New pages
Jump to navigation
Jump to search
16 June 2026
- 09:5509:55, 16 June 2026 Fair Use Policy (hist | edit) [922 bytes] Haars0011 (talk | contribs) (Phase 2 P2.8: create stub for Fair Use Policy — placeholder pending full policy text (via create-page on MediaWiki MCP Server))
- 09:4109:41, 16 June 2026 Monitoring Jobs (hist | edit) [9,574 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.7: merge Using Slurm § Monitoring + Monitoring job execution + SACCT + Node usage graph into Monitoring Jobs (via create-page on MediaWiki MCP Server))
- 09:2809:28, 16 June 2026 Batch Jobs (hist | edit) [8,772 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.4: merge Creating sbatch script + Using Slurm § Submitting into Batch Jobs (via create-page on MediaWiki MCP Server))
- 09:1909:19, 16 June 2026 Interactive Jobs (hist | edit) [2,234 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.5: split Interactive Jobs out of Using Slurm § sinteractive + § salloc (via create-page on MediaWiki MCP Server))
- 09:0609:06, 16 June 2026 Cancelling Jobs (hist | edit) [527 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.8: split Cancelling Jobs out of Using Slurm § scancel (via create-page on MediaWiki MCP Server))
- 09:0609:06, 16 June 2026 Choosing a node (constraints) (hist | edit) [2,598 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.3: split Choosing a node (constraints) out of Using Slurm § Defaults + § Using GPU (via create-page on MediaWiki MCP Server))
- 09:0609:06, 16 June 2026 Partitions / Queues (hist | edit) [1,181 bytes] Haars0011 (talk | contribs) (Phase 1 § 4 P1.4.2: split Partitions / Queues out of Using Slurm § Queues (via create-page on MediaWiki MCP Server))
11 June 2026
- 09:1709:17, 11 June 2026 Linux Basic/Linux Self Assessment (hist | edit) [6,535 bytes] Honfi001 (talk | contribs) (Created page with "= Linux Basics — Self-Assessment = This page lets you verify that you have mastered the material from the Linux Basics Course. Work through the parts in order on '''Anunna'''. The final challenge produces a report file that proves you completed every step — submit (or keep) that file as evidence. '''Prerequisites:''' an Anunna account and the course data at <code>/lustre/shared/hpcCourses/shell-lesson-data.zip</code>. '''Rules:''' * Do everything from the comm...")
14 April 2026
- 12:4412:44, 14 April 2026 Support (hist | edit) [1,046 bytes] Prins0891 (talk | contribs) (Created page with "Support")
25 March 2026
- 09:4209:42, 25 March 2026 Tutorials/Apptainer-GPUs (hist | edit) [7,606 bytes] Honfi001 (talk | contribs) (Created page with "= Running Apptainer with GPUs = Apptainer can pass through GPU hardware from the host into a container, allowing you to run GPU-accelerated workloads (such as deep learning inference or training) inside a fully contained environment. This page covers how to use both NVIDIA and AMD GPUs on the Anunna cluster. '''Important:''' Before you begin, make sure the following are in place: * Your <code>.sif</code> image files should be stored on '''Lustre''' (e.g. in your scrat...")
- 09:1809:18, 25 March 2026 Tutorials/Apptainer-Introduction (hist | edit) [5,751 bytes] Honfi001 (talk | contribs) (Created page with "= Introduction to Apptainer = == What is Apptainer? == Apptainer (formerly known as Singularity) is a container platform designed for High Performance Computing (HPC) environments. If you have heard of Docker, Apptainer solves a similar problem — it lets you package an application together with all of its dependencies (libraries, tools, configuration) into a single portable unit called a '''container'''. The key difference is that Apptainer was built from the ground...")