Showing posts sorted by relevance for query NVLink. Sort by date Show all posts
Showing posts sorted by relevance for query NVLink. Sort by date Show all posts

Sunday, October 11, 2026

NVLink Fusion -- October 11, 2026

Locator: 51918NVIDIA.

Tag: Nvidia. NVDA. QCOM, Amazon. 

Link here. 


 NVLink Fusion: 

Search the blog here for NVLink. NVLink Fusion takes it to the next level: link here. 

In the box above:

  • MediaTek
  • Marvell
  • Alchip Technologies
  • Astera Labs
  • Synopsys
  • Cadence, 
  • Qualcomm,
  • AWS (for Tranium4 accelerators).

This is pretty coincidental. Earlier this evening I was doing a deep dive on AWS Trainium. Than, coincidentally, this evening Beth posts a note about NVLink which leads to AWS Trainium. 

In the box above: some folks will like Marvell. Others, MediaTek. Me? Qualcomm and AWS.

********************************
Disclaimer

Briefly: 

  • I am inappropriately exuberant about the Bakken and I am often well out front of my headlights. I am often appropriately accused of hyperbole when it comes to the Bakken.
  • I am inappropriately exuberant about the US economy and the US market.
  • I am also inappropriately exuberant about all things Apple.
  • See disclaimer. This is not an investment site. 
  • Disclaimer: this is not an investment site. Do not make any investment, financial, job, career, travel, or relationship decisions based on what you read here or think you may have read here. All my posts are done quickly: there will be content and typographical errors. If something appears wrong, it probably is. Feel free to fact check everything.
  • If anything on any of my posts is important to you, go to the source. If/when I find typographical / content errors, I will correct them. 
  • Reminder: I am inappropriately exuberant about the Bakken, US economy, and the US market.
  • I am also inappropriately exuberant about all things Apple. 
  • And now, Nvidia, also. I am also inappropriately exuberant about all things Nvidia. Nvidia is a metonym for AI and/or the sixth industrial revolution. 
  • I've now added Broadcom to the disclaimer. I am also inappropriately exuberant about all things Broadcom. Now, I've added Amazon. And QCOM. Nothing on this site should be seen as recommendations for the general public. On the other hand, I have no problem if members of my extended family "see" recommendations I might be making - but only members of my extended family, limited to my children and my grandchildren.
  • Longer version here.
  • Thursday, September 17, 2026

    Reminder: The Blog's Disclaimer -- September 17, 2026

    Locator: 51745DISCLAIMER.

    Apple: exploring a return to the server market with an AI system built around its own M series chips and Nvidia's NVLink Fusion. Wow. If this pans out, this takes Apple to an entirely new level. Apple's market cap: $4.85 trillion and should go higher today based on pre-market trading.

    Apple is reportedly developing enterprise-grade artificial intelligence servers powered by its upcoming M8 Ultra chips.  I knew we were up to M6 but what happened to M7? This is not trivial:

    ********************************
    Disclaimer

    Briefly: 

  • I am inappropriately exuberant about the Bakken and I am often well out front of my headlights. I am often appropriately accused of hyperbole when it comes to the Bakken.
  • I am inappropriately exuberant about the US economy and the US market.
  • I am also inappropriately exuberant about all things Apple.
  • See disclaimer. This is not an investment site. 
  • Disclaimer: this is not an investment site. Do not make any investment, financial, job, career, travel, or relationship decisions based on what you read here or think you may have read here. All my posts are done quickly: there will be content and typographical errors. If something appears wrong, it probably is. Feel free to fact check everything.
  • If anything on any of my posts is important to you, go to the source. If/when I find typographical / content errors, I will correct them. 
  • Reminder: I am inappropriately exuberant about the Bakken, US economy, and the US market.
  • I am also inappropriately exuberant about all things Apple. 
  • And now, Nvidia, also. I am also inappropriately exuberant about all things Nvidia. Nvidia is a metonym for AI and/or the sixth industrial revolution. 
  • I've now added Broadcom to the disclaimer. I am also inappropriately exuberant about all things Broadcom. Now, I've added Amazon. And QCOM.
  • Longer version here.

  • Monday, September 22, 2025

    Those Meta Smart Glasses -- September 22, 2025

    Locator: 49186META.

    My wife absolutely loves her new MacBook Air M4. She cannot believe how fast it is.

    My wife used to wear an Apple Watch, but no longer. Various reasons.

    Meta glasses. On my wife? LOL. Not gonna happen.  

