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    A multithreading methodology with OpenMP on multi-core CPUs: SNPHAP case study
    (2011-08-12)
    Ranok, Udom
    ;
    Kittitornkun, Surin
    ;
    Tongsima, Sissades
    This paper presents a multithreading methodology for OpenMP library. The methodology can be applied to convert existing sequential and demanding programs to be multithreaded programs with OpenMP running on the Multi-core CPUs. In our experiments, we apply this methodology to SNPHAP, which is one of the best haplotype inference bioinformatics program in terms of speed. The results show that our significant achievement is the maximum Speedup 316% for Intel Xeon E5405 (8-core 2.0 GHz) and 410% for Intel Xeon E5520 (8-Core with HyperThreading 2.66GHz) faster than its own sequential version. © 2011 IEEE.
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    Multithreading bioinformatics software with OpenMP: SNPHAP case study
    (2010-12-01)
    Ranok, Udom
    ;
    Kittitornkun, Surin
    ;
    Tongsima, Sissades
    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.