Thanks for quick update. In the new tarball, I have already removed the junk files, as pointed out by Satish.
Sherry On Wed, Jul 29, 2015 at 8:36 AM, Hong <[email protected]> wrote: > Sherry, > With your bugfix, superlu_dist-4.1 works now: > > petsc/src/ksp/ksp/examples/tutorials (master) > $ mpiexec -n 4 ./ex10 -f0 Amat_binary.m -rhs 0 -pc_type lu > -pc_factor_mat_solver_package superlu_dist -mat_superlu_dist_parsymbfact > Number of iterations = 1 > Residual norm 2.11605e-11 > > Once you address Satish's request, we'll update petsc interface to this > version of superlu_dist. > > Anthony: > Please download the latest superlu_dist-v4.1, > then configure petsc with > '--download-superlu_dist=superlu_dist_4.1.tar.gz' > > Hong > > On Tue, Jul 28, 2015 at 11:11 AM, Satish Balay <[email protected]> wrote: > >> Sherry, >> >> One minor issue with the tarball. I see the following new files in the >> v4.1 tarball >> [when comparing it with v4.0]. Some of these files are perhaps junk files >> - and can >> be removed from the tarball? >> >> EXAMPLE/dscatter.c.bak >> EXAMPLE/g10.cua >> EXAMPLE/g4.cua >> EXAMPLE/g4.postorder.eps >> EXAMPLE/g4.rua >> EXAMPLE/g4_postorder.jpg >> EXAMPLE/hostname >> EXAMPLE/pdgssvx.c >> EXAMPLE/pdgstrf2.c >> EXAMPLE/pwd >> EXAMPLE/pzgstrf2.c >> EXAMPLE/pzgstrf_v3.3.c >> EXAMPLE/pzutil.c >> EXAMPLE/test.bat >> EXAMPLE/test.cpu.bat >> EXAMPLE/test.err >> EXAMPLE/test.err.1 >> EXAMPLE/zlook_ahead_update.c >> FORTRAN/make.out >> FORTRAN/zcreate_dist_matrix.c >> MAKE_INC/make.xc30 >> SRC/int_t >> SRC/lnbrow >> SRC/make.out >> SRC/rnbrow >> SRC/temp >> SRC/temp1 >> >> >> Thanks, >> Satish >> >> >> On Tue, 28 Jul 2015, Xiaoye S. Li wrote: >> >> > I am checking v4.1 now. I'll let you know when I fixed the problem. >> > >> > Sherry >> > >> > On Tue, Jul 28, 2015 at 8:27 AM, Hong <[email protected]> wrote: >> > >> > > Sherry, >> > > I tested with superlu_dist v4.1. The extra printings are gone, but >> hang >> > > remains. >> > > It hangs at >> > > >> > > #5 0x00007fde5af1c818 in PMPI_Wait (request=0xb6e4e0, >> > > status=0x7fff9cd83d60) >> > > at src/mpi/pt2pt/wait.c:168 >> > > #6 0x00007fde602dd635 in pzgstrf (options=0x9202f0, m=4900, n=4900, >> > > anorm=13.738475134194639, LUstruct=0x9203c8, grid=0x9202c8, >> > > stat=0x7fff9cd84880, info=0x7fff9cd848bc) at pzgstrf.c:1308 >> > > >> > > if (recv_req[0] != MPI_REQUEST_NULL) { >> > > --> MPI_Wait (&recv_req[0], &status); >> > > >> > > We will update petsc interface to superlu_dist v4.1. >> > > >> > > Hong >> > > >> > > >> > > On Mon, Jul 27, 2015 at 11:33 PM, Xiaoye S. Li <[email protected]> wrote: >> > > >> > >> Hong, >> > >> Thanks for trying out. >> > >> The extra printings are not properly guarded by the print level. I >> will >> > >> fix that. I will look into the hang problem soon. >> > >> >> > >> Sherry >> > >> >> > >> >> > >> On Mon, Jul 27, 2015 at 7:50 PM, Hong <[email protected]> wrote: >> > >> >> > >>> Sherry, >> > >>> >> > >>> I can repeat hang using petsc/src/ksp/ksp/examples/tutorials/ex10.c: >> > >>> mpiexec -n 4 ./ex10 -f0 /homes/hzhang/tmp/Amat_binary.m -rhs 0 >> -pc_type >> > >>> lu -pc_factor_mat_solver_package superlu_dist >> -mat_superlu_dist_parsymbfact >> > >>> ... >> > >>> .. Starting with 1 OpenMP threads >> > >>> [0] .. BIG U size 1342464 >> > >>> [0] .. BIG V size 131072 >> > >>> Max row size is 1311 >> > >>> Using buffer_size of 5000000 >> > >>> Threads per process 1 >> > >>> ... >> > >>> >> > >>> using a debugger (with petsc option '-start_in_debugger'), I find >> that >> > >>> hang occurs at >> > >>> #0 0x00007f117d870998 in __GI___poll (fds=0x20da750, nfds=4, >> > >>> timeout=<optimized out>, timeout@entry=-1) >> > >>> at ../sysdeps/unix/sysv/linux/poll.c:83 >> > >>> #1 0x00007f117de9f7de in MPIDU_Sock_wait (sock_set=0x20da550, >> > >>> millisecond_timeout=millisecond_timeout@entry=-1, >> > >>> eventp=eventp@entry=0x7fff654930b0) >> > >>> at src/mpid/common/sock/poll/sock_wait.i:123 >> > >>> #2 0x00007f117de898b8 in MPIDI_CH3i_Progress_wait ( >> > >>> progress_state=0x7fff65493120) >> > >>> at src/mpid/ch3/channels/sock/src/ch3_progress.c:218 >> > >>> #3 MPIDI_CH3I_Progress (blocking=blocking@entry=1, >> > >>> state=state@entry=0x7fff65493120) >> > >>> at src/mpid/ch3/channels/sock/src/ch3_progress.c:921 >> > >>> #4 0x00007f117de1a559 in MPIR_Wait_impl (request=request@entry >> > >>> =0x262df90, >> > >>> status=status@entry=0x7fff65493390) at src/mpi/pt2pt/wait.c:67 >> > >>> #5 0x00007f117de1a818 in PMPI_Wait (request=0x262df90, >> > >>> status=0x7fff65493390) >> > >>> at src/mpi/pt2pt/wait.c:168 >> > >>> #6 0x00007f11831da557 in pzgstrf (options=0x23dfda0, m=4900, >> n=4900, >> > >>> anorm=13.738475134194639, LUstruct=0x23dfe78, grid=0x23dfd78, >> > >>> stat=0x7fff65493ea0, info=0x7fff65493edc) at pzgstrf.c:1308 >> > >>> >> > >>> #7 0x00007f11831bf3bd in pzgssvx (options=0x23dfda0, A=0x23dfe30, >> > >>> ScalePermstruct=0x23dfe50, B=0x0, ldb=1225, nrhs=0, >> grid=0x23dfd78, >> > >>> LUstruct=0x23dfe78, SOLVEstruct=0x23dfe98, berr=0x0, >> > >>> stat=0x7fff65493ea0, >> > >>> ---Type <return> to continue, or q <return> to quit--- >> > >>> info=0x7fff65493edc) at pzgssvx.c:1063 >> > >>> >> > >>> #8 0x00007f11825c2340 in MatLUFactorNumeric_SuperLU_DIST >> (F=0x23a0110, >> > >>> A=0x21bb7e0, info=0x2355068) >> > >>> at >> > >>> >> /sandbox/hzhang/petsc/src/mat/impls/aij/mpi/superlu_dist/superlu_dist.c:411 >> > >>> #9 0x00007f1181c6c567 in MatLUFactorNumeric (fact=0x23a0110, >> > >>> mat=0x21bb7e0, >> > >>> info=0x2355068) at >> > >>> /sandbox/hzhang/petsc/src/mat/interface/matrix.c:2946 >> > >>> #10 0x00007f1182a56489 in PCSetUp_LU (pc=0x2353a10) >> > >>> at /sandbox/hzhang/petsc/src/ksp/pc/impls/factor/lu/lu.c:152 >> > >>> #11 0x00007f1182b16f24 in PCSetUp (pc=0x2353a10) >> > >>> at /sandbox/hzhang/petsc/src/ksp/pc/interface/precon.c:983 >> > >>> #12 0x00007f1182be61b5 in KSPSetUp (ksp=0x232c2a0) >> > >>> at /sandbox/hzhang/petsc/src/ksp/ksp/interface/itfunc.c:332 >> > >>> #13 0x0000000000405a31 in main (argc=11, args=0x7fff65499578) >> > >>> at >> /sandbox/hzhang/petsc/src/ksp/ksp/examples/tutorials/ex10.c:312 >> > >>> >> > >>> You may take a look at it. Sequential symbolic factorization works >> fine. >> > >>> >> > >>> Why superlu_dist (v4.0) in complex precision displays >> > >>> >> > >>> .. Starting with 1 OpenMP threads >> > >>> [0] .. BIG U size 1342464 >> > >>> [0] .. BIG V size 131072 >> > >>> Max row size is 1311 >> > >>> Using buffer_size of 5000000 >> > >>> Threads per process 1 >> > >>> ... >> > >>> >> > >>> I realize that I use superlu_dist v4.0. Would v4.1 works? I'll give >> it a >> > >>> try tomorrow. >> > >>> >> > >>> Hong >> > >>> >> > >>> On Mon, Jul 27, 2015 at 1:25 PM, Anthony Paul Haas < >> > >>> [email protected]> wrote: >> > >>> >> > >>>> Hi Hong, >> > >>>> >> > >>>> No that is not the correct matrix. Note that I