GPU Ray Tracing

Ray tracing, one of the earliest applications of GPUs, works by simulating light's journey backward. Imagine a virtual screen in front of your eye; rays lead from your eye through each pixel, eventually hitting a material. The color you see is determined by tracing the light's path from that material back to its light source.

This process is incredibly complex and demands serious computing power. While early GPUs focused on 2D graphics for interfaces, the rise of 3D games led them to take on ray tracing and related tasks like physics simulations (CUDA) and texture mapping (DirectX).

Even today, RT cores remain a key part of GPUs, representing some of the most valuable silicon real estate. Many AI workloads primarily utilize general-purpose CUDA and tensor cores, leaving RT cores often underutilized in data centers. Building specialized GPUs tailored to specific needs could free up significant silicon area and data center space, potentially saving hundreds of millions of dollars.

Data centers are also crucial for advancing digital twins – highly accurate virtual representations of the physical world. These twins can simulate complex systems, like jet engines, enabling optimization without the need for physical prototypes.

Our approach involves handling a wider spectrum of colors, going beyond the typical red, green, and blue representation. We delve into how a material's color is created through reflection and refraction, even at the atomic level, like with gold. While 8-bit RGB was sufficient for older CRT displays, digital twins in data centers can leverage the full spectrum, simulating not just visible light but also infrared, heat, and even X-ray radiation.

Link of the day.
Ray Tracing With CUDA. Here.