Optimization of dynamic data structures in multimedia embedded systems using evolutionary computation

Embedded consumer devices are increasing their capabilities and can now implement new multimedia applications reserved only for powerful desktops a few years ago. These applications share complex and intensive dynamic memory use. Thus, dynamic memory optimizations are a requirement when porting these applications. Within these optimizations, the refinement of the Dynamically (de)allocated Data Type (or DDT) implementations is one of the most important and difficult parts for an efficient mapping onto low-power embedded devices. In this paper, we describe a new automatic optimization approach for the DDTs of object-oriented multimedia applications. It is based on an analytical pre-characterization of the possible elementary DDT blocks, and a multi-objective genetic algorithm to explore the design space and to select the best implementation according to different optimization criteria (i.e., memory accesses, memory footprint and energy consumption). Our results in real-life multimedia applications show that the best implementations of DDTs can be obtained in an automated way in few hours, while typically designers would require days to find a suitable implementation, achieving important savings in exploration time with respect to other state-of-the-art heuristics-based optimization methods for this task.