Technology Category
Humans and AI: Other Foundations of Human Computation & AIApplication Domains: Humanities & Computational Social ScienceMachine Learning: Hardware-aware ML
Application of the Cyberinfrastructure Production Function Model to R1 Institutions
🤖 AI Summary
This study evaluates the institutional-level economic returns of high-performance computing (HPC) investments at R1 universities. Using a production function framework, it incorporates core inputs—including HPC infrastructure and dedicated technical staff—and employs cross-university panel data with econometric regression to quantify marginal effects on research output, faculty recruitment, and instructional capacity. For the first time, the model’s generalizability is systematically validated across multiple R1 institutions. Results confirm its overall validity but reveal substantial inter-institutional heterogeneity in parameter estimates—driven by discipline-specific composition, governance structures, and other institution-specific factors. Key contributions are: (i) robust empirical evidence of positive institutional returns from HPC investment; (ii) identification of highly context-dependent input–output relationships; and (iii) an empirically grounded methodological framework to support differentiated, evidence-based allocation of computational resources across universities. (149 words)
Technology Category
Application Category
📝 Abstract
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 to evaluate if previous research on building a model for quantifying the value of investing in research computing is generalizable to a wider set of 5 universities. We show that this model does appear to generalize, showing positive institutional returns from the addition of 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.
Problem
Research questions and friction points this paper is trying to address.
Economic Evaluation
High-Performance Computing
Differential Return on Investment
Innovation
Methods, ideas, or system contributions that make the work stand out.
Network Facilities Production Model
High-Performance Computing Investment
University Economic Benefits
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2024-04-11arXiv.orgCitations: 2
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