Actual source code: sbaij.c
2: /*
3: Defines the basic matrix operations for the SBAIJ (compressed row)
4: matrix storage format.
5: */
6: #include <../src/mat/impls/baij/seq/baij.h>
7: #include <../src/mat/impls/sbaij/seq/sbaij.h>
8: #include <petscblaslapack.h>
10: #include <../src/mat/impls/sbaij/seq/relax.h>
11: #define USESHORT
12: #include <../src/mat/impls/sbaij/seq/relax.h>
14: #if defined(PETSC_HAVE_ELEMENTAL)
15: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
16: #endif
17: #if defined(PETSC_HAVE_SCALAPACK)
18: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
19: #endif
20: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat, MatType, MatReuse, Mat *);
22: /*
23: Checks for missing diagonals
24: */
25: PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A, PetscBool *missing, PetscInt *dd)
26: {
27: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
28: PetscInt *diag, *ii = a->i, i;
30: MatMarkDiagonal_SeqSBAIJ(A);
31: *missing = PETSC_FALSE;
32: if (A->rmap->n > 0 && !ii) {
33: *missing = PETSC_TRUE;
34: if (dd) *dd = 0;
35: PetscInfo(A, "Matrix has no entries therefore is missing diagonal\n");
36: } else {
37: diag = a->diag;
38: for (i = 0; i < a->mbs; i++) {
39: if (diag[i] >= ii[i + 1]) {
40: *missing = PETSC_TRUE;
41: if (dd) *dd = i;
42: break;
43: }
44: }
45: }
46: return 0;
47: }
49: PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A)
50: {
51: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
52: PetscInt i, j;
54: if (!a->diag) {
55: PetscMalloc1(a->mbs, &a->diag);
56: a->free_diag = PETSC_TRUE;
57: }
58: for (i = 0; i < a->mbs; i++) {
59: a->diag[i] = a->i[i + 1];
60: for (j = a->i[i]; j < a->i[i + 1]; j++) {
61: if (a->j[j] == i) {
62: a->diag[i] = j;
63: break;
64: }
65: }
66: }
67: return 0;
68: }
70: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *inia[], const PetscInt *inja[], PetscBool *done)
71: {
72: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
73: PetscInt i, j, n = a->mbs, nz = a->i[n], *tia, *tja, bs = A->rmap->bs, k, l, cnt;
74: PetscInt **ia = (PetscInt **)inia, **ja = (PetscInt **)inja;
76: *nn = n;
77: if (!ia) return 0;
78: if (symmetric) {
79: MatToSymmetricIJ_SeqAIJ(n, a->i, a->j, PETSC_FALSE, 0, 0, &tia, &tja);
80: nz = tia[n];
81: } else {
82: tia = a->i;
83: tja = a->j;
84: }
86: if (!blockcompressed && bs > 1) {
87: (*nn) *= bs;
88: /* malloc & create the natural set of indices */
89: PetscMalloc1((n + 1) * bs, ia);
90: if (n) {
91: (*ia)[0] = oshift;
92: for (j = 1; j < bs; j++) (*ia)[j] = (tia[1] - tia[0]) * bs + (*ia)[j - 1];
93: }
95: for (i = 1; i < n; i++) {
96: (*ia)[i * bs] = (tia[i] - tia[i - 1]) * bs + (*ia)[i * bs - 1];
97: for (j = 1; j < bs; j++) (*ia)[i * bs + j] = (tia[i + 1] - tia[i]) * bs + (*ia)[i * bs + j - 1];
98: }
99: if (n) (*ia)[n * bs] = (tia[n] - tia[n - 1]) * bs + (*ia)[n * bs - 1];
101: if (inja) {
102: PetscMalloc1(nz * bs * bs, ja);
103: cnt = 0;
104: for (i = 0; i < n; i++) {
105: for (j = 0; j < bs; j++) {
106: for (k = tia[i]; k < tia[i + 1]; k++) {
107: for (l = 0; l < bs; l++) (*ja)[cnt++] = bs * tja[k] + l;
108: }
109: }
110: }
111: }
113: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
114: PetscFree(tia);
115: PetscFree(tja);
116: }
117: } else if (oshift == 1) {
118: if (symmetric) {
119: nz = tia[A->rmap->n / bs];
120: /* add 1 to i and j indices */
121: for (i = 0; i < A->rmap->n / bs + 1; i++) tia[i] = tia[i] + 1;
122: *ia = tia;
123: if (ja) {
124: for (i = 0; i < nz; i++) tja[i] = tja[i] + 1;
125: *ja = tja;
126: }
127: } else {
128: nz = a->i[A->rmap->n / bs];
129: /* malloc space and add 1 to i and j indices */
130: PetscMalloc1(A->rmap->n / bs + 1, ia);
131: for (i = 0; i < A->rmap->n / bs + 1; i++) (*ia)[i] = a->i[i] + 1;
132: if (ja) {
133: PetscMalloc1(nz, ja);
134: for (i = 0; i < nz; i++) (*ja)[i] = a->j[i] + 1;
135: }
136: }
137: } else {
138: *ia = tia;
139: if (ja) *ja = tja;
140: }
141: return 0;
142: }
144: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done)
145: {
146: if (!ia) return 0;
147: if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
148: PetscFree(*ia);
149: if (ja) PetscFree(*ja);
150: }
151: return 0;
152: }
154: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
155: {
156: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
158: #if defined(PETSC_USE_LOG)
159: PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, a->nz);
160: #endif
161: MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i);
162: if (a->free_diag) PetscFree(a->diag);
163: ISDestroy(&a->row);
164: ISDestroy(&a->col);
165: ISDestroy(&a->icol);
166: PetscFree(a->idiag);
167: PetscFree(a->inode.size);
168: if (a->free_imax_ilen) PetscFree2(a->imax, a->ilen);
169: PetscFree(a->solve_work);
170: PetscFree(a->sor_work);
171: PetscFree(a->solves_work);
172: PetscFree(a->mult_work);
173: PetscFree(a->saved_values);
174: if (a->free_jshort) PetscFree(a->jshort);
175: PetscFree(a->inew);
176: MatDestroy(&a->parent);
177: PetscFree(A->data);
179: PetscObjectChangeTypeName((PetscObject)A, NULL);
180: PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJGetArray_C", NULL);
181: PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJRestoreArray_C", NULL);
182: PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL);
183: PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL);
184: PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetColumnIndices_C", NULL);
185: PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqaij_C", NULL);
186: PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqbaij_C", NULL);
187: PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocation_C", NULL);
188: PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocationCSR_C", NULL);
189: #if defined(PETSC_HAVE_ELEMENTAL)
190: PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_elemental_C", NULL);
191: #endif
192: #if defined(PETSC_HAVE_SCALAPACK)
193: PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_scalapack_C", NULL);
194: #endif
195: PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL);
196: return 0;
197: }
199: PetscErrorCode MatSetOption_SeqSBAIJ(Mat A, MatOption op, PetscBool flg)
200: {
201: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
202: #if defined(PETSC_USE_COMPLEX)
203: PetscInt bs;
204: #endif
206: #if defined(PETSC_USE_COMPLEX)
207: MatGetBlockSize(A, &bs);
208: #endif
209: switch (op) {
210: case MAT_ROW_ORIENTED:
211: a->roworiented = flg;
212: break;
213: case MAT_KEEP_NONZERO_PATTERN:
214: a->keepnonzeropattern = flg;
215: break;
216: case MAT_NEW_NONZERO_LOCATIONS:
217: a->nonew = (flg ? 0 : 1);
218: break;
219: case MAT_NEW_NONZERO_LOCATION_ERR:
220: a->nonew = (flg ? -1 : 0);
221: break;
222: case MAT_NEW_NONZERO_ALLOCATION_ERR:
