Optimization of Dynamic Memory Managers for Embedded Systems Using Grammatical Evolution
New portable consumer embedded devices must execute multimedia applications (e.g., 3D games, video players and signal processing software, etc.) that demand extensive memory accesses and memory usage at a low energy consumption. Moreover, they must heavily rely on Dynamic Memory (DM) due to the unpredictability of the input data and system behavior. Within this context, consistent design methodologies that can tackle efficiently the complex DM behavior of these multimedia applications are in great need. In this paper, the authors present a novel design framework, based on genetic programming, which allows one to design custom DM management mechanisms, optimizing memory accesses, memory use and energy consumption for the target embedded system.