NVIDIA has released a datacenter CFD dataset on Hugging Face, featuring normalized OpenFOAM simulations for hot aisle configurations, including variations in rack count and geometry. This dataset is part of NVIDIA's PhysicsNeMo, an open-source deep-learning framework designed for developing AI models that integrate physics knowledge with data. PhysicsNeMo offers Python modules to create scalable training and inference pipelines, facilitating the exploration, validation, and deployment of AI models for real-time predictions. By supporting neural operators, GNNs, transformers, and Physics-Informed Neural Networks, PhysicsNeMo provides a comprehensive stack for training models at scale, advancing AI4Science and engineering applications. This matters because it enables more efficient and accurate simulations in datacenter environments, potentially leading to improved energy efficiency and performance.
