What is NVIDIA GPU Cloud (NGC)? Platform for AI and Data Science

In an era where Artificial Intelligence (AI), Data Science, and Machine Learning (ML) are driving innovation across various industries, NVIDIA GPU Cloud (NGC) has become a crucial platform that enables developers, researchers, and organizations to easily access high-performance computing tools and resources for AI and Data Science tasks.

NGC provides customized software for GPU operations, allowing users to run Machine Learning, Deep Learning, Data Analytics, and High-Performance Computing (HPC) models at full efficiency without worrying about installing or customizing the software themselves.

What is NVIDIA GPU Cloud (NGC)?

NVIDIA GPU Cloud (NGC) is a platform that provides a pre-optimized AI, ML, HPC, and Data Science software stack, designed to work seamlessly with NVIDIA GPUs.

NGC has containers, AI models, SDKs, and developer tools that can be used on the cloud, on-premises data centers, and edge devices, allowing users to access powerful resources without wasting time on installation or system configuration.

Structure and composition of NGC

NGC Catalog

A hub of software tailored for AI, ML, Deep Learning, HPC, and Data Science, including:

• Pre-trained AI Models - Pre-trained models for tasks such as Computer Vision, NLP, Speech Recognition.
• Containers - Pre-installed and pre-configured software, ready to use immediately
• Helm Charts - A tool to help install applications on Kubernetes
• SDK and Frameworks - such as TensorFlow, PyTorch, RAPIDS, NVIDIA Triton Inference Server

NGC Containers

NGC provides Docker Containers with installed AI Frameworks, HPC Applications, and Data Analytics Tools, which help reduce setup time and improve GPU performance.

Popular container examples

• TensorFlow, PyTorch, MXNet - for Machine Learning and Deep Learning
• RAPIDS AI - For Data Science and Big Data Processing
• NVIDIA CUDA Toolkit - For developers who want to use CUDA
• NVIDIA Clara - for AI in Healthcare and Biomedical

NGC Pre-trained Models

NGC has pre-trained artificial intelligence models to reduce the time needed to develop new models, which can be fine-tuned with your own data.

Examples of popular AI models in NGC

• BERT, Megatron-LM - for NLP (Natural Language Processing)
• StyleGAN, FastPitch - for Generative AI and Speech Synthesis
• DetectNet, YOLO, Mask R-CNN - for Computer Vision

NGC CLI & API

NGC has a Command Line Interface (CLI) and API that make it easier for developers to access software and models, as well as to download and manage containers easily.

Proper use of NVIDIA GPU Cloud (NGC)

• AI and Deep Learning - Use NGC Containers to run and train Machine Learning and Deep Learning models on GPU
• Data Science & Analytics - Use RAPIDS AI and Dask for big data processing
• High-Performance Computing (HPC) - Uses customized software for scientific simulations and calculations.
• Edge AI & IoT - Use NGC with NVIDIA Jetson for AI on Edge devices
• Cloud AI Deployment - Run AI on the cloud such as AWS, Google Cloud, Microsoft Azure that supports NGC

Advantages of NVIDIA GPU Cloud (NGC)

• Save time and reduce hassle - no need to install and configure AI Frameworks yourself.
• Enhance GPU performance - NGC Software is optimized to work fully with NVIDIA GPUs.
• Supports multiple platforms - can be used on On-Premises, Cloud, and Edge.
• Access advanced AI models - Pre-trained Models available for use and further customization.
• Supports various tasks - including AI, ML, Data Science, and HPC

NVIDIA GPU Cloud (NGC) is suitable for whom?

• AI and Machine Learning Developers - Use AI Frameworks and Pre-trained Models
• Data Scientists - Use RAPIDS AI for data analysis and Big Data
• Organizations that need AI Infrastructure - use NGC to run AI Workloads on Cloud or On-Premises
• Researchers and HPC developers - use NGC Containers for simulation and data computation tasks.

NVIDIA GPU Cloud (NGC) is a Cloud AI & Data Science platform that enables developers and organizations to utilize GPU resources efficiently without the need to spend time installing software themselves.

NGC provides ready-to-use Containers, AI Models, SDKs, and HPC Applications, making it suitable for AI, Deep Learning, Data Science, and High-Performance Computing (HPC) both on Cloud and On-Premises.

Using NGC makes AI and Machine Learning development easier, reduces setup time, and increases work speed, making it an essential platform for anyone looking to use AI and GPU Computing in the digital age.