forgot to mention >> that >> > >>>> it is a complex matrix. I tried loading the matrix I sent you this >> morning >> > >>>> with: >> > >>>> >> > >>>> !...Load a Matrix in Binary Format >> > >>>> call >> > >>>> >> PetscViewerBinaryOpen(PETSC_COMM_WORLD,"Amat_binary.m",FILE_MODE_READ,viewer,ierr) >> > >>>> call MatCreate(PETSC_COMM_WORLD,DLOAD,ierr) >> > >>>> call MatSetType(DLOAD,MATAIJ,ierr) >> > >>>> call MatLoad(DLOAD,viewer,ierr) >> > >>>> call PetscViewerDestroy(viewer,ierr) >> > >>>> >> > >>>> call MatView(DLOAD,PETSC_VIEWER_STDOUT_WORLD,ierr) >> > >>>> >> > >>>> The first 37 rows should look like this: >> > >>>> >> > >>>> Mat Object: 2 MPI processes >> > >>>> type: mpiaij >> > >>>> row 0: (0, 1) >> > >>>> row 1: (1, 1) >> > >>>> row 2: (2, 1) >> > >>>> row 3: (3, 1) >> > >>>> row 4: (4, 1) >> > >>>> row 5: (5, 1) >> > >>>> row 6: (6, 1) >> > >>>> row 7: (7, 1) >> > >>>> row 8: (8, 1) >> > >>>> row 9: (9, 1) >> > >>>> row 10: (10, 1) >> > >>>> row 11: (11, 1) >> > >>>> row 12: (12, 1) >> > >>>> row 13: (13, 1) >> > >>>> row 14: (14, 1) >> > >>>> row 15: (15, 1) >> > >>>> row 16: (16, 1) >> > >>>> row 17: (17, 1) >> > >>>> row 18: (18, 1) >> > >>>> row 19: (19, 1) >> > >>>> row 20: (20, 1) >> > >>>> row 21: (21, 1) >> > >>>> row 22: (22, 1) >> > >>>> row 23: (23, 1) >> > >>>> row 24: (24, 1) >> > >>>> row 25: (25, 1) >> > >>>> row 26: (26, 1) >> > >>>> row 27: (27, 1) >> > >>>> row 28: (28, 1) >> > >>>> row 29: (29, 1) >> > >>>> row 30: (30, 1) >> > >>>> row 31: (31, 1) >> > >>>> row 32: (32, 1) >> > >>>> row 33: (33, 1) >> > >>>> row 34: (34, 1) >> > >>>> row 35: (35, 1) >> > >>>> row 36: (1, -41.2444) (35, -41.2444) (36, 118.049 - 0.999271 i) >> (37, >> > >>>> -21.447) (38, 5.18873) (39, -2.34856) (40, 1.3607) (41, >> -0.898206) >> > >>>> (42, 0.642715) (43, -0.48593) (44, 0.382471) (45, -0.310476) >> (46, >> > >>>> 0.258302) (47, -0.219268) (48, 0.189304) (49, -0.165815) (50, >> > >>>> 0.147076) (51, -0.131907) (52, 0.119478) (53, -0.109189) (54, >> 0.1006) >> > >>>> (55, -0.0933795) (56, 0.0872779) (57, -0.0821019) (58, >> 0.0777011) (59, >> > >>>> -0.0739575) (60, 0.0707775) (61, -0.0680868) (62, 0.0658258) >> (63, >> > >>>> -0.0639473) (64, 0.0624137) (65, -0.0611954) (66, 0.0602698) >> (67, >> > >>>> -0.0596202) (68, 0.0592349) (69, -0.0295536) (71, -21.447) >> (106, >> > >>>> 5.18873) (141, -2.34856) (176, 1.3607) (211, -0.898206) (246, >> > >>>> 0.642715) (281, -0.48593) (316, 0.382471) (351, -0.310476) >> (386, >> > >>>> 0.258302) (421, -0.219268) (456, 0.189304) (491, -0.165815) >> (526, >> > >>>> 0.147076) (561, -0.131907) (596, 0.119478) (631, -0.109189) >> (666, >> > >>>> 0.1006) (701, -0.0933795) (736, 0.0872779) (771, -0.0821019) >> (806, >> > >>>> 0.0777011) (841, -0.0739575) (876, 0.0707775) (911, >> -0.0680868) (946, >> > >>>> 0.0658258) (981, -0.0639473) (1016, 0.0624137) (1051, >> -0.0611954) >> > >>>> (1086, 0.0602698) (1121, -0.0596202) (1156, 0.0592349) (1191, >> > >>>> -0.0295536) (1261, 0) (3676, 117.211) (3711, -58.4801) (3746, >> > >>>> -78.3633) (3781, 29.4911) (3816, -15.8073) (3851, 9.94324) >> (3886, >> > >>>> -6.87205) (3921, 5.05774) (3956, -3.89521) (3991, 3.10522) >> (4026, >> > >>>> -2.54388) (4061, 2.13082) (4096, -1.8182) (4131, 1.57606) >> (4166, >> > >>>> -1.38491) (4201, 1.23155) (4236, -1.10685) (4271, 1.00428) >> (4306, >> > >>>> -0.919116) (4341, 0.847829) (4376, -0.787776) (4411, 0.736933) >> (4446, >> > >>>> -0.693735) (4481, 