Liquid Cooling and AI Data Center Daily | 2026-06-20
A daily English mirror of liquid cooling, AI data center efficiency, research papers, products, policy, financing, and supply-chain signals.
1. Executive brief
This English edition mirrors the same public-source dataset used by the Chinese daily report for 2026-06-20.
- Collection window: 2026-06-19 08:00 北京时间 - 2026-06-20 08:00 北京时间.
- Coverage snapshot: 8 industry items; 5 technology items; 8 paper or white-paper items; 8 video signals.
- Current hot topics: 电力并网与能源约束, 智算中心 CapEx/扩建, AI 芯片供给与交付, NVIDIA Blackwell/GB200/GB300.
- The heat score is 10/10 and should be read as a source-density signal, not as an investment indicator.
All claims should be verified against the original source links listed at the end of this report.
Academic and Industry Briefs
Papers, videos, industry updates, policy, financing, and projects are compressed into scannable tags with a title, summary, and source link.
Academic
Research papers, methods, research-oriented videos, and academic signals.
Modal Analysis of Spatial Load Correlation in AI Data Center-Dominated Po…
Hyperscale AI data centers induce spatially and temporally correlated load fluctuations that violate classical independence assumpt…
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Modal Analysis of Spatial Load Correlation in AI Data Center-Dominated Power Systems
- Published
- 2026-06-12
- Authors
- Chandan Chaudhary, Michael Murillo, Mohammed Ben-Idris, Joydeep Mitra, Dilip Pandit, Atri Bera
- Theme
- 算电协同
Abstract
Hyperscale AI data centers induce spatially and temporally correlated load fluctuations that violate classical independence assumptions and are not captured by time-averaged spectral methods. These correlations are episodic and non-stationary, requiring analysis that resolves transient structure. This paper applies Dynamic Mode Decomposition (DMD) to the temporal evolution of pairwise inter-bus correlation coefficients to form a low-dimensional state representation that enables modal analysis without a stationarity assumption. DMD eigenvalues encode the correlation regime: their location in the complex plane distinguishes sustained coherence, decaying transients, and intensifying events, while oscillation frequency maps to underlying physical coupling mechanisms. Using an IEEE 39-bus Real-Time Digital Simulator (RTDS) testbed with three converter-interfaced AI data center loads driven by synthetic workload profiles, global DMD provides a time-averaged modal baseline in a slow thermal band ($f \approx 0.005$\,Hz, $|μ| = 0.91$) captures 93.6\% of total correlation energy. A sliding-window DMD formulation identifies transient intensification events: 51 of 775 windows (6.6\%) satisfy the $|μ_k^{(n)}| > 1$ criterion, which aligns with stochastic workload coincidences. Cross-validation with RTDS voltage coherence confirms elevated coupling during these intervals. The proposed modal growth indicator provides an early-warning signal of correlation intensification prior to peak pairwise coherence.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，算力负载与电网侧资源的协同调度正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用仿真建模和情景分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断智算中心建设是否受电网容量、负载波动和调度机制约束。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Chandan Chaudhary, Michael Murillo, Mohammed Ben-Idris, 等. Modal Analysis of Spatial Load Correlation in AI Data Center-Dominated Power Systems[J/OL]. (2026-06-12)[2026-06-20]. http://arxiv.org/abs/2606.13847v1.
Hosting Capacity Assessment and Enhancement for Edge Data Centers in Acti…
With the increasing demand for edge computing and AI-driven workloads, integrating small and medium-sized edge data centers into di…
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Hosting Capacity Assessment and Enhancement for Edge Data Centers in Active Distribution Networks
- Published
- 2026-06-01
- Authors
- Linhan Fang, Xingpeng Li
- Theme
- AI 运维优化
Abstract
With the increasing demand for edge computing and AI-driven workloads, integrating small and medium-sized edge data centers into distribution networks has become increasingly important. This paper investigates the hosting capacity of distribution networks for data center integration and identifies the key physical mechanisms that limit the maximum allowable data center load. The baseline analysis shows that data center hosting capacity varies significantly across candidate buses due to network topology and electrical distance. Three dominant limiting mechanisms are identified: current-constrained locations, voltage-constrained locations, and mixed-constrained locations where both current loading and voltage deviation jointly affect hosting capacity. To increase the hosting capacity, this study evaluates multiple flexible resources, including battery energy storage systems (BESS), dispatchable distributed generators (DDG), and static synchronous compensators (STATCOM). Numerical results demonstrate that these resources provide complementary benefits through active power support, sustained local generation, and reactive power compensation, effectively expanding data center hosting capacity in distribution systems.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，AI 运维、负载预测和设施调优正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用仿真建模和情景分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断AI 工具是否能降低运维复杂度并提升可用性。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Linhan Fang, Xingpeng Li. Hosting Capacity Assessment and Enhancement for Edge Data Centers in Active Distribution Networks[J/OL]. (2026-06-01)[2026-06-20]. http://arxiv.org/abs/2606.01407v1.
