Earlier quoted context omitted.
>Seems like it probably offloads most of the work on GPU It does just about everything on the GPU. All the CPU does is repeatedly render two triangles and play music: https://news.ycombinator.com/item?id=8070879 Here it has been adapted to WebGL: https://www.shadertoy.com/view/MdX3Rr Edit: I'm wrong about the two triangles. From the .nfo-file: for those wondering, this a (too) low density flat mesh displaced with a p…
Thanks for detailed response. I figured it mostly did GPU stuff. So, real computing necessary here is a massively-parallel chip with generic and custom hardware with a bunch of memory plus a regular core using 4KB on other end. I think a more interesting challenge would be to force use of a subset of GPU functions or memory plus tiny memory on CPU side. I don't follow demoscene close enough to know if they subset GPU…
Yes, there is massive amount of power available but it's not easy to use effectively. You need a different mental model how things work, there's very little shared state and all the algorithms used have to match the model of computation.
Using the GPU almost exclusively, generating everything procedurally is a massive accomplishment and much more difficult than "normal" CPU+GPU programming or using just the CPU.
I do not share your view that this would be somehow less impressive because it uses the GPU.