Scalable Design Space Exploration via Answer Set Programming

Abstract

The design of embedded systems is becoming continuously more complex such that the application of efficient high level design methods are crucial for competitive results regarding design time and performance. Recently, advances in Boolean constraint solvers for Answer Set Programming (ASP) allow for easy integration of background theories and more control over the solving process. The goal of this research is to leverage those advances for system level design space exploration while using specialized techniques from electronic design automation that drive new application-originated ideas for multi-objective combinatorial optimization