0.656958) (4516, -0.625638) (4551, 0.599007) >> (4586, >> > >>>> -0.576454) (4621, 0.557491) (4656, -0.541726) (4691, 0.528849) >> (4726, >> > >>>> -0.518617) (4761, 0.51084) (4796, -0.50538) (4831, 0.502142) >> (4866, >> > >>>> -0.250534) >> > >>>> >> > >>>> >> > >>>> Thanks, >> > >>>> >> > >>>> Anthony >> > >>>> >> > >>>> >> > >>>> >> > >>>> >> > >>>> >> > >>>> On Fri, Jul 24, 2015 at 7:56 PM, Hong <[email protected]> wrote: >> > >>>> >> > >>>>> Anthony: >> > >>>>> I test your Amat_binary.m >> > >>>>> using petsc/src/ksp/ksp/examples/tutorials/ex10.c. >> > >>>>> Your matrix has many zero rows: >> > >>>>> ./ex10 -f0 ~/tmp/Amat_binary.m -rhs 0 -mat_view |more >> > >>>>> Mat Object: 1 MPI processes >> > >>>>> type: seqaij >> > >>>>> row 0: (0, 1) >> > >>>>> row 1: (1, 0) >> > >>>>> row 2: (2, 1) >> > >>>>> row 3: (3, 0) >> > >>>>> row 4: (4, 1) >> > >>>>> row 5: (5, 0) >> > >>>>> row 6: (6, 1) >> > >>>>> row 7: (7, 0) >> > >>>>> row 8: (8, 1) >> > >>>>> row 9: (9, 0) >> > >>>>> ... >> > >>>>> row 36: (1, 1) (35, 0) (36, 1) (37, 0) (38, 1) (39, 0) (40, >> 1) >> > >>>>> (41, 0) (42, 1) (43, 0) (44, 1) (45, >> > >>>>> 0) (46, 1) (47, 0) (48, 1) (49, 0) (50, 1) (51, 0) (52, 1) >> > >>>>> (53, 0) (54, 1) (55, 0) (56, 1) (57, 0) >> > >>>>> (58, 1) (59, 0) (60, 1) ... >> > >>>>> >> > >>>>> Do you send us correct matrix? >> > >>>>> >> > >>>>>> >> > >>>>>> I ran my code through valgrind and gdb as suggested by Barry. I >> am >> > >>>>>> now coming back to some problem I have had while running with >> parallel >> > >>>>>> symbolic factorization. I am attaching a test matrix (petsc >> binary format) >> > >>>>>> that I LU decompose and then use to solve a linear system (see >> code below). >> > >>>>>> I can run on 2 processors with parsymbfact or with 4 processors >> without >> > >>>>>> parsymbfact. However, if I run on 4 procs with parsymbfact, the >> code is >> > >>>>>> just hanging. Below is the simplified test case that I have used >> to test. >> > >>>>>> The matrix A and B are built somewhere else in my program. The >> matrix I am >> > >>>>>> attaching is A-sigma*B (see below). >> > >>>>>> >> > >>>>>> One thing is that I don't know for sparse matrices what is the >> > >>>>>> optimum number of processors to use for a LU decomposition? Does >> it depend >> > >>>>>> on the total number of nonzero? Do you have an easy way to >> compute it? >> > >>>>>> >> > >>>>> >> > >>>>> You have to experiment your matrix on a target machine to find >> out. >> > >>>>> >> > >>>>> Hong >> > >>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> Subroutine HowBigLUCanBe(rank) >> > >>>>>> >> > >>>>>> IMPLICIT NONE >> > >>>>>> >> > >>>>>> integer(i4b),intent(in) :: rank >> > >>>>>> integer(i4b) :: i,ct >> > >>>>>> real(dp) :: begin,endd >> > >>>>>> complex(dpc) :: sigma >> > >>>>>> >> > >>>>>> PetscErrorCode ierr >> > >>>>>> >> > >>>>>> >> > >>>>>> if (rank==0) call cpu_time(begin) >> > >>>>>> >> > >>>>>> if (rank==0) then >> > >>>>>> write(*,*) >> > >>>>>> write(*,*)'Testing How Big LU Can Be...' >> > >>>>>> write(*,*)'============================' >> > >>>>>> write(*,*) >> > >>>>>> endif >> > >>>>>> >> > >>>>>> sigma = (1.0d0,0.0d0) >> > >>>>>> call MatAXPY(A,-sigma,B,DIFFERENT_NONZERO_PATTERN,ierr) ! >> on >> > >>>>>> exit A = A-sigma*B >> > >>>>>> >> > >>>>>> !.....Write Matrix to ASCII and Binary Format >> > >>>>>> !call >> > >>>>>> PetscViewerASCIIOpen(PETSC_COMM_WORLD,"Amat.m",viewer,ierr) >> > >>>>>> !call