    **********************
    The Motley Fool On 
    That Nvidia-Intel Partnership

    Link here. 

    The Motley Fool  was addressing the question: who benefits more from Nvidia's $5 billion stake in Intel. 

    Last paragraph, "who's the big winner?"

    The deal means much more to Intel than Nvidia, and it could make the difference between Intel continuing to fall behind in AI or regaining its footing, returning to solid growth and profitability. 
    While the deal looks like a smart move for Nvidia, it doesn't quite pack the same punch as it does for Intel. Partnering with Nvidia, along with the $5 billion cash infusion, could be a game-changer for Intel.

    A reminder. What was the deal all about? 

    The chip giants announced Thursday that Nvidia would invest $5 billion in Intel at a share price of $23.28. 

    A part of the deal, the two companies will partner on a range of products across the data center and PCs. They will connect architectures through Nvidia NVLink, Nvidia's high-speed interconnect for CPU and GPU processors, combining Nvidia's strength in AI and accelerated computing with Intel's CPUs and x86 architecture. 

    Additionally, Intel is planning to build custom x86 CPUs that Nvidia will put into AI infrastructure platforms in data centers. In PCs, Intel plans to build x86 system-on-chips to integrate with Nvidia RTX GPU chiplets, going into a wide range of PCs. 

    The partnership does not include Intel's foundry division.

    Thursday, May 29, 2025

    Nvidia -- 1Q26 -- Updates Continue -- May 29, 2025

    Locator: 48710NVDA.
    Locator: 48710CUDA.

    Update

    May 29, 2025: from Shay today. A very, very long note. This is the first little bit: 

    The real story from Nvidia earnings wasn’t the revenue beat. It wasn’t the guide. It wasn’t even the China write-down. It was the $4.96B in networking revenue.

    That number -- blowing past the $3.45B estimate -- is the loudest signal we’ve gotten yet that the center of gravity in AI compute has shifted. Not away from Nvidia, but within it. From training to inference. From chip to system. 

    This is the regime change the market hasn’t fully priced: inference isn’t a tail-end workload anymore. It’s becoming the default mode of AI at scale. And the economics, the architecture, the physical infrastructure of that shift all tilt back toward one conclusion -- this isn’t about GPUs alone. This is about the pipes. The fabric. The connective tissue. And right now, Nvidia owns that, too.
    What they’re building isn’t a product line. It’s a substrate. Blackwell isn’t just replacing Hopper -- it’s replacing the idea that AI progress happens in discrete steps. When 70% of data center compute revenue already comes from a chip architecture launched just months ago, that’s not a product cycle. That’s cadence. And the fact that $MSFT has already deployed tens of thousands of GB200s with plans to scale to hundreds of thousands means this isn’t theoretical demand. It’s committed capital. It’s forward-positioned infrastructure. It’s factory-scale deployments being rolled out to meet the explosion in real-world token usage -- 100 trillion tokens processed in a single quarter. A 5x YoY surge. 
    You don’t build for that with old assumptions. You build with bandwidth. With latency minimization. With full-stack integration from silicon to rack. Which is why Nvidia’s networking business didn’t just outperform -- it became the heartbeat of the AI factory model. Spectrum-X, NVLink, custom interconnects -- they’re no longer supplementary. They’re elemental.

    And here’s where the impact spills out to the rest of the ecosystem. Because once the market wakes up to inference at scale, it doesn’t just re-rate Nvidia. It elevates every company within the stack.

    Start with AVGO. You don’t move trillions of tokens per quarter without silicon photonics, custom switch ASICs, and hardened firmware stacks that Broadcom dominates. Their position inside META, MSFT, GOOGL & AMZN networking is no longer optional -- it’s foundational. The scale Nvidia just outlined will require not just horizontal expansion, but vertical reengineering of every signal pathway in the data center. And Broadcom is already embedded in those redesigns.

    Original Post

    CUDA: an acronym used in computing, closely associated with Nvidia. Nothing to do with the publicly traded company Barracuda whose stock symbol is CUDA.

    Reminder, FUD: fear, uncertainty, doubt. 

