Scheduling for optimum data memory compaction in block diagram oriented software synthesis

For the design of complex digital signal processing systems, block diagram oriented synthesis of real time software for programmable target processors has become an important design aid. The synthesis approach discussed in the paper is based on multirate block diagrams with scalable synchronous dataflow (SSDF) semantics. For this class of dataflow graphs the authors present scheduling techniques for optimum data memory compaction. These techniques can be employed to map signals of a block diagram onto a minimum data memory space. In order to formalize the data memory compaction problem, they first derive appropriate implementation measures. Based on these implementation measures it can be shown that optimum data memory compaction consists of optimum scheduling as well as optimum memory allocation. For the class of single appearance (SA) block diagrams with SSDF semantics, scheduling can be reduced to an integer linear programming (ILP) problem. Due to the computational complexity of ILP, the authors also present a suboptimum scheduling selection criterion, which call be used for SA and non SA-schedulers