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Radeon Instinct – Optimized Machine and Deep Learning
- zitterbewegung 10y agoDoes anyone use AMD for deep learning in scientific / industry ? All the libraries for deep learning I have seen require CUDA and NVIDIA is winning by merely being the most popular API. Searching github it looks like they are university assignment projects see https://github.com/search?utf8=%E2%9C%93&q=opencl+deep+learning&type=Repositories&ref=searchresults https://github.com/search?utf8=%E2%9C%93&q=opencl+deep+learn...
- mabbo 10y agoIf AMD can release solid hardware, all they would need to do is add support for their hardware to popular open-source projects like TensorFlow. I just hope they do the second part correctly.
- AlphaSite 10y agoIt looks like they're doing it, or already have done so. https://github.com/GPUOpen-ProfessionalCompute-Tools/HIP/issues/45 https://github.com/GPUOpen-ProfessionalCompute-Tools/HIP/iss...
- RockyMcNuts 10y agoTensorFlow is evolving rapidly and it's a challenge to keep up with GPU driver updates, CUDA updates, TensorFlow updates, and not fall into version hell. For instance I took the Udemy course a few months back, given by a Google scientist, and in at least one instance the code was pinned to CPU because it didn't run on GPU, presumably due to a TensorFlow issue. If they can get TensorFlow running well on AMD and release images that make it painless, it will be a huge win, but I'm a little skeptical. Big difference between getting a benchmark win and a stable platform.
- devy 10y agoFYI, AMD's people are helping TF to add OpenCL support. https://github.com/tensorflow/tensorflow/issues/22 https://github.com/tensorflow/tensorflow/issues/22
- dharma1 10y agoContributions from AMD are sorely lacking. It's mostly people from https://www.codeplay.com/ https://www.codeplay.com/ and https://github.com/hughperkins/ https://github.com/hughperkins/
- devy 10y agoI noticed Hugh Perkins has a AMD badge under "Organizations". Is he not working for AMD? Also one of the earlier participants of the TF OpenCL support conversations https://github.com/gujunli https://github.com/gujunli was working for AMD at the time[1]. https://electrek.co/2016/02/26/tesla-machine-learning-expert-autopilot/ https://electrek.co/2016/02/26/tesla-machine-learning-expert...
- dharma1 10y agoNo, Hugh works at asapp.com. AMD could really invest more in optimising deep learning libraries for their hardware if they want to be relevant
- devy 10y agoInteresting! He's definitely got some interesting background there. Normally someone wouldn't be added into a Github organization without an employment relationship there. > AMD could really invest more in optimising deep learning libraries for their hardware if they want to be relevant I am optimistic about AMD's involvement in AI. Just do a search of recent news on here, tons of exciting devleopment from AMD, especially Radeon Instinct. And here is an interesting comment about the comparison between Nvidia and AMD[1]. [1] https://news.ycombinator.com/item?id=13161050 https://news.ycombinator.com/item?id=13161050
- peller 10y agoFor what it's worth, AMD has been working on a CUDA compatibility solution for at least a year now. Announcement[0] and Progress[1] [0] http://www.anandtech.com/show/9792/amd-sc15-boltzmann-initiative-announced-c-and-cuda-compilers-for-amd-gpus http://www.anandtech.com/show/9792/amd-sc15-boltzmann-initia... [1] http://www.anandtech.com/show/10831/amd-sc16-rocm-13-released-boltzmann-realized http://www.anandtech.com/show/10831/amd-sc16-rocm-13-release...
- dogma1138 10y agoIt only works for the basic functionality they can't interop the "operational" CUDA features.
- slizard 10y ago> can't interop the "operational" CUDA features What exactly do you that mean?
- dogma1138 10y agoDMA, networking, storage and direct i/o, virtualization etc.
- slizard 10y agoThe tricky, but fun parts. It's certainly not trivial to port those, but I'm not too worried about it as long as there is solid runtime support in ROCm. More fun work for perf engineers like me. ;) Massive amount of boilerplate, heavy APIs or crappy software stack are more dangerous IMO than having to drop in replacements for NVIDIA-specific optimizations of GPU-to-NIC or GPU-to-GPU communication.
- dogma1138 10y agoNot only not trivial to port those but they are constantly will have to play catch up and be at the mercy of NVIDIA in regards to spec. AMD is in a catch 22, support CUDA and be effectively in a constant catch up position, not support it and continue to be ignored by the market at large simply because the momentum NVIDIA has managed to achieve with CUDA over the years.
