6533b839fe1ef96bd12a5d36
RESEARCH PRODUCT
CUDA-BLASTP: Accelerating BLASTP on CUDA-enabled graphics hardware
Wolfgang Müller-wittigBertil SchmidtWeiguo Liusubject
graphics hardwareSource codeComputer sciencemedia_common.quotation_subjectGraphics hardwareGraphics processing unitParallel computingGeneral Purpose Computation on Graphics Processing Unit (GPGPU)Computational scienceInstruction setCUDAGeneticsComputer GraphicsDatabases Proteinmedia_commondynamic programmingFinite-state machineSequence databaseApplied MathematicsProteinsCompute Unified Device Architecture (CUDA)sequence alignmentGeneral-purpose computing on graphics processing unitsAlgorithmsSoftwareBiotechnologydescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2011-02-23 |