The electric power supply for AI data centers is now the most significant bottleneck in the race toward Artificial General Intelligence, surpassing even the constraint of AI accelerator availability. To our knowledge, this paper is the first to describe the end-to-end power management process for a hyper-scale AI datacenter; from early power planning to accommodate next-generation accelerators 6--12 months before their general availability, to tuning power settings after large scale deployment, and finally to dynamic, runtime power management for evolving workloads. We present detailed power measurements for a 150 MW datacenter hosting a cluster of 83K GB200 GPUs. We share insights from building this state-of-the-art AI cluster. We hope this work encourages practitioners across the industry to share their own experiences as well.

翻译：人工智能数据中心的电力供应现已成为迈向通用人工智能（AGI）过程中最显著的瓶颈，其制约程度甚至超过了人工智能加速器的可用性限制。据我们所知，本文首次描述了超大规模AI数据中心端到端的电力管理流程：从下一代加速器普遍可用之前的6至12个月阶段，为容纳该类加速器而进行的早期电力规划，到大规模部署后的电源设置调优，再到针对动态演变工作负载进行的运行时电力管理。我们给出了一个容纳83K块GB200 GPU集群的150兆瓦数据中心的详细电力测量数据，并分享了建设这一先进AI集群的实践经验。希望本文能鼓励业界同行分享各自的相关经验。