Parallel Knowledge Compilation Algorithms for EPCCL Theory

被引：0
|
作者：
Niu D.-D. [1 ]
Liu L. [1 ]
Lü S. [1 ,2 ]
机构：
[1] College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin
[2] Key Laboratory of Symbolic Computation and Knowledge Engineering, Jilin University, Ministry of Education, Changchun, 130012, Jilin
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2018年 / 46卷 / 03期
关键词：
EPCCL theory; Extension rule; Hyper extension rule; Knowledge compilation; Parallel compilation;
D O I：
10.3969/j.issn.0372-2112.2018.03.004
中图分类号：
学科分类号：
摘要：
Based on HER (hyper extension rule), we prove that the parallelization of merging multiple EPCCL (each pair contains complementary literal) is feasible, and the corresponding algorithm PUAE (parallel computing union of any number of EPCCL) is proposed. Through using the origin CNF formulae of EPCCL theories, another efficient merging algorithm imp-PUAE (improvement of PUAE) is proposed. UKCHER (computing union sets of maximum terms for knowledge compilation based on hyper extension rule) is a knowledge compilation algorithm for EPCCL, which can be parallelized. Based on above methods, we proposed two parallel knowledge compilation algorithm P-UKCHER (UKCHER with PUAE) and impP-UKCHER (UKCHER with imp-PUAE), which use the PUAE algorithm and imp-PUAE algorithm, respectively. Experimentally, although P-UKCHER does not improve the efficiency of UKCHER, the compilation quality is improved. In the best case, the compilation quality can be improved 4 times by P-UKCHER. The impP-UKCHER can improve the efficiency and compilation quality of UKCHER at the same time, and the compilation quality can also be improved 4 times in the best case. © 2018, Chinese Institute of Electronics. All right reserved.
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页码：537 / 543
页数：6
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