I have run your larger matrix on my laptop with "default" optimization (so
--with-debugging=0) this is what I get
------------------------------------------------------------------------------------------------------------------------
Event Count Time (sec) Flop
--- Global --- --- Stage --- Total
Max Ratio Max Ratio Max Ratio Mess Avg len Reduct
%T %F %M %L %R %T %F %M %L %R Mflop/s
------------------------------------------------------------------------------------------------------------------------
AIJ
MatMult 5 1.0 7.7636e-02 1.0 1.42e+08 1.0 0.0e+00 0.0e+00
0.0e+00 12 16 0 0 0 16 16 0 0 0 1830
MatSolve 5 1.0 7.8164e-02 1.0 1.42e+08 1.0 0.0e+00 0.0e+00
0.0e+00 12 16 0 0 0 16 16 0 0 0 1818
MatLUFactorNum 1 1.0 2.3056e-01 1.0 5.95e+08 1.0 0.0e+00 0.0e+00
0.0e+00 35 67 0 0 0 46 67 0 0 0 2580
MatILUFactorSym 1 1.0 8.3201e-02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 13 0 0 0 0 17 0 0 0 0 0
BAIJ
MatMult 5 1.0 5.3482e-02 1.0 1.42e+08 1.0 0.0e+00 0.0e+00
0.0e+00 6 6 0 0 0 9 6 0 0 0 2657
MatSolve 5 1.0 6.2669e-02 1.0 1.39e+08 1.0 0.0e+00 0.0e+00
0.0e+00 7 6 0 0 0 11 6 0 0 0 2224
MatLUFactorNum 1 1.0 3.7688e-01 1.0 2.12e+09 1.0 0.0e+00 0.0e+00
0.0e+00 40 88 0 0 0 66 88 0 0 0 5635
MatILUFactorSym 1 1.0 4.4828e-02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 5 0 0 0 0 8 0 0 0 0 0
So BAIJ symbolic is faster (which definitely should be). BAIJ MatMult and
MatSolve are also faster, the numerical BAIJ factorization is slower.
Providing custom code for block size 11 should definitely improve the
performance of all three of these.
I note that the number of iterations 5 is much less than in the case you
emailed originally? Is this really the matrix of interest?
Barry
> On Mar 7, 2017, at 3:26 PM, Kong, Fande <[email protected]> wrote:
>
>
>
> On Tue, Mar 7, 2017 at 2:07 PM, Barry Smith <[email protected]> wrote:
>
> The matrix is too small. Please post ONE big matrix
>
> I am using "-ksp_view_pmat binary" to save the matrix. How can I save the
> latest one only for a time-dependent problem?
>
>
> Fande,
>
>
>
> > On Mar 7, 2017, at 2:26 PM, Kong, Fande <[email protected]> wrote:
> >
> > Uploaded to google drive, and sent you links in another email. Not sure if
> > it works or not.
> >
> > Fande,
> >
> > On Tue, Mar 7, 2017 at 12:29 PM, Barry Smith <[email protected]> wrote:
> >
> > It is too big for email you can post it somewhere so we can download it.
> >
> >
> > > On Mar 7, 2017, at 12:01 PM, Kong, Fande <[email protected]> wrote:
> > >
> > >
> > >
> > > On Tue, Mar 7, 2017 at 10:23 AM, Hong <[email protected]> wrote:
> > > I checked
> > > MatILUFactorSymbolic_SeqBAIJ() and MatILUFactorSymbolic_SeqAIJ(),
> > > they are virtually same. Why the version for BAIJ is so much slower?
> > > I'll investigate it.
> > >
> > > Fande,
> > > How large is your matrix? Is it possible to send us your matrix so I can
> > > test it?
> > >
> > > Thanks, Hong,
> > >
> > > It is a 3020875x3020875 matrix, and it is large. I can make a small one
> > > if you like, but not sure it will reproduce this issue or not.
> > >
> > > Fande,
> > >
> > >
> > >
> > > Hong
> > >
> > >
> > > On Mon, Mar 6, 2017 at 9:08 PM, Barry Smith <[email protected]> wrote:
> > >
> > > Thanks. Even the symbolic is slower for BAIJ. I don't like that, it
> > > definitely should not be since it is (at least should be) doing a
> > > symbolic factorization on a symbolic matrix 1/11th the size!
> > >
> > > Keep us informed.
> > >
> > >
> > >
> > > > On Mar 6, 2017, at 5:44 PM, Kong, Fande <[email protected]> wrote:
> > > >
> > > > 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> wrote:
> > > > >>
> > > > >>
> > > > >>
> > > > >> On Mon, Mar 6, 2017 at 3:27 PM, Patrick Sanan
> > > > >> <[email protected]> wrote:
> > > > >> On Mon, Mar 6, 2017 at 1:48 PM, Kong, Fande <[email protected]>
> > > > >> 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,
> > > > >>
> > > > >
> > > >
> > > >
> > >
> > >
> > >
> >
> >
>
>