- madenine 10y agoSome people do, but they're by far the minority. CUDA / cuDNN are well tuned and integrated with the most popular libraries. At this point, in order to get people to switch not only would your hardware have to be faster, but your replacement for cuDNN would have to be better as well. Which is by no means impossible, just difficult.
- x0x0 10y agoI disagree; most people use caffe / keras / theano / tensorflow / etc hiding the cuDNN details so end users won't care much. Offering more performance / shorter training loops is a big deal. Your typical ML learning loop with an expensive human regularly waiting for experiment results shows clear benefits.
- ogrisel 10y agoThe point is that there is no optimized cuDNN equivalent for AMD hardware at this point.
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- eightysixfour 10y agoAMD has built this middleware for all of those applications (keras, tensorflow, caffe, etc) and they show the performance results in their slides.
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- eightysixfour 10y agoLooks like AMD is building replacement middleware for most of the major ML stacks, some more information on this page: http://www.anandtech.com/show/10905/amd-announces-radeon-instinct-deep-learning-2017/3 http://www.anandtech.com/show/10905/amd-announces-radeon-ins...
- dr_zoidberg 10y agoI remember that a few years ago AMD had the only sensible solution for virtualizing GPUs, and you could make a bunch of them work together as a single unit without much trouble. But I didn't have a Radeon card so I never got to try it. Don't know what happened with that, it's true that they really lagged behind NVIDIA.
- viewtransform 10y agoAMD has a new virtualization solution which provides SR-IOV hardware based partitioning on their AMD FirePro S7150 or S7150 x2 gpu cards. http://www.amd.com/en-us/solutions/professional/virtualization http://www.amd.com/en-us/solutions/professional/virtualizati... This video explains what you get https://www.youtube.com/watch?v=tKBthlKTtvQ https://www.youtube.com/watch?v=tKBthlKTtvQ
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- deepnotderp 10y agoThey desperately need a cudnn competitor.
- hedgehog 10y agoYes, we use and like the R9 Nano. We wrote our own tools that are portable across GPUs so third party software support (eg cuDNN) is not a factor for us.
- raj_m 10y agoI really don't think this will make a dent in CUDA's platform. CUDA has a well established ecosystem in deep learning and compatible cards like Quadro coupled with very matured platform makes it miles ahead of platform. That said, I would love to be proven wrong. Healthy competition such as this fosters much better results. Also CUDA is not without issues in certain matters.
- mrlatinos 10y agoJust speaking from a personal perspective, I took a parallel computing course at my uni this past semester and CUDA was the main platform we worked on (and I'm an undergraduate). Nvidia also has a great Udacity course they offer for free. Unless AMD gets CUDA compatibility working soon, I really don't see how they're going to catch up as far as adoption goes.
- visarga 10y agoThey either get CUDA or compatibility with all major frameworks. And they'd better be cheaper or faster than NVIDIA.
- slizard 10y agoThe ML/deep learning technologies are peaking or will peak in the coming years on the hype curve [1], so it is not too late for AMD to join the show, there is plenty of newcomers and growing entities to buy hardware. So even though the CUDA ecosystem is far more established, let's not forget how much room for growth there is under an exponential growth curve! Even Intel is late to the game (and so far can't even compete with AMD in terms of hardware). [1] https://www.gartner.com/newsroom/id/3412017 https://www.gartner.com/newsroom/id/3412017
- slizard 10y agoWhat's particularly interesting here is that the Fiji card they propose is a very different beast than any of the NVIDIA offerings. The MI8 card's HBM has a great power and performance advantage (512 GB/s peak bandwidth) even if it's on 28 nm. NVIDIA has nothing that has even remotely comparable bandwidth in this price/perf/TDP regime. None of the NVIDIA GP10[24] Teslas have GDDR5X -- not to surprising given that it was rushed to marked, riddled with issues, and barely faster than GDDR5. Hence, the P4 has only 192 Gb/s peak BW; while the P40 does have 346 GB/s peak, it is far higher TDP, different form factor and not intended for cramming in into custom servers. [I don't work in the field, but] To the best of my knowledge inference is often memory bound (AFAIK GEMV-intensive so low flops/byte), so the Fiji card should be pretty good at inference. In such use-cases GP102 can't compete in bandwidth. So the MI8 with 1.5 the Flop rate, 2.5x bandwidth and likely ~2x higher TDP (possibly configurable like the P4) offers an interesting architectural balance which might very well be quite appealing for certain memory-bound use-cases -- unless of course the same cases are also need large memory. Update: should have looked closer at the benchmarks in the announcement; in particular the MIOpen benchmarks [1] MI8 clearly beating even TitanX-Pascal which has higher BW than the P40 indicates that this card will be pretty good for latency-sensitive inference as long as stuff fits in 4 GB. [1] http://images.anandtech.com/doci/10905/AMD%20Radeon%20Instinct_Final%20for%20Distribution-page-021.jpg http://images.anandtech.com/doci/10905/AMD%20Radeon%20Instin...
