8 ms·
Yes, Nvidia dominates in deep learning and AI, but the risk of disruption by Intel is much greater than a lot of non-technical people realize. Intel has to do
by cs702 10y ago
Yes, Nvidia dominates in deep learning and AI, but the risk of disruption by Intel is much greater than a lot of non-technical people realize. Intel has to do only two things to start taking market share away from Nvidia in DL/AI quickly:
1. Add "good enough" functionality to its high-end processors. Intel is already working on that: https://news.ycombinator.com/item?id=12709220 https://news.ycombinator.com/item?id=12709220
2. Contribute open-source code to the main branches of the most popular DL/AI frameworks (Tensorflow, Theano, Torch) so these frameworks support the new chip functionality "out of the box," without requiring any additional tweaking. This is not yet happening, but I'm hoping it will soon.
Many DL/AI developers would be content with "good enough" performance out-of-the-box from CPUs if it means not having to pay extra for Nvidia cards or deal with Nvidia's proprietary drivers.
It would be great for Nvidia to get real competition in this space.
- sonabinu 10y agoTrue but Nvidia has a first mover advantage which should not be discounted.
- arcanus 10y ago> It would be great for Nvidia to get real competition in this space. It seems obvious AMD will be a player, since they have similar hardware (GPUs) and with a proper port (using HCC, openCL, etc. ) for cuDNN should also have excellent performance for Tensorflow, Theano, etc. 'out of the box'.
- AlphaSite 10y agoTheir mixed GPU/CPU modules should be very interesting as well.
- frozenport 10y agoNo, they have inferior performance, and all the same issues as Nvidia- in addition to requiring a port.
- dharma1 10y agoinferior performance because of lack of performant DL libraries, like CuDNN, not because of the hardware itself
- dogma1138 10y agoIt's a mix of both, hardware is inferior for current use cases but current use cases are driven heavily by NVIDIA. NVIDIA knows how to do 2 things right; understanding that software matters, even more than hardware and deliver on that notion; and how manage developer relations. While AMD makes it easy to access information without NDA and sign ups NVIDIA blows it it if the water the moment you show even the slightest interest at signing up with them. NVIDIA at this point can probably spin off a pure consulting division for AI/ML and bring in more revenue than AMD in its entirety.
- arcanus 10y agoI liked some of this point except the end, which is not correct. > NVIDIA at this point can probably spin off a pure consulting division for AI/ML and bring in more revenue than AMD in its entirety AMD had $3.99 Billion in total revenue in 2015. Nvidia had 5 Billion. Perhaps you mean profit? Amd was operating at a loss and nvidia was very profitable.
- dogma1138 10y agoNVIDIA doesn't charge you for consulting services, they do expect you to buy pretty expensive hardware tho. They offer training and consulting services for "free" and paid services through their network of partners, to which NVIDIA provides services for free. If they spin off their in house knowledge and start charging for services and software instead of giving it out for "free", they might very well reach a 4bln $ a year revenue stream, that said a lot of people won't be happy about it...
- dharma1 10y agoHow is the hardware inferior for current use cases? The compute capabilities are pretty much the same for the latest NVidia/AMD cards in the same price range. It's a software thing - lack of optimised DL ops, particularly fast convolution kernels that is hurting the perf of AMD in deep learning
- rasz_pl 10y agoNo, AMD doesnt do software suppport. In words of their own developer: >>We don't happen to have the resources to pay someone else to do that for us.
- spangry 10y agoYeah, that whole ongoing saga is very unfortunate. Also very illustrative. Reading between the lines, my take is that AMD senior management are a bunch of generic MBA types optimising for higher profit in the present (Windows gaming market) by stealing from the future (HPC & server segments + growing niches like ML ---> Linux and open standards, in other words). It makes zero sense for them to place increasingly large bets on proprietary drivers when they're clearly not the market incumbent.
- touristtam 10y agoIt sounds what was happening when AMD, ATi were still seperate entities.
- jackyinger 10y agoAlong these lines... For inference, do you really want to put a Tesla M4 in every server in your cloud when you're already paying $$$$ for CPUs?
