Actual source code: ex27.c
1: static char help[] = "Reads a PETSc matrix and vector from a file and solves the normal equations.\n\n";
3: /*
4: Include "petscksp.h" so that we can use KSP solvers. Note that this file
5: automatically includes:
6: petscsys.h - base PETSc routines petscvec.h - vectors
7: petscmat.h - matrices
8: petscis.h - index sets petscksp.h - Krylov subspace methods
9: petscviewer.h - viewers petscpc.h - preconditioners
10: */
11: #include <petscksp.h>
12: #include <petscviewerhdf5.h>
14: static PetscErrorCode VecLoadIfExists_Private(Vec b, PetscViewer fd, PetscBool *has)
15: {
16: PetscBool hdf5 = PETSC_FALSE;
18: PetscFunctionBeginUser;
19: PetscCall(PetscObjectTypeCompare((PetscObject)fd, PETSCVIEWERHDF5, &hdf5));
20: if (hdf5) {
21: #if defined(PETSC_HAVE_HDF5)
22: PetscCall(PetscViewerHDF5HasObject(fd, (PetscObject)b, has));
23: if (*has) PetscCall(VecLoad(b, fd));
24: #else
25: SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_SUP, "PETSc must be configured with HDF5 to use this feature");
26: #endif
27: } else {
28: PetscErrorCode ierrp;
29: PetscCall(PetscPushErrorHandler(PetscReturnErrorHandler, NULL));
30: ierrp = VecLoad(b, fd);
31: PetscCall(PetscPopErrorHandler());
32: *has = ierrp ? PETSC_FALSE : PETSC_TRUE;
33: }
34: PetscFunctionReturn(PETSC_SUCCESS);
35: }
37: int main(int argc, char **args)
38: {
39: KSP ksp; /* linear solver context */
40: Mat A, N; /* matrix */
41: Vec x, b, r, Ab, v[2]; /* approx solution, RHS, residual */
42: PetscViewer fd; /* viewer */
43: char file[PETSC_MAX_PATH_LEN] = ""; /* input file name */
44: char file_x0[PETSC_MAX_PATH_LEN] = ""; /* name of input file with initial guess */
45: char A_name[128] = "A", b_name[128] = "b", x0_name[128] = "x0"; /* name of the matrix, RHS and initial guess */
46: KSPType ksptype;
47: PetscBool has;
48: PetscInt its, n, m;
49: PetscReal norm;
50: PetscBool nonzero_guess = PETSC_TRUE;
51: PetscBool solve_normal = PETSC_FALSE;
52: PetscBool solve_augmented = PETSC_FALSE;
53: PetscBool truncate = PETSC_FALSE;
54: PetscBool explicit_transpose = PETSC_FALSE;
55: PetscBool hdf5 = PETSC_FALSE;
56: PetscBool test_custom_layout = PETSC_FALSE;
57: PetscBool sbaij = PETSC_FALSE;
58: PetscMPIInt rank, size;
60: PetscFunctionBeginUser;
61: PetscCall(PetscInitialize(&argc, &args, NULL, help));
62: PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
63: PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size));
64: /*
65: Determine files from which we read the linear system
66: (matrix, right-hand side and initial guess vector).
67: */
68: PetscCall(PetscOptionsGetString(NULL, NULL, "-f", file, sizeof(file), NULL));
69: PetscCall(PetscOptionsGetBool(NULL, NULL, "-truncate", &truncate, NULL));
70: if (!truncate) PetscCall(PetscOptionsGetString(NULL, NULL, "-f_x0", file_x0, sizeof(file_x0), NULL));
71: PetscCall(PetscOptionsGetString(NULL, NULL, "-A_name", A_name, sizeof(A_name), NULL));
72: PetscCall(PetscOptionsGetString(NULL, NULL, "-b_name", b_name, sizeof(b_name), NULL));
73: PetscCall(PetscOptionsGetString(NULL, NULL, "-x0_name", x0_name, sizeof(x0_name), NULL));
74: /*
75: Decide whether to solve the original system (-solve_normal 0)
76: or the normal equation (-solve_normal 1).
