Levk: Created page with "= PowerIDE User Guide = PowerIDE provides interactive access to the HPC cluster through a web browser. You can run Jupyter notebooks and VS Code directly on compute nodes wit..."

2026-02-12T16:45:52Z

Created page with "= PowerIDE User Guide = PowerIDE provides interactive access to the HPC cluster through a web browser. You can run Jupyter notebooks and VS Code directly on compute nodes wit..."

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= PowerIDE User Guide =

PowerIDE provides interactive access to the HPC cluster through a web browser. You can run Jupyter notebooks and VS Code directly on compute nodes without needing SSH access.

---

== Getting Started ==

=== 1. Access PowerIDE ===

Open your web browser and navigate to:

'''[https://poweride.tau.ac.il/jupyter https://poweride.tau.ac.il/jupyter]'''

=== 2. Login ===

Log in with your '''TAU university credentials''':

* Username: Your TAU username
* Password: Your TAU password

This is the same login you use for email and other university services.

---

== Starting Your Server ==

After logging in, you'll see a page with a large orange button:

'''Click "Start My Server"'''

You will then be presented with a '''Server Options''' form where you configure your compute resources.

=== How It Works ===

When you start your server, PowerIDE submits a '''Slurm job''' to the '''PowerSlurm cluster'''. Your Jupyter session runs on a '''compute node''', not on the PowerIDE server itself.

This means:
* You get dedicated resources (CPUs, memory, GPUs) on a compute node
* Your job runs through the same Slurm scheduler as other HPC jobs
* The PowerIDE server is only the web interface - all computation happens on cluster nodes
* Your session will queue if the cluster is busy (just like regular batch jobs)

---

== Configuring Resources ==

[[File:Server_Options_Form.png|thumb|500px|Server Options form showing resource selection]]

The form includes the following fields:

=== Partition ===

Select which partition (queue) to run on. The dropdown will '''only show partitions you have access to''' based on your Slurm account permissions.

Common partitions:
* `power-general-shared-pool` - General purpose computing
* `gpu-general-pool` - GPU-enabled partition (if available)
* Check with your PI or HPC admin for which partitions you should use

=== QOS (Quality of Service) ===

Select the QOS for your job. This controls priority and resource limits.

* '''Default (owner)''' - Usually the best choice (uses your group's default QOS)
* Other options may be available based on your partition selection

The form will automatically show only valid QOS options for your selected partition.

=== GPUs ===

If you select a GPU-enabled partition, a '''GPUs''' field will appear. Specify how many GPUs you need (0 if none).

The maximum number of GPUs is automatically limited based on the partition's capabilities.

=== Time (D-HH:MM:SS) ===

Specify how long your session should run. Default is `04:00:00` (4 hours).

Formats accepted:
* `HH:MM:SS` - e.g., `02:30:00` for 2.5 hours
* `D-HH:MM:SS` - e.g., `1-12:00:00` for 1 day and 12 hours

'''Important:''' Your session will be terminated when time runs out. Save your work regularly!

=== CPUs per task ===

Number of CPU cores for your session. Default is `1`.

Increase this if you're running multi-threaded code.

=== Memory ===

Amount of RAM to allocate. Default is `1G`.

Examples:
* `2G` - 2 gigabytes
* `8G` - 8 gigabytes
* `500M` - 500 megabytes

'''Tip:''' Start with less and increase if needed. Over-requesting resources may delay job start.

=== Working directory ===

Default: Your LDAP home directory (e.g., `/a/home/cc/staff/yourusername`)

This is where your Jupyter session starts.

'''Recommendation:''' If you're working on a specific project located elsewhere, '''change this to your project directory'''. For example:
* `/a/home/cc/students/yourgroup/project1`
* `/scratch/yourusername/analysis`

This saves time navigating to your files after launch.

=== Stdout directory ===

Where to write job output logs. Default: your home directory.

'''Recommendation:''' Usually fine to leave as default, but you can change it to organize logs better (e.g., `~/logs/` or your project directory).

=== Stderr directory ===

Where to write job error logs. Default: your home directory.

'''Recommendation:''' Same as stdout - usually fine to keep default.

---

== Starting Your Session ==

After filling out the form, click the orange '''Start''' button at the bottom.

What happens next:

# PowerIDE submits a Slurm job with your requested resources
# You'll see a progress page saying "Your server is starting up..."
# Wait for a compute node to become available (usually 10-60 seconds)
# Once started, you'll automatically be redirected to JupyterLab

'''Note:''' If the cluster is busy, it may take longer. You can close the browser and come back - your session will start when resources are available.

