Synopsys, Inc., a leader in engineering solutions, has announced its participation in the Sustainable Tropical Data Centre Testbed Phase 2.0 (STDCT 2.0) Consortium, led by the National University of Singapore (NUS). This collaboration seeks to address the cooling challenges faced by data centres in tropical climates, where high temperatures and humidity levels significantly impact energy efficiency.
Data centres in tropical regions often experience ambient temperatures of 24-32°C and humidity levels of 70-80%, leading to increased energy consumption for cooling—up to 40% of total energy use. The partnership between Synopsys and NUS aims to develop sustainable, AI-ready data centre technologies by integrating engineering simulation, AI-assisted design, and reduced-order modelling with physical testbed validation.
Brandon Wang, Vice President of Technology Strategy & New Horizons at Synopsys, stated, “Our collaboration with STDCT 2.0 reflects our commitment by bringing our silicon-to-systems engineering capabilities into a real-world environment for sustainable AI infrastructure.”
The collaboration will focus on advanced liquid cooling, computational fluid dynamics, and digital twins to enhance thermal management. Initial research will explore two-phase direct-to-chip cooling for AI accelerators and predictive thermal management of liquid-cooled AI systems.
Padmesh Mandloi, Vice President of Synopsys Simulation and Analysis APAC, highlighted the importance of understanding multiscale and multiphysics behaviour, stating, “By combining Ansys multiscale and multiphysics simulation, AI-assisted engineering and surrogate modelling with STDCT 2.0 test data, we can help researchers connect and exchange data across scales.”
The initiative aims to build industry capability for sustainable data centres in tropical climates, contributing software access, technical expertise, and training to support research and technology validation. Professor Lee Poh Seng of NUS emphasised the goal of developing scalable cooling and digital twin solutions for AI-ready infrastructure in Singapore and the region.
