What is GPU – (Graphics Processing Unit)?

A GPU is a single-chip processor that creates lighting effects and transforms objects every time a 3D scene is redrawn. These are mathematically intensive tasks, which, otherwise, would put quite a strain on the CPU.

Modern GPUs are very efficient at manipulating computer graphics and image processing, and their highly coordinated structure makes them more efficient than general-purpose CPUs for algorithms where the processing of large blocks of data is done in parallel. In a personal computer, a GPU can be present on a video card, or it can be embedded on the motherboard or—in certain CPUs—on the CPU die.

It was popularized by Nvidia in 1999, who marketed the GeForce 256 as “the world’s first GPU”, or Graphics Processing Unit. It was presented as a “single-chip processor with integrated transform, lighting, triangle setup/clipping, and rendering engines”. Rival ATI Technologies coined the term “visual processing unit” or VP U, with the release of the Radon 9700 in 2002.

A graphics processing unit can render images more quickly than a CPU because of its parallel processing architecture, which allows it to perform multiple calculations at the same time. The resulting performance improvements have made GPUs popular chips for other resource-intensive tasks unrelated to graphics.

Computational Functions:-

Modern GPUs use most of their transistors to do calculations related to 3D computer graphics. They were originally used to accelerate the memory-intensive work of texture mapping and rendering polygons, later adding units to accelerate geometric calculations such as the rotation and translation of vertices into different coordinate systems.

In addition to the 3D hardware, today’s GPUs include basic 2D acceleration and frame buffer capabilities (usually with a VGA compatibility mode). Newer cards like AMD/ATI HD5000-HD7000 even lack 2D acceleration; it has to be emulated by 3D hardware.

GPU-Accelerated Computing:-

GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering 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. They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.

More recent graphics cards even decode high-definition video on the card, offloading the central processing unit. The most common APIs for GPU accelerated video decodings are DX VA for Microsoft Windows operating system and VDPAU, VA API, Xv MC, and Xv BA for Linux-based and UNIX-like operating systems. All except Xv MC are capable of decoding videos encoded with MPEG-1, MPEG-2, MPEG-4 ASP (MPEG-4 Part 2), MPEG-4 AVC (H.264 / DivX 6), VC-1, WMV3/WMV9, Xvid / Open DivX (DivX 4), and DivX 5 codecs, while Xv MC is only capable of decoding MPEG-1 and MPEG-2.

A simple way to understand the difference between a GPU and a CPU 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.

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