Synopsys joins NUS tropical data centre cooling consortium

Synopsys has joined the Sustainable Tropical Data Centre Testbed Phase 2.0 consortium at the National University of Singapore, adding a semiconductor and engineering software company to a Singapore research effort focused on data centre cooling in tropical conditions.

Led by the National University of Singapore and hosted by its College of Design and Engineering, the consortium will combine engineering simulation, AI-assisted design and reduced-order modelling with physical validation in the testbed.

The partnership addresses a growing challenge as artificial intelligence and high-performance computing drive up power use and heat output in data centres. In tropical markets, high temperatures and humidity make conventional cooling systems less efficient and more energy-intensive.

According to details released by the organisations, cooling can account for up to 40% of a tropical data centre's total energy consumption. That gives operators in Southeast Asia a stronger incentive to test liquid cooling, digital twins and other methods that reduce energy use while maintaining performance.

Research focus

Initial research will focus on two-phase direct-to-chip cooling for AI accelerators and digital twins for predictive thermal management. The planned workflow uses high-fidelity simulation to study thermal and fluid behaviour before designs are tested in the consortium's physical environment.

Once validated, the simulation results can be used to build reduced-order models, lighter computational models that support digital twin deployment and operational decisions. The collaboration also plans to develop repeatable workflows, case studies and validation methods.

For Synopsys, the project extends its simulation and analysis work into a live research environment focused on data centre infrastructure. Under the collaboration, it will provide software access, technical expertise, training, project mentoring and learning resources.

Brandon Wang, Vice President of Strategic Management, Technology Strategy & New Horizons at Synopsys, said, "At Synopsys, we look beyond today's opportunities to the new horizons that can strengthen our technology long term. Through our Technology Intelligence Centre, our team connects emerging technology shifts with Synopsys capabilities and leading research ecosystems to turn promising ideas into strategic opportunities. Our collaboration with STDCT 2.0 reflects that commitment by bringing our silicon-to-systems engineering capabilities into a real-world environment for sustainable AI infrastructure."

The announcement also reflects Singapore's broader push to improve the efficiency of digital infrastructure as demand for compute capacity grows. The city-state has sought to balance data centre expansion with energy and land constraints, making cooling efficiency a key area of research and investment.

Testbed model

STDCT 2.0 brings together research institutions, data centre operators and technology providers. Its remit covers energy efficiency, water efficiency, green energy, AI and future data centres, and green computing.

The structure gives academic and industry partners a platform to test ideas under conditions that mirror tropical environments, rather than relying solely on laboratory simulations. That matters because humidity, temperature and denser AI hardware create a different set of constraints from those in cooler regions.

Padmesh Mandloi, Vice President of Applications Engineering for Synopsys Simulation and Analysis APAC at Synopsys, said, "Efficient AI infrastructure requires a clear understanding of interconnected multiscale and multiphysics behavior, from chips to data centers. By combining Ansys multiscale and multiphysics simulation, AI-assisted engineering and surrogate modeling with STDCT 2.0 test data, we can help researchers connect and exchange data across scales, validate designs, and develop scalable cooling and digital twin solutions."

The project highlights the growing overlap between chip design tools, system simulation and data centre operations. As compute clusters become more concentrated, cooling design is no longer just a facilities issue. It increasingly connects component design, rack architecture and site-level thermal management.

Professor Lee Poh Seng, Programme Director of the Sustainable Tropical Data Centre Testbed and Head of the Department of Mechanical Engineering at the College of Design and Engineering at NUS, said, "STDCT 2.0 provides a co-innovation platform to move promising technologies from simulation to validation and towards real-world deployment in tropical data centers. By combining Synopsys' multiphysics simulation, AI-assisted engineering and digital modelling capabilities with our physical testbed, we aim to develop validated, scalable cooling and digital twin solutions for increasingly dense, AI-ready infrastructure in Singapore and across the region."