3D exploration of Uniprocessor Schedules for DSP algorithms
Jürgen Teich, Eckart Zitzler, Shuvra S. Bhattacharyya · Repository for Publications and Research Data (ETH Zurich) · 1999
When implementing software for programmable digital signal processors (PDSPs), the design space is dened by a complex range of constraints and optimization objectives.Three implementation metrics that are crucial in many PDSP applications are the program memory requirement (code size), data memory requirement, and execution time.This paper addresses the problem of exploring the 3-dimensional space of trade-os that is dened by these crucial metrics.Given a software library for a target PDSP, and a data ow-based block diagram specication of a DSP application in terms of this library, our objective in this paper is to compute a full range of Pareto-optimal solutions.For solving this multi-objective optimization problem, an evolutionary algorithm based approach is applied, where two dierent Pareto-optimization methods are considered.We illustrate our techniques by analyzing the trade-o fronts of a practical application for a number of well-known, commercial PDSPs.Moreover, the two evolutionary Pareto-optimization methods are quantitatively compared on nine DSP applications.