Nvidia Announces 'Nvidia Titan V' Video Card: GV100 for $3000 (anandtech.com)

Nvidia has announced the Titan V, the "world's most powerful PC GPU." It's based on Nvidia's Volta, the same architecture as the Nvidia Tesla V100 GPUs behind Amazon Web Service's recently launched top-end P3 instances, which are dedicated to artificial-intelligence applications. From a report: A mere 7 months after Volta was announced with the Tesla V100 accelerator and the GV100 GPU inside it, Nvidia continues its breakneck pace by releasing the GV100-powered Titan V, available for sale today. Aimed at a decidedly more compute-oriented market than ever before, the 815 mm2 behemoth die that is GV100 is now available to the broader public. [...] The Titan V, by extension, sees the Titan lineup finally switch loyalties and start using Nvidia's high-end compute-focused GPUs, in this case the Volta architecture based V100. The end result is that rather than being Nvidia's top prosumer card, the Titan V is decidedly more focused on compute, particularly due to the combination of the price tag and the unique feature set that comes from using the GV100 GPU. Which isn't to say that you can't do graphics on the card -- this is still very much a video card, outputs and all -- but Nvidia is first and foremost promoting it as a workstation-level AI compute card, and by extension focusing on the GV100 GPU's unique tensor cores and the massive neural networking performance advantages they offer over earlier Nvidia cards.

Comments

But can it pay for itself mining Coin?

[bobbied]

Somehow, I seriously doubt it.

Re:But can it pay for itself mining Coin?

[NicknameUnavailable]

It might be more useful in the realm of folding. Folding is a much more complex operation and tends to need more RAM, more cores being useful as well, and fast throughput on the bus. The big issue with mining cards when applied to folding is that you can't get a motherboard supporting more than 4, maybe 6 PCIe 8x-16x bus lines then you need a CPU core for each card on top of it. If you can pack 2 GPUs worth of power into a single card suddenly you have double the capacity (or rather, nearly on part with the 12 GPUs you can pack into a mining machine with PCIe 1x buses.)

Imagine a Beowulf cluster of these

[Anonymous Coward]

Imagine a Beowulf cluster of these

Built for number crunching

[UnknownSoldier]

Before we get the deluge of "What's this used for?" we need to take a look at the specs.

Float64 performance is only 1/2 of float32 -- WOW! This thing is built for number crunching! (The original Titan has 1/3 float64 performance. Gamers screamed bloody murder when it sold at $1,000 but they weren't the target audience.)

Bandwidth has been neutered at only 653 GB/sec due to the 3,072 bit Memory Bus Width compared to 900 GB/sec of the Tesla V100.

Compared to spending to $10,000 at $3,000 this is basically the "poor man's" Tesla V100 specifically designed for AI. I see the full 640 Tensor Cores.

TL:DR; If you are doing number crunching (C's "double"), or AI / ML (machine learning) this might be a bargain GPU. Otherwise, it has almost zero practical value from a Gamer's POV.

Re:Built for number crunching

[afidel]

What's interesting is the difference between the NVidia approach and Google's TensorFlow approach. NVidia is beefing up FLOAT64 performance while Google focused on 8bit and 16bit performance (OPS/W) which is why Googles newest gaming challenge used a single TPU running at 40W to run the AI (after training on 5,000 TPUs and thousands of cores).

Re:Built for number crunching

[Guybrush_T]

Quite the opposite. The focus seems to be on fp16 with tensor cores massively increasing the throughput at that precision. But fp64 is good as well, which could be good for other professional applications.

Re:Built for number crunching

[enjar]

Exactly. We had it in the plans to acquire some V100 servers as part of an upgrade this year, as well as update some of our Dev/QE desktops to the very dearly priced GP100. Management had seen the numbers for that and were kind of holding their noses while saying "yes" because 1) they had real-live business reasons for us to do it and 2) those business reasons are considered a high priority but 3) the plan was expensive, no two ways about it. Now that this is an option, the numbers look considerably better. I wonder if nVidia wasn't getting a lot of traction on the V100 cards. Compared to the prices that P100, K40/80/20, C* and the original Tesla cards debuted at, the V100 seemed like quite the step-function, especially when you have the GTX equivalents that are doing fantastic single performance stuff at price scales set for the consumer market. Our management understands there's a "server markup", but when "markup" starts to sound more like "gouging", smart people figure out ways around the problem.

Re:But will the drivers work?

[bobbied]

Lots of drivers are crap these days...

Why? Which one of you can write C or C++ anymore?

I have a Linksys router that has crappy wireless drivers with memory leaks. Paid a pile of money for it. It locks up about twice a week and requires a full factory reset to fix it. Linksys got the wireless drivers from the chip maker (or so they say) as a blob so they claim to be at their mercy. Who over there at the WiFi chip manufacturer doesn't know how to track down and fix memory leaks? I can see the first revision of the driver sneaking out with bugs because you simply have to meet the delivery deadlines, but we are on the third release now and STILL the problem persists....

I'm beginning to think nobody does quality drivers anymore. Just reboot every few days to fix it.... Now get off my lawn and learn to code in a language that doesn't have garbage collection...