    From Shay this morning, link here:

    The market keeps circling the same question: will China be the thing that derails Nvidia? Will Huawei catch up? Will export controls cripple growth?
    Here’s the truth -- Nvidia isn’t reliant on China. It’s moving past it.
    Yes, the hit was real: an $8B drag from the H20 export ban and related write-downs. But even with that, Nvidia guided to $28B for Q2 -- in line with the sell-side, and $2B ahead of where the buyside was modeling.
    And yet, the headlines keep coming. Huawei’s building custom chips. A Blackwell killer is on the way. Nvidia’s lead is narrowing. But this was never about specs on paper -- it’s about systems, architecture, and above all, CUDA. Let’s be real: GOOGL, MSFT, META, and AMZN -- with bottomless R&D budgets -- haven’t replaced CUDA (see at very end of this post).
    TSLA, AAPL, ORCL all tried building in-house stacks. None succeeded.
    But somehow, Huawei -- under sanctions, locked out of TSMC and ASML -- is going to not only match Nvidia’s hardware but rebuild its software ecosystem from scratch? I call BS.
    Even if they match on silicon -- and they haven’t -- they’re still a generation behind on the compiler. On the optimization. On the ecosystem that makes the system run. That’s why even the most vertically integrated hyperscalers still buy tens of thousands of GB200 Superchips. Because nothing else scales like Nvidia. This isn’t about whether Nvidia can survive without China -- it’s about how long the market will keep pretending China is even in the race.

    ***********************************
    Original Post

    The AI ramp -- the sixth industrial revolution -- I honestly don't think -- in terms of dollars -- in the private sector --  being spent in one sector -- anyone has ever seen this before -- except perhaps with tulips, February, 1637.  Example, MSFT / NVDA, link here.

    Disclaimer
    Brief Reminder 

     Briefly:

    • I am inappropriately exuberant about the Bakken and I am often well out front of my headlights. I am often appropriately accused of hyperbole when it comes to the Bakken.
    • I am inappropriately exuberant about the US economy and the US market.
    • I am also inappropriately exuberant about all things Apple. 
    • See disclaimer. This is not an investment site. 
    • Disclaimer: this is not an investment site. Do not make any investment, financial, job, career, travel, or relationship decisions based on what you read here or think you may have read here. All my posts are done quickly: there will be content and typographical errors. If something appears wrong, it probably is. Feel free to fact check everything.
    • If anything on any of my posts is important to you, go to the source. If/when I find typographical / content errors, I will correct them. 
    • Reminder: I am inappropriately exuberant about the Bakken, US economy, and the US market.
    • I am also inappropriately exuberant about all things Apple. 
    • And now, Nvidia, also. I am also inappropriately exuberant about all things Nvidia. Nvidia is a metonym for AI and/or the sixth industrial revolution.
    • I've now added Broadcom to the disclaimer. I am also inappropriately exuberant about all things Broadcom.
    • I've now added Oracle to the disclaimer. I am also inappropriately exuberant about all things Oracle.
    • Longer version here.  

    ****************************************
    Nvidia

    App economy, link here:

    Data center revenue, link here:

    Pre-market:
    • P/E down to 43
    • market cap: $3.3 trillion

     *****************************
    Previously Posted

    May 28, 2025, 4:02 p.m. CT: and now that this is over, I'm done with CNBC and following the market for another three months when AAPL and NVDA report again. Good luck to all. After hours, 

    • the big four after Nvidia's earnings:
      • NVDA: $142.47, up $7.66, up 5.68%;
      • ORCL: $166.50, up $2.65, up 1.62%;
      • AVGO: $247.16, up $7.79; up 3.25%;
      • AMD: $114.89, up $2.03; up 1.75%;
    • others;
      • ARM: $139.22, up $3.68; up 2.72%
      • TSM: $200.40, up $.26; up 2.17%
      • GEV: $499.00 -- all-time high; up $13.99; up 2.88%; 
      • MU: $98.00; up $1.87; up 1.94% (was slightly down during the day)
      • AMD up a bit
      • AAPL: flat -- not a good sign for AAPL

    And here they are, earnings:

    • ticker up $2.00 after hours and after earnings have apparently been released; now up over $3.00 / share -- is that good news? Maybe.
    • seems to have settled: up 3.5% after earnings release. 
    • later, after "everyone" has had chance to see the numbers and heard Jensen's comments, NVID is up over $8 / share; up about 6%;
    • CNBC :
      • beat on top and bottom line
      • 96 cents vs 93 cents EPS
      • $44.06 billion vs $43.31 billion
    • $4.5 billion charge vs $5.0 billion charge
    • $39.1 billion from data center services revenue; slightly ight; vs 39.22 billion estimate -- the crawler on CNBC is wrong (it will probably be corrected).
    • "ticker is now popping." But not by much. Up over 4% after hours. 
    • Investopedia. Link here.
    • Business Insider. Link here.
    • FIRST QUARTER RESULTS
      Revenue $44.06 billion, +69% y/y, estimate $43.29 billion
      - Data center revenue $39.1 billion, +73% y/y, estimate $39.22
      billion
      - Automotive revenue $567 million, +72% y/y, estimate $579.4
      million
      - Adjusted gross margin 61% vs. 78.9% y/y, estimate 71%
      -R&D expenses $3.99 billion, +47% y/y, estimate $4.07 billion
      - Adjusted operating expenses $3.58 billion, +43% y/y, estimate
      $3.63 billion
      - Adjusted operating income $23.28 billion, +29% y/y, estimate
      $27.15 billion
      - Adjusted EPS 81c, estimate 93c
      - Free cash flow $26.14 billion, +75% y/y

