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Archive for the 'AI' Category

  • November 12, 2024

    2006: The Twelve Months That Changed the Chip Industry

    By Michael Kanellos, Head of Influencer Relations, Marvell

    The semiconductor market is vastly different than it was a few years ago. Cloud service providers want custom silicon and collaborating with partners on designs. Chiplets and 3D devices, long discussed in the future tense, are a growing sector of the market. Moore’s Law? It’s still alive, but manufacturers and designers are following it by different means than simply shrinking transistors.

    And by sheer coincidence, many of the forces propelling these changes happened in the same year: 2006.

    The Magic of Scaling Slows.

    While Moore’s Law has slowed, it is still alive; semiconductor companies continue to be able to shrink the size of transistors at a somewhat predictable cadence.

    The benefits, however, changed. With so-called “Dennard Scaling,” chip designers could increase clock speed, reduce power—or both—with transistor shrinks. In practical terms, it meant that PC makers, phone designers and software developers could plan on a steady stream of hardware advances.

    Dennard Scaling effectively stopped in 20061. New technologies for keeping the hamster wheel spinning needed to be found, and fast. 

    Multi-Chip Module (MCM)

  • October 29, 2024

    Nine Things to Remember About the Future of Copper in Computing

    By Michael Kanellos, Head of Influencer Relations, Marvell and Vienna Alexander, Marketing Content Intern, Marvell

    Is copper dead?

    Not by a long shot. Copper technology, however, will undergo a dramatic transformation over the next several years. Here’s a guide.

    1. Copper is the Goldilocks Metal

    Copper has been a staple ingredient for interconnects since the days of Colossus and ENIAC. It is a superior conductor, costs far less than gold or silver and offers relatively low resistance. Copper also replaced aluminum for connecting transistors inside of chips in the late 90s because its 40% lower resistance improved performance by 15%1.

    Copper is also simple, reliable and hearty. Interconnects are essentially wires. By contrast, optical interconnects require a host of components such as optical DSPs, transimpedance amplifiers and lasers.

    “The first rule in optical technology is ‘Whatever you can do in copper, do in copper,’” says Dr. Loi Nguyen, EVP of optical technology at Marvell.

    2. But It’s Still a Metal

    Nonetheless, electrical resistance exists. As bandwidth and network speeds increase, so do heat and power consumption. Additionally, increasing bandwidth reduces the reach, so doubling the data rate reduces distance by roughly 30–50%  (see below).

    As a result, optical technologies have replaced copper in interconnects five meters or longer in data centers and telecommunication networks. 

    What are copper interconnects used

    Source: Marvell

  • September 25, 2024

    Marvell COLORZ 800 Named Most Innovative Product at ECOC 2024

    By Michael Kanellos, Head of Influencer Relations, Marvell

    With AI computing and cloud data centers requiring unprecedented levels of performance and power, Marvell is leading the way with transformative optical interconnect solutions for accelerated infrastructure to meet the rising demand for network bandwidth.

    At the ECOC 2024 Exhibition Industry Awards event, Marvell received the Most Innovative Pluggable Transceiver/Co-Packaged Module Award for the マーベル® COLORZ® 800 family. Launched in 2020 for ECOC’s 25th anniversary, the ECOC Exhibition Industry Awards spotlight innovation in optical communications, transport, and photonic technologies. This recognition highlights the company’s innovations in ZR/ZR+ technology for accelerated infrastructure and demonstrates its critical role in driving cloud and AI workloads.

    Marvell COLORZ 800 Named Most Innovative Product at ECOC 2024

  • September 22, 2024

    Five Things to Know About the Future of Long Distance Optics

    By Michael Kanellos, Head of Influencer Relations, Marvell

    Coherent optical digital signal processors (DSPs) are the long-haul truckers of the communications world. The chips are essential ingredients in the 600+ subsea Internet cables that crisscross the oceans (see map here) and the extended geographic links weaving together telecommunications networks and clouds.

    One of the most critical trends for long-distancer communications has been the shift from large, rack-scale transport equipment boxes running on embedded DSPs often from the same vendor to pluggable modules based on standardized form factors running DSPs from silicon suppliers tuned to the power limits of modules.

    With the advent of 800G ZR/ZR+ modules, the market arrives at another turning point. Here’s what you need to know. 


    It’s the Magic of Modularity

    PCs, smartphones, solar panels and other technologies that experienced rapid adoption had one thing in common: general agreement on the key ingredients. By building products around select components, accepted standards and modular form factors, an ecosystem of suppliers sprouted. And for customers that meant fewer shortages, lower prices and accelerated innovation.

    The same holds true of pluggable coherent modules. 100 Gbps coherent modules based on the ZR specification debuted in 2017. The modules could deliver data approximately 80 kilometers and consumed approximately 4.5 watts per 100G of data delivered. Microsoft became an early adopter and used the modules to build a mesh of metro data centers1.

    Flash forward to 2020. Power per 100G dropped to 4W and distance exploded: 120k connections became possible with modules based on the ZR standard and 400k with the ZR+ standard. (An organization called OIF maintains the ZR standard. ZR+ is controlled by OpenROADM. Module makers often make both varieties. The main difference between the two is the amplifier: the DSPs, number of channels and form factors are the same.) ®

    The market responded. 400ZR/ZR+ became adopted more rapidly than any other technology in optical history, according to Cignal AI principal analyst Scott Wilkinson.

    “It opened the floodgates to what you could do with coherent technology if you put it in the right form factor,” he said during a recent webinar.

  • June 18, 2024

    Custom Compute in the AI Era

    This article is the final installment in a series of talks delivered Accelerated Infrastructure for the AI Era, a one-day symposium held by Marvell in April 2024. 

    AI demands are pushing the limits of semiconductor technology, and hyperscale operators are at the forefront of adoption—they develop and deploy leading-edge technology that increases compute capacity. These large operators seek to optimize performance while simultaneously lowering total cost of ownership (TCO). With billions of dollars on the line, many have turned to custom silicon to meet their TCO and compute performance objectives.

    But building a custom compute solution is no small matter. Doing so requires a large IP portfolio, significant R&D scale and decades of experience to create the mix of ingredients that make up custom AI silicon. Today, Marvell is partnering with hyperscale operators to deliver custom compute silicon that’s enabling their AI growth trajectories.

    Why are hyperscale operators turning to custom compute?

    Hyperscale operators have always been focused on maximizing both performance and efficiency, but new demands from AI applications have amplified the pressure. According to Raghib Hussain, president of products and technologies at Marvell, “Every hyperscaler is focused on optimizing every aspect of their platform because the order of magnitude of impact is much, much higher than before. They are not only achieving the highest performance, but also saving billions of dollars.”

    With multiple business models in the cloud, including internal apps, infrastructure-as-a-service (IaaS), and software-as-a-service (SaaS)—the latter of which is the fastest-growing market thanks to generative AI—hyperscale operators are constantly seeking ways to improve their total cost of ownership. Custom compute allows them to do just that. Operators are first adopting custom compute platforms for their mass-scale internal applications, such as search and their own SaaS applications. Next up for greater custom adoption will be third-party SaaS and IaaS, where the operator offers their own custom compute as an alternative to merchant options.

    Progression of custom silicon adoption in hyperscale data centers.

    Progression of custom silicon adoption in hyperscale data centers.

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