How Real-Time Ray Tracing Works: Simulating Light at Interactive Speeds

Real-time ray tracing simulates light behavior for photorealistic images, made practical by specialized hardware. This process combines acceleration structures, dedicated RT Cores for efficient traversal, and AI denoising with Tensor Cores to achieve interactive speeds.

Kai Johnson

October 16, 2026 · 6 min read

Real-time ray tracing produces photorealistic images by simulating how light actually behaves, and it only became practical in interactive applications when hardware manufacturers built specialized silicon to shoulder its heaviest workloads. The core idea is simple: instead of approximating reflections and shadows with hand-tuned tricks, you trace rays of light through a scene and compute what they hit. The problem is that doing this for millions of pixels, dozens of times per second, is enormously expensive. NVIDIA's developer documentation describes the solution as a three-part engineering effort: tree-based acceleration structures that organize geometry, dedicated RT Cores that accelerate the most time-consuming traversal calculations, and Tensor Cores that use AI denoising to cut the number of rays needed in the first place.

**Video Series: Practical Real-Time Ray Tracing With RTX | NVIDIA Technical Blog**To visually demonstrate the practical application and visual impact of real-time ray tracing in a technical context, complementing the textual explanation.Watch on YouTube

Deconstructing the Real-Time Ray Tracing Pipeline

Ray tracing begins with rays cast from the eye through each pixel of the image, a narrowing that matters because it defines the direction of the computation: the renderer asks, for each pixel, what does the ray leaving the eye through this point strike first? As NVIDIA engineer Martin-Karl Lefrancois explains in the company's technical blog series on practical real-time ray tracing, when you trace a ray it hits the closest triangle and returns that result directly — the closest hit along the ray comes back without any manual sorting.

But a single primary ray is only the start. Once the ray finds its intersection point, further rays can be traced from that point to compute the shading for the pixel: shadow rays toward light sources, reflection rays off glossy surfaces, and so on. When a ray touches nothing at all, a miss shader takes over, typically supplying an environment or background color. Lefrancois describes this as a shader pipeline in which compiled shaders are declared and bound through a shading binding table, so that each intersection can trigger the right material logic. The final pixel color is the accumulated result of this branching tree of rays.

Hardware Acceleration: RT Cores for Efficient Traversal

Even with a well-built BVH, traversal is the dominant cost. NVIDIA's developer documentation is blunt about where the time goes: RT Cores accelerate BVH traversal, which the company identifies as the most time-consuming part of ray tracing calculations. This is specialized fixed-function hardware, not general-purpose shader cores doing the work alongside everything else.

One qualification deserves emphasis. RT Cores specifically accelerate the traversal of the hierarchy — walking the tree of bounding boxes and ruling out large regions of the scene quickly — rather than necessarily the final ray-triangle intersection test itself. Once traversal narrows a ray down to a bounding volume containing just a few triangles, those triangles are tested to find the closest hit. The division of labor is what matters: the general shader pipeline handles material logic and shading, while the RT Cores clear the geometric search that would otherwise overwhelm it.

The scale of the problem explains why the hardware is necessary at all. NVIDIA notes that movie makers have traditionally relied on vast CPU-based render farms that can take multiple days to render complex special effects. GPUs render realistic ray-traced scenes exponentially faster than CPUs, though historically limited by onboard memory, which constrained scene complexity. Real-time interactivity demanded more than a faster general processor — it demanded silicon designed around the specific structure of the ray-tracing problem.

The Real-Time Ray Tracing Pipeline: From Ray to Pixel

The table below assembles the full journey of a ray into a single sequential model, showing at each stage what is computed, what enables it, and why the stage matters for real-time performance. Follow it top to bottom to see exactly where hardware acceleration intervenes.

The real-time ray tracing pipeline, from ray generation to final pixel color
Process Stage	Key Operation	Enabling Hardware/Software	Performance Impact
Acceleration structure build	Bounding Volume Hierarchies (BLAS and TLAS) are created to organize scene geometry into nested bounding boxes	Driver/runtime BVH builders; TLAS transforms allow fast re-fits without touching geometry	Crucial for optimizing all subsequent ray intersection tests
Ray generation	Rays are cast from the eye through each pixel into the scene	Ray generation shaders	Defines the per-pixel workload the pipeline must sustain
BVH traversal	Rays walk the hierarchy depth-first, skipping any bounding box they miss	Dedicated RT Cores	Accelerates the most time-consuming part of ray tracing calculations
Ray-triangle intersection	Within the identified bounding volume, rays are tested against the few remaining triangles to find the closest hit	Intersection testing in the ray tracing pipeline	Determines where the ray interacts with an object
Shading	Further rays are traced from the hit point for shadows, reflections and global illumination; a miss shader supplies the environment	Shader pipeline with a shading binding table linking hits to materials	Determines the final color and appearance of the surface
AI denoising	A clean image is reconstructed from sparse ray-traced samples	Tensor Cores providing AI acceleration	Drastically reduces the number of rays that need to be cast

The real-time ray tracing pipeline, from ray generation to final pixel color

Process Stage

Key Operation

Enabling Hardware/Software

Performance Impact

Acceleration structure build

Bounding Volume Hierarchies (BLAS and TLAS) are created to organize scene geometry into nested bounding boxes

Driver/runtime BVH builders; TLAS transforms allow fast re-fits without touching geometry

Crucial for optimizing all subsequent ray intersection tests

Ray generation

Rays are cast from the eye through each pixel into the scene

Ray generation shaders

Defines the per-pixel workload the pipeline must sustain

BVH traversal

Rays walk the hierarchy depth-first, skipping any bounding box they miss

Dedicated RT Cores

Accelerates the most time-consuming part of ray tracing calculations

Ray-triangle intersection

Within the identified bounding volume, rays are tested against the few remaining triangles to find the closest hit

Intersection testing in the ray tracing pipeline

Determines where the ray interacts with an object

Shading

Further rays are traced from the hit point for shadows, reflections and global illumination; a miss shader supplies the environment

Shader pipeline with a shading binding table linking hits to materials

Determines the final color and appearance of the surface

AI denoising

A clean image is reconstructed from sparse ray-traced samples

Tensor Cores providing AI acceleration

Drastically reduces the number of rays that need to be cast

Read as a whole, the model shows that no single innovation makes real-time ray tracing work. The BVH shrinks the search space, the RT Cores accelerate the search itself, and the Tensor Cores shrink the number of searches required. Remove any one layer and the interactive frame rate collapses.