This page provides information on setting up V-Ray GPU.
GPU rendering allows V-Ray to perform the raytracing calculations on the GPUs installed in the system, rather than the CPU. Since GPUs are specifically designed for massively parallel calculations, they can speed up the rendering process by an order of magnitude.
To enable GPU rendering, select the CUDA or RTX option in the Export tab of the V-Ray Renderer settings.
Supported Hardware and Drivers
V-Ray GPU is based on the NVIDIA CUDA platform.
Below is a list of tests we have performed and the results:
- NVIDIA: NVIDIA GPUs use CUDA, since it runs faster and has more supported features. The CUDA engine is supported only in 64-bit builds of V-Ray for Maxwell-, Pascal-, Turing-, or Volta-based NVIDIA cards. See here if your card has the minimum required compute capability.
- NVIDIA RTX: Choosing RTX GPU mode works with RTX cards.
- Hybrid Rendering (running CUDA on GPU and CPU): V-Ray GPU rendering can be performed on CPUs and NVIDIA GPUs at the same time. Using the GPU Devices tool you can enable your CPUs as CUDA devices and allow the CUDA code to combine your CPUs and GPUs to utilize all available resources.
Rendering on multiple GPUs is supported and by default V-Ray GPU uses all available CUDA devices. See the sections below for information on how to choose devices to run V-Ray GPU on.
If V-Ray GPU cannot find a supported GPU device on the system, it silently falls back to CPU code. To see if the V-Ray render server is really rendering on the GPU, check out its console output.
When rendering, the console provides information about your current driver version. If the version is not compatible with V-Ray GPU, you will find a message with the recommended version.
Тo use NVLINK on supported hardware, NVLINK devices must be set to TCC mode. This is recommended for Pascal, Volta and Turning-based Quadro models. For GeForce RTX cards, a SLI setup is sufficient. Also note that to prevent performance loss, not all data is shared between devices.
For more information, see the OptiX and NVLink FAQ.
Choosing Which Devices to Use for Rendering
You may not want to use all available CUDA devices for rendering, especially if you have multiple GPUs and you want to leave one of them free for working on the user interface or you may want to combine your CPU and GPU together (see Hybrid Rendering section below). To do this, you can use the GPU Devices menu in the Export tab of the V-Ray Renderer node.
After changing this option, you need to restart the V-Ray render server (if it is running) for the changes to take effect. If the V-Ray render server is running as a Windows service, you may need to stop it from the Services applet in the Control Panel.
Balancing the GPU Load
If you have only one GPU on your system, you may find that the user interface becomes sluggish and unresponsive while IPR is rendering on the GPU. To alleviate this problem, reduce the Max. Paths Per Pixel and/or enable the Low GPU thread priority option in the Rendering section of the Renderer > IPR tab of V-Ray Renderer node. This breaks up the data passed to the GPU into smaller chunks so that the user interface requests can be processed faster. Note, however, that this reduces the rendering speed. Turn on the statistics display to check the difference in render speed and to find the optimal settings for your system.
Hybrid Rendering with CPUs and the CUDA Engine
V-Ray GPU can perform hybrid rendering with the CUDA engine utilizing both the CPU and NVIDIA GPUs. V-Ray can now execute the CUDA source on the CPU, as though the CPU was another CUDA device. To enable the hybrid rendering mode, simply enable the C++/CPU device from the list of CUDA devices.
The hybrid rendering mode does not require any special drivers. Furthermore, you can use the CPU as a CUDA device even if you don't have an NVIDIA GPU and/or NVIDIA drivers installed. Meaning, this mode can be used on computers that don't even have GPUs. The hybrid render engine running on a CPU supports the same features as the regular V-Ray GPU CUDA engine.
- The NVIDIA CUDA developer zone: https://developer.nvidia.com/category/zone/cuda-zone
- For more information on hardware recommendations, see the Hardware Recommendations article.