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Posts Tagged 'Data Center Interconnects'

  • June 11, 2024

    How AI Will Drive Cloud Switch Innovation

    This article is part five in a series on talks delivered at Accelerated Infrastructure for the AI Era, a one-day symposium held by Marvell in April 2024. 

    AI has fundamentally changed the network switching landscape. AI requirements are driving foundational shifts in the industry roadmap, expanding the use cases for cloud switching semiconductors and creating opportunities to redefine the terrain.

    Here’s how AI will drive cloud switching innovation.

    A changing network requires a change in scale

    In a modern cloud data center, the compute servers are connected to themselves and the internet through a network of high-bandwidth switches. The approach is like that of the internet itself, allowing operators to build a network of any size while mixing and matching products from various vendors to create a network architecture specific to their needs.

    Such a high-bandwidth switching network is critical for AI applications, and a higher-performing network can lead to a more profitable deployment.

    However, expanding and extending the general-purpose cloud network to AI isn’t quite as simple as just adding more building blocks. In the world of general-purpose computing, a single workload or more can fit on a single server CPU. In contrast, AI’s large datasets don’t fit on a single processor, whether it’s a CPU, GPU or other accelerated compute device (XPU), making it necessary to distribute the workload across multiple processors. These accelerated processors must function as a single computing element. 

    AI calls for enhanced cloud switch architecture

    AI requires accelerated infrastructure to split workloads across many processors.

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  • June 06, 2024

    Silicon Photonics Comes of Age

    This article is part four in a series on talks delivered at Accelerated Infrastructure for the AI Era, a one-day symposium held by Marvell in April 2024. 

    Silicon photonics—the technology of manufacturing the hundreds of components required for optical communications with CMOS processes—has been employed to produce coherent optical modules for metro and long-distance communications for years. The increasing bandwidth demands brought on by AI are now opening the door for silicon photonics to come inside data centers to enhance their economics and capabilities.  

    What’s inside an optical module?

    As the previous posts in this series noted, critical semiconductors like digital signal processors (DSPs), transimpedance amplifiers (TIAs) and drivers for producing optical modules have steadily improved in terms of performance and efficiency with each new generation of chips thanks to Moore’s Law and other factors.

    The same is not true for optics. Modulators, multiplexers, lenses, waveguides and other devices for managing light impulses have historically been delivered as discrete components.

    “Optics pretty much uses piece parts,” said Loi Nguyen, executive vice president and general manager of cloud optics at Marvell. “It is very hard to scale.”

    Lasers have been particularly challenging with module developers forced to choose between a wide variety of technologies. Electro-absorption-modulated (EML) lasers are currently the only commercially viable option capable of meeting the 200G per second speed necessary to support AI models. Often used for longer links, EML is the laser of choice for 1.6T optical modules. Not only is fab capacity for EML lasers constrained, but they are also incredibly expensive. Together, these factors make it difficult to scale at the rate needed for AI.

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  • June 02, 2024

    A Deep Dive into the Copper and Optical Interconnects Weaving AI Clusters Together

    This article is part three in a series on talks delivered at Accelerated Infrastructure for the AI Era, a one-day symposium held by Marvell in April 2024.

    Twenty-five years ago, network bandwidth ran at 100 Mbps, and it was aspirational to think about moving to 1 Gbps over optical. Today, links are running at 1 Tbps over optical, or 10,000 times faster than cutting edge speeds two decades ago.

    Another interesting fact. “Every single large language model today runs on compute clusters that are enabled by Marvell’s connectivity silicon,” said Achyut Shah, senior vice president and general manager of Connectivity at Marvell.

    To keep ahead of what customers need, Marvell continually seeks to boost capacity, speed, and performance of the digital signal processors (DSPs), transimpedance amplifiers or TIAs, drivers, firmware and other components inside interconnects. It’s an interdisciplinary endeavor involving expertise in high frequency analog, mixed signal, digital, firmware, software and other technologies. The following is a map to the different components and challenges shaping the future of interconnects and how that future will shape AI.

    Inside the Data Center

    From a high level, optical interconnects perform the task their name implies: they deliver data from one place to another while keeping errors from creeping in during transmission. Another important task, however, is enabling data center operators to scale quickly and reliably.

    “When our customers deploy networks, they don’t start deploying hundreds or thousands at a time,” said Shah. “They have these massive data center clusters—tens of thousands, hundreds of thousands and millions of (computing) units—that all need to work and come up at the exact same time. These are at multiple locations, across different data centers. The DSP helps ensure that they don’t have to fine tune every link by hand.”

    Optical Interconnect Module

     

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  • October 20, 2021

    Low Power DSP-Based Transceivers for Data Center Optical Fiber Communications

    By Radha Nagarajan, SVP and CTO, Optical and Copper Connectivity Business Group

    As the volume of global data continues to grow exponentially, data center operators often confront a frustrating challenge: how to process a rising tsunami of terabytes within the limits of their facility’s electrical power supply – a constraint imposed by the physical capacity of the cables that bring electric power from the grid into their data center.

    Fortunately, recent innovations in optical transmission technology – specifically, in the design of optical transceivers – have yielded tremendous gains in energy efficiency, which frees up electric power for more valuable computational work.

    Recently, at the invitation of the Institute of Electrical and Electronics Engineers, my Marvell  colleagues Ilya Lyubomirsky, Oscar Agazzi and I published a paper detailing these technological breakthroughs, titled Low Power DSP-based Transceivers for Data Center Optical Fiber Communications.

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