Open OnDemand User Guide HPC Cluster @ Vogelwarte Version 1.0 | Last Updated: December 2025 | Thx to Claude Code Introduction What is Open OnDemand? Open OnDemand (OOD) is a web-based portal that provides easy access to the VoWa HPC cluster. Through your web browser, you can: Launch interactive applications (JupyterLab, RStudio, VS Code, Remote Desktop) Manage files on the cluster Access terminal shells Submit and monitor computational jobs Work with your research data Accessing Open OnDemand Portal URL: https://hpc.vogelwarte.ch Authentication: Single Sign-On (SSO) via your Vogelwarte Microsoft/Azure AD account Requirements: A modern web browser (Chrome, Firefox, Edge, or Safari) Vogelwarte network access (VPN if working remotely) Active Vogelwarte account with HPC access permissions Getting Started First Login Navigate to https://hpc.vogelwarte.ch Click the login button Authenticate using your Vogelwarte credentials (same as email/Office 365) You'll be redirected to the Open OnDemand dashboard Dashboard Overview After logging in, you'll see the OOD dashboard with: Pinned Apps : Quick access to frequently used applications Files : File browser for managing your data Jobs : View and manage your running computational jobs Clusters : Shell access to cluster nodes Interactive Apps : Launch graphical applications Storage Access Your home directory and shared storage are automatically accessible: Location Path on hpc Path on Windows (Mac) Purpose Home Directory ~/ or /home/vogelwarte.ch/[username] \\pallidus.vogelwarte.ch\[username] Personal files and settings SciData ~/SciData Z:\SciData Shared scientific data storage (CephFS) Scratch ~/scratch Z:\SciData\ORG_Vogelwarte\scratch High-performance temporary storage Data /mnt/ceph Direct access to CephFS shared storage Note: The SciData and scratch directories are symbolic links created automatically in your home directory for convenient access. Interactive Applications Open OnDemand provides several interactive applications that run on compute nodes with dedicated resources. JupyterLab Description: Modern web-based interface for Jupyter notebooks, code editing, and data visualization. Pre-installed Packages: Python data science stack: NumPy, Pandas, Scikit-learn Visualization: Matplotlib, Seaborn JupyterLab, IPython kernel How to Launch: Click Interactive Apps → JupyterLab Configure your session: Account : Select your Slurm account (usually sci_it or root ) Partition : Choose compute for general work Number of cores : 1-16 (start with 2) Memory (GB) : 1-64 (start with 4) Hours : Maximum session time (1-72 hours) Click Launch Wait for the job to start (status: Queued → Running) Click Connect to JupyterLab when ready Tips: Start small (2 cores, 4GB RAM) and increase if needed Save your work frequently Your notebooks are saved in your home directory Use ~/SciData for accessing shared datasets RStudio Server Description: Full RStudio IDE in your browser for R programming and statistical analysis. Pre-installed Packages: Core: tidyverse, ggplot2, dplyr, data.table Spatial: sf, tmap, rnaturalearth, amt Statistics: randomForest, ranger, Bayesian tools (NIMBLE, JAGS) Data: RPostgres, DBI, readr, readxl Visualization: viridis, bayesplot, kableExtra And many more (see full list in role configuration) How to Launch: Click Interactive Apps → RStudio Server Configure your session: Account : Select your Slurm account Partition : Choose compute Number of cores : 1-16 (start with 2) Memory (GB) : 4-64 (R can be memory-intensive, start with 8GB) Hours : Session duration Click Launch Wait for job allocation Copy password because for security reason there is a temprary login Click Connect to RStudio Server Enter login [username] and copied temporary password Tips: RStudio sessions use more memory than JupyterLab (request at least 8GB) Install additional packages with install.packages() (saved in your home directory) Use renv for reproducible project environments Connect to PostgreSQL databases using RPostgres package Parallel processing available with foreach and doParallel packages VS Code Server (Code Server) Description: Full-featured Visual Studio Code development environment in your browser. Pre-installed Tools: Python: Development: black, flake8, pylint Interactive: IPython, Jupyter Data Science: pandas, numpy, matplotlib, seaborn Utilities: requests, pytest JavaScript/TypeScript: TypeScript compiler ESLint, Prettier Node.js and npm System Tools: Git, vim, wget, curl Build tools (gcc, make) How to Launch: Click Interactive Apps → Code Server Configure your session: Account : Select your Slurm account Partition : Choose compute Number of cores : 1-8 (start with 2) Memory (GB) : 2-32 (start with 4) Hours : Session duration Click Launch Copy temporary password Connect when ready Enter temporary password Tips: Install VS Code extensions from the marketplace Settings and extensions persist in your home directory Use integrated terminal for command-line access Great for multi-language projects Git integration built-in Remote Desktop (MATE) Description: Full Linux desktop environment with graphical applications. Use Cases: Running GUI applications (GIS tools, visualization software) Using applications not available in other interfaces Traditional desktop workflow How to Launch: Click Interactive Apps → Desktop Configure resources (similar to other apps) Choose MATE desktop environment Launch and connect Use the desktop like a regular Linux workstation Tips: Requires more resources (start with 4 cores, 8GB RAM) Best for applications that require GUI Can run multiple terminal windows Copy/paste between your local machine and remote desktop Resource Selection Guidelines Choosing the right resources helps you get work done efficiently without wasting cluster capacity: Application Typical Use Cores Memory Duration JupyterLab Data exploration 2 4 GB 2-4 hours JupyterLab Data processing 4-8 8-16 GB 4-8 hours RStudio Interactive analysis 2-4 8 GB 2-4 hours RStudio Large datasets 8-16 32-64 GB 4-8 hours Code Server Development 2 4 GB 4-8 hours Desktop GUI applications 4 8 GB 2-4 hours Remember: You can always launch a new session with more resources if needed. Start small and scale up. File Management Files App The built-in file manager lets you: Browse your home directory and shared storage Upload/download files Create, rename, move, and delete files/folders Edit text files directly in the browser View file permissions Accessing the File Manager: Click Files in the top menu Choose a location: Home Directory : Your personal files SciData : Shared scientific data Any custom path Common Operations: Upload : Click Upload button, select files Download : Right-click file → Download Create Folder : Click New Folder Edit File : Click on text file to open editor Move/Copy : Select files → Use toolbar buttons Change Permissions : Right-click → Change Permissions Data Transfer Small Files (<100 MB): Use the web file manager upload/download feature. Large Files (>100 MB): Use command-line tools via shell access: # From your local machine to cluster scp large_file.tar.gz username@hpc.vogelwarte.ch:/home/username@vogelwarte.ch/ # Using rsync for efficient transfer rsync -avzP local_directory/ username@hpc.vogelwarte.ch:~/remote_directory/ # From cluster to local machine scp username@hpc.vogelwarte.ch:~/results.zip ./ Shared Data Storage: Use ~/SciData for data that needs to be shared with collaborators Use ~/scratch for temporary high-performance storage Regular backups are performed on home directories, not scratch Shell Access Cluster Shell Access Open OnDemand provides web-based terminal access to the cluster. How to Access: Click Clusters in the top menu Select Shell Access or your cluster name A terminal window opens in your browser What You Can Do: Run command-line tools Submit batch jobs with Slurm Check job status Compile code Manage files with CLI tools Session Timeouts: Inactive timeout : 5 minutes (default) Maximum duration : 1 hour (default) Sessions close automatically after timeout for security Tips: Use interactive apps for long-running work For persistent sessions, use tmux or screen Shell ping-pong can be enabled (contact admin) for keep-alive Basic Slurm Commands If you need to submit batch jobs from the shell: # View partition information sinfo # Submit a batch job sbatch job_script.sh # Check your job queue squeue -u $USER # Cancel a job scancel # View job details scontrol show job # View cluster usage squeue Note: Most users will use interactive apps and won't need to submit batch jobs directly. Best Practices Resource Management Request Appropriate Resources Don't over-request cores/memory you won't use Start small and scale up if needed Consider other users sharing the cluster Session Duration Choose realistic time limits Terminate sessions when done (don't leave them running) Save your work frequently Data Storage Home