cuSolver has syevjBatched, which seems to fit your purpose. But I have never used it.
Lanczos is not competitive for such small matrices. Jose > El 6 jul 2021, a las 21:56, Jed Brown <[email protected]> escribió: > > Have you tried just calling LAPACK directly? (You could try dsyevx to see if > there's something to gain by computing less than all the eigenvalues.) I'm > not aware of a batched interface at this time, but that's what you'd want for > performance. > > Jacob Faibussowitsch <[email protected]> writes: > >> Hello PETSc/SLEPc users, >> >> Similar to a recent question I am looking for an algorithm to compute the >> smallest eigenvalue and eigenvector for a bunch of matrices however I have a >> few extra “restrictions”. All matrices have the following properties: >> >> - All matrices are the same size >> - All matrices are small (perhaps no larger than 12x12) >> - All matrices are SPD >> - I only need the smallest eigenpair >> >> So far my best bet seems to be Lanczos but I’m wondering if there is some >> wunder method I’ve overlooked. >> >> Best regards, >> >> Jacob Faibussowitsch >> (Jacob Fai - booss - oh - vitch)
