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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
PyTorch
PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.
Container
NVIDIA
NVIDIA
TensorRT
NVIDIA TensorRT is a C++ library that facilitates high-performance inference on NVIDIA graphics processing units (GPUs). TensorRT takes a trained network and produces a highly optimized runtime engine that performs inference for that network.
Container
NVIDIA
NVIDIA
vLLM
vLLM is a fast and easy-to-use library for LLM inference and serving. The NVIDIA vLLM NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
Container
NVIDIA
NVIDIA
CUDA Deep Learning
CUDA is a parallel computing platform and programming model that enhances computing performance using NVIDIA GPUs. CUDA Deep Learning integrates networking and GPU-accelerated libraries like cuDNN, cuTensor, NCCL, HPC-x, and the CUDA Toolkit.
Container
NVIDIA
NVIDIA
JAX
JAX is a framework for high-performance numerical computing and machine learning research. It includes Numpy-like APIs, automatic differentiation, XLA acceleration and simple primitives for scaling across GPUs and supports an ecosystem of libraries.
Container
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
NVIDIA
DGL
Deep Graph Library (DGL) is a Python package built for the implementation and training of graph neural networks on top of existing DL frameworks. The DGL NGC Container is built with the latest versions of DGL, PyTorch, and their dependencies.
Container
NVIDIA
NVIDIA
SGLang
SGLang is a fast serving framework for large language models and vision language models. The NVIDIA SGLang NGC Container is optimized for GPU acceleration, and contains a validated set of libraries that enable and optimize GPU performance.
Container

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