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GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU
Su, X.; Wang, X.; Xu, J.; Ning, K
2013
发表期刊Paper presented at the Systems Biology
期号2013.07.19
摘要 Motivation: The number of microbial community samples is increasing with exponential speed. Data-mining among microbial community samples could facilitate the discovery of valuable biological information yet hidden in the massive data. However, current methods for the comparison among microbial communities are limited by their ability to process very large amount of samples each with complex community structure.
Summary: We have developed an optimized GPU-based software, GPU-Meta-Storms, to efficiently measure the quantitative phylogenetic similarity among massive amount of microbial community samples. Our results have shown that GPU-Meta-Storms would be able to compute the pair-wise similarity scores for 10,240 samples within 20 minutes, which gained a speed-up of more than 17,000 times compared to single-core CPU, and more than 2,600 times compared to 16-core CPU. Therefore, the high-performance of GPU-Meta-Storms could facilitate in-depth data mining among massive microbial community samples, and make the real-time analysis and monitoring of temporal or conditional changes for microbial communities possible.
Availability: GPU-Meta-Storms is implemented by CUDA (Compute Unified Device Architecture) and C++. Source code is available at http://www.computationalbioenergy.org/meta-storms.html.
 
学科领域功能基因组
收录类别EI
语种英语
文献类型期刊论文
条目标识符http://ir.qibebt.ac.cn/handle/337004/1611
专题单细胞中心
推荐引用方式
GB/T 7714
Su, X.,Wang, X.,Xu, J.,et al. GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU[J]. Paper presented at the Systems Biology,2013(2013.07.19).
APA Su, X.,Wang, X.,Xu, J.,&Ning, K.(2013).GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU.Paper presented at the Systems Biology(2013.07.19).
MLA Su, X.,et al."GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU".Paper presented at the Systems Biology .2013.07.19(2013).
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