Optimized software synthesis for digital signal processing algorithms - an evolutionary approach

This paper addresses the problem of trading-off between the minimization of program and data memory requirements of single-processor implementations of dataflow programs. Based on the formal model of synchronous data flow (SDF) graphs [LM87], so called single appearance schedules are known to be program-memory optimal. Among these schedules, buffer memory schedules are investigated and explored based on a two-step approach: (1) An Evolutionary Algorithm (EA) is applied to efficiently explore the (in general) exponential search space of act or firing orders. (2) For each order, the buffer costs are evaluated by applying a dynamic programming post- optimization step (GDPPO). This iterative approach is compared to existing heuristics for buffer memory optimization