PowerIDE User Guide

PowerIDE provides interactive access to the HPC cluster through a web browser. Run Jupyter notebooks, VS Code, and RStudio directly on compute nodes without needing SSH access.
Access PowerIDE at: https://poweride.tau.ac.il/jupyter
Getting Started
Log in with your TAU university credentials (same as email and other university services).
After logging in, click Start My Server. You'll see a Server Options form to configure your compute resources.
When you start your server, PowerIDE submits a Slurm job to the PowerSlurm cluster. Your 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
Your session will queue if the cluster is busy
Configuring Resources
Partition
Select which partition to run on. The dropdown shows only partitions you have access to. Common options:
power-general-shared-pool — general purpose computing
gpu-general-pool — GPU-enabled nodes
Check with your PI or HPC admin if unsure which partition to use.
QOS
Controls priority and resource limits. Default (owner) is usually the right choice. Only valid QOS options for your selected partition are shown.
GPUs
Appears only when a GPU partition is selected. Specify how many GPUs you need (0 if none).
Time (D-HH:MM:SS)
How long your session should run. Default: 
04:00:00. Your session is terminated when time runs out — save your work regularly.
02:30:00 — 2.5 hours
1-12:00:00 — 1 day and 12 hours
CPUs per task
Default: 1. Increase for multi-threaded code.
Memory
Default: 1G. Examples: 
2G, 
8G, 
500M. Start small and increase if needed — over-requesting delays job start.
Working Directory
Default: your home directory. Change to your project directory to save navigation time after launch.
Stdout / Stderr Directory
Where job logs are written. Default (home directory) is fine for most users.
Starting Your Session
Click the orange Start button. PowerIDE submits a Slurm job and shows a progress page. Once a compute node is available (usually 10–60 seconds), you're automatically redirected to JupyterLab.
If the cluster is busy, you can close the browser and come back — your session will start when resources are available.
Using JupyterLab
Left sidebar — file browser, running kernels, extensions
Main area — notebooks, text files, terminals
+ button — opens the launcher for new tools
Common tasks:
New notebook — click + → choose a Python kernel
Terminal — click + → click Terminal (bash shell on the compute node)
Upload files — drag and drop into the file browser
Download files — right-click file → Download
Using VS Code
PowerIDE includes VS Code running in your browser:
Click + to open the launcher
Click the VS Code icon
VS Code opens in a new tab with access to all your files and the same resources as JupyterLab
Using RStudio
RStudio runs as a separate service on a dedicated compute node. It has its own launch form with R-specific options:
Click + to open the launcher
Click the RStudio icon
Fill in the resource form and select your R environment
Click Start — RStudio opens in a new tab once the job is running
R Environment
Select the R environment to load. Each environment is a named module (e.g. 
webR-genomics-2024) with R and a pre-installed set of packages. Contact HPC support if you need a package that isn't available.
R Library Path (optional)
If you have a personal R package library installed in a directory on the cluster, enter its full path here (e.g. 
/home/user/R/library). R will search this directory first, before the environment's default library.
Stopping RStudio
Use the Stop button in the PowerIDE topbar to terminate your RStudio job. Do not use File → Quit Session — that ends the R session but leaves the Slurm job running, continuing to consume resources.
Python Environments
PowerIDE provides one default kernel: Python 3.12 (Base).
You can register your own conda/mamba environments as kernels:
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 (only visible to you)
python -m ipykernel install --user --name my-project --display-name "My Project (Python 3.11)"
Refresh your browser — the new kernel appears in the launcher. To remove a kernel:
jupyter kernelspec uninstall kernel-name
Stopping Your Server
Always stop your server when done to free resources for others.
From JupyterLab — File → Hub Control Panel → Stop My Server
From PowerIDE home — navigate to https://poweride.tau.ac.il/jupyter/hub/home → Stop My Server
VS Code / RStudio — use the Stop button in the PowerIDE topbar
Best Practices
Request only what you need — over-requesting delays your job and others
Set a realistic time limit; restart if you need more
Only request GPUs if your code actually uses them
Store large datasets in scratch space, not your home directory
Use Git for code — not for large data files