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> > >>>>>>>>>>>> > >>>>>>>>>>>> > >>>>>>>>>>> > >>>>>>>>>> > >>>>>>>>> > >>>>>>>> > >>>>>>> > >>>>>> > >>>>>> > >>>>> > >>>> > >>> > >> > > >
