A recursive technique for computing lower-bound performance of schedules

We present a fast recursive technique for estimating lower-bound performance of data path schedules. The method relies on the determination of an ASAPUC a(s Soon As Possible Under Constraint) time-step value for each node of the DFG (Data-Flow Graph) that is based on the ASAPUC values of its predecessor nodes. That is, the lower-bound estimation is applied to each subgraph permitting the derivation of a tight lower bound on the performance of the complete DFG. Applying the greedy lower-bound estimator of Rim and Jain [1994] to each subgraph improves the complete lower bound in more than 50% of the experiments reported in Rim and Jain [1994], and the CPU time is only about twice as long. The recursive methodology can be extended to exploit other lower-bound techniques, for example, considering other constraints such as the number of busses or registers.