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Modulus

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Description

NVIDIA Modulus is a deep learning framework that blends the power of physics and partial differential equations (PDEs) with AI to build more robust models for better analysis.

Publisher

NVIDIA

Latest Tag

22.09

Modified

February 2, 2023

Compressed Size

7.76 GB

Multinode Support

No

Multi-Arch Support

No

22.09 (Latest) Scan Results

Linux / amd64

What is Modulus?

NVIDIA Modulus is a deep learning framework that blends the power of physics and partial differential equations (PDEs) with AI to build more robust models for better analysis.

With NVIDIA Modulus, we aim to provide researchers and industry specialists, various tools that will help accelerate your development of such models for the scientific discipline of your need.

Visit the Nvidia Modulus Website for more information.

Modulus Documentation

Key Features v22.09

  • Enhancements to FNO, PINO, and DeepONet architectures to enable more customizability and configure new networks
  • Modeling enhancements such as Selective Equations Term Suppression (SETS), Causal weighting scheme and criteria-based training termination APIs
  • Performance and usability enhancements such as FunTorch integration, more example-guided workflows for beginners

Key Features v22.07

  • Performance enhancements such as Meshless Finite Differentiation, leveraging CUDA Graphs and Tiny Cuda NN networks
  • Usability enhancements such as support for map style datasets, improved point cloud sampling for continuous and tessellated geometries
  • Support for generalized DeepOnet and FourCastNet

Key Features v22.03

  • FNO/AFNO support to create physics-ML models from data
  • Modulus Omniverse extension to visualize the outputs of the physics-ML model and interactively infer in real-time for new conditions defined by parameters
  • Support for DeepOnet architecture
  • Support for 2-eqn. turbulence models for modeling fully developed turbulent flow

Benefits

  • Broad Applicability - Models multiple physics types in forward and inverse simulations with accuracy and convergence.
  • Fast Turnaround Time - Provides parameterized system representation that solves for multiple scenarios simultaneously.
  • Easy to Adopt - Provides application programming interfaces (APIs) for implementing new physics and geometry and detailed user guide examples.

Modulus Forum

Please visit the Modulus Forum for :

  • Latest news and announcements on Modulus
  • Technical support
  • Report a bug
  • Customer success stories

License

By pulling and using the container, you accept the terms and conditions of this SOFTWARE DEVELOPER KITS, SAMPLES AND TOOLS LICENSE AGREEMENT.