Reduction of an N x N nonsymmetric matrix to Hessenberg form which takes o(N-3) flops and o(N-3/B) i/os is a major performance bottleneck in the computing of its eigenvalues. Usually toimprove the performance, this H...
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Reduction of an N x N nonsymmetric matrix to Hessenberg form which takes o(N-3) flops and o(N-3/B) i/os is a major performance bottleneck in the computing of its eigenvalues. Usually toimprove the performance, this Hessenberg reduction is computed in two steps: the first one reduces the matrix to a banded Hessenberg form, and the second one further reduces it to Hessenberg form by incorporating more matrix-matrixoperations in the computation. We analyse the two steps of the Hessenberg reduction problem on the external memory model (of Aggarwal and Vitter) for their i/o complexities. We propose and analyse a tile based algorithm for the first step of the reduction and show that it takes o(N-3/B min{t, root M}) i/os. For the reduction of a banded Hessenberg matrixof bandwidth t to Hessenberg form, we propose an algorithm, which uses tight packing of bulges, and requires only o(t(2)N(2)/B + N-3/tB) i/os. Combining the results of the two steps of the reduction, we show that the Hessenberg reduction can be performed in o(N-3/root MB) i/os, when N is sufficiently large. To the best of our knowledge, the proposed algorithm is the first i/ooptimal algorithm for Hessenberg reduction;the worst case i/o complexity matches the known lower bound of the problem.
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