Parallel Constraint Logic Programming Language Gdcc And Its Parallel Constraint Solvers

FGCS '92

Parallel Combinatorial Optimization

This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.

Parallel Constraint Logic Programming Language GDCC and Its Parallel Constraint Solvers

Abstract: "Parallelization of a constraint logic programming (CLP) language can be considered at two major levels; the execution of an inference engine and a solver in parallel, and the execution of a solver in parallel. GDCC is a parallel CLP language that satisfies this two level parallelism. It is implemented in KL1 and is currently running on the Multi-PSI, a loosely coupled distributed memory parallel machine. GDCC has multiple solvers and a block mechanism that enables meta-operation to a constraint set. Currently there are three solvers: an algebraic solver for nonlinear algebraic equations using the Buchberger algorithm, a boolean solver for boolean equations using the Boolean Buchberger algorithm, and a linear integer solver for mixed integer programming. The Buchberger algorithm is a basic technology for symbolic algebra, and several attempts at its parallelization have appeared in the recent literature, with some good results for shared memory machines. The algorithm we present is designed for the distributed memory machine, but nevertheless shows consistently good performance and speedups for a number of standard benchmarks from the literature."