GSNP: A DNA Single-Nucleotide Polymorphism Detection System with GPU Acceleration
Hong Kong University of Science and Technology
International Conference on Parallel Processing (ICPP), 2011
@inproceedings{lu2011gsnp,
title={GSNP: A DNA Single-Nucleotide Polymorphism Detection System with GPU Acceleration},
author={Lu, M. and Zhao, J. and Luo, Q. and Wang, B. and Fu, S. and Lin, Z.},
booktitle={Parallel Processing (ICPP), 2011 International Conference on},
pages={592–601},
year={2011},
organization={IEEE}
}
We have developed GSNP, a software package with GPU acceleration, for single-nucleotide polymorphism detection on DNA sequences generated from second-generation sequencing equipment. Compared with SOAPsnp, a popular, high-performance CPU-based SNP detection tool, GSNP has several distinguishing features: First, we design a sparse data representation format to reduce memory access as well as branch divergence. Second, we develop a multipass sorting network to efficiently sort a large number of small arrays on the GPU. Third, we compute a table of frequently used scores once to avoid repeated, expensive computation and to reduce random memory access. Fourth, we apply customized compression schemes to the output data to improve the I/O performance. As a result, on a server equipped with an Intel Xeon E5630 2.53 GHZ CPU and an NVIDIA Tesla M2050 GPU, it took GSNP about two hours to analyze a whole human genome dataset whereas the CPU-based, single-threaded SOAPsnp took three days for the same task on the same machine.
November 12, 2011 by hgpu
