The benefits include increased capacity for memory intensive problems, and improved performance for processor-intensive problems. The MPI library is used to enable the parallel version to be easily ported to massively parallel, SMP, and distributed computers. This implementation will reduce the changes required in the rest of the program by parallelization. Specific implementation details such as the hiding of communication latency behind local computation will also be discussed. Objectives Reduce run-times for large, complex simulations from weeks to days.
Distribute memory demands across machines, allowing larger simulations than possible otherwise.
Distribute computation to NOW's, MPP's, and SMP machines. Easy portation to different platforms. Release the code to the general public, with source code. Parallelization strategy Decompose physical model into computational regions. Pass particles and fields across the regions.