Somoclu: An Efficient Parallel Library for Self-Organizing Maps
Research output: Contribution to journal › Article › peer-review
Electronic versions
Documents
- 1305.1422v3
Accepted author manuscript, 1.44 MB, PDF document
Licence: CC BY Show licence
- 2017 somoclu an efficient parallel library
Final published version, 1.7 MB, PDF document
Licence: CC BY Show licence
DOI
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1-21 |
| Journal | Journal of Statistical Software |
| Volume | 78 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 9 Jun 2017 |
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