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Hmm, 24%-42% performance increase (14/16TFlops vs 11.3TFlops) for 70-90% price increase... And prices were already inflated by crypto that is now collapsing. No
by bitL 8y ago
Hmm, 24%-42% performance increase (14/16TFlops vs 11.3TFlops) for 70-90% price increase... And prices were already inflated by crypto that is now collapsing. Not sure who is the target market for this tech honestly. Still only 11GB RAM, even if 50% faster, making it a nonsense purchase for Deep Learning enthusiasts (state-of-art models are already larger).
Unless somebody invented RTX-based coin of course, then this is the minimal price...
- kmkemp 8y agoWell, one audience is obvious from your own sentence: people who are willing to pay to have the best performance currently possible.
- bitL 8y ago2x Quadro RTX 8000 96GB ~$20000.
- dogma1138 8y agoTuring and Volta can do concurrent Integer and FP operations wich will give them a huge boost in traditional graphics as well. How much will be the real question here.
- AstralStorm 8y agoI'd expect total of around 15% on 2080 TI, mostly due to more shaders and improved scheduler.
- aqme28 8y agoWhere are you getting a 70-90% price increase? 1080s are ~$450, will now be $799. 1070s are ~$400, will now be $599. (I'm going off the top hits on Newegg)
- kup0 8y agoThese are also Founders Edition prices. Still the 2080ti is pretty expensive even at non-FE pricing: RTX 2070 cards will start at $499, with RTX 2080 at $699, and the RTX 2080 Ti starting at $999.
- carbocation 8y agoFor the 1080, by your numbers, $799/$450 represents a ~78% price increase.
- Retric 8y agoFirst those are founders edition pricing which cost an extra 100$. https://news.ycombinator.com/item?id=17802871 https://news.ycombinator.com/item?id=17802871 Also 1080's did not start at 450$ each. The 2080's price will drop eventually, until then nVidia has no reason to lower prices when they are going to be sold out for weeks if not months.
- aqme28 8y agoAlright fair. 50-80%, not 70-90%.
- andoriyu 8y agoDid you forget that 1080 was 699 at launch? I remember because that's how much I paid for it.
- Art9681 8y agoThe price of 1080's where $600-$650 for the founders edition cards when they first came out. I know cause I preordered at those prices. I think the price of the 2080 FE cards are fair given that they are not only faster at raster graphics, but they also have the Raytracing/AI capabilities.
- deleted 8y ago[deleted]
- wlesieutre 8y agoThose are the "Founder's Edition" prices for the first cards from Nvidia, so it's not quite this bad either. MSRP on cards from OEMs should start at $499 for the 2070 and $699 for the 2080 ($100 cheaper than Nvidia's). Personally I still think it's insane. I have a GTX 970 from October 2014 and that was $369. EDIT: Even my $369 was a bit of a premium (OC edition and shortly after launch, I don't remember but I'm guessing I bought whatever was in stock). Wikipedia claims the GTX 970 launched in September 2014 at $329. Assuming the $329 MSRP is comparable to the $499 announcement, the __70 line is up 52% in two generations. I'm sure it's better hardware, but that's a big pile of money. And if my 970 experience holds through today, the OEM cards that are actually available are going to be pricier than the MSRP, but maybe still lower than the Founder's Edition. We'll see where the 2060 ends up.
- jasonlotito 8y agoFor those confused, these are about what the 10 series Founder's Editions were priced at originally. When the 10 series was released, the 9XX series was around the same price as the 10 series is now compared to 20. The price isn't going up by 70-90%. It's that the previous series (10) is going down. Does that mean the 10 series isn't worth it? By all means, no. The 9 series was still an excellent series when 10 was released, and people did pick the up.
- bitL 8y agoWhich 10x0 FE did cost $1200? Did I miss something?
- jasonlotito 8y ago1080 FE $699 USD 2080 FE $799 USD That qualifies as about the same price in my book, and not a 70-90% jump. As for the Ti price when 1080 series was released, there was none.
