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Graphics Processing Units for Constraint Satisfaction

A Constraint Satisfaction Problem (CSP) is a powerful formalism to represent constrained problems. A CSP includes a set of variables where each is defined over a set of possible values, and a set of relations restricting the values that the variables can simultaneously take. There are numerous problems that can be represented as CSPs. Solving CSPs is known to be quite challenging in general. The literature poses a great body of work geared towards finding efficient techniques to solve CSPs. These techniques are usually implemented in a system commonly referred to as a constraint solver. While many enhancements have been achieved over earlier ones, solvers still require powerful resources and techniques to solve a given problem in a reasonable running time. In this paper, a new parallel-based approach is proposed for solving CSPs. In particular, we design a new CSP solver that exploits the power of graphics processing units (GPU), which exist in modern day computers, as an affordable parallel computing architecture.