Abstract
This paper describes the design and implementation of a development environment for matrix based neurocomputers. A new virtual machine language provides a wide range of matrix operations and device-related input/output communications. Virtual machines may be implemented entirely on conventional workstations or may use matrix-based neurocomputer hardware. To assist in algorithm development and debugging, the virtual machine is able to generate monitoring messages. A graphical interface is used to view the workings of one or more virtual machines. The user interface allows a range of display techniques to be associated with VML scalar and matrix variables. Virtual machines and monitoring processes run under the control of a central scheduler. All communications are implemented using a message based protocol. This environment is currently being used to develop a wide range of applications.
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Angeniol, B., Fogelman, F., Marcadé, E., Pimont, J.M., Simon, C., Skoda, F., Archas, Y., Bru, B., Caillaud, C., Makram, S., Zorer, J.L., Ramacher, U., Anlauf, J., Recce, M., Taylor, J. (1992) The Galatea Project, proceedings NeuroNimes '92
Azema-Barac, M., Hewetson, M., Recce, M., Taylor, J.C., Treleaven, P.C., and Vellasco, M.M.B.R. (1991) PYGMALION neural network programming environment, Int. Neural Network Conference, Paris, France.
Duranton, M. and Sirat, J. (1990) Learning on VLSI: A General-Purpose Digital Neurochip, Philips Journal of Research, vol. 45, no. 1, pp. 1–17, 1990
Ramacher, U. and Raab, W. (1990) Fine-Grain System Architectures for Systolic Emulation of Neural Algorithms, Int. Conf. on Application Specific Array Processors, Princeton (USA), September, 1990.
Recce,M.L., Rocha,P.V. and Treleaven,P.C. (1992) Neural network programming environments, 1237–1244, Artificial Neural Networks 2 (Eds. Aleksander,J. and Taylor,J.) Elsevier Science Publishers B.V.
Recce, M. and Treleaven, P.C. (1988) Parallel architectures for neural computers, 487–495, Neural Computers (Eds. Eckmiller, R. and v.d. Malsburg, C.), Springer-Verlag Berlin Heidelberg.
Theeten, J.B., Duranton, M., Mauduit, N., Sirat, J.A. (1990) The L-Neuro-Chip: A Digital VLSI With On-Chip Learning Mechanism, Proc. Int. Neural Network Conf., pp 593–596, Kluwer Academic Publishers, July 1990.
Vellasco, M.M.B.R. (1991) Phd thesis, University College London, London
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© 1993 Springer-Verlag Berlin Heidelberg
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Taylor, J.C., Recce, M.L., Mangat, A.S. (1993). Flexible operating environment for matrix based neurocomputers. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_177
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DOI: https://doi.org/10.1007/3-540-56798-4_177
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