Create and Manage Cloud Center Clusters

Create and manage cloud clusters

Create and manage cloud clusters, and customize an Amazon^® Machine Image (AMI). Before you create a cluster, see AWS Identity and Access Management (IAM).

Cluster Operations

Create and Discover Clusters

Create and discover cloud clusters.

View, Edit, Start, or Stop Clusters

Find detailed information about your clusters, change your cluster characteristics, or shut down clusters.

Configure AWS VPC for Cloud Center

Create VPC and subnets, and connect to MATLAB^® Parallel Server™ running on the Amazon EC2^® cloud.

Global Cluster Access and Security Groups

How to access your cluster and limit access for security reasons.

Cluster Attributes

Sharing Options for Clusters

Specify a cluster's Shared State to be either Personal or Shareable.

Manage Cluster Access Automatically

Auto-Manage Cluster Access allows Cloud Center to manage a cluster’s inbound firewall rules on a cluster-by-cluster basis.

Choose Supported EC2 Instance Machine Types

Learn which instance types are supported.

Use a Dedicated Headnode Instance for Management Services

How to use a dedicated machine for management services.

Resize Clusters Automatically

How to allow cluster to resize automatically based on workload.

Cluster File System and Storage

How to access shared folders on your cluster.

Create a Custom Amazon Machine Image (AMI)

How to use an AMI to install drivers, libraries, or other utilities.

Cluster Examples

Scale Up from Desktop to Cluster (Parallel Computing Toolbox)

Develop your parallel MATLAB® code on your local machine and scale up to a cluster.

Process Big Data in the Cloud (Parallel Computing Toolbox)

This example shows how to access a large data set in the cloud and process it in a cloud cluster using MATLAB® capabilities for big data.

Use parfor to Train Multiple Deep Learning Networks (Deep Learning Toolbox)

This example shows how to use a parfor loop to perform a parameter sweep on a training option.

Optimize CSI Feedback Autoencoder Training Using MATLAB Parallel Server and Experiment Manager (Communications Toolbox)

Accelerate determination of the optimal training hyperparameters for a channel state information (CSI) autoencoder by using a Cloud Center cluster and Experiment Manager. (Since R2024a)