# A high performance computing cluster to support structural biology

> **NIH NIH S10** · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · 2024 · $571,780

## Abstract

Project Summary/Abstract (Description)
The aim of this Shared Instrumentation Grant application is to provide the growing structural biology
community at UT Health San Antonio (UTHSA) with access to High-Performance Computing capabilities. The
UTHSA Structural Biology Core Facility (SBC) enjoys a rich 25-year history in structural biology with a
consistent group of NIH-funded researchers using structural techniques (cryo-EM, X-ray crystallography, and
NMR) as a hallmark of their research programs focused on drug discovery and basic mechanisms aiming to
improve human health. While the SBC has managed to provide users with adequate computational and
storage resources to process X-ray crystallography and NMR data over the years, a severe computational
bottleneck for SBC users has arisen due to: 1) the recent addition of cryo-EM to the suite of structural biology
tools available at UTHSA and 2) the emergence of AI-based software used to process experimental structural
biology data and for modeling of large protein complexes. Both of these use cases require powerful hardware
that is currently unavailable anywhere on campus and is cost prohibitive for most individual investigators,
thereby creating a barrier to entry that limits the impact the SBC has on its users’ research programs.
These computing needs of the SBC are best served by dedicated hardware specifically tailored to meet the
system requirements of workhorse software used for cryo-EM, X-ray crystallography, and NMR data
processing. The proposed equipment prioritizes shared memory, high-throughput architecture, and storage
and consists of a GPU cluster of 6 nodes with 24 RTX A6000 GPUs with 48GB RAM in addition to a single
node with 4 state-of-the art A100 GPUs with 80 GB RAM. Each node comes with 2x Intel Xeon scalable 16-
core processors. For further parallelization and for less computation-heavy processes, a CPU cluster of 4x
Intel Xeon Scalable Gold 6330H Processor 24-Cores is included along with 1.5 petabytes of raw storage
capacity. This state-of-the-art configuration will allow SBC users to tap into all of the latest software for
structural biology data processing and is particularly well-suited for computationally intensive cryo-EM and AI-
based data processing that is sorely needed on our campus.
The proposed High-Performance Computing Cluster will be housed in the University’s Advanced Data Center
and will provide cost-effective resources for 15-20 UTHSA SBC users to simultaneously process cryo-EM, X-
ray, and NMR data using current state-of-the-art software while also opening up AI-based processing capability
to an even larger cohort of investigators on campus. The cluster will provide a boost to the productivity and
accessibility of our new cryo-EM laboratory at a crucial time in its development, while extending the capabilities
of longstanding SBC infrastructure. From a broader perspective, the cluster will accelerate the research efforts
of NIH-funded investigators, enrich the i...

## Key facts

- **NIH application ID:** 10852228
- **Project number:** 1S10OD036251-01
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
- **Principal Investigator:** Shaun Olsen
- **Activity code:** S10 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $571,780
- **Award type:** 1
- **Project period:** 2024-05-15 → 2025-05-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10852228

## Citation

> US National Institutes of Health, RePORTER application 10852228, A high performance computing cluster to support structural biology (1S10OD036251-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10852228. Licensed CC0.

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