RT Generic
T1 Procesamiento de imágenes cerebrales en GPU
T2 Neuroimage processing on GPU using CUDA
A1 Cabero Guerra, Javier
K1 Diagnóstico por imagen
K1 Ingeniería biomédica
K1 Computación de altas prestaciones
K1 Grado en Ingeniería Informática - Trabajos Fin de Grado
K1 Informática - Trabajos Fin de Grado
AB As time has passed, the general purpose programming paradigm hasevolved, producing different hardware architectures whose characteristicsdiffer widely. In this work, we are going to demonstrate, through differentapplications belonging to the field of Image Processing, the existingdifference between three Nvidia hardware platforms: two of them belong tothe GeForce graphics cards series, the GTX 480 and the GTX 980 and one ofthe low consumption platforms which purpose is to allow the execution ofembedded applications as well as providing an extreme efficiency: the JetsonTK1.With respect to the test applications we will use five examples from NvidiaCUDA Samples. These applications are directly related to Image Processing,as the algorithms they use are similar to those from the field of medical imageregistration. After the tests, it will be proven that GTX 980 is both the devicewith the highest computational power and the one that has greaterconsumption, it will be seen that Jetson TK1 is the most efficient platform, itwill be shown that GTX 480 produces more heat than the others and we willlearn other effects produced by the existing difference between thearchitecture of the devices.
YR 2016
FD 2016-05-19
LK http://hdl.handle.net/10630/11434
UL http://hdl.handle.net/10630/11434
LA eng
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026