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Introduction to High-Performance Computing: Glossary

Key Points

Why use a Cluster?	High Performance Computing (HPC) typically involves connecting to very large computing systems elsewhere in the world. These other systems can be used to do work that would either be impossible or much slower on smaller systems. HPC resources are shared by multiple users. The standard method of interacting with such systems is via a command line interface.
Connecting to a remote HPC system	An HPC system is a set of networked machines. HPC systems typically provide login nodes and a set of worker nodes. The resources found on independent (worker) nodes can vary in volume and type (amount of RAM, processor architecture, availability of network mounted filesystems, etc.). Files saved on one node are available on all nodes.
Exploring Remote Resources	An HPC system is a set of networked machines. HPC systems typically provide login nodes and a set of compute nodes. The resources found on independent (worker) nodes can vary in volume and type (amount of RAM, processor architecture, availability of network mounted filesystems, etc.). Files saved on shared storage are available on all nodes. The login node is a shared machine: be considerate of other users.
Scheduler Fundamentals	The scheduler handles how compute resources are shared between users. A job is just a shell script. Request slightly more resources than you will need.
Accessing software via Modules	Load software with `module load softwareName`. Unload software with `module unload` The module system handles software versioning and package conflicts for you automatically.
Transferring files with remote computers	`wget` and `curl -O` download a file from the internet. `scp` and `rsync` transfer files to and from your computer. You can use an SFTP client like FileZilla to transfer files through a GUI.
Running a parallel job	Parallel programming allows applications to take advantage of parallel hardware. The queuing system facilitates executing parallel tasks. Performance improvements from parallel execution do not scale linearly.
Using resources effectively	Accurate job scripts help the queuing system efficiently allocate shared resources.
Using shared resources responsibly	Be careful how you use the login node. Your data on the system is your responsibility. Plan and test large data transfers. It is often best to convert many files to a single archive file before transferring.

Glossary

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