Revision as of 07:35, 9 January 2026

JupyterLab (Web) Tutorial - KENET HPC Cluster

Overview

JupyterLab is an interactive web-based environment for notebooks, code, and data, ideal for data science, scientific computing, and machine learning workflows.

Use Cases:

• Interactive data analysis and visualization
• Machine learning model development and experimentation
• Creating reproducible research notebooks
• Teaching and sharing computational narratives
• Real-time data exploration with GPU acceleration

Access: Available through the KENET Open OnDemand web portal at https://ondemand.vlab.ac.ke

Prerequisites

Before using JupyterLab, ensure you have:

• Active KENET HPC cluster account
• Access to Open OnDemand portal
• Basic knowledge of Python, R, or Julia
• Data files stored in /home/username/localscratch

Launching JupyterLab

Step 1: Access Interactive Apps

1. Log into Open OnDemand: https://ondemand.vlab.ac.ke
2. Click Interactive Apps in the top navigation menu
3. Select JupyterLab from the dropdown list

Navigate to Interactive Apps → JupyterLab

Step 2: Configure Job Parameters

Fill in the job submission form with your requirements:

Job configuration form with recommended settings

Template:Tip

Step 3: Submit and Wait

1. Click Launch button
2. Wait for job to start (Status: "Queued" → "Running")
3. Click Connect to JupyterLab button when available (typically 30-60 seconds)

Session card showing "Running" status with Connect button

Quick Start Guide

Creating Your First Notebook

1. Click File → New → Notebook or click the Python 3 tile in the Launcher
2. Select kernel: Python 3, R, or Julia (if available)
3. Start writing code in cells

Creating a new notebook in JupyterLab

Basic Cell Operations