AI and HPC Containers
Develop and deploy applications faster with GPU-optimized containers from the NVIDIA NGC™ catalog.
What Are Containers?
A container is a portable unit of software that combines the application and all its dependencies into a single package that’s agnostic to the underlying host OS. It removes the need to build complex environments and simplifies the application development-to-deployment process.
The NVIDIA NGC catalog contains a host of GPU-optimized containers for deep learning, machine learning, visualization, and high-performance computing (HPC) applications that are tested for performance, security, and scalability.
Benefits of Containers from the NGC Catalog
Built-in libraries and dependencies allow you to easily deploy and run applications.
Deploy the containers on multi-GPU/multi-node systems anywhere—in the cloud, on premises, and at the edge—on bare metal, virtual machines (VMs), and Kubernetes.
Deploy with Confidence
Containers are scanned for common vulnerabilities and exposures (CVEs), come with security reports, and are backed by optional enterprise support through NVIDIA AI Enterprise.
Optimized for Performance
NVIDIA-built containers are updated monthly and third-party software is updated regularly to deliver the features needed to extract maximum performance from your existing infrastructure and reduce time to solution.
BERT-Large for Natural Language Processing
BERT-Large leverages mixed precision arithmetic and Tensor Cores on Volta V100 and Ampere A100 GPUs for faster training times while maintaining target accuracy.
BERT-Large and Training performance with TensorFlow on a single node 8x V100 (16GB) & A100 (40GB). Mixed Precision. Batch size for BERT: 3 (V100), 24 (A100)
ResNet50 v1.5 for Image Processing
This model is trained with mixed precision using Tensor Cores on Volta, Turing and NVIDIA Ampere GPU architectures for faster training.
ResNet 50 performance with TensorFlow on single-node 8x V100 (16GB) and A100 (40 GB). Mixed Precision. Batch size for ResNet50: 26
Matlab for Deep Learning
Continuous development of Matlab’s Deep Learning container improves performance for training and inference
Windows 10, Intel Xeon E5-2623 @2.4GHz, NVIDIA Titan V 12GB GPUs
Containers for Diverse Workloads
Get started today by selecting from over 80 containerized software applications and SDKs, developed by NVIDIA and our ecosystem of partners.
NVIDIA Triton Inference Server
NVIDIA Triton™ Inference Server is an open-source inference solution that maximizes utilization of and performance on GPUs.
NVIDIA TensorRT® is a C++ library that facilitates high-performance inference on NVIDIA GPUs.
DeepStream is the streaming analytics toolkit for AI-based video, audio, and image understanding for multi-sensor processing.
NVIDIA Riva, is an application framework for multimodal conversational AI services that delivers real-time performance on GPUs.
HugeCTR, a component of NVIDIA Merlin™, is a deep neural network training framework that is capable of distributed training across multiple GPUs and nodes for maximum performance.
NVIDIA HPC SDK
The NVIDIA HPC SDK is a comprehensive suite of compilers, libraries, and tools for building, deploying, and managing HPC applications.
NGC Catalog Resources
Learn how to use the NGC catalog with these step-by-step instructions.
Read about the latest NGC catalog updates and announcements.
Watch all the top NGC sessions on demand.
Walk through how to use the NGC catalog with these video tutorials.