MRI: Acquisition of a GPU Cluster for Multi-Disciplinary Research and Education at University of Nevada, Las Vegas

The project funds the purchase and commissioning of a high-performance graphical processing unit (GPU) cluster at the University of Nevada, Las Vegas (UNLV). The project will address emergent and longer-term needs, challenges, and opportunities in research and educational efforts across multiple disciplines: biomedical research, intelligent transportation systems and automated vehicles, genomics, astronomy, and physics.

The project will help advance national initiatives in big data, strategic computing, artificial intelligence, and smart infrastructure systems. These will integrate, synthesize, model, and visualize large volumes of data from various sources as well as develop and apply Artificial Intelligence (AI) techniques to assist decision making. For applied and basic research aspects of the project, the GPU cluster will leverage advances in computing hardware, software, sensor networks, and communications systems.

Some elements of the project will address near-term societal needs to preserve and enhance the quality of living of individuals and families, support economic competitiveness and growth of businesses, and foster the vitality of communities. These include topics related to public health, transportation, environment, and energy. The project’s longer-term initiatives will address explorations and innovations in basic research in these domains as well as in astronomy, physics, and genomics.

These activities will include partnerships with academia, government entities, and private sector organizations. The project will support curricular and co-curricular activities for undergraduate and graduate students to increase their interests in related education, research, and career opportunities. As a Minority-Serving Institution and Hispanic Serving Institution, this grant will help UNLV to significantly expand such opportunities for students from varied socio-economic and socio-demographic communities.

Thus, an outcome of the project will be to help develop skilled work-forces from diverse backgrounds.

The GPU cluster will support basic and applied research, as well as educational programs across multiple disciplines. Common elements for the research efforts include integrating, synthesizing, modeling, and visualizing large volumes of data along with the development and application of various AI techniques to support decision making. Efforts in Biomedicine will be to stratify individuals at risk for benzodiazepine and opioid overdose using interpretable deep learning techniques using publicly available pluripotency transcription factors datasets.

Activities related to intelligent transportation systems and automated vehicles will address comprehensive trajectory prediction challenges for near real-time applications on transportation networks to help accelerate the deployment of Connected Automated Vehicles and Infrastructure Systems; they will use data from various in-vehicle, on-roadway, and roadside sensors. Research in Genomics will be to better understand the evolution of novel transcription factor (TF) binding sites originating from endogenous retrovirus (ERV) integration.

Astronomy related endeavors will be to estimate planet mass from protoplanetary disk images using Convolutional Neural Networks (CNN). Efforts in Physics will be to develop rotationally equivariant CNN to simulate and evaluate force fields at atomistic scales of materials. Educational aspects of the project will include curricular and co-curricular initiatives at the undergraduate and graduate levels to help alert, engage, excite, and motivate students to pursue education, research, and career opportunities in related fields. The project will include partnerships with public and private sector organizations and academia.

This project is jointly funded by the Major Research Instrumentation (MRI) program, the Established Program to Stimulate Competitive Research (EPSCoR), and the Computer & Information Science & Engineering (CISE) Directorate.

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.