Somoclu: An Efficient Parallel Library for Self-Organizing Maps

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  • Peter Wittek
    University of Boras
  • Shi Chao Gao
    Tsinghua University
  • Ik Soo Lim
  • Li Zhao
    Tsinghua University
Somoclu is a massively parallel tool for training self-organizing maps on large data sets written in C++. It builds on OpenMP for multicore execution, and on MPI for distributing the workload across the nodes in a cluster. It is also able to boost training by using CUDA if graphics processing units are available. A sparse kernel is included, which is useful for high-dimensional but sparse data, such as the vector spaces common in text mining workflows. Python, R and MATLAB interfaces facilitate interactive use. Apart from fast execution, memory use is highly optimized, enabling training large emergent maps even on a single computer.
Original languageEnglish
Pages (from-to)1-21
JournalJournal of Statistical Software
Issue number9
Publication statusPublished - 9 Jun 2017

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