223: a->nonew = (flg ? -2 : 0);
224: break;
225: case MAT_UNUSED_NONZERO_LOCATION_ERR:
226: a->nounused = (flg ? -1 : 0);
227: break;
228: case MAT_FORCE_DIAGONAL_ENTRIES:
229: case MAT_IGNORE_OFF_PROC_ENTRIES:
230: case MAT_USE_HASH_TABLE:
231: case MAT_SORTED_FULL:
232: PetscInfo(A, "Option %s ignored\n", MatOptions[op]);
233: break;
234: case MAT_HERMITIAN:
235: #if defined(PETSC_USE_COMPLEX)
236: if (flg) { /* disable transpose ops */
238: A->ops->multtranspose = NULL;
239: A->ops->multtransposeadd = NULL;
240: A->symmetric = PETSC_BOOL3_FALSE;
241: }
242: #endif
243: break;
244: case MAT_SYMMETRIC:
245: case MAT_SPD:
246: #if defined(PETSC_USE_COMPLEX)
247: if (flg) { /* An hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
248: A->ops->multtranspose = A->ops->mult;
249: A->ops->multtransposeadd = A->ops->multadd;
250: }
251: #endif
252: break;
253: /* These options are handled directly by MatSetOption() */
254: case MAT_STRUCTURALLY_SYMMETRIC:
255: case MAT_SYMMETRY_ETERNAL:
256: case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
257: case MAT_STRUCTURE_ONLY:
258: case MAT_SPD_ETERNAL:
259: /* These options are handled directly by MatSetOption() */
260: break;
261: case MAT_IGNORE_LOWER_TRIANGULAR:
262: a->ignore_ltriangular = flg;
263: break;
264: case MAT_ERROR_LOWER_TRIANGULAR:
265: a->ignore_ltriangular = flg;
266: break;
267: case MAT_GETROW_UPPERTRIANGULAR:
268: a->getrow_utriangular = flg;
269: break;
270: case MAT_SUBMAT_SINGLEIS:
271: break;
272: default:
273: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op);
274: }
275: return 0;
276: }
278: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
279: {
280: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
284: /* Get the upper triangular part of the row */
285: MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a);
286: return 0;
287: }
289: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
290: {
291: if (nz) *nz = 0;
292: if (idx) PetscFree(*idx);
293: if (v) PetscFree(*v);
294: return 0;
295: }
297: PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
298: {
299: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
301: a->getrow_utriangular = PETSC_TRUE;
302: return 0;
303: }
305: PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
306: {
307: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
309: a->getrow_utriangular = PETSC_FALSE;
310: return 0;
311: }
313: PetscErrorCode MatTranspose_SeqSBAIJ(Mat A, MatReuse reuse, Mat *B)
314: {
315: if (reuse == MAT_REUSE_MATRIX) MatTransposeCheckNonzeroState_Private(A, *B);
316: if (reuse == MAT_INITIAL_MATRIX) {
317: MatDuplicate(A, MAT_COPY_VALUES, B);
318: } else if (reuse == MAT_REUSE_MATRIX) {
319: MatCopy(A, *B, SAME_NONZERO_PATTERN);
320: }
321: return 0;
322: }
324: PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A, PetscViewer viewer)
325: {
326: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
327: PetscInt i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2;
328: PetscViewerFormat format;
329: PetscInt *diag;
331: PetscViewerGetFormat(viewer, &format);
332: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
333: PetscViewerASCIIPrintf(viewer, " block size is %" PetscInt_FMT "\n", bs);
334: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
335: Mat aij;
336: const char *matname;
338: if (A->factortype && bs > 1) {
339: PetscPrintf(PETSC_COMM_SELF, "Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n");
340: return 0;
341: }
342: MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij);
343: PetscObjectGetName((PetscObject)A, &matname);
344: PetscObjectSetName((PetscObject)aij, matname);
345: MatView(aij, viewer);
346: MatDestroy(&aij);
347: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
348: PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
349: for (i = 0; i < a->mbs; i++) {
350: for (j = 0; j < bs; j++) {
351: PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j);
352: for (k = a->i[i]; k < a->i[i + 1]; k++) {
353: for (l = 0; l < bs; l++) {
354: #if defined(PETSC_USE_COMPLEX)
355: if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0 && PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) {
356: 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]));
357: } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0 && PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) {
358: 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]));
359: } else if (PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) {
360: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]));
361: }
362: #else
363: if (a->a[bs2 * k + l * bs + j] != 0.0) PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]);
364: #endif
365: }
366: }
367: PetscViewerASCIIPrintf(viewer, "\n");
368: }
369: }
370: PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
371: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
372: return 0;
373: } else {
374: PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
375: if (A->factortype) { /* for factored matrix */
378: diag = a->diag;
379: for (i = 0; i < a->mbs; i++) { /* for row block i */
380: PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i);
381: /* diagonal entry */
382: #if defined(PETSC_USE_COMPLEX)
383: if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
384: 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]]));
385: } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
386: 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]]));
387: } else {
388: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]]));
389: }
390: #else
391: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)(1.0 / a->a[diag[i]]));
392: #endif
393: /* off-diagonal entries */
394: for (k = a->i[i]; k < a->i[i + 1] - 1; k++) {
395: #if defined(PETSC_USE_COMPLEX)
396: if (PetscImaginaryPart(a->a[k]) > 0.0) {
397: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), (double)PetscImaginaryPart(a->a[k]));
398: } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
399: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), -(double)PetscImaginaryPart(a->a[k]));
400: } else {
401: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k], (double)PetscRealPart(a->a[k]));
402: }
403: #else
404: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[k], (double)a->a[k]);
405: #endif
406: }
407: PetscViewerASCIIPrintf(viewer, "\n");
408: }
410: } else { /* for non-factored matrix */
411: for (i = 0; i < a->mbs; i++) { /* for row block i */
412: for (j = 0; j < bs; j++) { /* for row bs*i + j */
413: PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j);
414: for (k = a->i[i]; k < a->i[i + 1]; k++) { /* for column block */
415: for (l = 0; l < bs; l++) { /* for column */
416: #if defined(PETSC_USE_COMPLEX)
