### Abstract

We have implemented a model-generation based parallel theorem prover in KL1 on a parallel inference machine, PIM. We have developed several techniques to improve the efficiency of forward reasoning theorem provers based on lazy model generation. The tasks of the model-generation based prover are the generation and testing of atoms to be the elements of a model for the given theorem. The problem with this method is the explosion in the number of generated atoms and in the computational cost in time and space, incurred by the generation processes. Lazy model generation is a new method that avoids the generation of unnecessary atoms that are irrelevant to obtaining proofs, and to provide flexible control for the efficient use of resources in a parallel environment. With this method we have achieved a more than one-hundred-fold speedup on a PIM consisting of 128 PEs.

Original language | English |
---|---|

Title of host publication | Automated Deduction — CADE-11 - 11 th International Conference on Automated Deduction, Proceedings |

Publisher | Springer Verlag |

Pages | 776-780 |

Number of pages | 5 |

Volume | 607 LNAI |

ISBN (Print) | 9783540556022 |

Publication status | Published - Jan 1 1992 |

Externally published | Yes |

Event | 11th International Conference on Automated Deduction, CADE, 1992 - Saratoga Springs, United States Duration: Jun 15 1992 → Jun 18 1992 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|

Volume | 607 LNAI |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 11th International Conference on Automated Deduction, CADE, 1992 |
---|---|

Country | United States |

City | Saratoga Springs |

Period | 6/15/92 → 6/18/92 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Automated Deduction — CADE-11 - 11 th International Conference on Automated Deduction, Proceedings*(Vol. 607 LNAI, pp. 776-780). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 607 LNAI). Springer Verlag.

**MGTP : A parallel theorem prover based on lazy model generation.** / Hasegawa, Ryuzo; Koshimura, Miyuki; Fujita, Hiroshi.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Automated Deduction — CADE-11 - 11 th International Conference on Automated Deduction, Proceedings.*vol. 607 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 607 LNAI, Springer Verlag, pp. 776-780, 11th International Conference on Automated Deduction, CADE, 1992, Saratoga Springs, United States, 6/15/92.

}

TY - GEN

T1 - MGTP

T2 - A parallel theorem prover based on lazy model generation

AU - Hasegawa, Ryuzo

AU - Koshimura, Miyuki

AU - Fujita, Hiroshi

PY - 1992/1/1

Y1 - 1992/1/1

N2 - We have implemented a model-generation based parallel theorem prover in KL1 on a parallel inference machine, PIM. We have developed several techniques to improve the efficiency of forward reasoning theorem provers based on lazy model generation. The tasks of the model-generation based prover are the generation and testing of atoms to be the elements of a model for the given theorem. The problem with this method is the explosion in the number of generated atoms and in the computational cost in time and space, incurred by the generation processes. Lazy model generation is a new method that avoids the generation of unnecessary atoms that are irrelevant to obtaining proofs, and to provide flexible control for the efficient use of resources in a parallel environment. With this method we have achieved a more than one-hundred-fold speedup on a PIM consisting of 128 PEs.

AB - We have implemented a model-generation based parallel theorem prover in KL1 on a parallel inference machine, PIM. We have developed several techniques to improve the efficiency of forward reasoning theorem provers based on lazy model generation. The tasks of the model-generation based prover are the generation and testing of atoms to be the elements of a model for the given theorem. The problem with this method is the explosion in the number of generated atoms and in the computational cost in time and space, incurred by the generation processes. Lazy model generation is a new method that avoids the generation of unnecessary atoms that are irrelevant to obtaining proofs, and to provide flexible control for the efficient use of resources in a parallel environment. With this method we have achieved a more than one-hundred-fold speedup on a PIM consisting of 128 PEs.

UR - http://www.scopus.com/inward/record.url?scp=85029578900&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85029578900&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85029578900

SN - 9783540556022

VL - 607 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 776

EP - 780

BT - Automated Deduction — CADE-11 - 11 th International Conference on Automated Deduction, Proceedings

PB - Springer Verlag

ER -