On Nov 14, 2007 10:37 AM, Tim Stitt <timothy.stitt at ichec.ie> wrote: > Can I just ask a question about MatLUFactorSymbolic() in this context? > What sizes should the 'row' and 'col' index sets be? Should they span > all global rows/columns in A?
Yes, the matrix is permuted as a whole. Matt > Matthew Knepley wrote: > > You appear to be setting every value in the sparse matrix. We do not > > throw out 0 values (since sometimes they are necessary for structural > > reasons). Thus you are allocating a ton of times. You need to remove > > the 0 values before calling MatSetValues (and their associated > > column entires as well). > > > > Matt > > > > On Nov 14, 2007 8:13 AM, Tim Stitt <timothy.stitt at ichec.ie> wrote: > > > >> Dear PETSc Users/Developers, > >> > >> I have the following sequential Fortran PETSc code that I have been > >> developing (on and off) based on the kind advice given by members of > >> this list, with respect to solving an inverse sparse matrix problem. > >> Essentially, the code reads in a square double complex matrix from > >> external file of size (order x order) and then proceeds to do a > >> MatMatSolve(), where A is the sparse matrix to invert, B is a dense > >> identity matrix and X is the resultant dense matrix....hope that makes > >> sense. > >> > >> My main problem is that the code stalls on the MatSetValues() for the > >> sparse matrix A. With a trivial test matrix of (224 x 224) the program > >> terminates successfully (by successfully I mean all instructions > >> execute...I am not interested in the validity of X right now). > >> Unfortunately, when I move up to a (2352 x 2352) matrix the > >> MatSetValues() routine for matrix A is still in progress after 15 > >> minutes on one processor of our AMD Opteron IBM Cluster. I know that > >> people will be screaming "preallocation"...but I have tried to take this > >> into account by running a loop over the rows in A and counting the > >> non-zero values explicitly prior to creation. I then pass this vector > >> into the creation routine for the nnz argument. For the large (2352 x > >> 2352) problem that seems to be taking forever to set...at most there are > >> only 200 elements per row that are non-zero according to the counts. > >> > >> Can anyone explain why the MatSetValues() routine is taking such a long > >> time. Maybe this expected for this specific task...although it seems > >> very long? > >> > >> I did notice that on the trivial (224 x 224) run that I was still > >> getting mallocs (approx 2000) for the A assembly when I used the -info > >> command line parameter. I thought that it should be 0 if my > >> preallocation counts were exact? Does this hint that I am doing > >> something wrong. I have checked the code but don't see any obvious > >> problems in the logic...not that means anything. > >> > >> I would be grateful if someone could advise on this matter. Also, if you > >> have a few seconds to spare I would be grateful if some experts could > >> scan the remaining logic of the code (not in fine detail) to make sure > >> that I am doing all that I need to do to get this calculation > >> working...assuming I can resolve the MatSetValues() problem. > >> > >> Once again many thanks in advance, > >> > >> Tim. > >> > >> ! Initialise the PETSc MPI Harness > >> call PetscInitialize(PETSC_NULL_CHARACTER,error);CHKERRQ(error) > >> > >> call MPI_COMM_SIZE(PETSC_COMM_SELF,processes,error);CHKERRQ(error) > >> call MPI_COMM_RANK(PETSC_COMM_SELF,ID,error);CHKERRQ(error) > >> > >> ! Read in Matrix > >> open(321,file='Hamiltonian.bin',form='unformatted') > >> read(321) order > >> if (ID==0) then > >> print * > >> print *,processes," Processing Elements being used" > >> print * > >> print *,"Matrix has order ",order," rows by ",order," columns" > >> print * > >> end if > >> > >> allocate(matrix(order,order)) > >> read(321) matrix > >> close(321) > >> > >> ! Allocate array for nnz > >> allocate(numberZero(order)) > >> > >> ! Count number of non-zero elements in each matrix row > >> do row=1,order > >> count=0 > >> do column=1,order > >> if (matrix(row,column).ne.(0,0)) count=count+1 > >> end do > >> numberZero(row)=count > >> end do > >> > >> ! Declare a PETSc Matrices > >> > >> call > >> MatCreateSeqAIJ(PETSC_COMM_SELF,order,order,PETSC_NULL_INTEGER,numberZero,A,error);CHKERRQ(error) > >> call > >> MatCreateSeqAIJ(PETSC_COMM_SELF,order,order,0,PETSC_NULL_INTEGER,factorMat,error);CHKERRQ(error) > >> call > >> MatCreateSeqDense(PETSC_COMM_SELF,order,order,PETSC_NULL_SCALAR,X,error);CHKERRQ(error) > >> call > >> MatCreateSeqDense(PETSC_COMM_SELF,order,order,PETSC_NULL_SCALAR,B,error);CHKERRQ(error) > >> > >> ! Set up zero-based array indexing for use in MatSetValues > >> allocate(columnIndices(order)) > >> > >> do column=1,order > >> columnIndices(column)=column-1 > >> end do > >> > >> ! Need to transpose values array as row-major arrays are used. > >> call > >> MatSetValues(A,order,columnIndices,order,columnIndices,transpose(matrix),INSERT_VALUES,error);CHKERRQ(error) > >> > >> ! Assemble Matrix A > >> call MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> call MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> > >> deallocate(matrix) > >> > >> ! Create Index Sets for Factorisation > >> call > >> ISCreateGeneral(PETSC_COMM_SELF,order,columnIndices,indexSet,error);CHKERRQ(error) > >> call MatFactorInfoInitialize(info,error);CHKERRQ(error) > >> call ISSetPermutation(indexSet,error);CHKERRQ(error) > >> call > >> MatLUFactorSymbolic(A,indexSet,indexSet,info,factorMat,error);CHKERRQ(error) > >> call MatLUFactorNumeric(A,info,factorMat,error);CHKERRQ(error) > >> > >> ! A no-longer needed > >> call MatDestroy(A,error);CHKERRQ(error) > >> > >> one=(1,0) > >> > >> ! Set Diagonal elements in Identity Matrix B > >> do row=0,order-1 > >> call MatSetValue(B,row,row,one,INSERT_VALUES,error);CHKERRQ(error) > >> end do > >> > >> ! Assemble B > >> call MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> call MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> > >> ! Assemble X > >> call MatAssemblyBegin(X,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> call MatAssemblyEnd(X,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error) > >> > >> ! Solve AX=B > >> call MatMatSolve(factorMat,B,X,error);CHKERRQ(error) > >> > >> ! Deallocate Storage > >> deallocate(columnIndices) > >> > >> call MatDestroy(factorMat,error);CHKERRQ(error) > >> call MatDestroy(B,error);CHKERRQ(error) > >> call MatDestroy(X,error);CHKERRQ(error) > >> > >> call PetscFinalize(error) > >> > >> -- > >> Dr. Timothy Stitt <timothy_dot_stitt_at_ichec.ie> > >> HPC Application Consultant - ICHEC (www.ichec.ie) > >> > >> Dublin Institute for Advanced Studies > >> 5 Merrion Square - Dublin 2 - Ireland > >> > >> +353-1-6621333 (tel) / +353-1-6621477 (fax) > >> > >> > >> > > > > > > > > > > > -- > Dr. Timothy Stitt <timothy_dot_stitt_at_ichec.ie> > HPC Application Consultant - ICHEC (www.ichec.ie) > > Dublin Institute for Advanced Studies > 5 Merrion Square - Dublin 2 - Ireland > > +353-1-6621333 (tel) / +353-1-6621477 (fax) > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener
