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Description
Effortlessly synchronize on-premises asset files with Amazon Simple Storage Service (S3) to guarantee cloud availability. Connect seamlessly with local servers, oversee data transfers prior to the rendering process, and categorize accounts and instances for precise billing. Acquire software licenses based on usage, utilize your own licenses, or combine both approaches to develop third-party digital content. Take advantage of Amazon Elastic Compute Cloud (EC2) Spot Instances to achieve savings of up to 90% compared to traditional on-demand pricing. Establish a render farm in just a few minutes, allowing for the execution of multiple projects simultaneously while enhancing cost management. Create either a hybrid or cloud-centric render farm that can scale to thousands of cores in mere minutes through the AWS Portal. Construct, customize, and implement render farms using the Render Farm Deployment Kit (RFDK) in well-known programming languages like Python. Employ the Jigsaw tool to accelerate the rendering of ultra-high-resolution images by distributing the workload across numerous machines, significantly improving efficiency. This integrated approach not only simplifies the rendering process but also optimizes resource utilization and cost-effectiveness.
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.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2
Amazon Web Services (AWS)
AMD Radeon ProRender
AWS Marketplace
AWS Thinkbox Sequoia
Amazon EKS
Amazon Elastic Inference
Amazon S3
Amazon SageMaker
CUDA
Integrations
Amazon EC2
Amazon Web Services (AWS)
AMD Radeon ProRender
AWS Marketplace
AWS Thinkbox Sequoia
Amazon EKS
Amazon Elastic Inference
Amazon S3
Amazon SageMaker
CUDA
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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/thinkbox-deadline/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/ec2/instance-types/g4/
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