- rjtobin 10y agoThe PCIE NVIDIA P100 has peak memory bandwidth of 730GB/s, at 250 Watts, which is almost exactly the same bw/watt as the MI8 (well, there are two PCIE P100s, I mean the better one).
- theandrewbailey 10y agoSo it's a headless passively cooled server version of the R9 Fury X? I figured this was a faster and improved version. Or is this Polaris based? http://www.anandtech.com/show/9390/the-amd-radeon-r9-fury-x-review http://www.anandtech.com/show/9390/the-amd-radeon-r9-fury-x-... Not sure if AMD is going to go all HBM on all it's high performance GPUs in 2017, or only offer one or two models with it. http://arstechnica.com/gadgets/2016/03/amd-gpu-vega-navi-revealed/ http://arstechnica.com/gadgets/2016/03/amd-gpu-vega-navi-rev... EDIT: MI6 is Polaris based, MI8 is Fiji with HBM, MI25 is Vega. https://www.amd.com/en-us/press-releases/Pages/radeon-instinct-2016dec12.aspx https://www.amd.com/en-us/press-releases/Pages/radeon-instin...
- rsp1984 10y agoInteresting that NVDA is down almost 4% for the day [1] while AMD is up 3% [2]. Is Wall Street realizing that NVidia is not alone in the ML Hardware space? [1] https://www.google.com/finance?q=NASDAQ:NVDA https://www.google.com/finance?q=NASDAQ:NVDA [2] https://www.google.com/finance?q=NASDAQ%3AAMD https://www.google.com/finance?q=NASDAQ%3AAMD
- Twirrim 10y agoIt's way too early to be making guesses like that. Micro-trends are mostly meaningless with stocks, unless you're trying to do high frequency work. Stock shifts and changes to small extents all the time based on the quirks of all sorts of trading companies, and each of Especially if there hasn't been any significant news about the company, and this isn't significant news. It's interesting, but it isn't really threatening Nvidia's dominance or profits at the moment. AMD needs to make a bigger name for itself in the sector, start picking up some splashy customers before most of the market might react. Looking at the bigger picture, Nvidia stock is up 160% so far this year, but has been fluctuating a bunch over the last month or so, and it's still well within the scope of those fluctuations.
- kyledrake 10y agoOne thing that would be interesting is if you could use cards like this for rendering multiple instances of X, for the purpose of running things like WebGL browser screenshotters. I had to ship out a high-end gamer GPU with a dummy HDMI adapter for this purpose recently. But it's obviously not very efficient. It would also be nice to be able to run multiple screens in parallel, not just one per GPU. I doubt there will ever be a product for my use case, but one can dream... That said, these are cool. I think they're lower power than the Nvidia equivalent, but I could be mistaken (I just recall the Tesla models being power hungry.. enough to cause a real problem in a datacenter rack).
- ipunchghosts 10y agoThis really doesnt matter for deep learning. There is a large ecosystem built around CUDA. Unless AMD becomes CUDA compatible (they are working on it but not there yet) and I can install Torch/TF and run it on my AMD GPU, I will stick with NVIDIA. I am all for choice, but AMD has a lot of catching up to do.
- LeanderK 10y agoAhh, what exciting times we live in. Just look at the example applications: - autonomous vehicles - autopilot drone - personal assistant - personal robots - ... i know it's optimistic, but it's not science-fiction.
- akerro 10y ago- running out of natural resources - child slavery to build new iPhones in Africa and China - killing and burning wildlife to build new farms in Latin America - still not having any solution for problem of drinkable water in 2/3 of World What a time to be alive!
- grzm 10y agoYes, the world is not perfect by any stretch of the imagination. Lots of things to be improved. If you could choose another time to live in, when would it be?
- akerro 10y agoWow, that's a great question. I can't decide if it would be in 20 years or 40 years ago. Just to be part or witness of creating Internet as we know it or as we will see it! When some of the above problems don't exist any more because of technological advancement and some worsen because of the very same reason, but we no longer see them, because no one is looking at the wild parts of the world.
