Batched Evaluation of Linear Tabled Logic Programs

• Tipo: Artigo em Revista Científica Internacional
• Data: 2013

Autores

Miguel Areias (Autor) Outra; Ricardo Rocha (Autor) FCUP

Revista

Título: Computer Science and Information Systems

Vol. 10

Páginas: 1775-1797

ISSN: 1820-0214

Editora: ComSIS Consortium

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-006-JVC

DOI: 10.2298/csis121129066a

Abstract (EN): Logic Programming languages, such as Prolog, provide a high-level, declarative approach to programming. Despite the power, flexibility and good performance that Prolog systems have achieved, some deficiencies in Prolog's evaluation strategy - SLD resolution - limit the potential of the logic programming paradigm. Tabled evaluation is a recognized and powerful technique that overcomes SLD's susceptibility in dealing with recursion and redundant sub-computations. In a tabled evaluation, there are several points where we may have to choose between different tabling operations. The decision on which operation to perform is determined by the scheduling algorithm. The two most successful tabling scheduling algorithms are local scheduling and batched scheduling. In previous work, we have developed a framework, on top of the Yap Prolog system, that supports the combination of different linear tabling strategies for local scheduling. In this work, we propose the extension of our framework to support batched scheduling. In particular, we are interested in the two most successful linear tabling strategies, the DRA and DRE strategies. To the best of our knowledge, no other Prolog system supports both strategies simultaneously for batched scheduling. Our experimental results show that the combination of the DRA and DRE strategies can effectively reduce the execution time for batched evaluation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 23