---

== Using JupyterLab ==

Once your server starts, you'll land in '''JupyterLab''' - a web-based development environment.

=== JupyterLab Interface ===

* '''Left sidebar:''' File browser, running kernels, extensions
* '''Main area:''' Notebooks, text files, terminals
* '''Launcher:''' Click the '''+''' button to see available tools

=== Common Tasks ===

'''Create a new notebook:'''
# Click the '''+''' button (or File → New Launcher)
# Click on a kernel (e.g., "Python 3")
# Start coding!

'''Open a terminal:'''
# Click the '''+''' button
# Click "Terminal" in the launcher
# You now have a bash shell on the compute node

'''Upload files:'''
* Drag and drop files into the file browser, OR
* Click the upload button (↑ icon) in the file browser

'''Download files:'''
* Right-click file → Download

---

== Using VS Code ==

PowerIDE includes '''VS Code''' (Visual Studio Code) running in your browser!

=== Starting VS Code ===

# From JupyterLab, click the '''+''' button to open the launcher
# Look for the '''VS Code''' icon in the launcher
# Click it - VS Code will open in a new tab/window

You now have a full VS Code environment running on the compute node with all your files accessible.

=== VS Code Features ===

* Full code editor with syntax highlighting
* Integrated terminal
* Extensions support
* Git integration
* File explorer

'''Tip:''' VS Code runs in the same job as JupyterLab, so it has access to all the same resources (CPUs, memory, GPUs) you requested.

---

== Python Environments ==

=== What is a Python Kernel? ===

A '''kernel''' is simply a Python interpreter that JupyterLab uses to run your code. When you create a notebook and select "Python 3.12 (Base)", you're choosing which Python environment to use.

Think of it like choosing which Python installation to run: `/usr/bin/python3` vs `/path/to/my-env/bin/python`

=== Default Kernel ===

PowerIDE provides one default kernel:
* '''Python 3.12 (Base)''' - Standard Python with JupyterLab and common packages

=== Creating Your Own Kernels ===

You can register your own conda/mamba environments as kernels! This lets you:
* Use different Python versions (3.9, 3.10, 3.11, etc.)
* Install custom packages without affecting others
* Have multiple project-specific environments

'''Steps to register your own environment:'''

# Create your conda/mamba environment (wherever you normally keep them)
# Activate it and make sure `ipykernel` is installed
# Register it as a kernel
# Refresh your browser - it will appear in the JupyterLab launcher!

'''Example:'''

<pre>
# From a JupyterLab terminal (or any cluster node):
module load mamba/mamba-2.1.1
mamba create -n my-project python=3.11 pandas matplotlib
mamba activate my-project
mamba install ipykernel

# Register as kernel (--user means only you will see it)
python -m ipykernel install --user --name my-project --display-name "My Project (Python 3.11)"

# Done! Refresh your browser and look for "My Project (Python 3.11)" in the launcher
</pre>

'''Need help?'''

If you need assistance:
* Installing `ipykernel` in your environment
* Registering your kernel
* Troubleshooting kernel issues

Contact us at '''hpc@tauex.tau.ac.il''' - we're happy to help!

'''Important notes:'''
* Kernels are just small config files (~1 KB) - they don't use your disk quota
* Each user only sees their own kernels (plus system defaults)
* You can have as many kernels as you want
* Remove a kernel: `jupyter kernelspec uninstall kernel-name`

---

== Stopping Your Server ==

'''Important:''' Always stop your server when you're done to free up resources for others!

There are two ways to stop:

=== Method 1: From JupyterLab ===

# Go to '''File → Hub Control Panel'''
# Click the red '''Stop My Server''' button

=== Method 2: From PowerIDE home ===

# Navigate to [https://poweride.tau.ac.il/jupyter/hub/home https://poweride.tau.ac.il/jupyter/hub/home]
# Click the red '''Stop My Server''' button

Your job will be terminated and the compute node will be freed.

---

== Best Practices ==

=== Resource Allocation ===

* '''Start small:''' Request fewer resources initially. You can always restart with more.
* '''Be realistic:''' Only request what you actually need
* '''Time limits:''' Set a reasonable time limit. You can always restart if you need more time.
* '''GPU usage:''' Only request GPUs if your code actually uses them

=== File Management ===

* '''Working directory:''' Set it to your project folder to save navigation time
* '''Save frequently:''' Your session will end when time runs out
* '''Large files:''' Store large datasets in scratch space, not your home directory

=== Data and Code ===

* '''Home directory:''' Your LDAP home directory - personal files, small projects
* '''Scratch space:''' Large temporary datasets
* '''Project directories:''' Shared group work (varies by group)

'''Tip:''' Use Git to version control your code, not for large data files.

