Thanks, Barry, Log info:
AIJ: MatSolve 850 1.0 8.6543e+00 4.2 3.04e+09 1.8 0.0e+00 0.0e+00 0.0e+00 0 41 0 0 0 0 41 0 0 0 49594 MatLUFactorNum 25 1.0 1.7622e+00 2.0 2.04e+09 2.1 0.0e+00 0.0e+00 0.0e+00 0 26 0 0 0 0 26 0 0 0 153394 MatILUFactorSym 13 1.0 2.8002e-01 2.9 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 BAIJ: MatSolve 826 1.0 1.3016e+01 1.7 1.42e+10 1.8 0.0e+00 0.0e+00 0.0e+00 1 29 0 0 0 1 29 0 0 0 154617 MatLUFactorNum 25 1.0 1.5503e+01 2.0 3.55e+10 2.1 0.0e+00 0.0e+00 0.0e+00 1 67 0 0 0 1 67 0 0 0 303190 MatILUFactorSym 13 1.0 5.7561e-01 1.8 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 It looks like both MatSolve and MatLUFactorNum are slower. I will try your suggestions. Fande On Mon, Mar 6, 2017 at 4:14 PM, Barry Smith <bsm...@mcs.anl.gov> wrote: > > Note also that if the 11 by 11 blocks are actually sparse (and you don't > store all the zeros in the blocks in the AIJ format) then then AIJ > non-block factorization involves less floating point operations and less > memory access so can be faster than the BAIJ format, depending on "how > sparse" the blocks are. If you actually "fill in" the 11 by 11 blocks with > AIJ (with zeros maybe in certain locations) then the above is not true. > > > > On Mar 6, 2017, at 5:10 PM, Barry Smith <bsm...@mcs.anl.gov> wrote: > > > > > > This is because for block size 11 it is using calls to LAPACK/BLAS for > the block operations instead of custom routines for that block size. > > > > Here is what you need to do. For a good sized case run both with > -log_view and check the time spent in > > MatLUFactorNumeric, MatLUFactorSymbolic and in MatSolve for AIJ and > BAIJ. If they have a different number of function calls then divide by the > function call count to determine the time per function call. > > > > This will tell you which routine needs to be optimized first either > MatLUFactorNumeric or MatSolve. My guess is MatSolve. > > > > So edit src/mat/impls/baij/seq/baijsolvnat.c and copy the function > MatSolve_SeqBAIJ_15_NaturalOrdering_ver1() to a new function > MatSolve_SeqBAIJ_11_NaturalOrdering_ver1. Edit the new function for the > block size of 11. > > > > Now edit MatLUFactorNumeric_SeqBAIJ_N() so that if block size is 11 it > uses the new routine something like. > > > > if (both_identity) { > > if (b->bs == 11) > > C->ops->solve = MatSolve_SeqBAIJ_11_NaturalOrdering_ver1; > > } else { > > C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering; > > } > > > > Rerun and look at the new -log_view. Send all three -log_view to use > at this point. If this optimization helps and now > > MatLUFactorNumeric is the time sink you can do the process to > MatLUFactorNumeric_SeqBAIJ_15_NaturalOrdering() to make an 11 size block > custom version. > > > > Barry > > > >> On Mar 6, 2017, at 4:32 PM, Kong, Fande <fande.k...@inl.gov> wrote: > >> > >> > >> > >> On Mon, Mar 6, 2017 at 3:27 PM, Patrick Sanan <patrick.sa...@gmail.com> > wrote: > >> On Mon, Mar 6, 2017 at 1:48 PM, Kong, Fande <fande.k...@inl.gov> wrote: > >>> Hi All, > >>> > >>> I am solving a nonlinear system whose Jacobian matrix has a block > structure. > >>> More precisely, there is a mesh, and for each vertex there are 11 > variables > >>> associated with it. I am using BAIJ. > >>> > >>> I thought block ILU(k) should be more efficient than the point-wise > ILU(k). > >>> After some numerical experiments, I found that the block ILU(K) is much > >>> slower than the point-wise version. > >> Do you mean that it takes more iterations to converge, or that the > >> time per iteration is greater, or both? > >> > >> The number of iterations is very similar, but the timer per iteration > is greater. > >> > >> > >>> > >>> Any thoughts? > >>> > >>> Fande, > >> > > > >