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paper

Somoclu: An Efficient Parallel Library for Self-Organizing Maps

arXiv:1305.1422 · doi:10.18637/jss.v078.i09

Abstract

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.

26 pages, 9 figures. The code is available at https://peterwittek.github.io/somoclu/