[petsc-users] Questions on convergence (SLEPC)

[Steve Ndengue]

Dear all,

I have few questions on achieving convergence with SLEPC.
I am doing some comparison on how SLEPC performs compare to a LAPACK 
installation on my system (an 8 processors icore7 with 3.4 GHz running 
Ubuntu).

1/ It appears that a calculation requesting the LAPACK eigensolver runs 
faster using my libraries than when done with SLEPC selecting the 
'lapack' method. I guess most of the time is spent when assembling the 
matrix? However if the time seems reasonable for a matrix of size less 
than 2000*2000, for one with 4000*4000 and above, the computation time 
seems more than ten times slower with SLEPC and the 'lapack' method!!!

2/ I was however expecting that running an iterative calculation such as 
'krylovschur', 'lanczos' or 'arnoldi' the time would be shorter but that 
is not the case. Inserting the Shift-and-Invert spectral transform, i 
could converge faster for small matrices but it takes more time using 
these iteratives methods than using the Lapack library on my system, 
when the size allows; even when requesting only few eigenstates (less 
than 50).

regarding the 2 previous comments I would like to know if there are some 
rules on how to ensure a fast convergence of a diagonalisation with SLEPC?

3/ About the diagonalisation on many processors, after we assign values 
to the matrix, does SLEPC automatically distribute the calculation among 
the requested processes or shall we need to insert commands on the code 
to enforce it?

Sincerely,


-- 
Steve

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