Abstract
The Edinburgh Concurrent Supercomputer Project is built around a Meiko Computing Surface, with presently some 400 floating point transputers and 1.6 Gbytes of memory. The first part of this paper gives a brief overview of the Project’s origins and status. In the second part we review work in neural network models, including analogue neurons for image restoration, studies of texture discrimination and protein structure predictions using a multi-layer perceptron simulator. The problem of optimization of machine topology is also discussed in the context of irregular graphs and genetic algorithms.
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Norman, M.G. et al. (1990). Neural Network Applications in the Edinburgh Concurrent Supercomputer Project. In: Soulié, F.F., Hérault, J. (eds) Neurocomputing. NATO ASI Series, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76153-9_24
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DOI: https://doi.org/10.1007/978-3-642-76153-9_24
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