77: */
78: PetscCall(PetscOptionsGetBool(NULL, NULL, "-solve_normal", &solve_normal, NULL));
79: if (!solve_normal) PetscCall(PetscOptionsGetBool(NULL, NULL, "-solve_augmented", &solve_augmented, NULL));
80: if (solve_augmented) {
81: PetscCall(PetscOptionsGetBool(NULL, NULL, "-explicit_transpose", &explicit_transpose, NULL));
82: PetscCall(PetscOptionsGetBool(NULL, NULL, "-sbaij", &sbaij, NULL));
83: }
84: /*
85: Decide whether to use the HDF5 reader.
86: */
87: PetscCall(PetscOptionsGetBool(NULL, NULL, "-hdf5", &hdf5, NULL));
88: /*
89: Decide whether custom matrix layout will be tested.
90: */
91: PetscCall(PetscOptionsGetBool(NULL, NULL, "-test_custom_layout", &test_custom_layout, NULL));
93: /* -----------------------------------------------------------
94: Beginning of linear solver loop
95: ----------------------------------------------------------- */
96: /*
97: Loop through the linear solve 2 times.
98: - The intention here is to preload and solve a small system;
99: then load another (larger) system and solve it as well.
100: This process preloads the instructions with the smaller
101: system so that more accurate performance monitoring (via
102: -log_view) can be done with the larger one (that actually
103: is the system of interest).
104: */
105: PetscPreLoadBegin(PETSC_FALSE, "Load system");
107: /* - - - - - - - - - - - New Stage - - - - - - - - - - - - -
108: Load system
109: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
111: /*
112: Open binary file. Note that we use FILE_MODE_READ to indicate
113: reading from this file.
114: */
115: if (hdf5) {
116: #if defined(PETSC_HAVE_HDF5)
117: PetscCall(PetscViewerHDF5Open(PETSC_COMM_WORLD, file, FILE_MODE_READ, &fd));
118: PetscCall(PetscViewerPushFormat(fd, PETSC_VIEWER_HDF5_MAT));
119: #else
120: SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_SUP, "PETSc must be configured with HDF5 to use this feature");
121: #endif
122: } else {
123: PetscCall(PetscViewerBinaryOpen(PETSC_COMM_WORLD, file, FILE_MODE_READ, &fd));
124: }
126: /*
127: Load the matrix.
128: Matrix type is set automatically but you can override it by MatSetType() prior to MatLoad().
129: Do that only if you really insist on the given type.
130: */
131: PetscCall(MatCreate(PETSC_COMM_WORLD, &A));
132: PetscCall(PetscObjectSetName((PetscObject)A, A_name));
133: PetscCall(MatSetFromOptions(A));
134: PetscCall(MatLoad(A, fd));
135: if (truncate) {
136: Mat P, B;
137: PetscInt M, N;
138: PetscCall(MatGetLocalSize(A, &m, &n));
139: PetscCall(MatGetSize(A, &M, &N));
140: PetscCall(MatCreateFromOptions(PETSC_COMM_WORLD, NULL, 1, m, PETSC_DECIDE, M, N / 1.5, &P));
141: PetscCall(MatGetOwnershipRangeColumn(P, &m, &n));
142: for (; m < n; ++m) PetscCall(MatSetValue(P, m, m, 1.0, INSERT_VALUES));
143: PetscCall(MatAssemblyBegin(P, MAT_FINAL_ASSEMBLY));
144: PetscCall(MatAssemblyEnd(P, MAT_FINAL_ASSEMBLY));
145: PetscCall(MatShift(P, 1.0));
146: PetscCall(MatMatMult(A, P, MAT_INITIAL_MATRIX, PETSC_DETERMINE, &B));
