Parallel and distributed algorithms for computational biology

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 th...

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Main Author: Liu, Weiguo
Other Authors: Bertil Schmidt
Format: Theses and Dissertations
Published: 2008
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Online Access:https://hdl.handle.net/10356/2474
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-24742020-11-10T08:45:01Z Parallel and distributed algorithms for computational biology Liu, Weiguo Bertil Schmidt School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems 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. DOCTOR OF PHILOSOPHY (SCE) 2008-09-17T09:03:52Z 2008-09-17T09:03:52Z 2006 2006 Thesis Liu, W. G. (2006). Parallel and distributed algorithms for computational biology. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/2474 10.32657/10356/2474 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems
spellingShingle DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems
Liu, Weiguo
Parallel and distributed algorithms for computational biology
description 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.
author2 Bertil Schmidt
author_facet Bertil Schmidt
Liu, Weiguo
format Theses and Dissertations
author Liu, Weiguo
author_sort Liu, Weiguo
title Parallel and distributed algorithms for computational biology
title_short Parallel and distributed algorithms for computational biology
title_full Parallel and distributed algorithms for computational biology
title_fullStr Parallel and distributed algorithms for computational biology
title_full_unstemmed Parallel and distributed algorithms for computational biology
title_sort parallel and distributed algorithms for computational biology
publishDate 2008
url https://hdl.handle.net/10356/2474
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