Abstract
We propose a transformation-based scheduling algorithm for the problem— given a loop construct, a target initiation interval and a set of resource constraints, schedule the loop in a pipelined fashion such that the iteration time of executing an iteration of the loop is minimized. The iteration time is an important quality measure of a data path design because it affects both storage and control costs. Our algorithm first performs an As Soon As Possible Pipelined (AS APp) scheduling regardless the resource constraint. It then resolves resource constraint violations by rescheduling some operations. The software system implementing the proposed algorithm, called Theda.Fold, can deal with behavioral loop descriptions that contain chained, multicycle and/or structural pipelined operations aswell as those having data dependencies across iteration boundaries. Experiment on a number of benchmarks is reported. © 1994 IEEE