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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 15 results
    NVIDIA HPC SDK
    NVIDIA
    The NVIDIA HPC SDK is a comprehensive suite of compilers, libraries and tools essential to maximizing developer productivity and the performance and portability of HPC applications.
    Container
    PyG
    NVIDIA
    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
    cuOpt
    NVIDIA
    NVIDIA® cuOpt™ is an open-source, GPU-accelerated engine for decision optimization designed to tackle large-scale problems with millions of variables and constraints.
    Container
    DPSCTL
    NVIDIA
    NVIDIA Dynamic Power Software (DPS) CLI
    Container
    Earth-2 FourCastNet 3
    NVIDIA
    FourCastNet 3 is a probabilistic global weather modeling that uses geometric machine learning.
    Model
    PhysicsNeMo Checkpoints: AFNO_DX_FI-V1-ERA5
    NVIDIA
    This deep learning model, based on the Adaptive Fourier Neural Operator framework (AFNO), interpolates a prognostic forecast model to a shorter time-step size (by default from 6 h to 1 h).
    Model
    NVIDIA PhysicsNeMo Sym Examples Supplemental Materials
    NVIDIA
    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
    PhysicsNeMo Checkpoints: AFNO_DX_TP-V1-ERA5
    NVIDIA
    This deep learning model, based on the Adaptive Fourier Neural Operator framework (AFNO), predicts 6-hour accumulated surface precipitation given 20 atmospheric variables plus invariants.
    Model
    PhysicsNeMo Datasets: Stokes Flow
    NVIDIA
    Stokes flow dataset with parameterized domain
    Resource
    NVIDIA PhysicsNeMo Examples Supplemental Materials
    NVIDIA
    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
    PhysicsNeMo Checkpoints: AFNO_DX_SR-V1-ERA5
    NVIDIA
    This deep learning model, based on the Adaptive Fourier Neural Operator framework (AFNO), predicts 6-hour accumulated surface solar irradiance given 24 atmospheric variables plus invariants.
    Model
    PhysicsNeMo Checkpoints: StormCast-V1-ERA5-HRRR
    NVIDIA
    StormCast-V1-ERA5-HRRR is a mesoscale machine learning AI model that autoregressively predicts 99 state variables at km scale using a 1-hour time step, with dense vertical resolution in the atmosphere boundary layer.
    Model
    PhysicsNeMo Checkpoints: AFNO_DX_WG-V1-ERA5
    NVIDIA
    This deep learning model, based on the Adaptive Fourier Neural Operator framework (AFNO), predicts 6-hour maximum 3-second wind gusts given 20 atmospheric variables plus invariants.
    Model
    cuOpt
    NVIDIA
    NVIDIA® cuOpt™ is an open-source, GPU-accelerated engine for decision optimization designed to tackle large-scale problems with millions of variables and constraints.
    Collection
    DeepStream SDK
    NVIDIA
    NVIDIA DeepStream SDK enables developers to build accelerated pipelines for a wide range of use-cases such as IVA, retail, industrial inspection, and many more with minimal development effort.
    Collection

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