Evolutionary design of the memory subsystem


The memory hierarchy has a high impact on the performance and power consumption in the system. Moreover, current embedded systems, included in mobile devices, are specifically designed to run multimedia applications, which are memory intensive. This increases the pressure on the memory subsystem and affects the performance and energy consumption. In this regard, the thermal problems, performance degradation and high energy consumption, can cause irreversible damage to the devices. We address the optimization of the whole memory subsystem with three approaches integrated as a single methodology. Firstly, the thermal impact of register file is analyzed and optimized. Secondly, the cache memory is addressed by optimizing cache configuration according to running applications and improving both performance and power consumption. Finally, we simplify the design and evaluation process of general-purpose and customized dynamic memory manager, in the main memory. To this aim, we apply different evolutionary algorithms in combination with memory simulators and profiling tools. This way, we are able to evaluate the quality of each candidate solution and take advantage of the exploration of solutions given by the optimization algorithm. We also provide an experimental experience where our proposal is assessed using well-known benchmark applications.

Applied Soft Computing
J. Manuel Colmenar
J. Manuel Colmenar
Profesor Titular 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.