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Parallel solution of large sparse matrix equations and parallel power flow

机译:大型稀疏矩阵方程和并行潮流的并行解

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摘要

A very efficient parallel LU factorization and substitution algorithm for solving large sparse network equations on shared memory multi-processor parallel computers is presented. By rearranging the order of the computations, better parallelism is obtained out of the traditionally sequential method. Performance results on an actual parallel computer are presented and discussed. Parallel gains for the power flow solution using Newton's and fast decoupled methods are presented to demonstrate it's effectiveness. Better speedup gains are obtained for larger systems and speedup of over 13 for Newton's power flow on a 20 processor shared memory computer has been obtained.
机译:提出了一种在共享内存多处理器并行计算机上求解大型稀疏网络方程的高效并行LU分解和替换算法。通过重新安排计算顺序,可以从传统的顺序方法中获得更好的并行性。提出并讨论了在实际并行计算机上的性能结果。提出了使用牛顿法和快速解耦法的潮流解决方案的并行增益,以证明其有效性。对于较大的系统,可以获得更好的加速增益,并且对于20处理器共享内存计算机上的牛顿功率流,可以获得超过13的加速。

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