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support

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Description

The latest Amazon EC2 Trn3 UltraServers represent AWS's state-of-the-art accelerated computing instances, featuring proprietary Trainium3 AI chips designed specifically for optimal performance in deep-learning training and inference tasks. These UltraServers come in two variants: the "Gen1," which is equipped with 64 Trainium3 chips, and the "Gen2," offering up to 144 Trainium3 chips per server. The Gen2 variant boasts an impressive capability of delivering 362 petaFLOPS of dense MXFP8 compute, along with 20 TB of HBM memory and an astonishing 706 TB/s of total memory bandwidth, positioning it among the most powerful AI computing platforms available. To facilitate seamless interconnectivity, a cutting-edge "NeuronSwitch-v1" fabric is employed, enabling all-to-all communication patterns that are crucial for large model training, mixture-of-experts frameworks, and extensive distributed training setups. This technological advancement in the architecture underscores AWS's commitment to pushing the boundaries of AI performance and efficiency.

Description

Amazon SageMaker HyperPod is a specialized and robust computing infrastructure designed to streamline and speed up the creation of extensive AI and machine learning models by managing distributed training, fine-tuning, and inference across numerous clusters equipped with hundreds or thousands of accelerators, such as GPUs and AWS Trainium chips. By alleviating the burdens associated with developing and overseeing machine learning infrastructure, it provides persistent clusters capable of automatically identifying and rectifying hardware malfunctions, resuming workloads seamlessly, and optimizing checkpointing to minimize the risk of interruptions — thus facilitating uninterrupted training sessions that can last for months. Furthermore, HyperPod features centralized resource governance, allowing administrators to establish priorities, quotas, and task-preemption rules to ensure that computing resources are allocated effectively among various tasks and teams, which maximizes utilization and decreases idle time. It also includes support for “recipes” and pre-configured settings, enabling rapid fine-tuning or customization of foundational models, such as Llama. This innovative infrastructure not only enhances efficiency but also empowers data scientists to focus more on developing their models rather than managing the underlying technology.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Trainium Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
AWS Batch Yes 
AWS EC2 Trn3 Instances No 
AWS Inferentia Yes 
AWS ParallelCluster Yes 
Amazon EKS Yes 
Amazon Elastic Container Service (Amazon ECS) Yes 
Amazon SageMaker HyperPod Yes 
Hugging Face Yes 
JAX Yes 
PyTorch Yes 

Integrations

AWS Trainium Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
AWS Batch No 
AWS EC2 Trn3 Instances Yes 
AWS Inferentia No 
AWS ParallelCluster No 
Amazon EKS No 
Amazon Elastic Container Service (Amazon ECS) No 
Amazon SageMaker HyperPod No 
Hugging Face No 
JAX No 
PyTorch No 

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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/ec2/instance-types/trn3/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/ai/hyperpod/

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 

Alternatives

Alternatives

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