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Effectiveness of Optimizing Compilation for CLP(R)
 In Proceedings of the Joint International Conference and Symposium on Logic Programming
, 1996
"... Constraint Logic Programming (CLP) languages extend logic programming by allowing constraints from different domains such as real numbers or Boolean functions. They have proved to be ideal for expressing problems that require interactive mathematical modelling and complex combinatorial optimization ..."
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Cited by 10 (2 self)
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Constraint Logic Programming (CLP) languages extend logic programming by allowing constraints from different domains such as real numbers or Boolean functions. They have proved to be ideal for expressing problems that require interactive mathematical modelling and complex combinatorial optimization problems. However, CLP languages have mainly been considered as research systems, useful for rapid prototyping, but not really competitive with more conventional programming languages when performance is crucial. One promising approach to improving the performance of CLP systems is the use of powerful program optimizations to reduce the cost of constraint solving. We extend work in this area by describing a new optimizing compiler for the CLP language CLP(R). The compiler implements six powerful optimizations: reordering of constraints, bypass of the constraint solver, splitting and dead code elimination, removal of redundant constraints, removal of redundant variables, and specialization of...
Redundant Hidden Variables in Finite Domain Constraint Problems
 Constraint Processing. SpringerVerlag, LNCS 923
, 1995
"... Finite domain constraint problems with hidden variables are very natural to use, for example, when one has to deal with a complex reallife situation, described as a set of constraints over a set of variables, and desires to (re)use such description several times selecting each time a different sub ..."
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Cited by 8 (3 self)
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Finite domain constraint problems with hidden variables are very natural to use, for example, when one has to deal with a complex reallife situation, described as a set of constraints over a set of variables, and desires to (re)use such description several times selecting each time a different subset of variables of interest. In this paper we study finite domain constraint problems with hidden variables and the possible redundancy of some of the hidden variables. Here for redundancy we mean that the elimination of such variables, together with all the constraints connecting them, does not change the set of solutions of the given problem. We propose several sufficient conditions for variable redundancy and we develop algorithms, based on such conditions, which remove the variables found to be redundant. This, combined with other preprocessing techniques which remove other kinds of redundancy (tuple redundancy, such as the local consistency algorithms, or also constraint redundancy), c...
Repeated Redundant Inequalities in Constraint Logic Programming
, 1994
"... A number of Constraint logic Programming systems, including CLP(R) and Prolog III, decide simultaneous linear inequalities as part of the fundamental operational step of constraint solving. While this can contribute tremendously to the usefulness of the systems, it is computationally quite expensive ..."
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Cited by 5 (4 self)
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A number of Constraint logic Programming systems, including CLP(R) and Prolog III, decide simultaneous linear inequalities as part of the fundamental operational step of constraint solving. While this can contribute tremendously to the usefulness of the systems, it is computationally quite expensive. Nonground inequalities must generally be tested for consistency with the collected constraint set and then added to it, increasing its size, and thus making the next such test more expensive. Future redundant inequalities in a program are those that are guaranteed to be subsumed after no more than one subsequent procedure call, usually in the context of a recursive procedure. It has been noted that such inequalities need only be tested for consistency with the current constraint set, thus resulting in dramatic savings in execution speed and space usage. In this paper we generalize the notion of future redundancy in a number of ways and thus broaden its applicability. Thus we show how to d...
Optimizing Compilation of Linear Arithmetic in a Class of Constraint Logic Programs
 Department of Computer and Information Science, The Ohio State University
, 1994
"... A central issue in the optimizing compilation of Constraint Logic Programming (CLP) languages is how to compile away as much general constraint solving as possible. Most such work relies on obtaining mode and type information by global analysis, and uses it to generate specialized code for individua ..."
