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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. 

A central focus of evolutionary biology is inferring the historical relationships among species and using this context to learn about how evolution has shaped diverse organisms. These historical relationships are represented by phylogenetic trees, and the methods used to infer these trees have been an active area of research for several decades. Despite this attention, phylogenetic workflows have changed little, even though extraordinary advances have occurred in the scale and pace at which genomic data have been collected in the past 20 years. Modern phylogenomic datasets have also raised fascinating new questions. Why do different parts of a genome often support different relationships among species? How are these different signals distributed across chromosomes? We developed a new computational framework, CloudForest, to tackle such questions. CloudForest is flexible, efficient, and tightly integrates a diverse set of tools. Here, we briefly describe the architecture of CloudForest, including the advantages it provides, and use it to investigate the distribution of phylogenetic signal along the entire X chromosome of 24 cat (Felidae) species.