Actual source code: ex3.c
1: static char help[] = "Test PC redistribute on matrix with load imbalance. \n\
2: Modified from src/ksp/ksp/tutorials/ex2.c.\n\
3: Input parameters include:\n\
4: -random_exact_sol : use a random exact solution vector\n\
5: -view_exact_sol : write exact solution vector to stdout\n\
6: -n <mesh_y> : number of mesh points\n\n";
7: /*
8: Example:
9: mpiexec -n 8 ./ex3 -n 10000 -ksp_type cg -pc_type bjacobi -sub_pc_type icc -ksp_rtol 1.e-8 -log_view
10: mpiexec -n 8 ./ex3 -n 10000 -ksp_type preonly -pc_type redistribute -redistribute_ksp_type cg -redistribute_pc_type bjacobi -redistribute_sub_pc_type icc -redistribute_ksp_rtol 1.e-8 -log_view
11: */
13: #include <petscksp.h>
15: int main(int argc, char **args)
16: {
17: Vec x, b, u; /* approx solution, RHS, exact solution */
18: Mat A; /* linear system matrix */
19: KSP ksp; /* linear solver context */
20: PetscRandom rctx; /* random number generator context */
21: PetscReal norm; /* norm of solution error */
22: PetscInt i, j, Ii, J, Istart, Iend, m, n = 7, its, nloc, matdistribute = 0;
23: PetscBool flg = PETSC_FALSE;
24: PetscScalar v;
25: PetscMPIInt rank, size;
26: PetscLogStage stage;
28: PetscFunctionBeginUser;
29: PetscCall(PetscInitialize(&argc, &args, (char *)0, help));
30: PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size));
31: PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
32: PetscCheck(size > 1, PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This example requires at least 2 MPI processes!");
34: PetscCall(PetscOptionsGetInt(NULL, NULL, "-n", &n, NULL));
35: PetscCall(PetscOptionsGetInt(NULL, NULL, "-matdistribute", &matdistribute, NULL));
36: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
37: Compute the matrix and right-hand-side vector that define
38: the linear system, Ax = b.
39: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
40: switch (matdistribute) {
41: case 1: /* very imbalanced process load for matrix A */
42: m = (1 + size) * size;
43: nloc = (rank + 1) * n;
44: if (rank == size - 1) { /* proc[size-1] stores all remaining rows */
45: nloc = m * n;
46: for (i = 0; i < size - 1; i++) nloc -= (i + 1) * n;
47: }
48: break;
49: default: /* proc[0] and proc[1] load much smaller row blocks, the rest processes have same loads */
50: if (rank == 0 || rank == 1) {
51: nloc = n;
52: } else {
53: nloc = 10 * n; /* 10x larger load */
54: }
55: m = 2 + (size - 2) * 10;
56: break;
57: }
58: PetscCall(MatCreate(PETSC_COMM_WORLD, &A));
59: PetscCall(MatSetSizes(A, nloc, nloc, PETSC_DECIDE, PETSC_DECIDE));
60: PetscCall(MatSetFromOptions(A));
61: PetscCall(MatMPIAIJSetPreallocation(A, 5, NULL, 5, NULL));
62: PetscCall(MatSeqAIJSetPreallocation(A, 5, NULL));
63: PetscCall(MatSetUp(A));
65: PetscCall(MatGetOwnershipRange(A, &Istart, &Iend));
66: nloc = Iend - Istart;
67: PetscCall(PetscSynchronizedPrintf(PETSC_COMM_WORLD, "[%d] A Istart,Iend: %" PetscInt_FMT " %" PetscInt_FMT "; nloc %" PetscInt_FMT "\n", rank, Istart, Iend, nloc));
68: PetscCall(PetscSynchronizedFlush(PETSC_COMM_WORLD, PETSC_STDOUT));
70: PetscCall(PetscLogStageRegister("Assembly", &stage));
71: PetscCall(PetscLogStagePush(stage));
72: for (Ii = Istart; Ii < Iend; Ii++) {
73: v = -1.0;
74: i = Ii / n;
75: j = Ii - i * n;
76: if (i > 0) {
77: J = Ii - n;
