Hi, this is my first post here, so bare with me.(adsbygoogle = window.adsbygoogle || []).push({});

So I need to compute the eigenvectors of a large matrix (1000x1000) to (10000x10000x) or so. However, I already have the eigenvalues and diagonal/superdiagonal form of the matrix. The equation (A-lambda*I)*v = 0, where A is the matrix, lambda is the given eigenvalue, and v is the eigenvector to solve for. However, with such large matrices there would be an absurd amount of equations to solve for, correct? A) Are there any BLAS algorithms to solve for this(seems unlikely) and B) Would it be easier to ignore the eigenvalues that I can get from a different program and just start at the beginning with something like a jacobi transformation? I know I can use programs like MATLAB to calculate these eigenvectors, but my goal is to implement a parallel version to increase the calculation time of the eigenvectors.

If any clarification is needed, please let me know. I will check this thread/forum at least a couple times during the work day (8am-5pm EST)

Thanks,

Joe

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# Eigenvector for Large Matrix

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