MatView(DXX,viewer,ierr) >> > >>>>>> !call PetscViewerDestroy(viewer,ierr) >> > >>>>>> >> > >>>>>> call >> > >>>>>> >> PetscViewerBinaryOpen(PETSC_COMM_WORLD,"Amat_binary.m",FILE_MODE_WRITE,viewer,ierr) >> > >>>>>> call MatView(A,viewer,ierr) >> > >>>>>> call PetscViewerDestroy(viewer,ierr) >> > >>>>>> >> > >>>>>> !.....Create Linear Solver Context >> > >>>>>> call KSPCreate(PETSC_COMM_WORLD,ksp,ierr) >> > >>>>>> >> > >>>>>> !.....Set operators. Here the matrix that defines the linear >> system >> > >>>>>> also serves as the preconditioning matrix. >> > >>>>>> !call >> KSPSetOperators(ksp,A,A,DIFFERENT_NONZERO_PATTERN,ierr) >> > >>>>>> !aha commented and replaced by next line >> > >>>>>> call KSPSetOperators(ksp,A,A,ierr) ! remember: here A = >> > >>>>>> A-sigma*B >> > >>>>>> >> > >>>>>> !.....Set Relative and Absolute Tolerances and Uses Default for >> > >>>>>> Divergence Tol >> > >>>>>> tol = 1.e-10 >> > >>>>>> call >> > >>>>>> >> KSPSetTolerances(ksp,tol,tol,PETSC_DEFAULT_REAL,PETSC_DEFAULT_INTEGER,ierr) >> > >>>>>> >> > >>>>>> !.....Set the Direct (LU) Solver >> > >>>>>> call KSPSetType(ksp,KSPPREONLY,ierr) >> > >>>>>> call KSPGetPC(ksp,pc,ierr) >> > >>>>>> call PCSetType(pc,PCLU,ierr) >> > >>>>>> call >> PCFactorSetMatSolverPackage(pc,MATSOLVERSUPERLU_DIST,ierr) >> > >>>>>> ! MATSOLVERSUPERLU_DIST MATSOLVERMUMPS >> > >>>>>> >> > >>>>>> !.....Create Right-Hand-Side Vector >> > >>>>>> call MatCreateVecs(A,frhs,PETSC_NULL_OBJECT,ierr) >> > >>>>>> call MatCreateVecs(A,sol,PETSC_NULL_OBJECT,ierr) >> > >>>>>> >> > >>>>>> allocate(xwork1(IendA-IstartA)) >> > >>>>>> allocate(loc(IendA-IstartA)) >> > >>>>>> >> > >>>>>> ct=0 >> > >>>>>> do i=IstartA,IendA-1 >> > >>>>>> ct=ct+1 >> > >>>>>> loc(ct)=i >> > >>>>>> xwork1(ct)=(1.0d0,0.0d0) >> > >>>>>> enddo >> > >>>>>> >> > >>>>>> call >> > >>>>>> VecSetValues(frhs,IendA-IstartA,loc,xwork1,INSERT_VALUES,ierr) >> > >>>>>> call VecZeroEntries(sol,ierr) >> > >>>>>> >> > >>>>>> deallocate(xwork1,loc) >> > >>>>>> >> > >>>>>> !.....Assemble Vectors >> > >>>>>> call VecAssemblyBegin(frhs,ierr) >> > >>>>>> call VecAssemblyEnd(frhs,ierr) >> > >>>>>> >> > >>>>>> !.....Solve the Linear System >> > >>>>>> call KSPSolve(ksp,frhs,sol,ierr) >> > >>>>>> >> > >>>>>> !call VecView(sol,PETSC_VIEWER_STDOUT_WORLD,ierr) >> > >>>>>> >> > >>>>>> if (rank==0) then >> > >>>>>> call cpu_time(endd) >> > >>>>>> write(*,*) >> > >>>>>> print '("Total time for HowBigLUCanBe = ",f21.3," >> > >>>>>> seconds.")',endd-begin >> > >>>>>> endif >> > >>>>>> >> > >>>>>> call SlepcFinalize(ierr) >> > >>>>>> >> > >>>>>> STOP >> > >>>>>> >> > >>>>>> >> > >>>>>> end Subroutine HowBigLUCanBe >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> On 07/08/2015 11:23 AM, Xiaoye S. Li wrote: >> > >>>>>> >> > >>>>>> Indeed, the parallel symbolic factorization routine needs power >> of >> > >>>>>> 2 processes, however, you can use however many processes you >> need; >> > >>>>>> internally, we redistribute matrix to nearest power of 2 >> processes, do >> > >>>>>> symbolic, then redistribute back to all the processes to do >> factorization, >> > >>>>>> triangular solve etc. So, there is no restriction from the >> users >> > >>>>>> viewpoint. >> > >>>>>> >> > >>>>>> It's difficult to tell what the problem is. Do you think you >> can >> > >>>>>> print your matrix, then, I can do some debugging by running >> superlu_dist >> > >>>>>> standalone? >> > >>>>>> >> > >>>>>> Sherry >> > >>>>>> >> > >>>>>> >> > >>>>>> On Wed, Jul 8, 2015 at 10:34 AM, Anthony Paul Haas < >> > >>>>>> [email protected]> wrote: >> > >>>>>> >> > >>>>>>> Hi, >> > >>>>>>> >> > >>>>>>> I have used the switch -mat_superlu_dist_parsymbfact in my pbs >> > >>>>>>> script. However, although my program worked fine with >> sequential symbolic >> > >>>>>>> factorization, I get one of the following 2 behaviors when I >> run with >> > >>>>>>> parallel symbolic factorization (depending on the number of >> processors that >> > >>>>>>> I use): >> > >>>>>>> >> > >>>>>>> 1) the program just hangs (it seems stuck in some subroutine >> ==> >> > >>>>>>> see test.out-hangs) >> > >>>>>>> 2) I get a floating point exception ==> see >> > >>>>>>> test.out-floating-point-exception >> > >>>>>>> >> > >>>>>>> Note that as suggested in the Superlu manual, I use a power of >> 2 >> > >>>>>>> number of procs. Are there any tunable parameters for the >> parallel symbolic >> > >>>>>>> factorization? Note that when I build my sparse matrix, most >> elements I add >> > >>>>>>> are nonzero of course but to simplify the programming, I also >> add a few >> > >>>>>>> zero elements in the sparse matrix. I was thinking that maybe >> if the >> > >>>>>>> parallel symbolic factorization proceed by block, there could >> be some >> > >>>>>>> blocks where the pivot would be zero, hence creating the FPE?? >> > >>>>>>> >> > >>>>>>> Thanks, >> > >>>>>>> >> > >>>>>>> Anthony >> > >>>>>>> >> > >>>>>>> >> > >>>>>>> >> > >>>>>>> On Wed, Jul 8, 2015 at 6:46 AM, Xiaoye S. Li <[email protected]> >> wrote: >> > >>>>>>> >> > >>>>>>>> Did you find out how to change option to use parallel symbolic >> > >>>>>>>> factorization? Perhaps PETSc team can help. >> > >>>>>>>> >> > >>>>>>>> Sherry >> > >>>>>>>> >> > >>>>>>>> >> > >>>>>>>> On Tue, Jul 7, 2015 at 3:58 PM, Xiaoye S. Li <[email protected]> >> wrote: >> > >>>>>>>> >> > >>>>>>>>> Is there an inquiry function that tells you all the available >> > >>>>>>>>> options? >> > >>>>>>>>> >> > >>>>>>>>> Sherry >> > >>>>>>>>> >> > >>>>>>>>> On Tue, Jul 7, 2015 at 3:25 PM, Anthony Paul Haas < >> > >>>>>>>>> [email protected]> wrote: >> > >>>>>>>>> >> > >>>>>>>>>> Hi Sherry, >> > >>>>>>>>>> >> > >>>>>>>>>> Thanks for your message. I have used superlu_dist default >> > >>>>>>>>>> options. I did not realize that I was doing serial symbolic >> factorization. >> > >>>>>>>>>> That is probably the cause of my problem. >> > >>>>>>>>>> Each node on Garnet has 60GB usable memory and I can run >> with >> > >>>>>>>>>> 1,2,4,8,16 or 32 core per node. >> > >>>>>>>>>> >> > >>>>>>>>>> So I should use: >> > >>>>>>>>>> >> > >>>>>>>>>> -mat_superlu_dist_r 20 >> > >>>>>>>>>> -mat_superlu_dist_c 32 >> > >>>>>>>>>> >> > >>>>>>>>>> How do you specify the parallel symbolic factorization >> option? >> > >>>>>>>>>> is it -mat_superlu_dist_matinput 1 >> > >>>>>>>>>> >> > >>>>>>>>>> Thanks, >> > >>>>>>>>>> >> > >>>>>>>>>> Anthony >> > >>>>>>>>>> >> > >>>>>>>>>> >> > >>>>>>>>>> On Tue, Jul 7, 2015 at 3:08 PM, Xiaoye S. Li <[email protected]> >> > >>>>>>>>>> wrote: >> > >>>>>>>>>> >> > >>>>>>>>>>> For superlu_dist failure, this occurs during symbolic >> > >>>>>>>>>>> factorization. Since you are using serial symbolic >> factorization, it >> > >>>>>>>>>>> requires the entire graph of A to be available in the >> memory of one MPI >> > >>>>>>>>>>> task. How much memory do you have for each