Modeling The Productivity Of Hpc Systems On A Computing Center Scale

In pursue of exaflop computing, the expenses of 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. In this work, we model overall productivity from a computing center's perspective. The productivity model uses as value the number of application runs possible during the lifetime of a given supercomputer. The cost is the total cost of ownership (TCO) of an HPC center including costs for administration and programming effort. For the latter, we include techniques for software cost estimation of large codes taken from the domain of software engineering. As tuning effort increases when more performance is required, we further focus on the impact of the 80-20 rule when it comes to development effort. Here, performance can be expressed with respect to Amdahl's law. Moreover, we include an asymptotic analysis for parameters like number of compute nodes and lifetime. We evaluate our approach on a real-world case: an engineering application in our integrative hosting environment.