Resumen
I/O is often a performance bottleneck in global ocean circulation models with fine spatial resolution. In this paper, we present an asynchronous parallel I/O framework and demonstrate its efficacy in the Mass Conservation Ocean Model (MaCOM) as a case study. By largely reducing I/O operations in computing processes and overlapping output in I/O processes with computation in computing processes, this framework significantly improves the performance of the MaCOM. Through both reordering output data for maintaining data continuity and combining file access for reducing file operations, the I/O optimizing algorithms are provided to improve output bandwidth. In the case study of the MaCOM, the cost of output in I/O processes can be overlapped by up to 99% with computation in computing processes as decreasing output frequency. The 1D data output bandwidth with these I/O optimizing algorithms is 3.1 times faster than before optimization at 16 I/O worker processes. Compared to the synchronous parallel I/O framework, the overall performance of MaCOM is improved by 38.8% at 1024 computing processes for a 7-day global ocean forecast with 1 output every 2 h through the asynchronous parallel I/O framework presented in this paper.