Provisioning to Runtime Optimization of a 100 MW-Scale AI Cluster
The electric power supply for AI data centers is now the most significant bottleneck in the race toward Artificial General Intellig…
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Provisioning to Runtime Optimization of a 100 MW-Scale AI Cluster
- Published
- 2026-05-23
- Authors
- Ehsan K. Ardestani, Leonardo Piga, Jovan Stojkovic, Pavan Balaji, Mustafa Ozdal, Mikel Jimenez Fernandez, Mihaela Dimovska, Luka Tadic
- Theme
- 芯片与算力
Abstract
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.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，芯片、服务器和高密度算力部署正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用建模优化、调度分析或算法评估，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断芯片路线和服务器密度变化如何传导到机房设计。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Ehsan K. Ardestani, Leonardo Piga, Jovan Stojkovic, 等. Provisioning to Runtime Optimization of a 100 MW-Scale AI Cluster[J/OL]. (2026-05-23)[2026-06-20]. http://arxiv.org/abs/2605.24461v2.
Wafer-Level Integrated 1200 V SiC MOSFET Package with Room-Temperature Wa…
热管理与液冷方向论文；Semantic Scholar 未提供可展示摘要，建议打开原文核验方法和数据边界。
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Wafer-Level Integrated 1200 V SiC MOSFET Package with Room-Temperature Wafer Bonding and Embedded Microfluidic Cooling
- Published
- 2026-05-26
- Authors
- Jiajing Nie, Jiuyang Tang, Hao Guan, Xinyue Wang, Tao Jiang, Junran Zhang, Guoqi Zhang, Guangyin Lei
- Theme
- 热管理与液冷
Abstract
Semantic Scholar did not provide an abstract for display. Open the source paper for details.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，液冷、热管理和数据中心能效正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用文献摘要中的模型、实验或案例分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向冷却效率、能源利用或运维策略的改进方向。意义：对日报读者而言，它可用于判断液冷方案、热管理路线和高密度部署节奏。摘要缺失，建议优先打开原文查看方法、数据和边界条件。
Reference
Jiajing Nie, Jiuyang Tang, Hao Guan, 等. Wafer-Level Integrated 1200 V SiC MOSFET Package with Room-Temperature Wafer Bonding and Embedded Microfluidic Cooling[J/OL]. Electronic Components and Technology Conference. (2026-05-26)[2026-06-20]. https://www.semanticscholar.org/paper/11fa662b073d777b3f9125fd8ef8a3bb5cf601cc.
Power Grid Infrastructure for AI Data Centers
This article addresses recent advances in artificial intelligence, which have set off an astounding race among technology frontiers…
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Power Grid Infrastructure for AI Data Centers
- Published
- 2026-05-31
- Authors
- Amir Sajadi, Muhy Eddin Za'ter, Maria Vabson, Kyri Baker, Bri-Mathias Hodge
- Theme
- 算电协同
Abstract
This article addresses recent advances in artificial intelligence, which have set off an astounding race among technology frontiers to build large data centers. It provides insights into impacts of large data centers on the planning and operation of the power grid.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，算力负载与电网侧资源的协同调度正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用文献摘要中的模型、实验或案例分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向AI 负载波动对电网设备寿命和调频边界的影响。意义：对日报读者而言，它可用于判断智算中心建设是否受电网容量、负载波动和调度机制约束。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Amir Sajadi, Muhy Eddin Za'ter, Maria Vabson, 等. Power Grid Infrastructure for AI Data Centers[J/OL]. (2026-05-31)[2026-06-20]. http://arxiv.org/abs/2606.00941v1.
