![]() ![]() I’ve seen sporadic results from Radeon cards using that benchmark that I have not seen on GeForces and Quadros. I had thought for about half a second to include standalone V-Ray Benchmark results here as well, but the fact of the matter is, that doesn’t work great on AMD GPUs, either. I’m not entirely opposed to drinking tea that looks like it does on the AMD card, but when it’s supposed to look like the much lighter tea in the original shot, I think I’d pass. But it renders poorly enough with the projects I do have to forego Radeon inclusion for the time-being.įor an example of what I’m talking about, compare the Teaset render on both NVIDIA/CUDA, and then AMD/OpenCL (notice the color of the Turkish Delight):Ī sample V-Ray render with AMD Radeon Pro I can only use what’s available to me, so it could be that your project would render just fine. That’s at least based on the public scenes I can find. While the renderer now offers OpenCL support for use with non-CUDA GPUs, AMD’s Radeon cards have yet to render a scene properly that does render properly on NVIDIA. That’s really all it takes to add Turing support to OctaneBench, and as we’ll see, the results are impressive.īefore finally jumping into testing, I have a few thoughts on V-Ray. How we got it to work was via a tip from the fine folks at Puget Systems, which is to simply download the 3.08 OctaneRender demo, and copy its engine files into the OctaneRender folder. Whenever it happens, I’ll be throwing RTX at it.Įven OctaneBench, included in this performance look, doesn’t support Turing. Currently, the blobs needed to support Turing are being kept internal, and I have no timeline on when that will transition into public code. In particular, the most up-to-date version of Blender will not render a scene with Turing, an issue known both to Blender and NVIDIA. I’d expect to see a few renderers take advantage of RTX features by the end of the year, but most of the love is going to come in 2019.Īcross the ecosystem, Turing support is a little rough in parts right now, but that’s par for the course when a brand-new GPU architecture launches. Chaos Group reported on its own benchmarking work this past week, at the same time noting that support for the RT core will come once NVIDIA’s OptiX engine itself supports it. On the topic of RTX, none of the tests included here can take advantage of the special features of Turing (right now) namely, the Tensor and RT cores. ![]() Fortunately, all three of the tests featured in this article perform the same on either GeForce or Quadro, which makes the GeForce RTX inclusion a good gauge of what can be expected from the equivalent workstation GPUs (with the Quadro RTX cards expecting to perform slightly better due to having the full GPU unlocked). That could change in the future, but I’m at the mercy of what NVIDIA wants to send, and when it wants to send it. To nip a question in the bud: we do not have Quadro RTX cards in the lab. What I am not entirely sure on at this point is whether or not RTX feature sets will vary at all in the future between GeForce and Quadro.Īrchitecture: GTX & TITAN = Pascal RTX = Turing Performance from Pascal to Turing has seen a nice boost as it is, but the future prospects of RTX features being taken advantage of is what makes the new Quadros (and GeForces) exciting.įor those hoping to get great performance on the cheap, you’ll be happy to know that GeForces will handle all three of the tasks on this page without issue. Even the RTX 5000 is attractive at its price-point in comparison to the last-gen P5000, though that could be said about all of the RTX cards. If 48GB is actually too much VRAM, or you’re wanting to save a few thousand dollars, the 24GB RTX 6000 is going to be a worthy consideration. ![]() Turing has so far infused three GPUs for both GeForce and Quadro, with the top-dog being the Quadro RTX 8000, priced at $10,000. It’s also Volta-based, but has TITAN Xp-matching levels of VRAM, at 12GB.ġ GDDR6 + ECC 2 GDDR6 3 GDDR5X + ECC 4 GDDR5X 5 GDDR5 + ECC 6 GDDR5 7 HBM2 + ECC 8 HBM2Īrchitecture: P = Pascal V = Volta RTX = Turing TITAN V could easily belong in the GeForce table, but given its focus, it’s worthier of being on the Quadro side. At the moment, most of NVIDIA’s current-gen GeForces and Quadros are Turing-based, with the Volta-based GV100 proving to still be a good choice for those with specific deep-learning needs (and a lot of memory bandwidth). ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |