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