An approach to enhance pnetCDF performance in environmental modeling applications.

Data intensive simulations are often limited by their I/O performance, and novel techniques need to be developed in order to overcome this limitation. The software package, pnetCDF which works with parallel file systems, was developed to address this issue by providing parallel I/O capability. This study examines the performance of a novel approach which performs data aggregation along either row or column dimension of MPI processes on a spatially decomposed domain, and then applies the pnetCDF parallel I/O paradigm. The test was done with three different domain sizes which represent small, moderately large, and large data domains, using a small-scale Community Multi-scale Air Quality model (CMAQ) mock-up code. The examination includes comparing I/O performance with traditional serial I/O technique, straight application of pnetCDF, and the data aggregation along row and column dimension before applying pnetCDF. After the comparison, "optimal" I/O configurations of this novel approach were quantified. Data aggregation along the row dimension (pnetCDFcr) works better than along the column dimension (pnetCDFcc) although it may perform slightly worse than the straight pnetCDF method with a small number of processors. When the number of processors becomes larger, pnetCDFcr out performs pnetCDF significantly. If the number of processors keeps increasing, pnetCDF reaches a point where the performance is even worse than the serial I/O technique. This new technique has also been tested for a real application where it performs two times better than the straight pnetCDF paradigm. [ABSTRACT FROM AUTHOR]