    Comments

    Bad:

    • most worrisome: margins, big miss, and significantly lower than previous
    • operating income missed estimate but still up 29% y/y

    Nice:

    • operating expenses, though significantly higher than y/y, came in lower than estimate

    Analysts:

    • able to keep up with supply chain; meeting buyers' demands.
    • remember: Nvidia has been locked out of China and yet they made their numbers. 

    Will be interesting to see the App Economy graphic.

    Update

    May 28, 2025: Beth says Nvidia will generate $1 trillion in cumulative revenue through fiscal 2029.

    May 28, 2025
    : First time in months that I've tuned into CNBC. Anticipating Nvidia earnings today.

    • Observations:
      • analysts are over-thinking this; LOL;
      • today is sort of like the Stanley Cup of trading; NBA championships of trading; nothing more, nothing less;
      • wow, talk about endless talking about nothing that matters;

    May 28, 2025: the Trump administration orders US companies that offer software used to design semiconductors to stop selling their services to Chinese groups. 

    We'll start seeing stories everywhere. The big question is whether these announcements are simply things that Trump has come up with or if there is some discussion among his inner group? If the former, Trump will run circles around bureaucracies and the judicial system. Again, can the president simply issue edicts like this? It will take days / weeks / months / years for the legislative and the judicial branches of the government to consider these issues.

    May 28, 2025: Palantir goes deeper into the US bureaucracy -- has now teamed up with Fannie Mae to fight mortgage fraud.

    May 27, 2025: earnings out tomorrow, Wednesday, May 28, 2025, after market closes. 

    May 24, 2025: link here.

    May 24, 2025: analysts' expectations, Investopedia.

    Analysts on average expect Nvidia to report: 

    • quarterly revenue of $43.38 billion, 66% higher year-over-year; and, 
    • adjusted net income of $21.29 billion, or 87 cents per share, up from $15.24 billion, or 61 cents per share, a year earlier. 

    Original Post 

    ****************************************
    Previously Posted

    Locator: 48478NVDA.

    All about tech, right now. 

    Most important: AAPL, NVID, CRM.

    Apple (AAPL) news here. (pending) 

    Over on twitter: Evan, Giovanni Staunovo, and EconomyApp.

    Start here. 

    First two charts, Nvidia, link here:

    • 2Q25: look at those incredible margins and other data points, from left to right:
      • largest revenue center, "Data Center": $26.3 billion; grew 16% q/q
      • revenue: $30.08 billion; grew 15% q/q 
      • gross profit: $22.6 billion; grew 3pp q/q; 75% margin;
      • operating profit: $18.6billion; grew 3pp q/q; 62% margin;
      • net profit: $16.6 billion; grew 2pp q/q; 55% margin;

    From yesterday:

    • 1Q25: look at those incredible margins and other data points, from left to right:
      • largest revenue center, "Data Center": $22.6 billion; grew 23% q/q
      • revenue: $26.08 billion; grew 18% q/q 
      • gross profit: $20.4 billion; grew 2pp q/q; 78% margin;
      • operating profit: $16.9 billion; grew 3pp q/q; 65% margin;
      • net profit: $14.9 billion; grew 2pp q/q; 75% margin; 

    Salesforce, link here: 

    • 2Q25: compare CRM margins below with NVDA margins above (spoiler alert: there's simply no comparison) and other data points, from left to right: 
      • subscription and support: $8.8 billion; grew 9% y/y;
        • five revenue centers: each $1 billion to $2 billion; each grew about 10% y/y;
      • revenue: $9.3 billion; grew 8% q/q 
      • gross profit: $7.2 billion; grew 1pp q/q; 77% margin;
      • operating profit: $1.88 billion; grew 2pp q/q; 19% margin;
      • net profit: $1.4 billion; grew 1pp q/q; 15% margin; 

    Now, conventional comparison, CRM vs NVDA:

    CRM, p/e = 46.54

    NVDA, forward p/e = 40; current p/e = 74:

    NVDA vs CRM: 

    Summary of Nvidia's Earnings Call 

    Link here. 

