Actual source code: sbaij.c
1: /*
2: Defines the basic matrix operations for the SBAIJ (compressed row)
3: matrix storage format.
4: */
5: #include <../src/mat/impls/baij/seq/baij.h>
6: #include <../src/mat/impls/sbaij/seq/sbaij.h>
7: #include <petscblaslapack.h>
9: #include <../src/mat/impls/sbaij/seq/relax.h>
10: #define USESHORT
11: #include <../src/mat/impls/sbaij/seq/relax.h>
13: /* defines MatSetValues_Seq_Hash(), MatAssemblyEnd_Seq_Hash(), MatSetUp_Seq_Hash() */
14: #define TYPE SBAIJ
15: #define TYPE_SBAIJ
16: #define TYPE_BS
17: #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h"
18: #undef TYPE_BS
19: #define TYPE_BS _BS
20: #define TYPE_BS_ON
21: #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h"
22: #undef TYPE_BS
23: #undef TYPE_SBAIJ
24: #include "../src/mat/impls/aij/seq/seqhashmat.h"
25: #undef TYPE
26: #undef TYPE_BS_ON
28: #if defined(PETSC_HAVE_ELEMENTAL)
29: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
30: #endif
31: #if defined(PETSC_HAVE_SCALAPACK)
32: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
33: #endif
34: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat, MatType, MatReuse, Mat *);
36: /*
37: Checks for missing diagonals
38: */
39: static PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A, PetscBool *missing, PetscInt *dd)
40: {
41: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
42: PetscInt *diag, *ii = a->i, i;
44: PetscFunctionBegin;
45: PetscCall(MatMarkDiagonal_SeqSBAIJ(A));
46: *missing = PETSC_FALSE;
47: if (A->rmap->n > 0 && !ii) {
48: *missing = PETSC_TRUE;
49: if (dd) *dd = 0;
50: PetscCall(PetscInfo(A, "Matrix has no entries therefore is missing diagonal\n"));
51: } else {
52: diag = a->diag;
53: for (i = 0; i < a->mbs; i++) {
54: if (diag[i] >= ii[i + 1]) {
55: *missing = PETSC_TRUE;
56: if (dd) *dd = i;
57: break;
58: }
59: }
60: }
61: PetscFunctionReturn(PETSC_SUCCESS);
62: }
64: PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A)
65: {
66: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
67: PetscInt i, j;
69: PetscFunctionBegin;
70: if (!a->diag) {
71: PetscCall(PetscMalloc1(a->mbs, &a->diag));
72: a->free_diag = PETSC_TRUE;
73: }
74: for (i = 0; i < a->mbs; i++) {
75: a->diag[i] = a->i[i + 1];
76: for (j = a->i[i]; j < a->i[i + 1]; j++) {
77: if (a->j[j] == i) {
78: a->diag[i] = j;
79: break;
80: }
81: }
82: }
83: PetscFunctionReturn(PETSC_SUCCESS);
84: }
86: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *inia[], const PetscInt *inja[], PetscBool *done)
87: {
88: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
89: PetscInt i, j, n = a->mbs, nz = a->i[n], *tia, *tja, bs = A->rmap->bs, k, l, cnt;
90: PetscInt **ia = (PetscInt **)inia, **ja = (PetscInt **)inja;
92: PetscFunctionBegin;
93: *nn = n;
94: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
95: if (symmetric) {
96: PetscCall(MatToSymmetricIJ_SeqAIJ(n, a->i, a->j, PETSC_FALSE, 0, 0, &tia, &tja));
97: nz = tia[n];
98: } else {
99: tia = a->i;
100: tja = a->j;
101: }
103: if (!blockcompressed && bs > 1) {
104: (*nn) *= bs;
105: /* malloc & create the natural set of indices */
106: PetscCall(PetscMalloc1((n + 1) * bs, ia));
107: if (n) {
108: (*ia)[0] = oshift;
109: for (j = 1; j < bs; j++) (*ia)[j] = (tia[1] - tia[0]) * bs + (*ia)[j - 1];
110: }
112: for (i = 1; i < n; i++) {
113: (*ia)[i * bs] = (tia[i] - tia[i - 1]) * bs + (*ia)[i * bs - 1];
114: for (j = 1; j < bs; j++) (*ia)[i * bs + j] = (tia[i + 1] - tia[i]) * bs + (*ia)[i * bs + j - 1];
115: }
116: if (n) (*ia)[n * bs] = (tia[n] - tia[n - 1]) * bs + (*ia)[n * bs - 1];
118: if (inja) {
119: PetscCall(PetscMalloc1(nz * bs * bs, ja));
120: cnt = 0;
121: for (i = 0; i < n; i++) {
122: for (j = 0; j < bs; j++) {
123: for (k = tia[i]; k < tia[i + 1]; k++) {
124: for (l = 0; l < bs; l++) (*ja)[cnt++] = bs * tja[k] + l;
125: }
126: }
127: }
128: }
130: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
131: PetscCall(PetscFree(tia));
132: PetscCall(PetscFree(tja));
133: }
134: } else if (oshift == 1) {
135: if (symmetric) {
136: nz = tia[A->rmap->n / bs];
137: /* add 1 to i and j indices */
138: for (i = 0; i < A->rmap->n / bs + 1; i++) tia[i] = tia[i] + 1;
139: *ia = tia;
140: if (ja) {
141: for (i = 0; i < nz; i++) tja[i] = tja[i] + 1;
142: *ja = tja;
143: }
144: } else {
145: nz = a->i[A->rmap->n / bs];
146: /* malloc space and add 1 to i and j indices */
147: PetscCall(PetscMalloc1(A->rmap->n / bs + 1, ia));
148: for (i = 0; i < A->rmap->n / bs + 1; i++) (*ia)[i] = a->i[i] + 1;
149: if (ja) {
150: PetscCall(PetscMalloc1(nz, ja));
151: for (i = 0; i < nz; i++) (*ja)[i] = a->j[i] + 1;
152: }
153: }
154: } else {
155: *ia = tia;
156: if (ja) *ja = tja;
157: }
158: PetscFunctionReturn(PETSC_SUCCESS);
159: }
161: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done)
162: {
163: PetscFunctionBegin;
164: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
165: if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
166: PetscCall(PetscFree(*ia));
167: if (ja) PetscCall(PetscFree(*ja));
168: }
169: PetscFunctionReturn(PETSC_SUCCESS);
170: }
172: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
173: {
174: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
176: PetscFunctionBegin;
177: if (A->hash_active) {
178: PetscInt bs;
179: A->ops[0] = a->cops;
180: PetscCall(PetscHMapIJVDestroy(&a->ht));
181: PetscCall(MatGetBlockSize(A, &bs));
182: if (bs > 1) PetscCall(PetscHSetIJDestroy(&a->bht));
183: PetscCall(PetscFree(a->dnz));
184: PetscCall(PetscFree(a->bdnz));
185: A->hash_active = PETSC_FALSE;
186: }
187: PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, a->nz));
188: PetscCall(MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i));
189: if (a->free_diag) PetscCall(PetscFree(a->diag));
190: PetscCall(ISDestroy(&a->row));
191: PetscCall(ISDestroy(&a->col));
192: PetscCall(ISDestroy(&a->icol));
193: PetscCall(PetscFree(a->idiag));
194: PetscCall(PetscFree(a->inode.size));
195: if (a->free_imax_ilen) PetscCall(PetscFree2(a->imax, a->ilen));
196: PetscCall(PetscFree(a->solve_work));
197: PetscCall(PetscFree(a->sor_work));
198: PetscCall(PetscFree(a->solves_work));
199: PetscCall(PetscFree(a->mult_work));
200: PetscCall(PetscFree(a->saved_values));
201: if (a->free_jshort) PetscCall(PetscFree(a->jshort));
202: PetscCall(PetscFree(a->inew));
203: PetscCall(MatDestroy(&a->parent));
204: PetscCall(PetscFree(A->data));
206: PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL));
207: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJGetArray_C", NULL));
208: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJRestoreArray_C", NULL));
209: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL));
210: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL));
211: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetColumnIndices_C", NULL));
212: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqaij_C", NULL));
213: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqbaij_C", NULL));
214: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocation_C", NULL));
215: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocationCSR_C", NULL));
216: #if defined(PETSC_HAVE_ELEMENTAL)
217: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_elemental_C", NULL));
218: #endif
219: #if defined(PETSC_HAVE_SCALAPACK)
220: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_scalapack_C", NULL));
221: #endif
222: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
223: PetscFunctionReturn(PETSC_SUCCESS);
224: }
226: static PetscErrorCode MatSetOption_SeqSBAIJ(Mat A, MatOption op, PetscBool flg)
227: {
228: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
229: #if defined(PETSC_USE_COMPLEX)
230: PetscInt bs;
231: #endif
233: PetscFunctionBegin;
234: #if defined(PETSC_USE_COMPLEX)
235: PetscCall(MatGetBlockSize(A, &bs));
236: #endif
237: switch (op) {
238: case MAT_ROW_ORIENTED:
239: a->roworiented = flg;
240: break;
241: case MAT_KEEP_NONZERO_PATTERN:
242: a->keepnonzeropattern = flg;
243: break;
244: case MAT_NEW_NONZERO_LOCATIONS:
245: a->nonew = (flg ? 0 : 1);
246: break;
247: case MAT_NEW_NONZERO_LOCATION_ERR:
248: a->nonew = (flg ? -1 : 0);
249: break;
250: case MAT_NEW_NONZERO_ALLOCATION_ERR:
251: a->nonew = (flg ? -2 : 0);
252: break;
253: case MAT_UNUSED_NONZERO_LOCATION_ERR:
254: a->nounused = (flg ? -1 : 0);
255: break;
256: case MAT_FORCE_DIAGONAL_ENTRIES:
257: case MAT_IGNORE_OFF_PROC_ENTRIES:
258: case MAT_USE_HASH_TABLE:
259: case MAT_SORTED_FULL:
260: PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op]));
261: break;
262: case MAT_HERMITIAN:
263: #if defined(PETSC_USE_COMPLEX)
264: if (flg) { /* disable transpose ops */
265: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for Hermitian with block size greater than 1");
266: A->ops->multtranspose = NULL;
267: A->ops->multtransposeadd = NULL;
268: A->symmetric = PETSC_BOOL3_FALSE;
269: }
270: #endif
271: break;
272: case MAT_SYMMETRIC:
273: case MAT_SPD:
274: #if defined(PETSC_USE_COMPLEX)
275: if (flg) { /* An hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
276: A->ops->multtranspose = A->ops->mult;
277: A->ops->multtransposeadd = A->ops->multadd;
278: }
279: #endif
280: break;
281: /* These options are handled directly by MatSetOption() */
282: case MAT_STRUCTURALLY_SYMMETRIC:
283: case MAT_SYMMETRY_ETERNAL:
284: case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
285: case MAT_STRUCTURE_ONLY:
286: case MAT_SPD_ETERNAL:
