Rule-Based Framework for Assessing Organizational Maturity in HPC Infrastructure Adoption

Assessing organizational readiness for highperformance computing (HPC) adoption requires evaluation beyond hardware benchmarking, encompassing workforce capabilities, software maturity, data interoperability, and regulatory compliance. This paper presents a modular, rule-based decision-support framework implemented in Python that evaluates HPC maturity across five integrated dimensions and generates a phased migration roadmap through a weighted scoring model and recommendation engine. The framework employs a formally defined aggregation formula with configurable dimension weights, and its outputs are validated through a basic sensitivity analysis demonstrating score stability under weight variation. Demonstrated on two simulated organizational profiles-a mid-sized research institute and a public administration body-the framework identified critical gaps in workforce readiness and governance compliance, highlighting the role of non-technical factors in HPC transition planning and the practical value of transparent, reproducible maturity assessment for early-stage decision-making.