He added, “GaN is relatively new technology, so expanding into these high-reliability areas has taken time.” Power Supplies: Translating Electricity from the Grid GaN is the gold standard for consumer fast-chargers and power adapters, but the challenge is proving that it can handle even higher power levels (thousands of watts at a time) as safely and robustly as silicon MOSFETs, said Oliver. While silicon still dominates, many of the movers and shakers in the world of power semiconductors, such as Infineon and TI, are also pushing for power switching devices based on GaN as an alternative. It’s placing everything possible into a single GaN power IC, including control, gate-drive, sensing, and protection features that lend themselves to the harsh realities of these applications. He contends that the silicon MOSFETs widely used today to convert and regulate the power entering each rack are reaching the end of their rope.įor its part, Navitas rolled out a new generation of gallium-nitride (GaN)-based power ICs, called GaNSafe, that “break through the glass ceiling” into high power levels reaching 22 kW in data centers, solar, and other renewable-energy storage, and even electric-vehicle (EV) subsystems. What must change to deliver power safely and reliably to these densely packed server racks? What about limiting and removing the heat generated in the process? For Stephen Oliver, VP of marketing and sales at Navitas Semiconductor, the solution starts in the power electronics. As rack power demands for data centers rise by up to 3X, delivering more power in a smaller space is vital. This is driving up power-per-rack specifications up to 90 kW, which conflicts with what most data centers can manage at 15 to 30 kW per rack. New power-hungry AI accelerators such as NVIDIA’s H100 GPUs have a thermal design power (TDP) of 700 W, while the most advanced CPUs and purpose-built AI chips are close behind. This article is part of the TechXchange: Gallium Nitride (GaN).Īs AI chips grow larger to handle the rapid development and deployment of large language models (LLMs) such as OpenAI’s ChatGPT, the amount of power that they require is rapidly ramping up, too.
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