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Data intensive simulations are often limited by their I/O (input/output) performance, and"novel" techniques need to be developed in order to overcome thislimitation. The software package  pnetCDF (parallel network Common Data Form), which works with parallel filesystems, was developed to address this issue by providing parallel I/Ocapability. This study examines the performance of an application-level dataaggregation approach which performs data aggregation along either row orcolumn dimension of MPI (Message Passing Interface) processes on a spatially decomposed domain, and thenapplies the pnetCDF parallel I/O paradigm. The test was done with threedifferent domain sizes which represent small, moderately large, and largedata domains, using a small-scale Community Multiscale Air Quality model(CMAQ) mock-up code. The examination includes comparing I/O performance withtraditional serial I/O technique, straight application of pnetCDF, and thedata aggregation along row and column dimension before applying pnetCDF.After the comparison, "optimal" I/O configurations of this application-level data aggregation approach were quantified. Data aggregation along therow dimension (pnetCDFcr) works better than along the column dimension(pnetCDFcc) although it may perform slightly worse than the straight pnetCDFmethod with a small number of processors. When the number of processorsbecomes larger, pnetCDFcr outperforms pnetCDF significantly. If the numberof processors keeps increasing, pnetCDF reaches a point where theperformance is even worse than the serial I/O technique. This new techniquehas also been tested for a real application where it performs two timesbetter than the straight pnetCDF paradigm

An approach to enhance pnetCDF performance in environmental modeling applications