Abstract
This paper presents DAOS, a model for exploitation of Andand Or-parallelism in logic programs. DAOS assumes a physically distributed memory environment and a logically shared address space. Exploiting both major forms of implicit parallelism should serve a broadest range of applications. Besides, a model that uses a distributed memory environment provides scalability and can be implemented over a computer network. However, distributed implementations of logic programs have to deal with communication overhead and inherent complexity of distributed memory managent. DAOS overcomes those problems through the use of a distributed shared memory layer to provide single-writer, multiple-readers sharing for the main execution stacks combined with explicit message passing for work distribution and management.

Abstract
One of the advantages of logic programming is the fact that it offers many sources of implicit parallelism, such as and-parallelism and or-parallelism. Arguably, or-parallel systems, such as Aurora and Muse, have been the most successful parallel logic programming systems so far. Or-parallel systems rely on techniques such as Environment Copying to address the problem that branches being explored in parallel may need to assign different bindings for the same shared variable. Recent research has led to two new binding representation approaches that also support independent and-parallelism: the Sparse Binding Array and the Copy-On-Write binding models. In this paper, we investigate whether these newer models are practical alternatives to copying for or-parallelism. We based our work on YapOr, an or-parallel copying system using the YAP Prolog engine, so that the three alternative systems share schedulers and the underlying engine.

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Logic programming is based on the idea that computation is controlled inference. The Extended Andorra Model provides a very powerful framework that supports both co-routining and parallelism. In this work we show that David H. D. Warren's design for the EAM with Implicit Control does not perform well for deterministic computations and we present several optimisations that allow the BEAM to achieve performance matching or even exceeding related systems. Our optimisations refine the original EAM control rule demonstrate that overheads can be reduced through combined execution rules, and show that a good design and emulator implementation is relevant, even for a complex system such as the BEAM.

Abstract
One of the major problems that actual logic programming systems have to address is whether and how to prune undesirable parts of the search space. A region of the search space would definitely be undesirable if it can only repeat previously found solutions, or if it is well-known that the whole computation will fail. Or it may be the case that we are interested in a subset of solutions. In this work we discuss how the BEAM addresses pruning issues. The BEAM is an implementation of David Warren's Extended Andorra Model. Because the BEAM relies on a very flexible execution mechanism, all cases of pruning discussed above should be considered. We show that all these different forms of pruning can be supported, and study their impact in applications.