Issue link: https://read.uberflip.com/i/1187300
Amazon Web Services – HPC Lens AWS Well-Architected Framework Page 33 Within each instance family, one or more instance sizes (see the Instance Type Matrix 7 ), allow vertical scaling of resources. Some applications require a larger instance type (for example, 16xlarge) while others run on smaller types (for example, large). Many smaller instances may be preferred for an HPC application over fewer larger instances. Applications vary in their requirements (for example, desired cores, processor speed, memory requirements, storage needs, and networking specifications). When selecting an instance family and type, start with the specific needs of the application. Instance types can be mixed and matched for applications requiring targeted instances for specific application components. Containers are a method of operating system virtualization that are attractive for many HPC workloads, particularly if the applications have already been containerized. AWS services such as AWS Batch, Amazon Elastic Container Service (ECS), and Amazon Elastic Container Service for Kubernetes (EKS) help deploy containerized applications. Functions abstract the execution environment. AWS Lambda allows you to execute code without deploying, running, or maintaining, an instance. Many AWS services emit events based on activity inside the service, and often a Lambda function can be triggered off of service events. For example, a Lambda function can be executed after an object is uploaded to Amazon S3. Many HPC users use Lambda to automatically execute code as part of their workflow. The following example question focuses on compute resources: HPCPERF 1: How do you select your compute solution? There are several choices to make when launching your selected compute instance: Operating system: A current operating system is critical to achieving the best performance and ensuring access to the most up-to-date libraries. Virtualization type: Hardware virtual machine (HVM) Amazon Machine Images (AMIs) can take advantage of special hardware extensions (CPU, network, and storage) for better performance. The HVM virtualization type is