Baidu PaddlePaddle AI Data Center Project
Time of issue:2025-12-19
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PaddlePaddle is Baidu's artificial intelligence platform, built on more than 13 years of R&D and technological accumulation. As the first independently developed deep learning platform in China, it underpins Baidu's large‑scale AI applications, including the “ERNIE Bot” foundation model.
To support rapidly growing model training and inference workloads, Baidu needed an AI data center infrastructure that could deliver high rack density, stable cooling, and lower operating costs, while remaining scalable and easy to manage.
Needs and Challenges
As AI workloads and GPU clusters expanded, the existing data center environment faced several pain points:
Low cabinet utilization
Loose initial planning led to low cabinet deployment rates and under‑utilized white space, resulting in poor ROI per square meter.
High energy consumption
Electricity costs accounted for over 70% of PEX, putting continuous pressure on operating budgets and limiting further AI capacity expansion.
INVT Solution
To address these challenges, the customer deployed INVT’s integrated IT infrastructure solution:
INVT iTalent series integrated data center
Compact, modular layout to increase cabinet deployment rate per unit area by 30%
Optimized room design and micro‑environment control to support high‑density AI racks
Separation of cold and hot air flows to avoid mixing losses and improve cooling effectiveness
INVT VCR series air‑cooled in‑row precision air conditioners
20%–100% adjustable cooling capacity to match real‑time IT load and reduce energy waste
Equipped with EC fans, variable‑frequency outdoor units, and electronic expansion valves to improve the annual energy efficiency ratio (AEER) and achieve low PUE
High return‑air temperature design to further enhance chiller efficiency and overall system performance
This combination delivered a high‑density, energy‑efficient AI data center environment that could keep pace with PaddlePaddle’s evolving compute requirements.
Customer Benefits
Space efficiency and density
Rack power density increased to 20 kW per cabinet
Overall space utilization improved by 50%, enabling more AI compute capacity within the same footprint
Energy cost optimization
Electricity costs were reduced by 20%, significantly improving OPEX
The optimized power and cooling structure supports the sustainable development of an independently controllable AI infrastructure for Baidu and the PaddlePaddle ecosystem
By partnering with INVT, Baidu's PaddlePaddle AI data center achieved higher utilization, lower energy costs, and a more scalable foundation for future AI innovation.
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