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NVIDIA Launches AI Cloud Container Registry to Accelerate Deep Learning

By   /  October 31, 2017  /  No Comments

by Angela Guess

A recent press release states, “NVIDIA today announced immediate availability of the NVIDIA® GPU Cloud (NGC) container registry for AI developers worldwide. In just a few steps, NGC helps developers get started with deep learning development through no-cost access to a comprehensive, easy-to-use, fully optimized deep learning software stack. The cloud-based service is available immediately to users of the just-announced Amazon Elastic Compute Cloud (Amazon EC2) P3 instances featuring NVIDIA Tesla® V100 GPUs. NVIDIA plans to expand support to other cloud platforms soon. After signing up for an NGC account, developers can download a containerized software stack that integrates and optimizes a wide range of deep learning frameworks, NVIDIA libraries and CUDA® runtime versions — which are kept up to date and run seamlessly in the cloud or on NVIDIA DGX™ systems.”

The release continues, “Developers who want to get started with deep learning right away using the NGC container registry can follow a three-step process: Sign up for a no-cost NGC account at www.nvidia.com/ngcsignup. Run an optimized NVIDIA image on cloud service provider platform. Pull containers from NGC and get started. Key benefits of the NGC container registry include: (1) Instant access to the most widely used GPU-accelerated frameworks: Containerized software includes NVCaffe, Caffe2, Microsoft Cognitive Toolkit (CNTK), DIGITS, MXNet, PyTorch, TensorFlow, Theano and Torch, as well as CUDA for application development. (2) Maximum Performance: Tuned, tested and certified by NVIDIA for maximum performance, the NGC container registry enables developers to get optimal performance on NVIDIA GPUs running on clouds. (3) Pre-integration: Easy-to-use containers allow users to begin deep learning jobs immediately, eliminating time-consuming and difficult do-it-yourself software integration.”

Read more at Globe Newswire.

Photo credit: NVIDIA

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