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Abstract: This paper investigates the architectural requirements for simulating neural networks using massively parallel multiprocessors. First, we model the connectivity patterns in large neural networks. A distributed processor/memory organization is developed for efficiently simulating asynchronous, value-passing connectionist models. Based on the network connectivity and mapping policy, we estimate the volume of messages that need to be exchanged among physical processors for simulating the weighted... (Update)
Context of citations to this paper: More
.... more homogeneity among its constituent neurons, has higher internal connectivity, and or is used to represent a particular hypothesis [GH89]. Well known examples include the neuronal groups of Edelman [Ede87] and the neural clusters used for distortion invariant pattern...
...networks, the adjacent layers are completely connected. For schemes that primarily deal with randomly sparse networks, see [7, 26, 27, 28, 29]. Parallelization schemes for BP can be classified into three broad categories: network partitioning schemes, pattern partitioning...
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BibTeX entry: (Update)
J. Ghosh and K. Hwang. Mapping neural networks onto message-passing multicomputers. J. of Parallel and Distributed Computing, 6:291--330, April, 1989. http://citeseer.ist.psu.edu/ghosh89mapping.html More
@article{ ghosh89mapping,
author = "J. Ghosh and K. Hwang",
title = "Mapping Neural Networks onto Message-Passing Multicomputers",
journal = "Journal of Parallel and Distributed Computing",
volume = "6",
number = "2",
publisher = "Academic Press",
address = "San Diego, New York, Boston, London, Syndey, Tokyo, Toronto",
pages = "291--330",
year = "1989",
url = "citeseer.ist.psu.edu/ghosh89mapping.html" }
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