Synopsys Inc. has joined the National University of Singapore’s (NUS) Sustainable Tropical Data Center Testbed Phase 2.0 (STDCT 2.0), a consortium developing energy-efficient data center technologies for tropical operating conditions. Led by NUS and hosted by its College of Design and Engineering (CDE), the initiative will combine Synopsys’ engineering simulation and digital modeling capabilities with NUS research and a physical testbed for evaluating data center technologies. High ambient temperatures and humidity in tropical climates increase cooling requirements. Cooling can account for up to 40% of a tropical data center’s total energy consumption. The growth of AI and high-performance computing is adding to the challenge as higher rack densities increase power demand and thermal loads. Synopsys and NUS CDE plan to integrate physics-based simulation, AI-assisted engineering and reduced-order modeling (ROM) with measurements from the testbed. Research areas include liquid cooling, computational fluid dynamics (CFD), multiphysics simulation and digital twins. “At Synopsys, we look beyond today’s opportunities to the new horizons that can strengthen our technology long term. Through our Technology Intelligence Center, 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,” said Brandon Wang, vice president of Technology Strategy & New Horizons at Synopsys. Initial research concepts include two-phase direct-to-chip cooling for high-heat-flux AI accelerators and uncertainty-aware reduced-order digital twins for predictive thermal management of liquid-cooled AI systems. The planned workflow will use high-fidelity simulations to assess thermal and fluid behavior, with results validated through physical experiments at the testbed. The validated data will support ROM development for digital twin integration, system optimization and operational decision-making. The partners also intend to develop reusable engineering workflows, validation methods and case studies, culminating in a demonstration linking design, simulation, ROM generation, digital twin integration and physical testing. “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,” said Padmesh Mandloi, vice president of Applications Engineering for Synopsys Simulation and Analysis APAC. Synopsys will provide software access, technical expertise, training, project mentoring and learning resources within the scope of the collaboration. STDCT 2.0 also brings together research institutions, data center operators and technology providers to address energy and water efficiency, green energy and future data center infrastructure. “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,” said Professor Lee Poh Seng, program director of the Sustainable Tropical Data Center Testbed and head of NUS CDE’s Department of Mechanical Engineering. The post Synopsys Joins NUS Testbed for Tropical Data Center Cooling Research appeared first on EE Times Asia .