@TechReport{thomas:panda,
  author = {Joel T. Thomas},
  title = {The {Panda} Array {I/O} Library on the {Galley} Parallel File
  System},
  year = {1996},
  month = {June},
  number = {PCS-TR96-288},
  institution = {Dept. of Computer Science, Dartmouth College},
  copyright = {Joel T. Thomas},
  note = {Senior Honors Thesis.},
  URL = {https://digitalcommons.dartmouth.edu/senior_theses/175/},
  keywords = {multiprocessor file system, parallel I/O, pario-bib},
  abstract = {The Panda Array I/O library, created at the University of
  Illinois, Urbana-Champaign, was built especially to address the needs of
  high-performance scientific applications. I/O has been one of the most
  frustrating bottlenecks to high performance for quite some time, and the
  Panda project is an attempt to ameliorate this problem while still providing
  the user with a simple, high-level interface. The Galley File System, with
  its hierarchical structure of files and strided requests, is another attempt
  at addressing the performance problem. My project was to redesign the Panda
  Array library for use on the Galley file system. This project involved
  porting Panda's three main functions: a checkpoint function for writing a
  large array periodically for 'safekeeping,' a restart function that would
  allow a checkpointed file to be read back in, and finally a timestep function
  that would allow the user to write a group of large arrays several times in a
  sequence. Panda supports several different distributions in both the
  compute-node memories and I/O-node disks. \par We have found that the Galley
  File System provides a good environment on which to build high-performance
  libraries, and that the mesh of Panda and Galley was a successful
  combination.},
  comment = {See seamons:thesis.}
}