1 2 static char help[] = "Tests ILU and ICC factorization with and without matrix ordering on seqsbaij format. Modified from ex30.c\n\ 3 Input parameters are:\n\ 4 -lf <level> : level of fill for ILU (default is 0)\n\ 5 -lu : use full LU or Cholesky factorization\n\ 6 -m <value>,-n <value> : grid dimensions\n\ 7 Note that most users should employ the KSP interface to the\n\ 8 linear solvers instead of using the factorization routines\n\ 9 directly.\n\n"; 10 11 #include <petscmat.h> 12 13 int main(int argc,char **args) 14 { 15 Mat C,sC,sA; 16 PetscInt i,j,m = 5,n = 5,Ii,J,lf = 0; 17 PetscBool CHOLESKY=PETSC_FALSE,TRIANGULAR=PETSC_FALSE,flg; 18 PetscScalar v; 19 IS row,col; 20 MatFactorInfo info; 21 Vec x,y,b,ytmp; 22 PetscReal norm2,tol = 100*PETSC_MACHINE_EPSILON; 23 PetscRandom rdm; 24 PetscMPIInt size; 25 26 PetscCall(PetscInitialize(&argc,&args,(char*)0,help)); 27 PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD,&size)); 28 PetscCheck(size == 1,PETSC_COMM_WORLD,PETSC_ERR_WRONG_MPI_SIZE,"This is a uniprocessor example only!"); 29 PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL)); 30 PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL)); 31 PetscCall(PetscOptionsGetInt(NULL,NULL,"-lf",&lf,NULL)); 32 33 PetscCall(MatCreate(PETSC_COMM_SELF,&C)); 34 PetscCall(MatSetSizes(C,m*n,m*n,m*n,m*n)); 35 PetscCall(MatSetFromOptions(C)); 36 PetscCall(MatSetUp(C)); 37 38 /* Create matrix C in seqaij format and sC in seqsbaij. (This is five-point stencil with some extra elements) */ 39 for (i=0; i<m; i++) { 40 for (j=0; j<n; j++) { 41 v = -1.0; Ii = j + n*i; 42 J = Ii - n; if (J>=0) PetscCall(MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES)); 43 J = Ii + n; if (J<m*n) PetscCall(MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES)); 44 J = Ii - 1; if (J>=0) PetscCall(MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES)); 45 J = Ii + 1; if (J<m*n) PetscCall(MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES)); 46 v = 4.0; PetscCall(MatSetValues(C,1,&Ii,1,&Ii,&v,INSERT_VALUES)); 47 } 48 } 49 PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY)); 50 PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY)); 51 52 PetscCall(MatIsSymmetric(C,0.0,&flg)); 53 PetscCheck(flg,PETSC_COMM_SELF,PETSC_ERR_SUP,"C is non-symmetric"); 54 PetscCall(MatConvert(C,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&sC)); 55 56 /* Create vectors for error checking */ 57 PetscCall(MatCreateVecs(C,&x,&b)); 58 PetscCall(VecDuplicate(x,&y)); 59 PetscCall(VecDuplicate(x,&ytmp)); 60 PetscCall(PetscRandomCreate(PETSC_COMM_SELF,&rdm)); 61 PetscCall(PetscRandomSetFromOptions(rdm)); 62 PetscCall(VecSetRandom(x,rdm)); 63 PetscCall(MatMult(C,x,b)); 64 65 PetscCall(MatGetOrdering(C,MATORDERINGNATURAL,&row,&col)); 66 67 /* Compute CHOLESKY or ICC factor sA */ 68 PetscCall(MatFactorInfoInitialize(&info)); 69 70 info.fill = 1.0; 71 info.diagonal_fill = 0; 72 info.zeropivot = 0.0; 73 74 PetscCall(PetscOptionsHasName(NULL,NULL,"-cholesky",&CHOLESKY)); 75 if (CHOLESKY) { 76 PetscCall(PetscPrintf(PETSC_COMM_SELF,"Test CHOLESKY...\n")); 77 PetscCall(MatGetFactor(sC,MATSOLVERPETSC,MAT_FACTOR_CHOLESKY,&sA)); 78 PetscCall(MatCholeskyFactorSymbolic(sA,sC,row,&info)); 79 } else { 80 PetscCall(PetscPrintf(PETSC_COMM_SELF,"Test ICC...\n")); 81 info.levels = lf; 82 83 PetscCall(MatGetFactor(sC,MATSOLVERPETSC,MAT_FACTOR_ICC,&sA)); 84 PetscCall(MatICCFactorSymbolic(sA,sC,row,&info)); 85 } 86 PetscCall(MatCholeskyFactorNumeric(sA,sC,&info)); 87 88 /* test MatForwardSolve() and MatBackwardSolve() with matrix reordering on aij matrix C */ 89 if (CHOLESKY) { 90 PetscCall(PetscOptionsHasName(NULL,NULL,"-triangular_solve",&TRIANGULAR)); 91 if (TRIANGULAR) { 92 PetscCall(PetscPrintf(PETSC_COMM_SELF,"Test MatForwardSolve...\n")); 93 PetscCall(MatForwardSolve(sA,b,ytmp)); 94 PetscCall(PetscPrintf(PETSC_COMM_SELF,"Test MatBackwardSolve...\n")); 95 PetscCall(MatBackwardSolve(sA,ytmp,y)); 96 PetscCall(VecAXPY(y,-1.0,x)); 97 PetscCall(VecNorm(y,NORM_2,&norm2)); 98 if (norm2 > tol) { 99 PetscCall(PetscPrintf(PETSC_COMM_SELF,"MatForwardSolve and BackwardSolve: Norm of error=%g\n",(double)norm2)); 100 } 101 } 102 } 103 104 PetscCall(MatSolve(sA,b,y)); 105 PetscCall(MatDestroy(&sC)); 106 PetscCall(MatDestroy(&sA)); 107 PetscCall(VecAXPY(y,-1.0,x)); 108 PetscCall(VecNorm(y,NORM_2,&norm2)); 109 if (lf == -1 && norm2 > tol) { 110 PetscCall(PetscPrintf(PETSC_COMM_SELF, " reordered SEQAIJ: Cholesky/ICC levels %" PetscInt_FMT ", residual %g\n",lf,(double)norm2)); 111 } 112 113 /* Free data structures */ 114 PetscCall(MatDestroy(&C)); 115 PetscCall(ISDestroy(&row)); 116 PetscCall(ISDestroy(&col)); 117 PetscCall(PetscRandomDestroy(&rdm)); 118 PetscCall(VecDestroy(&x)); 119 PetscCall(VecDestroy(&y)); 120 PetscCall(VecDestroy(&ytmp)); 121 PetscCall(VecDestroy(&b)); 122 PetscCall(PetscFinalize()); 123 return 0; 124 } 125 126 /*TEST 127 128 test: 129 output_file: output/ex128.out 130 131 test: 132 suffix: 2 133 args: -cholesky -triangular_solve 134 135 TEST*/ 136