RC-BLAST: Towards a Portable, Cost-Effective Open Source Hardware Implementation
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 7 - Volume 08
IEEE Transactions on Parallel and Distributed Systems
Single pass streaming BLAST on FPGAs
Parallel Computing
Scalable Parallel Programming with CUDA
Queue - GPU Computing
Mercury BLASTP: Accelerating Protein Sequence Alignment
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Massively parallel genomic sequence search on the Blue Gene/P architecture
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Accelerating BLASTP on the Cell Broadband Engine
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Optimizing data intensive GPGPU computations for DNA sequence alignment
Parallel Computing
Improvement of BLASTp on the FPGA-Based high-performance computer RIVYERA
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
Frequency-based re-sequencing tool for short reads on graphics processing units
International Journal of Computational Science and Engineering
International Journal of Computational Science and Engineering
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Scanning protein sequence database is an often repeated task in computational biology and bioinformatics. However, scanning large protein databases, such as GenBank, with popular tools such as BLASTP requires long runtimes on sequential architectures. Due to the continuing rapid growth of sequence databases, there is a high demand to accelerate this task. In this paper, we demonstrate how GPUs, powered by the Compute Unified Device Architecture (CUDA), can be used as an efficient computational platform to accelerate the BLASTP algorithm. In order to exploit the GPU's capabilities for accelerating BLASTP, we have used a compressed deterministic finite state automaton for hit detection as well as a hybrid parallelization scheme. Our implementation achieves speedups up to 10.0 on an NVIDIA GeForce GTX 295 GPU compared to the sequential NCBI BLASTP 2.2.22. CUDA-BLASTP source code which is available at https://sites.google.com/site/liuweiguohome/software