287: /* These options are handled directly by MatSetOption() */
288: break;
289: case MAT_IGNORE_LOWER_TRIANGULAR:
290: a->ignore_ltriangular = flg;
291: break;
292: case MAT_ERROR_LOWER_TRIANGULAR:
293: a->ignore_ltriangular = flg;
294: break;
295: case MAT_GETROW_UPPERTRIANGULAR:
296: a->getrow_utriangular = flg;
297: break;
298: case MAT_SUBMAT_SINGLEIS:
299: break;
300: default:
301: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op);
302: }
303: PetscFunctionReturn(PETSC_SUCCESS);
304: }
306: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
307: {
308: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
310: PetscFunctionBegin;
311: PetscCheck(!A || a->getrow_utriangular, PETSC_COMM_SELF, PETSC_ERR_SUP, "MatGetRow is not supported for SBAIJ matrix format. Getting the upper triangular part of row, run with -mat_getrow_uppertriangular, call MatSetOption(mat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE) or MatGetRowUpperTriangular()");
313: /* Get the upper triangular part of the row */
314: PetscCall(MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a));
315: PetscFunctionReturn(PETSC_SUCCESS);
316: }
318: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
319: {
320: PetscFunctionBegin;
321: if (idx) PetscCall(PetscFree(*idx));
322: if (v) PetscCall(PetscFree(*v));
323: PetscFunctionReturn(PETSC_SUCCESS);
324: }
326: static PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
327: {
328: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
330: PetscFunctionBegin;
331: a->getrow_utriangular = PETSC_TRUE;
332: PetscFunctionReturn(PETSC_SUCCESS);
333: }
335: static PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
336: {
337: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
339: PetscFunctionBegin;
340: a->getrow_utriangular = PETSC_FALSE;
341: PetscFunctionReturn(PETSC_SUCCESS);
342: }
344: static PetscErrorCode MatTranspose_SeqSBAIJ(Mat A, MatReuse reuse, Mat *B)
345: {
346: PetscFunctionBegin;
347: if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B));
348: if (reuse == MAT_INITIAL_MATRIX) {
349: PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B));
350: } else if (reuse == MAT_REUSE_MATRIX) {
351: PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN));
352: }
353: PetscFunctionReturn(PETSC_SUCCESS);
354: }
356: static PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A, PetscViewer viewer)
357: {
358: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
359: PetscInt i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2;
360: PetscViewerFormat format;
361: PetscInt *diag;
362: const char *matname;
364: PetscFunctionBegin;
365: PetscCall(PetscViewerGetFormat(viewer, &format));
366: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
367: PetscCall(PetscViewerASCIIPrintf(viewer, " block size is %" PetscInt_FMT "\n", bs));
368: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
369: Mat aij;
371: if (A->factortype && bs > 1) {
372: PetscCall(PetscPrintf(PETSC_COMM_SELF, "Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n"));
373: PetscFunctionReturn(PETSC_SUCCESS);
374: }
375: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij));
376: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
377: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)aij, matname));
378: PetscCall(MatView_SeqAIJ(aij, viewer));
379: PetscCall(MatDestroy(&aij));
380: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
381: Mat B;
383: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
384: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
385: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
386: PetscCall(MatView_SeqAIJ(B, viewer));
387: PetscCall(MatDestroy(&B));
388: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
389: PetscFunctionReturn(PETSC_SUCCESS);
390: } else {
391: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
392: if (A->factortype) { /* for factored matrix */
393: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "matrix is factored with bs>1. Not implemented yet");
395: diag = a->diag;
396: for (i = 0; i < a->mbs; i++) { /* for row block i */
397: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i));
398: /* diagonal entry */
399: #if defined(PETSC_USE_COMPLEX)
400: if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
401: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]]), (double)PetscImaginaryPart(1.0 / a->a[diag[i]])));
402: } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
403: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]]), -(double)PetscImaginaryPart(1.0 / a->a[diag[i]])));
404: } else {
405: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]])));
406: }
407: #else
408: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)(1.0 / a->a[diag[i]])));
409: #endif
410: /* off-diagonal entries */
411: for (k = a->i[i]; k < a->i[i + 1] - 1; k++) {
412: #if defined(PETSC_USE_COMPLEX)
413: if (PetscImaginaryPart(a->a[k]) > 0.0) {
414: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), (double)PetscImaginaryPart(a->a[k])));
415: } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
416: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), -(double)PetscImaginaryPart(a->a[k])));
417: } else {
418: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k], (double)PetscRealPart(a->a[k])));
419: }
420: #else
421: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[k], (double)a->a[k]));
422: #endif
423: }
424: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
425: }
427: } else { /* for non-factored matrix */
428: for (i = 0; i < a->mbs; i++) { /* for row block i */
429: for (j = 0; j < bs; j++) { /* for row bs*i + j */
430: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j));
431: for (k = a->i[i]; k < a->i[i + 1]; k++) { /* for column block */
432: for (l = 0; l < bs; l++) { /* for column */
433: #if defined(PETSC_USE_COMPLEX)
434: if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) {
435: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), (double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j])));
436: } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) {
437: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), -(double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j])));
438: } else {
439: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j])));
440: }
441: #else
442: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]));
443: #endif
444: }
445: }
446: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
447: }
448: }
449: }
450: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
451: }
452: PetscCall(PetscViewerFlush(viewer));
453: PetscFunctionReturn(PETSC_SUCCESS);
454: }
456: #include <petscdraw.h>
457: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw, void *Aa)
458: {
459: Mat A = (Mat)Aa;
460: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
461: PetscInt row, i, j, k, l, mbs = a->mbs, color, bs = A->rmap->bs, bs2 = a->bs2;
462: PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r;
463: MatScalar *aa;
464: PetscViewer viewer;
466: PetscFunctionBegin;
467: PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer));
468: PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr));
470: /* loop over matrix elements drawing boxes */
472: PetscDrawCollectiveBegin(draw);
473: PetscCall(PetscDrawString(draw, .3 * (xl + xr), .3 * (yl + yr), PETSC_DRAW_BLACK, "symmetric"));
474: /* Blue for negative, Cyan for zero and Red for positive */
475: color = PETSC_DRAW_BLUE;
476: for (i = 0, row = 0; i < mbs; i++, row += bs) {
477: for (j = a->i[i]; j < a->i[i + 1]; j++) {
478: y_l = A->rmap->N - row - 1.0;
479: y_r = y_l + 1.0;
480: x_l = a->j[j] * bs;
481: x_r = x_l + 1.0;
482: aa = a->a + j * bs2;
483: for (k = 0; k < bs; k++) {
484: for (l = 0; l < bs; l++) {
485: if (PetscRealPart(*aa++) >= 0.) continue;
486: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
487: }
488: }
489: }
490: }
491: color = PETSC_DRAW_CYAN;
492: for (i = 0, row = 0; i < mbs; i++, row += bs) {
493: for (j = a->i[i]; j < a->i[i + 1]; j++) {
494: y_l = A->rmap->N - row - 1.0;
495: y_r = y_l + 1.0;
496: x_l = a->j[j] * bs;
497: x_r = x_l + 1.0;
498: aa = a->a + j * bs2;
499: for (k = 0; k < bs; k++) {
500: for (l = 0; l < bs; l++) {
501: if (PetscRealPart(*aa++) != 0.) continue;
502: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
503: }
504: }
505: }
506: }
507: color = PETSC_DRAW_RED;
508: for (i = 0, row = 0; i < mbs; i++, row += bs) {
509: for (j = a->i[i]; j < a->i[i + 1]; j++) {
510: y_l = A->rmap->N - row - 1.0;
511: y_r = y_l + 1.0;
512: x_l = a->j[j] * bs;
513: x_r = x_l + 1.0;
514: aa = a->a + j * bs2;
515: for (k = 0; k < bs; k++) {
516: for (l = 0; l < bs; l++) {
517: if (PetscRealPart(*aa++) <= 0.) continue;
518: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
519: }
520: }
521: }
522: }
523: PetscDrawCollectiveEnd(draw);
524: PetscFunctionReturn(PETSC_SUCCESS);
525: }
527: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A, PetscViewer viewer)
528: {
529: PetscReal xl, yl, xr, yr, w, h;
530: PetscDraw draw;
531: PetscBool isnull;
533: PetscFunctionBegin;
534: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
535: PetscCall(PetscDrawIsNull(draw, &isnull));
536: if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
538: xr = A->rmap->N;
539: yr = A->rmap->N;
540: h = yr / 10.0;
541: w = xr / 10.0;
542: xr += w;
543: yr += h;
544: xl = -w;
545: yl = -h;
