With the advent of deep sub-micron era, there is a demand to consider the design closure problem in high-level synthesis. It is well known that the slack is an effective means of tolerating the uncertainties in operation delays. Previous work ever attempted to increase the usable slack based on a given initial schedule. Instead of the post-processing approach, this paper is the first attempt to the simultaneous application of operation scheduling and slack optimization. We use a 0-1 integer linear programming (0-1 ILP) approach to formally formulate the problem. Under the design constraints (timing and resource), our approach is applicable to two different objective functions: the maximization of the total usable slack and the maximization of the number of non-zero slack operations. Compared with previous work, our approach has the following two advantages: first, our approach guarantees the optimality; second, our approach is more suitable for the design space exploration.

At the behavioral level, large power savings are possible by shutting down unused operations, which is commonly referred to as power management. However, operation scheduling has a significant impact on the potential for power saving via power management. In this paper, we present an integer linear programming (ILP) model to formally formulate the simultaneous application of operation scheduling and power management in high level synthesis. Our objective is to maximize the power saving under both the timing constraints and the resource constraints. Note that our approach guarantees solving the problem optimally. Compared with previous work, experimental data consistently show that our approach has significant relative improvement in the power savings.