Efficient module selections for finding highly acceptable designs based on inclusion scheduling

In high level synthesis, module selection, scheduling, and resource binding are inter-dependent tasks. For a selected module set, the best schedule/binding should be generated in order to accurately assess the quality of a module selection. Exhaustively enumerating all module selections and constructing a schedule and binding for each one of them can be extremely expensive. In this paper, we present an iterative framework, called WIZARD to solve module selection problem under resource, latency, and power constraints. The framework associates a utility measure with each module. This measurement reflects the usefulness of the module for a given a design goal. Using modules with high utility values should result in superior designs. We propose a heuristic which iteratively perturbs module utility values until they lead to good module selections. Our experiments show that by keeping modules with high utility values, WIZARD can drastically reduce the module exploration space (approximately 99.2% reduction). Furthermore, the module selections formed by these modules belong to superior solutions in the enumerated set (top 15%).