NVIDIA GP/GPU

GPU ACCELERATED COMPUTING

GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate scientific, analytics, engineering, consumer, and enterprise applications. Pioneered in 2007 by NVIDIA®, GPU accelerators now power energy-efficient data-centers in government labs, universities, enterprises, and small-and-medium businesses around the world. GPUs are accelerating applications in platforms ranging from cars, to mobile phones and tablets, to drones and robots.

CPU VERSUS GPU

A simple way to understand the difference between a CPU and GPU is to compare how they process tasks. A CPU consists of a few cores optimized for sequential serial processing while a GPU has a massively parallel architecture consisting of thousands of smaller, more efficient cores designed for handling multiple tasks simultaneously.

GPUs have thousands of cores to process parallel workloads efficiently

GPUs have thousands of cores to process parallel workloads efficiently

Check out the video clip below for an entertaining CPU versus GPU.

Check out the video clip below for an entertaining CPU versus GPU