In this paper, we propose an effective asynchronous datapath synthesis system to optimize statistical performance of asynchronous systems. The proposed algorithm is a heuristic method which simultaneously performs scheduling and resource binding. During the design process, decisions will be made based on the statistical schedule length analysis. It is demonstrated that asynchronous datapaths with the reduced mean total computation time are successfully synthesized for some datapath synthesis benchmarks.

In this paper, we study loop pipeline scheduling problem under given resource assignment (operation to functional unit assignments and data to register assignments), which is one of the key tasks in data-path synthesis based on the assignment solution space exploration. We show an approach using a precedence constraint graph with parametric disjunctive arcs generated from the specified assignment information, and derive a scheduling method using branch-and-bound exploration of the parameter space. As an application of the proposed scheduling method, it is incorporated with Simulated-Annealing (SA) based exploration of assignment solution space, and it is demonstrated that data-paths of the fifth-order elliptic wave filter are successfully synthesized.