There are a few reasons the speedup scheme you’re talking about doesn’t get used for GPU ray tracing. On a GPU, time to first image that fills all pixels is not

There are a few reasons the speedup scheme you’re talking about doesn’t get used for GPU ray tracing. On a GPU, time to first image that fills all pixels is not typically a problem, and rendering every other pixel and interpolating is more complicated and might take long enough that it doesn’t actually help. Rendering every other pixel on a CPU in JavaScript is a huge advantage because ray tracing on that platform is incredibly slow compared to GPU ray tracing, and rendering is done sequentially one pixel at a time. Rendering on a GPU is very different because it handles thousands of rays at a time in parallel, and the typical time to get the first complete image on-screen is a fraction of a second. Today’s high end GPUs can trace tens of billions of rays per second, so with that kind of budget it’s easy to get through all the pixels of a 1080p image with multiple rays per pixel. The images in your blog post can be ray traced on today’s high end GPUs at 60hz with tens or even hundreds of samples per pixel for antialiasing. Another reason a pixel interpolation scheme isn’t used on GPUs is because you don’t have random access to neighboring pixels during a single launch. What this means in practice is you’d have to do a ray tracing launch followed by the interpolation launch. The launches have some overhead, and the UX would be that you first see the checkerboard pattern all at once, and then later you get the interpolated image. You don’t get to see partial progress as you go, unless you’re breaking the image into tiled launches, and that slows down rendering and adds more complication. (Many pro renderers on the market do have tiled rendering to give progressive feedback, BTW). On the GPU, maybe one of the closest things to what you describe that is being used in games today is DLSS; render a lower resolution image, then upscale to a higher resolution. Instead of interpolating neighbor pixels per se, it’s using a neural network to improve the interpolation based on the image content https://en.wikipedia.org/wiki/Deep_learning_super_sampling https://en.wikipedia.org/wiki/Deep_learning_super_sampling There are approaches to deferred shading on the GPU that do something similar to what you’re talking about https://graphics.geometrian.com/research/dacs_in_hw.html https://graphics.geometrian.com/research/dacs_in_hw.html There is also denoising, which has the same high level goal as what you’re doing (fill in missing data to get a high quality preview faster), but uses a much more sophisticated interpolation algorithm, and rather than skipping pixels works on Monte Carlo images with low samples per pixel. https://developer.nvidia.com/optix-denoiser https://developer.nvidia.com/optix-denoiser