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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:

  1. Click + to open the launcher
  2. Click the VS Code icon
  3. 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:

  1. Click + to open the launcher
  2. Click the RStudio icon
  3. Fill in the resource form and select your R environment
  4. 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
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