Optimal Graph Transformation Assuming Alternate Scheduling Models

Many computation-intensive iterative or recursive applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). The execution of all tasks of a DFG is called an iteration, with the average computation time of an iteration the iteration period. A great deal of research has been done attempting to optimize such applications by applying various graph transformation techniques to the DFG in order to minimize this iteration period. Two of the most popular are retiming and unfolding, which can be performed in tandem to achieve an optimal iteration period. In our previous work, we proposed a new technique, extended retiming, which can be combined with minimal unfolding to transform a DFG into one whose iteration period matches that of the optimal schedule under a pipelined design. However, we developed our technique while assuming a particular scheduling model. In this paper, we generalize our previous work so that it may be utilized if an alternate model is specified.