![]() ![]() GP100 allows having only 2 GPUs connected. Answer to those questions will come as more people gets to use and test those. I don't really know since we haven't tested that much, but the good thing is that we have controll on which memory gets allocated where, so if it gets too slow, or if it needs the opposite - sharing more stuff between the GPUs, it is quite easy to do. At some point I guess too much memory sharing would result in slowing down the render (because NVLINK transfer will become a bottleneck). We can also controll precisely which memory we want to have copies on each GPU. Will vray-rt support it? I mean will be 4 cluster of cards in one machine, i don't know if you see that way, maybe it isn't a problem at all(one can hope).Īnyway thank you very much for the answer, and the link.How much less than 32GB is scene specific and although we have tested the NVLINK I can't tell exactly how much less. Well, do you think that this "not very large in size but used often on each GPU" overcome 2G? because i'll be pretty happy with 30G for my scene(15G on each card).Īlso Blago, since you guys already working on this nvlink, do you think that is possible to build a machine with 8 GP100 or better saying 4 nvlinked GP100s? Just like a nvidia VCA. That's ok since you already let us know that this thing is even faster than P6000. On paper it should be slower, but it is different architecture and because of that comapring just TFLOPS doesn't tell the whole story. So usable memory will be below 32GB.Īlso, GP100 is about 25 to 65 percent faster than P6000 with V-Ray GPU. Also, we still make copies of data that is not very large in size but used often on each GPU. Yes, V-Ray GPU is the first comercial product outside NVIDIA that supports NVLINK. We plan to do some R&D on uses of FP16 for some calculations (but only for small parts of the code - no way to make everything FP16) when the FP16 becomes more massively adopted.Ģ. while pci is able to transfer up to 32G/s the nvlink run up to 80G/s, also Nvidia state that with 2 cards on this link a software can see not 16G x 2 but a single 32G card.Ģ) My question is: Vray-RT is one of this softwares? If so means one can load a 32G scene right? But here is the thing: It has a nvlink able to connect 2 cards. I know it's really expensive at $9,000 where you can have a 24G, 12Tflops fp32 P6000 at $6,000. Nvidia has this Quadro GP100 that have 5.2Tflops FP64, 10.3Tflops FP32 and 20.7 Tflops FP16ġ) So i'm wondering, does Vray-RT use FP64, FP32 or FP16?Īlso about memory, Quadro GP100 have only 16G hbm2. Enterprises deploying AI can use A30’s inference capabilities during peak demand periods and then repurpose the same compute servers for HPC and AI training workloads during off-peak periods.Originally Posted by abowen does anyone know if double precision (FP64) memory makes a noticeable difference on the titan black ? not sure its worth the extra coin verses getting an extra card maybe to add to your system.ĭouble-precision calculations make no difference to V-Ray RT (and most other GPU renderers out there). The combination of FP64 Tensor Cores and MIG empowers research institutions to securely partition the GPU to allow multiple researchers access to compute resources with guaranteed QoS and maximum GPU utilization. HPC applications can also leverage TF32 to achieve higher throughput for single-precision, dense matrix-multiply operations. Combined with 24 gigabytes (GB) of GPU memory with a bandwidth of 933 gigabytes per second (GB/s), researchers can rapidly solve double-precision calculations. ![]() ![]() NVIDIA A30 features FP64 NVIDIA Ampere architecture Tensor Cores that deliver the biggest leap in HPC performance since the introduction of GPUs. To unlock next-generation discoveries, scientists use simulations to better understand the world around us.
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