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首页> 外文期刊>IEICE transactions on information and systems >Repeatable Hybrid Parallel Implementation of an Inverse Matrix Computation Using the SMW Formula for a Time-Series Simulation
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Repeatable Hybrid Parallel Implementation of an Inverse Matrix Computation Using the SMW Formula for a Time-Series Simulation

机译:使用SMW公式进行时间序列仿真的逆矩阵计算的可重复混合并行实现

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In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.
机译:本文提出了利用SMW公式可逆混合计算的可逆并行并行实现方法。作者先前已经提出了用于逆矩阵计算的混合并行算法。一次计算逆矩阵的速度相当快,但是由于在每次迭代的开始都需要重新放置大矩阵,因此很难将这种算法重复应用于连续计算。为了消除大输入矩阵的重定位,该大输入矩阵是前一时间步的逆矩阵计算的输出,因此对计算算法进行了重新设计,以使输入矩阵的所需部分与输入矩阵的输出部分相同。每个节点中先前计算的矩阵。这使得可以在时序仿真中重复有效地应用SMW公式来计算逆矩阵。

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