البته vray یک نسخه vray rt هم داره که ازopenCL پشیبانی میکنه و از NVIDIA CUDA هم پشتبانی میکنه.بهتره از کارت گرافیک با بیش از 2 GB of video RAM استفاده کنی.بستگی به بودجه یک از کارت های NVIDIA رو انتخاب کن.
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V-Ray RT for GPU has two back-ends (or engines). One is based on OpenCL (see the references section below for more info on OpenCL) and the other one - on the nVidia CUDA platform.
The OpenCL engine should be able to run on any OpenCL-compatible hardware. However, as of the time of this writing (April 28th, 2012), only the nVidia implementation of OpenCL is sufficiently advanced to run it properly. For best results, a Fermi- or Kepler-based card with at least 2 GB of video RAM is recommended. Older cards will work, but performance will be significantly worse. Due to the large amount of RAM needed to compile the OpenCL code, currently it only works in 64-bit builds of V-Ray RT. It may be possible to run the OpenCL engine on software CPU implementations of OpenCL from AMD and Intel, however this has not been thoroughly tested.
The CUDA engine is supported only in 64-bit builds of V-Ray RT for Fermi- and Kepler-based nVidia cards. It is recommended to use the CUDA engine on nVidia GPUs.
Rendering on multiple GPUs is supported and by default V-Ray RT for GPU will use all available OpenCL/CUDA devices. See the sections below how to choose devices to run V-Ray RT GPU on.
V-Ray RT for GPU has been tested on a number of graphics cards including:
nVidia GeForce 680 GTX;
nVidia GeForce 580 GTX;
nVidia GeForce 590 GTX;
nVidia GeForce 570;
nVidia GeForce 480 GTX;
nVidia Tesla C2050;
nVidia Quadro 2000M;
If V-Ray RT for GPU cannot find a supported OpenCL/CUDA device on the system, it will silently fall back to CPU code. To see if the V-Ray render server is really rendering on the GPU, check out its console output
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