SPOOLES - a parallel direct solver for sparse systems
Usage:
-mat_type seqaijspooles -ksp_type preonly -pc_type lu
sequential seqaij matrix type
-mat_type mpiaijspooles -ksp_type preonly -pc_type lu
parallel sequential mpiaij matrix type
-mat_type seqsbaijspooles -ksp_type preonly -pc_type cholesky
sequential symmetric seqsbaij matrix type
-mat_type mpisbaijspooles -ksp_type preonly -pc_type cholesky
parallel symmetric mpisbaij matrix type
Options:
-mat_spooles_tau <tau>
upper bound on the magnitude of the largest element in L or U
-mat_spooles_seed <seed>
random number seed used for ordering
-mat_spooles_msglvl <msglvl>
message output level
-mat_spooles_ordering <BestOfNDandMS,MMD,MS,ND>
ordering used
-mat_spooles_maxdomainsize <n>
maximum subgraph size used by Spooles orderings
-mat_spooles_maxzeros <n>
maximum number of zeros inside a supernode
-mat_spooles_maxsize <n>
maximum size of a supernode
-mat_spooles_FrontMtxInfo <true,fase>
print Spooles information about the computed factorization
-mat_spooles_symmetryflag <0,1,2>
0: SPOOLES_SYMMETRIC, 1: SPOOLES_HERMITIAN, 2: SPOOLES_NONSYMMETRIC
-mat_spooles_patchAndGoFlag <0,1,2>
0: no patch, 1: use PatchAndGo strategy 1, 2: use PatchAndGo strategy 2
-mat_spooles_toosmall <dt>
drop tolerance for PatchAndGo strategy 1
-mat_spooles_storeids <bool integer>
if nonzero, stores row and col numbers where patches were applied in an IV object
-mat_spooles_fudge <delta>
fudge factor for rescaling diagonals with PatchAndGo strategy 2
-mat_spooles_storevalues <bool integer>
if nonzero and PatchAndGo strategy 2 is used, store change in diagonal value in a DV object