Toward Next-Generation AI Data Centers: Power Delivery Architecture Shifts, Emerging Technologies, and Challenges
Sangwhee Lee, Rafal P. Wojda, Cheol-Hee Jo, Shuntaro Inoue, Pedro Ribeiro, Gui-Jia Su, Mostak Mohammad, Himel Barua, Nishanth Gadiyar, Praveen Kumar, Spencer Cochran, Subho Mukherjee, Whit Vinson, Vandana Rallabandi, Shajjad Chowdhury, Burak Ozpineci
- 发表年份
- 2026
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- 开放获取
摘要
The rapid growth of AI workloads is driving unprecedented increases in data center power demand, current transients, and thermal stress, exposing fundamental limitations in traditional 48 V rack architectures, low-voltage AC distribution, and line-frequency transformer interfaces. This paper reviews the three stages of architectural shifts required to support next-generation AI data centers and identifies three enabling technological building blocks: high-voltage conversion-ratio DC/DC converters, facility-level low-voltage DC distribution, and medium-voltage solid-state transformers. The advantages, technical challenges, and potential solutions associated with each building block are reviewed. Finally, future research directions and open challenges are discussed.
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