- LeanderK 10y agowell, i was very active for greenpeace/other environmental organisations/the green party youth in germany. I know of these issues and it's getting better, but it's still awfully slow and frustrating. If you want some improvements way fewer are starving[0], food security improved for millions. I know there is no rational reason for children to starve, humanity produces enough food, but frankly we (as in first world) don't care. We really don't care. Most just donate something on the end of the month and think they are no part of the solution. But try explaining to people that they should scale back their consumption. They do stuff as long as there is not the slightest inconvenience. I really think that in a weird way technology can help (not solve) overcome, or better compensate for our human stupidity in some of these issues. Not alone, of course. But right now i don't see a path for me that's more effective in tackling these problems at the same rate as improving technology. (if you want to see it more pragmatic: NGO's really need some better tools, especially for campaigning and training (this may be the most important, most are volunteers). It is often very unprofessionlized and inefficient. It's really holding some of them back.) Maybe there will be a time when i see more potential impact for my personal political ambitions, but right now i don't see how this is going to work better than studying computer science. Also, it's been worse for humanity ;) We dropped like flies in the end of the 19. century due to diseases. [0] https://www.wfp.org/news/news-release/world-hunger-falls-under-800-million-eradication-next-goal-0 https://www.wfp.org/news/news-release/world-hunger-falls-und...
- stuckagain 10y agoI can't even look at the press picture without remembering that is the exact same metal card slot tab that I had on my IBM PC 35 years ago. They should take a picture of the other end or something.
- anoother 10y agoI wish modern chassis, and indeed, consumer cards, would come with these support brackets.
- echelon 10y agoWhat's a good GPU / setup for someone doing deep learning at home? Does anyone have recommendations?
- dylanbfox 10y agoI've been curious about this too. AWS does have K80 instances available for $0.90/hour which isn't too bad for playing around and as long as they keep updating their infrastructure, you can play with the newest stuff versus having to upgrade your own all the time.
- echelon 10y agoThat doesn't sound that bad. I might investigate AWS until putting an investment into my own dedicated hardware. I'm just starting off, so my primary concern is speed of iteration and learning. I want to train on and generate audio phonemes, so this will undoubtably take a lot of practice.
- Florin_Andrei 10y agoIf you also play video games, then just get one of the new Nvidia Pascal chips and install it in your home PC. Dual-boot Windows / Linux. Which card to get? Bigger is better but it also depends on your wallet.
- smaddali 10y agoNvidia 1080 is a good one. Take a look at this write up. http://timdettmers.com/2014/08/14/which-gpu-for-deep-learning/ http://timdettmers.com/2014/08/14/which-gpu-for-deep-learnin... its updated in July 2016 with info about the later versions.
- option 10y agoHere is a good PC build, also some software info: http://deeplearningathome.com/2016/09/Building-PC-For-Deep-Learning-Hardware.html http://deeplearningathome.com/2016/09/Building-PC-For-Deep-L...
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- cordite 10y agoOther than ML applications, what can I write on this? OpenCL? Something comparable to CUDA? What about utilizing Vulkan?
- ilaksh 10y agoBut Keras and Tensorflow still only work on nVidia right?
- mastazi 10y agoAMD is supporting development efforts to port Caffe, Tensorflow and Torch http://www.anandtech.com/show/10905/amd-announces-radeon-instinct-deep-learning-2017/3 http://www.anandtech.com/show/10905/amd-announces-radeon-ins...
- milesf 10y agoAm I the only one that saw this and immediately thought "mining cryptocurrency"? :)
- nickeleres 10y agoloving on the UI, very reflective of their product
- visionscaper 10y agoThere seems to be considerable effort being undertaken to allow TensorFlow to work with OpenCL [0]. Also see [1]. This coincides nicely with the introduction of these AMD cards. I'm looking forward to the day that Nvidia gets some competition in the GPUs-for-deeplearning market. Further, doing some smaller Deep learning experiments on my MacBook Pro with AMD discrete GPU is another benefit I'm looking forward to ;) [0] https://github.com/tensorflow/tensorflow/issues/22 https://github.com/tensorflow/tensorflow/issues/22 [1] https://github.com/benoitsteiner/tensorflow-opencl https://github.com/benoitsteiner/tensorflow-opencl
- rwmj 10y agoAre the drivers for this open source? That would be a major improvement over NVidia.
- jheriko 10y agothis website is terrible. it tries to sell me the product, but neglects to mention what it does.