- deleted 8y ago[deleted]
- aseipp 8y agoEhhhh, not really, but the release seems a bit different this time around. The 1080 Founders Edition and 1080 Ti FE cards both debuted at $700 USD. (The 1080 Ti was released nearly a year later.) This puts it closer to the now released 2080 FE, which is $800 USD. The 2080 Ti FE, however, is in a league closer to the Titan X/Xp, which were at $1,200. Also they're releasing the highest-end Ti edition at the same time as the ordinary version, which is a first for Nvidia, I think? (The Titan Xp was also launched after, not concurrently, with the 10xx series...) I think the concurrent launch of the 2080 Ti with the ordinary variant means they're positioning it more like an alternative to the Xp, while the non-Ti variants are closer to the ordinary gaming cards you'd normally get. In other words, for people willing to blow their price/perf budget a bit more. For DL workloads the 1080 Ti is very cost effective (vs the Xp), so it remains to be seen which variant will have the better bang/buck ratio for those uses. I suspect the fact these include Tensor Cores at their given price point will probably be a major selling point regardless of the exact model choice, especially among hobbyist DL users. The RTX line will almost certainly be better in terms of price/perf for local DL work, no matter the bloated margins vs older series. They may also be keeping prices a bit inflated, besides margins, so they can keep selling older stock and pushing it out. The 9xx series, as you said, continued to sell for a while after 10xx was released. I expect the same will be true this time around, too, especially with prices being so high.
- hooloovoo_zoo 8y agoI think it will still be popular for DL. The models themselves will fit and batches can be distributed over multiple cards during training.
- pmichalina 8y agoCollapsing? Nocoiners lol
- kevindqc 8y agoWow you have really compelling arguments as to why crypto isn't collapsing! Thanks you for you insight
- mavdi 8y agoLet's see your argument for it collapsing. It's been very volatile sure, but you'd still get insane gains if you invested just last year. BTC has gone up 45% in the past year. 1015% in 2 years. source: https://cryptowat.ch/ https://cryptowat.ch/ Collapsing.
- dang 8y agoPlease don't reply to a bad comment with another bad one. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- pmichalina 8y agoI suppose it’s collapsing up since 2009?
- sabalaba 8y agoIt's far from a nonsense purchase for Deep Learning professionals. At https://lambdalabs.com https://lambdalabs.com nearly every one of our customers is calling us up interested in the 2080Ti for Deep Learning. The reality is that very few people training neural networks need more than 11GB.
- bitL 8y agoThen most likely they would not be successful in their businesses; training older models or newer ones with a batch of 1 is not a recipe for success these days when you more like need 100s of GPUs running slight modifications to models in parallel to find the one that works.
- sgt101 8y agoWe used to call this model fishing and regard models that came from places that did it with fear and suspicion (due to sudden failure and poor performance in production) What has changed that people think this is a wise approach?
- bitL 8y agoAutoML and automated architecture/hyperparameter search used by FAANG, producing things like AmoebaNet-D, that beat all previous state-of-art results.
- matt4077 8y agoThey don't suddenly fail any more, and performance in production is fine... This is a rather empirical science right now. If forced to speculate, I'd say far larger datasets are part of the answer. If you can afford to hold back 30%+ of your data for (multi-tranche) verification the difference between testing and production becomes a problem for the philosophers.
- sgt101 8y agoHmm this isn't my experience. My experience is that highly complex models tend to reflect accurately the ground truth in the current dataset, but not the domain theory that generated it, so when things change (like, prevailing weather conditions, political alignments, interest rates, data usage) which move the distribution (but not the domain theory) they do fail. The question is : are you trading poorer compression for more fidelity or are you learning the system that generates the data?
- garmaine 8y agoNVIDIA isn’t used for any crypto currency mining AFAIK. It’s integer math performance per watt is not in the same ballpark as AMD.
- bitL 8y ago1070 was very popular for ETH last year, even beating some AMD cards in performance/watt.
- ArlenBales 8y ago> Not sure who is the target market for this tech honestly. The RTX series succeeds the GTX series, which historically targeted computer gamers.
- agumonkey 8y agointroducing fiatlux
- wlesieutre 8y agoIt's not as clever, but RayCoin would market better. Fiat Lux could be its tagline? I hope I'm joking.
- AboutTheWhisles 8y agoNo crypto currency that I know of has succeeded based on the utility of their proof of work algorithm producing something useful. Only proof of work algorithms in service of the currency itself have made an impact.
