Equipment: MRI: track #1 acquisition of high-performance computing cluster to support undergraduate research at trinity university

The National Science Foundation Office of Integrative Activities awarded Trinity University $750,000 for acquisition of a high-performance computing cluster to support undergraduate research under the Integrative Activities program (CFDA 47.083), effective August 1, 2026 through July 31, 2029.

The cluster features a hybrid CPU/GPU architecture with high-core-count processors, scientific-grade graphics processing units for artificial intelligence applications, dedicated high-memory nodes for whole-genome sequencing, and network-attached storage optimized for high-bandwidth, low-latency data transfers and data-intensive workflows. The system enables parallelized multiscale modeling and machine learning across multiple STEM disciplines. Trinity will integrate the computing infrastructure into undergraduate education across biology, computer science, chemistry, physics, mathematics, and engineering through classroom problem-solving, mentorship programs, summer research initiatives, and public outreach. The award targets workforce preparation in artificial intelligence and big data analysis while expanding participation among a diverse student population.

Place of performance is Olmos Park, Texas 78212.

Abstract

This award supports the acquisition of a high-performance computing cluster at trinity university to enable undergraduate research and training across multiple science, technology, engineering, and mathematics (stem) fields. Modern quantitative science increasingly depends on advanced computational infrastructure to solve complex scientific problems and to prepare the next generation of scientists to use these tools fluently. By integrating high-caliber computing tools into a primarily undergraduate institution, this project serves the national interest by directly preparing a diverse, skilled scientific workforce for highly skilled careers in artificial intelligence, big data analysis, and advanced research. The project expands participation for all students through established mentorship programs, summer research initiatives, and public outreach. IT also transforms undergraduate education by embedding computationally intensive, real-world problem-solving directly into the classroom across biology, computer science, chemistry, physics, mathematics, and engineering. Together, these efforts strengthen scientific literacy and contribute to societal benefit. This high-performance computing cluster establishes a hybrid CPU/GPU architecture featuring a scalable multi-node network optimized for high-bandwidth, low-latency data transfers and data-intensive workflows. The system is configured with high-core-count processors, scientific-grade graphics processing units (gpus) for artificial intelligence applications, dedicated high-memory nodes to facilitate whole-genome sequencing, and expansive network-attached storage. The platform utilizes optimized cluster management software to efficiently schedule concurrent, multi-disciplinary computing workflows. The primary technical objective is to enable parallelized multiscale modeling, machine learning, and complex simulations. Methodological approaches enabled by this instrument include applying deep neural networks to predict mammalian protein function, utilizing high-throughput bioinformatics and environmental DNA metabarcoding to survey amazonian biodiversity, constructing potential energy surfaces using density functional theory and post-hartree fock electronic structure models, and supporting multiscale molecular dynamics simulations of protein folding on complex cellular membranes and calibrated regularized stokeslet boundary methods to model computational fluid dynamics at low reynolds numbers. Together, these capabilities position trinity university to conduct cutting-edge, computationally driven research across disciplines at a scale typically inaccessible to primarily undergraduate institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.