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Description
AWS Inferentia accelerators, engineered by AWS, aim to provide exceptional performance while minimizing costs for deep learning (DL) inference tasks. The initial generation of AWS Inferentia accelerators supports Amazon Elastic Compute Cloud (Amazon EC2) Inf1 instances, boasting up to 2.3 times greater throughput and a 70% reduction in cost per inference compared to similar GPU-based Amazon EC2 instances. Numerous companies, such as Airbnb, Snap, Sprinklr, Money Forward, and Amazon Alexa, have embraced Inf1 instances and experienced significant advantages in both performance and cost. Each first-generation Inferentia accelerator is equipped with 8 GB of DDR4 memory along with a substantial amount of on-chip memory. The subsequent Inferentia2 model enhances capabilities by providing 32 GB of HBM2e memory per accelerator, quadrupling the total memory and decoupling the memory bandwidth, which is ten times greater than its predecessor. This evolution in technology not only optimizes the processing power but also significantly improves the efficiency of deep learning applications across various sectors.
Description
The AWS Nitro System serves as the backbone for the newest generation of Amazon EC2 instances, enabling quicker innovation, cost reductions for users, and improved security along with the introduction of new instance types. By rethinking virtualization infrastructure, AWS has transferred essential functions like CPU, storage, and networking virtualization to specialized hardware and software, thus freeing up nearly all server resources for use by instances. This innovative architecture includes several essential components: Nitro Cards, which accelerate and offload I/O tasks for services such as VPC, EBS, and instance storage; the Nitro Security Chip, which minimizes the attack surface and restricts administrative access to prevent human error and tampering; and the Nitro Hypervisor, a streamlined hypervisor that efficiently manages memory and CPU allocation, providing performance that closely resembles that of bare metal systems. Furthermore, the modular nature of the Nitro System facilitates the swift introduction of new EC2 instance types, enhancing the overall agility of AWS services. Overall, this comprehensive approach positions AWS to continue leading in cloud innovation and resource optimization.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
AWS EC2 Trn3 Instances
AWS Elastic Fabric Adapter (EFA)
AWS HPC
AWS Nitro Enclaves
AWS Parallel Computing Service
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Integrations
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
AWS EC2 Trn3 Instances
AWS Elastic Fabric Adapter (EFA)
AWS HPC
AWS Nitro Enclaves
AWS Parallel Computing Service
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
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
2006
Country
United States
Website
aws.amazon.com/machine-learning/inferentia/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/ec2/nitro/
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Infrastructure-as-a-Service (IaaS)
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring