7 ms·

A lot of Nvidia's new RTX tech may be marketed towards gaming but it's actually having an impact in 3D rendering. Cycles supports RTX out of the box now and I'm

by MH15 6y ago

A lot of Nvidia's new RTX tech may be marketed towards gaming but it's actually having an impact in 3D rendering. Cycles supports RTX out of the box now and I'm sure other renderers will/do as well. And the denoising tech is amazing, while not up to the challenge on final renders it's perfect for getting a quick frame upstream.

m12k 6y ago
If nothing else the tech allows 3D artists and level designers to get instant feedback while they are tweaking a scene, without having to wait for a full render/lightmap bake - having iteration time go from minutes to seconds is a game changer for creative work like that.
- fxtentacle 6y ago
  But sadly, it doesn't work like that. Let's say I render a reflective vase in V-Ray and use NVIDIA OptiX denoising. The ray-tracer will cast a few specular rays so that some pixels will get super bright from having a direct reflection of the light source, while other pixels will not yet receive specular illumination. The OptiX denoising will then blur things out, so that the entire vase is equally brightened up. But that quick preview looks so significantly different from the final rendering result, that it is effectively useless and, of course, highly misleading. In the final result, only the parts of the surface where the curvature is "just right" will receive specular. In my preview, everything will.
  - virtualritz 6y ago
    Using GPUs for offline rendering to gain speed is a dangerous fallacy. Dangerous because the GPU has many restrictions which developers have to invest time in working around. I feel in recent years makers of offline renderers have spent more time dealing with these restrictions to get their renderers to work well with GPUs than actually improving their renderers. I.e. reduce level of noise, better algorithms for hair, volumes, etc. The renderers produce way too much noise (or have prohibitive render times w/o except for big studios). Solution? Denoising! Which is (mostly) using GPU-powered ML! The irony of this seems lost on many freelancers who buy expensive GPU rigs to be able to deliver their jobs on the likes of OTOY or Redshift. For this money you can buy a vastly superior CPU rig. If only your renderer could use it! Most people compare apples to oranges here. When I hear people rave about GPU offline renderers, I usually ask them: - Have you made time to first pixel part of your comparison (complex scenes can take dozens of minutes before they start rendering on GPU renderers). - Are you comparing images as they come out of renderer A before denoising to images of renderer B before denoising? Because anyone can pipe their shit through Intel Open Image Denoise after the fact. It's free even. - Have you actually used a machine that has more than eight cores personally in production? If all your money goes into buying expensive graphics cards your CPU is usually shite. A notable exception is 3Delight which doesn't even ship a denoiser. On simple scenes the renderer can't beat the GPUs but on anything a bit more complex -- the stuff you deal with in actual production -- it smokes the competition CPU & GPU alike. Not least in the amount of noise it produces using comparable sampling settings. Without using any GPU compute. When this GPU craze took over other vendors who's renderers were traditionally CPU bound too, in the last 5-6 years, 3Delight's developers have spent all their time finessing the performance and output quality w/o relying on GPUs. It shows.
    - ben-schaaf 6y ago
      Cycles does the same work regardless of whether it's running on the CPU or GPU. You can even run mixed where both the CPU and GPU do rendering. The amount of noise has nothing to do with it running on the GPU or not, that's simply how path-tracing works...
      - wtracy 6y ago
        I think the implication is that GPU rendering ends up using lower-precision floating point numbers than are available on modern CPUs, which leads to more rounding errors.
