# A High Performance Research Image Repository (RIR) for the Washington University Center of High Performance Computing (CHPC)

> **NIH NIH S10** · WASHINGTON UNIVERSITY · 2021 · $1,927,344

## Abstract

Project Summary/Abstract:
We propose to build a Research Image Repository (RIR) to house large collections of biomedical imaging data.
The RIR will include datasets produced locally at Washington University: The Connectome Coordination
Facility (CCF) (which itself includes the Human Connectome Project (HCP) Young Adult study, The Lifespan
related projects, the Disease related projects, and assorted HCP-related projects), The Knight Alzheimer
Disease Research Center (ADRC), the Adolescent Brain Cognitive Development (ABCD) Study, The
Comprehensive Neuro-Oncology Data Repository (CONDR), and the clinically-based PACS image repository.
In addition, copies of external data collections such as the UK Biobank, The Alzheimer's Disease
Neuroimaging Initiative (ADNI), and The Cancer Image Archive (TCIA) will be maintained. The RIR includes a
data management software solution that will introduce many novel features (such as `data tagging' to enrich
datasets, and advanced search features) and will allow us to leverage existing storage including the Center for
High Performance Computing's (CHPC) 1.4PB of BeeGFS `scratch' storage, solid-state NVMe drives
integrated into the compute nodes, and 10PB of ZFS-based storage. All storage will be presented to the user
as a single file-system, while data will be migrated to different performance tiers based on the storage
requirements of the datasets or processing algorithms. The RIR will be integrated into the CHPC for data
processing. The proposal also includes two NVIDIA DGX A100 GPU servers providing state-of-the-art GPU-
based processing power. The combination of high-quality, diverse sets of biomedical imaging data with next-
generation computing power will have a transformative effect on biomedical imaging processing pipelines and
nowhere will the effects be more profound than in the emerging field of Deep Learning for image processing.

## Key facts

- **NIH application ID:** 10177147
- **Project number:** 1S10OD030477-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Daniel Scott Marcus
- **Activity code:** S10 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,927,344
- **Award type:** 1
- **Project period:** 2021-04-25 → 2024-04-24

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10177147

## Citation

> US National Institutes of Health, RePORTER application 10177147, A High Performance Research Image Repository (RIR) for the Washington University Center of High Performance Computing (CHPC) (1S10OD030477-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10177147. Licensed CC0.

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