Parallel Execution for Speeding Up Inductive Logic Programming Systems

  • Hayato Ohwada
  • Fumio Mizoguchi
Conference paper

DOI: 10.1007/3-540-46846-3_25

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1721)
Cite this paper as:
Ohwada H., Mizoguchi F. (1999) Parallel Execution for Speeding Up Inductive Logic Programming Systems. In: Arikawa S., Furukawa K. (eds) Discovery Science. DS 1999. Lecture Notes in Computer Science, vol 1721. Springer, Berlin, Heidelberg

Abstract

This paper describes a parallel algorithm and its implementation for a hypothesis space search in Inductive Logic Programming (ILP). A typical ILP system, Progol, regards induction as a search problem for finding a hypothesis, and an efficient search algorithm is used to find the optimal hypothesis. In this paper, we formalize the ILP task as a generalized branch-and-bound search and propose three methods of parallel executions for the optimal search. These methods are implemented in KL1, a parallel logic programming language, and are analyzed for execution speed and load balancing. An experiment on a benchmark test set was conducted using a shared memory parallel machine to evaluate the performance of the hypothesis search according to the number of processors. The result demonstrates that the statistics obtained coincide with the expected degree of parallelism.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Hayato Ohwada
    • 1
  • Fumio Mizoguchi
    • 1
  1. 1.Faculty of Sci. and Tech.Science University of Tokyo NodaChibaJapan

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