Abstract
Modern data-intensive structured datasets constantly undergo manipulation and migration through parallel scientific applications. Directly supporting these time-consuming operations is an important step in providing high-performance I/O solutions for modern large-scale applications. High-level interfaces such as HDF5 and parallel netCDF provide convenient APIs for accessing structured datasets, and the MPI IO interface also supports efficient access to structured data. Parallel file systems do not traditionally support such structured access from these higher level interfaces. In this work, we present two contributions. First, we demonstrate an implementation of structured data access support in the context of the Parallel Virtual File System (PVFS). We call this support 'datatype I/O' because of its similarity to MPI datatypes. This support is built with a reusable datatype-processing component from the MPICH2 MPI implementation. The second contribution of this work is a comparison of I/O characteristics of modern high-performance noncontiguous I/O methods.We use our I/O characteristics comparison to assess all the methods using three test applications. We also point to further optimisations that could be leveraged for even more efficient operation.
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