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Paper Details

  title = "{A} {C}omparison of {P}arallel {I}mplementations of {F}lux {C}orrected {T}ransport {C}odes",
  author= "Jong, Jing-ming and Stiles, G. S.",
  editor= "Wexler, J.",
  pages = "113--128",
  booktitle= "{OUG}-11: {D}eveloping {T}ransputer {A}pplications",
  isbn= "90 5199 020 0",
  year= "1989",
  month= "sep",
  abstract= "We present the results of comparing implementations of the
     Flux Corrected Transport (FCT) method on transputers and
     several other parallel and sequential machines. FCT is a
     finite difference scheme used to solve fluid dynamics
     problem which may involve steep gradients or shocks; it has
     proven useful for both one- and two-dimensional problems in
     plasma physics, atmospheric sciences, and detonation
     studies. The method vectorizes very well and hence runs
     quickly on supercomputers. Since the calculations at each
     point involve only a small number of neighbors, the method
     can also be efficiently implemented on multi-processor
     systems. We have run one- and two-dimensional problems on
     Transputers and several other systems, including a VAX 8650,
     a SUN 4/280, a four-processor Ardent Titan, an
     eight-processor Alliant FX/8, and a four-processor Silicon
     Graphics 240GTX. We shall also compare our results to those
     obtained by Gustafson (1988) on the NCube/ten.If, in the 1-d
     problem, we consider the speed of a single T800 to be 1.0,
     the SUN 4/280 ranks at 3.8, the VAX 8650 at 4.0, 8 TSOOs at
     7.9, the Silicon Graphics 240GTX at 27.0, the FX/8 at 56.9,
     and the Titan at 64.4. On the 1-d problem, again taking one
     T800 to have a speed of 1.0, the SUN comes in at 3.6, 16
     NCube nodes at 4.0, the 8650 at 4.3, 8 TSOOs at 7.7, the
     Titan at 65.3, and the FX/8 at 101.4. The transputer ranks
     highest if we calculate the cost-effectiveness of the
     various systems by dividing the relative speed by the
     approximate cost. If we assume the 8 TSOOs have a
     cost-effectiveness of 1.0 on the 1-d problem, the Titan is
     second at 0.52, followed by the 240GTX at 0.17, the FX/8 at
     0.094, the SUN at 0.081, and the VAX at 0.021."

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