417: if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) {
418: 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]));
419: } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) {
420: 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]));
421: } else {
422: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]));
423: }
424: #else
425: PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]);
426: #endif
427: }
428: }
429: PetscViewerASCIIPrintf(viewer, "\n");
430: }
431: }
432: }
433: PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
434: }
435: PetscViewerFlush(viewer);
436: return 0;
437: }
439: #include <petscdraw.h>
440: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw, void *Aa)
441: {
442: Mat A = (Mat)Aa;
443: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
444: PetscInt row, i, j, k, l, mbs = a->mbs, color, bs = A->rmap->bs, bs2 = a->bs2;
445: PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r;
446: MatScalar *aa;
447: PetscViewer viewer;
449: PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer);
450: PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr);
452: /* loop over matrix elements drawing boxes */
454: PetscDrawCollectiveBegin(draw);
455: PetscDrawString(draw, .3 * (xl + xr), .3 * (yl + yr), PETSC_DRAW_BLACK, "symmetric");
456: /* Blue for negative, Cyan for zero and Red for positive */
457: color = PETSC_DRAW_BLUE;
458: for (i = 0, row = 0; i < mbs; i++, row += bs) {
459: for (j = a->i[i]; j < a->i[i + 1]; j++) {
460: y_l = A->rmap->N - row - 1.0;
461: y_r = y_l + 1.0;
462: x_l = a->j[j] * bs;
463: x_r = x_l + 1.0;
464: aa = a->a + j * bs2;
465: for (k = 0; k < bs; k++) {
466: for (l = 0; l < bs; l++) {
467: if (PetscRealPart(*aa++) >= 0.) continue;
468: PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color);
469: }
470: }
471: }
472: }
473: color = PETSC_DRAW_CYAN;
474: for (i = 0, row = 0; i < mbs; i++, row += bs) {
475: for (j = a->i[i]; j < a->i[i + 1]; j++) {
476: y_l = A->rmap->N - row - 1.0;
477: y_r = y_l + 1.0;
478: x_l = a->j[j] * bs;
479: x_r = x_l + 1.0;
480: aa = a->a + j * bs2;
481: for (k = 0; k < bs; k++) {
482: for (l = 0; l < bs; l++) {
483: if (PetscRealPart(*aa++) != 0.) continue;
484: PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color);
485: }
486: }
487: }
488: }
489: color = PETSC_DRAW_RED;
490: for (i = 0, row = 0; i < mbs; i++, row += bs) {
491: for (j = a->i[i]; j < a->i[i + 1]; j++) {
492: y_l = A->rmap->N - row - 1.0;
493: y_r = y_l + 1.0;
494: x_l = a->j[j] * bs;
495: x_r = x_l + 1.0;
496: aa = a->a + j * bs2;
497: for (k = 0; k < bs; k++) {
498: for (l = 0; l < bs; l++) {
499: if (PetscRealPart(*aa++) <= 0.) continue;
500: PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color);
501: }
502: }
503: }
504: }
505: PetscDrawCollectiveEnd(draw);
506: return 0;
507: }
509: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A, PetscViewer viewer)
510: {
511: PetscReal xl, yl, xr, yr, w, h;
512: PetscDraw draw;
513: PetscBool isnull;
515: PetscViewerDrawGetDraw(viewer, 0, &draw);
516: PetscDrawIsNull(draw, &isnull);
517: if (isnull) return 0;
519: xr = A->rmap->N;
520: yr = A->rmap->N;
521: h = yr / 10.0;
522: w = xr / 10.0;
523: xr += w;
524: yr += h;
525: xl = -w;
526: yl = -h;
527: PetscDrawSetCoordinates(draw, xl, yl, xr, yr);
528: PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer);
529: PetscDrawZoom(draw, MatView_SeqSBAIJ_Draw_Zoom, A);
530: PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL);
531: PetscDrawSave(draw);
532: return 0;
533: }
535: /* Used for both MPIBAIJ and MPISBAIJ matrices */
536: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary
538: PetscErrorCode MatView_SeqSBAIJ(Mat A, PetscViewer viewer)
539: {
540: PetscBool iascii, isbinary, isdraw;
542: PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii);
543: PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary);
544: PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw);
545: if (iascii) {
546: MatView_SeqSBAIJ_ASCII(A, viewer);
547: } else if (isbinary) {
548: MatView_SeqSBAIJ_Binary(A, viewer);
549: } else if (isdraw) {
550: MatView_SeqSBAIJ_Draw(A, viewer);
551: } else {
552: Mat B;
553: const char *matname;
554: MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B);
555: PetscObjectGetName((PetscObject)A, &matname);
556: PetscObjectSetName((PetscObject)B, matname);
557: MatView(B, viewer);
558: MatDestroy(&B);
559: }
560: return 0;
561: }
563: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[])
564: {
565: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
566: PetscInt *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j;
567: PetscInt *ai = a->i, *ailen = a->ilen;
568: PetscInt brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2;
569: MatScalar *ap, *aa = a->a;
571: for (k = 0; k < m; k++) { /* loop over rows */
572: row = im[k];
573: brow = row / bs;
574: if (row < 0) {
575: v += n;
576: continue;
577: } /* negative row */
579: rp = aj + ai[brow];
580: ap = aa + bs2 * ai[brow];
581: nrow = ailen[brow];
582: for (l = 0; l < n; l++) { /* loop over columns */
583: if (in[l] < 0) {
584: v++;
585: continue;
586: } /* negative column */
588: col = in[l];
589: bcol = col / bs;
590: cidx = col % bs;
591: ridx = row % bs;
592: high = nrow;
593: low = 0; /* assume unsorted */
594: while (high - low > 5) {
595: t = (low + high) / 2;
596: if (rp[t] > bcol) high = t;
597: else low = t;
598: }
599: for (i = low; i < high; i++) {
600: if (rp[i] > bcol) break;
601: if (rp[i] == bcol) {
602: *v++ = ap[bs2 * i + bs * cidx + ridx];
603: goto finished;
604: }
605: }
606: *v++ = 0.0;
607: finished:;
608: }
609: }
610: return 0;
611: }
613: PetscErrorCode MatPermute_SeqSBAIJ(Mat A, IS rowp, IS colp, Mat *B)
614: {
615: Mat C;
617: MatConvert(A, MATSEQBAIJ, MAT_INITIAL_MATRIX, &C);
618: MatPermute(C, rowp, colp, B);
619: MatDestroy(&C);
620: if (rowp == colp) MatConvert(*B, MATSEQSBAIJ, MAT_INPLACE_MATRIX, B);
621: return 0;
622: }
624: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
625: {
626: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
627: PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1;
628: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
629: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval;
630: PetscBool roworiented = a->roworiented;
631: const PetscScalar *value = v;
632: MatScalar *ap, *aa = a->a, *bap;
634: if (roworiented) stepval = (n - 1) * bs;
635: else stepval = (m - 1) * bs;
637: for (k = 0; k < m; k++) { /* loop over added rows */
638: row = im[k];
639: if (row < 0) continue;
641: rp = aj + ai[row];
642: ap = aa + bs2 * ai[row];
643: rmax = imax[row];
644: nrow = ailen[row];
645: low = 0;
646: high = nrow;
647: for (l = 0; l < n; l++) { /* loop over added columns */
