At very low resolutions, the GPU sim may not be much faster.Īlso keep in mind the general performance guidelines. The larger the resolution the better the speedup (GPU vs. If you have a supported GPU but don't have anything to select but "Use CPUs", update your driver (see Supported GPUs above). And despite the slight difference between Python 2.7 and Python 3. The fact is that in this version Maxon changed the Python version supported by Cinema 4D. When your system has only one GPU and you run large simulations, disable the viewport preview to speed up the simulation. There has been a lot of work preparing my plugins for Cinema 4D R23 compatibility. Ideally use two GPUs: one (possibly smaller one) as primary display GPU and one as a secondary GPU for simulation only. When choosing a GPU, prefer the one with the most per-GPU memory (note that per-GPU memory for Dual-GPU boards is usually half of the advertised amount)Įven prefer a slower GPU if it has more memory than an alternative faster GPU (see this post for the rationale behind this advice) Please make sure to use the latest driver for your graphics card. While TurbulenceFD technically works with less than 1GB of GPU memory, a GPU with 4GB or more memory is highly recommended. Nvidia GPUs with Compute Capability 2.0 or newer, listed at It will then continue the simulation on the CPU. This is also what TurbulenceFD will do automatically, should it run out of GPU memory. In fact, you can switch between CPU and GPU simulation on-the-fly (see Simulation Window). All features are supported at the same quality. Unlike with some GPU accelerated tools, this is not just a stripped down version of the CPU pipeline. TurbulenceFD makes use of GPUs for it's simulation pipeline. Coupled with the appropriate amount of parallel compute power, GPUs are the ideal type of processor for fluid simulation. Today's fastest memory interfaces are found in GPUs - about 10 times faster than those of CPUs. This makes memory bandwidth the most important factor for simulation speed. Mostly because there is a huge amount of data to be pushed around. Fluid Simulation needs quite a bit of processing power.
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