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somoclu : An Efficient Parallel Library for Self-Organizing Maps

2017; Foundation for Open Access Statistics; Volume: 78; Issue: 9 Linguagem: Inglês

10.18637/jss.v078.i09

1548-7660

Péter Wittek, Shi Chao Gao, Ik Soo Lim, Zhao Li,

Time Series Analysis and Forecasting

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.