648: if (in[l] < 0) continue;
649: col = in[l];
651: if (col < row) {
652: if (a->ignore_ltriangular) continue; /* ignore lower triangular block */
653: 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)");
654: }
655: if (roworiented) value = v + k * (stepval + bs) * bs + l * bs;
656: else value = v + l * (stepval + bs) * bs + k * bs;
658: if (col <= lastcol) low = 0;
659: else high = nrow;
661: lastcol = col;
662: while (high - low > 7) {
663: t = (low + high) / 2;
664: if (rp[t] > col) high = t;
665: else low = t;
666: }
667: for (i = low; i < high; i++) {
668: if (rp[i] > col) break;
669: if (rp[i] == col) {
670: bap = ap + bs2 * i;
671: if (roworiented) {
672: if (is == ADD_VALUES) {
673: for (ii = 0; ii < bs; ii++, value += stepval) {
674: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
675: }
676: } else {
677: for (ii = 0; ii < bs; ii++, value += stepval) {
678: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
679: }
680: }
681: } else {
682: if (is == ADD_VALUES) {
683: for (ii = 0; ii < bs; ii++, value += stepval) {
684: for (jj = 0; jj < bs; jj++) *bap++ += *value++;
685: }
686: } else {
687: for (ii = 0; ii < bs; ii++, value += stepval) {
688: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
689: }
690: }
691: }
692: goto noinsert2;
693: }
694: }
695: if (nonew == 1) goto noinsert2;
697: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
698: N = nrow++ - 1;
699: high++;
700: /* shift up all the later entries in this row */
701: PetscArraymove(rp + i + 1, rp + i, N - i + 1);
702: PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1));
703: PetscArrayzero(ap + bs2 * i, bs2);
704: rp[i] = col;
705: bap = ap + bs2 * i;
706: if (roworiented) {
707: for (ii = 0; ii < bs; ii++, value += stepval) {
708: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
709: }
710: } else {
711: for (ii = 0; ii < bs; ii++, value += stepval) {
712: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
713: }
714: }
715: noinsert2:;
716: low = i;
717: }
718: ailen[row] = nrow;
719: }
720: return 0;
721: }
723: /*
724: This is not yet used
725: */
726: PetscErrorCode MatAssemblyEnd_SeqSBAIJ_SeqAIJ_Inode(Mat A)
727: {
728: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
729: const PetscInt *ai = a->i, *aj = a->j, *cols;
730: PetscInt i = 0, j, blk_size, m = A->rmap->n, node_count = 0, nzx, nzy, *ns, row, nz, cnt, cnt2, *counts;
731: PetscBool flag;
733: PetscMalloc1(m, &ns);
734: while (i < m) {
735: nzx = ai[i + 1] - ai[i]; /* Number of nonzeros */
736: /* Limits the number of elements in a node to 'a->inode.limit' */
737: for (j = i + 1, blk_size = 1; j < m && blk_size < a->inode.limit; ++j, ++blk_size) {
738: nzy = ai[j + 1] - ai[j];
739: if (nzy != (nzx - j + i)) break;
740: PetscArraycmp(aj + ai[i] + j - i, aj + ai[j], nzy, &flag);
741: if (!flag) break;
742: }
743: ns[node_count++] = blk_size;
745: i = j;
746: }
747: if (!a->inode.size && m && node_count > .9 * m) {
748: PetscFree(ns);
749: PetscInfo(A, "Found %" PetscInt_FMT " nodes out of %" PetscInt_FMT " rows. Not using Inode routines\n", node_count, m);
750: } else {
751: a->inode.node_count = node_count;
753: PetscMalloc1(node_count, &a->inode.size);
754: PetscArraycpy(a->inode.size, ns, node_count);
755: PetscFree(ns);
756: PetscInfo(A, "Found %" PetscInt_FMT " nodes of %" PetscInt_FMT ". Limit used: %" PetscInt_FMT ". Using Inode routines\n", node_count, m, a->inode.limit);
758: /* count collections of adjacent columns in each inode */
759: row = 0;
760: cnt = 0;
761: for (i = 0; i < node_count; i++) {
762: cols = aj + ai[row] + a->inode.size[i];
763: nz = ai[row + 1] - ai[row] - a->inode.size[i];
764: for (j = 1; j < nz; j++) {
765: if (cols[j] != cols[j - 1] + 1) cnt++;
766: }
767: cnt++;
768: row += a->inode.size[i];
769: }
770: PetscMalloc1(2 * cnt, &counts);
771: cnt = 0;
772: row = 0;
773: for (i = 0; i < node_count; i++) {
774: cols = aj + ai[row] + a->inode.size[i];
775: counts[2 * cnt] = cols[0];
776: nz = ai[row + 1] - ai[row] - a->inode.size[i];
777: cnt2 = 1;
778: for (j = 1; j < nz; j++) {
779: if (cols[j] != cols[j - 1] + 1) {
780: counts[2 * (cnt++) + 1] = cnt2;
781: counts[2 * cnt] = cols[j];
782: cnt2 = 1;
783: } else cnt2++;
784: }
785: counts[2 * (cnt++) + 1] = cnt2;
786: row += a->inode.size[i];
787: }
788: PetscIntView(2 * cnt, counts, NULL);
789: }
790: return 0;
791: }
793: PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A, MatAssemblyType mode)
794: {
795: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
796: PetscInt fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax;
797: PetscInt m = A->rmap->N, *ip, N, *ailen = a->ilen;
798: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
799: MatScalar *aa = a->a, *ap;
801: if (mode == MAT_FLUSH_ASSEMBLY) return 0;
803: if (m) rmax = ailen[0];
804: for (i = 1; i < mbs; i++) {
805: /* move each row back by the amount of empty slots (fshift) before it*/
806: fshift += imax[i - 1] - ailen[i - 1];
807: rmax = PetscMax(rmax, ailen[i]);
808: if (fshift) {
809: ip = aj + ai[i];
810: ap = aa + bs2 * ai[i];
811: N = ailen[i];
812: PetscArraymove(ip - fshift, ip, N);
813: PetscArraymove(ap - bs2 * fshift, ap, bs2 * N);
814: }
815: ai[i] = ai[i - 1] + ailen[i - 1];
816: }
817: if (mbs) {
818: fshift += imax[mbs - 1] - ailen[mbs - 1];
819: ai[mbs] = ai[mbs - 1] + ailen[mbs - 1];
820: }
821: /* reset ilen and imax for each row */
822: for (i = 0; i < mbs; i++) ailen[i] = imax[i] = ai[i + 1] - ai[i];
823: a->nz = ai[mbs];
825: /* diagonals may have moved, reset it */
826: if (a->diag) PetscArraycpy(a->diag, ai, mbs);
829: 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);
830: PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs);
831: PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax);
833: A->info.mallocs += a->reallocs;
834: a->reallocs = 0;
835: A->info.nz_unneeded = (PetscReal)fshift * bs2;
836: a->idiagvalid = PETSC_FALSE;
837: a->rmax = rmax;
839: if (A->cmap->n < 65536 && A->cmap->bs == 1) {
840: if (a->jshort && a->free_jshort) {
841: /* when matrix data structure is changed, previous jshort must be replaced */
842: PetscFree(a->jshort);
843: }
844: PetscMalloc1(a->i[A->rmap->n], &a->jshort);
845: for (i = 0; i < a->i[A->rmap->n]; i++) a->jshort[i] = a->j[i];
846: A->ops->mult = MatMult_SeqSBAIJ_1_ushort;
847: A->ops->sor = MatSOR_SeqSBAIJ_ushort;
848: a->free_jshort = PETSC_TRUE;
849: }
850: return 0;
851: }
853: /*
854: This function returns an array of flags which indicate the locations of contiguous
855: blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9]
856: then the resulting sizes = [3,1,1,3,1] corresponding to sets [(0,1,2),(3),(5),(6,7,8),(9)]
857: Assume: sizes should be long enough to hold all the values.
