In this post, we’ve covered what NVIDIA CUDA cores are, what they do, and how they’re commonly used.
Whether you’re playing PC games, using your computer to stream video, or simply using a visual interface for daily computing, you’ll be relying on a Graphics Processing Unit to render your content. Graphics Processing Units (GPUs) can either come integrated on your processor, or on a dedicated graphics card. (Check out our article on the differences between integrated and dedicated graphics.) GPUs process all screen-destined content and graphics that computers and gaming consoles produce.
NVIDIA is one of the leading GPU manufacturers, and has developed a parallel computing model called CUDA (Compute Unified Device Architecture) to render and display graphics. In this guide, we’re going to give you a quick rundown of NVIDIA’s CUDA cores, including what they are and how they’re used.
Understanding CUDA Cores
CUDA cores are highly analogous to the ‘cores’ found in a Central Processing Unit (CPU.) Many computer users are familiar with CPUs, as they are often advertised prominently with new computers. Most modern CPUs are dual- or quad-core, meaning they have two or four core components capable of processing data.
Buying a graphics card with multiple CUDA cores is akin to buying such a multi-core CPU, with an exception being CUDA cores are often numbered in the hundreds or thousands on a single GPU. CUDA cores are smaller than CPU cores, therefore you can fit more of them in a small space. Another reason for the discrepancy in how many cores are found in GPUs is that graphics cards tend to be about four to eight times larger in physical size than CPUs, allowing more real estate for chips.
Knowing that thousands of CUDA cores can be packed into a graphics card, you may still be wondering how they function. Again, it helps to think of them as analogous to the cores of a CPU, in terms of functionality. CUDA cores render low-level coding to output graphics that humans can see. Whereas CPU cores process low-level and assembly languages for a variety of functions, CUDA cores have one goal in mind; graphics.
CUDA cores can render the fine details of digital graphics, turning the coding behind high-resolution games and videos into smooth, life-like images and videos. CUDA cores perform such rendering and processing functions in parallel to each other, meaning each core works on a specific task while its neighboring cores are hard at work rendering other graphics. This makes for a highly efficient system, where no single core is waiting on another to finish its work.
How CUDA Cores Help
NVIDIA graphics cards (with their proprietary CUDA cores) are one of two main GPU options that gamers have (the other being AMD). That’s because CUDA cores are capable of displaying the high-resolution graphics associated with these types of files in a seamless, smooth, and fine-detailed manner.
CUDA cores help by rendering lighting, shading, physics, and other visual elements of graphics that work together to give you the experience that the objects you see on a flat LCD or LED screen are three-dimensional.
Another popular use for CUDA core-based GPUs is the mining of cryptocurrencies. Since GPUs are more efficient and faster than CPUs at rendering and processing data, many bitcoin miners and enthusiasts of other digital currencies put CUDA-backed GPUs to work mining for new and undiscovered currency. Researchers have also been known to take advantage of the speed of NVIDIA’s GPUs to analyze data more quickly than could be done on a traditional, integrated GPU.