AWS Marketplace: Habana® Deep Learning EKS AMI Kubernetes 1.29 (Ubuntu22.04)

Overview

The Habana Deep Learning EKS AMI is built on top of Ubuntu22.04, and is configured to serve as the base image for Habana Gaudi AI Processor instances in Amazon EKS Clusters

Highlights

Gaudi has been designed from the ground up for accelerating Deep Learning training workloads in datacenters
Provides AI developers with fast and easy access to Gaudi in the cloud, to be used with optimized deep learning framework containers from Habana

Details

Sold by

Habana Labs

Typical total price

This estimate is based on use of the seller's recommended configuration (dl1.24xlarge) in the US East (N. Virginia) Region. View pricing details

$13.109/hour

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Pricing

Habana® Deep Learning EKS AMI Kubernetes 1.29 (Ubuntu22.04)

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Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.

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Region

Usage costs (1)

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Instance type	Product cost/hour	EC2 cost/hour	Total/hour
dl1.24xlarge Recommended	$0.00	$13.109	$13.109

Additional AWS infrastructure costs

Type	Cost
EBS General Purpose SSD (gp2) volumes	$0.10/per GB/month of provisioned storage

Vendor refund policy

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Usage information

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Delivery details

64-bit (x86) Amazon Machine Image (AMI)

Amazon Machine Image (AMI)

An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

Version release notes

https://docs.habana.ai/en/latest/Release_Notes/GAUDI_Release_Notes.html

Additional details

Usage instructions

Launch EC2 Instance and use ubuntu as the username to ssh into the instance
Follow instructions in the following repo about Running/Pulling Docker Containers https://github.com/HabanaAI/Setup_and_Install
Follow Guides below for getting started with PyTorch (https://docs.habana.ai/en/latest/PyTorch_User_Guide/PyTorch_User_Guide.html )

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