NVIDIA Modulus

NVIDIA Modulus is an open-source framework for building, training, and fine-tuning Physics-ML models with a simple Python interface.


Using Modulus, engineers can build high-fidelity AI surrogate models that blend the causality of physics described by governing partial differential equations (PDEs) with simulation data from CAE solvers or observed data. Such AI models can predict with near-real-time latency and for a parameterized design space.


Use Modulus to bolster your engineering simulations with AI. You can build models for enterprise-scale digital twin applications across multiple physics domains, from CFD and structural to electromagnetics.

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NVIDIA Modulus, a Neural Network Framework


Modulus Data Sheet
NVIDIA Modulus Neural Network Framework

Benefits

Modulus is an open-source, freely available AI framework for developing physics-ML models and novel AI architectures for engineering systems.

AI toolkit for physics

AI Toolkit for Physics

Quickly configure, build, and train AI models for physical systems in any domain from engineering simulations to life sciences with simple Python APIs.

Customize models from NVIDIA NGC catalog

Customize Models

Download, build on, and customize state-of-the-art pretrained models from the NVIDIA NGC™ catalog.

Deploy and simulate AI surrogate models in real time

Near-Real-Time Inference

Deploy AI surrogate models as digital twins of your physical systems to simulate in near real time.

Scale training performance with NVIDIA AI

Scale With NVIDIA AI

Leverage NVIDIA AI to scale training performance from single-GPU to multi-node implementations.

AI toolkit for physics

Open-Source Design

Experience the benefits of open source. Modulus that is built on top of PyTorch and is released under the Apache 2.0 license.

Customize models from NVIDIA NGC catalog

Standardized

Work with the best practices of AI development for physics-ML models, with an immediate focus on engineering applications.

Deploy and simulate AI surrogate models in real time

User Friendly

Boost productivity with user-comprehensible error messages and easy-to-program Pythonic API interfaces.

Scale training performance with NVIDIA AI

High Quality

Use high-quality software with enterprise-grade development, tutorials for getting started, and robust validation and documentation.

See Modulus in Action

Accelerating Extreme Weather Prediction With FourCastNet


Siemens Energy HRSG Digital Twin Simulation Using NVIDIA Modulus and Omniverse

Maximizing Wind Energy Production Using Wake Optimization


Accelerating Carbon Capture and Storage With Fourier Neural Operator and NVIDIA Modulus


Predicting Extreme Weather Events Three Weeks in Advance With
FourCastNet


Contribute to Modulus’ Development

Modulus provides a unique platform for collaboration within the scientific community. Domain experts are invited to contribute and accelerate physics-ML across a variety of use cases and applications.


Go to GitHub

Key Features

New Model Architectures

Modulus offers a variety of approaches for training physics-based models, from purely physics-driven models like PINNs to physics-based, data-driven architectures such as neural operators.

Modulus includes curated Physics-ML model architectures, Fourier feature networks, or Fourier neural operators trained on NVIDIA DGX across open-source, free datasets found in the documentation.

Training State-of-the-Art Physics-ML Models

Modulus provides an end-to-end pipeline for training Physics-ML models—from ingesting geometry to adding PDEs and scaling the training to multi-node GPUs. Modulus also includes training recipes in the form of reference applications.

Explicit Parameterization

Modulus provides explicit parameter specifications for training the surrogate model with a range of values to learn for the design space and for inferring multiple scenarios simultaneously.

Documentation

Omniverse Integration

Modulus is now integrated with NVIDIA Omniverse™ via the Modulus extension that can be used to visualize the outputs of a Modulus-trained model. The extension enables you to import the output results into a visualization pipeline for common output scenarios, such as streamlines and iso-surfaces. It also provides an interface that enables interactive exploration of design variables and parameters for inferring new system behavior and visualizing it in near real time.

Omniverse Integration Documentation

Production-Ready Solution With NVIDIA AI Enterprise

Modulus is now available with NVIDIA AI Enterprise, an end-to-end AI software platform optimized to accelerate enterprises to the leading edge of AI. NVIDIA AI Enterprise delivers validation and integration for NVIDIA AI open-source software, access to AI solution workflows to speed time to production, certifications to deploy AI everywhere, and enterprise-grade support, security, and API stability while mitigating the potential risks of open-source software.

Learn more about NVIDIA AI Enterprise

Ways to Get Started With NVIDIA Modulus

Download Containers and Models for Development

Download Containers and Models for Development

Develop Physics-ML models using Modulus container and pretrained models, available for free on NVIDIA NGC.


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Enterprise-Scale Workflows

Enterprise-Scale Workflows

Get free access to NVIDIA cloud workflows for Modulus and experience the ease of scaling to enterprise workloads.


Try on NVIDIA LaunchPad
Self-Paced Online Course

Self-Paced Online Course

Take a hands-on introductory course from the NVIDIA Deep Learning Institute (DLI) to explore physics-informed machine learning with Modulus.


Access Course

What Others Are Saying



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Watch presentation about developing Digital Twins for weather, climate, and energy

Developing Digital Twins for Weather, Climate, and Energy



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Modulus Featured Content

Download the NVIDIA Modulus Framework Today