Abstract
We describe here the RAIN project, aimed at demonstrating the use of High Performance Computing and Networking technologies in neural network applications for industry and medicine. The target architecture of the demonstrators is a workstation cluster: a choice suggested by the cost-effectiveness of this architecture. In order to manage both the cluster and the applications running on it, we built a Java-based interface that can be executed by any Java-enhanced browser.
Preview
Unable to display preview. Download preview PDF.
References
Anderson, E.C., Dongarra, J.: Performance of LAPACK: A Portable Library of Numerical Linear Algebra Routines. Proc. of the IEEE 81 (1993) 1094–1101
Anguita, D., Parodi, G., Zunino, R.: An Efficient Implementation of BP on RISCbased Workstations. Neurocomputing 6 (1994) 57–65
Anguita, D., DaCanal, A., DaCanal, W., Falcone, A., Scapolla, A.M.: On the distributed implementation of back-propagation. Proc. of ICANN 1994, 1376–1379
Corana, A., Rolando, C., Ridella, S.: A Highly Efficient Implementation of Back-propagation Algorithm on SIMD Computers. High Performance Computing, J.-L.Delhaye and E.Gelenbe (Eds.) (1989) 181–190
Corana, A., Rolando, C., Ridella, S.: Use of Level 3 BLAS Kernels in Neural Networks: The Back-propagation algorithm. Parallel Computing 89 (1990) 269–274
Frey, P.W., Slate, D.J.: Letter Recognition Using Holland-style Adaptive Classifiers. Machine Learning 6 (1991) 161–182
Geist, A. et al.: PVM: Parallel Virtual Machine, a Users's Guide and Tutorial for Networked Parallel Computing. The MIT Press (1994)
Hjorth, J.S.: Computer Intensive Statistical Methods: Validation Model Selection and Bootstrap. Chapman & Hall (1994)
Karp, A.H., Lusk, E., Bailey, D.H.: 1997 Gordon Bell Prize Winners. IEEE Computer 31 (1998) 86–92
Marsh, A.: EUROMED — Combining WWW and HPCN to Support Advanced Medical Imaging, International Conference and Exhibition HPCN Europe 1997, Vienna, pp. 95–104
Murphy, P.M., Aha, D.W.: UCI Repository of machine learning databases http://www.ics.uci.edu/-mlearn/MLRepository.html. Irvine, CA: University of California, Department of Information and Computer Science (1994)
Panda, D.K. and Ni, L.M.: Special Issue on Workstation Clusters and Network-Based Computing. J. of Parallel and Distributed Computing 40 (1997)
Raudys, S.J. and Jain, A.K.: Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners. IEEE Trans. on Pattern Analysis and Machine Intelligence 13 (1991) 252–263
Rovetta S., Zunino R., Buffrini L., Rovetta G.: Prototyping neural networks learn Lyme borreliosis. 8th IEEE Symp. on Computer-Based Medical Systems (1995)
Rumelhart, D.E. and McClelland, J.L.: Parallel Distributed Processing Vol. 1. MIT Press (1986)
Thurman, D.:http://www.isye.gatech.edu/JavaPVM/
Wang, C., Venkatesh, S.S., Judd, J.S.: Optimal Stopping and Effective Machine Complexity in Learning. Advances in Neural Information Processing Systems 6 (1994) 303–310
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Anguita, D., Boni, A., Chirico, M., Giudici, F., Scapolla, A.M., Parodi, G. (1998). High performance neurocomputing: Industrial and medical applications of the RAIN system. In: Sloot, P., Bubak, M., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1998. Lecture Notes in Computer Science, vol 1401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0037130
Download citation
DOI: https://doi.org/10.1007/BFb0037130
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64443-9
Online ISBN: 978-3-540-69783-1
eBook Packages: Springer Book Archive