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Multithreading bioinformatics software with OpenMP: SNPHAP case study
Author(s)
Date Issued
December 1, 2010
Type
Conference Paper
Abstract
This paper presents a parallelization framework for infer- ring haplotypes using an expectation maximization (EM) algorithm. Our framework utilizes GProf profiling tool, OpenMP library, and ompP profiling tool to parallelize the algorithm by determining the hotspot functions, mul- tithreading, and executing them on the Multi-core CPUs. In our experiments, we choose the SNPHAP program for this case study and run it on an 8-core Xeon Linux ma- chine. The results show that our framework can signifi- cantly speedup up to 214% on a large data set with 151 loci of a 10,000 data samples. In addition, deep profiles of multithreaded SNPHAP support our discovery that maxi- mum speedup can be achieved when the number of parallel threads equals to the number of physical cores.
Citation
Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems, 17-24, 2010
