Thank you for suggestion. Is it interfaced to SLEPC?
On 08/29/2019 04:14 PM, Jose E. Roman wrote: > I am not an expert in contour integral eigensolvers. I think difficulties > come with corners, so ellipses are the best choice. I don't think ring > regions are relevant here. > > Have you considered using ScaLAPACK. Some time ago we were able to address > problems of size up to 400k https://doi.org/10.1017/jfm.2016.208 > > Jose > > >> El 29 ago 2019, a las 21:55, Povolotskyi, Mykhailo <[email protected]> >> escribió: >> >> Thank you, Jose, >> >> what about rings? Are they better than rectangles? >> >> Michael. >> >> >> On 08/29/2019 03:44 PM, Jose E. Roman wrote: >>> The CISS solver is supposed to estimate the number of eigenvalues contained >>> in the contour. My impression is that the estimation is less accurate in >>> case of rectangular contours, compared to elliptic ones. But of course, >>> with ellipses it is not possible to fully cover the complex plane unless >>> there is some overlap. >>> >>> Jose >>> >>> >>>> El 29 ago 2019, a las 20:56, Povolotskyi, Mykhailo via petsc-users >>>> <[email protected]> escribió: >>>> >>>> Hello everyone, >>>> >>>> this is a question about SLEPc. >>>> >>>> The problem that I need to solve is as follows. >>>> >>>> I have a matrix and I need a full spectrum of it (both eigenvalues and >>>> eigenvectors). >>>> >>>> The regular way is to use Lapack, but it is slow. I decided to try the >>>> following: >>>> >>>> a) compute the bounds of the spectrum using Krylov Schur approach. >>>> >>>> b) divide the complex eigenvalue plane into rectangular areas, then >>>> apply CISS to each area in parallel. >>>> >>>> However, I found that the solver is missing some eigenvalues, even if my >>>> rectangles cover the whole spectral area. >>>> >>>> My question: can this approach work in principle? If yes, how one can >>>> set-up CISS solver to not loose the eigenvalues? >>>> >>>> Thank you, >>>> >>>> Michael. >>>>
