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International Conference on Artificial Neural Networks

ICANN 1997: Artificial Neural Networks — ICANN'97 pp 1235–1240Cite as

The SAND neurochip and its embedding in the MiND system

  • Part VIII: Implementations
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

Abstract

The system MiND (Multipurpose integrated Neural Device) is a tool for the development of artificial neural network applications which integrates hardware and software components. It includes a PCI neuro-board with up to four SAND (Simple Applicable Neural Device) neuro-chips. The neuro-board accelerates feedforward networks, Radial-Basis-Function networks, and Kohonen feature maps. There are several simple to use software layers for exploiting the neuro-board. At the bottom, there is the driver's C interface. Secondly, a number of C++ network classes are built on the C-drivers. Thirdly, comfortable simulators with graphical interfaces base on the C++ classes. These stein from a pool of “predefined” simulators provided by the MiND system. Each simulator is constituted by a network definition written in the neural network description language CONNECT, and by an interface definition script. The interface definition is based on a C++ network class generated from the CONNECT definition, and on abstract graphical user interface classes. A user can develop own network or interface definitions. Also, the C++ network classes can be exported for integration into custom applications.

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References

  1. H. Gemmeke, W. Eppler, T. Fischer, A. Menchikov, S. Neusser: Neural Network Chips for Trigger Purposes in High Energy Physics. Proceedings of Nuclear Science Symposium (NSS) (1996)

    Google Scholar 

  2. D. Hammerstrom, W. Henry, M. Kuhn: A Neurocomputer for Neural-Network Applications. Parallel Digital Implementations of Neural Networks (K.W. Przytula, V.K. Prasanna, eds.), Prentice Hall (1993) 107–138

    Google Scholar 

  3. G. Kock, N.B. Šerbedžija: Artificial Neural Networks: From Compact Descriptions to C++. Proc. of the Int. Conf. on Artificial Neural Networks (1994) 1372–1375

    Google Scholar 

  4. G. Kock, N.B. Šerbedžija: Simulation of Artificial Neural Networks. Systems Analysis — Modelling — Simulation (SAMS) 27 (1996) 15–59

    Google Scholar 

  5. A. König: Survey and Current Status of Neural Network Hardware. Proc. of the Int. Conf. on Artificial Neural Networks (1995) 391–410

    Google Scholar 

  6. J.M.J. Murre: Neurosimulators. The Handbook of Brain Theory and Neural Networks (M.A. Arbib, Ed.), MIT Press (1995) 634–639

    Google Scholar 

  7. U. Ramacher: SYNAPSE — A Neurocomputer that Syntheses Neural Algorithms on a Parallel Engine. Journal of Parallel and Distributed Computing 14 (1992) 306–318

    Google Scholar 

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Author information

Authors and Affiliations

  1. Forschungszentrum Karlsruhe (HPE), POB 3640, 76021, Karlsruhe, Germany

    T. Fischer, W. Eppler & H. Gemmeke

  2. GMD FIRST, Rudower Chaussee 5, 12489, Berlin, Germany

    G. Kock

  3. INCO Systeme GmbH, Stöhrerstrasse 17, 04347, Leipzig, Germany

    T. Becher

Authors
  1. T. Fischer
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  2. W. Eppler
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  3. H. Gemmeke
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  4. G. Kock
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  5. T. Becher
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Fischer, T., Eppler, W., Gemmeke, H., Kock, G., Becher, T. (1997). The SAND neurochip and its embedding in the MiND system. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020320

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  • DOI: https://doi.org/10.1007/BFb0020320

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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