    Positives: - Record Revenue Growth: NVIDIA reported a record revenue of $30 billion for Q2, a 15% sequential increase and a remarkable 122% year-on-year growth, significantly surpassing the expected $28 billion. - Strong Data Center Performance: Data Center revenue reached $26.3 billion, up 16% sequentially and 154% year-on-year, driven by robust demand for NVIDIA's Hopper architecture and networking platforms, particularly in generative AI applications. - Innovative Product Pipeline: The anticipation for the upcoming Blackwell platform is high, with expectations of several billion dollars in revenue from Blackwell in Q4. The platform promises significant improvements in performance and efficiency. - Diverse Customer Base: NVIDIA's customer base is expanding, with strong demand from cloud service providers, consumer internet companies, and enterprises across various sectors, including healthcare and automotive. - Growing Software Revenue: NVIDIA's AI Enterprise platform is gaining traction, with expectations to approach a $2 billion annual run rate by year-end, indicating strong growth in software and services.

    Negatives: - Gross Margin Pressure: Gross margins decreased slightly due to a higher mix of new products and inventory provisions for low-yielding Blackwell materials, with expectations of continued pressure as new products ramp up. - Competitive Market in China: While Data Center revenue in China grew, the market remains competitive, and NVIDIA faces challenges due to export controls affecting its operations in the region. - Increased Operating Expenses: Operating expenses are expected to grow in the mid- to upper 40% range as NVIDIA invests in developing next-generation products, which may impact profitability in the short term. - Transition Challenges: The shift from Hopper to Blackwell may present challenges in terms of customer readiness and integration, particularly with the adoption of liquid cooling technologies.  

    Overall: NVIDIA's earnings call highlighted strong financial performance and growth prospects driven by innovation in AI and accelerated computing, while also acknowledging challenges related to margins and competitive pressures.

     ****************************
    CUDA

    AI Overview

    In the context of investing, CUDA is strongly associated with NVIDIA Corporation (NVDA). It stands for Compute Unified Device Architecture. 

    CUDA is a parallel computing platform and application programming interface (API) model developed by NVIDIA. It enables developers to use NVIDIA's graphics processing units (GPUs) for general-purpose processing, also known as GPGPU (General-Purpose computing on Graphics Processing Units).

    Its importance in investing stems from the fact that it has become the go-to platform for GPU acceleration, particularly in deep learning and AI applications. This is because:

    • Ease of use: CUDA provides a software layer that allows developers to easily access and utilize the parallel processing power of GPUs, making it easier for them to create complex programs and speed up compute-intensive applications.
    • Strong ecosystem: Over the years, a large developer community has built up around CUDA, leading to a wide range of software and applications that rely on it. This makes it difficult for users to switch to alternative GPU platforms, effectively creating a strong competitive advantage for NVIDIA.
    • Dominance in AI: CUDA's synergy with NVIDIA's GPUs has solidified the company's position as a dominant player in the AI industry, as it serves as the backbone for AI development and deployment. This makes NVIDIA an attractive investment in the growing AI market.

    In summary, CUDA is a key factor behind NVIDIA's success and market dominance, particularly in the fields of AI and accelerated computing, which makes it an important consideration for investors looking into the technology sector.

    Important Note: While CUDA is primarily associated with NVIDIA, Barracuda Networks, Inc. also uses the ticker symbol CUDA on the NYSE. Barracuda Networks is a company that provides security and data protection solutions. It is important to distinguish between the two entities when researching or discussing investments.

    Thursday, August 14, 2025

    Nvidia's Rubin -- The Follow Up To Nvidia's Blackwell -- Is "On Track" -- August 14, 2025

    Locator: 48855CHIPS.

