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The rise of AI is creating new variety in the chip market, and trouble for Intel

economist.com

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Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#41

Post by ansgri »

ganfortran wrote: post #22
friedman23 wrote: post #5

> Instead of making ASICS or FPGAs, Intel focused in recent years on making its CPU processors ever more powerful If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation. AI is not going to eat intel's lunch, all those computers still require cpus. AMD on the other hand may eat intel's lunch by releasing powerful multicor…

> AI is not going to eat intel's lunch, all those computers still require cpus. But they might not need that powerful CPU anymore, if computational heavy task happens elsewhere anyway. So as time goes, CPU will become less critical, meaning less money for Intel

Let's see. As these early ML-heavy prototypes will start becoming industrial and safety-critical products, the emphasis will be on explainability and graceful degradation. This inevitably leads to a hybrid system with poorly vectorizable parts (expert systems, ad-hoc solutions), which will have to be tightly integrated. Also, full of various auditing and monitoring systems, which are "oligo-threaded" by nature.

Therefore you'll need a capable several-core CPU anyway, and unless the memory is shared (which means you have a SoC, where there's no clear leader AFAIU), moving data in and out becomes a major bottleneck.

I think for most systems where explainability and audit trail are important it will be easier (I mean cheaper) to build on a powerful CPU from the start, and when the system is successful (i.e. approved by real customers), then the highly-parallel parts may be factored out to special hardware. Using them from the start is very risky.

These thoughts are from experience building an all-weather computer vision system for traffic control applications (99.5+% vehicle classification, with errors requiring human intervention and explanation), and being rather familiar with a company which makes specialized ID-recognizing mobile apps.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#42

Post by ansgri »

petra wrote: post #7
friedman23 wrote: post #5

> Instead of making ASICS or FPGAs, Intel focused in recent years on making its CPU processors ever more powerful If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation. AI is not going to eat intel's lunch, all those computers still require cpus. AMD on the other hand may eat intel's lunch by releasing powerful multicor…

ASIC/FPGA or even GPU's aren't the future of neural computing. The future is analog(orders of magnitude perf/watt and perf/$). That require older fabs, optimized for analog, and having good embedded flash, which TSMC has and Intel mostly hasn't got. And that same future applies not only for neural computing, but for a field called approximate-computing, i.e. computing where results aren't accurate.Some/many signal an…

I'm sure AC will be a major revolution in computing in general, though ANN-based systems may come there earlier.

Also, there's a huge application domain in image preprocessing: the pixel value is analog and noisy anyway, so building an analog primary visual cortex with a bank of common filters (line segments, stable features etc.) makes a lot of sense.

ADD: I'm also thinking about accelerating RANSAC-type algorithms, where you perform lots of preliminary evaluations to filter out the outliers. I bet one can cheaply implement an "100-argmins of 100 x 100 fixed10 distance matrix" computation in a handful of cycles with analog circuits. And high-dimensional RANSAC-type algorithms are what needed for robust and precise 3D visual navigation.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#43

Post by phkahler »

Do most of these application (machine learning, vision, etc) rely on OpenCL? It seems to me that GPUs are better suited to OpenCL than a regular CPU, but if that's what all the excitement is about I suggest reading up on some of the work on adding vector extensions to RISC-V and the corresponding flops/watt they're may achieve. They are basing some of the work on results from here: http://hwacha.org although they make it clear that hwacha will not be the standard vector instruction set.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#44

Post by clarry »

Retric wrote: post #23
coldtea wrote: post #13

Earlier quoted context omitted.

> If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation. And why is that because of "abusing their market position", as opposed to plainly and clearly being more difficult to get faster processors at 14 nm and lower resolutions (and with the low power requirements of today)? Besides, the trend the article points to is a…

They put 'crappy' GPU's on die which they continued to upgrade even when the CPU side stagnated. So, while the last upgrade may have been a process issue, the last 4 CPU refreshes have all been classic monopolist behavior. PS: GPU's might seem like something you want on the CPU, but bandwidth is a killer worse they add heat which directly lowers CPU performance.

Frankly the updates to the GPUs have been very minor, over the past few generations. And for some reason, they don't put anything close to Iris or Iris Pro on the desktop CPUs.

I've been waiting for a few generations now to get an Intel CPU with decent iGPU but it's really been stagnant. I gave up the wait and pre-ordered a Ryzen last week.

