Time-constrained scheduling of large pipelined datapaths

This paper addresses the most crucial optimization problem of high-level synthesis: scheduling. A formal framework is described that was tailored specifically for the definition and investigation of the time-constrained scheduling problem of pipelined datapaths. Theoretical results are presented on the complexity of the problem. Moreover, two new heuristic algorithms are introduced. The first one is a genetic algorithm, which, unlike previous approaches, searches the space of schedulings directly. The second algorithm realizes a heuristic search using constraint logic programming methods. The performance of the proposed algorithms has been evaluated on a set of benchmarks and compared to previous approaches.

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