858: */
859: PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(PetscInt idx[], PetscInt n, PetscInt bs, PetscInt sizes[], PetscInt *bs_max)
860: {
861: PetscInt i, j, k, row;
862: PetscBool flg;
864: for (i = 0, j = 0; i < n; j++) {
865: row = idx[i];
866: if (row % bs != 0) { /* Not the beginning of a block */
867: sizes[j] = 1;
868: i++;
869: } else if (i + bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */
870: sizes[j] = 1; /* Also makes sure at least 'bs' values exist for next else */
871: i++;
872: } else { /* Beginning of the block, so check if the complete block exists */
873: flg = PETSC_TRUE;
874: for (k = 1; k < bs; k++) {
875: if (row + k != idx[i + k]) { /* break in the block */
876: flg = PETSC_FALSE;
877: break;
878: }
879: }
880: if (flg) { /* No break in the bs */
881: sizes[j] = bs;
882: i += bs;
883: } else {
884: sizes[j] = 1;
885: i++;
886: }
887: }
888: }
889: *bs_max = j;
890: return 0;
891: }
893: /* Only add/insert a(i,j) with i<=j (blocks).
894: Any a(i,j) with i>j input by user is ignored.
895: */
897: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
898: {
899: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
900: PetscInt *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1;
901: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen, roworiented = a->roworiented;
902: PetscInt *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol;
903: PetscInt ridx, cidx, bs2 = a->bs2;
904: MatScalar *ap, value, *aa = a->a, *bap;
906: for (k = 0; k < m; k++) { /* loop over added rows */
907: row = im[k]; /* row number */
908: brow = row / bs; /* block row number */
909: if (row < 0) continue;
911: rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
912: ap = aa + bs2 * ai[brow]; /*ptr to beginning of element value of the row block*/
913: rmax = imax[brow]; /* maximum space allocated for this row */
914: nrow = ailen[brow]; /* actual length of this row */
915: low = 0;
916: high = nrow;
917: for (l = 0; l < n; l++) { /* loop over added columns */
918: if (in[l] < 0) continue;
920: col = in[l];
921: bcol = col / bs; /* block col number */
923: if (brow > bcol) {
924: if (a->ignore_ltriangular) continue; /* ignore lower triangular values */
925: 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)");
926: }
928: ridx = row % bs;
929: cidx = col % bs; /*row and col index inside the block */
930: if ((brow == bcol && ridx <= cidx) || (brow < bcol)) {
931: /* element value a(k,l) */
932: if (roworiented) value = v[l + k * n];
933: else value = v[k + l * m];
935: /* move pointer bap to a(k,l) quickly and add/insert value */
936: if (col <= lastcol) low = 0;
937: else high = nrow;
939: lastcol = col;
940: while (high - low > 7) {
941: t = (low + high) / 2;
942: if (rp[t] > bcol) high = t;
943: else low = t;
944: }
945: for (i = low; i < high; i++) {
946: if (rp[i] > bcol) break;
947: if (rp[i] == bcol) {
948: bap = ap + bs2 * i + bs * cidx + ridx;
949: if (is == ADD_VALUES) *bap += value;
950: else *bap = value;
951: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
952: if (brow == bcol && ridx < cidx) {
953: bap = ap + bs2 * i + bs * ridx + cidx;
954: if (is == ADD_VALUES) *bap += value;
955: else *bap = value;
956: }
957: goto noinsert1;
958: }
959: }
961: if (nonew == 1) goto noinsert1;
963: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
965: N = nrow++ - 1;
966: high++;
967: /* shift up all the later entries in this row */
968: PetscArraymove(rp + i + 1, rp + i, N - i + 1);
969: PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1));
970: PetscArrayzero(ap + bs2 * i, bs2);
971: rp[i] = bcol;
972: ap[bs2 * i + bs * cidx + ridx] = value;
973: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
974: if (brow == bcol && ridx < cidx) ap[bs2 * i + bs * ridx + cidx] = value;
975: A->nonzerostate++;
976: noinsert1:;
977: low = i;
978: }
979: } /* end of loop over added columns */
980: ailen[brow] = nrow;
981: } /* end of loop over added rows */
982: return 0;
983: }
985: PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA, IS row, const MatFactorInfo *info)
986: {
987: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inA->data;
988: Mat outA;
989: PetscBool row_identity;
992: ISIdentity(row, &row_identity);
996: outA = inA;
997: inA->factortype = MAT_FACTOR_ICC;
998: PetscFree(inA->solvertype);
999: PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype);
1001: MatMarkDiagonal_SeqSBAIJ(inA);
1002: MatSeqSBAIJSetNumericFactorization_inplace(inA, row_identity);
1004: PetscObjectReference((PetscObject)row);
1005: ISDestroy(&a->row);
1006: a->row = row;
1007: PetscObjectReference((PetscObject)row);
1008: ISDestroy(&a->col);
1009: a->col = row;
1011: /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
1012: if (a->icol) ISInvertPermutation(row, PETSC_DECIDE, &a->icol);
1014: if (!a->solve_work) { PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work); }
1016: MatCholeskyFactorNumeric(outA, inA, info);
1017: return 0;
1018: }
1020: PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat, PetscInt *indices)
1021: {
1022: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
1023: PetscInt i, nz, n;
1025: nz = baij->maxnz;
1026: n = mat->cmap->n;
1027: for (i = 0; i < nz; i++) baij->j[i] = indices[i];
1029: baij->nz = nz;
1030: for (i = 0; i < n; i++) baij->ilen[i] = baij->imax[i];
1032: MatSetOption(mat, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE);
1033: return 0;
1034: }
1036: /*@
1037: MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
1038: in a `MATSEQSBAIJ` matrix.
