libNMF -- A Library for Nonnegative Matrix Factorization

Authors

  • Andreas Janecek
  • Stefan Schulze Grotthoff
  • Wilfried N. Gansterer

Keywords:

Nonnegative matrix factorization, low-rank approximation, evaluation, NMF library, NMF software

Abstract

We present libNMF -- a computationally efficient high performance library for computing nonnegative matrix factorizations (NMF) written in C. Various algorithms and algorithmic variants for computing NMF are supported. libNMF is based on external routines from BLAS (Basic Linear Algebra Subprograms), LAPack (Linear Algebra package) and ARPack, which provide efficient building blocks for performing central vector and matrix operations. Since modern BLAS implementations support multi-threading, libNMF can exploit the potential of multi-core architectures. In this paper, the basic NMF algorithms contained in libNMF and existing implementations found in the literature are briefly reviewed. Then, libNMF is evaluated in terms of computational efficiency and numerical accuracy and compared with the best existing codes available. libNMF is publicly available at http://rlcta.univie.ac.at/software.

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Author Biographies

Andreas Janecek

University of Vienna, Austria
Faculty of Computer Science
Research Lab Computational Technologies and Applications
Lenaugasse 2/8
1080-Vienna, Austria

Stefan Schulze Grotthoff

University of Vienna, Austria
Faculty of Computer Science
Research Lab Computational Technologies and Applications
Lenaugasse 2/8
1080-Vienna, Austria

Wilfried N. Gansterer

University of Vienna, Austria
Faculty of Computer Science
Research Lab Computational Technologies and Applications
Lenaugasse 2/8
1080-Vienna, Austria

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Published

2012-01-26

How to Cite

Janecek, A., Grotthoff, S. S., & Gansterer, W. N. (2012). libNMF -- A Library for Nonnegative Matrix Factorization. Computing and Informatics, 30(2), 205–224. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/161

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Section

Special Section Articles