Abstract
An approach for parallelizing a three-dimensional multiblock Euler flow solver of high-speed-train computational fluid dynamics is reported in this paper. Parallelization is performed using a "parallel in k" strategy to nearly balance the load of each processor for a given fixed number of mesh blocks. Communication among processors is made via message passing subroutine calls in the model of message passing interface (MPI) or via direct remote-memory access in the model of bulk synchronous parallelization (BSP). The parallelized code is practiced on the shared-memory machine, SGI powerchallenge XL (R8000), with 10 processors to compute the three-dimensional unsteady Euler flow field of a high-speed train moving in a tunnel with single vertical shaft. The performance of parallelization is compared between the two models and the results show that the BSP model is comparable to the MPI model, while the former is easy to read, write, and debug.
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