Efficient Algorithms for Finding Highly Acceptable Designs Based on Module-Utility Selections£

In this paper, we present an iterative framework 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 will 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 the module selections formed by combinations of modules with high utility values are superior solutions. Further, by keeping modules with high utility values, the module exploration space can drastically be reduced.