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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Amazon EC2 G4 instances are specifically designed to enhance the performance of machine learning inference and applications that require high graphics capabilities. Users can select between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad) according to their requirements. The G4dn instances combine NVIDIA T4 GPUs with bespoke Intel Cascade Lake CPUs, ensuring an optimal mix of computational power, memory, and networking bandwidth. These instances are well-suited for tasks such as deploying machine learning models, video transcoding, game streaming, and rendering graphics. On the other hand, G4ad instances, equipped with AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, offer a budget-friendly option for handling graphics-intensive workloads. Both instance types utilize Amazon Elastic Inference, which permits users to add economical GPU-powered inference acceleration to Amazon EC2, thereby lowering costs associated with deep learning inference. They come in a range of sizes tailored to meet diverse performance demands and seamlessly integrate with various AWS services, including Amazon SageMaker, Amazon ECS, and Amazon EKS. Additionally, this versatility makes G4 instances an attractive choice for organizations looking to leverage cloud-based machine learning and graphics processing capabilities.

Description

The Intel® Distribution of OpenVINO™ toolkit serves as an open-source AI development resource that speeds up inference on various Intel hardware platforms. This toolkit is crafted to enhance AI workflows, enabling developers to implement refined deep learning models tailored for applications in computer vision, generative AI, and large language models (LLMs). Equipped with integrated model optimization tools, it guarantees elevated throughput and minimal latency while decreasing the model size without sacrificing accuracy. OpenVINO™ is an ideal choice for developers aiming to implement AI solutions in diverse settings, spanning from edge devices to cloud infrastructures, thereby assuring both scalability and peak performance across Intel architectures. Ultimately, its versatile design supports a wide range of AI applications, making it a valuable asset in modern AI development.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AMD Radeon ProRender
Amazon EC2
Amazon Elastic Inference
Amazon SageMaker
Amazon Web Services (AWS)
CUDA
Caffe
Cameralyze
EndoAim
Hugging Face
Intel Geti
Intel Open Edge Platform
Keras
LaunchX
Nero AI
Nutanix Karbon Platform Services
ONNX
OpenGL
PyTorch
TensorFlow

Integrations

AMD Radeon ProRender
Amazon EC2
Amazon Elastic Inference
Amazon SageMaker
Amazon Web Services (AWS)
CUDA
Caffe
Cameralyze
EndoAim
Hugging Face
Intel Geti
Intel Open Edge Platform
Keras
LaunchX
Nero AI
Nutanix Karbon Platform Services
ONNX
OpenGL
PyTorch
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

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

Vendor Details

Company Name

Intel

Founded

1968

Country

United States

Website

www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html

Product Features

Deep Learning

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

HPC

Product Features

Deep Learning

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

Alternatives

Alternatives

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