78: PetscCall(MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES));
79: }
80: if (i < m - 1) {
81: J = Ii + n;
82: PetscCall(MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES));
83: }
84: if (j > 0) {
85: J = Ii - 1;
86: PetscCall(MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES));
87: }
88: if (j < n - 1) {
89: J = Ii + 1;
90: PetscCall(MatSetValues(A, 1, &Ii, 1, &J, &v, INSERT_VALUES));
91: }
92: v = 4.0;
93: PetscCall(MatSetValues(A, 1, &Ii, 1, &Ii, &v, INSERT_VALUES));
94: }
95: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
96: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
97: PetscCall(PetscLogStagePop());
99: /* A is symmetric. Set symmetric flag to enable ICC/Cholesky preconditioner */
100: PetscCall(MatSetOption(A, MAT_SYMMETRIC, PETSC_TRUE));
102: /* Create parallel vectors. */
103: PetscCall(VecCreate(PETSC_COMM_WORLD, &u));
104: PetscCall(VecSetSizes(u, nloc, PETSC_DECIDE));
105: PetscCall(VecSetFromOptions(u));
106: PetscCall(VecDuplicate(u, &b));
107: PetscCall(VecDuplicate(b, &x));
109: /* Set exact solution; then compute right-hand-side vector. */
110: PetscCall(PetscOptionsGetBool(NULL, NULL, "-random_exact_sol", &flg, NULL));
111: if (flg) {
112: PetscCall(PetscRandomCreate(PETSC_COMM_WORLD, &rctx));
113: PetscCall(PetscRandomSetFromOptions(rctx));
114: PetscCall(VecSetRandom(u, rctx));
115: PetscCall(PetscRandomDestroy(&rctx));
116: } else {
117: PetscCall(VecSet(u, 1.0));
118: }
119: PetscCall(MatMult(A, u, b));
121: /* View the exact solution vector if desired */
122: flg = PETSC_FALSE;
123: PetscCall(PetscOptionsGetBool(NULL, NULL, "-view_exact_sol", &flg, NULL));
124: if (flg) PetscCall(VecView(u, PETSC_VIEWER_STDOUT_WORLD));
126: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
127: Create the linear solver and set various options
128: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
129: PetscCall(KSPCreate(PETSC_COMM_WORLD, &ksp));
130: PetscCall(KSPSetOperators(ksp, A, A));
131: PetscCall(KSPSetTolerances(ksp, 1.e-2 / ((m + 1) * (n + 1)), PETSC_DEFAULT, PETSC_DEFAULT, PETSC_DEFAULT));
132: PetscCall(KSPSetFromOptions(ksp));
134: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
135: Solve the linear system
136: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
137: PetscCall(KSPSolve(ksp, b, x));
139: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
140: Check solution and clean up
141: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
142: PetscCall(VecAXPY(x, -1.0, u));
143: PetscCall(VecNorm(x, NORM_2, &norm));
144: PetscCall(KSPGetIterationNumber(ksp, &its));
145: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Norm of error %g iterations %" PetscInt_FMT "\n", (double)norm, its));
147: /* Free work space. */
148: PetscCall(KSPDestroy(&ksp));
149: PetscCall(VecDestroy(&u));
150: PetscCall(VecDestroy(&x));
151: PetscCall(VecDestroy(&b));
152: PetscCall(MatDestroy(&A));
153: PetscCall(PetscFinalize());
154: return 0;
155: }
157: /*TEST
159: test:
160: nsize: 8
161: args: -n 100 -ksp_type cg -pc_type bjacobi -sub_pc_type icc -ksp_rtol 1.e-8
163: test:
164: suffix: 2
165: nsize: 8
166: args: -n 100 -ksp_type preonly -pc_type redistribute -redistribute_ksp_type cg -redistribute_pc_type bjacobi -redistribute_sub_pc_type icc -redistribute_ksp_rtol 1.e-8
168: TEST*/