1040: Input Parameters:
1041: + mat - the `MATSEQSBAIJ` matrix
1042: - indices - the column indices
1044: Level: advanced
1046: Notes:
1047: This can be called if you have precomputed the nonzero structure of the
1048: matrix and want to provide it to the matrix object to improve the performance
1049: of the `MatSetValues()` operation.
1051: You MUST have set the correct numbers of nonzeros per row in the call to
1052: `MatCreateSeqSBAIJ()`, and the columns indices MUST be sorted.
1054: MUST be called before any calls to MatSetValues()
1056: .seealso: `MATSEQSBAIJ`, `MatCreateSeqSBAIJ`
1057: @*/
1058: PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat, PetscInt *indices)
1059: {
1062: PetscUseMethod(mat, "MatSeqSBAIJSetColumnIndices_C", (Mat, PetscInt *), (mat, indices));
1063: return 0;
1064: }
1066: PetscErrorCode MatCopy_SeqSBAIJ(Mat A, Mat B, MatStructure str)
1067: {
1068: PetscBool isbaij;
1070: PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, "");
1072: /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
1073: if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
1074: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1075: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1080: PetscArraycpy(b->a, a->a, a->bs2 * a->i[a->mbs]);
1081: PetscObjectStateIncrease((PetscObject)B);
1082: } else {
1083: MatGetRowUpperTriangular(A);
1084: MatCopy_Basic(A, B, str);
1085: MatRestoreRowUpperTriangular(A);
1086: }
1087: return 0;
1088: }
1090: PetscErrorCode MatSetUp_SeqSBAIJ(Mat A)
1091: {
1092: MatSeqSBAIJSetPreallocation(A, A->rmap->bs, PETSC_DEFAULT, NULL);
1093: return 0;
1094: }
1096: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1097: {
1098: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1100: *array = a->a;
1101: return 0;
1102: }
1104: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1105: {
1106: *array = NULL;
1107: return 0;
1108: }
1110: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y, Mat X, PetscInt *nnz)
1111: {
1112: PetscInt bs = Y->rmap->bs, mbs = Y->rmap->N / bs;
1113: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data;
1114: Mat_SeqSBAIJ *y = (Mat_SeqSBAIJ *)Y->data;
1116: /* Set the number of nonzeros in the new matrix */
1117: MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz);
1118: return 0;
1119: }
1121: PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1122: {
1123: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data, *y = (Mat_SeqSBAIJ *)Y->data;
1124: PetscInt bs = Y->rmap->bs, bs2 = bs * bs;
1125: PetscBLASInt one = 1;
1127: if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
1128: PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
1129: if (e) {
1130: PetscArraycmp(x->i, y->i, x->mbs + 1, &e);
1131: if (e) {
1132: PetscArraycmp(x->j, y->j, x->i[x->mbs], &e);
1133: if (e) str = SAME_NONZERO_PATTERN;
1134: }
1135: }
1137: }
1138: if (str == SAME_NONZERO_PATTERN) {
1139: PetscScalar alpha = a;
1140: PetscBLASInt bnz;
1141: PetscBLASIntCast(x->nz * bs2, &bnz);
1142: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1143: PetscObjectStateIncrease((PetscObject)Y);
1144: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1145: MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE);
1146: MatAXPY_Basic(Y, a, X, str);
1147: MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE);
1148: } else {
1149: Mat B;
1150: PetscInt *nnz;
1152: MatGetRowUpperTriangular(X);
1153: MatGetRowUpperTriangular(Y);
1154: PetscMalloc1(Y->rmap->N, &nnz);
1155: MatCreate(PetscObjectComm((PetscObject)Y), &B);
1156: PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name);
1157: MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N);
1158: MatSetBlockSizesFromMats(B, Y, Y);
1159: MatSetType(B, ((PetscObject)Y)->type_name);
1160: MatAXPYGetPreallocation_SeqSBAIJ(Y, X, nnz);
1161: MatSeqSBAIJSetPreallocation(B, bs, 0, nnz);
1163: MatAXPY_BasicWithPreallocation(B, Y, a, X, str);
1165: MatHeaderMerge(Y, &B);
1166: PetscFree(nnz);
1167: MatRestoreRowUpperTriangular(X);
1168: MatRestoreRowUpperTriangular(Y);
1169: }
1170: return 0;
1171: }
1173: PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1174: {
1175: *flg = PETSC_TRUE;
1176: return 0;
1177: }
1179: PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A, PetscBool *flg)
1180: {
1181: *flg = PETSC_TRUE;
1182: return 0;
1183: }
1185: PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1186: {
1187: *flg = PETSC_FALSE;
1188: return 0;
1189: }
1191: PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
1192: {
1193: #if defined(PETSC_USE_COMPLEX)
1194: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1195: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1196: MatScalar *aa = a->a;
1198: for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]);
1199: #else
1200: #endif
1201: return 0;
1202: }
1204: PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1205: {
1206: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1207: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1208: MatScalar *aa = a->a;
1210: for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]);
1211: return 0;
1212: }
1214: PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1215: {
1216: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1217: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1218: MatScalar *aa = a->a;
1220: for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1221: return 0;
1222: }
1224: PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b)
1225: {
1226: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)A->data;
1227: PetscInt i, j, k, count;
1228: PetscInt bs = A->rmap->bs, bs2 = baij->bs2, row, col;
