Nvidia shows signs in [2021]

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Timothy Prickett Morgan: And now there is a two-year cadence in place for GPUs, DPUs, and soon CPUs as well that enterprises can count on.

Obviously, AMD is much more competitive with its “Aldebaran” Instinct MI200 series GPU accelerators than it has ever been. It is really two GPUs, not one, and I reminded everyone that AMD had “pulled a K80” by putting two GPUs on one device, but nonetheless, this GPU has won two exascale-class systems and many more smaller systems.

I realize that there will not be new GPU announcements from Nvidia until next year, based on the cadence, but what is your response to this competition from AMD, and soon, to a lesser extent, from Intel in the GPU compute arena?

Jensen Huang: First of all, we have competition all the time. So it is not true that this is the first so-called Nvidia killer that has come out. Every year there’s an Nvidia killer and people call it that.

Timothy Prickett Morgan: I mean in the upper echelon HPC and AI supercomputer space. For the past decade and a half, when it comes to GPU-accelerated supercomputers, you have been the whole game.

Jensen Huang: Actually, I think this is the absolutely easiest space, and let me tell you why. The reason for that is because an HPL machine needs two things – just two things. HPC centers order everything years in advance, so they have no idea what performance will be for any given device, but here’s the equation for you …

Timothy Prickett Morgan: Go ahead …

Jensen Huang: The number of peak FP64 flops and memory capacity, put those two things put into one bucket. And in the other bucket, put in dollars. That’s it. That’s the equation. And you know that …

Timothy Prickett Morgan: And so AMD decided to jack up the flops and slash the price? That’s what I think happened …

Jensen Huang: The question is how do we see the world, and the reason why competition is so intense for us. And it’s seriously intense. It’s not minor intense. It’s seriously intense. Accelerated computing is not for the faint of heart. So let me just prove it.

You can build the world’s best fricking everything-anything chip, you stick it into the computer, what will you accelerate? Absolutely nothing. Isn’t that right? Accelerated computing is insanely hard. And the reason for that is Moore’s law is insanely good. No one has ever looked at Moore’s Law, even at its reduced rate and said over the course of time, that is not one of the most formidable technology forces in the history of humankind. And yet, in order for us to succeed as a company, we have to deliver results well above Moore’s law.
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https://wccftech.com/nvidia-ceo-on-...t-have-any-magic-bullets-to-tackle-shortages/
 
Comptetion's good. Hardware is evolving at quite good rates, perhaps even more so then 8 years ago. Apple's also responsible for that.
 
Atos and NVIDIA to Advance Climate and Healthcare Research With Exascale Computing (hpcwire.com)
November 15, 2021
Atos and NVIDIA today announced the Excellence AI Lab (EXAIL), which brings together scientists and researchers to help advance European computing technologies, education and research.

The lab’s first research projects will focus on five key areas enabled by advances in high performance computing and AI: climate research, healthcare and genomics, hybridization with quantum computing, edge AI/computer vision and cybersecurity

Atos will develop an exascale-class BullSequana X supercomputer with NVIDIA’s Arm-based Grace CPU, NVIDIA’s next-generation GPU, Atos BXI Exascale Interconnect and NVIDIA Quantum-2 InfiniBand networking platform.
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NVIDIA Announces Financial Results for Third Quarter Fiscal 2022 (hpcwire.com)
November 17, 2021
  • Record revenue of $7.10 billion, up 50 percent from a year earlier
  • Record Data Center revenue of $2.94 billion, up 55 percent from a year earlier
  • Record Gaming revenue of $3.22 billion, up 42 percent from a year earlier
NVIDIA today reported record revenue for the third quarter ended October 31, 2021, of $7.10 billion, up 50 percent from a year earlier and up 9 percent from the previous quarter, with record revenue from the company’s Gaming, Data Center and Professional Visualization market platforms.