Space-CIM: Enabling Compute-In-Memory Accelerators for Thermally-Constrai…
The rapid growth in compute demand from artificial intelligence (AI) has driven a massive surge in data center construction, precip…
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Space-CIM: Enabling Compute-In-Memory Accelerators for Thermally-Constrained Space Platforms
- Published
- 2026-06-04
- Authors
- Sohan Salahuddin Mugdho, Md. Shahedul Hasan, Cheng Wang
- Theme
- 芯片与算力
Abstract
The rapid growth in compute demand from artificial intelligence (AI) has driven a massive surge in data center construction, precipitating an energy and sustainability crisis. Motivated by the abundant solar energy in outer space and the recent sharp reduction in space launch costs, orbital data centers are emerging as a potential pathway for the future scaling of AI compute infrastructure. While the cold background in vacuum seems appealing for cooling, computing systems operating in space without convection ultimately rely on radiative cooling, requiring large-area radiators. Such limitations in thermal management pose a significant challenge for deploying the standard liquid/air-cooled computers in space. In this work, we investigate the impact of the thermal constraints in space on both graphics processing units (GPUs) with high-bandwidth memory (HBM) and the emerging compute-in-memory (CIM) accelerators. We develop a radiator-in-the-loop co-design methodology that directly links the permitted system TOPS (terra-operations per second) with the practical radiator cooling capacity in space. Our thermal simulations reveal that the separately located GPU die and HBMs create severe thermal hotspots under limited radiator capacity, necessitating GPU thermal throttling. In contrast, CIM accelerators exhibit a much more uniform heat distribution and consistently outperform GPUs in TOPS/W across a wide range of radiator budgets. We systematically evaluated the performance of CIM and GPU across various AI workloads and demonstrated that CIM has a magnified advantage for deployment in space under realistic thermal constraints.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，芯片、服务器和高密度算力部署正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用综述归纳和指标比较，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断芯片路线和服务器密度变化如何传导到机房设计。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Sohan Salahuddin Mugdho, Md. Shahedul Hasan, Cheng Wang. Space-CIM: Enabling Compute-In-Memory Accelerators for Thermally-Constrained Space Platforms[J/OL]. (2026-06-04)[2026-06-20]. http://arxiv.org/abs/2606.05741v1.
Pushing the Frontiers for Floating Solar Photovoltaics -- The Case for So…
Floating solar photovoltaic (FSPV) systems provide a land-efficient pathway to expand clean electricity access in energy-poor regio…
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Pushing the Frontiers for Floating Solar Photovoltaics -- The Case for South America
- Published
- 2026-06-11
- Authors
- Soham Ghosh, Anik Goswami, Krishna Kumba
- Theme
- 算电协同
Abstract
Floating solar photovoltaic (FSPV) systems provide a land-efficient pathway to expand clean electricity access in energy-poor regions. South America has among the highest global FSPV potential (approx 38.26 TWh per million acres of water surface), yet deployment remains limited. This study presents a techno-socio-economic framework to assess FSPV for energy access, water security, and grid flexibility, with case studies in Nicaragua, Honduras, and Guyana. Estimated yields for 50 to 398 MW systems exceed 1,500 to 2,000 kWh per kW annually with capacity factors above 20 percent. At El Cajon, FSPV could significantly reduce emissions relative to fossil generation. Results show competitive costs with land-based PV when accounting for avoided land use, shared hydropower infrastructure, and water benefits. The framework also highlights co-location with hydropower and AI data centers, offering a scalable model for deployment in underserved regions.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，算力负载与电网侧资源的协同调度正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用框架构建和频域/系统级分析，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向AI 负载波动对电网设备寿命和调频边界的影响。意义：对日报读者而言，它可用于判断智算中心建设是否受电网容量、负载波动和调度机制约束。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Soham Ghosh, Anik Goswami, Krishna Kumba. Pushing the Frontiers for Floating Solar Photovoltaics -- The Case for South America[J/OL]. (2026-06-11)[2026-06-20]. http://arxiv.org/abs/2606.12798v1.
