4/12/2023 0 Comments Titan v fp64 performanceTaking a step back, the approach with Volta doesn’t mesh with NVIDIA’s previous approaches with Pascal and others. If that were to change with the Quadro GV100, cryptomining will ensure that prices are kept apart. Other than NVLink, Titan V’s main compute functions (FP64, FP16, tensor core) are uncrippled, which makes sense as single node Titan V’s don’t quite cannibalize sales of NVIDIA’s other compute products. And on that note, while Titan V’s non-ECC HBM2 and GeForce driver stack are more consumer oriented, the card still directly benefits from software support with frameworks and APIs as part of NVIDIA’s overall deep learning development efforts. Ultimately, as we’ve discussed prior, NVIDIA seeds academics, developers, and other researchers at a lower cost-of-entry to Tesla V100s, with the feedback contributing to ecosystem support of Volta. So a more-prosumer-than-consumer Titan V part would be the best – and only – fit, given that the gaming performance isn’t at the level of $3000. Meanwhile, it’s fair to assume pushing the reticle limit (815mm 2) on a new process node (12nm FFN) with new microarchitecture and additional HBM2 packaging results in poor-yielding silicon, and thus fewer options for salvage parts, especially if they needed to be validated at enterprise level (i.e. Nor is there any particular competitive pressure in pricing or performance – the GeForce GTX 1080 Ti has no direct competition while the Pascal-based Titan X/Xp has carved out a $1200 price bracket above the previous $1000 mark. NVIDIA has less need to make a name for itself with the Titan line, of which the original GTX Titan did exactly that by invoking the NVIDIA’s K20Xs powering Oak Ridge National Laboratory’s Titan supercomputer, and then setting a new high in performance (and price). Remaking of a Titan: Less Flagship, More Computeĭeep learning and compute aside, there are a few more factors involved in this iteration of the Titan brand. So as it stands, Volta is only available to the broader public in the form of the Titan V, though depending on the definition of ‘broader public,’ the $9000 32GB Quadro GV100 released in March might fall under that category too. With Volta, there's little detail of anything other than GV100 existing, outside of Tegra Xavier’s Volta iGPU, which is also part of Drive PX Pegasus. NVIDIA Tesla/Titan Family Specification Comparison Up until Titan V, NVIDIA’s Titan lineup more-or-less represented that design methodology, where a big GPU served as lynchpin for both compute and consumer lines. Looking back, it’s a far cry from the original Kepler-based GeForce GTX Titan, a jack-of-all-trades video card that acted as enthusiast flagship with full double precision (FP64) compute for prosumers. Complete with a workstation-class price tag of $3000, the Titan V doubled-down on high performance compute (HPC) and deep learning (DL) acceleration in hardware and software, while maintaining the fastest graphics performance around. NVIDIA GPU Specification ComparisonĬircling back to NVIDIA’s compute endeavors, with Titan V, the Titan brand became closer than ever to workstation-class compute, featuring a high-end compute-centric GPU for the first time: the gargantuan 815 mm 2 GV100. Matching up with the NVIDIA Titan V are the Titan Xp and GeForce GTX Titan X (Maxwell), with the AMD Radeon RX Vega 64 also present for some tests. The most eye-catching of Volta’s new features are the new specialized processing blocks – tensor cores – but as we will see, this is very much integrated with the rest of Volta's microarchitectural improvements and surrounding software/framework support for deep learning (DL) and high performance compute (HPC). Deep learning prowess is the calling card of the Titan V and of Volta in general, and that performance is what we will be investigating today. Which is to say, deep learning and neural networking has quickly become the driving force behind NVIDIA GPUs as state-of-the-art compute accelerators, now incorporating built-in hardware and software acceleration for machine learning operations. We came away with the understanding that the Volta-based Titan V was a new breed of NVIDIA’s prosumer line of video cards, one that essentially encapsulated NVIDIA’s recent datacenter/compute achievements and how they got there. When we last discussed the NVIDIA Titan V in our preview, it was only a few weeks after its surprise launch at the 2017 Neural Information Processing Systems conference.
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