Parallel Rank Coherence in Networks for Inferring Disease Phenotype and Gene Set Associations

摘要：

　　The RCNet (Rank Coherence in Networks) algorithm has been used to find out the associations between the gene sets and disease phenotypes.However,it suffers from high computational cost when the size of dataset is very large.In this paper,we design three mechanisms to solve the RCNet algorithm on heterogeneous CPU-GPU system based on CUDA and OpenMP programming model.The pipeline mechanism is much suitable for the collaborative computing on CPU and dual-GPUs,which can achieve more than 33 times performance gains.The work plays an important role in reconstructing the disease phoneme-genome association efficiently.

关键词： disease phenotype gene set RCNet CUDA OpenMP

作者: Tao Li Duo Wang Shuai Zhang Yulu Yang

作者单位: Department of Computer Science and Information Security,Nankai University Tianjin,China

会议类型: 国际会议

会议名称: ACA,Advanced Computer Architecture(2014年全国计算机体系结构学术会议)

会议地点: 沈阳

会议语种:英文

页码: 163-176

在线出版日期: 2014-08-23（万方平台首次上网日期，不代表论文的发表时间）