• ACCESS ID
• Basic understanding of navigating the Linux command line
• Basic knowledge/skills in any interpreted language (e.g. R, Python) will be beneficial, but not critical

About the Instructor: Dr. Wesley Brashear is an Assistant Research Scientist with High Performance Research Computing at Texas A&M University. His background is in genetics and bioinformatics and has extensive expertise in R.

Containers for HPC Reproducibility: Building, Deploying, and Optimizing

Tuesday, May 21 9:00AM-12:00PM

Instructor: Dr. Carlos del-Castillo-Negrete, Research Associate, Texas Advanced Computing Center

Software containers have gained immense popularity as an effective means for enhancing the portability and reproducibility of high-performance computing (HPC) applications.

This hands-on workshop is designed to provide a comprehensive introduction to building, running, and distributing Docker and Singularity/Apptainer containers specifically tailored for HPC environments. Participants will receive in-depth guidance on creating HPC-compliant containers that are not only suitable for local testing and development but also optimized for deployment on advanced HPC systems.

Presentation Slides: (pdf)

Special attention will be given to the intricacies of building containers that can run on multiple nodes using MPI and using accelerated hardware such as GPUs. Moreover, the workshop will delve into best practices for containerization in HPC contexts, troubleshooting common issues, and strategies for ensuring the seamless integration of containers into existing HPC workflows.

Prerequisites: ACCESS ID

• Docker and Singularity/Apptainer basics
• Containerizing your own code
• Multi-stage and Multi-architecture Docker builds
• Running containers on HPC systems, including MPI parallelism and GPU enabled containers

About the presenter: Dr. Carlos del-Castillo-Negrete is a Research Associate in the High Performance Computing Group at the Texas Advanced Computing Center. His research interests center around developing HPC applications for machine learning and uncertainty quantification, particularly in the realm of climate and natural hazards modeling.

CUDA Programming: Basic Concepts in C and Fortran

Tuesday, May 21 9:00AM-12:00PM

Instructor: Dr. Lars Koesterke, Research Associate, Texas Advanced Computing Center

This workshop is designed to teach the fundamentals of CUDA programming for those with a background in programming (C/C++/Fortran) but little to no exposure to CUDA programming.

Presentation Slides: (pdf)

• Basic CUDA programming concepts: ‘software matching hardware’
• Performance optimization and techniques beneficial under most circumstances

Prerequisites: Basic knowledge of C/Fortran, or generally of a programming language, ACCESS ID

About the presenter: Dr. Lars Koesterke joined TACC is as a Research Associate in the High Performance Computing group at TACC. Before coming to TACC, he held positions at the Astronomy Department at The University of Texas at Austin, NASA's Goddard Space Flight Center and the Universities of Potsdam and Kiel (both Germany). His work at TACC is focused on performance evaluation and optimization.

Charliecloud Container Training

Tuesday, May 21 1:00PM-4:00PM

Instructor: Megan Phinney, Los Alamos National Laboratory

This workshop will provide participants with background and hands-on experience to use basic Charliecloud containers for HPC applications. We will discuss what containers are, why they matter for HPC, and how they work. We’ll give an overview of Charliecloud, the unprivileged container solution from Los Alamos National Laboratory’s HPC Division. Participants will build toy containers and a real HPC application, and then run them in parallel on a supercomputer. This will be a highly interactive workshop with lots of Q&A.

Presentation Slides: (pdf)

Exercises: (pdf)

About the presenter: Megan Phinney is a computer scientist in the High Performance Computing – Environments group at Los Alamos National Laboratory, where she provides user support for the institutional HPC systems. Her research interests include secure user space container environments and performance of file systems.

Accelerate seismic facies classification using wavelet-informed deep learning

Tuesday, May 21 1:00PM-3:30PM

Hosted by MathWorks

Instructor: Ayon K. Dey, PhD, Senior Application Engineer, MathWorks

Interpretation of geological facies from large seismic datasets is one of the key steps in modeling and simulating subsurface reservoirs to support oil & gas exploration, field development planning, unconventional play development, and carbon storage – just to name a few use cases. MATLAB enables the creation of a fast and robust workflow to classify facies using large seismic datasets by integrating unique geophysical and deep learning methodologies.

Prerequisites: ACCESS ID

• How to accelerate seismic facies classification by integrating geophysics (multi-resolution analysis or MRA) and deep learning (recurrent neural networks or RNN) while reducing overfitting with unique wavelet signals;
• How to reduce computing time using GPU computing capabilities on very large seismic datasets;
• How RNN proves to be more effective to classify seismic facies compared to other deep learning methods (e.g., convolutional neural networks or CNN) based on results from blind tests conducted at the 2021 SEAM Hackathon.

About the presenter: Ayon K. Dey is a Senior Application Engineer at MathWorks based in Texas. Ayon’s experience spans over 30 years working in multiple Geosciences roles for oil, gas, and chemical companies based in Canada, USA, Saudi Arabia, South Africa, and UAE, as well as for research institutions in Canada and The Netherlands. Ayon has 17 expanded abstract and journal publications in technical geoscience; holds a Ph.D. degree in Applied Physics from Delft University of Technology, an M.Sc. degree in Geology and Geophysics from University of Calgary, and a B.Sc. in Applied Mathematics from Memorial University of Newfoundland.

Introduction to AlphaFold for 3D Protein Structure Prediction

Tuesday, May 21 1:00 PM - 3:30 PM

Instructors: Dr. Michael Dickens, Texas A&M High Performance Research Computing and Dr. Devon Boland, Texas A&M Institute for Genome Sciences & Society

In this workshop, participants will learn how to run AlphaFold and about the fundamentals of AlphaFold as applied to real world applications.

Presentation Slides: (pdf)

Prerequisites: ACCESS ID

• Introduction to AlphaFold
• Running AlphaFold on Grace
• AlphaFold Workflows
• Visualizing AlphaFold results

Fundamentals of Accelerated Computing with CUDA C/C++, NVIDIA DLI Workshop

Friday, May 24 8:00AM-5:00PM

Instructor: Jian Tao, PhD, Assistant Professor, School of Performance, Visualization & Fine Arts, Texas A&M University.

This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you’ll have access to additional resources to create new GPU-accelerated applications on your own.

• Write code to be executed by a GPU accelerator
• Expose and express data and instruction-level parallelism in C/C++ applications using CUDA
• Utilize CUDA-managed memory and optimize memory migration using asynchronous prefetching
• Leverage command line and visual profilers to guide your work
• Utilize concurrent streams for instruction-level parallelism
• Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach

• Learn to build deep learning and accelerated computing applications for industries such as autonomous vehicles, finance, game development, healthcare, robotics, and more.
• Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
• Gain real-world expertise through content designed in collaboration with industry leaders such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
• Earn an NVIDIA DLI certificate to demonstrate your subject matter competency and support career growth.
• Access content anywhere, anytime with a fully configured, GPU-accelerated workstation in the cloud.

Full Schedule (All times are CT), subject to change

Last Update: May 21, 2024

Posters

Thanks to our Sponsors!

Texas A&M Research Computing Symposium is supported in part by NSF award #1925764, CC* Team: SWEETER -- SouthWest Expertise in Expanding, Training, Education and Research and NSF award #2112356, ACSS: ACES - Accelerating Computing for Emerging Sciences.