Choose Supported EC2 Instance Machine Types

When you create a cluster, you must select a Headnode Machine Type and a Worker Machine Type from the list. You can also edit the instance type on existing clusters. Amazon® Web Services (AWS®) provides instance types with various combinations of CPU, GPU, memory, network performance, and storage. Choose an instance that suits your application. For more information on instance types, see the AWS documentation on Amazon EC2 instance types.

Tip

For deep learning, choose an instance with NVIDIA® 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.

For clusters, Cloud Center supports only the instance types belonging to the instance classes in the table below. For example, the instance type m5.8xlarge is supported as it belongs to the instance class m5. To check support for NVIDIA GPU architectures by MATLAB release, consult the column GPU Architecture and Compute Capability and compare it with the information in GPU Computing Requirements (Parallel Computing Toolbox).

For pricing and billing information, see the Amazon web site: Amazon EC2 Pricing.

Reserved Instances

Note

  • For clusters, Cloud Center supports reserved instances in addition to On-demand. Cloud Center does not support dedicated or spot instances.

  • Cloud Center supports at most one worker per physical core. Although Amazon Web Services machines can have many virtual cores, Cloud Center restricts use to at most one worker per physical core for optimal performance. Each physical core has two virtual cores with a shared Floating Point Unit. Most MATLAB computations use this unit because they are double-precision floating point. Restricting to one worker per physical core ensures that each worker has exclusive access to a Floating Point Unit and optimizes performance.

For machines with GPUs, for optimal performance, use only 1 worker per GPU in the machine.

To use reserved instances for clusters with Cloud Center, you need to purchase reserved instances with the following Cloud Center supported attributes:

  • Instance type: one of the machine types supported by Cloud Center for clusters, to identify supported instances, consult the table above.

  • Platform description: Linux.

  • Tenancy: default.

  • Region: one of regions supported by Cloud Center for clusters (US East (N.Virginia), EU West (Ireland), AP Northeast (Tokyo)).

  • Availability Zone: Availability Zone within the selected region, must match the Availability Zone of the subnet selected.

AWS Resource Limits

The maximum number of instances that you can start in Cloud Center depends on your AWS On-demand instance limits. On-demand instance limits determine the maximum number of virtual central processing units (vCPUs) that you can use. In most cases, a physical core corresponds to 2 vCPUs. For example, a m5.8xlarge instance has 16 physical CPU cores, which corresponds to 32 vCPUs. To determine how many vCPUs you need, use the vCPU limits calculator, which you can find in your AWS EC2 console by selecting Limits>Calculate vCPU limit. For more information on On-demand instance limits, see On-Demand Instances.

In some subnets (availability zones), GPU machines might be scarce. You can try different subnets in the current VPC or a different VPC or in different regions to find available GPU machines.

For more information on AWS EC2 limits for any type of resource, see Amazon EC2 Service Quotas.

See Also

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