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There is widespread belief in the computer science community that MPI is a difficult and time-intensive approach to developing parallel software. Nevertheless, MPI remains the dominant programming model for HPC systems, and many projects have made effective use of it. It remains unknown how much impact the use of MPI truly has on the productivity of computational scientists. In this paper, we examine a mature, ongoing HPC project, the Flash Center at the University of Chicago, to understand how MPI is used and to estimate the time that programmers spend on MPI-related issues during development. Our analysis is based on an examination of the source code, version control history, and regression testing history of the software. Based on our study, we estimate that about 20% of the development effort is related to MPI. This implies a maximum productivity improvement of 25% for switching to an alternate parallel programming model.