A framework for automation of system-level design space exploration
Design Space Exploration is the task of identifying optimal implementation architectures for an application. On the front-end, it involves multi-objective optimization through a large space of options, and lends itself to a multitude of algorithmic approaches. On the back-end, it relies extensively on common capabilities such as model refinement, simulation and assessment of parameters like performance and cost. These characteristics present an opportunity to create an infrastructure that enables multiple approaches to be deployed using generic back-end services. In this work, we describe such a framework, developed using the System-on-Chip Environment, and we demonstrate the benefits and feasibility of deploying a variety of design space exploration approaches built on top of this basic infrastructure.