Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The NVIDIA GPU-Optimized AMI serves as a virtual machine image designed to enhance your GPU-accelerated workloads in Machine Learning, Deep Learning, Data Science, and High-Performance Computing (HPC). By utilizing this AMI, you can quickly launch a GPU-accelerated EC2 virtual machine instance, complete with a pre-installed Ubuntu operating system, GPU driver, Docker, and the NVIDIA container toolkit, all within a matter of minutes.
This AMI simplifies access to NVIDIA's NGC Catalog, which acts as a central hub for GPU-optimized software, enabling users to easily pull and run performance-tuned, thoroughly tested, and NVIDIA-certified Docker containers. The NGC catalog offers complimentary access to a variety of containerized applications for AI, Data Science, and HPC, along with pre-trained models, AI SDKs, and additional resources, allowing data scientists, developers, and researchers to concentrate on creating and deploying innovative solutions.
Additionally, this GPU-optimized AMI is available at no charge, with an option for users to purchase enterprise support through NVIDIA AI Enterprise. For further details on obtaining support for this AMI, please refer to the section labeled 'Support Information' below. Moreover, leveraging this AMI can significantly streamline the development process for projects requiring intensive computational resources.
Description
balenaEngine is a specialized container engine designed specifically for embedded systems and IoT applications, utilizing technology from the Moby Project by Docker. It is significantly smaller than Docker CE, boasting a size reduction of 3.5 times and is distributed as a single binary. This engine is compatible with a diverse range of chipset architectures, catering to everything from small IoT devices to larger industrial gateways. It offers bandwidth-efficient updates using binary diffs that can be 10 to 70 times smaller compared to the traditional method of pulling layers in various scenarios. To mitigate excessive disk writing and safeguard against potential storage corruption, it extracts layers as they are received. Additionally, its atomic and durable image pulls ensure protection against incomplete container downloads in case of power interruptions. The design also minimizes page cache thrashing during image pulls, allowing applications to run smoothly even in low-memory environments. In summary, balenaEngine is an innovative solution that not only supports Docker containers but also enhances bandwidth efficiency for container updates. This makes it an ideal choice for developers seeking reliability and efficiency in IoT and embedded systems.
API Access
Has API
No
API Access
Has API
No
Integrations
AWS Marketplace
Yes
Amazon Web Services (AWS)
Yes
Azure Marketplace
Yes
Docker
No
Gaia
Yes
NVIDIA NGC
Yes
OpenLIT
Yes
Integrations
AWS Marketplace
No
Amazon Web Services (AWS)
No
Azure Marketplace
No
Docker
Yes
Gaia
No
NVIDIA NGC
No
OpenLIT
No
Pricing Details
$3.06 per hour
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/marketplace/pp/prodview-7ikjtg3um26wq
Vendor Details
Company Name
balena
Founded
2013
Country
United States
Website
www.balena.io/engine/
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
Product Features
Container Management
Access Control
No
Application Development
No
Automatic Scaling
No
Build Automation
No
Container Health Management
No
Container Storage
No
Deployment Automation
No
File Isolation
No
Hybrid Deployments
No
Network Isolation
No
Orchestration
No
Shared File Systems
No
Version Control
No
Virtualization
No
IoT
Application Development
No
Big Data Analytics
No
Configuration Management
No
Connectivity Management
No
Data Collection
No
Data Management
No
Device Management
No
Performance Management
No
Prototyping
No
Visualization
No