Abstract
This paper presents the Stony Brook Parallel Ocean Model (sbPOM) for execution on workstations, Linux clusters and massively parallel supercomputers. The sbPOM is derived from the Princenton Ocean Model (POM), a widely used community ocean circulation model. Two-dimensional data decomposition of the horizontal domain is used with a halo of ghost cells to minimize communication between processors. Communication consists of the exchange of information between neighbor processors based on the Message Passing Interface (MPI) standard interface. The Parallel-NetCDF library is also implemented to achieve a high efficient input and output (I/O). Parallel performance is tested on an IBM Blue Gene/L massively parallel supercomputer, and efficiency using up to 2048 processors remains very good.
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