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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Enhance engineering processes with the only comprehensive and user-friendly CFD platform designed for multidisciplinary design and optimization. Computational fluid dynamics (CFD) plays a crucial role in multiphysics system analysis, allowing for the simulation of fluid behavior and thermodynamic characteristics through advanced numerical models. Engineers leverage the Cadence Fidelity CFD platform for various design tasks, including propulsion, aerodynamics, hydrodynamics, and combustion, to enhance product efficiency while minimizing the need for costly and time-intensive physical testing. This robust Fidelity CFD platform offers a seamless end-to-end solution tailored for applications across aerospace, automotive, turbomachinery, and marine sectors. With its efficient workflows, massively parallel architecture, and cutting-edge solver technology, the platform delivers remarkable performance and accuracy, significantly boosting engineering productivity in addressing contemporary design challenges. Ultimately, Fidelity stands out by not only simplifying complex processes but also enabling engineers to innovate rapidly and effectively.

Description

NVIDIA PhysicsNeMo is a publicly available Python-based deep-learning framework designed for the creation, training, fine-tuning, and inference of physics-AI models that integrate physical principles with data, thereby enhancing simulations, developing accurate surrogate models, and facilitating near-real-time predictions in various fields such as computational fluid dynamics, structural mechanics, electromagnetics, weather forecasting, climate studies, and digital twin technologies. This framework offers powerful, GPU-accelerated capabilities along with Python APIs that are built on the PyTorch platform and distributed under the Apache 2.0 license, featuring a selection of curated model architectures that include physics-informed neural networks, neural operators, graph neural networks, and generative AI techniques, enabling developers to effectively leverage physics-based causal relationships together with empirical data for high-quality engineering modeling. Additionally, PhysicsNeMo provides comprehensive training pipelines that encompass everything from geometry ingestion to the application of differential equations, along with reference application recipes that help users quickly initiate their development workflows. This combination of features makes PhysicsNeMo an essential tool for engineers and researchers seeking to advance their work in physics-driven AI applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

PyTorch
Python

Integrations

PyTorch
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cadence Design Systems

Country

United States

Website

www.cadence.com/en_US/home/tools/system-analysis/computational-fluid-dynamics/fidelity.html

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/physicsnemo

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Product Features

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