Introduction to NVIDIA GPU Cloud

NVIDIA GPU Cloud (NGC) is a GPU-accelerated cloud platform optimized for deep learning and scientific computing. In this release, NGC includes NGC containers, the NGC container registry, the NGC website, and platform software for running the deep learning containers. This document provides an overview of the NVIDIA GPU Cloud and how to use it.

NGC Containers

NGC Containers are designed to enable a software platform centered around minimal OS requirements, Docker and driver installation on the server or workstation, and provisioning of all application and SDK software in the NGC containers through the NGC container registry.

NGC manages a catalog of fully integrated and optimized deep learning framework containers that take full advantage of NVIDIA GPUs in both single GPU and multi-GPU configurations. They include CUDA Toolkit, DIGITS workflow, and the following deep learning frameworks: NVCaffe, Caffe2, Microsoft Cognitive Toolkit (CNTK), MXNet, PyTorch, TensorFlow, Theano, and Torch. These framework containers are delivered ready-to-run, including all necessary dependencies such as CUDA runtime, NVIDIA libraries, and an operating system.

Each framework container image also includes the framework source code to enable custom modifications and enhancements, along with the complete software development stack.

NVIDIA updates these deep learning containers monthly to ensure they continue to provide peak performance.

In addition NGC provides a catalog of HPC visualization containers, now available in beta, featuring the industry’s leading visualization tools, including ParaView with NVIDIA IndeX volume renderer, NVIDIA OptiX ray-tracing library and NVIDIA Holodeck for interactive real-time visualization and high-quality visuals.

NGC also hosts popular third-party GPU ready HPC application containers which conform to NGC container standards and best practices, making it easy to get the latest GPU optimized HPC software up and running quickly.

NGC Container Registry

The NGC container registry stores the container images for distribution at nvcr.io.  With an NGC API Key, you can pull and run NGC containers from the registry.

NGC Website

The NGC website (https://ngc.nvidia.com) is the portal for managing NGC. Easily view the contents of the NGC container registry, create your API Key that authorizes you to use the containers, and see which cloud service providers offer virtual machine instances that are optimized for NGC containers.

Optimized Accelerated Computing Environments

All NGC containers are qualified to take full advantage of NVIDIA GPUs and are ready-to-run on supported accelerated computing environments (ACEs) such as NVIDIA DGX systems and supported cloud service providers.

Currently, supported cloud services providers include Amazon Web Services with Amazon EC2 P3 instances.

Running Deep Learning Frameworks Using NGC

The process for running deep learning framework containers can be summarized as follows:

Preparing the Accelerated Computing Environment (ACE)

Prepare the accelerated computing environment (ACE) for running the NGC containers. See the following documentation for instructions on setting up the ACE:

Obtaining NGC Credentials and Selecting a Container

Sign up for an NGC account at https://ngc.nvidia.com, log in, then create your NGC API Key which is needed to use the containers in the NGC container registry.

Browse the Registry section of the NGC website to identify a container and tag to use.

See Getting Started with NGC for details.

Running Containers

Connect to the ACE, log into nvcr.io, then enter commands to run the containers that you identified from the Registry.

See the NVIDIA Docker Containers for Deep Learning Frameworks User Guide for more information on running deep learning containers.

See the NGC Container User Guide for more information on running other NGC containers.

Notices

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