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Nvidia Corp. is bringing artificial intelligence to the edge of the network with the launch early Monday of its new Nvidia EGX platform that can perceive, understand and act on data in real time without sending it to the cloud or a data center first.
Delivering AI to edge devices such as smartphones, sensors and factory machines is the next step in the technology’s evolutionary progress. The earliest AI algorithms were so complex that they could be processed only on powerful machines running in cloud data centers, and that means sending lots of information across the network. But this is undesirable because it requires lots of bandwidth and results in higher latencies, which makes “real-time” AI something less than that.
What companies really want is AI to be performed where the data itself is created, be it at manufacturing facilities, retail stores or warehouses. And it’s a problem that several tech firms have attempted to address, most recently Intel Corp. with the launch of its first 10-nanometer “Ice Lake” chips today but also dozens of startups.
But Nvidia’s entrance into the AI edge is notable because the company’s graphics processing units are widely regarded as some of the best AI-processing hardware around. That includes its Tesla V100 for deep learning, and its Quadro GV100, which enables ray tracing, the process of creating realistic images, to be done in real time.
The new NVIDIA EGX platform is scalable from a light server based on the Jetson Nano processor that performs 0.5 Trillion operations per second in a few watts, to a micro data center with a rack of NVIDIA T4 based edge servers that can do 10,000 trillion operations per second. The energy-saving capabilities of the chip are important for AI, since traditional hardware is a massive power hog when running such tasks.
In a media briefing, Justin Boitano, senior director of enterprise and edge computing at Nvidia, said there will be huge demand for a platform such as NGX because there will be something like 150 billion machine sensors and “internet of things” devices in the world by 2025. He said many of these sensors would be used for initiatives such as “smart cities,” and will be pumping out data that needs to be processed onsite, for reasons such as a demand for lower latency, real-time response, data sovereignty rules or privacy concerns.
“AI is really the killer application in all industries both in vision and in speech,” Boitano said.
Partnerships are important as well if people are actually going to put those chips to good use. For that reason Nvidia is integrating the NVIDIA Edge Stack software than runs on EGX with Red Hat Inc.’s OpenShift Kubernetes container orchestration platform in order to make it compatible with modern software applications.
The platform also integrates security, storage and networking technologies from Mellanox Technologies Ltd., which is a company that Nvidia intends to acquire by the end of year for a cool $6.9 billion.
“Mellanox Smart NICs and switches provide the ideal I/O connectivity for data access that scale from the edge to hyperscale data centers,” said Mellanox Chief Technology Officer Michael Kagan.
Nvidia is teaming up with no fewer than 13 different server makers to sell the EGX platform, including big-name manufacturers such as Cisco Systems Inc., Dell-EMC, Hewlett Packard Enterprise Co. and Lenovo Group Holding Ltd.
NGX is also compatible with AI applications running on major cloud infrastructure services such as Amazon Web Services and Microsoft Azure, and can connect to IoT services such as AWS IoT Greengrass and Azure IoT Edge.
Nvidia stock rose as much as 7% on Thursday after hours, after the company reported better-than-expected fiscal-second quarter earnings.
Here’s what the company reported:
Earnings: $1.24 per share, excluding certain items, vs. $1.15 per share as expected by analysts, according to Refinitiv.
Revenue: $2.58 billion, vs. $2.54 billion as expected by analysts, according to Refinitiv.
Nvidia’s revenue fell 17% on an annualized basis in the quarter, which ended on July 28, according to a statement.
Nvidia’s biggest segment, gaming, produced $1.31 billion in venue, down 27% on an annualized basis and just above the $1.30 billion consensus estimate among analysts surveyed by FactSet. Nvidia saw fewer shipments of graphics cards for desktop PCs and system-on-chip components for gaming systems.
The company’s data center segment came in with $655 million in revenue. That’s down 14% on an annualized basis and a bit less than the $668.5 million FactSet consensus. Nvidia cited a decline in revenue from “hyperscale” customers like cloud infrastructure providers. “While sales for internal hyperscale use were muted, the engineering focus on AI is growing,” Nvidia’s chief financial officer, Colette Kress, said on a conference call with analysts on Thursday.