147: PetscCall(MatDestroy(&P));
148: PetscCall(MatDestroy(&A));
149: A = B;
150: }
151: if (test_custom_layout && size > 1) {
152: /* Perturb the local sizes and create the matrix anew */
153: PetscInt m1, n1;
154: PetscCall(MatGetLocalSize(A, &m, &n));
155: m = rank ? m - 1 : m + size - 1;
156: n = (rank == size - 1) ? n + size - 1 : n - 1;
157: PetscCall(MatDestroy(&A));
158: PetscCall(MatCreate(PETSC_COMM_WORLD, &A));
159: PetscCall(PetscObjectSetName((PetscObject)A, A_name));
160: PetscCall(MatSetSizes(A, m, n, PETSC_DECIDE, PETSC_DECIDE));
161: PetscCall(MatSetFromOptions(A));
162: PetscCall(MatLoad(A, fd));
163: PetscCall(MatGetLocalSize(A, &m1, &n1));
164: PetscCheck(m1 == m && n1 == n, PETSC_COMM_WORLD, PETSC_ERR_PLIB, "resulting sizes differ from requested ones: %" PetscInt_FMT " %" PetscInt_FMT " != %" PetscInt_FMT " %" PetscInt_FMT, m1, n1, m, n);
165: }
166: PetscCall(MatGetLocalSize(A, &m, &n));
168: /*
169: Load the RHS vector if it is present in the file, otherwise use a vector of all ones.
170: */
171: PetscCall(MatCreateVecs(A, &x, &b));
172: PetscCall(PetscObjectSetName((PetscObject)b, b_name));
173: PetscCall(VecSetFromOptions(b));
174: PetscCall(VecLoadIfExists_Private(b, fd, &has));
175: if (!has) {
176: PetscScalar one = 1.0;
177: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Failed to load RHS, so use a vector of all ones.\n"));
178: PetscCall(VecSetFromOptions(b));
179: PetscCall(VecSet(b, one));
180: }
182: /*
183: Load the initial guess vector if it is present in the file, otherwise use a vector of all zeros.
184: */
185: PetscCall(PetscObjectSetName((PetscObject)x, x0_name));
186: PetscCall(VecSetFromOptions(x));
187: if (!truncate) {
188: /* load file_x0 if it is specified, otherwise try to reuse file */
189: if (file_x0[0]) {
190: PetscCall(PetscViewerDestroy(&fd));
191: if (hdf5) {
192: #if defined(PETSC_HAVE_HDF5)
193: PetscCall(PetscViewerHDF5Open(PETSC_COMM_WORLD, file_x0, FILE_MODE_READ, &fd));
194: #endif
195: } else {
196: PetscCall(PetscViewerBinaryOpen(PETSC_COMM_WORLD, file_x0, FILE_MODE_READ, &fd));
197: }
198: }
199: PetscCall(VecLoadIfExists_Private(x, fd, &has));
200: } else has = PETSC_FALSE;
201: if (truncate || !has) {
202: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Failed to load initial guess, so use a vector of all zeros.\n"));
203: PetscCall(VecSet(x, 0.0));
204: nonzero_guess = PETSC_FALSE;
205: }
206: PetscCall(PetscViewerDestroy(&fd));
208: PetscCall(VecDuplicate(x, &Ab));
210: /* - - - - - - - - - - - New Stage - - - - - - - - - - - - -
211: Setup solve for system
212: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
214: /*
215: Conclude profiling last stage; begin profiling next stage.
216: */
217: PetscPreLoadStage("KSPSetUp");
219: PetscCall(MatCreateNormalHermitian(A, &N));
220: PetscCall(MatMultHermitianTranspose(A, b, Ab));
222: /*
223: Create linear solver; set operators; set runtime options.
