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MapReduce Model Using FPGA Acceleration for Chromosome Y Sequence Mapping
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DOI：10.1109/ACCESS.2021.3085997.png)
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摘要
En 中文
Genome assemblies sequenced by a Whole Genome Shotgun (WGS) project predict an organism's function and history. Sequence alignment is the foundation of bioinformatics by a computational search through large genome sequence databases, which generally requires enormous amounts of memory and takes a long execution time. In this paper, an Optimized Smith-Waterman algorithm based on the Gotoh algorithm with an affine gap for accuracy alignment, the divide and conquer technique, and the MapReduce framework implemented to establish a parallel process. This model was implemented on Virtex 7 field-programmable gate arrays (FPGAs). These techniques provide a better performance, reduce the hardware requirements, improve the accuracy, increase the computational throughput, and accelerate the alignment process for big data available in a complete Y chromosome. The hardware proposed system can achieve high performance, low time consumption 1.699 ns, and decrease FPGA utilization for big data alignments Y chromosome is used as an example.
Keyword:
Field programmable gate arrays
Bioinformatics
Biological cells
Genomics
Hardware
DNA
Software
MapReduce
PHSW-DC
Gotoh
smith-waterman
Y chromosome
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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