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Parallel matching and sorting with TACO's distributed collections-a case study from molecular biology research

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2 Author(s)
J. Nolte ; Real World Comput. Partnership, Ibaraki, Japan ; P. Horton

TACO is a template library that implements higher-order parallel operations on distributed object sets by means of reusable topology classes and C++ function templates. We discuss an experimental application that exploits TACO's distributed object groups and collective operations for computing the similarity between groups of molecular sequences, a computationally intensive core problem in molecular biology research. In particular we show how TACO's distributed collections can be conveniently combined with well known concepts found in the C++ standard template library (STL) to solve matching and sorting problems effectively on distributed hardware platforms. The resulting implementation is concise and gives excellent parallel performance on PC- and workstation clusters

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High-Performance Distributed Computing, 2000. Proceedings. The Ninth International Symposium on

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