546: PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr));
547: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer));
548: PetscCall(PetscDrawZoom(draw, MatView_SeqSBAIJ_Draw_Zoom, A));
549: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL));
550: PetscCall(PetscDrawSave(draw));
551: PetscFunctionReturn(PETSC_SUCCESS);
552: }
554: /* Used for both MPIBAIJ and MPISBAIJ matrices */
555: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary
557: PetscErrorCode MatView_SeqSBAIJ(Mat A, PetscViewer viewer)
558: {
559: PetscBool iascii, isbinary, isdraw;
561: PetscFunctionBegin;
562: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
563: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
564: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
565: if (iascii) {
566: PetscCall(MatView_SeqSBAIJ_ASCII(A, viewer));
567: } else if (isbinary) {
568: PetscCall(MatView_SeqSBAIJ_Binary(A, viewer));
569: } else if (isdraw) {
570: PetscCall(MatView_SeqSBAIJ_Draw(A, viewer));
571: } else {
572: Mat B;
573: const char *matname;
574: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
575: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
576: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
577: PetscCall(MatView(B, viewer));
578: PetscCall(MatDestroy(&B));
579: }
580: PetscFunctionReturn(PETSC_SUCCESS);
581: }
583: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[])
584: {
585: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
586: PetscInt *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j;
587: PetscInt *ai = a->i, *ailen = a->ilen;
588: PetscInt brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2;
589: MatScalar *ap, *aa = a->a;
591: PetscFunctionBegin;
592: for (k = 0; k < m; k++) { /* loop over rows */
593: row = im[k];
594: brow = row / bs;
595: if (row < 0) {
596: v += n;
597: continue;
598: } /* negative row */
599: PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->N - 1);
600: rp = aj + ai[brow];
601: ap = aa + bs2 * ai[brow];
602: nrow = ailen[brow];
603: for (l = 0; l < n; l++) { /* loop over columns */
604: if (in[l] < 0) {
605: v++;
606: continue;
607: } /* negative column */
608: PetscCheck(in[l] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[l], A->cmap->n - 1);
609: col = in[l];
610: bcol = col / bs;
611: cidx = col % bs;
612: ridx = row % bs;
613: high = nrow;
614: low = 0; /* assume unsorted */
615: while (high - low > 5) {
616: t = (low + high) / 2;
617: if (rp[t] > bcol) high = t;
618: else low = t;
619: }
620: for (i = low; i < high; i++) {
621: if (rp[i] > bcol) break;
622: if (rp[i] == bcol) {
623: *v++ = ap[bs2 * i + bs * cidx + ridx];
624: goto finished;
625: }
626: }
627: *v++ = 0.0;
628: finished:;
629: }
630: }
631: PetscFunctionReturn(PETSC_SUCCESS);
632: }
634: static PetscErrorCode MatPermute_SeqSBAIJ(Mat A, IS rowp, IS colp, Mat *B)
635: {
636: Mat C;
637: PetscBool flg = (PetscBool)(rowp == colp);
639: PetscFunctionBegin;
640: PetscCall(MatConvert(A, MATSEQBAIJ, MAT_INITIAL_MATRIX, &C));
641: PetscCall(MatPermute(C, rowp, colp, B));
642: PetscCall(MatDestroy(&C));
643: if (!flg) PetscCall(ISEqual(rowp, colp, &flg));
644: if (flg) PetscCall(MatConvert(*B, MATSEQSBAIJ, MAT_INPLACE_MATRIX, B));
645: PetscFunctionReturn(PETSC_SUCCESS);
646: }
648: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
649: {
650: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
651: PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1;
652: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
653: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval;
654: PetscBool roworiented = a->roworiented;
655: const PetscScalar *value = v;
656: MatScalar *ap, *aa = a->a, *bap;
658: PetscFunctionBegin;
659: if (roworiented) stepval = (n - 1) * bs;
660: else stepval = (m - 1) * bs;
662: for (k = 0; k < m; k++) { /* loop over added rows */
663: row = im[k];
664: if (row < 0) continue;
665: PetscCheck(row < a->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block index row too large %" PetscInt_FMT " max %" PetscInt_FMT, row, a->mbs - 1);
666: rp = aj + ai[row];
667: ap = aa + bs2 * ai[row];
668: rmax = imax[row];
669: nrow = ailen[row];
670: low = 0;
671: high = nrow;
672: for (l = 0; l < n; l++) { /* loop over added columns */
673: if (in[l] < 0) continue;
674: col = in[l];
675: PetscCheck(col < a->nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block index column too large %" PetscInt_FMT " max %" PetscInt_FMT, col, a->nbs - 1);
676: if (col < row) {
677: if (a->ignore_ltriangular) continue; /* ignore lower triangular block */
678: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
679: }
680: if (roworiented) value = v + k * (stepval + bs) * bs + l * bs;
681: else value = v + l * (stepval + bs) * bs + k * bs;
683: if (col <= lastcol) low = 0;
684: else high = nrow;
686: lastcol = col;
687: while (high - low > 7) {
688: t = (low + high) / 2;
689: if (rp[t] > col) high = t;
690: else low = t;
691: }
692: for (i = low; i < high; i++) {
693: if (rp[i] > col) break;
694: if (rp[i] == col) {
695: bap = ap + bs2 * i;
696: if (roworiented) {
697: if (is == ADD_VALUES) {
698: for (ii = 0; ii < bs; ii++, value += stepval) {
699: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
700: }
701: } else {
702: for (ii = 0; ii < bs; ii++, value += stepval) {
703: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
704: }
705: }
706: } else {
707: if (is == ADD_VALUES) {
708: for (ii = 0; ii < bs; ii++, value += stepval) {
709: for (jj = 0; jj < bs; jj++) *bap++ += *value++;
710: }
711: } else {
712: for (ii = 0; ii < bs; ii++, value += stepval) {
713: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
714: }
715: }
716: }
717: goto noinsert2;
718: }
719: }
720: if (nonew == 1) goto noinsert2;
721: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new block index nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
722: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
723: N = nrow++ - 1;
724: high++;
725: /* shift up all the later entries in this row */
726: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
727: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
728: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
729: rp[i] = col;
730: bap = ap + bs2 * i;
731: if (roworiented) {
732: for (ii = 0; ii < bs; ii++, value += stepval) {
733: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
734: }
735: } else {
736: for (ii = 0; ii < bs; ii++, value += stepval) {
737: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
738: }
739: }
740: noinsert2:;
741: low = i;
742: }
743: ailen[row] = nrow;
744: }
745: PetscFunctionReturn(PETSC_SUCCESS);
746: }
748: static PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A, MatAssemblyType mode)
749: {
750: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
751: PetscInt fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax;
752: PetscInt m = A->rmap->N, *ip, N, *ailen = a->ilen;
753: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
754: MatScalar *aa = a->a, *ap;
756: PetscFunctionBegin;
757: if (mode == MAT_FLUSH_ASSEMBLY || (A->was_assembled && A->ass_nonzerostate == A->nonzerostate)) PetscFunctionReturn(PETSC_SUCCESS);
759: if (m) rmax = ailen[0];
760: for (i = 1; i < mbs; i++) {
761: /* move each row back by the amount of empty slots (fshift) before it*/
762: fshift += imax[i - 1] - ailen[i - 1];
763: rmax = PetscMax(rmax, ailen[i]);
764: if (fshift) {
765: ip = aj + ai[i];
766: ap = aa + bs2 * ai[i];
767: N = ailen[i];
768: PetscCall(PetscArraymove(ip - fshift, ip, N));
769: PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2 * N));
770: }
771: ai[i] = ai[i - 1] + ailen[i - 1];
772: }
773: if (mbs) {
774: fshift += imax[mbs - 1] - ailen[mbs - 1];
775: ai[mbs] = ai[mbs - 1] + ailen[mbs - 1];
776: }
777: /* reset ilen and imax for each row */
778: for (i = 0; i < mbs; i++) ailen[i] = imax[i] = ai[i + 1] - ai[i];
779: a->nz = ai[mbs];
781: /* diagonals may have moved, reset it */
782: if (a->diag) PetscCall(PetscArraycpy(a->diag, ai, mbs));
783: PetscCheck(!fshift || a->nounused != -1, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Unused space detected in matrix: %" PetscInt_FMT " X %" PetscInt_FMT " block size %" PetscInt_FMT ", %" PetscInt_FMT " unneeded", m, A->cmap->n, A->rmap->bs, fshift * bs2);
785: PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT ", block size %" PetscInt_FMT "; storage space: %" PetscInt_FMT " unneeded, %" PetscInt_FMT " used\n", m, A->rmap->N, A->rmap->bs, fshift * bs2, a->nz * bs2));
786: PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs));
787: PetscCall(PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax));
789: A->info.mallocs += a->reallocs;
790: a->reallocs = 0;
791: A->info.nz_unneeded = (PetscReal)fshift * bs2;
792: a->idiagvalid = PETSC_FALSE;
793: a->rmax = rmax;
795: if (A->cmap->n < 65536 && A->cmap->bs == 1) {
796: if (a->jshort && a->free_jshort) {
797: /* when matrix data structure is changed, previous jshort must be replaced */
798: PetscCall(PetscFree(a->jshort));
799: }
800: PetscCall(PetscMalloc1(a->i[A->rmap->n], &a->jshort));
801: for (i = 0; i < a->i[A->rmap->n]; i++) a->jshort[i] = a->j[i];
802: A->ops->mult = MatMult_SeqSBAIJ_1_ushort;
803: A->ops->sor = MatSOR_SeqSBAIJ_ushort;
804: a->free_jshort = PETSC_TRUE;
805: }
806: PetscFunctionReturn(PETSC_SUCCESS);
807: }
809: /* Only add/insert a(i,j) with i<=j (blocks).
810: Any a(i,j) with i>j input by user is ignored.