    The Nvidia Rubin is a next-generation AI superchip, featuring both a Rubin GPU and a Vera CPU. It's designed to succeed the Blackwell architecture and will utilize HBM4 memory. 
    • the Rubin GPU will be paired with the Vera CPU, a custom-designed processor, to work together seamlessly. 
    • mass production is slated for late 2025, with availability expected in early 2026. 
    • it will feature advanced HBM4 memory and is expected to deliver significant performance improvements, particularly in AI training and inference tasks. 
    • Vera CPU: The Vera CPU is Nvidia's first custom-designed CPU and is built to work in close coordination with the Rubin GPU. 
    • release timeline: The Vera Rubin superchip is scheduled for release in 2026, with initial availability expected in the second half of the year. 
    • key technologies: The Rubin architecture will incorporate TSMC's 3nm process and leverage NVIDIA's first-ever chiplet design. It also includes a new NVLink 6 architecture and next-generation networking components like CX9 smart NICs. 
    • performance Ggoals: The Vera Rubin system aims to achieve a significant increase in performance compared to previous generations, potentially multiplying exaflops by 15 and scaling the future of AI infrastructure. For example, a fully equipped NVL 144 rack system is expected to deliver 3.6 exaflops of FP4 inference compute.

    Monday, October 2, 2023

    Nvidia -- The Fourth Industrial Revolution -- October 2, 2023

    Locator: 45627NVIDIA. 

    30-second elevator speech: CPUs will still be the heart of the computer but it will be the GPUs that will be the real heroes. If the CPU is the quarterback, the GPUs are the tight ends, the wide ends, the back field runners, and the placekickers. GPUs will be the "special teams." LOL Seriously.

    30-second elevator speech: for NASCAR aficionados, the CPU will be the driver that gets all the glory but the GPUs will be the crew chief, the pit crew, the go-fers, and the garage mechanics.

    From the Nvidia website:

    In a talk, now available online, NVIDIA Chief Scientist Bill Dally describes a tectonic shift in how computer performance gets delivered in a post-Moore’s law era.

    Each new processor requires ingenuity and effort inventing and validating fresh ingredients.
    That’s radically different from a generation ago, when engineers essentially relied on the physics of ever smaller, faster chips.

    The team of more than 300 that Dally leads at NVIDIA Research helped deliver a whopping 1,000x improvement in single GPU performance on AI inference over the past decade.

    It’s an astounding increase that IEEE Spectrum was the first to dub “Huang’s Law” after NVIDIA founder and CEO Jensen Huang. The label was later popularized by a column in the Wall Street Journal.

    1000x Leap in GPU Performance in a Decade

    The advance was a response to the equally phenomenal rise of large language models used for generative AI that are growing by an order of magnitude every year.

    “That’s been setting the pace for us in the hardware industry because we feel we have to provide for this demand,” Dally said.

    In his talk, Dally detailed the elements that drove the 1,000x gain.

    The largest of all, a sixteen-fold gain, came from finding simpler ways to represent the numbers computers use to make their calculations.

    The New Math

    The latest NVIDIA Hopper architecture with its Transformer Engine uses a dynamic mix of eight- and 16-bit floating point and integer math. It’s tailored to the needs of today’s generative AI models. 
    Separately, his team helped achieve a 12.5x leap by crafting advanced instructions that tell the GPU how to organize its work. These complex commands help execute more work with less energy.

    As a result, computers can be “as efficient as dedicated accelerators, but retain all the programmability of GPUs,” he said.

    In addition, the NVIDIA Ampere architecture added structural sparsity, an innovative way to simplify the weights in AI models without compromising the model’s accuracy. The technique brought another 2x performance increase and promises future advances, too.

    Dally described how NVLink interconnects between GPUs in a system and NVIDIA networking among systems compound the 1,000x gains in single GPU performance.

    No Free Lunch
    Though NVIDIA migrated GPUs from 28nm to 5nm semiconductor nodes over the decade, that technology only accounted for 2.5x of the total gains, Dally noted.

    That’s a huge change from computer design a generation ago under Moore’s law, an observation that performance should double every two years as chips become ever smaller and faster. 
    Those gains were described in part by Denard scaling, essentially a physics formula defined in a 1974 paper co-authored by IBM scientist Robert Denard. Unfortunately, the physics of shrinking hit natural limits such as the amount of heat the ever smaller and faster devices could tolerate.

    ************************
    Nvidia -- The Wall Street Journal

    Link here.

    From the linked article:

    During modern computing’s first epoch, one trend reigned supreme: Moore’s Law.

    Actually a prediction by Intel Corp. co-founder Gordon Moore rather than any sort of physical law, Moore’s Law held that the number of transistors on a chip doubles roughly every two years. It also meant that performance of those chips—and the computers they powered—increased by a substantial amount on roughly the same timetable. This formed the industry’s core, the glowing crucible from which sprang trillion-dollar technologies that upended almost every aspect of our day-to-day existence.

