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

Abstract

Abstract 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 W i Z ard 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, W i Z ard 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%).