With respect to guidance, Nvidia says that in the fiscal third quarter it expects $2.90 billion in revenue, plus or minus 2%. That would represent a roughly 9% annualized decline, and it’s below the $2.97 billion consensus estimate among analysts polled by Refinitiv.
Nvidia said it estimates gross margin in the fiscal third quarter to be 62.5%, plus or minus 50 basis points; analysts polled by FactSet had been looking for 60.2%.
Prior to earnings, shares of Nvidia had risen 11% since the start of 2019. In the fiscal second quarter Nvidia announced GeForce RTX Super graphics cards for gaming.
In the past few quarters, Nvidia’s results were impacted by supply issues. In a Tuesday note Matt Bryson of Wedbush Securities told clients that there are reasons to be optimistic about a return to normalcy in the second half of 2019. He pointed to pickup of Nintendo products containing Nvidia components and the introduction of the Nintendo Switch Lite console.
“Our meeting with [PC maker] Maingear indicated NVDA continues to dominate the high end/custom PC GPU market and is holding share vs. AMD, ” wrote Bryson, who has an outperform rating on Nvidia stock.
“Essentially our business is normalized,” Kress said.
Amazon Brings AI Performance to the Cloud with NVIDIA T4 GPUs blogs.nvidia.com AWS EC2 G4 instances feature highly efficient Turing architecture processors to deploy accelerated hyperscale AI inference, cloud gaming and the latest RTX graphics.
Nvidia beat on the top and bottom lines, but quarterly revenue guidance was below expectations.
The company’s revenue has now declined four quarters in a row.
Nvidia shares seesawed in extended trading on Thursday after the company issued better-than-expected fiscal third-quarter results and slightly soft quarterly guidance.
Here’s how the company did:
Earnings: Excluding certain items, $1.78 per share, vs. $1.57 per share as expected by analysts, according to Refinitiv.
Revenue: $3.01 billion, vs. $2.91 billion as expected by analysts, according to Refinitiv.
Nvidia’s revenue fell 5% from a year ago in the quarter, which ended on October 27, according to a statement. The company sold inventory that it had previously written off in the quarter, but revenue has now declined four quarters in a row on an annualized basis.
Nvidia’s largest business segment, Gaming, shrunk 6% year-over-year at $1.66 billion in quarterly revenue, which is above the $1.54 billion consensus among analysts polled by FactSet.
The company Data Center business delivered $726 million in revenue, less than the $754.2 million FactSet consensus estimate. The Professional Visualization segment came up with revenue of $324 million, higher than the $315.4 million estimate.
In the fiscal third quarter Nvidia announced new GeForce Super graphics processing units for gaming and a new kind of Microsoft Azure Data Box Edge hardware product containing its T4 GPUs.
In terms of guidance, Nvidia said it expects $2.95 billion in revenue, plus or minus 2%, for the fiscal fourth quarter, which implies a nearly 34% increase. But analysts polled by Refinitiv had expected $3.06 billion in fiscal fourth-quarter revenue.
The company believes the Data Center business will post a sequential improvement in the fiscal fourth quarter. Nvidia’s forecast doesn’t include the impact from Mellanox, a $6.9 billion acquisition that has not yet closed.
Nvidia is calling for $805 million in operating expenses in the fiscal fourth quarter, excluding certain items, more than the FactSet estimate of $768 million.
In the past year Nvidia has dealt with numerous issues, including the disappearance in revenue from selling cards for mining cryptocurrencies and a pause in spending from companies that operate hefty data centers, and they’ve hurt the company’s track record of surpassing expectations, Deutsche Bank analysts led by Ross Seymore wrote in a note distributed to clients on Sunday.
