Modern GPU architectures incorporate dedicated silicon, often referred to Ray Tracing (RT) Cores or equivalent structures, to handle the computationally intensive demands of realistic light transport simulation, moving beyond the approximations of the traditional rasterization pipeline. The ray tracing process fundamentally involves tracing the path of light rays backward from the camera into the scene. This begins with Ray Generation, where the initial camera rays are cast across the viewport. The GPU then utilizes a highly optimized spatial data structure, the Bounding Volume Hierarchy (BVH), which is essentially a tree structure bounding the scene’s geometry. When a ray is cast, the dedicated RT hardware traverses this BVH, rapidly discarding large groups of objects that the ray could not possibly intersect, thereby minimizing the number of expensive Intersection Tests required.

Upon a successful intersection with an object’s geometry, the GPU determines the lighting, shading, and material properties. Since realism requires calculating reflections, refractions, and shadows, the original ray is often recursively spawned into secondary rays—reflection rays, shadow rays, and potentially diffuse rays—which continue the process deeper into the scene. Shadow rays, for example, are cast from the point of intersection toward light sources, checking for occluding objects to determine if the point is in shadow. The management of these recursively spawned rays, along with the data structures linking geometry to their corresponding shading programs (the Shader Binding Table), represents a significant administrative load handled by the GPU’s specialized processing units and memory management logic. Due to the inherent stochastic (random) nature of sampling and tracing light paths, the resulting image is initially highly noisy. Therefore, a crucial final step involves the use of Denoising algorithms, typically implemented as deep learning filters running on the GPU’s compute units, to reconstruct a smooth, high-fidelity final image from the sparse sample data, completing the physics-based rendering cycle.