811: */
813: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
814: {
815: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
816: PetscInt *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1;
817: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen, roworiented = a->roworiented;
818: PetscInt *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol;
819: PetscInt ridx, cidx, bs2 = a->bs2;
820: MatScalar *ap, value, *aa = a->a, *bap;
822: PetscFunctionBegin;
823: for (k = 0; k < m; k++) { /* loop over added rows */
824: row = im[k]; /* row number */
825: brow = row / bs; /* block row number */
826: if (row < 0) continue;
827: PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->N - 1);
828: rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
829: ap = aa + bs2 * ai[brow]; /*ptr to beginning of element value of the row block*/
830: rmax = imax[brow]; /* maximum space allocated for this row */
831: nrow = ailen[brow]; /* actual length of this row */
832: low = 0;
833: high = nrow;
834: for (l = 0; l < n; l++) { /* loop over added columns */
835: if (in[l] < 0) continue;
836: PetscCheck(in[l] < A->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[l], A->cmap->N - 1);
837: col = in[l];
838: bcol = col / bs; /* block col number */
840: if (brow > bcol) {
841: if (a->ignore_ltriangular) continue; /* ignore lower triangular values */
842: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
843: }
845: ridx = row % bs;
846: cidx = col % bs; /*row and col index inside the block */
847: if ((brow == bcol && ridx <= cidx) || (brow < bcol)) {
848: /* element value a(k,l) */
849: if (roworiented) value = v[l + k * n];
850: else value = v[k + l * m];
852: /* move pointer bap to a(k,l) quickly and add/insert value */
853: if (col <= lastcol) low = 0;
854: else high = nrow;
856: lastcol = col;
857: while (high - low > 7) {
858: t = (low + high) / 2;
859: if (rp[t] > bcol) high = t;
860: else low = t;
861: }
862: for (i = low; i < high; i++) {
863: if (rp[i] > bcol) break;
864: if (rp[i] == bcol) {
865: bap = ap + bs2 * i + bs * cidx + ridx;
866: if (is == ADD_VALUES) *bap += value;
867: else *bap = value;
868: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
869: if (brow == bcol && ridx < cidx) {
870: bap = ap + bs2 * i + bs * ridx + cidx;
871: if (is == ADD_VALUES) *bap += value;
872: else *bap = value;
873: }
874: goto noinsert1;
875: }
876: }
878: if (nonew == 1) goto noinsert1;
879: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
880: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
882: N = nrow++ - 1;
883: high++;
884: /* shift up all the later entries in this row */
885: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
886: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
887: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
888: rp[i] = bcol;
889: ap[bs2 * i + bs * cidx + ridx] = value;
890: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
891: if (brow == bcol && ridx < cidx) ap[bs2 * i + bs * ridx + cidx] = value;
892: A->nonzerostate++;
893: noinsert1:;
894: low = i;
895: }
896: } /* end of loop over added columns */
897: ailen[brow] = nrow;
898: } /* end of loop over added rows */
899: PetscFunctionReturn(PETSC_SUCCESS);
900: }
902: static PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA, IS row, const MatFactorInfo *info)
903: {
904: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inA->data;
905: Mat outA;
906: PetscBool row_identity;
908: PetscFunctionBegin;
909: PetscCheck(info->levels == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only levels=0 is supported for in-place icc");
910: PetscCall(ISIdentity(row, &row_identity));
911: PetscCheck(row_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported");
912: PetscCheck(inA->rmap->bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix block size %" PetscInt_FMT " is not supported", inA->rmap->bs); /* Need to replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR()! */
914: outA = inA;
915: inA->factortype = MAT_FACTOR_ICC;
916: PetscCall(PetscFree(inA->solvertype));
917: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype));
919: PetscCall(MatMarkDiagonal_SeqSBAIJ(inA));
920: PetscCall(MatSeqSBAIJSetNumericFactorization_inplace(inA, row_identity));
922: PetscCall(PetscObjectReference((PetscObject)row));
923: PetscCall(ISDestroy(&a->row));
924: a->row = row;
925: PetscCall(PetscObjectReference((PetscObject)row));
926: PetscCall(ISDestroy(&a->col));
927: a->col = row;
929: /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
930: if (a->icol) PetscCall(ISInvertPermutation(row, PETSC_DECIDE, &a->icol));
932: if (!a->solve_work) PetscCall(PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work));
934: PetscCall(MatCholeskyFactorNumeric(outA, inA, info));
935: PetscFunctionReturn(PETSC_SUCCESS);
936: }
938: static PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat, PetscInt *indices)
939: {
940: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
941: PetscInt i, nz, n;
943: PetscFunctionBegin;
944: nz = baij->maxnz;
945: n = mat->cmap->n;
946: for (i = 0; i < nz; i++) baij->j[i] = indices[i];
948: baij->nz = nz;
949: for (i = 0; i < n; i++) baij->ilen[i] = baij->imax[i];
951: PetscCall(MatSetOption(mat, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
952: PetscFunctionReturn(PETSC_SUCCESS);
953: }
955: /*@
956: MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
957: in a `MATSEQSBAIJ` matrix.
959: Input Parameters:
960: + mat - the `MATSEQSBAIJ` matrix
961: - indices - the column indices
963: Level: advanced
965: Notes:
966: This can be called if you have precomputed the nonzero structure of the
967: matrix and want to provide it to the matrix object to improve the performance
968: of the `MatSetValues()` operation.
970: You MUST have set the correct numbers of nonzeros per row in the call to
971: `MatCreateSeqSBAIJ()`, and the columns indices MUST be sorted.
973: MUST be called before any calls to `MatSetValues()`
975: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ`
976: @*/
977: PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat, PetscInt *indices)
978: {
979: PetscFunctionBegin;
981: PetscAssertPointer(indices, 2);
982: PetscUseMethod(mat, "MatSeqSBAIJSetColumnIndices_C", (Mat, PetscInt *), (mat, indices));
983: PetscFunctionReturn(PETSC_SUCCESS);
984: }
986: static PetscErrorCode MatCopy_SeqSBAIJ(Mat A, Mat B, MatStructure str)
987: {
988: PetscBool isbaij;
990: PetscFunctionBegin;
991: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, ""));
992: PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name);
993: /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
994: if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
995: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
996: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
998: PetscCheck(a->i[a->mbs] == b->i[b->mbs], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzeros in two matrices are different");
999: PetscCheck(a->mbs == b->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of rows in two matrices are different");
1000: PetscCheck(a->bs2 == b->bs2, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Different block size");
1001: PetscCall(PetscArraycpy(b->a, a->a, a->bs2 * a->i[a->mbs]));
1002: PetscCall(PetscObjectStateIncrease((PetscObject)B));
1003: } else {
1004: PetscCall(MatGetRowUpperTriangular(A));
1005: PetscCall(MatCopy_Basic(A, B, str));
1006: PetscCall(MatRestoreRowUpperTriangular(A));
1007: }
1008: PetscFunctionReturn(PETSC_SUCCESS);
1009: }
1011: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1012: {
1013: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1015: PetscFunctionBegin;
1016: *array = a->a;
1017: PetscFunctionReturn(PETSC_SUCCESS);
1018: }
1020: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1021: {
1022: PetscFunctionBegin;
1023: *array = NULL;
1024: PetscFunctionReturn(PETSC_SUCCESS);
1025: }
1027: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y, Mat X, PetscInt *nnz)
1028: {
1029: PetscInt bs = Y->rmap->bs, mbs = Y->rmap->N / bs;
1030: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data;
1031: Mat_SeqSBAIJ *y = (Mat_SeqSBAIJ *)Y->data;
1033: PetscFunctionBegin;
1034: /* Set the number of nonzeros in the new matrix */
1035: PetscCall(MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz));
1036: PetscFunctionReturn(PETSC_SUCCESS);
1037: }
1039: static PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1040: {
1041: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data, *y = (Mat_SeqSBAIJ *)Y->data;
1042: PetscInt bs = Y->rmap->bs, bs2 = bs * bs;
1043: PetscBLASInt one = 1;
1045: PetscFunctionBegin;
1046: if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
1047: PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
1048: if (e) {
1049: PetscCall(PetscArraycmp(x->i, y->i, x->mbs + 1, &e));
1050: if (e) {
1051: PetscCall(PetscArraycmp(x->j, y->j, x->i[x->mbs], &e));
1052: if (e) str = SAME_NONZERO_PATTERN;
1053: }
1054: }
1055: if (!e) PetscCheck(str != SAME_NONZERO_PATTERN, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "MatStructure is not SAME_NONZERO_PATTERN");
1056: }
1057: if (str == SAME_NONZERO_PATTERN) {
1058: PetscScalar alpha = a;
1059: PetscBLASInt bnz;
1060: PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
1061: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1062: PetscCall(PetscObjectStateIncrease((PetscObject)Y));
1063: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1064: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
1065: PetscCall(MatAXPY_Basic(Y, a, X, str));
1066: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
1067: } else {
1068: Mat B;
1069: PetscInt *nnz;
1070: PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size");
1071: PetscCall(MatGetRowUpperTriangular(X));
1072: PetscCall(MatGetRowUpperTriangular(Y));
1073: PetscCall(PetscMalloc1(Y->rmap->N, &nnz));
1074: PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1075: PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1076: PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1077: PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1078: PetscCall(MatSetType(B, ((PetscObject)Y)->type_name));
1079: PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(Y, X, nnz));