The analysts, who have a hold rating on Nvidia, said it was likely the company would achieve “positive follow-through” in its Data Center segment in the fiscal fourth quarter, although the Gaming business would have a tougher sequential revenue comparison, partly because of negative seasonality effects from Nintendo Switch console sales.
Nvidia stock has risen 57% since the start of 2019.
Nvidia Stock Is Gaining After a Morgan Stanley Upgrade. Here's What the Analyst Sees. -- Barrons.com DOW JONES & COMPANY, INC. 8:08 AM ET 11/25/2019
Symbol Last Price Change
QUOTES AS OF 04:15:00 PM ET 11/22/2019
Nvidia (NVDA) stock is trading higher early Monday after Morgan Stanley semiconductor analyst Joseph Moore upped his rating on the chipmaker to Overweight from Equal Weight, with a new price target of $259, from $217, citing improving sales prospects for both gaming and data center applications.
"Both gaming and data center fell short of expectations over the course of 2019, and we were surprised at how well the stock was doing in light of that," Moore writes in a research note. "But the stock has not meaningfully outperformed the robust semiconductor group, and as we look into 2020, we see catalysts for Nvidia's(NVDA) growth accelerating on nearly every vector, even in what we expect will be a tough semiconductor environment -- ray tracing software support should generate more gamer enthusiasm in gaming products, and new data center workloads around conversational AI should lead to another leg of data center growth."
Moore concedes that the stock is pricey on near-term earnings, and says he had held back on turning more bullish on the theory that January quarter consensus estimates were too high -- but adds that the observation while accurate " didn't give us the pullback/entry point that we had hoped for."
The analyst writes that he sees "upside from here." Concludes Moore: "All semiconductor stocks are at a premium multiple on 2020 earnings, but across the group we see Nvidia(NVDA) as having one of the best opportunities to maintain a high multiple as we shift to 2021."
The analyst expects 18% growth in the company's gaming business in 2020 after "an investment year" in 2019, with " double digit potential growth thereafter."
In the data center, he sees Nvidia's(NVDA) business roughly doubling over the next three years, as investment increased in machine learning and artificial intelligence applications.
"The company remains nearly unchallenged in its key [machine learning] training market, maintains high market share in emerging areas such as inference, and is leading the way in new growth opportunities such as traditional machine learning analytics," he writes.
NVDA early Monday is up 2.5%, to $216.23, while S&P 500 futures have advanced 0.2%, Dow Jones Industrial Average futures have risen 0.2%, and Nasdaq Composite futures have gained 0.3%.
Write to Eric J. Savitz at email@example.com
Nvidia's Biggest Pleasant Surprise May Be Yet to Come
Tae Kim 2 days ago
Nvidia's Biggest Pleasant Surprise May Be Yet to Come
(Bloomberg Opinion) -- These days, with the fallout from the coronavirus pandemic wreaking havoc on economic and business projections, a company can stand out just by maintaining its outlook. For chipmaker Nvidia Corp., it helps that the outlook was already rosy to begin with.
On Tuesday, a day after Applied Materials Inc. and Twitter Inc. both withdrew their current-quarter forecasts, Nvidia surprised investors by not altering the financial guidance it gave on Feb. 13. At the time, the chipmaker projected revenue of $3 billion, plus or minus 2 percent, for its fiscal first quarter ending in April, representing a 35% increase from the prior year. The shares surged more than 17%, and continued their climb Wednesday, adding another 2.9%.
Nvidia may prove more resilient than most in dealing with the negative effects of the virus outbreak. In fact, its two key businesses — gaming and cloud computing — have actually benefited from some of the coronavirus mitigation developments in recent weeks.
With social distancing, shelter-in-place restrictions and widespread school and other closures leaving more people inside with time on their hands, video-gaming trends are soaring. That bodes well for Nvidia, as the gaming segment accounts for nearly half of its revenue. Nvidia management said they saw a 50% surge in total gaming hours from its installed base as many students and workers were staying-at-home. The company’s other core business — data centers, which generated almost a third of revenue in the latest quarter — is also humming, with usage of internet services rising as more people work from home. Chief Financial Officer Colette Kress said companies are increasingly using Nvidia’s chips for artificial intelligence workloads such as natural language understanding and supply-demand forecasting.
