This page provides key details about the maintenance schedule and purpose. We will add content with specifics about the maintenance as we complete our planning and building.Maintenance DatesGreat Lakes: June 9-10Armis2/Lighthouse: June 9-12HPC (High-Performance Computing) - All ClustersSummer 2025(version changes in bold)Winter 2025Red Hat 8.10
Advanced Research Computing
ARC Maintenance UpdatesThis page provides key details about the maintenance schedule and purpose.
As of January 13th the /scratch upgrade plan has changed.NOTE: Scratch is a global temporary space and high-value data you cannot part with should not reside there for any extended period of time. It has no backups or replication and is subject to loss in a failure.
This page provides key details about the maintenance schedule and purpose. We will add content with specifics about the maintenance as we complete our planning and building.Maintenance DatesGreat Lakes: June 15Armis2/Lighthouse: June 15-18HPC (High-Performance Computing) - All Clusters Summer 2026
2026 ARC Winter Maintenance ARC Maintenance UpdatesThis page provides key details about the maintenance schedule and purpose.
Review upcoming and previous maintenance periods and updates in Advanced Research Computing.
The Advanced Research Computing (ARC) high-performance computing (HPC) cluster has integrated the Scientific Package Manager Spack (https://spack.io) to streamline software development for users. Spack allows users to build software from its source code or install pre-built binaries directly into their environments.
Armis2 is is a campus-wide HPC cluster suitable for export controlled and HIPAA regulated data, but users are responsible for security and compliance related to sensitive code and/or data. It utilizes Slurm as its workload manager, enabling users to work interactively or submit batch jobs.
Because of the design of Data Den, projects will often need to be bundled to form larger single file archives. The most common tool with which to do this is tar. Tar can also optionally compress the data but can take much longer. We also recommend using archivetar when using the ARC HPC clusters, also available as a container for Linux systems.
Great Lakes is a campus-wide HPC cluster designed to meet the diverse needs of researchers across the university. It supports a variety of applications, including simulation, modeling, machine learning, data science, genomics, and more. The platform offers a well-balanced mix of computing power, I/O performance, storage capability, and GPUs. It utilizes Slurm as its workload manager, enabling users to work interactively or submit batch jobs.