This module focuses on the efficient fine-tuning of Stable Diffusion* with 4th generation Intel® Xeon® processors on AWS using Hugging Face* Accelerate and Intel® Extension for PyTorch*.
Learn how to fine-tune nanoGPT on a cluster of Intel Xeon CPUs on AWS.
Learn how to build and register images to Amazon Elastic Container Register (Amazon ECR) for the xgboost-daal4py app and the Lambda inference handler.
Learn how to build accelerated machine learning pipelines using Amazon Elastic Kubernetes Services* (Amazon EKS) with Intel® Optimization for XGBoost*.
This module creates an ECS cluster using the latest Intel® architecture available for the AWS ECS Service.
This repository provides an example to create an Amazon EKS cluster optimized on 3rd generation Intel® Xeon® Scalable processors (formerly code named Ice Lake). The example will be creating an Amazon EKS cluster with an Amazon EKS managed node group.
This module creates an Amazon ElastiCache* for Redis cluster based on Intel architecture and creates a new or existing VPC. This module uses the cache.r5.large by default, which is the latest Intel Xeon processor available at the time of this module publication.
Configuration in this directory creates an AWS VM (instance). The instance is created on a 3rd generation Intel Xeon Scalable processor by default.
Configuration in this directory creates an Amazon RDS for MariaDB instance. The instance is created on an Intel Xeon Scalable processor instance M6i.xlarge by default. The instance is preconfigured with parameters within the database parameter group that is optimized for Intel architecture. The goal of this module is to get you started with a database configured to run best on Intel architecture.
Configuration in this directory creates an Amazon RDS instance for Microsoft SQL Server*. The instance is created on an Intel Xeon Scalable processor instance M6i.xlarge by default. The goal of this module is to get you started with a database that runs on the latest Intel architecture.
Configuration in this directory creates an Amazon RDS instance for MySQL*. The instance is created on an Intel Xeon Scalable processor instance M6i.xlarge by default. The instance is preconfigured with parameters within the database parameter group that is optimized for Intel architecture. The goal of this module is to get you started with a database configured to run best on Intel architecture.
This module can be used to deploy an Intel-optimized Amazon RDS for PostgreSQL* server database instance. Instance selection and PostgreSQL optimization are included by default in the code.


Introduction and Environment Setup (Part 1 of 3)


Resource Creation and Application Deployment (Part 2 of 3)


Application Testing and Summary (Part 3 of 3)

This module focuses on the distributed fine-tuning of Stable Diffusion* on Azure using Hugging Face* Accelerate and Intel® Extension for PyTorch*.
Learn how to fine-tune nanoGPT on an Azure cluster of Intel® Xeon® CPUs.
This module builds an accelerated machine learning pipeline using Intel® Optimization for XGBoost* on an Azure Kubernetes* Services (AKS) cluster.
This module can be used to build confidential Kubeflow* pipelines for machine learning with Intel Optimization for XGBoost and Intel® oneAPI Data Analytics Library (oneDAL) on an AKS cluster.
This module selects Azure v5 instances based on 3rd generation Intel Xeon Scalable processors (formerly code named Ice Lake) for optimal cost and performance. The code will create an AKS cluster with one or many AKS node groups. This example provides parameters to scale the minimum and maximum sizes of the AKS cluster.
This module can be used to create and optimize Azure App Service for Linux* web app.
This module can be used to deploy an Intel-optimized Azure Service Plan. This module favors V3 Premium instances, which run on faster processors.
This modules streamlines provisioning and optimizing of the Azure App Service for Windows*.
Quickly deploy an Intel-optimized Azure Databricks workspace.
Linux Virtual Machines in Azure are optimized to take advantage of built-in acceleration on Intel-based cloud instances.
This module can be used to deploy an Intel-optimized Azure Database for a MySQL* Flexible Server instance. Instance selection and MySQL optimization are included by default in the code.
No need to guess what cloud instance is right for your PostgreSQL* Flexible Server. The Azure Database for PostgreSQL will optimize and select the latest generation instance to deliver optimal performance. You can edit the instance selection if you have already determined what you would like to use.
Take advantage of years of Intel and Microsoft co-engineering with the Azure SQL Managed Instance module. This module will deploy optimizations for Azure SQL Server instances. Instance selection is included by default in the code.


Introduction and Overview (Part 1 of 3)


Hands-on Walk-through (Part 2 of 3)


Summary and Action Items (Part 3 of 3)

Learn how to fine-tune the nanoGPT (124 M parameter) model on a cluster of Intel® Xeon® CPUs on Google Cloud Platform* service.
This module deploys an accelerated Kubeflow* pipeline on Google Cloud Platform service using Intel® Optimization for XGBoost* and daal4py.
This example illustrates how to create a simple regional GKE* cluster within GCP*. The cluster is created on a 4th generation Intel® Xeon® Scalable processor (formerly code named Sapphire Rapids).
This module provides the functionality to ensure that you are using Intel's latest generation processor in the creation of a virtual machine in GCP.

Kubernetes* is the leading software platform for deploying cloud-native workloads across a wide set of use cases. How applications perform depends on how well infrastructure capabilities are used. Intel's work with Kubernetes aims to improve application performance on Intel infrastructures.

 

 

In collaboration with Accenture*, Intel has launched a series of trained AI reference kits to the open source community to help enterprises innovate and accelerate their digital transformation journey. With these kits, Intel further builds upon the AI application tools it provides to data scientists and developers.

 

 

Performance considerations are vital for the overall success of cloud computing. Discover how workloads will perform on Intel-based cloud solutions.