Minimizing resources in a repeating schedule for a split-node data-flow graph

Many computation-intensive or recursive applications commonly found in digital signal processing and image processing applications can be repre-sented by data-flow graphs (DFGs). In our previous work, we proposed a new technique, extended retiming, which can be combined with minimal unfolding to transform a DFG into one which is rate-optimal. The result, however, is a DFG with split nodes, a concise representation for pipelined schedules. This model and the extraction of the pipelined schedule it rep-resents have heretofore not been explored. In this paper, we demonstrate one scheduling algorithm for such graphs, and then discuss a way to reduce the hardware requirements of the resulting schedule. In the process, we state and prove a tight upper bound on the minimum number of processors required to execute the static schedule produced by our algorithms. Finally, we demonstrate our methods on a specific example