Abstract
The block Fourier decomposition method recently proposed by the first author is a special method for decoupling any block tridiagonal matrix of the form K = block-tridiag [B, A, B], where A and B are square submatrices, into diagonal blocks. Unlike the traditional fast Poisson solver, block cyclic reductions, or the FACR algorithm, this approach does not require A and B be symmetric or commute. Presented in this paper is a parallel solver using this block decomposition method to solve linear systems whose coefficient matrices are of the form of K. We describe the computational procedure and implementation for parallel executions on distributed workstations. The performance from our numerical experiments is reported to demonstrate the usefulness of this approach.
This work was supported in part by the Army Research Laboratory under Grant No. DAAL01-98-2-D065.
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Chen, HC., Tzeng, SY. (2003). A Parallel Solver Using Block Fourier Decompositions. In: Guo, M., Yang, L.T. (eds) Parallel and Distributed Processing and Applications. ISPA 2003. Lecture Notes in Computer Science, vol 2745. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-37619-4_34
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DOI: https://doi.org/10.1007/3-540-37619-4_34
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