On the contrary, a GPU core doesn’t do anything that complicated and, anyway, it does not do much in terms of out-of-order execution. In this way, it can prepare the operands and execute those in advance ( speculative execution), thus saving time. For the sake of optimization, a CPU can execute instructions in an order different from that they came in or it can predict the instructions most likely needed in the near future when encontering a branch ( multiple branch prediction). A Jetson NANO installed on a robot for indoor mapping and navigation is a relevant example of the need of keeping at a minimum the power consumption to extend the battery life.(see, Indoor Mapping and Navigation Robot Build with ROS and Nvidia Jetson Nano):Ī proof of the “smartness” of a CPU core is the capability to perform out-of-order executions. Opposite to that, GPUs have experienced clock slow downs to limit consumption and accommodate installations in mobile or embedded devices. Over the time, CPU cores have benefitted of a progressive increase in clock speed to improve performance ( The evolution of a GPU: from gaming to computing). The size and the number evoke what a CPU or GPU cores are capable to do and their numerosity in a device.Ī CPU core is faster and “smarter” than a GPU core. The color convention is that green represents the computational units, or cores, orange the memories and yellow the control units.Īt first glance, in a CPU, the computational units are “bigger”, but few in number, while, in a GPU, the computational units are “smaller”, but numerous. Left: CPU architecture right: GPU architecture.
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