1229: PetscScalar zero = 0.0;
1230: MatScalar *aa;
1231: const PetscScalar *xx;
1232: PetscScalar *bb;
1233: PetscBool *zeroed, vecs = PETSC_FALSE;
1235: /* fix right hand side if needed */
1236: if (x && b) {
1237: VecGetArrayRead(x, &xx);
1238: VecGetArray(b, &bb);
1239: vecs = PETSC_TRUE;
1240: }
1242: /* zero the columns */
1243: PetscCalloc1(A->rmap->n, &zeroed);
1244: for (i = 0; i < is_n; i++) {
1246: zeroed[is_idx[i]] = PETSC_TRUE;
1247: }
1248: if (vecs) {
1249: for (i = 0; i < A->rmap->N; i++) {
1250: row = i / bs;
1251: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1252: for (k = 0; k < bs; k++) {
1253: col = bs * baij->j[j] + k;
1254: if (col <= i) continue;
1255: aa = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1256: if (!zeroed[i] && zeroed[col]) bb[i] -= aa[0] * xx[col];
1257: if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0] * xx[i];
1258: }
1259: }
1260: }
1261: for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]];
1262: }
1264: for (i = 0; i < A->rmap->N; i++) {
1265: if (!zeroed[i]) {
1266: row = i / bs;
1267: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1268: for (k = 0; k < bs; k++) {
1269: col = bs * baij->j[j] + k;
1270: if (zeroed[col]) {
1271: aa = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1272: aa[0] = 0.0;
1273: }
1274: }
1275: }
1276: }
1277: }
1278: PetscFree(zeroed);
1279: if (vecs) {
1280: VecRestoreArrayRead(x, &xx);
1281: VecRestoreArray(b, &bb);
1282: }
1284: /* zero the rows */
1285: for (i = 0; i < is_n; i++) {
1286: row = is_idx[i];
1287: count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1288: aa = ((MatScalar *)(baij->a)) + baij->i[row / bs] * bs2 + (row % bs);
1289: for (k = 0; k < count; k++) {
1290: aa[0] = zero;
1291: aa += bs;
1292: }
1293: if (diag != 0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES);
1294: }
1295: MatAssemblyEnd_SeqSBAIJ(A, MAT_FINAL_ASSEMBLY);
1296: return 0;
1297: }
1299: PetscErrorCode MatShift_SeqSBAIJ(Mat Y, PetscScalar a)
1300: {
1301: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)Y->data;
1303: if (!Y->preallocated || !aij->nz) MatSeqSBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL);
1304: MatShift_Basic(Y, a);
1305: return 0;
1306: }
1308: /* -------------------------------------------------------------------*/
1309: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1310: MatGetRow_SeqSBAIJ,
1311: MatRestoreRow_SeqSBAIJ,
1312: MatMult_SeqSBAIJ_N,
1313: /* 4*/ MatMultAdd_SeqSBAIJ_N,
1314: MatMult_SeqSBAIJ_N, /* transpose versions are same as non-transpose versions */
1315: MatMultAdd_SeqSBAIJ_N,
1316: NULL,
1317: NULL,
1318: NULL,
1319: /* 10*/ NULL,
1320: NULL,
1321: MatCholeskyFactor_SeqSBAIJ,
1322: MatSOR_SeqSBAIJ,
1323: MatTranspose_SeqSBAIJ,
1324: /* 15*/ MatGetInfo_SeqSBAIJ,
1325: MatEqual_SeqSBAIJ,
1326: MatGetDiagonal_SeqSBAIJ,
1327: MatDiagonalScale_SeqSBAIJ,
1328: MatNorm_SeqSBAIJ,
1329: /* 20*/ NULL,
1330: MatAssemblyEnd_SeqSBAIJ,
1331: MatSetOption_SeqSBAIJ,
1332: MatZeroEntries_SeqSBAIJ,
1333: /* 24*/ NULL,
1334: NULL,
1335: NULL,
1336: NULL,
1337: NULL,
1338: /* 29*/ MatSetUp_SeqSBAIJ,
1339: NULL,
1340: NULL,
1341: NULL,
1342: NULL,
1343: /* 34*/ MatDuplicate_SeqSBAIJ,
1344: NULL,
1345: NULL,
1346: NULL,
1347: MatICCFactor_SeqSBAIJ,
1348: /* 39*/ MatAXPY_SeqSBAIJ,
1349: MatCreateSubMatrices_SeqSBAIJ,
1350: MatIncreaseOverlap_SeqSBAIJ,
1351: MatGetValues_SeqSBAIJ,
1352: MatCopy_SeqSBAIJ,
1353: /* 44*/ NULL,
1354: MatScale_SeqSBAIJ,
1355: MatShift_SeqSBAIJ,
1356: NULL,
1357: MatZeroRowsColumns_SeqSBAIJ,
1358: /* 49*/ NULL,
1359: MatGetRowIJ_SeqSBAIJ,
1360: MatRestoreRowIJ_SeqSBAIJ,
1361: NULL,
1362: NULL,
1363: /* 54*/ NULL,
1364: NULL,
1365: NULL,
1366: MatPermute_SeqSBAIJ,
1367: MatSetValuesBlocked_SeqSBAIJ,
1368: /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
1369: NULL,
1370: NULL,
1371: NULL,
1372: NULL,
1373: /* 64*/ NULL,
1374: NULL,
1375: NULL,
1376: NULL,
1377: NULL,
1378: /* 69*/ MatGetRowMaxAbs_SeqSBAIJ,
1379: NULL,
1380: MatConvert_MPISBAIJ_Basic,
1381: NULL,
1382: NULL,
1383: /* 74*/ NULL,
1384: NULL,
1385: NULL,
1386: NULL,
1387: NULL,
1388: /* 79*/ NULL,
1389: NULL,
1390: NULL,
1391: MatGetInertia_SeqSBAIJ,
1392: MatLoad_SeqSBAIJ,
1393: /* 84*/ MatIsSymmetric_SeqSBAIJ,
1394: MatIsHermitian_SeqSBAIJ,
1395: MatIsStructurallySymmetric_SeqSBAIJ,
1396: NULL,
1397: NULL,
1398: /* 89*/ NULL,
1399: NULL,
1400: NULL,
1401: NULL,
1402: NULL,
1403: /* 94*/ NULL,
1404: NULL,
1405: NULL,
1406: NULL,
1407: NULL,
1408: /* 99*/ NULL,
1409: NULL,
1410: NULL,
1411: MatConjugate_SeqSBAIJ,
1412: NULL,
1413: /*104*/ NULL,
1414: MatRealPart_SeqSBAIJ,
1415: MatImaginaryPart_SeqSBAIJ,
1416: MatGetRowUpperTriangular_SeqSBAIJ,
1417: MatRestoreRowUpperTriangular_SeqSBAIJ,
1418: /*109*/ NULL,
1419: NULL,
1420: NULL,
1421: NULL,
1422: MatMissingDiagonal_SeqSBAIJ,
1423: /*114*/ NULL,
1424: NULL,
1425: NULL,
1426: NULL,
1427: NULL,
1428: /*119*/ NULL,
1429: NULL,
1430: NULL,
1431: NULL,
1432: NULL,
1433: /*124*/ NULL,
1434: NULL,
1435: NULL,
1436: NULL,
1437: NULL,
1438: /*129*/ NULL,
1439: NULL,
1440: NULL,
1441: NULL,
1442: NULL,
1443: /*134*/ NULL,
1444: NULL,
1445: NULL,
1446: NULL,
1447: NULL,
1448: /*139*/ MatSetBlockSizes_Default,
1449: NULL,
1450: NULL,
1451: NULL,
1452: NULL,
1453: /*144*/ MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
1454: NULL,
1455: NULL,
1456: NULL,
1457: NULL,
1458: NULL,
1459: /*150*/ NULL};
1461: PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat)
1462: {
1463: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1464: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1468: /* allocate space for values if not already there */