        gmueckl 6y ago
        No, CPU renderers also use IEEE single precision floats for performance. Unless you do something really absurd[0], single precision has more than enough range and resolution to not lead to any noticable inaccuracies in the result. [0] like trying to render an insect eye to scale while having everything shifted 1000km from the origin.
        fxtentacle 6y ago
        While that is in general correct, most GPUs do not fully adhere to IEEE or they do not calculate at full resolution. It's a well-documented fact that the same floating point operations on a GPU will have less precision than on CPU, despite both using the same IEEE storage format. https://developer.nvidia.com/sites/default/files/akamai/cuda/files/NVIDIA-CUDA-Floating-Point.pdf https://developer.nvidia.com/sites/default/files/akamai/cuda...
        dahart 6y ago
        That paper does not say what you claim it does, it is not showing that GPUs are computing at lower resolution, nor that CUDA is failing to adhere to the IEEE 754 standard. In at least two cases, it says the opposite of what you just claimed: FMA on the GPU was a way to achieve higher float precision than you could with CPU math, in 2011 when the paper was written. That is changing now with CPU adoption of fma, but that doesn't change the claims of the paper. The GPU's strict adherence to IEEE 754 is mentioned multiple times. "The same inputs will give the same results for individual IEEE 754 operations to a given precision on the CPU and GPU. As we have explained, there are many reasons why the same sequence of operations may not be performed on the CPU and GPU. The GPU has fused multiply-add while the CPU does not. Parallelizing algorithms may rearrange operations, yielding different numeric results. The CPU may be computing results in a precision higher than expected. Finally, many common mathematical functions are not required by the IEEE 754 standard to be correctly rounded so should not be expected to yield identical results between implementations."
  - dahart 6y ago
    You’re attempting to draw a broad conclusion from a contrived corner case example. All you have to do is wait a little longer for more specular samples. The question is whether you wait for less time with denoising than without to get a pretty good preview, and the answer is yes. Many artists are really happy with denoising, and would rather have it than not, regardless of whether the processor is a GPU or CPU.
    - fxtentacle 6y ago
      Well I had to pick an example to illustrate my grief with denoising, but the problems are not limited to my example. In general, if you take an AI to replace your noisy image with a noise free but plausible alternative, you should be aware that you're replacing content, so that this can change what you see to the point where it is not representative of the fully converged image anymore.
      - dahart 6y ago
        In general, it's still true that denoising a higher quality input will yield a higher quality (closer to resolved) output, so all you have to do is wait a little longer. Denoising is typically applied in interactive environments where you don't get a static result, you get a new denoised result that includes more samples every frame. Undersampling is easy to spot because the denoised image jumps a lot every frame. Once it stops moving a lot, you can have a lot more confidence. So the problem you're citing is not one that you're stuck with, and it's not a problem in practice.
  - m12k 6y ago
    I don't know if you noticed that one of the use cases I mentioned was level artists. 9 times out of 10, a level artist isn't trying to optimize some specular highlight in a vase, they are trying to see if this room is lit in a good way (aesthetically pleasing, the player can see the right things and so on). So I agree that there are use cases for which a fast denoised preview isn't useful, like the one you mention, but there certainly are ones for which it is quite sufficient, and infinitely better than waiting around for minutes waiting for the lightmaps to bake GI.

