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Description

It enables efficient training on Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances powered by AWS Trainium. Additionally, for model deployment, it facilitates both high-performance and low-latency inference utilizing AWS Inferentia-based Amazon EC2 Inf1 instances along with AWS Inferentia2-based Amazon EC2 Inf2 instances. With the Neuron SDK, users can leverage widely-used frameworks like TensorFlow and PyTorch to effectively train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal alterations to their code and no reliance on vendor-specific tools. The integration of the AWS Neuron SDK with these frameworks allows for seamless continuation of existing workflows, requiring only minor code adjustments to get started. For those involved in distributed model training, the Neuron SDK also accommodates libraries such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP), enhancing its versatility and scalability for various ML tasks. By providing robust support for these frameworks and libraries, it significantly streamlines the process of developing and deploying advanced machine learning solutions.

Description

Amazon Elastic Inference provides an affordable way to enhance Amazon EC2 and Sagemaker instances or Amazon ECS tasks with GPU-powered acceleration, potentially cutting deep learning inference costs by as much as 75%. It is compatible with models built on TensorFlow, Apache MXNet, PyTorch, and ONNX. The term "inference" refers to the act of generating predictions from a trained model. In the realm of deep learning, inference can represent up to 90% of the total operational expenses, primarily for two reasons. Firstly, GPU instances are generally optimized for model training rather than inference, as training tasks can handle numerous data samples simultaneously, while inference typically involves processing one input at a time in real-time, resulting in minimal GPU usage. Consequently, relying solely on GPU instances for inference can lead to higher costs. Conversely, CPU instances lack the necessary specialization for matrix computations, making them inefficient and often too sluggish for deep learning inference tasks. This necessitates a solution like Elastic Inference, which optimally balances cost and performance in inference scenarios.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
AWS Deep Learning AMIs Yes 
AWS Deep Learning Containers Yes 
AWS Trainium Yes 
Amazon EC2 No 
Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 G4 Instances No 
Amazon EC2 Inf1 Instances Yes 
Amazon EC2 P4 Instances Yes 
Amazon EC2 P5 Instances Yes 
Amazon EC2 Trn1 Instances Yes 
Amazon EC2 Trn2 Instances Yes 
Amazon EC2 UltraClusters Yes 
Amazon EKS Yes 
Amazon EKS Anywhere Yes 
Amazon Elastic Container Service (Amazon ECS) Yes 
Amazon SageMaker Yes 
MXNet No 
PyTorch No 
TensorFlow No 

Integrations

Amazon Web Services (AWS) Yes 
AWS Deep Learning AMIs No 
AWS Deep Learning Containers No 
AWS Trainium No 
Amazon EC2 Yes 
Amazon EC2 Capacity Blocks for ML No 
Amazon EC2 G4 Instances Yes 
Amazon EC2 Inf1 Instances No 
Amazon EC2 P4 Instances No 
Amazon EC2 P5 Instances No 
Amazon EC2 Trn1 Instances No 
Amazon EC2 Trn2 Instances No 
Amazon EC2 UltraClusters No 
Amazon EKS No 
Amazon EKS Anywhere No 
Amazon Elastic Container Service (Amazon ECS) No 
Amazon SageMaker No 
MXNet Yes 
PyTorch Yes 
TensorFlow Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
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 No 
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 Web Services

Founded

2006

Country

United States

Website

aws.amazon.com/machine-learning/neuron/

Vendor Details

Company Name

Amazon

Founded

2006

Country

United States

Website

aws.amazon.com/machine-learning/elastic-inference/

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 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Infrastructure-as-a-Service (IaaS)

Analytics / Reporting No 
Configuration Management No 
Data Migration No 
Data Security No 
Load Balancing No 
Log Access No 
Network Monitoring No 
Performance Monitoring No 
SLA Monitoring No 

Alternatives

Alternatives

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