@Article{oldfield:seismic,
  author = {Ron A. Oldfield and David E. Womble and Curtis C. Ober},
  title = {Efficient Parallel {I/O} in Seismic Imaging},
  journal = {The International Journal of High Performance Computing
  Applications},
  year = {1998},
  month = {Fall},
  volume = {12},
  number = {3},
  pages = {333--344},
  publisher = {Sage Science Press},
  copyright = {Sage Publications},
  URL = {ftp://ftp.cs.dartmouth.edu/pub/raoldfi/salvo/salvoIO.ps.gz},
  keywords = {parallel I/O application, pario-bib},
  abstract = {While high performance computers tend to be measured by their
  processor and communications speeds, the bottleneck for many large-scale
  applications is the I/O performance rather than the computational or
  communication performance. One such application is the processing of 3D
  seismic data. Seismic data sets, consisting of recorded pressure waves, can
  be very large, sometimes more than a terabyte in size. Even if the
  computations can be performed in-core, the time required to read the initial
  seismic data and velocity model and write images is substantial. This paper
  will discuss our approach in handling the massive I/O requirements of seismic
  processing and show the performance of our imaging code (Salvo) on the Intel
  Paragon.},
  comment = {In a Special Issue on I/O in Parallel Applications, volume 12,
  numbers 3 and 4.}
}