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Towards Highly Parallel and Compute-Bound Computation of Eigenvectors of Matrices in Schur Form

機(jī)譯:邁向Schur形式的矩陣特征向量的高度并行和計(jì)算界計(jì)算

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In this paper we discuss the problem of computing eigenvectors for matrices in Schur form using parallel computing. We develop a new parallel algorithm and report on the performance of our MPI based implementation. We have also implemented a new parallel algorithm for scaling during the backsubstitution phase. We have increased the arithmetic intensity by interleaving the compution of several eigenvectors and by merging the backward substitution and the back-transformation of the eigenvector computation.

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