Meanwhile, in China — which represents about one-quarter of its revenue — the situation is improving, as gaming cafes reopen and laptop sales rebound. Kress said the company’s manufacturing supply chain is coming back online and expects capacity to return to about 70% to 80% normal levels by month-end.
But even more important, the new products Nvidia originally planned to reveal this week are on track and expected to contribute revenue in the current quarter. Investors shouldn’t overlook this tidbit. Nvidia’s launch of its next-generation chips based on its code-named “Ampere” architecture may be its most promising one since 2016, one that led to a series of positive earnings surprises and large gains for its stock price.
So while Nvidia is being rewarded for staying the course even as the coronavirus throws many other companies off track, it’s what’s not even baked in yet that may cheer investors the most.
This column does not necessarily reflect the opinion of Bloomberg LP and its owners.
Tae Kim is a Bloomberg Opinion columnist covering technology. He previously covered technology for Barron's, following an earlier career as an equity analyst.
Nvidia's A100 chip has 54 billion transistors. Image Credit: Nvidia
Nvidia unwrapped its Nvidia A100 artificial intelligence chip today, and CEO Jensen Huang called it the ultimate instrument for advancing AI. Huang said it can make supercomputing tasks — which are vital in the fight against COVID-19 — much more cost-efficient and powerful than today’s more expensive systems.
The chip has a monstrous 54 billion transistors (the on-off switches that are the building blocks of all things electronic), and it can execute 5 petaflops of performance, or about 20 times more than the previous-generation chip Volta. Huang made the announcement during his keynote at the Nvidia GTC event, which was digital this year.
The launch was originally scheduled for March 24 but was delayed by the pandemic. Nvidia rescheduled the release for today, as the chips and the DGX A100 systems that used the chips are now available and shipping.
The Nvidia A100 chip uses the same Ampere architecture (named after French mathematician and physicist André-Marie Ampère) that could be used in consumer applications such as Nvidia’s GeForce graphics chips. In contrast to Advanced Micro Devices (AMD), Nvidia is focused on creating a single microarchitecture for its GPUs for both commercial AI and consumer graphics use. But Huang said mixing and matching the different elements on the chip will determine whether it is used for AI or graphics.
The DGX A100 is the third generation of Nvidia’s AI DGX platform, and Huang said it essentially puts the capabilities of an entire datacenter into a single rack. That is hyperbole, but Paresh Kharya, director of product management datacenter and cloud platforms, said in a press briefing that the 7-nanometer chip, codenamed Ampere, can take the place of a lot of AI systems being used today.
“You get all of the overhead of additional memory, CPUs, and power supplies of 56 servers … collapsed into one,” Huang said. “The economic value proposition is really off the charts, and that’s the thing that is really exciting.”
Nvidia’s Jensen Huang holds the world’s largest graphics card.
Image Credit: Nvidia
For instance, to handle AI training tasks today, one customer needs 600 central processing unit (CPU) systems to handle millions of queries for datacenter applications. That costs $11 million, and it would require 25 racks of servers and 630 kilowatts of power. With Ampere, Nvidia can do the same amount of processing for $1 million, a single server rack, and 28 kilowatts of power.
“That’s why you hear Jensen say, ‘The more you buy, the more you save,'” Kharya said.
Huang added, “It’s going to replace a whole bunch of inference servers. The throughput of training and inference is off the charts — 20 times is off the charts.”
The first order
Above: DGX A100 servers in use at the Argonne National Lab.
Image Credit: Argonne
The first order for the chips is going to the U.S. Department of Energy’s (DOE) Argonne National Laboratory, which will use the cluster’s AI and computing power to better understand and fight COVID-19. DGX A100 systems use eight of the new Nvidia A100 Tensor Core GPUs, providing 320 gigabytes of memory for training the largest AI data sets, and the latest high-speed Nvidia Mellanox HDR 200Gbps interconnects.
