Improving reliability of embedded systems through dynamic memory manager optimization using grammatical evolution

Resumen

Technology scaling has offered advantages to embedded systems, such as increased performance, more available memory and reduced energy consumption. However, scaling also brings a number of problems like reliability degradation mechanisms. The intensive activity of devices and high operating temperatures are key factors for reliability degradation in latest technology nodes. Focusing on embedded systems, the memory is prone to suffer reliability problems due to the intensive use of dynamic memory on wireless and multimedia applications. In this work we present a new approach to automatically design dynamic memory managers considering reliability, and improving performance, memory footprint and energy consumption. Our approach, based on Grammatical Evolution, obtains a maximum improvement of 39% in execution time, 38% in memory usage and 50% in energy consumption over state-of-the-art dynamic memory managers for several real-life applications. In addition, the resulting distributions of memory accesses improve reliability. To the best of our knowledge, this is the first proposal for automatic dynamic memory manager design that considers reliability.

J. Manuel Colmenar

Catedrático de Universidad

Mis intereses de investigación se centran en las metaheurísticas aplicadas a problemas de optimización. He trabajado en diferentes problemas de optimización combinatoria aplicando algoritmos trajectoriales como GRASP o VNS. Además, estoy muy interesado en las aplicaciones de la Evolución Gramatical, específicamente en el dominio de los modelos y la predicción, como alternativa a los enfoques de aprendizaje automático.