A Methodology Towards Software Metrics for an Estimation of Total Cost of Ownership in High-Performance Computing
In pursuit of exaflop computing, the expenses of high-performance computing (HPC) centers increase in terms of acquisition, energy, employment, and programming. Thus, a quantifiable metric for productivity as value per cost gets more important to make an informed decision on how to invest available budgets. Productivity with respect to a computing center is influenced by the runtime of parallel applications (i.e. getting a certain value) and the centers total cost of ownership (TCO). The latter is also dependent on developer costs. These are possibly again dependent on the project size, the kind of application, personnel factors (e.g. knowledge of a certain programming model), the programming model itself, the architecture and the programming environment. This work deals with the investigation of the impact and importance of these factors to finally create a methodology for software and total ownership cost estimation in high-performance computing.