1080: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1082: PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
1084: PetscCall(MatHeaderMerge(Y, &B));
1085: PetscCall(PetscFree(nnz));
1086: PetscCall(MatRestoreRowUpperTriangular(X));
1087: PetscCall(MatRestoreRowUpperTriangular(Y));
1088: }
1089: PetscFunctionReturn(PETSC_SUCCESS);
1090: }
1092: static PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A, PetscBool *flg)
1093: {
1094: PetscFunctionBegin;
1095: *flg = PETSC_TRUE;
1096: PetscFunctionReturn(PETSC_SUCCESS);
1097: }
1099: static PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
1100: {
1101: #if defined(PETSC_USE_COMPLEX)
1102: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1103: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1104: MatScalar *aa = a->a;
1106: PetscFunctionBegin;
1107: for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]);
1108: #else
1109: PetscFunctionBegin;
1110: #endif
1111: PetscFunctionReturn(PETSC_SUCCESS);
1112: }
1114: static PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1115: {
1116: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1117: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1118: MatScalar *aa = a->a;
1120: PetscFunctionBegin;
1121: for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]);
1122: PetscFunctionReturn(PETSC_SUCCESS);
1123: }
1125: static PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1126: {
1127: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1128: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1129: MatScalar *aa = a->a;
1131: PetscFunctionBegin;
1132: for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1133: PetscFunctionReturn(PETSC_SUCCESS);
1134: }
1136: static PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b)
1137: {
1138: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)A->data;
1139: PetscInt i, j, k, count;
1140: PetscInt bs = A->rmap->bs, bs2 = baij->bs2, row, col;
1141: PetscScalar zero = 0.0;
1142: MatScalar *aa;
1143: const PetscScalar *xx;
1144: PetscScalar *bb;
1145: PetscBool *zeroed, vecs = PETSC_FALSE;
1147: PetscFunctionBegin;
1148: /* fix right-hand side if needed */
1149: if (x && b) {
1150: PetscCall(VecGetArrayRead(x, &xx));
1151: PetscCall(VecGetArray(b, &bb));
1152: vecs = PETSC_TRUE;
1153: }
1155: /* zero the columns */
1156: PetscCall(PetscCalloc1(A->rmap->n, &zeroed));
1157: for (i = 0; i < is_n; i++) {
1158: PetscCheck(is_idx[i] >= 0 && is_idx[i] < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "row %" PetscInt_FMT " out of range", is_idx[i]);
1159: zeroed[is_idx[i]] = PETSC_TRUE;
1160: }
1161: if (vecs) {
1162: for (i = 0; i < A->rmap->N; i++) {
1163: row = i / bs;
1164: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1165: for (k = 0; k < bs; k++) {
1166: col = bs * baij->j[j] + k;
1167: if (col <= i) continue;
1168: aa = ((MatScalar *)baij->a) + j * bs2 + (i % bs) + bs * k;
1169: if (!zeroed[i] && zeroed[col]) bb[i] -= aa[0] * xx[col];
1170: if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0] * xx[i];
1171: }
1172: }
1173: }
1174: for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]];
1175: }
1177: for (i = 0; i < A->rmap->N; i++) {
1178: if (!zeroed[i]) {
1179: row = i / bs;
1180: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1181: for (k = 0; k < bs; k++) {
1182: col = bs * baij->j[j] + k;
1183: if (zeroed[col]) {
1184: aa = ((MatScalar *)baij->a) + j * bs2 + (i % bs) + bs * k;
1185: aa[0] = 0.0;
1186: }
1187: }
1188: }
1189: }
1190: }
1191: PetscCall(PetscFree(zeroed));
1192: if (vecs) {
1193: PetscCall(VecRestoreArrayRead(x, &xx));
1194: PetscCall(VecRestoreArray(b, &bb));
1195: }
1197: /* zero the rows */
1198: for (i = 0; i < is_n; i++) {
1199: row = is_idx[i];
1200: count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1201: aa = ((MatScalar *)baij->a) + baij->i[row / bs] * bs2 + (row % bs);
1202: for (k = 0; k < count; k++) {
1203: aa[0] = zero;
1204: aa += bs;
1205: }
1206: if (diag != 0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES);
1207: }
1208: PetscCall(MatAssemblyEnd_SeqSBAIJ(A, MAT_FINAL_ASSEMBLY));
1209: PetscFunctionReturn(PETSC_SUCCESS);
1210: }
1212: static PetscErrorCode MatShift_SeqSBAIJ(Mat Y, PetscScalar a)
1213: {
1214: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)Y->data;
1216: PetscFunctionBegin;
1217: if (!Y->preallocated || !aij->nz) PetscCall(MatSeqSBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL));
1218: PetscCall(MatShift_Basic(Y, a));
1219: PetscFunctionReturn(PETSC_SUCCESS);
1220: }
1222: PetscErrorCode MatEliminateZeros_SeqSBAIJ(Mat A, PetscBool keep)
1223: {
1224: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1225: PetscInt fshift = 0, fshift_prev = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax, j, k;
1226: PetscInt m = A->rmap->N, *ailen = a->ilen;
1227: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
1228: MatScalar *aa = a->a, *ap;
1229: PetscBool zero;
1231: PetscFunctionBegin;
1232: PetscCheck(A->assembled, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Cannot eliminate zeros for unassembled matrix");
1233: if (m) rmax = ailen[0];
1234: for (i = 1; i <= mbs; i++) {
1235: for (k = ai[i - 1]; k < ai[i]; k++) {
1236: zero = PETSC_TRUE;
1237: ap = aa + bs2 * k;
1238: for (j = 0; j < bs2 && zero; j++) {
1239: if (ap[j] != 0.0) zero = PETSC_FALSE;
1240: }
1241: if (zero && (aj[k] != i - 1 || !keep)) fshift++;
1242: else {
1243: if (zero && aj[k] == i - 1) PetscCall(PetscInfo(A, "Keep the diagonal block at row %" PetscInt_FMT "\n", i - 1));
1244: aj[k - fshift] = aj[k];
1245: PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2));
1246: }
1247: }
1248: ai[i - 1] -= fshift_prev;
1249: fshift_prev = fshift;
1250: ailen[i - 1] = imax[i - 1] = ai[i] - fshift - ai[i - 1];
1251: a->nonzerorowcnt += ((ai[i] - fshift - ai[i - 1]) > 0);
1252: rmax = PetscMax(rmax, ailen[i - 1]);
1253: }
1254: if (fshift) {
1255: if (mbs) {
1256: ai[mbs] -= fshift;
1257: a->nz = ai[mbs];
1258: }
1259: PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT "; zeros eliminated: %" PetscInt_FMT "; nonzeros left: %" PetscInt_FMT "\n", m, A->cmap->n, fshift, a->nz));
1260: A->nonzerostate++;
1261: A->info.nz_unneeded += (PetscReal)fshift;
1262: a->rmax = rmax;
1263: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
1264: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
1265: }
1266: PetscFunctionReturn(PETSC_SUCCESS);
1267: }
1269: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1270: MatGetRow_SeqSBAIJ,
1271: MatRestoreRow_SeqSBAIJ,
1272: MatMult_SeqSBAIJ_N,
1273: /* 4*/ MatMultAdd_SeqSBAIJ_N,
1274: MatMult_SeqSBAIJ_N, /* transpose versions are same as non-transpose versions */
1275: MatMultAdd_SeqSBAIJ_N,
1276: NULL,
1277: NULL,
1278: NULL,
1279: /* 10*/ NULL,
1280: NULL,
1281: MatCholeskyFactor_SeqSBAIJ,
1282: MatSOR_SeqSBAIJ,
1283: MatTranspose_SeqSBAIJ,
1284: /* 15*/ MatGetInfo_SeqSBAIJ,
1285: MatEqual_SeqSBAIJ,
1286: MatGetDiagonal_SeqSBAIJ,
1287: MatDiagonalScale_SeqSBAIJ,
1288: MatNorm_SeqSBAIJ,
1289: /* 20*/ NULL,
1290: MatAssemblyEnd_SeqSBAIJ,
1291: MatSetOption_SeqSBAIJ,
1292: MatZeroEntries_SeqSBAIJ,
1293: /* 24*/ NULL,
1294: NULL,
1295: NULL,
1296: NULL,
1297: NULL,
1298: /* 29*/ MatSetUp_Seq_Hash,
1299: NULL,
1300: NULL,
1301: NULL,
1302: NULL,
1303: /* 34*/ MatDuplicate_SeqSBAIJ,
1304: NULL,
1305: NULL,
1306: NULL,
1307: MatICCFactor_SeqSBAIJ,
1308: /* 39*/ MatAXPY_SeqSBAIJ,
1309: MatCreateSubMatrices_SeqSBAIJ,
1310: MatIncreaseOverlap_SeqSBAIJ,
1311: MatGetValues_SeqSBAIJ,
1312: MatCopy_SeqSBAIJ,
1313: /* 44*/ NULL,
1314: MatScale_SeqSBAIJ,
1315: MatShift_SeqSBAIJ,
1316: NULL,
1317: MatZeroRowsColumns_SeqSBAIJ,
1318: /* 49*/ NULL,
1319: MatGetRowIJ_SeqSBAIJ,
1320: MatRestoreRowIJ_SeqSBAIJ,
1321: NULL,
1322: NULL,
1323: /* 54*/ NULL,
1324: NULL,
1325: NULL,
1326: MatPermute_SeqSBAIJ,
1327: MatSetValuesBlocked_SeqSBAIJ,
1328: /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
1329: NULL,
1330: NULL,
1331: NULL,
1332: NULL,
1333: /* 64*/ NULL,
1334: NULL,
1335: NULL,
1336: NULL,
1337: NULL,
1338: /* 69*/ MatGetRowMaxAbs_SeqSBAIJ,
1339: NULL,
1340: MatConvert_MPISBAIJ_Basic,
1341: NULL,
1342: NULL,
1343: /* 74*/ NULL,
1344: NULL,
1345: NULL,
1346: NULL,
1347: NULL,
1348: /* 79*/ NULL,
1349: NULL,
1350: NULL,
1351: MatGetInertia_SeqSBAIJ,
1352: MatLoad_SeqSBAIJ,
1353: /* 84*/ NULL,
1354: NULL,
1355: MatIsStructurallySymmetric_SeqSBAIJ,
1356: NULL,
1357: NULL,
1358: /* 89*/ NULL,
1359: NULL,
1360: NULL,
1361: NULL,
1362: NULL,
1363: /* 94*/ NULL,
1364: NULL,
1365: NULL,
1366: NULL,
1367: NULL,
1368: /* 99*/ NULL,
1369: NULL,
1370: NULL,
1371: MatConjugate_SeqSBAIJ,
1372: NULL,
1373: /*104*/ NULL,
1374: MatRealPart_SeqSBAIJ,
1375: MatImaginaryPart_SeqSBAIJ,
1376: MatGetRowUpperTriangular_SeqSBAIJ,
1377: MatRestoreRowUpperTriangular_SeqSBAIJ,
1378: /*109*/ NULL,
1379: NULL,
1380: NULL,
1381: NULL,
1382: MatMissingDiagonal_SeqSBAIJ,
1383: /*114*/ NULL,
1384: NULL,
1385: NULL,
1386: NULL,
1387: NULL,
1388: /*119*/ NULL,
1389: NULL,
1390: NULL,
1391: NULL,
1392: NULL,
1393: /*124*/ NULL,
1394: NULL,
1395: NULL,
1396: NULL,
1397: NULL,
1398: /*129*/ NULL,
1399: NULL,
1400: NULL,
1401: NULL,
1402: NULL,
1403: /*134*/ NULL,
1404: NULL,
1405: NULL,
1406: NULL,
1407: NULL,
1408: /*139*/ MatSetBlockSizes_Default,
1409: NULL,
1410: NULL,
1411: NULL,
1412: NULL,
1413: /*144*/ MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
1414: NULL,
1415: NULL,
1416: NULL,
1417: NULL,
1418: NULL,
1419: /*150*/ NULL,
1420: MatEliminateZeros_SeqSBAIJ,
1421: NULL};
1423: static PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat)
1424: {
1425: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1426: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1428: PetscFunctionBegin;
1429: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1431: /* allocate space for values if not already there */
1432: if (!aij->saved_values) PetscCall(PetscMalloc1(nz + 1, &aij->saved_values));
1434: /* copy values over */
1435: PetscCall(PetscArraycpy(aij->saved_values, aij->a, nz));
1436: PetscFunctionReturn(PETSC_SUCCESS);
1437: }
1439: static PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat)
1440: {
1441: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1442: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1444: PetscFunctionBegin;
