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CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms
Author(s) -
Kai Kohlhoff,
Marc H. Sosnick,
William Hsu,
Vijay S. Pande,
Russ B. Altman
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr386
Subject(s) - computer science , cluster analysis , cuda , parallel computing , massively parallel , toolbox , source code , software , algorithm , operating system , programming language , artificial intelligence
Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created Clustering Algorithms for Massively Parallel Architectures, Including GPU Nodes (CAMPAIGN), a central resource for data clustering algorithms and tools that are implemented specifically for execution on massively parallel processing architectures.

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