Courses

Last Updated: March 27, 2026

Every semester, Texas A&M High Performance Research Computing (HPRC) offers short courses covering a range of topics for beginning, intermediate, and advanced researchers. Courses taught early in the semester on the clusters and schedulers form the basis for using the respective clusters effectively. We also offer short "primer" classes taught throughout the semester to brush up on basics quickly. All courses will be delivered in an interactive style through a live login session. In general, slides and other supplemental materials are available on each course page.

Registration is required for each primer or short course. Attendees will need to use their own device. Workstations are not provided. The typical short course runs for 2.5 hours, unless otherwise noted. Each primer runs for 1 hour.

Most courses will require one of two accounts:

In-class short courses have a seating limit of about 45 students.

For our course offerings from previous semesters, please consult this page.

Short Course List for Spring 2026

(Courses listed with only months are tentative)

ACES: AI/ML TechLab on Graphcore IPUs

Instructor(s): Dr. Zhenhua He

Time: Tuesday, March 31, 2026 10:00AM-12:30PM CT

Location: Online using Zoom

Description: This course introduces researchers to Graphcore Intelligence Processing Units (IPUs) on the ACES cluster, a composable accelerator testbed. The instructor will lead participants through the execution of models from different frameworks on the IPU system. Participants will gain practical experience in converting TensorFlow and PyTorch code into IPU code through hands-on exercises.

Prerequisite(s): Current ACCESS ID; basic Linux/Unix skills; basic understanding of machine learning concepts, neural networks, and deep learning; familiarity with deep learning frameworks TensorFlow and/or PyTorch

View Details Remote Attendee Registration

ACES: Introduction to CuPy: NumPy & SciPy for GPU

Instructor(s): Jian Tao

Time: Tuesday, March 31, 2026 1:30PM-4:00PM CT

Location: Online using Zoom

Description: This course covers basic topics in numerical computation and scientific programming using CuPy for GPU acceleration in Python. Topics include CuPy's API (compatible to NumPy and SciPy), device memory and transfers, performance best practices, and relevant open-source tools and workflows.

Prerequisite(s): Current ACCESS ID, basic Python skills

View Details Remote Attendee Registration

ACES: Python for Data Scientists

Instructor(s): Richard Lawrence

Time: Tuesday, April 7, 2026 — 10:00AM-4:00PM CT (with a 1-hour lunch break)

Location: Online using Zoom

Description: This short course for experienced programmers introduces the Numpy, Pandas, and Matplotlib libraries commonly used to manage and display large datasets in Python.

Prerequisite(s): Active ACCESS ID, some Python or programming experience

View Details Remote Attendee Registration

Generative AI for Protein Design: A Hands-On Introduction to RFdiffusion

Instructor(s): Dr. Dinesh Devarajan

Time: Friday, April 10, 2026 — 10:00AM-12:30PM CT

Location: Blocker 220

Description: This short course provides hands-on introduction to diffusion-based generative models for protein design, with a focus on RFdiffusion. Participants will learn how to run RFdiffusion inference workflows on HPRC clusters.

Prerequisite(s): Active HPRC Account, Linux/Unix skills

View Details In-Person Attendee Registration

ACES: Ab Initio Molecular Dynamics on NEC Vector Engine

Instructor(s): Dr. James Mao

Time: Friday, April 10, 2026 — 1:30PM-4:00PM CT

Location: Online using Zoom

Description: This short course provides an introduction to performing ab initio molecular dynamics simulations using the Vienna Ab initio Simulation (VASP) and Quantum ESPRESSO packages on the ACES cluster using NEC Vector Engine (VE) cards.

Prerequisite(s): Current ACCESS ID; basic Linux/Unix skills; basic understanding of computational chemistry concepts

View Details Remote Attendee Registration

ACES: Python for High Performance Computing Workflows

Instructor(s): Richard Lawrence

Time: Tuesday, April 14, 2026 — 10:00AM-4:00PM CT (with a 1-hour lunch break)

Location: Online using Zoom

Description: This short course for experienced Python programmers will cover several topics relevant to Python workloads running on HPC systems, including environment setup, parallelism, and checkpointing.