1445: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1446: PetscCheck(aij->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first");
1448: /* copy values over */
1449: PetscCall(PetscArraycpy(aij->a, aij->saved_values, nz));
1450: PetscFunctionReturn(PETSC_SUCCESS);
1451: }
1453: static PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
1454: {
1455: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1456: PetscInt i, mbs, nbs, bs2;
1457: PetscBool skipallocation = PETSC_FALSE, flg = PETSC_FALSE, realalloc = PETSC_FALSE;
1459: PetscFunctionBegin;
1460: if (B->hash_active) {
1461: PetscInt bs;
1462: B->ops[0] = b->cops;
1463: PetscCall(PetscHMapIJVDestroy(&b->ht));
1464: PetscCall(MatGetBlockSize(B, &bs));
1465: if (bs > 1) PetscCall(PetscHSetIJDestroy(&b->bht));
1466: PetscCall(PetscFree(b->dnz));
1467: PetscCall(PetscFree(b->bdnz));
1468: B->hash_active = PETSC_FALSE;
1469: }
1470: if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
1472: PetscCall(MatSetBlockSize(B, PetscAbs(bs)));
1473: PetscCall(PetscLayoutSetUp(B->rmap));
1474: PetscCall(PetscLayoutSetUp(B->cmap));
1475: PetscCheck(B->rmap->N <= B->cmap->N, PETSC_COMM_SELF, PETSC_ERR_SUP, "SEQSBAIJ matrix cannot have more rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->N, B->cmap->N);
1476: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1478: B->preallocated = PETSC_TRUE;
1480: mbs = B->rmap->N / bs;
1481: nbs = B->cmap->n / bs;
1482: bs2 = bs * bs;
1484: PetscCheck(mbs * bs == B->rmap->N && nbs * bs == B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Number rows, cols must be divisible by blocksize");
1486: if (nz == MAT_SKIP_ALLOCATION) {
1487: skipallocation = PETSC_TRUE;
1488: nz = 0;
1489: }
1491: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1492: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nz cannot be less than 0: value %" PetscInt_FMT, nz);
1493: if (nnz) {
1494: for (i = 0; i < mbs; i++) {
1495: PetscCheck(nnz[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be less than 0: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, nnz[i]);
1496: PetscCheck(nnz[i] <= nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be greater than block row length: local row %" PetscInt_FMT " value %" PetscInt_FMT " block rowlength %" PetscInt_FMT, i, nnz[i], nbs);
1497: }
1498: }
1500: B->ops->mult = MatMult_SeqSBAIJ_N;
1501: B->ops->multadd = MatMultAdd_SeqSBAIJ_N;
1502: B->ops->multtranspose = MatMult_SeqSBAIJ_N;
1503: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;
1505: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1506: if (!flg) {
1507: switch (bs) {
1508: case 1:
1509: B->ops->mult = MatMult_SeqSBAIJ_1;
1510: B->ops->multadd = MatMultAdd_SeqSBAIJ_1;
1511: B->ops->multtranspose = MatMult_SeqSBAIJ_1;
1512: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1513: break;
1514: case 2:
1515: B->ops->mult = MatMult_SeqSBAIJ_2;
1516: B->ops->multadd = MatMultAdd_SeqSBAIJ_2;
1517: B->ops->multtranspose = MatMult_SeqSBAIJ_2;
1518: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1519: break;
1520: case 3:
1521: B->ops->mult = MatMult_SeqSBAIJ_3;
1522: B->ops->multadd = MatMultAdd_SeqSBAIJ_3;
1523: B->ops->multtranspose = MatMult_SeqSBAIJ_3;
1524: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1525: break;
1526: case 4:
1527: B->ops->mult = MatMult_SeqSBAIJ_4;
1528: B->ops->multadd = MatMultAdd_SeqSBAIJ_4;
1529: B->ops->multtranspose = MatMult_SeqSBAIJ_4;
1530: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1531: break;
1532: case 5:
1533: B->ops->mult = MatMult_SeqSBAIJ_5;
1534: B->ops->multadd = MatMultAdd_SeqSBAIJ_5;
1535: B->ops->multtranspose = MatMult_SeqSBAIJ_5;
1536: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1537: break;
1538: case 6:
1539: B->ops->mult = MatMult_SeqSBAIJ_6;
1540: B->ops->multadd = MatMultAdd_SeqSBAIJ_6;
1541: B->ops->multtranspose = MatMult_SeqSBAIJ_6;
1542: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1543: break;
1544: case 7:
1545: B->ops->mult = MatMult_SeqSBAIJ_7;
1546: B->ops->multadd = MatMultAdd_SeqSBAIJ_7;
1547: B->ops->multtranspose = MatMult_SeqSBAIJ_7;
1548: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1549: break;
1550: }
1551: }
1553: b->mbs = mbs;
1554: b->nbs = nbs;
1555: if (!skipallocation) {
1556: if (!b->imax) {
1557: PetscCall(PetscMalloc2(mbs, &b->imax, mbs, &b->ilen));
1559: b->free_imax_ilen = PETSC_TRUE;
1560: }
1561: if (!nnz) {
1562: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1563: else if (nz <= 0) nz = 1;
1564: nz = PetscMin(nbs, nz);
1565: for (i = 0; i < mbs; i++) b->imax[i] = nz;
1566: PetscCall(PetscIntMultError(nz, mbs, &nz));
1567: } else {
1568: PetscInt64 nz64 = 0;
1569: for (i = 0; i < mbs; i++) {
1570: b->imax[i] = nnz[i];
1571: nz64 += nnz[i];
1572: }
1573: PetscCall(PetscIntCast(nz64, &nz));
1574: }
1575: /* b->ilen will count nonzeros in each block row so far. */
1576: for (i = 0; i < mbs; i++) b->ilen[i] = 0;
1577: /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */
1579: /* allocate the matrix space */
1580: PetscCall(MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i));
1581: PetscCall(PetscMalloc3(bs2 * nz, &b->a, nz, &b->j, B->rmap->N + 1, &b->i));
1582: PetscCall(PetscArrayzero(b->a, nz * bs2));
1583: PetscCall(PetscArrayzero(b->j, nz));
1585: b->singlemalloc = PETSC_TRUE;
1587: /* pointer to beginning of each row */
1588: b->i[0] = 0;
1589: for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1];
1591: b->free_a = PETSC_TRUE;
1592: b->free_ij = PETSC_TRUE;
1593: } else {
1594: b->free_a = PETSC_FALSE;
1595: b->free_ij = PETSC_FALSE;
1596: }
1598: b->bs2 = bs2;
1599: b->nz = 0;
1600: b->maxnz = nz;
1601: b->inew = NULL;
1602: b->jnew = NULL;
1603: b->anew = NULL;
1604: b->a2anew = NULL;
1605: b->permute = PETSC_FALSE;
1607: B->was_assembled = PETSC_FALSE;
1608: B->assembled = PETSC_FALSE;
1609: if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE));
1610: PetscFunctionReturn(PETSC_SUCCESS);
1611: }
1613: static PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
1614: {
1615: PetscInt i, j, m, nz, anz, nz_max = 0, *nnz;
1616: PetscScalar *values = NULL;
1617: PetscBool roworiented = ((Mat_SeqSBAIJ *)B->data)->roworiented;
1619: PetscFunctionBegin;
1620: PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs);
1621: PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
1622: PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
1623: PetscCall(PetscLayoutSetUp(B->rmap));
1624: PetscCall(PetscLayoutSetUp(B->cmap));
1625: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1626: m = B->rmap->n / bs;
1628: PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
1629: PetscCall(PetscMalloc1(m + 1, &nnz));
1630: for (i = 0; i < m; i++) {
1631: nz = ii[i + 1] - ii[i];
1632: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
1633: anz = 0;
1634: for (j = 0; j < nz; j++) {
1635: /* count only values on the diagonal or above */
1636: if (jj[ii[i] + j] >= i) {
1637: anz = nz - j;
1638: break;
1639: }
1640: }
1641: nz_max = PetscMax(nz_max, anz);
1642: nnz[i] = anz;
1643: }
1644: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1645: PetscCall(PetscFree(nnz));
1647: values = (PetscScalar *)V;
1648: if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
1649: for (i = 0; i < m; i++) {
1650: PetscInt ncols = ii[i + 1] - ii[i];
1651: const PetscInt *icols = jj + ii[i];
1652: if (!roworiented || bs == 1) {
1653: const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
1654: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES));
1655: } else {
1656: for (j = 0; j < ncols; j++) {
1657: const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
1658: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES));
1659: }
1660: }
1661: }
1662: if (!V) PetscCall(PetscFree(values));
1663: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
1664: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
1665: PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1666: PetscFunctionReturn(PETSC_SUCCESS);
1667: }
1669: /*
1670: This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1671: */
1672: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B, PetscBool natural)
1673: {
1674: PetscBool flg = PETSC_FALSE;
1675: PetscInt bs = B->rmap->bs;
1677: PetscFunctionBegin;
1678: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1679: if (flg) bs = 8;
1681: if (!natural) {
1682: switch (bs) {
1683: case 1:
1684: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
1685: break;
1686: case 2:
1687: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1688: break;
1689: case 3:
1690: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1691: break;
1692: case 4:
1693: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1694: break;
1695: case 5:
1696: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1697: break;
1698: case 6:
1699: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1700: break;
1701: case 7:
1702: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1703: break;
1704: default:
1705: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1706: break;
1707: }
1708: } else {
1709: switch (bs) {
1710: case 1:
1711: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
1712: break;
1713: case 2:
1714: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1715: break;
1716: case 3:
1717: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1718: break;
1719: case 4:
1720: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1721: break;
1722: case 5:
1723: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1724: break;
1725: case 6:
1726: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1727: break;
1728: case 7:
1729: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1730: break;
1731: default:
1732: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1733: break;
1734: }
1735: }
1736: PetscFunctionReturn(PETSC_SUCCESS);
1737: }
1739: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
1740: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
1741: static PetscErrorCode MatFactorGetSolverType_petsc(Mat A, MatSolverType *type)
1742: {
1743: PetscFunctionBegin;
1744: *type = MATSOLVERPETSC;
1745: PetscFunctionReturn(PETSC_SUCCESS);
1746: }
1748: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A, MatFactorType ftype, Mat *B)
1749: {
1750: PetscInt n = A->rmap->n;