- mastazi 10y agoDo you really want to put a Xeon Phi in every server in your cloud when you're already paying $$$$ for CPUs?
- boulos 10y agoI'll point out that this same argument applied to discrete GPUs when Intel tried to enter the market with Larrabee (before giving up and claiming that HPC was where it's at anyway). "This time is different" might apply here though, because training is "just" a lot of low precision matrix math. This requires a lot less new ecosystem / software for Intel (Intel has a long history in matrix math), so much like SSE, AVX, and now AVX-512 (or as I still call it LRBni) Intel can easily make some tweaks to at least get 70% of the gains.
- deleted 10y ago[deleted]
- sgift 10y agoAlso: Intel learned many things with Larabee. Larabee may have been a failure in public perception, but for Intel it seems to have been a fruitful experience which still helps them. (Somewhere, I've read that they've won the contract for one of the next super computers based on their Knights Landing architecture)
- modeless 10y agoThere is zero chance that Intel can add "good enough" functionality to their CPUs without changing their memory architecture. A high end i7 might have 35 GB/s of memory bandwidth. Even the biggest, most ridiculously expensive ($6000) Xeons have only about 100 GB/s. Nvidia's GTX 1080 has 320 GB/s. Their P100 has 732 GB/s. The threat to Nvidia from Intel is in the Nervana chips they recently acquired. Those are presumably using HBM2 and could potentially beat GPUs for neural net training performance.
- bonzini 10y ago100 GB/s is the bandwidth of six DDR4 channels. Knights Landing has 500 GB/s of local memory bandwidth, plus the same 100 GB/s of a Xeon for DDR4. If future Xeons integrated RAM like Knights Landing does, this would make GPUs less interesting. But KNL can already be used as the main CPU, if I remember correctly.
- geezerjay 10y agoYou're ignoring the main factor: cost. Intel's offering costs as high as €4000 per processor, which come with a meager 8 cores. NVidia's offering sells, right now, for less than €1000 a pop.
- daemin 10y agoWhat about ongoing electricity costs? IIRC my graphics card chews up more power than my CPU.
- geezerjay 10y agoA delta of $3000 per component buys you a whole lot of electricity. Furthermore, the performance of each of NVidia's GPUs falls somewhere between 5 and 20 teraFLOPs. A Haswell Xeon gets you about half a teraFLOP for around 1/3 of the power consumption of a NVidia Tesla P100 GPU.
- 10y ago
- shas3 10y agoHow exactly Nvidia and ARM are competitors of Intel is an interesting question in itself. Nvidia and ARM are fabless and compete against a subset of Intel's IP and products. Intel may take multiple routes to reacting against superior competition without necessarily even making better GPGPUs.
- frozenport 10y ago>>This is not yet happening, but I'm hoping it will soon. Intel made massive gains promoting OpenCL, when they helped to redo OpenCV's umat infrastructure.
- chris11 10y agoIsn't some of the advantage coming from the fact that gpus are much better designed for massively parallel computations?
- dharma1 10y agoThe high end Intel CPUs like Xeon Phis that have enough compute muscle to get anywhere near NVidia GPU perf for deep learning are far too expensive to be able to replace them
- geezerjay 10y agoPrecisely. Intel is trying to compete with NVidia by offering inferior performance at a premium price. In massively parallel applications, cost is closely tied to performance. NVidia has both aspects secured very well. In fact, NVidia is already a prominent part in supplying components for the 3rd place in the Top500, Oak Ridge National Laboratory's Titan system, which mixes up AMD Opterons with NVIdia k20x GPUs.
- geezerjay 10y ago> Intel has to do only two things to start taking market share away from Nvidia in DL/AI quickly: ...except that Intel has been trying to do that for over a decade, and Intel has been failing repeatedly for over a decade. If that was as simple and easy as you lead to believe, Intel would've already done it by now. Except it didn't, because it can't.
- raverbashing 10y agoNo, there's no "Good Enough" it needs to be fast enough. Xeon Phi is their contender, but we'll have to see enough A high-end GPU is around 10x faster than your avg CPU https://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-benchmarks.html https://www.nvidia.com/object/gpu-accelerated-applications-t...