Entailment of Finite Domain Constraints

Carlson, Björn; Carlsson, Mats; Díaz, Daniel

doi:10.7551/mitpress/4316.003.0038

Cited by 10 publications

(2 citation statements)

References 3 publications

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“…Automatically proving the monotonicity of arbitrary functions is a challenging task. Rules are given by Carlson, Carlsson, and Diaz (1994) for the restricted language of indexicals, and Monette, Flener, and Pearson (2012) discuss the topic on an extended indexicals language. In PCCP, the next lemma provides a useful lattice-theoretic view of partial orders as monotone functions:…”

Section: Parallel Concurrent Constraint Programmingmentioning

confidence: 99%

A Variant of Concurrent Constraint Programming on GPU

Talbot¹,

Pinel²,

Bouvry³

2022

AAAI

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The number of cores on graphical computing units (GPUs) is reaching thousands nowadays, whereas the clock speed of processors stagnates. Unfortunately, constraint programming solvers do not take advantage yet of GPU parallelism. One reason is that constraint solvers were primarily designed within the mental frame of sequential computation. To solve this issue, we take a step back and contribute to a simple, intrinsically parallel, lock-free and formally correct programming language based on concurrent constraint programming. We then re-examine parallel constraint solving on GPUs within this formalism, and develop Turbo, a simple constraint solver entirely programmed on GPUs. Turbo validates the correctness of our approach and compares positively to a parallel CPU-based solver.

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Section: Parallel Concurrent Constraint Programmingmentioning

confidence: 99%

A Variant of Concurrent Constraint Programming on GPU

Talbot¹,

Pinel²,

Bouvry³

2022

AAAI

View full text Add to dashboard Cite

show abstract

Section: Parallel Concurrent Constraint Programmingmentioning

confidence: 99%

A Variant of Concurrent Constraint Programming on GPU

Talbot,

Pinel,

Bouvry

2022

Preprint

View full text Add to dashboard Cite

The number of cores on graphical computing units (GPUs) is reaching thousands nowadays, whereas the clock speed of processors stagnates. Unfortunately, constraint programming solvers do not take advantage yet of GPU parallelism. One reason is that constraint solvers were primarily designed within the mental frame of sequential computation. To solve this issue, we take a step back and contribute to a simple, intrinsically parallel, lock-free and formally correct programming language based on concurrent constraint programming. We then re-examine parallel constraint solving on GPUs within this formalism, and develop TURBO, a simple constraint solver entirely programmed on GPUs. TURBO validates the correctness of our approach and compares positively to a parallel CPU-based solver.

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A simple and efficient boolean solver for Constraint Logic Programming

Codognet¹,

Díaz²

1996

J Autom Reasoning

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We study in this paper the use of consistency techniques and local propagation methods, originally developped for constraints over finite domains, for solving boolean constraints in Constraint Logic Programming (CLP). We present a boolean CLP language clp(B/FD) built upon a CLP language over finite domains clp(FD) which uses a propagation-based constraint solver. It is based on a single primitive constraint which allows the boolean solver to be encoded at a low-level. The boolean solver obtained in this way is both very simple and very efficient: on average it is eight times faster than the CHIP propagation-based boolean solver, i.e. nearly an order of magnitude faster, and infinitely better than the CHIP boolean unification solver. It also performs on average several times faster than special-purpose stand-alone boolean solvers. We further present several simplifications of the above approach, leading to the design of a very simple and compact dedicated boolean solver. This solver can be implemented in a WAM-based logical engine with a minimal extension limited to four new abstract instructions. This clp(B) system provides a further factor two speedup w.r.t. clp(B/FD).

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Entailment of Finite Domain Constraints

Cited by 10 publications

References 3 publications

A Variant of Concurrent Constraint Programming on GPU

A Variant of Concurrent Constraint Programming on GPU

A Variant of Concurrent Constraint Programming on GPU

A simple and efficient boolean solver for Constraint Logic Programming

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