224: */
225: PetscCall(KSPCreate(PETSC_COMM_WORLD, &ksp));
227: if (solve_normal) {
228: PetscCall(KSPSetOperators(ksp, N, N));
229: } else if (solve_augmented) {
230: Mat array[4], C, S;
231: Vec view;
232: PetscInt M, n;
233: PetscReal diag;
235: PetscCall(MatDestroy(&N));
236: PetscCall(MatGetSize(A, &M, NULL));
237: PetscCall(MatGetLocalSize(A, NULL, &n));
238: PetscCall(MatCreateConstantDiagonal(PETSC_COMM_WORLD, m, m, M, M, -1.0, array));
239: array[1] = A;
240: if (!explicit_transpose) PetscCall(MatCreateHermitianTranspose(A, array + 2));
241: else PetscCall(MatHermitianTranspose(A, MAT_INITIAL_MATRIX, array + 2));
242: PetscCall(PetscOptionsGetReal(NULL, NULL, "-nonzero_A11", &diag, &has));
243: if (has) PetscCall(MatCreateConstantDiagonal(PETSC_COMM_WORLD, n, n, PETSC_DECIDE, PETSC_DECIDE, diag, array + 3));
244: else array[3] = NULL;
245: PetscCall(MatCreateNest(PETSC_COMM_WORLD, 2, NULL, 2, NULL, array, &C));
246: if (!sbaij) PetscCall(MatNestSetVecType(C, VECNEST));
247: PetscCall(MatCreateVecs(C, v + 1, v));
248: if (!sbaij) {
249: PetscCall(VecNestGetSubVec(v[0], 0, &view));
250: PetscCall(VecCopy(b, view));
251: PetscCall(VecNestGetSubVec(v[1], 1, &view));
252: PetscCall(VecCopy(x, view));
253: PetscCall(KSPSetOperators(ksp, C, C));
254: } else {
255: const PetscScalar *read;
256: PetscScalar *write;
257: PetscCall(VecGetArrayRead(b, &read));
258: PetscCall(VecGetArrayWrite(v[0], &write));
259: for (PetscInt i = 0; i < m; ++i) write[i] = read[i];
260: PetscCall(VecRestoreArrayWrite(v[0], &write));
261: PetscCall(VecRestoreArrayRead(b, &read));
262: PetscCall(VecGetArrayRead(x, &read));
263: PetscCall(VecGetArrayWrite(v[1], &write));
264: for (PetscInt i = 0; i < n; ++i) write[m + i] = read[i];
265: PetscCall(VecRestoreArrayWrite(v[1], &write));
266: PetscCall(VecRestoreArrayRead(x, &read));
267: PetscCall(MatConvert(C, MATSBAIJ, MAT_INITIAL_MATRIX, &S));
268: PetscCall(KSPSetOperators(ksp, S, S));
269: PetscCall(MatDestroy(&S));
270: }
271: PetscCall(MatDestroy(&C));
272: PetscCall(MatDestroy(array));
273: PetscCall(MatDestroy(array + 2));
274: PetscCall(MatDestroy(array + 3));
275: } else {
276: PC pc;
277: PetscCall(KSPSetType(ksp, KSPLSQR));
278: PetscCall(KSPGetPC(ksp, &pc));
279: PetscCall(PCSetType(pc, PCNONE));
280: PetscCall(KSPSetOperators(ksp, A, N));
281: }
282: PetscCall(KSPSetInitialGuessNonzero(ksp, nonzero_guess));
283: PetscCall(KSPSetFromOptions(ksp));
285: /*
286: Here we explicitly call KSPSetUp() and KSPSetUpOnBlocks() to
287: enable more precise profiling of setting up the preconditioner.
288: These calls are optional, since both will be called within
289: KSPSolve() if they haven't been called already.
