Digital Twins for Science
DescriptionDigital Twins have emerged as one of the hot new modeling concepts in HPC as we enter the Post Exascale Era. Originally conceived as a modeling tool for manufacturing and Product Life Cycle Management Digital Twins are evolving in HPC with the convergence of simulation, machine learning and live data. The introduction of machine learning into the HPC workflows has been a critical component in the evolution of the Digital Twin for Science where for the first time models with fidelity at the atomic level can scale to the full scope of a physical object or system.

The talk will include examples from physics, biology and climate science and describe how the NVIDIA platform can address the requirements for first principles simulation using the HPC SDK, the RAPIDS SDK and Modulus to develop the robust machine learning models, Holoscan our tool set to enable data acquisition from live data sources and Omniverse our SDK to aggregate the workflow components and visualize it.
Event Type
Exhibitor Forum
TimeWednesday, 15 November 20234pm - 4:30pm MST
Artificial Intelligence/Machine Learning
Fault Handling and Tolerance
Large Scale Systems
Programming Frameworks and System Software
Registration Categories