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Application of the cyberinfrastructure production function model to R1 institutions
Preston M Smith1, Jill Gemmill2, David Y Hancock3
1Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN, United States.
Frontiers in Research Metrics and Analytics
|September 8, 2025
Summary
Investment in high-performance computing (HPC) infrastructure yields positive institutional returns in higher education. The production function model effectively quantifies the value of research computing, though specific outcomes vary by institution.
Area of Science:
- Economics
- Computer Science
- Higher Education Administration
Background:
- High-performance computing (HPC) is integral to higher education for modeling, simulation, and AI.
- Supercomputers represent significant capital and operating costs, necessitating careful investment evaluation.
Purpose of the Study:
- To assess the generalizability of a production function model for quantifying research computing investment value across universities.
- To develop a model for capacity planning of HPC investments by inverting the production function.
Main Methods:
- Application of economic production function concepts.
- Evaluation of model generalizability across diverse university settings.
- Inversion of the production function for HPC capacity planning.
Main Results:
- The production function model demonstrates generalizability and indicates positive institutional returns on HPC investment.
- Investment in computing resources and staff positively impacts institutional outcomes.
- Relative input-output relationships within the model vary across institutions due to specific factors.
Conclusions:
- The production function model is a viable tool for evaluating HPC investments in higher education.
- Positive returns justify investment in research computing infrastructure and personnel.
- Institution-specific factors necessitate tailored approaches to HPC capacity planning.
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