290: */
291: PetscCall(KSPSetUp(ksp));
292: PetscCall(KSPSetUpOnBlocks(ksp));
294: /*
295: Solve system
296: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
298: /*
299: Begin profiling next stage
300: */
301: PetscPreLoadStage("KSPSolve");
303: /*
304: Solve linear system
305: */
306: if (solve_normal) {
307: PetscCall(KSPSolve(ksp, Ab, x));
308: } else if (solve_augmented) {
309: KSP *subksp;
310: PC pc;
311: Mat C;
312: Vec view;
313: PetscBool flg;
315: PetscCall(KSPGetPC(ksp, &pc));
316: PetscCall(PetscObjectTypeCompare((PetscObject)pc, PCFIELDSPLIT, &flg));
317: if (flg) {
318: PetscCall(KSPGetOperators(ksp, &C, NULL));
319: PetscCall(PCFieldSplitGetSubKSP(pc, NULL, &subksp));
320: PetscCall(KSPGetPC(subksp[1], &pc));
321: PetscCall(PetscObjectTypeCompare((PetscObject)pc, PCHPDDM, &flg));
322: if (flg) {
323: #if defined(PETSC_HAVE_HPDDM) && defined(PETSC_HAVE_DYNAMIC_LIBRARIES) && defined(PETSC_USE_SHARED_LIBRARIES)
324: Mat aux, S, **array;
325: IS is;
327: PetscCall(MatCreate(PETSC_COMM_SELF, &aux));
328: PetscCall(ISCreate(PETSC_COMM_SELF, &is));
329: PetscCall(PCHPDDMSetAuxiliaryMat(pc, is, aux, NULL, NULL)); /* dummy objects just to cover corner cases in PCSetUp() */
330: PetscCall(ISDestroy(&is));
331: PetscCall(MatDestroy(&aux));
332: PetscCall(MatNestGetSubMats(C, NULL, NULL, &array));
333: PetscCall(MatCreateSchurComplement(array[0][0], array[0][0], array[0][1], array[1][0], array[1][1], &S));
334: PetscCall(MatSetOptionsPrefix(S, "fieldsplit_1_"));
335: PetscCall(KSPSetOperators(subksp[1], S, S));
336: PetscCall(MatDestroy(&S));
337: PetscCall(PCSetFromOptions(pc));
338: #endif
339: }
340: PetscCall(PetscFree(subksp));
341: }
342: PetscCall(KSPSolve(ksp, v[0], v[1]));
343: if (!sbaij) {
344: PetscCall(VecNestGetSubVec(v[1], 1, &view));
345: PetscCall(VecCopy(view, x));
346: } else {
347: const PetscScalar *read;
348: PetscScalar *write;
349: PetscCall(MatGetLocalSize(A, &m, &n));
350: PetscCall(VecGetArrayRead(v[1], &read));
351: PetscCall(VecGetArrayWrite(x, &write));
352: for (PetscInt i = 0; i < n; ++i) write[i] = read[m + i];
353: PetscCall(VecRestoreArrayWrite(x, &write));
354: PetscCall(VecRestoreArrayRead(v[1], &read));
355: }
356: } else {
357: PetscCall(KSPSolve(ksp, b, x));
358: }
359: PetscCall(PetscObjectSetName((PetscObject)x, "x"));
361: /*
362: Conclude profiling this stage
363: */
364: PetscPreLoadStage("Cleanup");
366: /* - - - - - - - - - - - New Stage - - - - - - - - - - - - -
367: Check error, print output, free data structures.
368: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
370: /*
371: Check error
372: */
373: PetscCall(VecDuplicate(b, &r));
374: PetscCall(MatMult(A, x, r));
375: PetscCall(VecAXPY(r, -1.0, b));
376: PetscCall(VecNorm(r, NORM_2, &norm));
377: PetscCall(KSPGetIterationNumber(ksp, &its));
378: PetscCall(KSPGetType(ksp, &ksptype));
379: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "KSP type: %s\n", ksptype));
380: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Number of iterations = %3" PetscInt_FMT "\n", its));
381: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Residual norm %g\n", (double)norm));
383: /*
384: Free work space. All PETSc objects should be destroyed when they
385: are no longer needed.
