There are lots of functions to compute eigenvalue, for example ?sygvx can select eigenvalues by specifying either or range of indices for the desired eigenvalues. For more details please refer to the MKL developer reference: https://software.intel.com/content/www/us/en/develop/documentation/mkl-developer-reference-fortran/top/lapack-routines/lapack-least-squares-and-eigenvalue-problem-routines/lapack-least-squares-and-eigenvalue-problem-driver-routines/generalized-symmetric-definite-eigenvalue-problems-lapack-driver-routines/sygvx.html
Yeah, I know there are many functions for Fortran 95 to compute the eigenvalue of real matrix. But in my test, the syevd is the most fast function than other functions, such as the sygvx, which can select eigenvalues. So I want to konw which function is the most efficient to compute the eigenvalues?
Have you checked this function below in the developer reference for computing the largest/smallest eigenvalues and corresponding eigenvectors of a standard eigenvalue problem:
and set the first input parameter "which" as:
which = 'L'indicates the largest eigenvalues.
which = 'S'indicates the smallest eigenvalues.
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