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SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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Displaying 8 results
NVIDIA
NVIDIA
PyG
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Container
NVIDIA AI Enterprise
NVIDIA
NVIDIA
PyG PB October 2024 (PB 24h2)
PyG Production Branch October 2024 (PB 24h2) offers a 9-month lifecycle for API stability, with monthly patches for high and critical software vulnerabilities.
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
ALCHEMI Batched Geometry Relaxation NIM
Atomistic Geometry Optimization/Relaxation NIM with machine learning interatomic potentials.
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
ALCHEMI Batched Molecular Dynamics
Atomistic Molecular Dynamics NIM with machine learning interatomic potentials.
Container
NVIDIA
NVIDIA
NVIDIA PhysicsNeMo Sym Examples Supplemental Materials
This contains all the supplemental data for PhysicsNeMo Sym examples. This includes validation data, training data, large CSV/STLs, etc. For the python scripts, please refer https://github.com/nvidia/physicsnemo-sym
Resource
NVIDIA
NVIDIA
PhysicsNeMo Datasets: Stokes Flow
Stokes flow dataset with parameterized domain
Resource
NVIDIA
NVIDIA
NVIDIA PhysicsNeMo Examples Supplemental Materials
This contains all the supplemental data for PhysicsNeMo examples. This includes files apart from the actual dataset required for training. For the python scripts, please refer https://github.com/nvidia/physicsnemo
Resource
Collection
NVIDIA
NVIDIA
Deep Learning Frameworks
This collection contains performance-optimized Deep Learning frameworks.
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