AI-on-Chip Systems: A Cross-Layer Review of Architectures, Interconnects,…
The rapid growth of artificial intelligence (AI) workloads is reshaping semiconductor design across architecture, interconnect, mem…
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AI-on-Chip Systems: A Cross-Layer Review of Architectures, Interconnects, Design Automation, and Embedded Intelligence
- Published
- 2026-06-15
- Authors
- Mohamed M. Morsy
- Theme
- 芯片与算力
Abstract
The rapid growth of artificial intelligence (AI) workloads is reshaping semiconductor design across architecture, interconnect, memory hierarchy, packaging, timing, and design automation. Rather than converging on a single hardware solution, the field is expanding into a heterogeneous ecosystem that includes data-center graphics processing units (GPUs), edge neural processing units (NPUs), and application-specific integrated circuits (ASICs), field-programmable gate array (FPGA)-based and hybrid AI system-on-chip (SoC) platforms, chiplet-enabled systems, and emerging beyond-conventional-silicon approaches such as photonic, neuromorphic, and analog in-memory processors. This paper presents a comprehensive review of AI-on-chip systems from a cross-layer perspective. It examines AI chip architectures and hardware platforms, network-on-chip (NoC) designs for AI communication patterns, and algorithm–hardware co-design methods for model acceleration, including compression, quantization, and sparsity-aware optimization. It also reviews clocking, synchronization, and clock-domain-crossing (CDC) challenges in large heterogeneous systems and chiplets, as well as manufacturing, advanced packaging, and reliability issues, including two-and-a-half-dimensional (2.5D) and three-dimensional (3D) integration, thermal and mechanical constraints, assembly quality, and long-term yield considerations. In parallel, the paper surveys the growing role of AI in chip design itself, covering machine-learning-assisted analysis, Bayesian and reinforcement-learning-based optimization, and the emerging use of large language models (LLMs) and AI agents for register-transfer level (RTL) generation, design-space exploration, and autonomous electronic design automation (EDA) workflows. Finally, it discusses beyond-silicon AI chip directions and the broader economic and industry context shaping cloud, on-premises, and edge deployment. By integrating these topics into a unified framework, this review highlights the key technological drivers, system-level tradeoffs, and future research directions that will define next-generation scalable, reliable, and energy-efficient AI-on-chip systems.
Chinese interpretation
背景：AI 数据中心负载、功率密度和能源约束同步上升，芯片、服务器和高密度算力部署正在成为智算中心设计的关键变量。问题：论文聚焦现有方案在效率、可靠性或工程协同上的瓶颈。方法：摘要显示作者采用综述归纳和指标比较，把运行负载、冷却/能源系统和基础设施约束放在同一分析框架中。结果：研究重点指向跨地域数据中心负载与电力资源之间的调度关系。意义：对日报读者而言，它可用于判断芯片路线和服务器密度变化如何传导到机房设计。仍需结合全文实验条件、样本范围和成本假设核验。
Reference
Mohamed M. Morsy. AI-on-Chip Systems: A Cross-Layer Review of Architectures, Interconnects, Design Automation, and Embedded Intelligence[J/OL]. Electronics. (2026-06-15)[2026-06-20]. https://www.semanticscholar.org/paper/6559f17a3e4aaa83cbf55ab2f8c0657056399288.
Are data centers in space feasible? Ariel Ekblaw weighs in
Washington Post Live · Query: AI datacenter power grid university lecture。Useful as technical or research context.
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US Forces Grids to Fix Data Center Power Crisis — Is AI Draining America'…
𝙀𝙈𝙈𝙔𝙎𝘾𝙊𝙋𝙀 𝙉𝙀𝙒𝙎 · Query: AI datacenter power grid university lecture。Useful as technical or research context.
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ASHRAE ITALY - LIQUID COOLING AND CHALLANGES IN IMPLEMENTATION
ASHRAE Italy · Query: data center thermal management seminar。Useful as technical or research context.
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电力并网与能源约束
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智算中心 CapEx/扩建
Same-source item from the Chinese report. Verify details against the original linked source: 智算中心 CapEx/扩建
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AI 芯片供给与交付
Same-source item from the Chinese report. Verify details against the original linked source: AI 芯片供给与交付
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Industry
Industry news, products, policy, financing, projects, and market-oriented videos.
