Péter Szeredi

The Aurora or-parallel Prolog system

Aurora is a prototype or-parallel implementation of the full Prolog language for shared-memory multiprocessors, developed as part of an informal research collaboration known as the “Gigalips Project”. It currently runs on Sequent and Encore machines. It has been constructed by adapting Sicstus Prolog, a fast, portable, sequential Prolog system. The techniques for constructing a portable multiprocessor version follow those pioneered in a predecessor system, ANL-WAM. The SRI model was adopted as the means to extend the Sicstus Prolog engine for or-parallel operation. We describe the design and main implementation features of the current Aurora system, and present some experimental results. For a range of benchmarks, Aurora on a 20-processor Sequent Symmetry is 4 to 7 times faster than Quintus Prolog on a Sun 3/75. Good performance is also reported on some large-scale Prolog applications.

Efficient description logic reasoning in prolog: The dlog system

Traditional algorithms for description logic (DL) instance retrieval are inefficient for large amounts of underlying data. As DL is becoming more and more popular in areas such as the Semantic Web and information integration, it is very important to have systems which can reason efficiently over large data sets. In this paper we present an approach to transform DL axioms, formalised in the

Flexible scheduling of or-parallelism is Aurora: the Bristol scheduler

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The Application of Prolog to the Development of QA and DBM Systems

DL language, into a Prolog program under the unique name assumption. This transformation is performed with no knowledge about particular individuals: they are accessed dynamically during the normal Prolog execution of the generated program. This technique, together with the top-down Prolog execution, implies that only those pieces of data are accessed that are indeed important for answering the query. This makes it possible to store the individuals in a database instead of memory, which results in better scalability and helps in using DL ontologies directly on top of existing information sources. The transformation process consists of two steps: (1) the DL axioms are converted to first-order clauses of a restricted form, and (2) a Prolog program is generated from these clauses. Step (2), which is the focus of the present paper, actually works on more general clauses than those obtainable by applying step (1) to a

Prolog Based Description Logic Reasoning

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Translating description logic queries to prolog

knowledge base. We first present a base transformation, the output of which can be either executed using a simple interpreter or further extended to executable Prolog code. We then discuss several optimisation techniques, applicable to the output of the base transformation. Some of these techniques are specific to our approach, while others are general enough to be interesting for DL reasoner implementors not using Prolog. We give an overview of DLog, a DL reasoner in Prolog, which is an implementation of the techniques outlined above. We evaluate the performance of DLog and compare it to some widely used DL reasoners, such as RacerPro, Pellet and KAON2.

A Logic-Based System for Application Integration

Aurora is a prototype or-parallel implementation of the full Prolog language for shared memory multiprocessors, based on the SRI model of execution. It consists of a Prolog engine based on SICStus Prolog and several alternative schedulers. The task of the schedulers is to share the work available in the Prolog search tree

Interfacing engines and schedulers in Or-paralllel Prolog systems

Experience gained in the development of Question-Answering (QA) and Data Base Management (DBM) systems using a logic-based, very high level language, PROLOG, is summarized. The PROLOG language is introduced first. Those modifications to the language that were necessitated by the above applications are described. Subsequently, an experimental QA system dealing with drug data and drug interactions, and two operative DBM systems are described. Finally, some advantages obtained in using PROLOG for QA and DBM system implementations are discussed, and continued developments of PROLOG are presented.

MProlog: an Implementation Overview

In this paper we present the recent developments of the DLog system, an ABox reasoning engine for the the

Scalable Web Reasoning Using Logic Programming Techniques

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