Amazon Web Services (AWS) cloud computing service, Elastic Cloud Compute (EC2) provides scalable computing capacity. EC2 eliminates your need to invest in hardware upfront. You can use EC2 to launch as many virtual machines as you need, configure security and networking and manage storage. EC2 enables you to scale up or down to handle changes in requirements, reducing your need to forecast demand.
Users can run Lumerical simulations on EC2, which provides quick, accessible, cost-effective, and scalable computing infrastructure to perform ever-larger volumes of simulations to design and optimize next-generation optoelectronic components, circuits, and systems.
AWS charges are based on the amount of time and storage used. The majority costs incurred when running Lumerical Products on AWS while following our most common use-cases are:
- EC2 (Elastic Cloud Compute) Instances: For EC2 you only pay for what you use on a sub-second basis (while the instance is in the "Running" state). Our uses cases use on-demand instances, however, there are cheaper hourly rates available for longer-term contracts and spot computing instances. See Amazon EC2 pricing for details.
- EBS (Elastic Block Storage): These volumes are used by each EC2 instance as a system drive and are a fixed size set when the instance is launched. Charges are incurred whether the instances are in the "Running" or "Stopped" state. See Amazon EBS Pricing for details.
- EFS (Elastic File System): These volumes are dynamically sized and you only pay for the storage you use. These volumes are used as a shared filesystem between multiple instances. See Amazon EFS pricing for details.
- S3 (Simple Storage Solution): Your price is calculated based on your bucket type (this guide uses Standard), the amount of data you store in a month, and how frequently you access the data. See Amazon S3 Pricing for details.
- Outbound data transfer: there is no charge for inbound data transfers. Outbound data transfer fees can be found here, or in the cost calculator (see below).
While this is not an exhaustive list of AWS services used in our examples, it does cover the vast majority of fees that will be incurred. We always recommend that you use AWS Cost Explorer to monitor your usage closely. You can also use Amazon Cost Calculator to create a detailed cost estimate for your specific needs.
Lumerical License Pricing
To discuss your simulation and cloud computing needs or to request a quote, please contact Ansys Lumerical Sales or your Ansys Account Manager.
To start testing your workflow with AWS you will need to do the following (estimated time: 2 hours - 2 days):
- Create an Amazon Web Services account: Use AWS's wizard to create an AWS account, you will need to provide credit card information which will be used to bill your incurred monthly charges.
- Secure your AWS account following best practices.
- Get an Ansys Lumerical Products License. To request a quote and/or a trial, please contact our sales department or your Ansys Account Manager.
- Access to Ansys Lumerical Quick Start AMIs (if this use case is selected).
- Ansys Lumerical user account for access to product downloads.
Once you have completed the prerequisites you are now ready to start creating resources in AWS. For all deployments of Lumerical Products on the cloud, you will need to configure a network for your cluster and create a License Server (estimated time: 1 hour):
- Setting up your VPC, Subnet, and Security Group
- Using S3 Buckets
- Keys (key pairs), IAM Roles, and AWS CLI
Using Lumerical Quick-start Linux AMI
- Getting access to Lumerical quick-start Linux AMIs
- Creating the Ansys Lumerical license server instance
- Creating the Ansys Lumerical products/compute instance
Creating an EC2 Instance
- Creating a Windows License server instance
- Creating a Windows Lumerical compute instance/AMI
- AWS Tutorial: Get started with EC2 Linux
We have created the following guides for the most common use-case with a variety of computing resources and features for you to follow along with and modify to best suit your needs (estimated time 30 minutes - 2 hours):
- Use Case: Create a single Windows or Linux workstation.
- Use Case: Create a multi-node Linux cluster using launch templates.
- Use Case: Auto-Scaling Cluster with a SLURM Job Scheduler (or QSUB or Torque) using AWS ParallelCluster:
If you're not sure which use case to select, we recommend the Use Case: Single Large Workstation. After completing this guide you will be able to easily launch as many pre-configured Lumerical Product instances of varying EC2 resource configurations within minutes of each other, eg. 1 x (c5.24xlarge), 10 x (c5.24xlarge), 2 x (5 x (m5.24xlarge)).
Lumerical-AWS Python Integration Module (Deprecated)
The AWS-Python integration module allows running FDTD parameter sweeps or optimizations on AWS-EC2 from the Python command prompt or the FDTD CAD's script prompt.