As time has passed, the general purpose programming paradigm has
evolved, producing different hardware architectures whose characteristics
differ widely. In this work, we are going to demonstrate, through different
applications belonging to the field of Image Processing, the existing
difference between three Nvidia hardware platforms: two of them belong to
the GeForce graphics cards series, the GTX 480 and the GTX 980 and one of
the low consumption platforms which purpose is to allow the execution of
embedded applications as well as providing an extreme efficiency: the Jetson
TK1.
With respect to the test applications we will use five examples from Nvidia
CUDA Samples. These applications are directly related to Image Processing,
as the algorithms they use are similar to those from the field of medical image
registration. After the tests, it will be proven that GTX 980 is both the device
with the highest computational power and the one that has greater
consumption, it will be seen that Jetson TK1 is the most efficient platform, it
will be shown that GTX 480 produces more heat than the others and we will
learn other effects produced by the existing difference between the
architecture of the devices
