UMBC HPC Bootcamp

iHARP at UMBC held a High Performance Computing (HPC) bootcamp in November 2024, below are the resources that were developed. Please note some access to materials and high performance resources are restricted to UMBC members only.

Introduction

The video and document (access restricted to UMBC) introduces basic BASH commands for navigating the Linux terminal, including file navigation and manipulation. It then walks users through the process of accessing Ada, the university’s High-Performance Computing (HPC) cluster, via CLI tools. This section provides instructions for logging in, navigating the cluster environment, and accessing resources.

The resources covers job management with SLURM, teaching users how to write, submit, and track SLURM jobs on Ada. This includes creating job scripts, submitting tasks to the cluster, tracking job progress, and optimizing resource usage to ensure that computational workloads run smoothly and efficiently on the HPC cluster.

 

Instructional Introduction Video on UMBC’s High Performance Computing Ada Cluster

The bootcamp recording includes a voice over walk-through of UMBC’s Ada cluster.

 

 

 

UMBC High Performance Computing (HPC) Bootcamp Walk-through Documentation

Click here to navigate to the Google Document that contains written documentation and instructions to access UMBC High-Performance Computing (HPC) Ada cluster.

*Please note you must be a UMBC member to access the Google Document

  • 00:00 UMBC HPC Bootcamp 2024
  • 00:25 Let’s log in to ADA
  • 01:10 High Performance Computing
  • 01:15 What is HPC?
  • 02:10 Purpose of HPC?
  • 03:04 Nodes in ADA
  • 03:16 Login Node
  • 04:13 Worker Nodes
  • 05:37 Storage System
  • 05:43 Storage on Ada
  • 05:55Home directory vs Working directory
  • 07:16 Home Directory
  • 08:16 Shared Group Storage
  • 09:13 HPCF Research Storage
  • 11:22 Scratch Space
  • 12:49 List of Commands
  • 13:04 ID Share
  • 17:55 p! List of Commands
  • 19:22 List of Commands * st a
  • 21:46 Running the Bash Script created earlier
  • 21:52 3. Modules
  • 22:34 my test.sh test/
  • 25:10 Environment Setup
  • 25:28 Bash Environment
  • 27:33 Why we need modules?
  • 28:51 Solution
  • 30:08 List of Commands
  • 31:58 ID Share
  • 32:38 Python Environment
  • 34:32 Venv Environment
  • 37:37 Conda Environment
  • 42:00 SLURM
  • 42:33 (HARP
  • 43:21 Requesting Resources
  • 44:36 Requesting Memory
  • 45:21 Requesting GPUs
  • 46:21 Requesting Time
  • 47:48 Batch Jobs
  • 49:05 Running MNIST script through sbatch
  • 50:14 Install the following packages
  • 50:53 How to create a shell file to request resources
  • 57:59 6. Jupyter Notebooks
  • 1:00:11 List of Commands 4- m
  • 1:06:21 Monitoring SLURM Jobs
  • 1:06:27 Monitoring the status of the running jobs
  • 1:06:57 SQUEUE Command
  • 1:07:27 Modifying Jobs
  • 1:08:39 Case Study: Using patch -CNN in High -Performance Computing…
  • 1:09:29 Overview
  • 1:10:21 Problem Statement
  • 1:11:05 Motivation
  • 1:11:53 Model Explanation
  • 1:13:13 Research Objectives
  • 1:13:59 Methodology Overview
  • 1:15:23 Challenges
  • 1:16:13 Results
  • 1:16:49 Conclusion
  • 1:18:10 C ►► Code
  • 1:18:13 Antarctica
  • 1:18:54 median IC:
  • 1:20:23 3 e myenv Idle
  • 1:20:40 Cancelling jobs