Design space exploration for dynamically reconfigurable architectures

By incorporating reconfigurable hardware in embedded system architectures it has become easier to satisfy the performance constraints of demanding applications while lowering system cost. In order to evaluate the performance of a candidate architecture, the nodes (tasks) of the data flow graphs that describe an application must be assigned to the computing resources of the architecture: programmable processors and reconfigurable FPGA, whose run-time reconfiguration capabilities must be exploited. In this paper we present a novel design exploration tool - based on a local search algorithm with global convergence properties - which simultaneously explores choices for computing resources, assignments of nodes to these resources, task schedules on the programmable processors and context definitions for the reconfigurable circuits. The tool finds a solution that minimizes system cost while meeting the performance constraints; more precisely it lets the designer select the quality of the optimization (hence its computing time) and finds accordingly a solution with close-to-minimal cost.