GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications
NIBIB - National Institute of Biomedical Imaging and Bioengineering
About This Grant
Project Summary/Abstract Computation and high-performance computing are essential to advancing biomedical research and healthcare applications, driving progress in areas such as wearable health technology, medical image analysis, and health informatics. These fields require substantial computational power to process and analyze large datasets from diverse sources, including sensor data, medical images, and electronic health records (EHR). The ability to utilize GPU acceleration for deep learning model development and real-time data processing is critical for addressing the growing complexity of data-driven healthcare applications. As such, the proposal is to acquire a dedicated GPU server to support biomedical research and educational efforts across two UNT colleges: the College of Engineering and the College of Information Science. The proposed Dell PowerEdge XE9680 Rack Server, equipped with 8 NVIDIA HGX H100 80GB SXM5 GPUs, will provide the necessary computational resources to enable cutting-edge biomedical research and enhance student education in health technologies. This GPU cluster will support research projects focused on AI-driven health monitoring systems, including wearable devices for diabetes management and hydration monitoring, as well as applications in medical image processing and natural language processing for health informatics. The server will be used in various graduate-level courses in both colleges, including those focused on medical image acquisition, processing, and AI applications in clinical settings. The GPU cluster will facilitate the development and deployment of complex machine learning models, including vision transformers (ViTs), convolutional neural networks (CNNs), and transformer-based models, for tasks such as disease detection, image classification, and biomedical data analysis. The requested GPU infrastructure is crucial for enabling high-performance computing in biomedical and health informatics research. It will enable students and researchers to process large datasets in real-time, accelerate the training of deep learning models, and support the integration of multimodal data streams from medical images and sensor data for comprehensive health monitoring solutions. The server will also enhance the hands-on learning experience for students by providing access to cutting-edge computational tools used in AI-driven healthcare systems. This will better prepare students for careers in health technology, research, and digital medicine. Given the loss of access to Talon 3.0, the proposed GPU server will fill the gap in computational resources, ensuring that UNT’s research teams and students have access to the necessary infrastructure to support innovative research and training in health technology and biomedical applications. The availability of this powerful system will continue to drive advancements in biomedical sciences, contributing to breakthroughs in areas such as skin cancer detection, kidney tissue analysis, and clinical decision support systems. The integration of this GPU-powered infrastructure will position UNT as a leader in AI and health informatics, providing critical support for interdisciplinary research and educational programs across the College of Engineering and the College of Information Science.
Grant Summary
GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications is a NIBIB - National Institute of Biomedical Imaging and Bioengineering grant providing up to $250K for university, nonprofit, healthcare org. Applications are due 2027-07-31 (open). Check eligibility and apply with FindGrants.
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Focus Areas
Eligibility
How to Apply
Up to $250K
2027-07-31
- 1Confirm your organization is eligible for GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications from NIBIB - National Institute of Biomedical Imaging and Bioengineering, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIBIB - National Institute of Biomedical Imaging and Bioengineering before the deadline.
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GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications: Frequently Asked Questions
Who is eligible for the GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications?
GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications is offered by NIBIB - National Institute of Biomedical Imaging and Bioengineering and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications provide?
GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications provides up to $250K per award from NIBIB - National Institute of Biomedical Imaging and Bioengineering. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications deadline?
Applications for GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications are due 2027-07-31 (open). Because deadlines can change, verify the date with the funder, NIBIB - National Institute of Biomedical Imaging and Bioengineering, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications?
To apply for GPU-Accelerated Computational Infrastructure for Biomedically-Driven Applications, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIBIB - National Institute of Biomedical Imaging and Bioengineering.