MPI task? >> > >>>>>>>>>>> >> > >>>>>>>>>>> It won't help even if you use more processes. You should >> try >> > >>>>>>>>>>> to use parallel symbolic factorization option. >> > >>>>>>>>>>> >> > >>>>>>>>>>> Another point. You set up process grid as: >> > >>>>>>>>>>> Process grid nprow 32 x npcol 20 >> > >>>>>>>>>>> For better performance, you show swap the grid dimension. >> That >> > >>>>>>>>>>> is, it's better to use 20 x 32, never gives nprow larger >> than npcol. >> > >>>>>>>>>>> >> > >>>>>>>>>>> >> > >>>>>>>>>>> Sherry >> > >>>>>>>>>>> >> > >>>>>>>>>>> >> > >>>>>>>>>>> On Tue, Jul 7, 2015 at 1:27 PM, Barry Smith < >> [email protected]> >> > >>>>>>>>>>> wrote: >> > >>>>>>>>>>> >> > >>>>>>>>>>>> >> > >>>>>>>>>>>> I would suggest running a sequence of problems, 101 by >> 101 >> > >>>>>>>>>>>> 111 by 111 etc and get the memory usage in each case (when >> you run out of >> > >>>>>>>>>>>> memory you can get NO useful information out about memory >> needs). You can >> > >>>>>>>>>>>> then plot memory usage as a function of problem size to >> get a handle on how >> > >>>>>>>>>>>> much memory it is using. You can also run on more and >> more processes >> > >>>>>>>>>>>> (which have a total of more memory) to see how large a >> problem you may be >> > >>>>>>>>>>>> able to reach. >> > >>>>>>>>>>>> >> > >>>>>>>>>>>> MUMPS also has an "out of core" version (which we have >> never >> > >>>>>>>>>>>> used) that could in theory anyways let you get to large >> problems if you >> > >>>>>>>>>>>> have lots of disk space, but you are on your own figuring >> out how to use it. >> > >>>>>>>>>>>> >> > >>>>>>>>>>>> Barry >> > >>>>>>>>>>>> >> > >>>>>>>>>>>> > On Jul 7, 2015, at 2:37 PM, Anthony Paul Haas < >> > >>>>>>>>>>>> [email protected]> wrote: >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Hi Jose, >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > In my code, I use once PETSc to solve a linear system to >> get >> > >>>>>>>>>>>> the baseflow (without using SLEPc) and then I use SLEPc to >> do the stability >> > >>>>>>>>>>>> analysis of that baseflow. This is why, there are some >> SLEPc options that >> > >>>>>>>>>>>> are not used in test.out-superlu_dist-151x151 (when I am >> solving for the >> > >>>>>>>>>>>> baseflow with PETSc only). I have attached a 101x101 case >> for which I get >> > >>>>>>>>>>>> the eigenvalues. That case works fine. However If i >> increase to 151x151, I >> > >>>>>>>>>>>> get the error that you can see in >> test.out-superlu_dist-151x151 (similar >> > >>>>>>>>>>>> error with mumps: see test.out-mumps-151x151 line 2918 ). >> If you look a the >> > >>>>>>>>>>>> very end of the files test.out-superlu_dist-151x151 and >> > >>>>>>>>>>>> test.out-mumps-151x151, you will see that the last info >> message printed is: >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > On Processor (after EPSSetFromOptions) 0 memory: >> > >>>>>>>>>>>> 0.65073152000E+08 =====> (see line 807 of >> module_petsc.F90) >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > This means that the memory error probably occurs in the >> call >> > >>>>>>>>>>>> to EPSSolve (see module_petsc.F90 line 810). I would like >> to evaluate how >> > >>>>>>>>>>>> much memory is required by the most memory intensive >> operation within >> > >>>>>>>>>>>> EPSSolve. Since I am solving a generalized EVP, I would >> imagine that it >> > >>>>>>>>>>>> would be the LU decomposition. But is there