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.

• Planar and toroid maps.

• Both dense and sparse input data are supported.

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

• Integration with Databionic ESOM Tools.

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

Changes to previous version:

• Python, R, and MATLAB interfaces added.
• Learning rate parameter included.
• Linear and exponential cooling strategies added for radius and learning rate.
• CLI interface made more user-friendly.
• Default radius depends on both X and Y of the map.
• Bug fixes: CUDA build without MPI, best matching unit passing without MPI, coordinate order in best matching unit file.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux, Os X

Data Formats: Ascii, Libsvm, Esom

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

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