We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.
13 Jan 2021
Source: 11th International Workshop on Polyhedral Compilation Techniques (I...
We present an approach to enhancing the optimization process in a polyhedral compiler by introducing compile-time versioning, i.e., the production…