I do still think it makes sense for Intel to ship CPUs with those integrated CPUs, although maybe it wouldn't be a bad idea to offer a chip with more cores and no GPU for the enthusiasts.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#45

Post by kogepathic »

varelse wrote: post #32

Crazy idea: buy the rights to sell AMD's Vega GPUs fabbed out of Intel and use Intel's resources to build top-notch math and AI libraries for them. Stupid idea: Keep insisting that x86-compatibility is the killer feature for winning the parallel processor wars. Stupidest idea: CS professors continuing to tell their students that learning concurrent programming is too hard.

> Crazy idea: buy the rights to sell AMD's Vega GPUs fabbed out of Intel

1) I don't think Intel has a lot of spare fab capacity. Certainly not on the nodes AMD is looking to produce Vega on.

2) Intel only just announced a deal to start manufacturing ARM chips on their fabs. [0]

Honestly I can't believe it took Intel so long to wake up and realize that their x86 business is okay, but if they want to survive long term they have to accept that they need another business segment to bring in money after x86 stops being as relevant as it is today.

Just look at TSMC [1] if you want an example of why Intel is foolish to think they can keep being top dog with only x86. TSMC was nobody in the 90's, and now their market cap is within ~10% of Intel's [2] (TSMC @ 160B versus Intel @ 175B).

TSMC doesn't even design their own chips. I'm not saying building semiconductors is easy, or that TSMC has no R&D costs, but you're talking about a company which specializes only in manufacturing some of the most advanced chips on the planet, and doing it at volumes I doubt Intel can match. I predict unless Intel does something major in the near future (The former CEO of Intel Paul Otellini captured it best himself:

"It wasn't one of these things you can make up on volume. And in hindsight, the forecasted cost was wrong and the volume was 100x what anyone thought." [3]

Intel still thinks they can kill it by selling expensive CPUs. TSMC is proving that thinking is outdated. You don't have to have a 60%+ margin on your chips, you just have to make it up in volume.

Where do you think the next billion chips are going to be sold? It's not going to be $500 x86 CPUs. It's going to be [0] http://www.theverge.com/2016/8/16/12507568/intel-arm-mobile-...

[1] http://www.google.com/finance?q=NYSE%3ATSM

[2] http://www.google.com/finance?q=NASDAQ%3AINTC

[3] http://www.theinquirer.net/inquirer/news/2268985/outgoing-in...

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#48

Post by lowglow »

deepnotderp wrote: post #39

Founder of a similar startup here. The strategy that nervana is taking is to reduce precision to 16 bit fixed point and then accumulate in 48 bits (which appears to be unnecessary and 24 bits should be sufficient). I can answer any questions if anyone has any.

Yeah, what's a good intro on understanding all of this? I've got an EE/Chem/Math background.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#49

Post by astrodust »

jhj wrote: post #34

The "3,854 cores" versus "28 cores" is dubious as always. 3,854 I think counts just the individual fp32 ALUs; a true similar comparison would be number of warp schedulers or maximum number of warps resident at once, or even just SM count (which share a cache). Apples to oranges (a super-hyperthreaded 1024/2048-bit wide vector machine with minimal cache to a minimally hyperthreaded 128/256-bit wide vector machine with…

Apples to oranges? It's more like how a hundred thousand squirrels can't write a novel no matter how long they're given but one person can given a few months.

Not all compute devices are equivalent and "core" vs. "core" is a totally absurd comparison.

Re: The rise of AI is creating new variety in the chip market, and trouble for Intel

#50

Post by deepnotderp »

lowglow wrote: post #48
deepnotderp wrote: post #39

Founder of a similar startup here. The strategy that nervana is taking is to reduce precision to 16 bit fixed point and then accumulate in 48 bits (which appears to be unnecessary and 24 bits should be sufficient). I can answer any questions if anyone has any.

Yeah, what's a good intro on understanding all of this? I've got an EE/Chem/Math background.

For deep learning or chips for deep learning? With an EE/Chem/Math background you should be set to go :)

For deep learning, I highly recommend the cs231n course materials (available for free online) and the Deep Learning Book by Goodfellow et al.

For chip design for deep learning specifically, it's a fairly new field, and a lot of commercial interests, hence why a lot of it isn't available in the form of an "Intro to Deep Learning Chip Design" course. But, the basic point is that deep learning can both train and perform inference in astonishingly low precision.

For training: https://arxiv.org/abs/1502.02551

For inference, there are so many papers confirming this fact that there really isn't one key paper to point to. This article is a good introduction however: https://petewarden.com/2015/05/23/why-are-eight-bits-enough-...

Other than that, stripping out the cache hierarchy, HBM memory, etc. are the obvious steps to take in targeting deep learning. Note that it's my opinion that deep learning chip startups (such as ours) need another "secret sauce" beyond simply lowering precision, we're not like Intel which can just say "okay, here's $100mil, make me an 8-bit GPU, Go."

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