I. High-Density Computing Power for Scientific Research
Meeting Multidisciplinary Computational Needs:
The system supports intensive computing tasks, including AI training, biological computation, and big data analytics, enabling high-speed data processing and secure storage for scientific research.
Scalable Architecture:
With a modular design, the infrastructure supports flexible expansion on demand, accommodating the dynamic growth of campus research activities and preventing resource waste.
II. Green and Energy-Efficient Data Center
- Optimized Cabinet Layout
Server cabinets are arranged in a front-to-front and back-to-back configuration, combined with enclosed cold aisle design to prevent air mixing, reducing condensation and energy loss.
- Energy Efficiency Control
Based on PUE (Power Usage Effectiveness) optimization principles, AI algorithms are used to predict load and dynamically adjust cooling strategies, significantly cutting energy consumption.
- Sustainability Leadership
In alignment with the “Twin Zones” low-carbon strategy, this project serves as a green and energy-efficient benchmark for university campuses.
III. Intelligent Operation & System Integration
- End-to-End Intelligent Monitoring
A digital twin platform provides real-time visibility into data center conditions, enabling early load prediction and optimal resource scheduling.
- Programmable Power System
The power infrastructure is programmable to precisely match the intermittent high-load characteristics of research equipment, ensuring stable power supply.
IV. Tailored for High-Standard Academic Environments
- Noise Reduction Design
Equipped with low-noise in-row air conditioners and vibration-damping structures, ensuring a quiet environment conducive to teaching and research.
- Balanced Transparency and Soundproofing
Cold aisle enclosures use tempered glass panels, combining effective sound insulation with visual transparency.
- Optimized Space Utilization
Custom 1200mm deep server cabinets accommodate high-performance heterogeneous devices, achieving a balance between space efficiency and computational capacity.
V. Seamless Engineering & Ecosystem Integration
- Disruption-Free Construction
Construction schedules are offset from academic terms, with BIM simulation and modular deployment used to minimize on-site modifications and risks.
- Industry-Academia-Research Collaboration
Working with the university to develop intelligent O&M algorithms, the data center also serves as a platform for teaching and hands-on training, promoting research translation and innovation.
Project Highlights
Focusing on research applications, this project integrates green design, intelligent operations, and modular architecture to build a secure, flexible, and expandable data center infrastructure. By fostering collaboration with academia and local tech enterprises, it contributes to a robust industry-academia-research ecosystem—supporting Shenzhen’s vision to become a globally recognized innovation-driven city.
