somoclu: An Efficient Parallel Library for Self-Organizing Maps. 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.
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References in zbMATH (referenced in 2 articles , 1 standard article )
Showing results 1 to 2 of 2.
- Ron Wehrens; Johannes Kruisselbrink: Flexible Self-Organizing Maps in kohonen 3.0 (2018) not zbMATH
- Peter Wittek and Shi Gao and Ik Lim and Li Zhao: somoclu: An Efficient Parallel Library for Self-Organizing Maps (2017) not zbMATH