@InProceedings{chen:panda,
  author = {Y. Chen and M. Winslett and K. E. Seamons and S. Kuo and Y. Cho and
  M. Subramaniam},
  title = {Scalable Message Passing in {Panda}},
  booktitle = {Proceedings of the Fourth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1996},
  month = {May},
  pages = {109--121},
  publisher = {ACM Press},
  address = {Philadelphia},
  keywords = {parallel I/O, parallel file system, pario-bib},
  abstract = {To provide high performance for applications with a wide variety
  of i/o requirements and to support many different parallel platforms, the
  design of a parallel i/o system must provide for efficient utilization of
  available bandwidth both for disk traffic and for message passing. In this
  paper we discuss the message-passing scalability of the server-directed i/o
  architecture of Panda, a library for synchronized i/o of multidimensional
  arrays on parallel platforms. We show how to improve i/o performance in
  situations where message-passing is a bottleneck, by combining the
  server-directed i/o strategy for highly efficient use of available disk
  bandwidth with new mechanisms to minimize internal communication and
  computation overhead in Panda. We present experimental results that show that
  with these improvements, Panda will provide high i/o performance for a wider
  range of applications, such as applications running with slow interconnects,
  applications performing i/o operations on large numbers of arrays, or
  applications that require drastic data rearrangements as data are moved
  between memory and disk (e.g., array transposition). We also argue that in
  the future, the improved approach to message-passing will allow Panda to
  support applications that are not closely synchronized or that run in
  heterogeneous environments.},
  comment = {see seamons:panda. This paper goes further with some communication
  improvements.}
}