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MPI collective I/O is a widely used I/O method that helps data-intensive scientific applications gain better I/O performance. However, it has been observed that existing collective I/O strategies do not perform well due to the access contention problem. Existing collective I/O optimization strategies mainly focus on the I/O phase efficiency and ignore the shuffle cost that may limit the potential of their performance improvement. We observe that as the size of I/O becomes larger, one I/Odoi:10.1109/ccgrid.2014.61 dblp:conf/ccgrid/WangSJWC14 fatcat:yidrtylnnrafpmdl3i7bycygne