The term "graphics processing unit" was coined by Nvidia in 1999. GPUs are designed to accelerate the rendering of images, video, and animations to a display device. They are used in a wide range of applications, including video games, scientific visualization, and machine learning. GPUs are typically used in conjunction with a central processing unit (CPU) to perform tasks that are not suitable for the CPU, such as rendering graphics and processing large amounts of data in parallel.
GPUs are typically composed of thousands of smaller, more efficient cores designed to handle multiple tasks simultaneously. This allows GPUs to perform complex calculations much faster than a CPU. GPUs are also designed to handle large amounts of data in parallel, making them ideal for tasks such as machine learning and scientific computing.
In recent years, GPUs have become increasingly important in the field of artificial intelligence and machine learning. GPUs are used to accelerate the training of neural networks and other machine learning algorithms. This has led to the development of specialized GPUs, such as the Nvidia Tesla and the AMD Instinct, which are designed specifically for machine learning and scientific computing.
GPUs are also used in a wide range of other applications, including video editing, 3D modeling, and scientific visualization. They are used in a wide range of devices, including personal computers, workstations, and game consoles. GPUs are also used in embedded systems, such as smartphones and tablets, to accelerate the rendering of graphics and video.
In summary, a GPU is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in a wide range of applications, including video games, scientific visualization, and machine learning. They are typically used in conjunction with a central processing unit (CPU) to perform tasks that are not suitable for the CPU, such as rendering graphics and processing large amounts of data in parallel.