The Self-Organizing Maps (SOMs) are popular artificial neural networks that are often used for data analyses through clustering and visualisation. SOM's mathematical model is inherently parallel. However, many implementations have not successfully exploited its parallelism because previous attempts often required cluster-like infrastructures. This article presents the parallel implementation of SOMs, particularly the batch map variant using Graphics Processing Units (GPUs) through the use of Open Computing Language (OpenCL). © 2010 Springer-Verlag.
CITATION STYLE
Takatsuka, M., & Bui, M. (2010). Parallel batch training of the self-organizing map using OpenCL. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6444 LNCS, pp. 470–476). https://doi.org/10.1007/978-3-642-17534-3_58
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