Abstract
The architecture of the Connection Machine system is particularly appropriate for large database applications. The Connection Machine system consists of 65,536 processors, each with its own memory, coupled by a high speed communications network. In large database applications, individual data elements are stored in separate processors and are operated on simultaneously. This paper examines two applications of this technology. The first, which will be examined in the greatest detail, is the use of the Connection Machine System for document retrieval. The second topic is the application of the Connection Machine to associative memory or content addressable memory tasks. This ability has been put to use in a method called “memory-based reasoning” which can produce expert system-like behavior from a database of records of earlier decisions. These classes of applications both scale well; the application of supercomputer power to such problems offers unprecedented functionality and opportunities.
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References
Blair, D.C., and M.E. Maron. “An Evaluation of Retrieval Effectiveness for a Full-Text Document-Retrieval System”. Communications of the ACM, 28 (1985) 3, pp. 285–299.
Stanfill, C., and B. Kahle. “Parallel Free Text Search on the Connection Machine System.” Communications of the ACM, 29 (1986) 12, PP. 1229–1239.
Thinking Machines Corporation, Introduction to Data Level Parallelism. Cambridge, MA, April, 1986.
Hillis, D. The Connection Machine. Cambridge, MA. MIT Press, 1985.
C. Stanfill, R. Thau, and D.L. Waltz, “A Parallel Indexed Algorithm for Information Retrieval”, Proceedings of the 12th International Conference on Research and Development in Information Retrieval (SIGIR-89), Cambridge, MA, June 26–28, 1986.
Stanfill, C. and D.L. Waltz. “Toward Memory-Based Reasoning”, Communications of the ACM, 29 (1986) 12, pp. 1213–1228.
Sejnowski, T.J. and C.R. Rosenberg. “NETtalk: A Parallel Network that Learns to Read Aloud”. The John Hopkins University Electrical Engineering and Computer Science Tecnical Report JHU/EECS-86.
Merriam Webster’s Pocket Dictionary, 1974.
Stanfill, C. “Memory-Based Reasoning Applied to English Pronunciation”. Porceedings, Sixth National Conference on Artificial Intelligence (AAAI -87), Seattle, Washington, July 13–17, 1987.
Zhang, X., D.L. Waltz, and J.P. Mesirov, “Protein Structure Prediction by a Data-level Parallel Algorithm”, to appear in Proc. of Supercomputing-89. Nov. 1989, Reno, NV.
Atkeson, C., “Roles of Knowledge in Motor Learning”, Massachusetts Institute of Technology Technical Report 942, Sept. 1986.
Zhang, X., M. McKenna, J.P. Mesirov, and D.L. Waltz, “An Efficient Implementation of the Backpropagation Algorithm on the CM-2”, to appear in Proc. of NIPS Conf.. Nov. 1989, Butler, Co.
Singer, A., paper forthcoming.
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© 1990 Springer-Verlag Berlin Heidelberg
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Waltz, D., Stanfill, C. (1990). Very Large Database Applications of the Connection Machine System. In: Kowalik, J.S. (eds) Supercomputing. NATO ASI Series, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75771-6_22
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DOI: https://doi.org/10.1007/978-3-642-75771-6_22
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