XPU is useful for generating fast, high-quality preview renders, within its current capabilities. Apple M1/M2 16 GB oder AMD Navi oder Vega GPU mit mindestens 8 GB VRAM. Karma XPU is not (currently) a replacement for the CPU engine, but rather a high performance, feature-limited subset intended to accelerate iterations for artists. R21 oder neuer SideFX Houdini (Windows, Linux): 64-bit, Version 17.5 oder. However, XPU may have less functionality, and/or generate less-correct or just different output from the CPU-only engine. ![]() Making an existing solver differentiable requires only a few modifications and the model is compatible with both modern CPU and GPU multi-core hardware. ![]() No matter what mixture of devices it uses, the XPU engine should produce the exact same result.īecause it uses hardware acceleration, Karma XPU is extremely fast compared to the CPU-only engine. SideFX has now officially released Houdini for Apple Silicon. Our approach demonstrates excellent efficiency and we demonstrate this on high resolution meshes with optimizations involving over 26 million degrees of freedom. ![]() If a device fails, as may be the case with a GPU running out of memory, the other devices (including the CPU) will pick up the load and finish rendering the frame. It will use any compatible devices it can detect, including multiple GPUs. Karma XPU is a selectable engine of the Karma renderer that uses CPU resources and also takes advantage of the GPU and hardware acceleration. Also please note that this help page represents XPU as of the latest daily release. The current functionality is unfinished and subject to change, and may have thin or no documentation. So any advice on the most optimal way to build a multi GPU rig would be greatly appreciated.The XPU engine is currently in beta. My original thinking was that each card would be used totally independently. The first one showcases the possibilities of the VAT tool and demonstrates its RBD interpolation techniques, fluid UVs, tangent-space normal support, texture memory reduction, streamlined workflows, up to 9 channels of custom data, and a lot of extendability. Below are my specs: CPU Intel Core i7 10700 CPU 2.90GHz (16 CPUs) 2.9GHz Motherboard Gigabyte H47- HD3 Memory (2 16GB 2400MHz CL15, DDR4) GPU NVIDIA GeForce GTX 1080 It's kind of difficult to work on Houdini sometimes as it gets very laggy between frames, and rendering times are just too slow. And in general, a rig with multiple GPU's will always get throttled down to the slowest GPU. The SideFx Labs team has released 2 great and in-depth tutorials on using VAT. Ideally I'd like to use my 2 old cards, and then eventually add something beefier as well: 660ti 3gb - viewport card 1070ti 8gb - for sim and rendering Titan RTX 24 gb - TBD on this last card, but it will be something big for sim and rendering I'm being told on the Tom's hardware forum that using these cards will basically result in bottlenecking everything because the 660ti is so old. Houdini 15 requires an OpenGL 3 compliant graphics card and a driver that provides OpenGL 3.3 support. So I'd like to get some advice if it's possible to mix and match different cards to do this, or if they need to be relatively similar or the same card. I understand only one GPU can be used for OpenCL, and one is used for viewport. ![]() I'm building a new rig and am trying to understand the most optimal way to build in multiple GPU's for sim and rendering.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |