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Conclusions

We have extensively analyzed the performance of parallel solvers for power systems applications on the Thinking Machines CM-5. We have shown that the node-tearing-based partitioning algorithm can yield matrices in block-diagonal-bordered form with balanced workloads for power systems networks with homogeneous voltage distribution lines; and we have shown that the performance of our parallel block-diagonal-bordered sparse iterative linear solvers can yield good speedups for Gauss-Seidel methods for those networks with balanced workloads. Not unexpectedly, low-latency communications paradigms greatly improve the performance of the algorithm, because of both improved communications performance and significantly simpler implementations.



David P. Koester
Sun Oct 22 17:27:14 EDT 1995