an accurate >> way of doing it? >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Before starting with iterative solvers, I would like to >> > >>>>>>>>>>>> exploit as much as I can direct solvers. I tried GMRES >> with default >> > >>>>>>>>>>>> preconditioner at some point but I had convergence >> problem. What >> > >>>>>>>>>>>> solver/preconditioner would you recommend for a >> generalized non-Hermitian >> > >>>>>>>>>>>> (EPS_GNHEP) EVP? >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Thanks, >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Anthony >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > On Tue, Jul 7, 2015 at 12:17 AM, Jose E. Roman < >> > >>>>>>>>>>>> [email protected]> wrote: >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > El 07/07/2015, a las 02:33, Anthony Haas escribió: >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > > Hi, >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > I am computing eigenvalues using PETSc/SLEPc and >> > >>>>>>>>>>>> superlu_dist for the LU decomposition (my problem is a >> generalized >> > >>>>>>>>>>>> eigenvalue problem). The code runs fine for a grid with >> 101x101 but when I >> > >>>>>>>>>>>> increase to 151x151, I get the following error: >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > Can't expand MemType 1: jcol 16104 (and then [NID >> 00037] >> > >>>>>>>>>>>> 2015-07-06 19:19:17 Apid 31025976: OOM killer terminated >> this process.) >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > It seems to be a memory problem. I monitor the memory >> usage >> > >>>>>>>>>>>> as far as I can and it seems that memory usage is pretty >> low. The most >> > >>>>>>>>>>>> memory intensive part of the program is probably the LU >> decomposition in >> > >>>>>>>>>>>> the context of the generalized EVP. Is there a way to >> evaluate how much >> > >>>>>>>>>>>> memory will be required for that step? I am currently >> running the debug >> > >>>>>>>>>>>> version of the code which I would assume would use more >> memory? >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > I have attached the output of the job. Note that the >> > >>>>>>>>>>>> program uses twice PETSc: 1) to solve a linear system for >> which no problem >> > >>>>>>>>>>>> occurs, and, 2) to solve the Generalized EVP with SLEPc, >> where I get the >> > >>>>>>>>>>>> error. >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > Thanks >> > >>>>>>>>>>>> > > >> > >>>>>>>>>>>> > > Anthony >> > >>>>>>>>>>>> > > <test.out-superlu_dist-151x151> >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > In the output you are attaching there are no SLEPc >> objects in >> > >>>>>>>>>>>> the report and SLEPc options are not used. It seems that >> SLEPc calls are >> > >>>>>>>>>>>> skipped? >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Do you get the same error with MUMPS? Have you tried to >> solve >> > >>>>>>>>>>>> linear systems with a preconditioned iterative solver? >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > Jose >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> > >> > >>>>>>>>>>>> >> <module_petsc.F90><test.out-mumps-151x151><test.out_superlu_dist-101x101><test.out-superlu_dist-151x151> >> > >>>>>>>>>>>> >> > >>>>>>>>>>>> >> > >>>>>>>>>>> >> > >>>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>> >> > >>>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>> >> > >>>> >> > >>> >> > >> >> > > >> > >> > >
