GPUs are best suited for repetitive and highly-parallel computing tasks. Beyond video rendering, GPUs excel in machine learning, Artificial Intelligence, and many other types of scientific computations.
GPUs for Gaming
Rendering scenarios, such as video games, require GPUs for graphics acceleration and real-time rendering, and also require massive computing capacities, memory, and storage. With advanced display technologies, such as 4K screens and high refresh rates, along with the rise of virtual reality gaming, demands on graphics processing are growing fast. GPUs can have hundreds or thousands of small cores and are perfect for 2D and 3D calculations and rendering 3D graphics. With better graphics performance, games can be played at higher resolution, at faster frame rates, or both.
GPUs for Video Editing and Content Creation
Working with video editing, visual effects, and animation requires a high-performing PC to efficiently handle the resource-heavy tasks and avoid waiting for projects to render and encode. GPUs usually have hundreds or thousands of small cores. These highly task-parallel, specialized computing cores are perfectly used for graphics processing, making it faster and easier to render video and graphics in higher-definition formats.
GPU for Machine Learning
Artificial Intelligence and Machine Learning operations often require processing massive amounts of images or videos. Because GPUs incorporate an extraordinary amount of computational capability, they can deliver incredible acceleration in workloads that take advantage of the highly parallel nature of GPUs, such as image recognition.