Optimizing Performance of L1 Cache Memory for Embedded Systems driven by Differential Evolution
Abstract
Embedded systems, mainly battery-powered, must guarantee low power consumption and good performance. The cache memory design is crucial in embedded systems. Given the high number of parameters and their ranges of values, the exhaustive exploration of resulting solution space is an unaffordable task.
Type
Publication
Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation
J. Manuel Colmenar
Full Professor
My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.