A Case Study on Pattern-Based Systems for High Performance Computational Biology

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@InProceedings{10.1109/IPDPS.2005.2,
  author =       "Weiguo Liu and Bertil Schmidt",
  title =        "A Case Study on Pattern-Based Systems for High
                 Performance Computational Biology",
  year =         "2005",
  booktitle =    "19th IEEE International Parallel and Distributed
                 Processing Symposium (IPDPS'05) - Workshop 7",
  pages =        "197b",
  publisher =    "IEEE Computer Society",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.hicomb.org/papers/HICOMB2005-04.pdf",
  DOI =          "doi:10.1109/IPDPS.2005.2",
  size =         "8 pages",
  abstract =     "Computational biology research is now faced with the
                 burgeoning number of genome data. The rigorous
                 postprocessing of this data requires an increased role
                 for high performance computing (HPC). Because the
                 development of HPC applications for computational
                 biology problems is much more complex than the
                 corresponding sequential applications, existing
                 traditional programming techniques have demonstrated
                 their inadequacy. Many high level programming
                 techniques, such as skeleton and pattern based
                 programming, have therefore been designed to provide
                 users new ways to get HPC applications without much
                 effort. However, most of them remain absent from the
                 mainstream practice for computational biology. In this
                 paper, we present a new parallel pattern-based system
                 prototype for computational biology. The underlying
                 programming techniques are based on generic
                 programming, a programming technique suited for the
                 generic representation of abstract concepts. This
                 allows the system to be built in a generic way at
                 application level and thus provides good extensibility
                 and flexibility. We show how this system can be used to
                 develop HPC applications for popular computational
                 biology algorithms and lead to significant runtime
                 savings on distributed memory architectures.",
}

Genetic Programming entries for Weiguo Liu Bertil Schmidt

Citations