---

== Troubleshooting ==

=== My server won't start ===

'''Possible reasons:'''

* '''Cluster is full:''' Wait a few minutes and try again
* '''Invalid partition:''' Make sure you selected a partition you have access to
* '''Too many resources:''' Try requesting fewer CPUs/memory
* '''No QOS access:''' You may not have any QOS configured for your account

'''What to do:'''
# Wait 2-3 minutes
# If still pending, go to Hub Control Panel and click "Stop My Server"
# Try again with fewer resources or different partition
# If QOS dropdown is empty, contact HPC support - you may need Slurm associations configured

=== I see "404: Not Found" ===

This usually means your job didn't start successfully.

Check:
# Go to your home directory on a login node (or check via terminal)
# Look for files named `jupyterhub-JOBID.err` (where JOBID is a number)
# Check the file for error messages
# Contact HPC support if you can't resolve it

=== VS Code icon doesn't appear ===

This is rare - if it happens:
# Try refreshing your browser
# If still missing, contact HPC support

=== My session was killed ===

'''Common reasons:'''

* '''Time limit reached:''' Your session ran for the full time you requested
* '''Out of memory:''' Your code used more RAM than allocated
* '''Node failure:''' Rare, but compute nodes can crash

'''Solution:'''
* Save your work frequently
* Request more time/memory next time
* Check `jupyterhub-JOBID.err` file for clues

---

== Getting Help ==

=== Support ===

For technical issues:

* Email: `hpc@tauex.tau.ac.il`

'''When asking for help, include:'''
* Your username
* What you were trying to do
* Error messages (copy/paste or screenshot)
* Job ID if available (from error file name)

Email: `hpc@tauex.tau.ac.il`

---

== FAQ ==

'''Q: Can I run multiple servers at once?'''

A: No, you can only have one server running at a time per user.

'''Q: How long can my session run?'''

A: Varies by partition - most partitions allow up to 7 days maximum.

'''Q: Can I install Python packages?'''

A: Yes! Create your own conda/mamba environment, install whatever packages you need, and register it as a kernel (see "Python Environments" section). You have full control over your own environments.

'''Q: Why is my QOS dropdown empty?'''

A: This means you don't have any QOS associations configured in Slurm. Contact HPC support - they need to add you to a Slurm account with appropriate QOS access.

'''Q: Do I need to use the terminal for everything?'''

A: No! JupyterLab notebooks are great for interactive work. Use the terminal only when needed.

'''Q: What happens to my files when I stop my server?'''

A: Your files are safe! Only the running session is terminated. All files in your home directory and project directories remain intact.

'''Q: Can I share my session with a colleague?'''

A: No, sessions are personal. However, you can share notebooks and code files through the filesystem or Git.

'''Q: Is PowerIDE the same as the login nodes?'''

A: No! PowerIDE runs on compute nodes through the Slurm scheduler, giving you dedicated resources. Login nodes are shared by everyone.

'''Q: How do I get access to different partitions?'''

A: Partition access is controlled by Slurm account associations. Contact your PI or HPC admin to request access to specific partitions.

---

== Quick Reference Card ==

{| class="wikitable"
! Action !! How-To
|-
| Access PowerIDE || [https://poweride.tau.ac.il/jupyter https://poweride.tau.ac.il/jupyter]
|-
| Start server || Click "Start My Server" → Fill form → Click "Start"
|-
| Open notebook || Click '''+''' → Choose Python kernel
|-
| Open terminal || Click '''+''' → Click "Terminal"
|-
| Start VS Code || Click '''+''' → Click "VS Code" icon
|-
| Stop server || File → Hub Control Panel → "Stop My Server"
|-
| Upload files || Drag & drop into file browser
|-
| Download files || Right-click file → Download
|-
| Request custom environment || Email hpc@tauex.tau.ac.il with requirements
|-
| Get help || Email hpc@tauex.tau.ac.il
|}

---

''Happy computing! 🚀''

PowerIDE User Guide - Revision history

Levk: Created page with "= PowerIDE User Guide = PowerIDE provides interactive access to the HPC cluster through a web browser. You can run Jupyter notebooks and VS Code directly on compute nodes wit..."