Effectiveness of Optimizing Compilation for CLP(R)

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 constraints which cannot fail. We systematically evaluate the effectiveness of each optimization in isolation and also in combination. Our empirical evaluation of the compiler verifies that optimizing compilation can be made efficient enough to allow compilation of real-world programs and that it is worth performing such compilation because it gives significant time and space performance improvements.