- wlesieutre 8y agoI'm thinking more that a blockchain enthusiast will design a new coin that abuses the raytracing hardware into running some new crypto-token just because. This series tentatively looks like it won't be subject to the insane price hikes and scarcity of the 10 series because it's already expensive for adding more diverse hardware that doesn't immediately help you mine ethereum (or whatever's the GPU coin of choice these days). But you never know... It doesn't need to _do_ anything as long as you can convince people that they should buy RayCoins because everyone else is going to buy RayCoins and they'd better get in on the ground floor here.
- antpol 8y agoIf any glimpse of success of that venture happens, soon to follow * RaCoin * BeamCoin * BeaconCoin * <insert ray synonym here>Coin
- solomatov 8y agoYou can always decrease a batch size to fit in smaller RAM.
- bitL 8y agoUnless you are already on a batch size 1 and TensorFlow greets you with a nice OOM message... Try some Wide-ResNet for state-of-art classification and play with its widening parameter.
- p1esk 8y agoUse gradient checkpointing.
- rspeer 8y ago...if the batch is the thing that doesn't fit in RAM, as opposed to the model.
- jdietrich 8y ago>Not sure who is the target market for this tech honestly. These are gaming GPUs being announced at a games conference to an audience of gamers and games journalists. The focus of Huang's talk was how accelerated ray tracing will improve the graphical fidelity of games. GPU compute is a spin-off from gaming. Gamers remain the primary market. They generate the volume that allows Nvidia to sell a supercomputer on a card for under $1000. If you want a professional product, Nvidia are more than happy to sell you a Tesla or a Quadro at a professional price point.
- bitL 8y agoThe point was different - it is way too expensive for regular gamers, 2080Ti likely won't be able to do 4k@60Hz like 1080Ti couldn't either and 10 games featuring RTX in the nearly future is not a sufficient draw, especially when some of the effects now look subjectively worse with RTX ON (see those shadows from multiple lights above dancing people from Jenson's demo). So the question remains - who is the real target audience that will actually buy those cards at these prices? Did NVidia turn into Apple and made RTX its own iPhone X? Waiting this generation out until RTX is more wide-spread/tested and going for the next 7nm generation with hopefully AMD having a proper GPU to compete seems like a better strategy for most gamers out there.
- xxs 8y agoNot only that later in the same demo you can notice the fps drop during the explosion sequence.
- jdietrich 8y ago>it is way too expensive for regular gamers The 80 series has always been a low-volume, high-margin halo product within Nvidia's gaming range. It's dirt cheap and high-volume compared to Quadro, but top-of-the-range for gaming. Cryptomania has revealed to Nvidia that they probably priced the 1080 too low at launch - many gamers were in fact willing to pay substantially inflated prices for The Best GPU. If the mass market decides to wait for the RTX 1060 or 1050, that's fine with Nvidia, as they face no real competition from AMD at the moment. It's very much in Nvidia's interests to make the most of their market dominance.
- blihp 8y agoFor video professionals doing ray tracing this upgrade would likely be a must-have. This assumes the improvement (i.e. 6x or anything in that ballpark) is real and their software supports it... if so, hell, nVidia could double or triple the price of the card and it would still make sense for them. nVidia is just cashing in on a lack of any real competition at the high-end currently... hopefully we'll see AMD get back in the game at some point re: GPUs.
- dragontamer 8y agoIsn't this just an implementation of Microsoft's DirectX Raytracing API? If so, only video games are really going to use that API. I doubt that a software renderer (or CUDA-renderer) would leave raytracing / light calculations to a 3rd party. There's a rumor that Dinsey bought a bunch of real-time raytracing equipment for their theme parks (the Star Wars section in Disney World). So high-quality realtime computation is needed for high-tech entertainment / theme parks / etc. etc. So there's definitely a market, even if gamers don't buy in.
- bufferoverflow 8y agoYou're wrong. Pretty much every major raytracing company is excited about this development. Blender is the only major one that I heard nothing from.
