Accelerating Processing Speed in Pathway Research Based on GPU

摘要：

　　Genome-wide association study (GWAS) has become an effective and successful method to identify disease loci by considering SNPs independently.However,it may be invalid for uncovering the disease loci that not reaching a stringent genome-wide significance threshold.As a result,multi-SNP GWAS is developing rapidly as a complement to traditional GWAS.However,the high computational cost becomes a major limitation for it.The graphical processing unit (GPU) is a programmable graphics processor which has powerful parallel computing ability.And with the development,GPUs have been feasible for many scientific studies.Hence,we are motivated to use GPUs for pathway-based GWAS to improve computational efficiency.The experiment results attained showed the speed-up ratio can reach up to more than 160.

关键词： GWAS Pathway analysis Complex disease GPU CUDA

作者: Bo Liao Ting Yao Xiong Li

作者单位: College of Information Science andEngineeringHunan University, Changsha, China

会议类型: 国际会议

会议名称: 7th International Conference on Systems Biology(第7届计算系统生物学国际研讨会)(ISB2013)

会议地点: 安徽黄山

会议语种:英文

页码: 75-79

在线出版日期: 2013-08-22（万方平台首次上网日期，不代表论文的发表时间）