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What is NVIDIA GPU-Optimized AMI?

The NVIDIA GPU-Optimized AMI is a specialized virtual machine image crafted to optimize performance for GPU-accelerated tasks in fields such as Machine Learning, Deep Learning, Data Science, and High-Performance Computing (HPC). With this AMI, users can swiftly set up a GPU-accelerated EC2 virtual machine instance, which comes equipped with a pre-configured Ubuntu operating system, GPU driver, Docker, and the NVIDIA container toolkit, making the setup process efficient and quick. This AMI also facilitates easy access to the NVIDIA NGC Catalog, a comprehensive resource for GPU-optimized software, which allows users to seamlessly pull and utilize performance-optimized, vetted, and NVIDIA-certified Docker containers. The NGC catalog provides free access to a wide array of containerized applications tailored for AI, Data Science, and HPC, in addition to pre-trained models, AI SDKs, and numerous other tools, empowering data scientists, developers, and researchers to focus on developing and deploying cutting-edge solutions. Furthermore, the GPU-optimized AMI is offered at no cost, with an additional option for users to acquire enterprise support through NVIDIA AI Enterprise services. For more information regarding support options associated with this AMI, please consult the 'Support Information' section below. Ultimately, using this AMI not only simplifies the setup of computational resources but also enhances overall productivity for projects demanding substantial processing power, thereby significantly accelerating the innovation cycle in these domains.

What is Amazon EC2 G4 Instances?

Amazon EC2 G4 instances are meticulously engineered to boost the efficiency of machine learning inference and applications that demand superior graphics performance. Users have the option to choose between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad) based on their specific needs. The G4dn instances merge NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing an ideal combination of processing power, memory, and networking capacity. These instances excel in various applications, including the deployment of machine learning models, video transcoding, game streaming, and graphic rendering. Conversely, the G4ad instances, which feature AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, present a cost-effective solution for managing graphics-heavy tasks. Both types of instances take advantage of Amazon Elastic Inference, enabling users to incorporate affordable GPU-enhanced inference acceleration to Amazon EC2, which helps reduce expenses tied to deep learning inference. Available in multiple sizes, these instances are tailored to accommodate varying performance needs and they integrate smoothly with a multitude of AWS services, such as Amazon SageMaker, Amazon ECS, and Amazon EKS. Furthermore, this adaptability positions G4 instances as a highly appealing option for businesses aiming to harness the power of cloud-based machine learning and graphics processing workflows, thereby facilitating innovation and efficiency.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
AMD Radeon ProRender
AWS Marketplace
Amazon EC2
Amazon EKS
Amazon Elastic Inference
Amazon SageMaker
Azure Marketplace
CUDA
Gaia
NVIDIA NGC
OpenGL
OpenLIT

Integrations Supported

Amazon Web Services (AWS)
AMD Radeon ProRender
AWS Marketplace
Amazon EC2
Amazon EKS
Amazon Elastic Inference
Amazon SageMaker
Azure Marketplace
CUDA
Gaia
NVIDIA NGC
OpenGL
OpenLIT

API Availability

Has API

API Availability

Has API

Pricing Information

$3.06 per hour
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/marketplace/pp/prodview-7ikjtg3um26wq

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/instance-types/g4/

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Popular Alternatives

Popular Alternatives

NVIDIA NGC Reviews & Ratings

NVIDIA NGC

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