Create and Discover Clusters

Create a Cloud Cluster

If you are new to cloud clusters, see Getting Started with Cloud Center.

Sign in to Cloud Center at https://cloudcenter.mathworks.com.
If you have never used Cloud Center before, there is a one-time setup to link your cloud account with Cloud Center. See Link Your Cloud Account to Cloud Center.
To start any cloud resources, click the Cloud Resources tab.
Next to MATLAB^® Parallel Server™, click Create.

On the Create Cluster page, specify your cluster options.

Tip

Specify a cluster name and click Create Cluster to try a default cluster. Cloud Center prompts you if you need to create a new SSH key. You might want to configure other cluster settings, such as cluster size, machine types and storage options. For example, for deep learning, choose a Machine type with GPUs such as the P3, G4dn, or G5 instances.

Option	Description
Give this cluster a name	Specify a name.
MATLAB Version	Select the same version as your local desktop client MATLAB.
Automatically terminate cluster	Select a timeout for the cluster so that it shuts down automatically.
Cluster Log Level	Change the cluster log level. If you need to diagnose cluster issues with support engineers, increase the log level for more detail. Log levels above Medium can negatively impact performance.
Location & Network	Select the Region where your cluster will run. Consider your location and connectivity. Select a Network and Subnet that meet the requirements for Connecting a Desktop Computer (Client Machine) to MATLAB Parallel Server Running on the Amazon EC2 Cloud. You can only use the Amazon Virtual Private Cloud (VPC) network type with Cloud Center. For more information, see Configure AWS VPC for Cloud Center.
Shared State	Select Personal Cluster or Shareable Cluster. See Sharing Options for Clusters.
	Personal Cluster (default) - A personal cluster is one that is accessible only by you. Auto-Manage Cluster Access - This attribute is checked by default. Deselect this option if you prefer to manage cluster access to and from MATLAB manually. Dedicated headnode - Leave the dedicated headnode checked (by default when you select Personal Cluster) to have your cluster access files on your MATLAB Drive™ (read-only).
	Shareable Cluster - Shareable clusters can be shared with other people. Shared With (R2019b only) — Enter the email addresses and/or domains of people that are allowed to access your cluster. Auto-Manage Cluster Access — This attribute is deselected when you specify a Shareable Cluster. Check this option if you prefer to have Cloud Center manage the access to and from MATLAB.
Auto-Manage Cluster Access	Auto-Manage Cluster Access automatically manages inbound cluster firewall rules that allow MATLAB or MATLAB Online™ to interact with the cluster. See Manage Cluster Access Automatically.
	Selected - Allows Cloud Center to manage a cluster’s inbound firewall rules.
	Deselected - Manually manage a cluster's inbound firewall rules.
Worker Machine Type	Choose an instance that suits your application. Types vary by hardware specification, including number of cores, memory, and GPU support. For details, see Choose Supported EC2 Instance Machine Types. Tip For deep learning, choose a machine type with GPUs such as the P3, G4dn, or G5 instances. P3s have GPUs with high performance for general computation. G4dn and G5 instances have GPUs with high single-precision performance for deep learning, image processing, computer vision, and automated driving simulations.
Workers per Machine	The maximum number of workers per machine depends on your selected Worker Machine Type, and it corresponds to the number of physical CPU cores.
Use a dedicated headnode	Enabled (default) - Add a headnode instance that only runs management services (for example, the job manager or MATLAB Drive), and does not host any MATLAB workers. Cloud Center uses the instance type shown in Headnode Machine Type (read-only). This mode improves performance. For details, see Use a Dedicated Headnode Instance for Management Services.
Use a dedicated headnode	Disabled - The headnode shares the job manager and workers. This mode minimizes machine cost, but can reduce performance. For details see Use a Shared Instance for Management Services.
Allow cluster to auto-resize	Enabled - The number of machines in your cluster will shrink or grow depending on the amount of work submitted to the cluster. Set Workers in Cluster to the maximum number of workers you want in the cluster. You must use a dedicated headnode to enable the auto-resize feature. For more information, see Resize Clusters Automatically.
Allow cluster to auto-resize	Disabled (default) - The number of machines in your cluster remains fixed at the number of workers set by Workers in Cluster.
Workers in Cluster	Choose the number of workers, using the Upper Limit menu. If you select a number greater than the Workers per Machine, you see the Machines in Cluster information update to show more than one machine. Cloud Center supports a maximum of 1024 workers per cluster. The Initial Count field shows the number of workers your cluster will start with. If Allow cluster to auto-resize is disabled, the Initial Count field matches your Upper Limit selection. If Allow cluster to auto-resize is enabled, the Upper Limit menu sets the maximum number of workers for your cluster, in increments of Workers per Machine. The Initial Count field is zero. You cluster starts with zero workers and can resize up to the maximum number of workers. For more information, see Resize Clusters Automatically.
Cluster Shared Storage, Local Machine Storage	For details, see Cluster File System and Storage.
SSH Key	If you do not have a key, Cloud Center prompts you to create one. AWS requires an SSH key to start EC2 instances. Click create a new key, in the dialog box, enter a name, and click Download Key. Your browser might require you to identify a location. You get a root access key file with the extension `.pem`. Store this file in a safe place, because you cannot download it again. However, you can always create a new key, and download its key file. You can specify the same SSH key for multiple clusters. If you want to log in as ubuntu (root) to your cloud cluster machines, you need the root SSH key. Cluster machines have no password, so you use a key to log in using SSH. Cloud Center also provides a clouduser (nonroot) user access key file, which is unique to each cluster. For details on the user access key file, see Download SSH Key Identity File. If you have existing keys, select from the keys for the specified region of your AWS account, or create a new key. Otherwise, Cloud Center uses the previously selected key or the first key listed alphabetically in the AWS account.
Operating System Image (AMI)	If you have created a custom AMI, you can select it. See Create a Custom Amazon Machine Image (AMI).