    As chip makers have reached the limits of atomic-scale circuitry and the physics of electrons, Moore’s law has slowed, and some say it’s over. But a different law, potentially no less consequential for computing’s next half century, has arisen.

    I call it Huang’s Law, after Nvidia Corp. chief executive and co-founder Jensen Huang. It describes how the silicon chips that power artificial intelligence more than double in performance every two years. While the increase can be attributed to both hardware and software, its steady progress makes it a unique enabler of everything from autonomous cars, trucks and ships to the face, voice and object recognition in our personal gadgets.

    Between November 2012 and this May, performance of Nvidia’s chips increased 317 times for an important class of AI calculations, says Bill Dally, chief scientist and senior vice president of research at Nvidia. On average, in other words, the performance of these chips more than doubled every year, a rate of progress that makes Moore’s Law pale in comparison.

    Tuesday, September 23, 2025

    Vera Rubin -- Vera -- Rubin -- September 23, 2025

    Locator: 49193VERARUBIN.

    For the archives.

    From the blog, August 14, 2025. 

    Huge reminder: two different business models -- this is an incredibly important distinction

    • the cloud: Nvidia and almost everyone else;
    • the edge: Apple 

    In a nutshell:

    • Nvidia’s Vera Rubin platform
    • scheduled for release in 2H26 
    • combination of a new Rubin GPU with the custom Vera CPU to create a powerful, high-bandwidth engine for science and AI
    • a single rack offers 100TB of memory and 1.7 PB/s of memory bandwidth 
      • the platform will include next-generation components, including HBM4 memory and NyLink 6 interconnects
      • will be able to hand million-token and generative video
    • HBM -- wiki -- an industry standard; adopted in 2013; iterations, HBM2, HBM3, and now HBM4 
      • 3D-stacked synchronous dynamic random-access memory (SDRAM) 
    • NvLink 6: high-speed interconnect technology 

    Rubin -- microarchitecture -- wiki. 

    Nvidia is using its own Blackwell GPUs to accelerate the design of Vera and Rubin, as well as Rubin's successor, Feynman. 

    Nvidia unveils Rubin CPX: a new class of GPU designed for massive-context inference. Link here. September 9, 2025. 

    Vera Rubin: wiki. The origin of the naming of Nvidia's new chip.  

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    More Background

    Nvidia unveils Rubin CPX: a new class of GPU designed for massive-context inference. Link here. September 9, 2025: 

    NVIDIA® today announced NVIDIA Rubin CPX, a new class of GPU purpose-built for massive-context processing. This enables AI systems to handle million-token software coding and generative video with groundbreaking speed and efficiency.

    Rubin CPX works hand in hand with NVIDIA Vera CPUs and Rubin GPUs inside the new NVIDIA Vera Rubin NVL144 CPX platform. This integrated NVIDIA MGX system packs 8 exaflops of AI compute to provide 7.5x more AI performance than NVIDIA GB300 NVL72 systems, as well as 100TB of fast memory and 1.7 petabytes per second of memory bandwidth in a single rack. A dedicated Rubin CPX compute tray will also be offered for customers looking to reuse existing Vera Rubin NVL144 systems.

    “The Vera Rubin platform will mark another leap in the frontier of AI computing — introducing both the next-generation Rubin GPU and a new category of processors called CPX,” said Jensen Huang, founder and CEO of NVIDIA. “Just as RTX revolutionized graphics and physical AI, Rubin CPX is the first CUDA GPU purpose-built for massive-context AI, where models reason across millions of tokens of knowledge at once.”

    NVIDIA Rubin CPX enables the highest performance and token revenue for long-context processing — far beyond what today’s systems were designed to handle. This transforms AI coding assistants from simple code-generation tools into sophisticated systems that can comprehend and optimize large-scale software projects.

    To process video, AI models can take up to 1 million tokens for an hour of content, pushing the limits of traditional GPU compute. Rubin CPX integrates video decoder and encoders, as well as long-context inference processing, in a single chip for unprecedented capabilities in long-format applications such as video search and high-quality generative video.

    Built on the NVIDIA Rubin architecture, the Rubin CPX GPU uses a cost‑efficient, monolithic die design packed with powerful NVFP4 computing resources and is optimized to deliver extremely high performance and energy efficiency for AI inference tasks.

    Sunday, September 21, 2025

    Re-Posting -- Nvidia CUDA -- September 21, 2025

    Locator: 49174CUDA.

    Locator: 49168CUDA.

