Workshops and Tutorials - Archive

Owned by Simon Alexander
Last updated: Aug 05, 2024 by Lisa Stafford
3 min read

Why invest the time and effort to learn HPC?

Learning how to use HPC will likely not be valuable for all users in all cases, but it can be exceptionally valuable and save significant time and effort in certain situations. Learning these skills provide HPC knowledgable users with a strategic advantage that can serve them throughout their academic, research, and professional careers.

Anyone with a workstation crashing due to memory problems from too much data, running time consuming computational tasks, performing repetitive computations, wanting to scale their computational work, or just needing more compute power should consider using HPC resources for improved speed, efficiency and time-savings.

Common HPC Skills

Becoming an expert in HPC requires knowledge in Linux Command Line, and mastering a number of tools. The tools that provide the greatest value to you may be different from those in other scientific domains. While it may seem initially daunting, UW ARCC helps all researchers regardless of HPC experience level. Our department has developed a number of tutorials and we offer bi-weekly office hours allowing you to learn HPC at your own pace. Below is a very general list of common set of skill to master to become an expert HPC user:

  1. General HPC Use and Knowledge

  2. The Linux Operating System

  3. Command Line Interface (CLI)

    1. Text Editors

  4. Data Management

  5. Commonly Used Software on HPC Clusters

    1. Environments and Software Package Management: Conda & Pip

    2. Python

    3. R and R Studio

    4. Jupyter Notebooks

ARCC Hosted Training

Fall 2024

More HPC Training Resources

During Spring and Fall semesters, ARCC and the Digital Scholarship Center offer a number of relevant workshops on HPC, R, Python, Data Management, and other helpful and related topics.

To see currently scheduled topics, please see the the Library Events Calendar

Spring 2024

Fall 2023

  • February 28, 2023 3-4:30PM @COE302: R for Data Visualization, delivered by the Libraries DSC

  • March 1, 2023 4-5 PM @COE302: NWSC Allocation Prep, jointly delivered by ARCC and the Libraries DSC

  • March 6, 2023 3-4:30PM @COE302: Intermediate Linux

  • March 23, 2023 11-2:30pm @COE216: Deep Learning with MATLAB: Time Series, Images, Signals and More, delivered by Mathworks

  • April 3, 2023 11-2pm @COE216: Intel Analytics Tools, delivered by Intel

  • April 17, 2023 11-2:30PM @COE216: Intel oneAPI AI Analytics Toolkit

  • April 18, 2023 3-4:30PM @COE302: Intermediate Cluster Computing

  • May 15, 2023 3-5PM @AG316: Nextflow for Workflow Management, delivered by the UW Department of Mathematics and Statistics, and the Public Health Lab at the Wyoming Department of Health

  • May 17, 2023 11:30-3PM: Remote workshop: Intel OneAPI AI Analytics Toolkit, delivered by Intel

Spring 2023

  • February 28, 2023 3-4:30PM @COE302: R for Data Visualization, delivered by the Libraries DSC

  • March 1, 2023 4-5 PM @COE302: NWSC Allocation Prep, jointly delivered by ARCC and the Libraries DSC

  • March 6, 2023 3-4:30PM @COE302: Intermediate Linux

  • March 23, 2023 11-2:30pm @COE216: Deep Learning with MATLAB: Time Series, Images, Signals and More, delivered by Mathworks

  • April 3, 2023 11-2pm @COE216: Intel Analytics Tools, delivered by Intel

  • April 17, 2023 11-2:30PM @COE216: Intel oneAPI AI Analytics Toolkit

  • April 18, 2023 3-4:30PM @COE302: Intermediate Cluster Computing

  • May 15, 2023 3-5PM @AG316: Nextflow for Workflow Management, delivered by the UW Department of Mathematics and Statistics, and the Public Health Lab at the Wyoming Department of Health

  • May 17, 2023 11:30-3PM: Remote workshop: Intel OneAPI AI Analytics Toolkit, delivered by Intel

Fall 2022

Spring 2022

  • Wild Iris Train the Trainer

  • Matlab remote workshop

Introductory videos

  1. Intro to ARCC: who we are, what we do, our services.

  2. Intro to HPC clusters: high level architectural concepts

  3. Getting started on ARCC infrastructure: where to put data, how to connect to cluster, how to start compute jobs.

RMACC Courses

Other Members of RMACC have shared their training online. Visit the RMACC Training web page for more information.