Cultivating Multidisciplinary AI Workforce Development on iTiger GPU Cluster: Practices and Challenges
This work addresses the problem of limited access to GPU infrastructure for educators, students, and researchers at under-resourced institutions in the Mid-South region, though it is incremental in nature.
The paper tackles the challenge of providing large-scale computing resources for under-resourced institutions by establishing the iTiger GPU cluster at the University of Memphis, resulting in initiatives like seed grants and workshops to support multidisciplinary AI research and education across fields such as precision agriculture and health informatics.
To support rapid AI advances and broaden access to large-scale computing resources for under-resourced institutions at the Mid-South, we established the first regional mid-scale GPU cluster at the University of Memphis (UofM), iTiger. We present and analyze efforts of infrastructure management and computational support for educators, students, and researchers across scientific and engineering disciplines, such as precision agriculture, smart transportation, and health informatics. We outline our initiatives to broaden cluster adoption on research and education, such as seed grant programs, workshop trainings, course integration, and other outreach activities. We also identify challenges and further discuss findings of GPU infrastructure adoptions among college students and multidisciplinary researchers. The insights will indicate how to effectively and broaden infrastructure adoption and integrate into research and workforce developments.