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Advanced Computing Workshop

August 19 @ 8:00 am August 21 @ 5:00 pm

This workshop focuses on Hybrid MPI-CUDA Programming for Massively Parallel Applications on Large GPU Clusters and will prepare Texas A&M researchers to use the LAUNCH cluster and the upcoming NVIDIA DGX H200 Superpod purchased by the Texas A&M University System

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REGISTRATION DEADLINE AUGUST 14, 2025

Workshop Overview


The rapid evolution of high-performance computing and increasing utilization across research and operations has made GPU programming an essential skill for researchers and engineers working with computationally intensive applications. This workshop addresses the growing demand for expertise in massively parallel programming by combining CUDA for GPU acceleration with Message Passing Interface (MPI) for distributed computing across multiple nodes.

This three-day in-person intensive workshop represents a collaborative effort between Texas A&M High Performance Research Computing (HPRC), the Texas A&M Institute of Data Science (TAMIDS), the NSF National Center for Atmospheric Research (NCAR), and the Texas A&M University System (TAMUS) to advance GPU programming skills for massively parallel computing applications. Participants will gain hands-on experience with Texas A&M’s state-of-the-art LAUNCH computing cluster, CUDA programming fundamentals, MPI parallel programming patterns, and the integration of both technologies for multi-node, multi-GPU applications using Texas A&M’s world-class supercomputing infrastructure.

The skills taught in this workshop will prepare researchers to leverage state-of-the-art resources like the LAUNCH computing cluster and the upcoming NVIDIA DGX H200 SuperPod purchased by TAMUS.

Prerequisites and Preparation


Required Background Knowledge

Participants must have solid programming experience in C or C++, including familiarity with pointers, arrays, and function implementations. A basic understanding of parallel computing concepts is helpful but not required, as fundamental principles will be covered during the workshop. Previous experience with Linux command-line environments and batch job submission systems is recommended, as all practical exercises will be conducted on Texas A&M’s supercomputing clusters.

Technical Requirements

All participants must bring a laptop capable of SSH connectivity to Texas A&M’s computing resources. Workshop organizers will provide temporary accounts on the HPRC systems, including access to the HPRC cluster with their extensive GPU resources. Participants should ensure their laptops have SSH client software installed and are capable of secure file transfer protocols for code development and data analysis.

NSF ACCESS ID

To participate in the hands-on sessions, you will need an ACCESS ID to get on the LAUNCH cluster. If you do not have one, you can receive one for FREE. Please see the walkthrough to register for an ACCESS ID at: https://hprc.tamu.edu/kb/Helpful-Pages/ACCESS-ID

Learning Objectives


Day 1: Introduction to Launch and CUDA Programming Fundamentals

Participants will master the essential concepts of GPU programming using CUDA, building from basic kernel development to advanced memory management techniques. The curriculum covers GPU architecture, threading models, memory hierarchy optimization, and performance analysis tools that are crucial for effective GPU programming. Hands-on exercises will provide immediate application of theoretical concepts using Texas A&M’s GPU clusters, ensuring participants develop both understanding and practical experience.


Day 2: MPI and Parallel Programming Patterns

The second day focuses on distributed computing using MPI, covering fundamental communication patterns, collective operations, and scalable algorithm design. Participants will learn to decompose computational problems across multiple processors and implement efficient communication strategies for large-scale parallel applications. The training emphasizes modern MPI features and best practices for achieving optimal performance on contemporary supercomputing architectures.


Day 3: Integrated MPI+CUDA Applications

The final day synthesizes knowledge from the previous sessions, teaching participants to develop applications that leverage both GPU acceleration and distributed computing. This includes managing GPU resources across multiple nodes, optimizing data movement between CPUs and GPUs in distributed environments, and implementing scalable multi-GPU algorithms. Real-world application examples will demonstrate the practical implementation of these advanced programming paradigms.

Travel Support


We will reimburse up to $800 in travel expenses for participants from outside the Bryan College Station area. After the workshop, we will reach out to collect receipts and reimburse you.

Texas A&M’s payment processing system requires non-TAMUS members to fill out a Substitute W9 & Vendor Direct Deposit Form. If you believe you are already set up in Texas A&M’s system, please let us know, and we can verify with our business administrators. Please fill out the applicable forms and return them to TAMIDS via emailing Angie Rollins (a-rollins@tamu.edu), faxing 979.458.7511, or handing in a physical copy during the event.

Remember to bring your Texas Hotel Occupancy Tax Exemption Certificate and Texas Sales and Use Tax Exemption Certificate while traveling to avoid paying taxes. We cannot reimburse any taxes you have paid. Additionally, State of Texas employees (non-TAMUS only) must also fill out a State of Texas Employee Statement to confirm that there is no conflict of interest in attending.

Workshop Organizers


Jian Tao Profile Picture

Dr. Jian Tao

Assistant Director for Project Development & TAMIDS Digital Twin Lab Director; Assistant Professor, Visual Computing and Creative Media Section (College of Performance, Visualization, & Fine Arts)
jtao@tamu.edu

Dr. Honggao Liu

Director, High Performance Research Computing
honggao@tamu.edu

Dr. John Dennis

Scientist, National Center for Atmospheric Research
dennis@ucar.edu

If you have any questions regarding the LAUNCH cluster, accessing the HPRC systems, or about the learning objectives, please email events@hprc.tamu.edu.

Travel support and logistics can be directed to Angie Rollins, Administrative Coordinator at the Texas A&M Institute of Data Science

PHONE: (979) 458-6252
FAX: (979) 458-7511
EMAIL: a-rollins@tamu.edu


Acknowledgement

The Advanced Computing Workshop is supported in part by the NSF Office of Advanced Cyberinfrastructure (OAC) award number 2232895  and by the National Center for Atmospheric Research (NCAR).