MULTITHREADING BIOINFORMATICS SOFTWARE WITH OPENMP: SNPHAP CASE STUDY

摘要

This paper presents a parallelization framework for inferring 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, multithreading, 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 machine. The results show that our framework can significantly 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 maximum speedup can be achieved when the number of parallel threads equals to the number of physical cores.