Prerequisite(s): Active ACCESS ID, some Python or programming experience

View Details Remote Attendee Registration

Setting Up Molecular Dynamics Simulations

Instructor(s): Dr. James Mao

Time: Friday, April 17, 2026 — 10:00AM-12:30PM CT

Location: Blocker 220

Description: This short course provides a step-by-step guide to setting up molecular dynamics (MD) simulations. The course will also cover performing production MD simulations using various software available on the HPRC cluster.

Prerequisite(s): Active HPRC account, active CHARMM-GUI account, basic Linux/Unix skills

View Details In-Person Attendee Registration

Running Molecular Dynamics Simulations Using LAMMPS

Instructor(s): Dr. Dinesh Devarajan

Time: Friday, April 17, 2026 — 1:30PM-4:00PM CT

Location: Blocker 220

Description: This short course offers a comprehensive, step-by-step guide for setting up and running molecular dynamics (MD) simulations of a variety of systems.

Prerequisite(s): Active HPRC account, basic Linux/Unix skills

View Details In-Person Attendee Registration

ACES: Intro to the Grace Hopper Superchip

Instructor(s): Dr. Dinesh Devarajan

Time: Tuesday, April 21, 2026 — 10:00AM-12:30PM CT

Location: online using Zoom

Description: This short course covers technical aspects of the Grace Hopper Superchip, its advantages, challenges, and architectural design. The benchmarks conducted by HPRC researchers will be presented, highlighting the Grace Hopper system's performance across a variety of HPC workloads.

Prerequisite(s): Active ACCESS ID, general understanding of computer architecture

View Details Remote Attendee Registration

ACES: Introduction to Julia

Instructor(s): Dr. Wes Brashear

Time: Tuesday, April 21, 2026 — 1:30PM-4:00PM CT

Location: online using Zoom

Description: This short course covers basic topics in numerical computation and scientific programming in the Julia language, including basic language elements and concepts, best practices in programming, and relevant open source tools.

Prerequisite(s): Current ACCESS ID

View Details Remote Attendee Registration

Setting up Environments for AI Research and Software Development on TAMU HPRC

Instructor(s): Dr. Thang Ha

Time: Friday, April 24, 2026 — 10:00AM-12:30PM CT

Location: Blocker 220

Description: In this short course, attendees will learn to set up environments for common AI research workflows involving Python (with PyTorch) and R, as well as set up environments for building and developing software written in compiled languages like C/C++/Fortran.

Prerequisite(s): Active HPRC account,

View Details In-Person Attendee Registration

ACES: Incorporating Snakemake in HPC Workflows

Instructor(s): Dr. Wes Brashear

Time: Tuesday, April 28, 2026 — 10:00AM-12:30PM CT

Location: Online using Zoom

Description: Snakemake is a Python-based workflow management system for creating reproducible and scalable data science pipelines. Students will learn best practices on how to incorporate Snakemake in their workflows on HPRC systems and complete hands-on exercises creating simple Snakemake workflows to more complex, multi-step pipelines culminating in descriptive workflow reports.

Prerequisite(s): Active HPRC account

View Details Remote Attendee Registration

ACES: AI/ML TechLab on Intel PVC GPUs

Instructor(s): Dr. Zhenhua He

Time: Tuesday, April 28, 2026 — 1:30PM-4:00PM CT

Location: online using Zoom

Description: This course provides an overview of Intel PVC GPUs, guidance on accessing these GPUs on the ACES cluster at Texas A&M High Performance Research Computing, and demonstrations of running AI/ML models with the GPUs using PyTorch and Tensorflow.

Prerequisite(s): Current ACCESS ID; basic Linux/Unix skills; basic understanding of machine learning concepts, neural networks, and deep learning; familiarity with deep learning frameworks TensorFlow and/or PyTorch

View Details Remote Attendee Registration