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A parallel architecture for signal understanding through inference on uncertain data

  • P. G. Bosco
  • E. Giachin
  • G. Giandonato
  • G. Martinengo
  • C. Rullent
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 258)

Abstract

This paper describes an architecture for rule-based interpretation of uncertain data, which is currently under development at our labs. Inference on uncertain input facts is a central topic in Al, with application, e.g., to the syntactic-semantic layers of speech understanding systems. The severe requirements of real-time applications dictate a parallel approach to this problem. The description covers the main aspects related to parallelism and communication at the three levels which have interacted in the design of this architecture: the hardware machine, a highly-parallel homogeneous structure of processing element — memory pairs interconnected by a fast packet-switching network; the programming language, which is a dialect of Lisp augmented with asynchronous message passing primitives; the inferential algorithm, which unifies goal-driven and data-driven strategies under a score-guided search control. Rules are mapped into a set of processes which cooperate by exchanging, via the primitives and the network mentioned above, messages corresponding to succinct representations of intermediate deductions.

Keywords

Uncertain Data Physical Machine Local Scheduler Deductive Process Processing Element Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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5 References

  1. [1]
    R. Pieraccini, F. Raineri, A. Giordana, P. Laface, A. Kaltenmeier, H. Mangold, "Algorithms for Speech Data-reduction and Recognition", Proceedings of the 1985 ESPRIT Technical Week, Brussels, Sept. 1985.Google Scholar
  2. [2]
    C.L. Seitz, "Concurrent VLSI Architectures", IEEE Trans. on Computers, Vol. C-33, No.12 Dec. 1984, pp. 1247–1265.Google Scholar
  3. [3]
    Arvind, R. A. Iannucci, "Two Fundamental Issues in Multiprocessing", Computation Structures Group Memo 226-3, Lab. for Comp. Science, MIT, Cambridge, Aug. 1985Google Scholar
  4. [4]
    C. Whitby-Strevens, "The Transputer", Proceedings of the 12th Annual Inter. Symp. on Computer Architeture, Boston, Mass., June 1985, pp. 292–300.Google Scholar
  5. [5]
    F. W. Burton, M. M. Huntbach, "Virtual Tree Architectures", IEEE Trans. on Computers, Vol.C-33, No. 3, March 1984, pp. 278–280.Google Scholar
  6. [6]
    B. W. Wah, G. Li, C. F. Yu, "Multiprocessing of Combinatorial Search Problems" IEEE Computer, June 1985, pp.93–108.Google Scholar
  7. [7]
    J. Chailloux, M. Devin, J. Hullot, "LeLisp, a Portable and Efficient LISP System" Proc. of the 1984 ACM Symp. on LISP and Functional Programming, Austin, Texas, Aug. 1984,pp.113–122.Google Scholar
  8. [8]
    D.D.Corkill, V.R.Lesser, E.Hudlicka, "Unifying data-directed and goal-directed control an example and experiments", Proc. of the AAAI '82, Pittsburgh, PA, pp.143–147.Google Scholar
  9. [9]
    W. A. Woods, "Optimal Search Strategies for Speech Understanding Control", Artificial Intelligence 18, 1982, pp. 295–236.Google Scholar
  10. [10]
    L. D. Erman, F. Hayes-Roth, V. R. Lesser, D. Raj Reddy, "The Hearsay-II Speech Understanding System: Integrating Knowledge to Resolve Uncertainty", ACM Computing Survey 12, 1980, pp. 213–253.Google Scholar
  11. [11]
    G. Giandonato, G. Sofi, "Parallelizing Prolog-based Inference Engines", ESPRIT Project N. 26, Subtask T4.3 Techn. Rep., Sept. 1986.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • P. G. Bosco
    • 1
  • E. Giachin
    • 1
  • G. Giandonato
    • 1
  • G. Martinengo
    • 1
  • C. Rullent
    • 1
  1. 1.CSELT Centro Studi e Laboratori Telecomunicazioni S.p.ATORINOITALY

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