- dragontamer 8y agoI mean, it'd be exciting if true. Do you have a link of one of these raytracing companies explaining how they plan to use NVidia's RTX cards for this sort of thing? As far as I'm aware, the only API to access these RTX raytracing cores is through the DirectX12 Raytracing API. I did a quick check on Khronos, but it doesn't seem like they have anything ready for OpenGL or Vulkan. Alternatively, maybe NVidia is opening up a new Raytracing API to access the hardware. But I didn't see any information on that either. EDIT: It seems like NVidia does have a specialized Raytracing API that various industry partners have announced support of: https://blogs.nvidia.com/blog/2018/08/13/turing-industry-support/#source=pr https://blogs.nvidia.com/blog/2018/08/13/turing-industry-sup...
- h4b4n3r0 8y agoWhether it's substantially better for deep learning depends on whether they chose to neuter fp16 like they did in all other consumer GPUs. The main bottleneck is not actually the size of the model per se (sizes of the models have been mostly going _down_ as of late), it's the size of the batch during training. Both batch size and model size determine the size of the main memory hog: activations that you need to keep to do training. You don't need to keep activations to do inference: you can discard them after they're fed into the next layer. So it's not entirely accurate to say that this is useless for DL. What could make it totally kickass for AI would be a proper, non-neutered implementation of fp16, similar to what you'd find in P100, V100 and (surprisingly) Jetson TX2, which would effectively double the possible batch size, which in turn leads to quicker convergence. It could also halve the model size as an added bonus. This is NVIDIA, however, so I would bet good money fp16 is still neutered in "consumer" SKUs.
- bitL 8y agoOf course, for inferencing assuming >100 TFlops on float 16 and >400 TOPS in INT4 as demoed by Jenson would be awesome for already trained/pruned models. Though for training I am not so sure, even V100 have rough edges in doing that with TensorFlow. And for model size - I guess it all depends on area in which are you are focusing; I run out of memory all the time these days even with batches of size 1 :(
- saltcured 8y agoIf it's data size in GPU RAM you are concerned about, couldn't you store fp16 and cast into fp32 just in the kernel? In OpenCL, you would do this with vload_halfN and vstore_halfN to convert during load and store. You won't get double throughput compared to fp32, but you shouldn't fall back to some terribly slow path either.
- h4b4n3r0 8y agoI haven't looked into it myself, but it could be that due to all this massaging you'd lose more on throughput than you gain on memory use. It's similar to doing 8 bit quantized stuff on general purpose CPUs. It's very hard to make it any faster than float32 due to all the futzing that has to be done before and after the (rather small) computation. In comparison, no futzing at all is needed for float32: load 4/8/16 things at a time (depending on the ISA), do your stuff, store 4/8/16 things at a time. Simple.
- nwsm 8y ago>70-90% price increase... And prices were already inflated by crypto If you are going off the inflated prices, this is hardly a price increase at all. 70% is the increase from 1080 Ti release price, not from the inflated crypto prices.
- bitL 8y agoI meant that the release price was subsequently inflated by crypto which in the meantime cooled down significantly; if crypto were still hot, then inflated 20x0 prices would be expected; this seems more like an opportunistic move, "residual crypto-wave surfing", and resembles strategy NVidia was doing in pro segment for a while due to no competition.
- cma 8y ago1080ti launched in March 2017 before the big 2017 boom.
- VikingCoder 8y agoThe "target audience" is the hype train. If you believe Nvidia has a better long term future, that's good for Nvidia. Stuff like this trickles down to the main stream eventually.
- throwaway5752 8y agohttps://en.wikipedia.org/wiki/ASCI_Red#First_to_TFLOPS https://en.wikipedia.org/wiki/ASCI_Red#First_to_TFLOPS for those feeling sentimental.
- beerlord 8y agoFor the money they're charging, they could have at least thrown us a bone by including HDMI 2.1 VRR, or ideally even adaptive sync. Nvidia users still have to pay an Nvidia-tax to access expensive G-sync monitors, which are far fewer in availability and selection than Freesync (which also works with Xbox).
- Phlarp 8y agoDon't give people ideas like this. It only leads to misery for everyone.
- golergka 8y agoTFlops is correllated with perfomance, but this corellation is not that perfect that you can just use TFlops as a stand-in for perfomance. Perfomance is complex. I'd wait for benchmarks.
- ajsalminen 8y agoWhere are you getting these TFLOPS numbers? I haven't seen them in anything other than rumors that got a lot of things wrong so I wouldn't be too certain about them.