Increasing the Scalability of PISM for High Resolution Ice Sheet Models

The issue of global climate change is of great interest to scientists and a critical concern of society at large. One important piece of the climate puzzle is how the dynamics of large-scale ice sheets, such as those in Greenland and Antarctica, will react in response to such climate change. Domain scientists have developed several simulation models to predict and understand the behavior of large-scale ice sheets, but the depth of knowledge gained from such models is largely dependent upon the resolution at which they can be efficiently executed. The problem, however, is that relatively small increases in the resolution of the model result in very large increases in the size of the input and output data sets, and an explosion in the number of grid points that must be considered by the simulation. Thus, increasing the resolution of ice-sheet models, in general, requires the use of supercomputing technologies and the application of tools and techniques developed within the high-performance computing research community. In this paper, we discuss our work in evaluating and increasing the performance of the Parallel Ice Sheet Model (PISM) [6, 25, 38], using a high-resolution model of the Greenland ice sheet, on a state-of-the-art supercomputer. In particular, we found that the computation performed by PISM was highly scalable, but that the I/O demands of the higher-resolution model were a significant drag on overall performance. We then performed a series of experiments to determine the cause of the relatively poor I/O performance and how such performance could be improved. By making simple changes to the PISM source code and one of the I/O libraries used by PISM we were able to provide an 8-fold increase in I/O performance.