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Cited by 4 (1 self)
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A central issue in the optimizing compilation of Constraint Logic Programming (CLP) languages is how to compile away as much general constraint solving as possible. Most such work relies on obtaining mode and type information by global analysis, and uses it to generate specialized code for individual constraints and calls, often with the aid of multiple specialization. Some recent work has augmented these techniques with procedurelevel analysis of the interrelationships between constraints, to detect constraints that subsume other constraints, and variables that cease to be reachable at some point in a computation. In combination, these techniques have been shown to dramatically improve performance for a number of programs. Here we continue this line of investigation by considering a class of programs that accumulate and simplify systems of linear arithmetic constraints. The programs contain procedures that relate their parameters by an affine transform. For some calling patterns, th...
Optimizing Compilation for CLP(R)
"... Constraint Logic Programming (CLP) is a recent innovation in programming language design. CLP languages extend logic programming by allowing constraints from different domains such as real numbers or Boolean functions. This gives considerable expressive power and flexibility and CLP programs have pr ..."
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Cited by 4 (3 self)
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Constraint Logic Programming (CLP) is a recent innovation in programming language design. CLP languages extend logic programming by allowing constraints from different domains such as real numbers or Boolean functions. This gives considerable expressive power and flexibility and CLP programs have proven to be a highlevel programming paradigm for applications based on interactive mathematical modeling. These advantages, however, are not without cost. Implementations of CLP languages must include expensive constraint solving algorithms tailored to the specific domains. Indeed, performance of the current generation of CLP compilers and interpreters is one of the main obstacles to the widespread use of CLP. Here we outline the design of a highly optimizing compiler for CLP(R) , a CLP language which extends Prolog by allowing linear arithmetic constraints. This compiler is intended to overcome the efficiency problems of the current implementation technology. The main innovation in the comp...
Early Projection in CLP(R)
 In Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming, CP`98, number 1520 in Lecture Notes in Computer Science
, 1998
"... . During the evaluation of a constraint logic program, many local variables become inaccessible, or dead . In Prolog and other programming languages, the data bound to local variables can be removed automatically by garbage collection. The case of CLP is more complex, as the variables may be involve ..."
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Cited by 3 (0 self)
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. During the evaluation of a constraint logic program, many local variables become inaccessible, or dead . In Prolog and other programming languages, the data bound to local variables can be removed automatically by garbage collection. The case of CLP is more complex, as the variables may be involved in several constraints. We can consider dead variables to be existentially quantified. Removing an existential variable from a set of constraints is then a problem of quantifier elimination, or projection. Eliminating variables not only allows recovery of space but also can decrease the cost of further consistency tests. Surprisingly, the existing systems do not exploit these advantages. Instead, the primary use of projection is as a mechanism for obtaining answer constraints. In this paper, we will give a general system architecture for automatic early projection and specify the heuristics for CLP(R) together with an insitu removal method. We then show the effectiveness of early projecti...
Skeletons and techniques for the systematic development of constraint logic programs
 Department of Computer and Information Science, The Ohio State University
, 1994
"... ..."
Efficient Extraction of Imperative Computation in Constraint Logic Programs
, 1995
"... In most Constraint Logic Programming (CLP) languages, procedures can be transformed to improve the efficiency of constraint solving for a particular set of calling patterns. In particular, it is often possible to take advantage of groundness information to replace a considerable amount of constrai ..."
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Cited by 1 (0 self)
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In most Constraint Logic Programming (CLP) languages, procedures can be transformed to improve the efficiency of constraint solving for a particular set of calling patterns. In particular, it is often possible to take advantage of groundness information to replace a considerable amount of constraint solving with ground imperative computation. We present an efficient algorithm for identifying the specializations of a procedure that allow such optimization. This algorithm generates efficiently a concise representation of information flow in a procedure. This representation can be used to produce a set of calling patterns for which specialization is likely to be fruitful, together with the suitably transformed procedure for each specialization. 1 Introduction Many Constraint Logic Programming (CLP) [8] languages incorporate complex and potentially expensive constraint solving as a basic operational step. However, in most of them constraints can be solved easily and efficiently if...