386: */
387: PetscCall(MatDestroy(&A));
388: PetscCall(VecDestroy(&b));
389: PetscCall(MatDestroy(&N));
390: PetscCall(VecDestroy(&Ab));
391: PetscCall(VecDestroy(&r));
392: PetscCall(VecDestroy(&x));
393: if (solve_augmented) {
394: PetscCall(VecDestroy(v));
395: PetscCall(VecDestroy(v + 1));
396: }
397: PetscCall(KSPDestroy(&ksp));
398: PetscPreLoadEnd();
399: /* -----------------------------------------------------------
400: End of linear solver loop
401: ----------------------------------------------------------- */
403: PetscCall(PetscFinalize());
404: return 0;
405: }
407: /*TEST
409: test:
410: suffix: 1
411: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES)
412: args: -f ${DATAFILESPATH}/matrices/medium -ksp_view -ksp_monitor_short -ksp_max_it 100 -solve_normal
414: test:
415: suffix: 2
416: nsize: 2
417: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES)
418: args: -f ${DATAFILESPATH}/matrices/shallow_water1 -ksp_view -ksp_monitor_short -ksp_max_it 100 -solve_normal -pc_type none
420: # Test handling failing VecLoad without abort
421: testset:
422: requires: double !complex !defined(PETSC_USE_64BIT_INDICES)
423: args: -ksp_type cg -ksp_view -ksp_converged_reason -ksp_monitor_short -ksp_max_it 10
424: test:
425: suffix: 3
426: nsize: {{1 2}separate output}
427: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/tiny_system
428: args: -f_x0 ${wPETSC_DIR}/share/petsc/datafiles/matrices/tiny_system_x0
429: test:
430: suffix: 3a
431: nsize: {{1 2}separate output}
432: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/tiny_system
433: args: -f_x0 NONEXISTING_FILE
434: test:
435: suffix: 3b
436: nsize: {{1 2}separate output}
437: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/tiny_system_with_x0 # this file includes all A, b and x0
438: test:
439: # Load square matrix, RHS and initial guess from HDF5 (Version 7.3 MAT-File)
440: suffix: 3b_hdf5
441: requires: hdf5 defined(PETSC_HDF5_HAVE_ZLIB)
442: nsize: {{1 2}separate output}
443: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/tiny_system_with_x0.mat -hdf5
445: # Test least-square algorithms
446: testset:
447: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES)
448: args: -f ${DATAFILESPATH}/matrices/rectangular_ultrasound_4889x841
449: test:
450: suffix: 4
451: nsize: {{1 2 4}}
452: args: -ksp_converged_reason -ksp_monitor_short -ksp_rtol 1e-5 -ksp_max_it 100
453: args: -solve_normal -ksp_type cg
454: test:
455: suffix: 4a
456: nsize: {{1 2 4}}
457: args: -ksp_converged_reason -ksp_monitor_short -ksp_rtol 1e-5 -ksp_max_it 100
458: args: -ksp_type {{cgls lsqr}separate output}
459: test:
460: # Test KSPLSQR-specific options
461: suffix: 4b
462: nsize: 2
463: args: -ksp_converged_reason -ksp_rtol 1e-3 -ksp_max_it 200 -ksp_view
464: args: -ksp_type lsqr -ksp_convergence_test lsqr -ksp_lsqr_monitor -ksp_lsqr_compute_standard_error -ksp_lsqr_exact_mat_norm {{0 1}separate output}
465: test:
466: suffix: 4c
467: nsize: 4
468: requires: hpddm slepc defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
469: filter: grep -v "shared subdomain KSP between SLEPc and PETSc" | grep -v "total: nonzeros="
470: args: -ksp_converged_reason -ksp_rtol 1e-5 -ksp_max_it 100 -ksp_view
471: args: -ksp_type lsqr -pc_type hpddm -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp {{false true}shared output}
472: args: -pc_hpddm_levels_1_pc_asm_sub_mat_type aij -pc_hpddm_levels_1_pc_asm_type basic -pc_hpddm_levels_1_sub_pc_type cholesky
473: test:
474: suffix: 4d
475: nsize: 4
476: requires: hpddm slepc suitesparse defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
477: filter: grep -v "shared subdomain KSP between SLEPc and PETSc"
478: args: -ksp_converged_reason -ksp_rtol 1e-5 -ksp_max_it 100 -ksp_view
479: args: -ksp_type lsqr -pc_type hpddm -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp {{false true}shared output} -pc_hpddm_levels_1_st_pc_type qr
