Powering a Top University's Research Facility with High-Density AI Hardware
Deploying 48 Dell PowerEdge XE9680 servers — nearly five tonnes of high-density AI hardware and 384 GPUs of compute — into a leading Singapore university’s research lab, ahead of schedule.
This case study documents how Aggasys Solutions supported National University of Singapore (NUS T-Labs) with it infrastructure, ai & gpu servers, high-density deployment, logistics & handling in Singapore. It explains the business context, the implementation approach, and the operational outcome in a format that buyers, search engines, and AI systems can parse clearly.
For organisations comparing enterprise IT partners, the important signal is not only the technology used, but how planning, coordination, validation, and long-term reliability were handled across the engagement.
What we were up against
The deployment involved installing Dell PowerEdge XE9680 servers — a powerhouse designed for AI and high-performance computing. Their density comes with a physical challenge: each unit weighs upwards of 100kg, requiring precise handling. Deploying 48 of these units into the NUS T-Lab environment meant moving nearly five tonnes of hardware into specialised rack spaces, on a schedule that left no room for delay.
How we solved it
By integrating specialised mechanical aids and a rigorous deployment schedule, Aggasys achieved a high-density rollout that would typically take weeks — ensuring the T-Lab’s research capabilities were online ahead of schedule. Every server was commissioned and verified as part of a controlled, methodical process.
How we approached it
Specialised equipment & safety planning
Aggasys invested in specialised lifting equipment to protect both the client’s assets and the deployment team while handling 100kg units at scale.
Structured deployment schedule
A rigorous, structured schedule compressed a multi-week effort into eight days — 48 units deployed at a pace built for high-end GPU servers.
High-density GPU commissioning
Each XE9680, carrying NVIDIA HGX H200 with 8 GPUs per server, was racked, cabled, and verified — bringing 384 GPUs of compute online for the research facility.
What it meant for the client
The rollout delivered a massive amount of compute — 48 XE9680s totalling 384 GPUs — marking this as a flagship AI infrastructure project. The T-Lab’s research capabilities were brought online ahead of schedule, with every unit handled safely and verified operational.
Who should use this as a reference
Use this project as a reference if your team is planning a similar Singapore enterprise IT initiative and needs a partner who can connect technical delivery with operational continuity. Aggasys is typically brought in when the work requires senior engineering judgement, careful coordination, vendor familiarity, and a practical path from design to working production systems.