1752: PetscFunctionBegin;
1753: #if defined(PETSC_USE_COMPLEX)
1754: if ((ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) && A->hermitian == PETSC_BOOL3_TRUE && A->symmetric != PETSC_BOOL3_TRUE) {
1755: PetscCall(PetscInfo(A, "Hermitian MAT_FACTOR_CHOLESKY or MAT_FACTOR_ICC are not supported. Use MAT_FACTOR_LU instead.\n"));
1756: *B = NULL;
1757: PetscFunctionReturn(PETSC_SUCCESS);
1758: }
1759: #endif
1761: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B));
1762: PetscCall(MatSetSizes(*B, n, n, n, n));
1763: if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1764: PetscCall(MatSetType(*B, MATSEQSBAIJ));
1765: PetscCall(MatSeqSBAIJSetPreallocation(*B, A->rmap->bs, MAT_SKIP_ALLOCATION, NULL));
1767: (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1768: (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;
1769: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]));
1770: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]));
1771: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
1773: (*B)->factortype = ftype;
1774: (*B)->canuseordering = PETSC_TRUE;
1775: PetscCall(PetscFree((*B)->solvertype));
1776: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &(*B)->solvertype));
1777: PetscCall(PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_petsc));
1778: PetscFunctionReturn(PETSC_SUCCESS);
1779: }
1781: /*@C
1782: MatSeqSBAIJGetArray - gives access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored
1784: Not Collective
1786: Input Parameter:
1787: . A - a `MATSEQSBAIJ` matrix
1789: Output Parameter:
1790: . array - pointer to the data
1792: Level: intermediate
1794: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1795: @*/
1796: PetscErrorCode MatSeqSBAIJGetArray(Mat A, PetscScalar **array)
1797: {
1798: PetscFunctionBegin;
1799: PetscUseMethod(A, "MatSeqSBAIJGetArray_C", (Mat, PetscScalar **), (A, array));
1800: PetscFunctionReturn(PETSC_SUCCESS);
1801: }
1803: /*@C
1804: MatSeqSBAIJRestoreArray - returns access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored obtained by `MatSeqSBAIJGetArray()`
1806: Not Collective
1808: Input Parameters:
1809: + A - a `MATSEQSBAIJ` matrix
1810: - array - pointer to the data
1812: Level: intermediate
1814: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1815: @*/
1816: PetscErrorCode MatSeqSBAIJRestoreArray(Mat A, PetscScalar **array)
1817: {
1818: PetscFunctionBegin;
1819: PetscUseMethod(A, "MatSeqSBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array));
1820: PetscFunctionReturn(PETSC_SUCCESS);
1821: }
1823: /*MC
1824: MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
1825: based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored.
1827: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1828: can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`).
1830: Options Database Key:
1831: . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to `MatSetFromOptions()`
1833: Level: beginner
1835: Notes:
1836: By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
1837: stored and it is assumed they symmetric to the upper triangular). If you call `MatSetOption`(`Mat`,`MAT_IGNORE_LOWER_TRIANGULAR`,`PETSC_FALSE`) or use
1838: the options database `-mat_ignore_lower_triangular` false it will generate an error if you try to set a value in the lower triangular portion.
1840: The number of rows in the matrix must be less than or equal to the number of columns
1842: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ()`, `MatType`, `MATMPISBAIJ`
1843: M*/
1844: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
1845: {
1846: Mat_SeqSBAIJ *b;
1847: PetscMPIInt size;
1848: PetscBool no_unroll = PETSC_FALSE, no_inode = PETSC_FALSE;
1850: PetscFunctionBegin;
1851: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
1852: PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1");
1854: PetscCall(PetscNew(&b));
1855: B->data = (void *)b;
1856: B->ops[0] = MatOps_Values;
1858: B->ops->destroy = MatDestroy_SeqSBAIJ;
1859: B->ops->view = MatView_SeqSBAIJ;
1860: b->row = NULL;
1861: b->icol = NULL;
1862: b->reallocs = 0;
1863: b->saved_values = NULL;
1864: b->inode.limit = 5;
1865: b->inode.max_limit = 5;
1867: b->roworiented = PETSC_TRUE;
1868: b->nonew = 0;
1869: b->diag = NULL;
1870: b->solve_work = NULL;
1871: b->mult_work = NULL;
1872: B->spptr = NULL;
1873: B->info.nz_unneeded = (PetscReal)b->maxnz * b->bs2;
1874: b->keepnonzeropattern = PETSC_FALSE;
1876: b->inew = NULL;
1877: b->jnew = NULL;
1878: b->anew = NULL;
1879: b->a2anew = NULL;
1880: b->permute = PETSC_FALSE;
1882: b->ignore_ltriangular = PETSC_TRUE;
1884: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_ignore_lower_triangular", &b->ignore_ltriangular, NULL));
1886: b->getrow_utriangular = PETSC_FALSE;
1888: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_getrow_uppertriangular", &b->getrow_utriangular, NULL));
1890: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJGetArray_C", MatSeqSBAIJGetArray_SeqSBAIJ));
1891: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJRestoreArray_C", MatSeqSBAIJRestoreArray_SeqSBAIJ));
1892: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSBAIJ));
1893: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSBAIJ));
1894: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetColumnIndices_C", MatSeqSBAIJSetColumnIndices_SeqSBAIJ));
1895: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqaij_C", MatConvert_SeqSBAIJ_SeqAIJ));
1896: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqbaij_C", MatConvert_SeqSBAIJ_SeqBAIJ));
1897: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocation_C", MatSeqSBAIJSetPreallocation_SeqSBAIJ));
1898: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocationCSR_C", MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ));
1899: #if defined(PETSC_HAVE_ELEMENTAL)
1900: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_elemental_C", MatConvert_SeqSBAIJ_Elemental));
1901: #endif
1902: #if defined(PETSC_HAVE_SCALAPACK)
1903: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK));
1904: #endif
1906: B->symmetry_eternal = PETSC_TRUE;
1907: B->structural_symmetry_eternal = PETSC_TRUE;
1908: B->symmetric = PETSC_BOOL3_TRUE;
1909: B->structurally_symmetric = PETSC_BOOL3_TRUE;
1910: #if defined(PETSC_USE_COMPLEX)
1911: B->hermitian = PETSC_BOOL3_FALSE;
1912: #else
1913: B->hermitian = PETSC_BOOL3_TRUE;
1914: #endif
1916: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQSBAIJ));
1918: PetscOptionsBegin(PetscObjectComm((PetscObject)B), ((PetscObject)B)->prefix, "Options for SEQSBAIJ matrix", "Mat");
1919: PetscCall(PetscOptionsBool("-mat_no_unroll", "Do not optimize for inodes (slower)", NULL, no_unroll, &no_unroll, NULL));
1920: if (no_unroll) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_unroll\n"));
1921: PetscCall(PetscOptionsBool("-mat_no_inode", "Do not optimize for inodes (slower)", NULL, no_inode, &no_inode, NULL));
1922: if (no_inode) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_inode\n"));
1923: PetscCall(PetscOptionsInt("-mat_inode_limit", "Do not use inodes larger then this value", NULL, b->inode.limit, &b->inode.limit, NULL));
1924: PetscOptionsEnd();
1925: b->inode.use = (PetscBool)(!(no_unroll || no_inode));
1926: if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
1927: PetscFunctionReturn(PETSC_SUCCESS);
1928: }
1930: /*@C
1931: MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
1932: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
1933: user should preallocate the matrix storage by setting the parameter `nz`
1934: (or the array `nnz`).
1936: Collective
1938: Input Parameters:
1939: + B - the symmetric matrix
1940: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
1941: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
1942: . nz - number of block nonzeros per block row (same for all rows)
1943: - nnz - array containing the number of block nonzeros in the upper triangular plus
1944: diagonal portion of each block (possibly different for each block row) or `NULL`
1946: Options Database Keys:
1947: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower)
1948: - -mat_block_size - size of the blocks to use (only works if a negative bs is passed in
1950: Level: intermediate
1952: Notes:
1953: Specify the preallocated storage with either `nz` or `nnz` (not both).
1954: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
1955: allocation. See [Sparse Matrices](sec_matsparse) for details.
1957: You can call `MatGetInfo()` to get information on how effective the preallocation was;
1958: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1959: You can also run with the option `-info` and look for messages with the string
1960: malloc in them to see if additional memory allocation was needed.
1962: If the `nnz` parameter is given then the `nz` parameter is ignored
1964: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
1965: @*/
1966: PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
1967: {
1968: PetscFunctionBegin;
1972: PetscTryMethod(B, "MatSeqSBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz));
1973: PetscFunctionReturn(PETSC_SUCCESS);
1974: }
1976: /*@C
1977: MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATSEQSBAIJ` format using the given nonzero structure and (optional) numerical values
1979: Input Parameters:
1980: + B - the matrix
1981: . bs - size of block, the blocks are ALWAYS square.
1982: . i - the indices into `j` for the start of each local row (indices start with zero)
1983: . j - the column indices for each local row (indices start with zero) these must be sorted for each row
1984: - v - optional values in the matrix, use `NULL` if not provided
1986: Level: advanced
1988: Notes:
1989: The `i`,`j`,`v` values are COPIED with this routine; to avoid the copy use `MatCreateSeqSBAIJWithArrays()`
1991: The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`. For example, C programs
1992: may want to use the default `MAT_ROW_ORIENTED` = `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
1993: over rows within a block and the last index is over columns within a block row. Fortran programs will likely set
1994: `MAT_ROW_ORIENTED` = `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
1995: block column and the second index is over columns within a block.