Multiple smaller workloads can be accelerated by partitioning the DGX A100 into as many as 56 instances per system, using the A100 multi-instance GPU feature. Combining these capabilities enables enterprises to optimize computing power and resources on demand to accelerate diverse workloads — including data analytics, training, and inference — on a single fully integrated, software-defined platform.
Immediate DGX A100 adoption and support
Above: DGX A100 system at Argonne National Lab.
Image Credit: Argonne
Nvidia said a number of the world’s largest companies, service providers, and government agencies have placed initial orders for the DGX A100, with the first systems delivered to Argonne earlier this month.
Rick Stevens, associate laboratory director for Computing, Environment, and Life Sciences at Argonne National Lab, said in a statement that the center’s supercomputers are being used to fight the coronavirus, with AI models and simulations running on the machines in hopes of finding treatments and a vaccine. The DGX A100 systems’ power will enable scientists to do a year’s worth of work in months or days.
The University of Florida will be the first U.S. institution of higher learning to receive DGX A100 systems, which it will deploy to infuse AI across its entire curriculum to foster an AI-enabled workforce.
Among other early adopters are the Center for Biomedical AI at the University Medical Center Hamburg-Eppendorf, Germany, which will leverage DGX A100 to advance clinical decision support and process optimization.
Thousands of previous-generation DGX systems are currently being used around the globe by a wide range of public and private organizations. Among these users are some of the world’s leading businesses, including automakers, health care providers, retailers, financial institutions, and logistics companies that are adopting AI across their industries.
Nvidia also revealed its next-generation DGX SuperPod, a cluster of 140 DGX A100 systems capable of achieving 700 petaflops of AI computing power. Combining 140 DGX A100 systems with Nvidia Mellanox HDR 200Gbps InfiniBand interconnects, the company built its own next-generation DGX SuperPod AI supercomputer for internal research in areas such as conversational AI, genomics, and autonomous driving.
It took only three weeks to build that SuperPod, Kharya said, and the cluster is one of the world’s fastest AI supercomputers — achieving a level of performance that previously required thousands of servers.
To help customers build their own A100-powered datacenters, Nvidia has released a new DGX SuperPod reference architecture. This gives customers a blueprint that follows the same design principles and best practices Nvidia used.
Nvidia also launched the Nvidia DGXpert program, which brings DGX customers together with the company’s AI experts, and the Nvidia DGX-ready software program, which helps customers take advantage of certified, enterprise-grade software for AI workflows.
The company said that each DGX A100 system has eight Nvidia A100 Tensor Core graphics processing units (GPUs), delivering 5 petaflops of AI power, with 320GB in total GPU memory and 12.4TB per second in bandwidth.
The systems also have six Nvidia NVSwitch interconnect fabrics with third-generation Nvidia NVLink technology for 4.8 terabytes per second of bi-directional bandwidth. And they have nine Nvidia Mellanox ConnectX-6 HDR 200Gb per second network interfaces, offering a total of 3.6 terabits per second of bi-directional bandwidth.
The chips are made by TSMC in a 7-nanometer process. Nvidia DGX A100 systems start at $199,000 and are shipping now through Nvidia Partner Network resellers worldwide.
Huang said the DGX A100 uses the HGX motherboard, which weighs about 50 pounds and is “the most complex motherboard in the world.” (This is the board he pulled out of his home oven in a teaser video). It has 30,000 components and a kilometer of wire traces.
As for a consumer graphics chip, Nvidia would configure an Ampere-based chip in a very different way. The A100 uses high-bandwidth memory for datacenter applications, but that wouldn’t be used in consumer graphics. The cores would also be heavily biased for graphics instead of the double-precision floating point calculations datacenters need, he said.
“We’ll bias it differently, but every single workload runs on every single GPU,” Huang said.
