Parallel Sequence Matching with TACO's Distributed Object Groups – A Case Study from Molecular Biology

  • Authors:

  • Jörg Nolte;Paul Horton

  • Affiliations:

  • Real World Computing Partnership, Tsukuba Mitsui Bldg. 16F, 1-6-1 Takezono, Tsukuba 305-0032, Ibaraki, Japan;Real World Computing Partnership, Tsukuba Mitsui Bldg. 16F, 1-6-1 Takezono, Tsukuba 305-0032, Ibaraki, Japan

  • Venue:
  • Cluster Computing
  • Year:
  • 2001

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Abstract

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. In this paper 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.