1997: Any entries provided that lie below the diagonal are ignored
1999: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2000: and usually the numerical values as well
2002: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValuesBlocked()`, `MatSeqSBAIJSetPreallocation()`
2003: @*/
2004: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2005: {
2006: PetscFunctionBegin;
2010: PetscTryMethod(B, "MatSeqSBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2011: PetscFunctionReturn(PETSC_SUCCESS);
2012: }
2014: /*@C
2015: MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in (block
2016: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
2017: user should preallocate the matrix storage by setting the parameter `nz`
2018: (or the array `nnz`).
2020: Collective
2022: Input Parameters:
2023: + comm - MPI communicator, set to `PETSC_COMM_SELF`
2024: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2025: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2026: . m - number of rows
2027: . n - number of columns
2028: . nz - number of block nonzeros per block row (same for all rows)
2029: - nnz - array containing the number of block nonzeros in the upper triangular plus
2030: diagonal portion of each block (possibly different for each block row) or `NULL`
2032: Output Parameter:
2033: . A - the symmetric matrix
2035: Options Database Keys:
2036: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower)
2037: - -mat_block_size - size of the blocks to use
2039: Level: intermediate
2041: Notes:
2042: It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
2043: MatXXXXSetPreallocation() paradigm instead of this routine directly.
2044: [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]
2046: The number of rows and columns must be divisible by blocksize.
2047: This matrix type does not support complex Hermitian operation.
2049: Specify the preallocated storage with either `nz` or `nnz` (not both).
2050: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
2051: allocation. See [Sparse Matrices](sec_matsparse) for details.
2053: If the `nnz` parameter is given then the `nz` parameter is ignored
2055: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2056: @*/
2057: PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
2058: {
2059: PetscFunctionBegin;
2060: PetscCall(MatCreate(comm, A));
2061: PetscCall(MatSetSizes(*A, m, n, m, n));
2062: PetscCall(MatSetType(*A, MATSEQSBAIJ));
2063: PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz));
2064: PetscFunctionReturn(PETSC_SUCCESS);
2065: }
2067: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B)
2068: {
2069: Mat C;
2070: Mat_SeqSBAIJ *c, *a = (Mat_SeqSBAIJ *)A->data;
2071: PetscInt i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2;
2073: PetscFunctionBegin;
2074: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Cannot duplicate unassembled matrix");
2075: PetscCheck(a->i[mbs] == nz, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupt matrix");
2077: *B = NULL;
2078: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &C));
2079: PetscCall(MatSetSizes(C, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n));
2080: PetscCall(MatSetBlockSizesFromMats(C, A, A));
2081: PetscCall(MatSetType(C, MATSEQSBAIJ));
2082: c = (Mat_SeqSBAIJ *)C->data;
2084: C->preallocated = PETSC_TRUE;
2085: C->factortype = A->factortype;
2086: c->row = NULL;
2087: c->icol = NULL;
2088: c->saved_values = NULL;
2089: c->keepnonzeropattern = a->keepnonzeropattern;
2090: C->assembled = PETSC_TRUE;
2092: PetscCall(PetscLayoutReference(A->rmap, &C->rmap));
2093: PetscCall(PetscLayoutReference(A->cmap, &C->cmap));
2094: c->bs2 = a->bs2;
2095: c->mbs = a->mbs;
2096: c->nbs = a->nbs;
2098: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2099: c->imax = a->imax;
2100: c->ilen = a->ilen;
2101: c->free_imax_ilen = PETSC_FALSE;
2102: } else {
2103: PetscCall(PetscMalloc2((mbs + 1), &c->imax, (mbs + 1), &c->ilen));
2104: for (i = 0; i < mbs; i++) {
2105: c->imax[i] = a->imax[i];
2106: c->ilen[i] = a->ilen[i];
2107: }
2108: c->free_imax_ilen = PETSC_TRUE;
2109: }
2111: /* allocate the matrix space */
2112: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2113: PetscCall(PetscMalloc1(bs2 * nz, &c->a));
2114: c->i = a->i;
2115: c->j = a->j;
2116: c->singlemalloc = PETSC_FALSE;
2117: c->free_a = PETSC_TRUE;
2118: c->free_ij = PETSC_FALSE;
2119: c->parent = A;
2120: PetscCall(PetscObjectReference((PetscObject)A));
2121: PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2122: PetscCall(MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2123: } else {
2124: PetscCall(PetscMalloc3(bs2 * nz, &c->a, nz, &c->j, mbs + 1, &c->i));
2125: PetscCall(PetscArraycpy(c->i, a->i, mbs + 1));
2126: c->singlemalloc = PETSC_TRUE;
2127: c->free_a = PETSC_TRUE;
2128: c->free_ij = PETSC_TRUE;
2129: }
2130: if (mbs > 0) {
2131: if (cpvalues != MAT_SHARE_NONZERO_PATTERN) PetscCall(PetscArraycpy(c->j, a->j, nz));
2132: if (cpvalues == MAT_COPY_VALUES) {
2133: PetscCall(PetscArraycpy(c->a, a->a, bs2 * nz));
2134: } else {
2135: PetscCall(PetscArrayzero(c->a, bs2 * nz));
2136: }
2137: if (a->jshort) {
2138: /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
2139: /* if the parent matrix is reassembled, this child matrix will never notice */
2140: PetscCall(PetscMalloc1(nz, &c->jshort));
2141: PetscCall(PetscArraycpy(c->jshort, a->jshort, nz));
2143: c->free_jshort = PETSC_TRUE;
2144: }
2145: }
2147: c->roworiented = a->roworiented;
2148: c->nonew = a->nonew;
2150: if (a->diag) {
2151: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2152: c->diag = a->diag;
2153: c->free_diag = PETSC_FALSE;
2154: } else {
2155: PetscCall(PetscMalloc1(mbs, &c->diag));
2156: for (i = 0; i < mbs; i++) c->diag[i] = a->diag[i];
2157: c->free_diag = PETSC_TRUE;
2158: }
2159: }
2160: c->nz = a->nz;
2161: c->maxnz = a->nz; /* Since we allocate exactly the right amount */
2162: c->solve_work = NULL;
2163: c->mult_work = NULL;
2165: *B = C;
2166: PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist));
2167: PetscFunctionReturn(PETSC_SUCCESS);
2168: }
2170: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
2171: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary
2173: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat, PetscViewer viewer)
2174: {
2175: PetscBool isbinary;
2177: PetscFunctionBegin;
2178: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
2179: PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name);
2180: PetscCall(MatLoad_SeqSBAIJ_Binary(mat, viewer));
2181: PetscFunctionReturn(PETSC_SUCCESS);
2182: }
2184: /*@
2185: MatCreateSeqSBAIJWithArrays - Creates an sequential `MATSEQSBAIJ` matrix using matrix elements
2186: (upper triangular entries in CSR format) provided by the user.
2188: Collective
2190: Input Parameters:
2191: + comm - must be an MPI communicator of size 1
2192: . bs - size of block
2193: . m - number of rows
2194: . n - number of columns
2195: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
2196: . j - column indices
2197: - a - matrix values
2199: Output Parameter:
2200: . mat - the matrix
2202: Level: advanced
2204: Notes:
2205: The `i`, `j`, and `a` arrays are not copied by this routine, the user must free these arrays
2206: once the matrix is destroyed
2208: You cannot set new nonzero locations into this matrix, that will generate an error.
2210: The `i` and `j` indices are 0 based
2212: When block size is greater than 1 the matrix values must be stored using the `MATSBAIJ` storage format. For block size of 1
2213: it is the regular CSR format excluding the lower triangular elements.
2215: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSBAIJ()`, `MatCreateSeqSBAIJ()`
2216: @*/
2217: PetscErrorCode MatCreateSeqSBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat)
2218: {
2219: PetscInt ii;
2220: Mat_SeqSBAIJ *sbaij;
2222: PetscFunctionBegin;
2223: PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "block size %" PetscInt_FMT " > 1 is not supported yet", bs);
2224: PetscCheck(m == 0 || i[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");
2226: PetscCall(MatCreate(comm, mat));
2227: PetscCall(MatSetSizes(*mat, m, n, m, n));
2228: PetscCall(MatSetType(*mat, MATSEQSBAIJ));
2229: PetscCall(MatSeqSBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL));
2230: sbaij = (Mat_SeqSBAIJ *)(*mat)->data;
2231: PetscCall(PetscMalloc2(m, &sbaij->imax, m, &sbaij->ilen));
2233: sbaij->i = i;
2234: sbaij->j = j;
2235: sbaij->a = a;
2237: sbaij->singlemalloc = PETSC_FALSE;
2238: sbaij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2239: sbaij->free_a = PETSC_FALSE;
2240: sbaij->free_ij = PETSC_FALSE;
2241: sbaij->free_imax_ilen = PETSC_TRUE;
2243: for (ii = 0; ii < m; ii++) {
2244: sbaij->ilen[ii] = sbaij->imax[ii] = i[ii + 1] - i[ii];
2245: PetscCheck(i[ii + 1] >= i[ii], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row length in i (row indices) row = %" PetscInt_FMT " length = %" PetscInt_FMT, ii, i[ii + 1] - i[ii]);
2246: }
2247: if (PetscDefined(USE_DEBUG)) {
2248: for (ii = 0; ii < sbaij->i[m]; ii++) {
2249: PetscCheck(j[ii] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative column index at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2250: PetscCheck(j[ii] < n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column index too large at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2251: }
2252: }
2254: PetscCall(MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY));
2255: PetscCall(MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY));
2256: PetscFunctionReturn(PETSC_SUCCESS);
2257: }
2259: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2260: {
2261: PetscFunctionBegin;
2262: PetscCall(MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm, inmat, n, scall, outmat));
2263: PetscFunctionReturn(PETSC_SUCCESS);
2264: }