In:
The International Journal of High Performance Computing Applications, SAGE Publications, Vol. 29, No. 4 ( 2015-11), p. 506-510
Abstract:
Detecting epistasis, such as 2-SNP interactions, in genome-wide association studies (GWAS) is an important but time consuming operation. Consequently, GPUs have already been used to accelerate these studies, reducing the runtime for moderately-sized datasets to less than 1 hour. However, single-GPU approaches cannot perform large-scale GWAS in reasonable time. In this work we present multiEpistSearch, a tool to detect epistasis that works on GPU clusters. While CUDA is used for parallelization within each GPU, the workload distribution among GPUs is performed with Unified Parallel C+ + (UPC+ +), a novel extension of C+ + that follows the Partitioned Global Address Space (PGAS) model. multiEpistSearch is able to analyze large-scale datasets with 5 million SNPs from 10,000 individuals in less than 3 hours using 24 NVIDIA GTX Titans.
Type of Medium:
Online Resource
ISSN:
1094-3420
,
1741-2846
DOI:
10.1177/1094342015585846
Language:
English
Publisher:
SAGE Publications
Publication Date:
2015
detail.hit.zdb_id:
2017480-9
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