High Performance Research Computing

Dates and Location

Apply Dates: July 18, 2025 - July 20, 2025 (Friday – Sunday)
Location: Sonesta Columbus Downtown, Columbus OH (map)
Application Deadline: June 13, 2025

Travel Support is Available!

Overview

Please join Texas A&M High Performance Research Computing (HPRC) for the third ACES Researcher Workshop. You’ll learn how the ACES (Accelerating Computing for Emerging Sciences) testbed complements the National Science Foundation’s (NSF) portfolio of advanced cyberinfrastructure (CI) resources and services. This pre-conference workshop, ahead of the Practice & Experience in Advanced Research Computing (PEARC25) conference, allows participants to meet kindred community members and future collaborators from across the country.

ACES features a menu of accelerators in a hardware composable infrastructure designed to excel with artificial intelligence/machine learning (AI/ML) tasks with an Open OnDemand interface that commands a robust and growing software ecosystem. The ACES advanced user support team will conduct tutorials demonstrating how ACES can be used to solve data-intensive AI/ML tasks with greater speed, precision and efficiency. Participants from all domains are welcome to deliver lightning talks about their own ACES experience, and share how it has influenced their plans for the future.

Registration waivers, travel support and lodging are available for a limited number of U.S.-based academic applicants. Non-academic industry or government affiliates will be charged a $350 registration fee. If you have questions, or if you’d like to present your research, please contact: events@hprc.tamu.edu.

The application requires a brief description of your current research, future plans for using ACES, and a copy of your NSF biosketch. Questions and offers to assist are welcome!

Tutorials will include running AI/ML and other common HPC workloads using the novel accelerators on ACES. Check back regularly for updated details on the tutorials sessions.

Schedule (Subject to Change, all times are EDT)

Last updated: May 20, 2025

Friday, July 18	Reception and Dinner
	Sonesta Columbus Downtown Map Address: 33 East Nationwide Blvd, Columbus, OH 43215
4:00PM - 5:00PM	Opening Remarks and Overview of the ACES Project
5:00PM - 6:00PM	Reception
6:00PM - 9:00PM	Buffet Dinner

Saturday, July 19	Tutorials and Lightning Talks
8:00AM - 9:00AM	Continental Breakfast
9:00AM - 12:00PM	Morning Tutorials
12:00PM - 1:30PM	Lunch and Lightning Talks
1:30PM - 5:00PM	Afternoon Tutorials
6:00PM - 9:00PM	Dinner

Sunday, July 20	Tutorials and Special Session
8:00AM - 9:00AM	Continental Breakfast
9:00AM - 12:00PM	Morning Tutorials
12:00PM - 1:00PM	Lunch
1:00PM - 5:00PM	Afternoon Special Session and Office Hours

ACES Testimonials:

Ruisi Cai (UT-Austin) uses ACES to process long context sequences in Large Language Models (LLMs). “Due to transformers’ quadratic memory requirements, LLMs command substantial computational power and agile memory management,” said Cai. The UT-Austin team developed a unique approach that was highlighted in a paper titled, “Learning to Compress Long Contexts by Dropping-In Convolutions.” Their paper was accepted by the International Conference on Machine Learning (ICML24).

Aocheng Li (Purdue) uses ACES for data-driven archaeological site reconstruction. They said, “I love its elegant and light-weight web interface for file manipulation and job creation/submission. Using the composability features, I combine virtual network computing and TensorBoard servers to launch jobs and monitor training output with just a few clicks - all within one browser session. The HPRC staff are extremely helpful, and are quick to solve my issues and concerns. Using ACES has been an enjoyable experience.”

Freddie Witherden (Texas A&M Department of Ocean Engineering) used ACES to perform high-order accurate fluid flow calculations of bluff bodies. “The range of hardware, including CPUs, NVIDIA GPUs, and Intel GPUs, is perfect for the development, testing, and evaluation of performance-portable coding paradigms. Additionally, the large-memory nodes have proved invaluable for enabling us to perform preprocessing work for simulations on leadership-class computing resources.”

Rubem Mondaini (University of Houston) uses ACES to study quantum many-body problems in Condensed Matter Physics with the goal of understanding how Coulomb repulsion between electrons can affect quantum matter topology. "ACES’ abundant supply of the latest CPUs (Sapphire Rapids), large memory and fast interconnect make it possible to reach physical system sizes unforeseen until now," said Dr. Mondaini. “This unique combination of assets makes all the difference with investigations in the quantum world,” he added.

Chen-Chun Chen (Ohio State University NOWLAB) primarily uses the Intel GPUs and XeLink nodes on ACES. “Using TensorFlow and Horovod, I’ve been running OSU Micro Benchmarks (OMB) to extend the MVAPICH library to support Intel PVC GPUs,” he said, and added, “I receive invaluable assistance from the HPRC helpdesk, and my experiments on ACES have been consistently smooth.”

Junyuan Hong (UT-Austin) cited ACES in his latest research which presents a new method for private prompt tuning of LLMs, like ChatGPT. The solution is called Differentially-Private Offsite Prompt Tuning (DP-OPT) which employs a discrete client-side prompt that can be applied to desired cloud models without significantly compromising performance.

Wonmuk Hwang (Texas A&M Department of Biomedical Engineering) performs molecular dynamics simulations of biomolecules - a task best performed with state-of-the-art computational resources. Dr. Hwang uses ACES to investigate the mechanical response of T-cell receptors which defend against pathogens like influenza and the SARS CoV-2 virus that was responsible for the COVID pandemic. “The NVIDIA H100s are great for carrying out multiple simulations, and the HPRC staff are always helpful when troubleshooting aspects of this novel testbed,” he said.

Hanning Chen (Texas Advanced Computing Center) used ACES to conduct a Molecular Dynamics (MD) simulation of Satellite Tobacco Mosaic Virus with more than 28 million atoms. “MD simulations of large biological systems are significant because they reveal functions contributed by millions of atoms, or more,” he said, and added, “Our benchmark test with NAMD3 and a 64-node run revealed a performance of 4.8 ns/day, with an impressive 80 percent scaling factor when we increased the number of nodes from 1 to 64. ACES is a powerful tool for MD simulations, and the HPRC support team’s knowledge of this novel platform helps researchers progress quicker.”

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Acknowledgment

The ACES team gratefully acknowledges support from the NSF. The ACES project is supported by the Office of Advanced Cyberinfrastructure (OAC) award number 2112356. For more information about ACES, please visit https://hprc.tamu.edu/aces/.

Contact Information

Phone: 979-845-0219
Email: events@hprc.tamu.edu

Texas A&M High Performance Research Computing