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Florida’s First NSF-funded AI and Deep Learning Laboratory

From left: Carolina Schultz de Oliveira, HPC administrator in ����Ƶ’s Office of Information Technology (OIT); Xingquan (Hill) Zhu, Ph.D., principal investigator and a professor in ����Ƶ’s Department of Computer and Electrical Engineering and Computer Science; and Rhian Resnick, associate director of research computing, Enterprise Systems, in ����Ƶ’s OIT. (Photo by Alex Dolce)

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’s , in collaboration with researchers from ����Ƶ’s and ����Ƶ’s , one of the university's four research pillars, has received a $652,820 grant from the National Science Foundation (NSF) to establish the first NSF-funded Major Research Instrumentation (MRI) Artificial Intelligence and Deep Learning (AIDL) Training and Research Laboratory in Florida. 

NSF’s MRI program serves to increase access to multi-user scientific and engineering instrumentation for research and research training in institutions of higher education and not-for-profit scientific/engineering research organizations in the United States.

Hosted at the university, ����Ƶ’s AIDL laboratory will be shared across multiple campuses and research disciplines and will significantly advance ����Ƶ’s role in artificial intelligence and deep learning-based intelligent information analysis. 

“This important National Science Foundation grant will enable us to create an infrastructure for a deep learning platform for health, web services, biomedicine and ocean research as well as other related domains at ����Ƶ,” said , Ph.D., dean of ����Ƶ’s College of Engineering and Computer Science. “This laboratory will provide a training hub for our university and industry partners to work closely on advancing artificial intelligence applications to stimulate South Florida’s technical innovations and task force development, which will ultimately benefit economic growth in this region.”

Artificial intelligence and deep learning are fast evolving and making significant strides to transform heavily regulated industries such as financial services, health care, and the life science industry as it relates to tissue engineering, cancer detection, and pervasive sensing. The cores of these applications are intensive computing and learning units, which feed data to repetitive training process and output reliable statistical/predictive models. In many cases, training is computationally demanding and takes days or months to have a well-trained deep learning model if carried out on traditional CPU-based systems. On the other hand, researchers in health, biomedical science, and various engineering fields often do not receive sufficient training in using the most powerful artificial intelligence and deep learning approaches. This is because these hardware and software platforms rarely are part of the information technology resources available for researchers outside the field of computer science.

“Our laboratory aims to close this gap and support computational intensive tasks in numerous domains and provide a great opportunity for investigators to address some of the most difficult challenges in their domains and significantly advance research in their fields,” said , Ph.D., principal investigator (PI) of the grant and a professor in ����Ƶ’s .

����Ƶ’s AIDL laboratory infrastructure features a graphics processing unit (GPU) cluster – a computer cluster that enables the performance of very fast calculations – and includes 18 GPU servers and 72 Nvidia Tesla V-100 GPU cards and a 38.4 Terabyte flash memory server. The GPU cards are among the world’s best technology for artificial intelligence and deep learning. This project will nearly quadruple the number of GPU cards at ����Ƶ from 31 to 103 cards and will increase the onboard GPU memory six times from 381GB to 2,304 GB.

The platform will be shared across ����Ƶ’s campuses, resulting in a centralized cross-campus interdisciplinary platform and augmented deep learning and related artificial intelligence tools for interdisciplinary research. The AIDL laboratory also will serve as the training and research platform to support graduate student teaching and research activities across multiple campuses, colleges, and disciplines as well as ����Ƶ’s research pillars (����Ƶ , ����Ƶ Biomedical Research Institute, , ����Ƶ Institute for Sensing and Embedded Network Systems Engineering, , and ����Ƶ’s Harbor Branch).

Spearheaded by Zhu, the project includes 12 investigators (co-PIs and senior personnel). Co-PI’s of the project from ����Ƶ’s Department of Computer and Electrical Engineering and Computer Science are , Ph.D., Motorola professor; , Ph.D., professor, I-SENSE Fellow and Charles E. Schmidt Eminent Scholar in Engineering; and , Ph.D., associate chair and professor; and , Ph.D., associate research professor in ����Ƶ’s Harbor Branch.

Senior personnel for the project from ����Ƶ’s Department of Computer and Electrical Engineering and Computer Science are , Ph.D., assistant professor and director of ����Ƶ’s Cyber Threat Intelligence Laboratory and ; , Ph.D., associate chair and professor; , Ph.D., assistant professor; , Ph.D., assistant professor and I-SENSE Fellow; and , Ph.D., assistant professor. Representing ����Ƶ’s Schmidt College of Medicine are , Ph.D., director of faculty development and ombudsman, and , Ph.D., distinguished professor.

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