Description:

Somoclu is a C++ tool for training self-organizing maps on large data sets using a massively parallel resources. It relies on OpenMP for multicore execution and it builds on MPI for distributing the workload across the nodes of the 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 use in data analysis. The code is released under GNU GPLv3 licence.

Key features:

• Fast execution by parallelization: OpenMP, MPI, and CUDA are supported.

• Python, R, and MATLAB interfaces for the dense multicore CPU kernel.

• Planar and toroid maps.

• Rectangular and hexagonal grids.

• Gaussian and bubble neighborhood functions.

• Both dense and sparse input data are supported.

• Large emergent maps of several hundred thousand neurons are feasible.

• Integration with Databionic ESOM Tools.

Changes to previous version:

• Changed: In-place codebook updates when compiled without MPI. This improves update speed and substantially cuts memory use.
• Changed: Compatible with Visual Studio 15.
• Fixed: The BMUs returned after training were from before the last epoch. Now another round of BMU search is done.
• Fixed: Training can continue on the same data in the Python wrapper.
• Fixed: GPU memory allocation problem on Windows.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux, Windows, Os X

Data Formats: Ascii, Libsvm, Esom

Tags: Cuda, Self Organizing Maps, Mpi, Esom, Openmp

Archive: download here

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