With V-Ray Hybrid they can render using all the hardware they have. Many artists and studios have GPU & CPU workstations and CPU render nodes. If you have a powerful workstation, say 40 CPU cores and 4 GPUs, you can take advantage of all its computing power. Let’s consider a few use cases for V-Ray Hybrid It’s a welcome speed boost, rather than leaving these powerful CPUs idle. To find out the speed boost we get by adding CPUs to the GPU mix, we benchmarked two V-Ray CUDA scenes from our friends at Dabarti Studio.įor these scenes, the addition of CPUs helped reduce render times by 13% and 25%. Now that V-Ray CUDA was rendering on both CPUs and GPUs, and producing the exact same results, V-Ray Hybrid rendering was officially born. Once he had it working, Blago could identify exactly which line of code caused the crash.

To make GPU debugging easier, our lead GPU developer Blago Taskov had the idea to port the CUDA code over to the CPU, where he could use better debugging tools. This process can be tedious and time consuming. To uncover the cause, a developer will comment out each section of the code until the culprit is found. When the code crashes, as it inevitably does, it may only return a kernel dump, with no information about which part of the code actually caused the crash.

Vray benchmark results