分析500台AI超算趋势，揭示算力每9个月翻倍的惊人进展。
Trends in AI Supercomputers
- 构建2019-2025年500台AI超算数据集，追踪性能、功耗与成本变化。
- 算力每9个月翻倍，2025年顶级系统用20万芯片，耗电300MW，成本70亿美元。
- 企业主导算力增长，美国占全球75%性能，适合关注AI基础设施的决策者。
前沿人工智能发展依赖强大的AI超算，但相关系统分析仍有限。本文构建了2019至2025年间500台AI超算的数据集，分析其性能、功耗、硬件成本、所有权及全球分布趋势。研究发现，AI超算的计算性能每9个月翻倍，硬件采购成本和功耗均每年翻倍。截至2025年3月，领先系统xAI的Colossus使用20万块AI芯片，硬件成本达70亿美元，需300兆瓦电力，相当于25万户家庭用电量。随着AI超算从科研工具转向工业设备，企业占据的总算力份额迅速上升，而政府与学术机构占比下降。全球范围内，美国占总量约75%，中国居第二位，占比15%。若趋势持续，2030年最先进系统将实现2×10²² 16位浮点运算/秒，使用200万块AI芯片，硬件成本达2000亿美元，耗电9吉瓦。本分析为政策制定者评估资源需求、所有权结构与国家竞争力提供了关键洞见。
原文摘要 · Abstract (English)
Frontier AI development relies on powerful AI supercomputers, yet analysis of these systems is limited. We create a dataset of 500 AI supercomputers from 2019 to 2025 and analyze key trends in performance, power needs, hardware cost, ownership, and global distribution. We find that the computational performance of AI supercomputers has doubled every nine months, while hardware acquisition cost and power needs both doubled every year. The leading system in March 2025, xAI's Colossus, used 200,000 AI chips, had a hardware cost of \$7B, and required 300 MW of power, as much as 250,000 households. As AI supercomputers evolved from tools for science to industrial machines, companies rapidly expanded their share of total AI supercomputer performance, while the share of governments and academia diminished. Globally, the United States accounts for about 75% of total performance in our dataset, with China in second place at 15%. If the observed trends continue, the leading AI supercomputer in 2030 will achieve $2\times10^{22}$ 16-bit FLOP/s, use two million AI chips, have a hardware cost of \$200 billion, and require 9 GW of power. Our analysis provides visibility into the AI supercomputer landscape, allowing policymakers to assess key AI trends like resource needs, ownership, and national competitiveness.
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