by MH15 6y ago

m12k 6y ago

If nothing else the tech allows 3D artists and level designers to get instant feedback while they are tweaking a scene, without having to wait for a full render/lightmap bake - having iteration time go from minutes to seconds is a game changer for creative work like that.

fxtentacle 6y ago
But sadly, it doesn't work like that. Let's say I render a reflective vase in V-Ray and use NVIDIA OptiX denoising. The ray-tracer will cast a few specular rays so that some pixels will get super bright from having a direct reflection of the light source, while other pixels will not yet receive specular illumination. The OptiX denoising will then blur things out, so that the entire vase is equally brightened up. But that quick preview looks so significantly different from the final rendering result, that it is effectively useless and, of course, highly misleading. In the final result, only the parts of the surface where the curvature is "just right" will receive specular. In my preview, everything will.
- virtualritz 6y ago
  Using GPUs for offline rendering to gain speed is a dangerous fallacy. Dangerous because the GPU has many restrictions which developers have to invest time in working around. I feel in recent years makers of offline renderers have spent more time dealing with these restrictions to get their renderers to work well with GPUs than actually improving their renderers. I.e. reduce level of noise, better algorithms for hair, volumes, etc. The renderers produce way too much noise (or have prohibitive render times w/o except for big studios). Solution? Denoising! Which is (mostly) using GPU-powered ML! The irony of this seems lost on many freelancers who buy expensive GPU rigs to be able to deliver their jobs on the likes of OTOY or Redshift. For this money you can buy a vastly superior CPU rig. If only your renderer could use it! Most people compare apples to oranges here. When I hear people rave about GPU offline renderers, I usually ask them: - Have you made time to first pixel part of your comparison (complex scenes can take dozens of minutes before they start rendering on GPU renderers). - Are you comparing images as they come out of renderer A before denoising to images of renderer B before denoising? Because anyone can pipe their shit through Intel Open Image Denoise after the fact. It's free even. - Have you actually used a machine that has more than eight cores personally in production? If all your money goes into buying expensive graphics cards your CPU is usually shite. A notable exception is 3Delight which doesn't even ship a denoiser. On simple scenes the renderer can't beat the GPUs but on anything a bit more complex -- the stuff you deal with in actual production -- it smokes the competition CPU & GPU alike. Not least in the amount of noise it produces using comparable sampling settings. Without using any GPU compute. When this GPU craze took over other vendors who's renderers were traditionally CPU bound too, in the last 5-6 years, 3Delight's developers have spent all their time finessing the performance and output quality w/o relying on GPUs. It shows.
  - ben-schaaf 6y ago
    Cycles does the same work regardless of whether it's running on the CPU or GPU. You can even run mixed where both the CPU and GPU do rendering. The amount of noise has nothing to do with it running on the GPU or not, that's simply how path-tracing works...
    - wtracy 6y ago
      I think the implication is that GPU rendering ends up using lower-precision floating point numbers than are available on modern CPUs, which leads to more rounding errors.
      - gmueckl 6y ago
        No, CPU renderers also use IEEE single precision floats for performance. Unless you do something really absurd[0], single precision has more than enough range and resolution to not lead to any noticable inaccuracies in the result. [0] like trying to render an insect eye to scale while having everything shifted 1000km from the origin.
        fxtentacle 6y ago
        While that is in general correct, most GPUs do not fully adhere to IEEE or they do not calculate at full resolution. It's a well-documented fact that the same floating point operations on a GPU will have less precision than on CPU, despite both using the same IEEE storage format. https://developer.nvidia.com/sites/default/files/akamai/cuda/files/NVIDIA-CUDA-Floating-Point.pdf https://developer.nvidia.com/sites/default/files/akamai/cuda...
        dahart 6y ago
        That paper does not say what you claim it does, it is not showing that GPUs are computing at lower resolution, nor that CUDA is failing to adhere to the IEEE 754 standard. In at least two cases, it says the opposite of what you just claimed: FMA on the GPU was a way to achieve higher float precision than you could with CPU math, in 2011 when the paper was written. That is changing now with CPU adoption of fma, but that doesn't change the claims of the paper. The GPU's strict adherence to IEEE 754 is mentioned multiple times. "The same inputs will give the same results for individual IEEE 754 operations to a given precision on the CPU and GPU. As we have explained, there are many reasons why the same sequence of operations may not be performed on the CPU and GPU. The GPU has fused multiply-add while the CPU does not. Parallelizing algorithms may rearrange operations, yielding different numeric results. The CPU may be computing results in a precision higher than expected. Finally, many common mathematical functions are not required by the IEEE 754 standard to be correctly rounded so should not be expected to yield identical results between implementations."
- dahart 6y ago
  You’re attempting to draw a broad conclusion from a contrived corner case example. All you have to do is wait a little longer for more specular samples. The question is whether you wait for less time with denoising than without to get a pretty good preview, and the answer is yes. Many artists are really happy with denoising, and would rather have it than not, regardless of whether the processor is a GPU or CPU.
  - fxtentacle 6y ago
    Well I had to pick an example to illustrate my grief with denoising, but the problems are not limited to my example. In general, if you take an AI to replace your noisy image with a noise free but plausible alternative, you should be aware that you're replacing content, so that this can change what you see to the point where it is not representative of the fully converged image anymore.
    - dahart 6y ago
      In general, it's still true that denoising a higher quality input will yield a higher quality (closer to resolved) output, so all you have to do is wait a little longer. Denoising is typically applied in interactive environments where you don't get a static result, you get a new denoised result that includes more samples every frame. Undersampling is easy to spot because the denoised image jumps a lot every frame. Once it stops moving a lot, you can have a lot more confidence. So the problem you're citing is not one that you're stuck with, and it's not a problem in practice.
- m12k 6y ago
  I don't know if you noticed that one of the use cases I mentioned was level artists. 9 times out of 10, a level artist isn't trying to optimize some specular highlight in a vase, they are trying to see if this room is lit in a good way (aesthetically pleasing, the player can see the right things and so on). So I agree that there are use cases for which a fast denoised preview isn't useful, like the one you mention, but there certainly are ones for which it is quite sufficient, and infinitely better than waiting around for minutes waiting for the lightmaps to bake GI.