NVIDIA PhysicsNeMoNVIDIA
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Related Products
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About
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.
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About
NVIDIA Triton™ inference server delivers fast and scalable AI in production. Open-source inference serving software, Triton inference server streamlines AI inference by enabling teams deploy trained AI models from any framework (TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, custom and more on any GPU- or CPU-based infrastructure (cloud, data center, or edge). Triton runs models concurrently on GPUs to maximize throughput and utilization, supports x86 and ARM CPU-based inferencing, and offers features like dynamic batching, model analyzer, model ensemble, and audio streaming. Triton helps developers deliver high-performance inference aTriton integrates with Kubernetes for orchestration and scaling, exports Prometheus metrics for monitoring, supports live model updates, and can be used in all major public cloud machine learning (ML) and managed Kubernetes platforms. Triton helps standardize model deployment in production.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Researchers, engineers, and developers who need an open source Python AI framework to build, train, fine-tune, and deploy physics-informed machine learning models for simulation, digital twins, and real-time prediction
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Audience
Developers and companies searching for an inference server solution to improve AI production
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationNVIDIA
Founded: 1993
United States
developer.nvidia.com/physicsnemo
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Company InformationNVIDIA
United States
developer.nvidia.com/nvidia-triton-inference-server
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Categories |
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Integrations
PyTorch
Alibaba CloudAP
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Azure Kubernetes Service (AKS)
Azure Machine Learning
FauxPilot
Google Kubernetes Engine (GKE)
HPE Ezmeral
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Integrations
PyTorch
Alibaba CloudAP
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Azure Kubernetes Service (AKS)
Azure Machine Learning
FauxPilot
Google Kubernetes Engine (GKE)
HPE Ezmeral
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