GAAP earnings per diluted share for the quarter were $0.97, up 83 percent from a year ago and up 3 percent from the previous quarter. Non-GAAP earnings per diluted share were $1.17, up 60 percent from a year ago and up 13 percent from the previous quarter.
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DegustatoR said:
https://wccftech.com/nvidia-ceo-on-...t-have-any-magic-bullets-to-tackle-shortages/
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Given that it’s a government contract he is probably right about the equation. Still hard to believe that those labs are looking at just raw flops and dollars. They have to actually use the thing right? That’s assuming of course that these labs actually do any real work. I did an internship at los alamos and the pace of work was glacial. There was no urgency to do anything.
 
DegustatoR said:
Does anyone really believe in the ~100M USD mining profits number they are specifying?
I mean they see ~100% YoY growth in proviz - a segment which was on a downslide for the last several years.
What does that tell us here?
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Of course it's not 100M. It's 100M from Mining GPU. They said themself, that they don't know how much is mining.

But i'm not agreeing on proviz. Proviz was only declining because of start of corona, before it was growing slowly. Homeoffice, pend up demand because of corona and most important omniverse are pushing proviz. Their omniverse software business is inside proviz, this will lead to 1 billion quarterly revenue in a pretty short time.

trinibwoy said:
Given that it’s a government contract he is probably right about the equation. Still hard to believe that those labs are looking at just raw flops and dollars. They have to actually use the thing right? That’s assuming of course that these labs actually do any real work. I did an internship at los alamos and the pace of work was glacial. There was no urgency to do anything.
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Just look at theorethical FP64 and performance numbers given by amd. MI200 has 4,9 times FP64 vs A100, but is just 2,8 faster in HPL. In other benchmarks it's even worse. So you need ~2xFlops in MI200 vs A100 for the same speed. It's just prestige to have a exascale system like the chinese. You want a really balanced system for many workloads? Take Ponte Vecchio, probably Hopper and MI300. MI200 is just Flops for the exascale game.
 
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Excellent read on Nvidia's future strategy, check article for more detail.
AMD Is Beating Nvidia At Its 2017 Game, But The Game Has Moved On (nextplatform.com)
November 17, 2021
In the call with Wall Street analysts, Huang did not break the Nvidia datacenter revenue stream down by application type – HPC simulation and modeling, AI machine learning training and inference, database acceleration (analytics and Spark databases), virtual desktops, and such – but he did say that Nvidia has over 25,000 customers who are using its AI platform for machine learning inference, and probably a similar number have been using it for machine learning training. That would imply that the AI part of the Nvidia business has a customer set that is perhaps two orders of magnitude larger in terms of customer count (but significantly less in terms of aggregate compute, we think) than its HPC business. There are some truly large GPU-accelerated HPC systems out there in the world, and they have a lot of oomph.

AI is on a hockey stick exponential growth path, and HPC seems to be growing more linearly.
...
Huang and Colette Kress, Nvidia’s chief financial officer, rattled off a bunch of interesting statistics during the call. Let’s just rattle them off for a second, and forgive us for once for using bullets:

  • There are over 3 million CUDA application developers and the CUDA development tools have been downloaded over 30 million times in the past decade and a half. Which means people are keeping current.
  • The company’s gaming business is going like gangbusters, and only about a quarter of the installed base has moved to the RTX architecture, so there is just a huge wave of business that can be done here. And it isn’t cryptocurrency, either.
  • The cryptocurrency-specific GPUs, which do not have their hashing functions crimped, only generated $105 million of revenue in fiscal Q3, so this is not a mining bubble.
  • The AI Enterprise software stack is now generally available and is certified to run atop VMware’s vSphere/ESXi server virtualization stack, making it easily consumable by enterprises.
  • The Launchpad co-location stacks with partner Equinix are now available in nine different locations, and of course, all the major clouds also have GPU-accelerated gear long-since.
  • In networking, demand for the former Mellanox products outstripped supply, with older 200 Gb/sec Spectrum and Quantum InfiniBand switches and ASICs and ConnectX-5 and ConnectX-6 adapter cards, and the company is poised to ramp up sales of 400 Gb/sec Quantum-2 InfiniBand and their companion ConnectX-7 adapter cards and BlueField-3 DPUs.
  • No matter how skeptical you might be about GPU-based inference, the TensorRT software stack and the Triton inference server stack are being adopted by the market, and we think this is not necessarily because the GPU offers the best or cheapest inference processing, but because of its compatibility with machine learning training platforms. Nvidia says that inference revenues are growing faster than the overall growth in the datacenter business.
  • There are over 700 companies that are evaluating the Omniverse 3D design and digital twin software stack, and since the open beta started in December 2020, it has been downloaded over 70,000 times. Nvidia estimates that there are over 40 million 3D designers in the world, which is, by the way, a much larger installed base than Java or PHP or C/C++ programmers individually and probably on the same order of magnitude collectively across those three languages, just to give you some scale. The Omniverse opportunity is going to accelerate the Nvidia business further, and it will be half hardware and half software.
We have been wondering why Nvidia is not more freaked out by AMD having such big wins with the exascale-class supercomputers in the United States and smaller machines around the globe in HPC centers. We have spent some time with Huang puzzling out the Omniverse opportunity, and now we understand the scope of the datacenter business. AI, and its extension and merging with HPC and other design technologies and VR/AR adjuncts is just so much more of an opportunity.

There are 300 or so hyperscalers, cloud builders, and service providers who represent more than half of the aggregate compute consumed in the world and probably a little less than half of the revenue. There are somewhere on the order of 50,000 large enterprises that do interesting things that consume most of the other half. The 3,000 or so HPC centers in the world do interesting things and are solving hard problems, but they represent only a sliver of the compute and money.
......
We have been in the trenches for so long, watching HPC accelerate with GPUs and then AI emerge as a new computing paradigm, that we didn’t see the hugeness of the Omniverse, which will obliterate such distinctions and which is such a huge opportunity that even Nvidia has trouble getting its arms around it

Huang put it this way: In the next five years, tens of millions of retail outlets will have some form of conversational AI avatar speaking to customers instead of actual human beings, who don’t want a low-paying job. The AI avatar doesn’t get tired or sick, like people do, and it will cost less than people do we suspect. And this population of virtual people will require enormous amounts of hardware and software, and companies will spend money on this just like they did 50 years ago to get rid of file clerks shuffling through file cabinets with manila folders and accountants working with pencil on greenbar in the back office.

No one will talk about it that way, but it is damned well going to happen. Every avatar will have an Omniverse license, and you can bet it will cost less than health insurance for a real person, and the hardware to drive those avatars will cost less than a salary for a real person.
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GPU shipments increase year-over-year in Q3 | Jon Peddie Research
November 22, 2021
AMD's overall market share percentage from last quarter increased 1.4%, Intel's market share decreased by -6.2%, and Nvidia's market share increased 4.86%, as indicated in the following chart.
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PR_MW-Q321-001.png

PC dGPU marketshare for Q3'21: Nvidia 83%, AMD 17%.

Overall GPU unit shipments decreased by -18.2% from last quarter, AMD shipments decreased by -11.4%, Intel's shipments decreased by -25.6%, and Nvidia's shipments increased 8.0%.
...
Jon Peddie, President of JPR, noted, “Covid continues to unbalance the fragile supply chain that relied too heavily upon a just-in-time strategy. We don’t expect to see a stabilized supply chain until the end of 2022. In the meantime, there will be some surprises.”
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“The FTC is suing to block the largest semiconductor chip merger in history to prevent a chip conglomerate from stifling the innovation pipeline for next-generation technologies,” said FTC Bureau of Competition Director Holly Vedova. “Tomorrow’s technologies depend on preserving today’s competitive, cutting-edge chip markets. This proposed deal would distort Arm’s incentives in chip markets and allow the combined firm to unfairly undermine Nvidia’s rivals. The FTC’s lawsuit should send a strong signal that we will act aggressively to protect our critical infrastructure markets from illegal vertical mergers that have far-reaching and damaging effects on future innovations.”

https://www.ftc.gov/news-events/pre...es-block-40-billion-semiconductor-chip-merger
 
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