•GPU stands for Graphics Processing Unit.

•GPUs are also known as video cards or graphics cards.

•In order to display pictures, videos, and 2D or 3D animations, each device uses a GPU.

•A GPU performs fast calculations of arithmetic, so it helps the main CPU keeping free to do different things.

•A CPU makes use of some cores primarily based on sequential serial processing.

•But a GPU has lots of smaller cores made for multi-tasking.

•In the world of computing, graphics processing technology, content creation, machine learning, gaming, etc. GPU provides lots of possibilities.

Function of GPU

•In the 1990s, Nvidia brings it in the market to power up in the field graphics system.

•Some simple objects, by desktop CPU can handle by the limited flexibility of graphics processing built into that CPU.

•But for the additional workloads require the extra horsepower that comes with a dedicated GPU.

•The GPU is designed for parallel processing and is used in various applications, including video rendering and graphics.

•Originally, GPUs were designed to accelerate 3D graphics rendering.

• Over the time the technology upgraded and have become more modular and programmable and so capabilities.

•It enables graphics programmers with shadowing techniques and advanced lighting to create more exciting visual effects and more realistic scenes.

Usage of GPU

•GPUs are generally used for high-quality gaming experiences, creating life-like super-slick rendering and graphic design.

•There are also many business applications, which depend on strong graphics chips.

•The GPU is more programmable now a days, so it brings the potentiality to speed up a wide variety of applications that is beyond conventional graphics rendering.

For gaming –

•With new display technology, like 4K displays and high refresh rates, and the increase of virtual reality gaming, graphics processing demand increases rapidly.

• Games may be played at a better resolution, better frame rate, or each with advanced graphics performance.

For Machine Learning –

•GPUs have an exceptional amount of computational power.

•It can provide tremendous acceleration in workloads.

•So Artificial Intelligence and Machine Learning offer several exciting packages for GPU technology.

•It can be used for image recognition also working in combination with CPUs.

For Video Editing and Content Creation—

•There was a problem for many years, for video editors, graphics designers, and different professionals for Video Editing and Content Creation.

•Now, GPU’s parallel processing makes rendering video and graphics in higher quality formats easier and faster.