Academic High-Performance Computing Cluster

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Overview

The Academic High-Performance Computing (HPC) cluster provides a high-performance computing cluster for use in teaching and learning. HPC refers to the use of powerful computers and parallel processing techniques to solve complex problems and perform large-scale computations at high speeds.

Access and Usage Guidelines

  • The cluster is not to be used for research.
  • Instructors must request access for course members each semester. Access will be revoked at the end of the semester unless a renewal request is submitted.
  • All data processed, transferred, or stored during and after use of the environment must comply with the University Data Classification & Handling Standard.

Technical Specifications and Standards

Computing Resources

  • CPU: 16 cores
  • Memory: 24 GB
  • GPU Nodes: 1
  • Compute Nodes: 2
  • Job Runtime: Up to 8 hours per job

Storage Quota  

  • 20 GB / User

Backups and File Retention

  • Backups services are NOT provided for user data.
  • Users are responsible for maintaining backups of data or in OneDrive.

Get Started

Using the Academic HPC

Academic HPC - Connecting to Open OnDemand

Open OnDemand (OOD) provides a user-friendly web interface for accessing the Academic High-Performance Computing (HPC) environment, enabling users to run jobs, manage files, and use interactive applications.

Academic HPC - Running Jobs Using Open OnDemand

This guide walks users through the process of submitting jobs to the Academic HPC cluster using Open OnDemand.

Software Installation Request

  • Before installation, software undergoes a thorough review to ensure compliance with security and data protection standards. Software must be approved by the Information Security Office before installation.
  • The review process may take 4–8 weeks.

Related Policies

 
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Related Articles (2)

Open OnDemand (OOD) provides a user-friendly web interface for accessing the Academic High-Performance Computing (HPC) environment, enabling users to run jobs, manage files, and use interactive applications.
This guide walks users through the process of submitting jobs to the Academic HPC cluster using Open OnDemand.