Association for Computing Machinery
Scheduling plays a central role in the behavioral synthesis process, which automatically compiles high-level specifications into optimized hardware implementations. However, most of the existing behavior-level scheduling heuristics either have a limited efficiency in a specific class of applications or lack general support of various design constraints. In this paper, the authors describe a new scheduler that converts a rich set of scheduling constraints into a System of Difference Constraints (SDC) and performs a variety of powerful optimizations under a unified mathematical programming framework. In particular, they show that their SDC-based scheduling algorithm can efficiently support resource constraints, frequency constraints, latency constraints, and relative timing constraints, and effectively optimize longest path latency, expected overall latency, and the slack distribution.