CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware

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 d...

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Bibliographic Details
Published in:IEEE/ACM transactions on computational biology and bioinformatics 2011-11, Vol.8 (6), p.1678-1684
Main Authors: Weiguo Liu, Schmidt, Bertil, Muller-Wittig, Wolfgang
Format: Article
Language:English
Subjects:
Algorithms
Bioinformatics
BLAST
Computer Graphics
CUDA
Databases, Protein
Doped fiber amplifiers
Dynamic programming
GPGPU
graphics hardware
Graphics processing unit
Instruction sets
Proteins - chemistry
sequence alignment
Software
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Summary: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.
ISSN:1545-5963
1557-9964
DOI:10.1109/TCBB.2011.33