Application of the Cyberinfrastructure Production Function Model to R1 Institutions

Preston Smith^1*Jill Gemmill²David Hancock³Brian O'Shea⁴Winona Snapp-Childs³James Wilgenbusch⁵

• ¹Purdue University, West Lafayette, United States
• ²Clemson University, Clemson, South Carolina, United States
• ³Indiana University, Bloomington, Indiana, United States
• ⁴Michigan State University, East Lansing, Michigan, United States
• ⁵University of Minnesota Twin Cities, St. Paul, Minnesota, United States

High-performance computing (HPC) is widely used in higher education for modeling, simulation, and AI applications. A critical piece of infrastructure with which to secure funding, attract and retain faculty, and teach students, supercomputers come with high capital and operating costs that must be considered against other competing priorities. This study applies the concepts of the production function model from economics with two thrusts: 1) to evaluate if previous research on building a model for quantifying the value of investment in research computing is generalizable to a wider set of universities, and 2) to define a model with which to capacity plan HPC investment, based on institutional production -inverting the production function. We show that the production function model does appear to generalize, showing positive institutional returns from the investment in computing resources and staff. We do, however, find that the relative relationships between model inputs and outputs vary across institutions, which can often be attributed to understandable institution-specific factors.