Page 5 - 2022 OIT Progress Report

Research and Data Science Make Inroads to R1
In less than four years, the OIT Research and Data Science Services
team has grown to include experts in data science, high-performance computing, the Internet of Things (IoT), and artificial intelligence. The small yet agile team has assisted all areas of the SMU community by consulting on and supporting research projects across multiple disciplines.
This past year they have advanced high-performance computing in Texas by deploying, alongside the OIT Infrastructure Team, the second NVIDIA DGX SuperPOD at a US university. This exciting development was the result of a partnership with NVIDIA to make SMU a hub for AI innovation in North Texas. The SuperPOD increases the University’s current supercomputer memory tenfold and sets the stage for AI and machine learning 25 times faster than current levels by producing a theoretical 100 petaflops of computing power. This commitment to high performance computing helps pave the way for SMU on the road to R1 by providing educational opportunities and new artificial intelligence (AI) projects.
University President R. Gerald Turner remarked, “This partnership will put us in the fast lane for artificial intelligence. Research universities like ours have an obligation to actively engage in the development and application of AI for societal good, and this partnership gives us the tools to do it.”
The OIT Research and Data Science Services team has also been working with the Center for Research Computing to provide computational and digital data infrastructure necessary to support the research endeavors of SMU’s faculty, including training and outlining the framework for M3, a new research cluster to come online in Spring 2023.
“This partnership is a significant boost to our plans for high-performance computing prowess in the academic realm and the expansion of data science across the SMU curriculum,” said Elizabeth Loboa, SMU Provost and Vice President for Academic Affairs. “This will be of great value to our faculty and students who are already using accelerated computing in areas such as drug discovery, computational chemistry, virtualization, astrophysics and engineering.”
RESEARch And dATA ScIEncE mAkE InROAdS TO R1
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