Tutorials

HPC Tutorials

The WAVE HPC at SCU utilizes a powerful cluster environment to support research, coursework, and advanced computational projects across disciplines. Users can submit and monitor SLURM jobs, request GPUs and memory, manage software environments with Conda, and run tools like MATLAB, C/C++, Jupyter, and machine learning workflows through Open OnDemand. These resources enable efficient, scalable computing while simplifying access to high-performance infrastructure. To help users understand how to navigate the many aspects of the HPC, we offer tutorials on this page that should help a beginner familiarize themselves with the WAVE HPC as well as tutorials for more niche applications of the HPC.

HPC Courses

Santa Clara University offers courses to help students, researchers, and faculty learn how to use the SCU WAVE High Performance Computing (HPC) system, from basic access and job scheduling to running AI and machine learning workloads. These tutorials give the user the most holistic overview on how to use the HPC, and are a great starting point for new users.

AI/ML on the HPC

Learn how to run machine learning and AI workloads on the SCU WAVE High Performance Computing system. This robust course covers everything from introductory information, options for connecting to the cluster and scheduling jobs with SLURM to managing software environments and running AI/ML experiments at scale. The course offers helpful hands-on practice that will familiarize the user with the various steps involved with running jobs on the HPC.

Introduction to WAVE HPC

A light, introductory course on using SCU’s WAVE High Performance Computing system. Learn the fundamentals of HPC, how to create an account, access the system, schedule resources with SLURM and manage modules and files. This course succinctly provides the basics on usage of the HPC, but does not include practice.

HPC Basics

These tutorials offer useful information for navigating to the HPC for the first time and on how it functions as well as common terminal commands and how to set up quick connection via a SSH key. Helpful for first time and returning users.

Getting to know the Terminal

Foundational skills for navigating the HPC system using the terminal and list of helpful commands.

SSH Keys

Teaches you how to connect securely to the HPC and set up an SSH Key for quick access.

Introductory Training Session Recordings

Recordings of past training sessions for users who want to learn at their own pace.

HPC Essentials

These tutorials teach the user the two methods of interfacing with the HPC: scheduling batch and interactive jobs with SLURM or connecting through Open OnDemand for web based access. Each of these have their own use cases, but SLURM is often used for submitting large jobs to the HPC while Open OnDemand is used for interactive access and apps.

SLURM Tutorials

Covers submitting, scheduling, and managing jobs, including batch and interactive jobs, partitions and queues, requesting GPU resources and memory, and monitoring jobs.

Open OnDemand

Web-based access to the cluster, including launching apps, managing files/jobs/clusters, JupyterLabs integration, Compute GUI, and MATLAB integration.

HPC Extensions

These tools on the HPC are paramount for users to create reproducible runtime environments for their projects. Conda allows the user to set up specialized environments to control and manage software packages and prevent dependency conflicts between projects. Containers allow the user to package applications to be run seamlessly from one computing environment to another.

Conda Tutorial

Managing software environments and dependencies for reproducible research and coding workflows.

Containers Tutorial

Building and running containerized workloads with Podman and Singularity, including creating images, configuring storage, and running containers inside SLURM jobs.

HPC Tools

These tutorials cover more specific use cases of the HPC such as how to compile C/C++ code efficiently, scale MATLAB workloads and run machine learning workflows.