{"id":3505,"date":"2024-05-10T14:14:40","date_gmt":"2024-05-10T21:14:40","guid":{"rendered":"https:\/\/in.nau.edu\/arc\/?page_id=3505"},"modified":"2024-08-14T08:07:42","modified_gmt":"2024-08-14T15:07:42","slug":"apptainer-quickstart","status":"publish","type":"page","link":"https:\/\/in.nau.edu\/arc\/apptainer-quickstart\/","title":{"rendered":"Apptainer – Quickstart Guide"},"content":{"rendered":"\n
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Advanced Research Computing<\/h3>\n <\/div>\n
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Apptainer – Quickstart Guide<\/h1>\n

Apptainer, formerly known as Singularity, is an open-source container platform designed to facilitate the deployment of complex applications on high-performance computing (HPC) clusters. It provides a simple, portable, and reproducible method for running applications, allowing researchers to execute scientific programs without the need for native installation by cluster administrators.<\/p>\n

Understanding Containers<\/h2>\n

Basic Concepts of Containerization<\/h3>\n

Containerization is a method of packaging software so that it can run with its dependencies in isolated environments called containers. These containers are lightweight and include everything needed to run the application: code, runtime, system tools, libraries, and settings.
\nThis technology allows developers to easily deploy applications across different computing environments, from a developer\u2019s laptop to a test environment, from a staging environment into production, and from a physical machine in a data center to a virtual machine in a public or private cloud.<\/p>\n

Difference Between Containers and VM’s<\/h3>\n

Containers and Virtual Machines (VMs) are both technologies used to create efficient, isolated environments for running applications, but they operate differently.
\nA\u00a0container<\/strong>\u00a0encapsulates an application\u2019s code along with its libraries, dependencies, and some lightweight operating system APIs and services, all running on the host\u2019s operating system kernel. This makes containers highly portable and efficient, as they are smaller in size and require less overhead than VMs.
\nOn the other hand, a\u00a0VM<\/strong>\u00a0includes a full copy of an operating system, including its own kernel, on top of a hypervisor which runs on the physical hardware. This means each VM is entirely isolated with its own resources, but this also results in greater resource consumption compared to containers.<\/p>\n

Use Cases for Containers in Scientific Computing<\/h3>\n

Containers have several use cases for scientific computing:<\/p>\n