Title: Career Talk: "A Framework for Developing Physics ML Neural Network Models"
We present NVIDIA Modulus, a neural network framework that offers building blocks for a developing physics machine learning surrogate models trained using both physics and data. Modulus accelerates stimulations across a wide range of disciplines in science and engineering and addresses a wide range of use cases - coupled forward simulations without any training data, inverse and data assimilation problems, parameterized simulations, super-resolution, etc. Modulus is customizable with API's that enable user extensions to geometry, physics, and network architecture. It has advanced network architectures that are optimized for high- performance GPU computing and offers scalable performance for multi-GPU and multi-Node implementation. Join us in person at Beckman Room 3269 or online at TCBG Seminar (uiuc.edu)
