You aren’t able to grasp the basics of your GPU because it sounds like technical gibberish. We get the struggle! But understanding the architecture of your graphics card is crucial if you want to better analyse your options before purchase.
Although, with AI now taking over everything, including GPUs, new components have made a wild-card entry. No longer will you find Gen-Z squabbling over heatsink capacity and RAMDAC, because now, the hype surrounds the three cores.
CUDA, RT, and tensor cores have become the holy trinity for achieving good graphics. With these core components, your laptop will be unstoppable, quite literally. So, here’s all that you need to know about how GPU cores work before you invest in a laptop.
Let’s get started.
What is CUDA Core?
The word CUDA is short for Compute Unified Device Architecture, and it’s a specialised processor installed within the NVIDIA GPU. Designed to direct parallel computing, the new generation of GPUs is nothing without this star unit. The main difference between traditional CPUs and modern GPUs is multitasking, which is possible thanks to these cores.
They enable your device to keep up with your demands in real-time by enabling massive parallel execution. What makes this possible is the quantity of thousands of cores in each chip, making it a processor within a processor. Due to this, your device executes thousands of threads simultaneously, cutting down time and power consumption.
Functions | Description |
Vertex Shading | Helps in positioning how a 3D object appears to the user from different camera angles by calculating screen space. |
Pixel Shading | It determines the color shade, texture, and lighting of each individual pixel for fast rendering and buffer-free gameplay. |
Geometric Processing | Uses defined algorithms to create and manipulate 3D shapes and the design of a scene, for example, creating terrain layers. |
Video Acceleration | Offloads CPU tasks related to video encoding and decoding for low-lag streaming and enhancing video quality to 4K and 8K. |
GPGPU Computation | Performs non-graphic related tasks efficiently by training AI models, enabling scientific simulations, and analysing the data. |
What is RT Core?
RT or Real-time Ray Tracing core is a set of processing units in NVIDIA GPUs embedded in the Streaming Multiprocessors. These cores are mainly responsible for casting lights, shadows, and reflections in your image so that it appears enhanced. RT cores help you achieve what traditional rasterisation could never; creating a realistic or 3D virtual environment.
You must be thinking that the ray tracing technology has been around longer than the AI-powered GPUs, which is right. These RT cores work towards improving the existing ray tracing technology, and for one-on-one interactive content, it’s a real gem. It is particularly crucial in gaming, design, and animation because of their need for cinematic graphics.
Functions | Description |
BVH Traversal | Bounding Volume Hierarchy organises 3D objects in a tree-shaped hierarchy structure to discover which objects are exposed to a ray. |
Testing Ray Intersections | Calculations to ensure lighting, shadows, and reflections are placed accurately; also, spot the exact location where the ray hits an object. |
AI Denoising | Skims and removes visually distracting elements so that there is no ambient noise, whether the image is still or in motion. |
Testing Shadows & Reflections | Separates objects into two groups: those that cast a shadow and those that reflect light, achieved by simulating more rays. |
Global Illumination | Directs and simulates light movement while it bounces to add realism to an image through regulating brightness and tracing rays. |
What is Tensor Core?
To understand what a tensor core is, you first need to know about matrix operations because they go hand-in-hand. There are mathematical calculations involving matrices that are crucial for computer graphics, physics simulation, AI inference, and deep learning. Even though it’s possible to perform matrix operations without tensor cores (CUDA takes over), they accelerate the process.
Tensor cores are mandatory to handle AI workload with speed and precision. There are four generations of these cores: Volta, Turing, Ampere, and the most advanced Ada Lovelace. Unlike older generations, the latest Ada Lovelace features FP8 precision support, DLSS frame generation, and higher throughput. It also enables parallel AI plus graphics integration that is especially helpful for professional gamers.
Functions | Description |
Upscaling Images | Without compromising on performance, it turns low-resolution images into high resolution by creating sharper images and predicting pixel shortage. |
Machine Learning Inference | Handles machine learning operations to run trained AI models for taking real-time decisions, like making the choice of resource allocation. |
Matrix Multiplication | Expands the number of matrices for better information processing and fast parallel processing. |
Precision Calculation | Switches between different precision formats after predicting which tasks require what amount of accuracy and balancing speed. |
Scientific Computations | Uses matrix processing and complex calculations for carrying out specific functions of the GPU without causing stress. |
Association Between CUDA, RT, and Tensor Cores
All three processing units work in collaboration with each other to deliver bombastic graphics that set NVIDIA GPUs apart. The majority of input is by CUDA, sure, but without the other two cores, you’ll have to compromise on acceleration and quality. So it all starts when your app sends out a rendering command to the GPU.
After the data is compiled, semi-processed, and sent to the CUDA cores, it gets polished on the outside. The raw skeleton of the image is constructed using vertex shading and transforming 3D models. Then the skeleton is passed on to the RT cores for ray generation, intersection, and BVH traversal for acceleration.
From there, CUDA takes over again for an even deeper polish of the ray-traced image. Npot only does it add more shading and texture, but it also gives your lights, shadows, and reflections a visible glow-up. The semi-complete image is then passed to the tensor cores for frame generation. Here, all the tiny spots are filled in, and low resolution is transformed into high resolution.
In the final stage, the image is sent back to the CUDA cores for final touch-ups. By adding screen effects like removing motion blur and applying HUD overlay, the image is made completely photorealistic. It also ensures the final color correction is done right, so you can enjoy realism.
Final Word
In modern-day GPUs, the three cores are a literal dream team. They make the new GPUs a huge upgrade from the regular integrated GPUs, that’s for sure. With CUDA being the captain, it manages everything, from drafting the sketch to perfecting the final copy. The RT brings drama and character to the visually plain sketches, whereas Tensor upscales, enhances, and denoises like a pro.
Together, these cores turn raw data into awe-worthy visuals and that too at blazing speed. It makes magic from scrap and ensures the process is smart, synchronised, and speedy. So now that you know what your GPU is made of, you can invest in one stress-free.
