Right now I’m going to suggest we get 1 of each card, and test with our own software, however it would be nice to have some actual FP64 benchmarks to show. The use case is computing linear algebra, specifically complex matrix operations. ![]() I would like to find a FP64 benchmark that doesn’t involve any ML/Deep Learning/AI, as I don’t want the additional tensor cores in the A6000 to impact the results, as these will be largely useless for our use case. However, I have been unable to find any FP64 benchmarks that have tested both the A6000 and the 3090 card, to confirm the numbers in the specifications. If the statement above is true I’d recommend the A6000, as it has much lower TDP than 2x 3090, making it easier to cool, and add cards later on. For example, on a GTX 780 Ti, the FP64 performance is 1/24 FP32. So vendors like NVIDIA and AMD do not cram FP64 compute cores in their GPUs. This is because they are targeted towards gamers and game developers, who do not really care about high precision compute. The GA102 graphics processor is a large chip with a die area of 628 mm and 28,300 million transistors. Built on the 8 nm process, and based on the GA102 graphics processor, the card supports DirectX 12 Ultimate. My colleagues doesn’t know anything about GPU’s and I’ve only built them as a hobby for gaming, so I was the best candidate (.įor our price range, I’ve narrowed it down to either 3090 or A6000.Īs I see it, the VRAM to cost ratio is basically identical for the 3090 and A6000, and the FP64 performance to cost ratio is also somewhat identical for the two cards. GPUs, at least consumer grade, are not built for high performance FP64. The RTX A6000 is an enthusiast-class professional graphics card by NVIDIA, launched on October 5th, 2020. I’ve been tasked with picking parts for a new workhorse pc. I’m working for a small engineering firm, that produces water simulation software.
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