NVIDIA® SimNet™ is a Physics Informed Neural Networks (PINNs) toolkit for students and researchers who are either looking to get started with AI-driven physics simulations or are looking to leverage a powerful, existing framework to implement their domain knowledge to solve complex nonlinear physics problems with real-world applications.


Key Features

  • Novel Neural Network Architecture — PDEs with physical constraints while maintaining accuracy and convergence.
  • Design Space Exploration —Parameterized system representation that solves for multiple scenarios simultaneously.
  • Optimized for Multi-physics Problems —Solve complex PDEs on non-trivial geometries, or data assimilation or inverse problem use cases.

Dependencies NVIDIA Tensorflow 20.03 NGC container image Note: See the TensorFlow release notes for driver and GPU compatibility information.
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