@InProceedings{ching:efficient,
  author = {Avery Ching and Alok Choudhary and Wei-keng Liao and Robert Ross
  and William Gropp},
  title = {Efficient structured data access in parallel file systems},
  booktitle = {Proceedings of the IEEE International Conference on Cluster
  Computing},
  year = {2003},
  month = {December},
  pages = {326--335},
  institution = {Northwestern Univ, Dept Elect \& Comp Engn, Evanston, IL 60208
  USA},
  publisher = {IEEE Computer Society Press},
  address = {Hong Kong, China},
  URL =
  {http://www.ece.northwestern.edu/~wkliao/SciDAC/Publications/cluster2003.pdf},
  keywords = {I/O interface, high-level libraries, PVFS, structured data
  representations, pario-bib},
  abstract = {Parallel scientific applications store and retrieve very large,
  structured datasets. Directly supporting these structured accesses is an
  important step in providing high-performance I/O solutions for these
  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. However, parallel file
  systems do not traditionally support such access. In this work, we present 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 by using a
  reusable datatype-processing component from the MPICH2 MPI implementation. We
  describe how this component is leveraged to efficiently process structured
  data representations resulting from MPI-IO operations. We quantitatively
  assess the solution using three test applications. We also point to further
  optimizations in the processing path that could be leveraged for even more
  efficient operation.},
  comment = {not read, don't have}
}