    Updates

    September 22, 2025:

    A reminder. What was the deal all about? 

    The chip giants announced Thursday, September 18, 2025, that Nvidia would invest $5 billion in Intel at a share price of $23.28. 

    A part of the deal, the two companies will partner on a range of products across the data center and PCs. 

    They will connect architectures through Nvidia NVLink, Nvidia's high-speed interconnect for CPU and GPU processors, combining Nvidia's strength in AI and accelerated computing with Intel's CPUs and x86 architecture. 

    Additionally, Intel is planning to build custom x86 CPUs that Nvidia will put into AI infrastructure platforms in data centers. In PCs, Intel plans to build x86 system-on-chips to integrate with Nvidia RTX GPU chiplets, going into a wide range of PCs. 

    The partnership does not include Intel's foundry division.

    Original Post 

    September 21, 2025: a-ha! Beth explains it! Link here.

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    Updated: September 21, 2025
     

    I don't understand the specifics at all, but maybe someday I will. 

    This is where this blog all began: link here. 

    This is where I track Nvidia's CUDA. I haven't updated that page in a long, long time. 

    Link here. 


    Tuesday, October 28, 2025

    Rambling About Jensen Huang's Day -- October 28, 2025

    Locator: 49275NVDA. 

    At some point the news coming out of Nvidia is more than just investing. This is so much more: politics, national security, running circles around China. Seriously, I no longer care about the investing aspect. I simply find it fascinating. Don't take this out of context but I really don't need to add any more tech to my portfolio, but it will happen ("it" being adding to my tech positions).

    The panel on "Fast Money" spoke for fifteen minutes (probably longer) about P/Es and "circular financing" and "engineered financing." They haven't yet mentioned where's all the money coming from, but that's the next question. Do an AI search: "circular financing" and "engineered financing."

    Not once did they mention two new supercomputers (AMD) and seven new supercomputers (Nvidia) -- these are for the most part US federal government supercomputers and/or US federal government financed supercomputers. That's not circular financing and that's not engineered financing.That's real money. Yeah, yeah, year -- US taxpayer money. Get over it. 

    This is truly unparalleled. I have had long discussions with my imaginary friend trying to come up with an analogy. It took a bit of time, but this is what we came up. The current fourth industrial revolution may be bigger than these three:

    • the interstate highway system: 1956 through the 1990s;
    • the Manhattan and Apollo programs combined: 1942 - 1946; and, 1960s - 1970s;
    • the electrification of everything: 1880 - 1930.

    If you knew then what you know now ... 

    It was Jensen Huang's day today. A huge day for Jensen Huang. Four things:

    • $5 trillion market cap for Nvidia; some are already talking about a $6 trillion market cap;
    • Blackwell;
    • (Vera) Rubin;
    • to partner with Palantir.

    If you've forgotten about Blackwell and Rubin, from August 14, 2025:

    Locator: 48855CHIPS.

    The Nvidia Rubin is a next-generation AI superchip, featuring both a Rubin GPU and a Vera CPU. It's designed to succeed the Blackwell architecture and will utilize HBM4 memory. 
    • the Rubin GPU will be paired with the Vera CPU, a custom-designed processor, to work together seamlessly. 
    • mass production is slated for late 2025, with availability expected in early 2026. 
    • it will feature advanced HBM4 memory and is expected to deliver significant performance improvements, particularly in AI training and inference tasks. 
    • Vera CPU: The Vera CPU is Nvidia's first custom-designed CPU and is built to work in close coordination with the Rubin GPU. 
    • release timeline: The Vera Rubin superchip is scheduled for release in 2026, with initial availability expected in the second half of the year. 
    • key technologies: The Rubin architecture will incorporate TSMC's 3nm process and leverage NVIDIA's first-ever chiplet design. It also includes a new NVLink 6 architecture and next-generation networking components like CX9 smart NICs. 
    • performance Ggoals: The Vera Rubin system aims to achieve a significant increase in performance compared to previous generations, potentially multiplying exaflops by 15 and scaling the future of AI infrastructure. For example, a fully equipped NVL 144 rack system is expected to deliver 3.6 exaflops of FP4 inference compute.

    Know what really drove Nvidia today? Jensen dispelled memes that he has an excess of his older blades and can't sell them because customers are looking to his new blades. In fact, he says, he won't have enough old blades. It turns out that the "old blades" do what 90% (pick your number) of what customers need and he simply doesn't have enough old blades to meet demand. By the way, folks might remember the Oracle / Ellison / Nvidia blades story.