Year: 2025
Type: article
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 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.
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,418
Funder: National Science Foundation
Awards: High Performance Computing System Acquisition: Jetstream - A Self-Provisioned, Scalable Science and Engineering Cloud Environment, Category I: Anvil - A National Composable Advanced Computational Resource for the Future of Science and Engineering, Collaborative Research: SCIPE: CyberInfrastructure Professionals InnoVating and brOadening the adoption of advanced Technologies (CI PIVOT), RCN:CIP: Midwest Research Computing and Data Consortium, Category I: Jetstream 2: Accelerating Science and Engineering On-Demand
OpenAlex ID: W4413367934