109 research outputs found
Implementing Groundness Analysis with Definite Boolean Functions
The domain of definite Boolean functions, Def, can be used to express the groundness of, and trace grounding dependencies between, program variables in (constraint) logic programs. In this paper, previously unexploited computational properties of Def are utilised to develop an efficient and succinct groundness analyser that can be coded in Prolog. In particular, entailment checking is used to prevent unnecessary least upper bound calculations. It is also demonstrated that join can be defined in terms of other operations, thereby eliminating code and removing the need for preprocessing formulae to a normal form. This saves space and time. Furthermore, the join can be adapted to straightforwardly implement the downward closure operator that arises in set sharing analyses. Experimental results indicate that the new Def implementation gives favourable results in comparison with BDD-based groundness analyses
Efficient Groundness Analysis in Prolog
Boolean functions can be used to express the groundness of, and trace
grounding dependencies between, program variables in (constraint) logic
programs. In this paper, a variety of issues pertaining to the efficient Prolog
implementation of groundness analysis are investigated, focusing on the domain
of definite Boolean functions, Def. The systematic design of the representation
of an abstract domain is discussed in relation to its impact on the algorithmic
complexity of the domain operations; the most frequently called operations
should be the most lightweight. This methodology is applied to Def, resulting
in a new representation, together with new algorithms for its domain operations
utilising previously unexploited properties of Def -- for instance,
quadratic-time entailment checking. The iteration strategy driving the analysis
is also discussed and a simple, but very effective, optimisation of induced
magic is described. The analysis can be implemented straightforwardly in Prolog
and the use of a non-ground representation results in an efficient, scalable
tool which does not require widening to be invoked, even on the largest
benchmarks. An extensive experimental evaluation is givenComment: 31 pages To appear in Theory and Practice of Logic Programmin
Enhanced sharing analysis techniques: a comprehensive evaluation
Sharing, an abstract domain developed by D. Jacobs and A. Langen for the analysis of logic
programs, derives useful aliasing information. It is well-known that a commonly used core
of techniques, such as the integration of Sharing with freeness and linearity information, can
significantly improve the precision of the analysis. However, a number of other proposals for
refined domain combinations have been circulating for years. One feature that is common
to these proposals is that they do not seem to have undergone a thorough experimental
evaluation even with respect to the expected precision gains.
In this paper we experimentally
evaluate: helping Sharing with the definitely ground variables found using Pos, the domain
of positive Boolean formulas; the incorporation of explicit structural information; a full
implementation of the reduced product of Sharing and Pos; the issue of reordering the
bindings in the computation of the abstract mgu; an original proposal for the addition of
a new mode recording the set of variables that are deemed to be ground or free; a refined
way of using linearity to improve the analysis; the recovery of hidden information in the
combination of Sharing with freeness information. Finally, we discuss the issue of whether
tracking compoundness allows the computation of more sharing information
A correct, precise and efficient integration of set-sharing, freeness and linearity for the analysis of finite and rational tree languages
It is well known that freeness and linearity information positively interact with aliasing information, allowing both the precision and the efficiency of the sharing analysis of logic programs to be improved. In this paper, we present a novel combination of set-sharing with freeness and linearity information, which is characterized by an improved abstract unification operator. We provide a new abstraction function and prove the correctness of the analysis for both the finite tree and the rational tree cases.
Moreover, we show that the same notion of redundant information as identified in Bagnara et al. (2000) and Zaffanella et al. (2002) also applies to this abstract domain combination: this allows for the implementation of an abstract unification operator running in polynomial time and achieving the same precision on all the considered observable properties
The AND-Prolog compiler system — Automatic parallelization tools for LP
This report presents an overview of the current work performed by us in the context of the efficient parallel implementation of traditional logic programming systems. The
work is based on the &-Prolog System, a system for the automatic parallelization and execution of logic programming languages within the Independent And-parallelism
model, and the global analysis and parallelization tools which have been developed for this system. In order to make the report self-contained, we first describe the "classical" tools of the &-Prolog system. We then explain in detail the work performed in improving and generalizing the global analysis and parallelization tools. Also, we describe the objectives which will drive our future work in this area
Determination of variable dependence information through abstract interpretation
Traditional schemes for abstract interpretation-based global analysis of logic programs generally focus on obtaining procedure argument mode and type information. Variable sharing information is often given only the attention needed to preserve the correctness of the analysis. However, such sharing information can be very useful. In particular, it can be used for predicting run-time goal independence, which can eliminate costly run-time checks in and-parallel execution. In this paper, a new algorithm for doing abstract interpretation in logic programs is described which infers the dependencies of the terms bound to program variables with increased precisiĂłn and at all points in the execution of the program, rather than just at a procedure level. Algorithms are presented for computing abstract entry and success substitutions
which extensively keep track of variable aliasing and term dependence information. The algorithms are illustrated with examples
Effectiveness of global analysis in strict independence-based automatic program parallelization
This paper presents a study of the effectiveness of global analysis in the parallelization of logic programs using strict independence. A number of well-known approximation domains are selected and tlieir usefulness for the
application in hand is explained. Also, methods for using the information provided by such domains to improve parallelization are proposed. Local and global analyses are built using these domains and such analyses are embedded in a complete parallelizing compiler. Then, the performance of the domains (and the system in general) is assessed for this application through a number of experiments. We argĂĽe that the results offer significant insight into the characteristics of these domains, the demands of the application, and the tradeoffs involved
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