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Issue No.04 - July-Aug. (2012 vol.9)
pp: 1245-1256
J. S. Torres , Centro Mixto CSIC, Univ. Politec. de Valencia-CIEMAT, Valencia, Spain
General Purpose Graphic Processing Units (GPGPUs) constitute an inexpensive resource for computing-intensive applications that could exploit an intrinsic fine-grain parallelism. This paper presents the design and implementation in GPGPUs of an exact alignment tool for nucleotide sequences based on the Burrows-Wheeler Transform. We compare this algorithm with state-of-the-art implementations of the same algorithm over standard CPUs, and considering the same conditions in terms of I/O. Excluding disk transfers, the implementation of the algorithm in GPUs shows a speedup larger than 12×, when compared to CPU execution. This implementation exploits the parallelism by concurrently searching different sequences on the same reference search tree, maximizing memory locality and ensuring a symmetric access to the data. The paper describes the behavior of the algorithm in GPU, showing a good scalability in the performance, only limited by the size of the GPU inner memory.
tree searching, biology computing, genetics, graphics processing units, parallel processing, sequences, transforms, GPU inner memory, short-read genetic sequences, Burrows-Wheeler transform, general purpose graphic processing unit, GPGPU, fine-grain parallelism, exact alignment tool, nucleotide sequence, standard CPU, I/O, CPU execution, search tree, memory locality, Graphics processing unit, Bioinformatics, Transforms, Algorithm design and analysis, Vectors, Genomics, Indexes, Burrows-Wheeler Transform., Short-read alignment, CUDA, GPU
J. S. Torres, "Using GPUs for the Exact Alignment of Short-Read Genetic Sequences by Means of the Burrows-Wheeler Transform", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no. 4, pp. 1245-1256, July-Aug. 2012, doi:10.1109/TCBB.2012.49
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