Open Accessgcn.MOPS: Accelerating cn.MOPS with GPU
Author(s) -
Moh A. Alkhamis
Publication year - 2019
Publication title -
epic series in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 2398-7340
DOI - 10.29007/hb5r
Subject(s) - speedup , computer science , parallel computing , central processing unit , cpu shielding , multi core processor , acceleration , process (computing) , single core , parallelism (grammar) , computer hardware , operating system , physics , classical mechanics
cn.MOPS is a frequently cited model-based algorithm used to quantitatively detect copy-number variations in next-generation, DNA-sequencing data. Previous work has implemented the algorithm as an R package and has achieved considerable yet limited performance improvement by employing multi-CPU parallelism (maximum achievable speedup was experimentally determined to be 9.24). In this paper, we propose an alternative mechanism of process acceleration. Using one CPU core and a GPU device in the proposed solution, gcn.MOPS, we achieve a speedup factor of 159 and reduce memory usage by more than half compared to cn.MOPS running on one CPU core.