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RealFlow | Cinema 4D's fluid solver, and "Rigid" and "Elastic" deformers are GPU-accelerated. To enable this feature go to Scene > Solver > GPU and select a graphic board:

 

 

 

Q & A 

I can’t see any improvements in performance when I enable the GPU with RealFlow | Cinema 4D. Why?

RealFlow’s Dyverso solver is highly optimized for CPU multi-core and many-core processors. Some GPUs, on the other hand, do not have enough computational power to outperform a 8 or 12 core processor - which is common hardware today. For this reason a GPU-based simulation can be slower than a pure CPU-based simulation.

Which GPU do you recommend for improving performance with RealFlow | Cinema 4D?

We have observed that the number of GPU cores makes the difference. As a simple rule we can say: the more GPU cores, the better. A simulation with a NVIDIA Quadro K6000 (2880 cores) is about 3x faster than an Intel Core i7-3930K, for example.

Boards from the GeForce GTX 10 series, e.g. 1080 or 1080 Ti perform very good with RealFlow | Cinema 4D and offer the best value for money.

Unfortunately, we have observed problems with GeForce Titan X boards from time to time. Please contact us if you encounter crashes or slow simulations. Thank you!

In some simulations I observe an increased simulation speed with the GPU enabled, but others don’t perform better. Why?

Only the fluid solver is GPU-accelerated, but some processes, e.g. fluid-object collision, are entirely calculated by the CPU. In scenes with many collision objects and other, computationally expensive elements, you might not see a boost in performance by enabling the GPU.

My simulation is slower with the GPU enabled. What happens there?

This is a typical effect when GPUs are not supported or when the GPU is slower than the CPU.

Is it possible to use multiple GPUs or SLI-linked boards?

Sorry, currently not.

CUDA or OpenCL?

Both technologies are supported and the choice is made automatically by RealFlow | Cinema 4D.

How many particles can be simulated with my GPU?
  • The amount of VRAM determines the size of the simulation and there is currently no fallback on the mainboard's RAM.
  • It's difficult to give solid figures, because the final number depends on the entire scene, the used fluid type, and currently opened programs.
  • With 8 GB of VRAM, for example, it is possible to simulate 12-15 millions of Liquid PBD particles (assuming that the only open program is Cinema 4D with a scene containing one emitter, one fluid container, and one daemon).
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