Click Create Cluster to create and start your cluster machines. The cluster starts a number of machines (instances) determined by your choices of number of workers and workers per machine. Cloud Center displays the cluster status Starting, and indicates the interim status of all the cluster machines.
It can take up to several minutes for a cluster to completely start up. The status indicates the stages of the process. To get status on any individual cluster machine, under Cluster Details, click Headnode or Worker expanders.
When the cluster is started and ready for use, Cloud Center displays the cluster status as Online.

Tip

For next steps using your new cluster, discover the running cluster from MATLAB. See Discover Clusters.

This figure shows an example of Create Cluster settings for a personal cluster.

Create Cluster window with example settings for a personal cluster. Set the Shared State in the Cluster Configuration to Personal Cluster.

This figure shows an example of Create Cluster settings for a shareable cluster.

Create Cluster window with example settings for a shareable cluster. Set the Shared State in the Cluster Configuration to Shareable Cluster.

This figure shows a typical shareable cluster status after starting a standard 16-worker cluster with a 2-hour time limit.

Cluster Summary window. The Default Run Time field is 2 Hours, Workers per Machine is 16 and the Shared State under More Details is Shareable.

If the cluster fails to start completely, its status will indicate that. For information on the failure, under Cluster Details, click the appropriate Headnode or Worker expander to read the respective log. Often you can shut down your failed cluster and attempt to start it again.

Discover Clusters on Local Machine

To access a running cluster created in your account, use Discover Clusters from MATLAB. See Discover Clusters.

Alternatively, it can be useful to download and share the cluster profile. When your cloud cluster is starting or online, click MATLAB Cluster Profile to save a cluster profile from Cloud Center onto your local machine or MATLAB Drive, allowing you to access that cluster from MATLAB and the Cluster Profile Manager. Save the profile in a folder accessible from your client MATLAB. See Import Cluster Profiles.