Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The intricacies of data center infrastructure are on the rise, necessitating advanced solutions that enhance the simplicity of network management. With NVIDIA Air, users can achieve cloud-scale efficiency by generating precise replicas of actual data center setups. This innovative tool enables the modeling of data center environments with complete software capabilities, effectively creating a digital twin. By simulating, validating, and automating modifications and updates, organizations can transform and optimize their network operations. Users can create one-to-one virtual replicas of data centers featuring numerous switches and servers. Confidence in deployment is heightened through the automation of essential patches and security updates. Additionally, sharing simulations with team members fosters improved training and knowledge transfer among colleagues. The platform provides complimentary access to critical NVIDIA networking software via Air, which operates seamlessly in the cloud. It also supports the simulation of Cumulus Linux and SONiC network operating systems, along with the comprehensive NetQ network operations toolset, ensuring users have the necessary resources to manage their networks effectively. This capability not only enhances operational efficiency but also empowers teams to adapt and innovate in a rapidly evolving digital landscape.
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
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
NVIDIA
Founded
1993
Country
United States
Website
www.nvidia.com/en-us/networking/ethernet-switching/air/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/physicsnemo
Product Features
Data Center Management
Audit Trail
Behavior-Based Acceleration
Cross Reference System
Device Auto Discovery
Diagnostic Testing
Import / Export Data
JCL Management
Multi-Platform
Multi-User
Power Management
Sarbanes-Oxley Compliance