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NVIDIA Develops NVLink Switch: NVSwitch, 18 Ports For DGX-2
- jsheard 9y agoI'll just put the follow-up articles here rather than spamming tons of similar stories: More DGX-2 information - https://www.anandtech.com/show/12587/nvidias-dgx2-sixteen-v100-gpus-30-tb-of-nvme-only-400k https://www.anandtech.com/show/12587/nvidias-dgx2-sixteen-v1... Quadro GV100 announced - https://www.anandtech.com/show/12579/big-volta-comes-to-quadro-nvidia-announces-quadro-gv100 https://www.anandtech.com/show/12579/big-volta-comes-to-quad... Tesla V100 memory bumped to 32GB - https://www.anandtech.com/show/12576/nvidia-bumps-all-tesla-v100-models-to-32gb https://www.anandtech.com/show/12576/nvidia-bumps-all-tesla-...
- make3 9y agowhat are the differences between the Tesla V100 and the Quadro GV100? mostly just the display port? so is the GV100 more expensive then the V100? Have they published a price for the GV100?
- ihsw2 9y agoThere is no published price and the difference is the new Quadro supports Nvidia's OptiX ray-tracing API, as well as a very moderate performance boost over the Tesla V100 card. While it is eye-popping, you would be correct in saying this is pretty much just a relaunch under the Quadro brand.
- lsb 9y agoFive and a half years ago, one DGX-2 would be in the top 10 supercomputers in the world[1], and you'll probably be able to rent one on EC2 for under twenty bucks an hour before the year's out. You can already get the DGX-1 for under ten bucks an hour right now. [1] 1920 petaflops of 4x4+4 matrix multiply/add, and see https://www.top500.org/lists/2012/11/ https://www.top500.org/lists/2012/11/
- p1esk 9y agoNo it would not. You are comparing FP16 to FP64 performance.
- twtw 9y agoIt falls around 220th in the November 2012 list, and would make it onto the top 10 for the November 2007 list (comparing Rpeak) and the June 2008 list (comparing Rmax). Systems of comparable performance in the top 10 used between 300-500 kW (30-50x the DGX2). Red Storm, which has a listed Rpeak of 127 TFLOPs and placed sixth in the November 2007 TOP500, was "relatively inexpensive," costing only in the ballpark of $75M (~180x the price of the DGX2).
- throwaway84742 9y agoWithout reading the article first, let me guess, $200k?
- wlesieutre 9y ago$400k https://www.anandtech.com/show/12587/nvidias-dgx2-sixteen-v100-gpus-30-tb-of-nvme-only-400k https://www.anandtech.com/show/12587/nvidias-dgx2-sixteen-v1...
- throwaway84742 9y agoSheeeit. I’d love some of the stuff they’re smoking. You can build a 100 GPU rig for half as much. Just scatter it around the office so it’s not “in the data center”.
- steve_musk 9y ago100 Titan Vs = $300k. And the big deal about this system is the NvSwitch which allows the GPUs to appear to software as a single huge GPU.
- chrischen 9y agoSo you can run a single neural net model that can use > 12gb memory?
- dogma1138 9y agoYou can already do that with Pascal since it supports unified memory you have an address space of 49bits. Now it’s even faster since you won’t have to fetch pages from system memory or worse. But this isn’t new NVLINK supported memory unification of this sort since it’s introduciton but never in this scale. I’m pretty sure that if their numbers to be believed they have just made the worlds “fastest” single switched fabric.
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- nabla9 9y agoCan someone explain the technology edge Nvidia has? AMD, Intel etc. have not been able to compute in high-performance GPU market, so Nvidia must have an edge. How big and sustainable it is?
- dogma1138 9y agoThey understood really early on that you need to invest in software just as much as you would need to invest in hardware if not more. Open standards tend to be a horse designed by a committee, it can take years for them to evolve and to reach any consensus and they would never be able to match the speed in which hardware can evolve and adapt to market requirements. So NVIDIA essentially made their own software ecosystem which can be just as flexible as their hardware and more importantly it allows NVIDIA to be proactive rather than reactive.
- ethbro 9y agoThey also realized non-CS researchers don't have the time, expertise, budget, or interest in writing optimized ML libraries. And that if a graphics card company wrote easier to use / higher stack libaries, this would be a competitive advantage.
- deleted 9y ago[deleted]
- shmerl 9y agoThey don't really have an edge today. They just achieved big lock-in, and inertia of those who depend on CUDA now prevents them from using other hardware.
- ggg9990 9y agoWhat prevents other vendors from making CUDA compliant hardware? I thought the result of Oracle v. Google is that APIs can’t be copyrighted?
- 9y ago
- everyone 9y agoDoes anyone know when graphics cards will be available at sane prices for people who actually want to use them one (or two max) at a time to render graphics?
- Obi_Juan_Kenobi 9y agoIt's really hard to come up with a timeline, but I'd say the worst has passed. It will take time to recover inventory, but the alt-coin market (basically, not-Bitcoin cryptocurrencies) has died down a lot and the rush to acquire mining capital has likely diminished. 6 months to a year, maybe?
- TeMPOraL 9y agoLet's hope the deep learning craze doesn't pick up pace.
- redbeard0x0a 9y agoYeah, it should be getting better soon. Especially since ETH is now 1/3 what it was in Jan ($458.42 at the moment, $1350+ in Jan). As long as the prices don't rally again!
- nielsole 9y agoKeep an eye on the used graphics card market. If we see a burst / die down the market should be flooded with excess high end cards
- blacksmith_tb 9y agoI am not sure I would pay too much for card that had been run flat-out for months in a rusting hangar with standing water, though.
- crowbahr 9y agoRun flat out but undervolted because you get better electrical efficiency. I'd take that.
- jftuga 9y ago10,000 watts...wow!
- xvilka 9y agoToo bad this came from the one of the worst companies in the world, according to the policy towards open source. Too bad Google playing on their side by do not merging OpenCL support in TensorFlow.