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In the pre-NVLink days, connecting multiple GPUs via an SLI bridge would do nothing to increase GPU rendering performance. However, there is one aspect of NVLink that should be a big boon to content creators right now, and that is the fact that the technology allows multiple GPUs to share framebuffer memory. In the short term, when adding a second Titan card to your rig, performance will probably scale in a very similar way to SLI.
#Nvidia gtx titan fp64 software#
NVLink is fairly new, and software developers need to tune their products to really take advantage of that bandwidth, so don’t expect to see massive performance increases just yet. Technology focus: NVLink and DirectX Raytracing Along the top of the card, Nvidia has done away with SLI in favor of its newer NVLink technology: a high-speed GPU interconnect boasting a bandwidth of 100 GB/s. Nvidia claims that the DisplayPort 1.4 connector can drive up to an 8K display at 60Hz on a single link. This card wants to be in a windowed, LED-ridden, art-project PC.Īt the rear of the card are five display outputs: three DisplayPort 1.4 ports, an HDMI 2.0 port, and a USB Type-C port.
It’s so pretty that it looked way out of place in the wire-jumbled workstation I used for testing. The Titan RTX uses Nvidia’s reference design cooler with its full-length vapour chamber and dual axial fans, but unlike the silver/aluminium GeForce RTX 20 Ti, it sports a bling-tastic gold colour scheme. Nvidia recommends a minimum 650W power supply, although 800W or higher would probably be preferable, especially if your system is sporting a newer high-core-count CPU like an AMD Ryzen Threadripper or an Intel Core i9. The Titan RTX is a 280W card, with a pair of 8-pin power connectors to feed the hungry GPU. The Titan RTX’s one weakness is compute performance: its FP32 performance is 16.3 Tflops, and its FP64 performance just 509 Gflops, much lower than the previous-generation Titan V. At 1,350 MHz, its base clock speed is the same as the 2080 Ti, but it boasts a slightly higher boost clock speed: 1,770 MHz as opposed to 1,635 MHZ. In addition, the Titan RTX sports a fully unlocked TU102 GPU sporting 4,608 CUDA cores, 72 streaming multiprocessors, 576 Tensor cores for machine learning, and 72 RT cores for ray tracing. It has 12 memory controllers on a 384-bit bus, for a total memory bandwidth of 672 GB/s. The Titan RTX has higher specs than any of Nvidia’s current-generation GeForce RTX cards, with its 24GB of GDDR6 memory more than double that available on the GeForce GTX 2080 Ti.
Now, with the Titan RTX, Nvidia is officially including content creators, as well as data scientists and developers of AI and deep learning systems, as part of its target market.
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On top of that, there were the rumors that Nvidia had begun quietly tuning the Titan drivers to boost performance in DCC applications, further cementing the reputation of the Titan GPUs as ‘Quadro, but not Quadro’.
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Content creators who needed more compute power – and more importantly, more memory – than Nvidia’s GeForce range of gaming cards, but who didn’t need the ISV certifications or support available with its more expensive professional Quadro cards, were turning to the Titans to power their desktop workstations. But as time went on, it began to feel like they were unofficially filling a niche in the 3D graphics market. The Titan GPUs started out as super-high-end gaming cards for those who wanted the best performance available, and for whom money was no object. The original Titan GPU, the GeForce GTX Titan, showed up back in early 2013, and was followed a year later by the much-loved GeForce GTX Titan Black and the GeForce GTX Titan Z, with new cards being added each time Nvidia moved to a new GPU architecture. The RTX-powered GPU we are looking at today is the newest of Nvidia’s high-end Titan range of graphics cards, the $2,499.99 Titan RTX. Instead, I am going to focus on how Turing performs in the real world – and specifically, how it affects DCC software. I won’t be going into technical detail here (if you want to how the hardware works, Anandtech has a good article). Turing is a huge advance over previous Nvidia architectures: not only is it faster all around, but it supports dedicated hardware-accelerated ray tracing through the processors’ new RT cores. One of the key innovations has been Nvidia’s Turing GPU architecture, found in its latest RTX graphics cards.
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Jason Lewis assesses how it performs with a range of key DCC and rendering applications.Īs I mentioned in my recent review of AMD’s Radeon Pro WX 8200, the last couple of years have seen huge steps forward in workstation hardware. Nvidia’s latest Turing GPU offers the power of a workstation card at a price closer to that of a gaming GPU.
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