This paper presents an implementation of multi-dimensional Self-Organizing Maps on a scalable SIMD structure of a CNAPS computer with up to 512 parallel ...
Multi-Dimensional Self-Organizing Maps on Massively Parallel Hardware. Udo Seiffert and Bernd Michaelis. Institute for Electronics, Signal Processing and ...
Although available (sequential) computer hardware is very powerful nowadays, the implementation of artificial neural networks on massively parallel hardware ...
In this paper, we present a fully parallel SOM hardware architecture, optimized for high-throughput, by reducing the SOM data processing cycle.
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This paper describes two variants of the Kohonen's self-organizing feature map (SOFM) algorithm. Both variants update the weights only after presentation of ...
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A hardware accelerator for self-organizing feature maps is presented. We have developed a massively parallel architecture that, on the one hand, allows a ...
Abstract somoclu is a massively parallel tool for training self-organizing maps on large data sets written in C++. It builds on OpenMP for multicore ...
This paper describes the architecture design of novel massively parallel self-organizing map (SOM) neural networks. The proposed architecture, referred to ...
Self-Organizing Maps (SOMs) are extensively used for data clustering and dimensionality reduction. However, if applications are to fully benefit from SOM ...
Michaelis, Multi-dimensional Self-Organizing Maps on massively par- allel hardware, In: N. Allinson et al. (Eds): Advances in Self-Organising Maps (London:.