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. We present an implementation of parallel I∕O in theModular Ocean Model (MOM), a numerical ocean model used for climateforecasting, and determine its optimal performance over a range of tuningparameters. Our implementation uses the parallel API of the netCDF library,and we investigate the potential bottlenecks associated with the modelconfiguration, netCDF implementation, the underpinning MPI-IOlibrary/implementations and Lustre filesystem. We investigate theperformance of a global 0.25 ∘ resolution model using 240 and 960 CPUs. The best performance is observed when we limit the number ofcontiguous I∕O domains on each compute node and assign one MPI rank toaggregate and to write the data from each node, while ensuring that all nodesparticipate in writing this data to our Lustre filesystem. These best-performance configurations are then applied to a higher 0.1 ∘ resolution global model using 720 and 1440 CPUs, where we observe evengreater performance improvements. In all cases, the tuned parallel I∕O implementation achieves much faster write speeds relative to serialsingle-file I∕O , with write speeds up to 60 times faster at higherresolutions. Under the constraints outlined above, we observe that theperformance scales as the number of compute nodes and I∕O aggregators areincreased, ensuring the continued scalability of I∕O -intensive MOM5 modelruns that will be used in our next-generation higher-resolution simulations.

Parallel I∕O in Flexible Modelling System (FMS) and Modular Ocean Model 5 (MOM5)