directory: Personal files, code, small datasets SciData: Shared datasets, collaborative projects Scratch: Temporary high-I/O work (files may be deleted) Security Authentication Never share your credentials Log out when finished Use VPN when accessing remotely Data Handling Don't store sensitive data without proper permissions Check file permissions for shared data Follow institutional data policies Performance Efficient Computing Close unused applications to free resources Use appropriate partitions for your work Optimize code before requesting large resources File Operations Use rsync for large transfers Avoid many small file operations Clean up old files and data regularly Troubleshooting Common Issues Issue: Cannot log in Solution : Verify VPN connection, check credentials, contact IT Issue: Interactive app won't start (stays in "Queued" state) Possible causes: Cluster is busy (wait a bit) Requested resources exceed limits Requested partition doesn't exist Solution : Try reducing resources or contact support Issue: Session disconnected unexpectedly Possible causes: Network interruption Session timeout Cluster maintenance Solution : Reconnect; your work may be saved depending on the application Issue: Application runs out of memory Solution : Terminate and relaunch with more memory Issue: Can't access shared data Possible causes: Permissions issue Mount point not available Solution : Check file permissions, contact admin if storage mount is down Issue: Files don't appear in file manager Solution : Refresh browser, check path, verify permissions Getting Help Before Contacting Support: Note the exact error message Record what you were trying to do Check this guide and FAQs Try basic troubleshooting steps Session Information: When reporting issues with interactive apps, provide: Application name (JupyterLab, RStudio, etc.) Session ID (visible in "My Interactive Sessions") Time of issue Error messages Support Documentation This Guide : Comprehensive user documentation Open OnDemand Official Docs : https://osc.github.io/ood-documentation/ Slurm Documentation : https://slurm.schedmd.com/documentation.html Contact VoWa HPC Support Team Email : scientific.it@vogelwarte.ch What to Include in Support Requests: Your username Description of the issue Steps to reproduce Error messages (screenshots helpful) Application and session information System Status Check Cluster Status: Dashboard shows current cluster availability Maintenance windows announced via email Emergency maintenance posted on login page Appendix Slurm Accounts Your jobs run under Slurm accounts for resource tracking: Account Description Typical Use sci_it IT Science Account General scientific computing root Root Account Administrative or special projects Check your accounts: sacctmgr show user $USER Partitions Compute resources are divided into partitions: Partition Description Typical Resources normal General computing Standard CPU nodes Software Environment Containerized Applications: All interactive apps run in Apptainer (formerly Singularity) containers, providing: Consistent software environments Pre-configured tool stacks Isolation and security Reproducibility Custom Software: Contact support if you need: Additional Python/R packages Specialized scientific software Custom container images System-wide installations Keyboard Shortcuts In Web Shell: Ctrl+C : Cancel current command Ctrl+D : Exit shell Ctrl+L : Clear screen Tab : Auto-complete In File Manager: Ctrl+A : Select all Delete : Delete selected F2 : Rename In Interactive Apps: Depends on the application (JupyterLab, RStudio, VS Code each have their own shortcuts) Changelog Version 1.0 (December 2025) Initial release Covers JupyterLab, RStudio, Code Server, and Desktop apps Basic file management and shell access Resource management guidelines Quick Reference Card URLs Portal : https://hpc.vogelwarte.ch File Manager : Click "Files" → "Home Directory" Shell : Click "Clusters" → "Shell Access" Getting Help Check this guide first Contact HPC support via [email/portal] Include error messages and session details Resource Recommendations Light work : 2 cores, 4 GB, 2-4 hours Medium work : 4-8 cores, 8-16 GB, 4-8 hours Heavy work : 8-16 cores, 32-64 GB, 8-24 hours Storage Paths Home : ~/ or /home/vogelwarte.ch/[username] Shared Data : ~/SciData or /mnt/ceph Scratch : ~/scratch End of User Guide This guide is maintained by the SciIT-Team. Suggestions and corrections welcome!