480: args: -pc_hpddm_levels_1_pc_asm_sub_mat_type normalh -pc_hpddm_levels_1_pc_asm_type basic -pc_hpddm_levels_1_sub_pc_type qr
481: test:
482: suffix: 4e
483: nsize: 4
484: requires: hpddm slepc defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
485: args: -solve_augmented -ksp_type gmres
486: args: -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition self -fieldsplit_0_pc_type jacobi -fieldsplit_ksp_type preonly
487: args: -prefix_push fieldsplit_1_ -pc_type hpddm -pc_hpddm_schur_precondition least_squares -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp -pc_hpddm_levels_1_sub_pc_type cholesky -prefix_pop -fieldsplit_1_mat_schur_complement_ainv_type {{lump blockdiag}shared output}
488: test:
489: suffix: 4f
490: nsize: 4
491: requires: hpddm slepc suitesparse defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
492: filter: sed -e "s/(1,0) : type=mpiaij/(1,0) : type=transpose/g" -e "s/hermitiantranspose/transpose/g"
493: args: -solve_augmented -ksp_type gmres -ksp_view -explicit_transpose {{false true}shared output}
494: args: -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition self -fieldsplit_0_pc_type jacobi -fieldsplit_ksp_type preonly
495: args: -prefix_push fieldsplit_1_ -pc_type hpddm -pc_hpddm_schur_precondition least_squares -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp -pc_hpddm_levels_1_sub_pc_type qr -prefix_pop
496: test:
497: suffix: 4f_nonzero
498: nsize: 4
499: requires: hpddm slepc suitesparse defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
500: args: -solve_augmented -nonzero_A11 {{0.0 1e-14}shared output} -ksp_type gmres
501: args: -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition self -fieldsplit_0_pc_type jacobi -fieldsplit_ksp_type preonly
502: args: -prefix_push fieldsplit_1_ -pc_type hpddm -pc_hpddm_schur_precondition least_squares -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp -pc_hpddm_levels_1_sub_pc_type qr -prefix_pop
503: test:
504: suffix: 4f_nonzero_shift
505: nsize: 4
506: output_file: output/ex27_4f_nonzero.out
507: requires: hpddm slepc defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
508: args: -solve_augmented -nonzero_A11 {{0.0 1e-6}shared output} -ksp_type gmres
509: args: -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition self -fieldsplit_0_pc_type jacobi -fieldsplit_ksp_type preonly
510: args: -prefix_push fieldsplit_1_ -pc_type hpddm -pc_hpddm_schur_precondition least_squares -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_st_share_sub_ksp -pc_hpddm_levels_1_sub_pc_type cholesky -pc_hpddm_levels_1_eps_gen_non_hermitian -prefix_pop
511: test:
512: suffix: 4g
513: nsize: 4
514: requires: hypre !defined(PETSC_HAVE_HYPRE_DEVICE)
515: args: -ksp_converged_reason -ksp_monitor_short -ksp_rtol 1e-5 -ksp_max_it 100
516: args: -ksp_type lsqr -pc_type hypre
517: test:
518: suffix: 4h
519: nsize: {{1 4}}
520: args: -solve_augmented -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition self -pc_fieldsplit_detect_saddle_point -sbaij true -ksp_type fgmres
522: test:
523: # Load rectangular matrix from HDF5 (Version 7.3 MAT-File)
524: suffix: 4a_lsqr_hdf5
525: nsize: {{1 2 4 8}}
526: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES) hdf5 defined(PETSC_HDF5_HAVE_ZLIB)
527: args: -f ${DATAFILESPATH}/matrices/matlab/rectangular_ultrasound_4889x841.mat -hdf5
528: args: -ksp_converged_reason -ksp_monitor_short -ksp_rtol 1e-5 -ksp_max_it 100
529: args: -ksp_type lsqr
530: args: -test_custom_layout {{0 1}}
532: # Test for correct cgls convergence reason
533: test:
534: suffix: 5
535: nsize: 1
536: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES)
537: args: -f ${DATAFILESPATH}/matrices/rectangular_ultrasound_4889x841
538: args: -ksp_converged_reason -ksp_rtol 1e-2 -ksp_max_it 100
539: args: -ksp_type cgls
541: # Load a matrix, RHS and solution from HDF5 (Version 7.3 MAT-File). Test immediate convergence.