智算中心/数据中心建设进展：Data Center Dynamics 发布相关报道（原文标题：Plans filed for three-buil…
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：Building the data center workfo…
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：DMG signs first prefab data cen…
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AI 算力基础设施动态：Data Center Dynamics 发布相关报道（原文标题：Amazon could sell Trainium A…
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：Hyperscale Data plans to deploy…
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AI 算力基础设施动态：Data Center Dynamics 发布相关报道，涉及 $5、10GW（原文标题：California startu…
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数据中心产业动态：Data Center Dynamics 发布相关报道（原文标题：AWS inks recycled water supply …
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数据中心产业动态：Data Center Dynamics 发布相关报道，涉及 12 w（原文标题：Equinix trials hydrogen…
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液冷与热管理进展：ServeTheHome 发布相关报道，涉及 2026 W（原文标题：81920 Cores Per Rack with AMD…
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液冷与热管理进展：Data Center Knowledge 发布相关报道（原文标题：Evaporative Cooling in Data Ce…
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AI 算力基础设施动态：Data Center Knowledge 发布相关报道（原文标题：HPE, Vultr Go All In on AI …
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电力与能源约束观察：Data Center Knowledge 发布相关报道（原文标题：From Grid Constraints to On-S…
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AI 算力基础设施动态：HPCwire 发布相关报道（原文标题：OpenMetal Expands v5 Hardware Catalog wit…
Same-source item from the Chinese report. Verify details against the original linked source: AI 算力基础设施动态：HPCwire 发布相关报道（原文标题：OpenMe…
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电力与能源约束观察：Data Center Knowledge 发布相关报道（原文标题：Data Center Automation: What’…
Same-source item from the Chinese report. Verify details against the original linked source: 电力与能源约束观察：Data Center Knowledge 发布相关报道…
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智算中心/数据中心建设进展：Data Center Dynamics 发布相关报道，涉及 $49（原文标题：Nuclear physics res…
Same-source item from the Chinese report. Verify details against the original linked source: 智算中心/数据中心建设进展：Data Center Dynamics 发布相…
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电力与能源约束观察：Data Center Dynamics 发布相关报道，涉及 $54（原文标题：Verse raises $54m in Se…
Same-source item from the Chinese report. Verify details against the original linked source: 电力与能源约束观察：Data Center Dynamics 发布相关报道，…
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OCP 2020 Virtual Summit: Managing Barbeques in Data Centers with Sustaina…
Open Compute Project · Query: OCP data center cooling workshop。Useful for product, market, or deployment context.
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OCP AI/ML Physical Infra Workshop 2 Workshop call (May 15, 2025)
Open Compute Project · Query: OCP data center cooling workshop。Useful for product, market, or deployment context.
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OCP Data Center Engineering Workshop - 3/10/15
Open Compute Project · Query: OCP data center cooling workshop。Useful for product, market, or deployment context.
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OCPREG19 - Building and Operating an OCP Data Center at Small Scale
Open Compute Project · Query: OCP data center cooling workshop。Useful for product, market, or deployment context.
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OCPUS18–Innovative Immersion Cooling Approach for Shrinking OCP Data Cent…
Open Compute Project · Query: OCP data center cooling workshop。Useful for product, market, or deployment context.
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产业热度指数 10/10
Same-source item from the Chinese report. Verify details against the original linked source: 产业热度指数 10/10
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NVIDIA Blackwell/GB200/GB300
Same-source item from the Chinese report. Verify details against the original linked source: NVIDIA Blackwell/GB200/GB300
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AI 芯片供给与交付
Same-source item from the Chinese report. Verify details against the original linked source: AI 芯片供给与交付
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智算中心 CapEx/扩建
Same-source item from the Chinese report. Verify details against the original linked source: 智算中心 CapEx/扩建
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4. Video signals
Are data centers in space feasible? Ariel Ekblaw weighs in
专家讲座 · Washington Post Live · Query: AI datacenter power grid university lecture
Open on YouTubeUS Forces Grids to Fix Data Center Power Crisis — Is AI Draining America's Power?
专家讲座 · 𝙀𝙈𝙈𝙔𝙎𝘾𝙊𝙋𝙀 𝙉𝙀𝙒𝙎 · Query: AI datacenter power grid university lecture
Open on YouTubeOCP 2020 Virtual Summit: Managing Barbeques in Data Centers with Sustainability; Adaptability
行业论坛 · Open Compute Project · Query: OCP data center cooling workshop
Open on YouTubeOCP AI/ML Physical Infra Workshop 2 Workshop call (May 15, 2025)
行业论坛 · Open Compute Project · Query: OCP data center cooling workshop
Open on YouTubeOCP Data Center Engineering Workshop - 3/10/15
行业论坛 · Open Compute Project · Query: OCP data center cooling workshop
Open on YouTubeOCPREG19 - Building and Operating an OCP Data Center at Small Scale
行业论坛 · Open Compute Project · Query: OCP data center cooling workshop
Open on YouTubeOCPUS18–Innovative Immersion Cooling Approach for Shrinking OCP Data Center Size, Complexity & Costs
行业论坛 · Open Compute Project · Query: OCP data center cooling workshop
Open on YouTubeASHRAE ITALY - LIQUID COOLING AND CHALLANGES IN IMPLEMENTATION
专家讲座 · ASHRAE Italy · Query: data center thermal management seminar
Open on YouTubeSources
Collection notes
- 论文池：已从本地论文池读取 22 条候选；池更新时间 2026-06-20 02:55。
- When optional automation services are unavailable, this page uses traceable public sources and conservative rule-based summaries only; unverifiable facts are not filled in.