Abstract
The FLASH code is a computational science tool for simulating and studying thermonuclear reactions. The program periodically outputs large checkpoint files (to resume a calculation from a particular point in time) and smaller plot files (for visualization and analysis). Initial experiments on BlueGene/P spent excessive time in input/output (I/O), making it difficult to do actual science. Our investigation of time spent in I/O revealed several locations in the I/O software stack where we could make improvements. Fixing data corruption in the MPI-IO library allowed us to use collective I/O, yielding an order of magnitude improvement. Restructuring the data layout provided a more efficient I/O access pattern and yielded another doubling of performance, but broke format assumptions made by other tools in the application workflow. Using new nonblocking APIs in the Parallel-NetCDF library allowed us to keep high performance and maintain backward compatibility. The I/O research community has studied a host of optimizations and strategies. Sometimes the challenge for applications is knowing how to apply these new techniques to production codes. In this case study, we offer a demonstration of how computational scientists, with a detailed understanding of their application, and the I/O community, with a wide array of approaches from which to choose, can magnify each other's efforts and achieve tremendous application productivity gains.
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