic data
Integration, the VLSI Journal
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Approximate string matching is fundamental to bioinformatics and has been the subject of numerous FPGA acceleration studies. We address issues with respect to FPGA implementations of both BLAST- and dynamic-programming- (DP) based methods. Our primary contribution is a new algorithm for emulating the seeding and extension phases of BLAST. This operates in a single pass through a database at streaming rate, and with no preprocessing other than loading the query string. Moreover, it emulates parameters turned to maximum possible sensitivity with no slowdown. While current DP-based methods also operate at streaming rate, generating results can be cumbersome. We address this with a new structure for data extraction. We present results from several implementations showing order of magnitude acceleration over serial reference code. A simple extension assures compatibility with NCBI BLAST.