An effective methodology for functional pipelining

The problem of scheduling a loop in a pipelined fashion such that the iteration time (turnaround time) is minimized, given a loop behavior, a target initiation interval, and resource constraints, is considered. The iteration time is an important quality measure of a data path design because of its direct correlation with both the storage and the control costs. The scheduler starts with performing as-soon-as-possible-pipelined (ASAP/sub p/) scheduling without regard to the resource constraint. It then resolves the resource constraint violations, if there are any, by repeatedly rescheduling some operations.<<ETX>>