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.
