CPUs and GPUs share a similar design, including a similar number of cores and transistors for processing tasks, but CPUs are more general-purpose in their functions than GPUs. GPUs tend to be focused on a singular, specific computing task, such as graphics processing or machine learning.
CPUs are the heart and brain of a computer system or device. They receive general instructions or requests regarding a task from a program or software application. A GPU, on the other hand, has a more specific task—typically involving the processing of high-resolution images and videos quickly. To accomplish their task, GPUs constantly perform complex mathematical calculations required for rendering graphics or other compute intensive functions.
One of the biggest differences between CPUs and GPUs is that CPUs tend to use fewer cores and perform their tasks in a linear order, while GPUs have hundreds—even thousands—of cores, enabling the parallel processing that drives their lightning-fast processing capabilities.
The first GPUs were built to speed 3D graphics rendering, making movie and video game scenes seem more realistic and engaging. The first GPU chip, the GeForce from Nvidia, was released in 1999, and was quickly followed by a rapid period of growth that saw GPU capabilities expand into other areas due to their high-speed parallel processing capabilities.
Parallel processing, or parallel computing, is a kind of computing that relies on two or more processors to accomplish different subsets of an overall computing task. Before GPUs, older generation computers could only run one program at a time, often taking hours to complete a task. GPUs' parallel processing function performs many calculations or tasks simultaneously, making them faster and more efficient than CPUs in older computers.
