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What is Amazon EC2 Capacity Blocks for ML?

Amazon EC2 Capacity Blocks are designed for machine learning, allowing users to secure accelerated compute instances within Amazon EC2 UltraClusters that are specifically optimized for their ML tasks. This service encompasses a variety of instance types, including P5en, P5e, P5, and P4d, which leverage NVIDIA's H200, H100, and A100 Tensor Core GPUs, along with Trn2 and Trn1 instances that utilize AWS Trainium. Users can reserve these instances for periods of up to six months, with flexible cluster sizes ranging from a single instance to as many as 64 instances, accommodating a maximum of 512 GPUs or 1,024 Trainium chips to meet a wide array of machine learning needs. Reservations can be conveniently made as much as eight weeks in advance. By employing Amazon EC2 UltraClusters, Capacity Blocks deliver a low-latency and high-throughput network, significantly improving the efficiency of distributed training processes. This setup ensures dependable access to superior computing resources, empowering you to plan your machine learning projects strategically, run experiments, develop prototypes, and manage anticipated surges in demand for machine learning applications. Ultimately, this service is crafted to enhance the machine learning workflow while promoting both scalability and performance, thereby allowing users to focus more on innovation and less on infrastructure. It stands as a pivotal tool for organizations looking to advance their machine learning initiatives effectively.

What is AWS Elastic Fabric Adapter (EFA)?

The Elastic Fabric Adapter (EFA) is a dedicated network interface tailored for Amazon EC2 instances, aimed at facilitating applications that require extensive communication between nodes when operating at large scales on AWS. By employing a unique operating system (OS), EFA bypasses conventional hardware interfaces, greatly enhancing communication efficiency among instances, which is vital for the scalability of these applications. This technology empowers High-Performance Computing (HPC) applications that utilize the Message Passing Interface (MPI) and Machine Learning (ML) applications that depend on the NVIDIA Collective Communications Library (NCCL), enabling them to seamlessly scale to thousands of CPUs or GPUs. As a result, users can achieve performance benchmarks comparable to those of traditional on-premises HPC clusters while enjoying the flexible, on-demand capabilities offered by the AWS cloud environment. This feature serves as an optional enhancement for EC2 networking and can be enabled on any compatible EC2 instance without additional costs. Furthermore, EFA integrates smoothly with a majority of commonly used interfaces, APIs, and libraries designed for inter-node communications, making it a flexible option for developers in various fields. The ability to scale applications while preserving high performance is increasingly essential in today’s data-driven world, as organizations strive to meet ever-growing computational demands. Such advancements not only enhance operational efficiency but also drive innovation across numerous industries.

Media

Media

Integrations Supported

AWS Nitro System
Amazon EC2
Amazon Web Services (AWS)
PyTorch
TensorFlow
AWS HPC
AWS Neuron
AWS Trainium
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Caffe
Greenovative
MXNet
OpenFOAM
SAP Store

Integrations Supported

AWS Nitro System
Amazon EC2
Amazon Web Services (AWS)
PyTorch
TensorFlow
AWS HPC
AWS Neuron
AWS Trainium
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Caffe
Greenovative
MXNet
OpenFOAM
SAP Store

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/capacityblocks/

Company Facts

Organization Name

United States

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/hpc/efa/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

HPC

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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