542: testset:
543: nsize: {{1 2 4 8}}
544: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES) hdf5 defined(PETSC_HDF5_HAVE_ZLIB)
545: args: -ksp_converged_reason -ksp_monitor_short -ksp_rtol 1e-5 -ksp_max_it 10
546: args: -ksp_type lsqr
547: args: -test_custom_layout {{0 1}}
548: args: -hdf5 -x0_name x
549: test:
550: suffix: 6_hdf5
551: args: -f ${DATAFILESPATH}/matrices/matlab/small.mat
552: test:
553: suffix: 6_hdf5_rect
554: args: -f ${DATAFILESPATH}/matrices/matlab/small_rect.mat
555: test:
556: suffix: 6_hdf5_dense
557: args: -f ${DATAFILESPATH}/matrices/matlab/small_dense.mat -mat_type dense
558: test:
559: suffix: 6_hdf5_rect_dense
560: args: -f ${DATAFILESPATH}/matrices/matlab/small_rect_dense.mat -mat_type dense
562: # Test correct handling of local dimensions in PCApply
563: testset:
564: requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES)
565: requires: hdf5 defined(PETSC_HDF5_HAVE_ZLIB)
566: nsize: 3
567: suffix: 7
568: args: -f ${DATAFILESPATH}/matrices/matlab/small.mat -hdf5 -test_custom_layout 1 -ksp_type lsqr -pc_type jacobi
570: # Test complex matrices
571: testset:
572: requires: double complex !defined(PETSC_USE_64BIT_INDICES)
573: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/nh-complex-int32-float64
574: output_file: output/ex27_8.out
575: filter: grep -v "KSP type"
576: test:
577: suffix: 8
578: args: -solve_normal 0 -ksp_type {{lsqr cgls}}
579: test:
580: suffix: 8_normal
581: args: -solve_normal 1 -ksp_type {{cg bicg}}
583: testset:
584: requires: double suitesparse !defined(PETSC_USE_64BIT_INDICES)
585: args: -solve_normal {{0 1}shared output} -pc_type qr
586: output_file: output/ex27_9.out
587: filter: grep -v "KSP type"
588: test:
589: suffix: 9_real
590: requires: !complex
591: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/ns-real-int32-float64
592: test:
593: suffix: 9_complex
594: requires: complex
595: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/nh-complex-int32-float64
597: test:
598: suffix: 10
599: requires: !complex double suitesparse !defined(PETSC_USE_64BIT_INDICES)
600: nsize: 2
601: args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/ns-real-int32-float64 -pc_type bjacobi -sub_pc_type qr
603: test:
604: suffix: 11
605: nsize: 4
606: requires: datafilespath double complex !defined(PETSC_USE_64BIT_INDICES) hpddm slepc defined(PETSC_HAVE_DYNAMIC_LIBRARIES) defined(PETSC_USE_SHARED_LIBRARIES)
607: args: -f ${DATAFILESPATH}/matrices/farzad_B_rhs -truncate
608: args: -ksp_converged_reason -ksp_rtol 1e-5 -ksp_max_it 100
609: args: -ksp_type lsqr -pc_type hpddm -pc_hpddm_define_subdomains -pc_hpddm_levels_1_eps_nev 20 -pc_hpddm_levels_1_eps_threshold_absolute 1e-6
610: args: -pc_hpddm_levels_1_pc_asm_sub_mat_type aij -pc_hpddm_levels_1_pc_asm_type basic -pc_hpddm_levels_1_sub_pc_type lu -pc_hpddm_coarse_pc_type lu
611: filter: sed -e "s/ 10/ 9/g"
613: TEST*/