Nvidia CEO Jensen Huang has been holding geeks spellbound with the mysterious topic of his speech for May 14 at 6 a.m. Pacific time, when he will deliver the GTC event keynote address. Now we know from this sneak peek video that it’s the “world’s largest graphics card.”
Huang originally planned to make the speech on March 23 at the GTC event in San Jose, California. But the coronavirus pandemic put that speech on hold, and Nvidia moved the conference online as GTC Digital. And now Huang will catch up and give the keynote.
In this preview video, Huang says he’s been cooking something for a while in his kitchen. Then he pulls out a giant board with multiple graphics processing units (GPUs) on it.
Above: Jensen Huang of Nvidia holds the world’s largest graphics card.
Image Credit: Nvidia
Nvidia isn’t commenting on the announcement that goes with this video. But as you can tell from the grunt that Huang makes as he pulls it out of his oven, it’s a pretty hefty thing.
Enthusiast websites have speculated that the new graphics cards will feature a new GPU architecture, dubbed Ampere. These GPUs are expected to be part of the GeForce RTX 3080 and GeForce RTX 3070 cards coming later in the year, and they’re expected to be 75% faster than current-generation GPUs based on the Turing architecture, the websites speculated. One of the advantages is that they will be built on a 7-nanometer manufacturing process at Nvidia’s factory partner TSMC. These Ampere-based GPUs will have thousands of cores dedicated to non-graphics tasks (CUDA cores), AI work (Tensor Cores), and real-time ray tracing (RT cores).
The speech will air on YouTube on May 14 at 6 a.m. Pacific time. Nvidia has said that Huang will highlight the company’s latest innovations in AI, high-performance computing, data science, autonomous machines, healthcare, and graphics during the recorded keynote.
-- Nvidia reported first-quarter earnings on Thursday.
-- The stock is up over 50% on the year, not including Thursday’s after-hours move.
-- The company’s data center business reported over $1 billion in revenue for the first time.
Nvidia reported first-quarter earnings after the bell on Wednesday.
The stock was essentially unchanged in after-hours trading after losing a little more than 2% on the day.
Here’s how it did:
EPS: $1.80, adjusted
Revenue: $3.08 billion
Wall Street had anticipated adjusted earnings per share of $1.69 on revenue of $3 billion, according to Refinitiv consensus estimates. However, it’s difficult to compare reported earnings to analyst estimates as the coronavirus pandemic continues to affect global economies and makes earnings impact difficult to assess.
“COVID-19 created challenges in supply and demand. Early in the quarter, our partners’ supply chains were disrupted. Shelter-in-place resulted in closure of retail outlets and China iCafes, affecting sales of our gaming products,” the company said in a letter from the CFO. “However, work from home, learn at home, and gaming drove a surge in e-tail demand.”
Last year during its first fiscal quarter, Nvidia reported adjusted earnings per share of $0.88 on revenue of $2.22 billion.
Nvidia expects to report about $3.65 billion in revenue in its second fiscal quarter with gross margins around 58.6%.
Under Nvidia’s fiscal calendar, the quarter ended on April 26, over a month after widespread lockdowns in the United States and other countries started. The company said that its employees are working from home “very effectively.”
Nvidia is best known for making graphic processing units. Its gaming segment was up 25% year-over-year to $1.9 billion, the company said. But its fastest growing segment is related to its chips for data centers, which are used for computationally intensive tasks, such as machine learning. Nvidia said that segment grew 80% year-over-year, topping $1 billion for the first time with revenue of $1.14 billion. The company also said that it said it closed the acquisition of Mellanox in April, which will also help Nvidia’s data center business.
“Gaming and workstation growth are directly tied to competitive products and the need to work, govern and school from home,” Patrick Moorhead, president and principal at Moor Insights & Strategy, said.
Not including the after-hours move, Nvidia shares are up more than 50% for the year while the S&P 500 is has fallen more than 8%.
Nvidia said on Thursday that it is evaluating the “timing” of its share repurchase program and that it will continue to pay dividends.