Abstract
The increasing transistor scale integration poses, among others, the thermal-aware floorplanning problem consisting of how to place the hardware components in order to reduce overheating by dissipation. Because of the huge amount of feasible floorplans, most of the solutions found in the literature include an evolutionary algorithm for, either partially or completely, carrying out the task of floorplanning. Evolutionary algorithms usually have a bottleneck in the fitness evaluation. In the problem of thermal-aware floorplanning, the layout evaluation by the thermal model takes 99.5% of the computational time for the best floorplanning algorithm proposed so far. The contribution of this paper is to present a parallelization of this evaluation phase in a master-worker model to achieve a dramatic speed-up of the thermal-aware floorplanning process. Exhaustive experimentation was carried out over 3D integrated circuits, with 48 and 128 cores, outperforming previous published works. Copyright © 2012 John Wiley & Sons, Ltd.
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.