# Cluster Introduction ## Purpose The cluster was purchased by the Computer Systems Lab to serve the Parallel Computing and Computer Vision classes, but is available for usage by all TJ students and staff. Several senior research labs have expressed interest in using the cluster's resources for their own purposes. Academic jobs run on the cluster will receive priority allocation of resources, but non-academic jobs are accepted as well as long as they abide by the FCPS Acceptable Use Policy (Regulation 6410). ## Specifications The full cluster consists of 12 HPC cluster nodes, 40 Borg nodes, and 1 dedicated GPU node (zoidberg). This setup occupies almost 3 full racks in the server room. The CSL obtained the 40-node Borg cluster from NASA through an educational grant. The Borg nodes are named borg\[1-40] consecutively and the HPC nodes are named hpc\[1-12]. The login node is `infoprism` ### SSH Access You can directly access any available cluster node through `ssh`. To `ssh` into a cluster node: 1. `ssh` into `remote.tjhsst.edu` using your TJCSL username and password * `ssh 2021abagali1@remote.tjhsst.edu` 2. `ssh` into a cluster node * `ssh borg1` (or any available node) ## Slurm Speaking of SLURM (the Simple Linux Utility for Resource Management), Slurm is the utility used for job control and submission. Users log in to `infoprism`, run some simple commands, specifying what they want to run, how many resources it should have, priority, and other optional arguments, and SLURM takes care of allocating cluster resources for them, and provides job accounting so users know the status of their jobs. More information at our [Slurm docs](/research/using-infoprism.md). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://guides.tjhsst.edu/research/cluster-introduction.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.