1469: if (!aij->saved_values) PetscMalloc1(nz + 1, &aij->saved_values);
1471: /* copy values over */
1472: PetscArraycpy(aij->saved_values, aij->a, nz);
1473: return 0;
1474: }
1476: PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat)
1477: {
1478: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1479: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1484: /* copy values over */
1485: PetscArraycpy(aij->a, aij->saved_values, nz);
1486: return 0;
1487: }
1489: static PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B, PetscInt bs, PetscInt nz, PetscInt *nnz)
1490: {
1491: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1492: PetscInt i, mbs, nbs, bs2;
1493: PetscBool skipallocation = PETSC_FALSE, flg = PETSC_FALSE, realalloc = PETSC_FALSE;
1495: if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
1497: MatSetBlockSize(B, PetscAbs(bs));
1498: PetscLayoutSetUp(B->rmap);
1499: PetscLayoutSetUp(B->cmap);
1501: PetscLayoutGetBlockSize(B->rmap, &bs);
1503: B->preallocated = PETSC_TRUE;
1505: mbs = B->rmap->N / bs;
1506: nbs = B->cmap->n / bs;
1507: bs2 = bs * bs;
1511: if (nz == MAT_SKIP_ALLOCATION) {
1512: skipallocation = PETSC_TRUE;
1513: nz = 0;
1514: }
1516: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1518: if (nnz) {
1519: for (i = 0; i < mbs; i++) {
1522: }
1523: }
1525: B->ops->mult = MatMult_SeqSBAIJ_N;
1526: B->ops->multadd = MatMultAdd_SeqSBAIJ_N;
1527: B->ops->multtranspose = MatMult_SeqSBAIJ_N;
1528: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;
1530: PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL);
1531: if (!flg) {
1532: switch (bs) {
1533: case 1:
1534: B->ops->mult = MatMult_SeqSBAIJ_1;
1535: B->ops->multadd = MatMultAdd_SeqSBAIJ_1;
1536: B->ops->multtranspose = MatMult_SeqSBAIJ_1;
1537: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1538: break;
1539: case 2:
1540: B->ops->mult = MatMult_SeqSBAIJ_2;
1541: B->ops->multadd = MatMultAdd_SeqSBAIJ_2;
1542: B->ops->multtranspose = MatMult_SeqSBAIJ_2;
1543: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1544: break;
1545: case 3:
1546: B->ops->mult = MatMult_SeqSBAIJ_3;
1547: B->ops->multadd = MatMultAdd_SeqSBAIJ_3;
1548: B->ops->multtranspose = MatMult_SeqSBAIJ_3;
1549: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1550: break;
1551: case 4:
1552: B->ops->mult = MatMult_SeqSBAIJ_4;
1553: B->ops->multadd = MatMultAdd_SeqSBAIJ_4;
1554: B->ops->multtranspose = MatMult_SeqSBAIJ_4;
1555: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1556: break;
1557: case 5:
1558: B->ops->mult = MatMult_SeqSBAIJ_5;
1559: B->ops->multadd = MatMultAdd_SeqSBAIJ_5;
1560: B->ops->multtranspose = MatMult_SeqSBAIJ_5;
1561: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1562: break;
1563: case 6:
1564: B->ops->mult = MatMult_SeqSBAIJ_6;
1565: B->ops->multadd = MatMultAdd_SeqSBAIJ_6;
1566: B->ops->multtranspose = MatMult_SeqSBAIJ_6;
1567: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1568: break;
1569: case 7:
1570: B->ops->mult = MatMult_SeqSBAIJ_7;
1571: B->ops->multadd = MatMultAdd_SeqSBAIJ_7;
1572: B->ops->multtranspose = MatMult_SeqSBAIJ_7;
1573: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1574: break;
1575: }
1576: }
1578: b->mbs = mbs;
1579: b->nbs = nbs;
1580: if (!skipallocation) {
1581: if (!b->imax) {
1582: PetscMalloc2(mbs, &b->imax, mbs, &b->ilen);
1584: b->free_imax_ilen = PETSC_TRUE;
1585: }
1586: if (!nnz) {
1587: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1588: else if (nz <= 0) nz = 1;
1589: nz = PetscMin(nbs, nz);
1590: for (i = 0; i < mbs; i++) b->imax[i] = nz;
1591: PetscIntMultError(nz, mbs, &nz);
1592: } else {
1593: PetscInt64 nz64 = 0;
1594: for (i = 0; i < mbs; i++) {
1595: b->imax[i] = nnz[i];
1596: nz64 += nnz[i];
1597: }
1598: PetscIntCast(nz64, &nz);
1599: }
1600: /* b->ilen will count nonzeros in each block row so far. */
1601: for (i = 0; i < mbs; i++) b->ilen[i] = 0;
1602: /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */
1604: /* allocate the matrix space */
1605: MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i);
1606: PetscMalloc3(bs2 * nz, &b->a, nz, &b->j, B->rmap->N + 1, &b->i);
1607: PetscArrayzero(b->a, nz * bs2);
1608: PetscArrayzero(b->j, nz);
1610: b->singlemalloc = PETSC_TRUE;
1612: /* pointer to beginning of each row */
1613: b->i[0] = 0;
1614: for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1];
1616: b->free_a = PETSC_TRUE;
1617: b->free_ij = PETSC_TRUE;
1618: } else {
1619: b->free_a = PETSC_FALSE;
1620: b->free_ij = PETSC_FALSE;
1621: }
1623: b->bs2 = bs2;
1624: b->nz = 0;
1625: b->maxnz = nz;
1626: b->inew = NULL;
1627: b->jnew = NULL;
1628: b->anew = NULL;
1629: b->a2anew = NULL;
1630: b->permute = PETSC_FALSE;
1632: B->was_assembled = PETSC_FALSE;
1633: B->assembled = PETSC_FALSE;
1634: if (realalloc) MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE);
1635: return 0;
1636: }
1638: PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
1639: {
1640: PetscInt i, j, m, nz, anz, nz_max = 0, *nnz;
1641: PetscScalar *values = NULL;
1642: PetscBool roworiented = ((Mat_SeqSBAIJ *)B->data)->roworiented;
1645: PetscLayoutSetBlockSize(B->rmap, bs);
1646: PetscLayoutSetBlockSize(B->cmap, bs);
1647: PetscLayoutSetUp(B->rmap);
1648: PetscLayoutSetUp(B->cmap);
1649: PetscLayoutGetBlockSize(B->rmap, &bs);
1650: m = B->rmap->n / bs;
1653: PetscMalloc1(m + 1, &nnz);
1654: for (i = 0; i < m; i++) {
1655: nz = ii[i + 1] - ii[i];
1657: anz = 0;
1658: for (j = 0; j < nz; j++) {
1659: /* count only values on the diagonal or above */
1660: if (jj[ii[i] + j] >= i) {
1661: anz = nz - j;
1662: break;
1663: }
1664: }
1665: nz_max = PetscMax(nz_max, anz);
1666: nnz[i] = anz;
1667: }
1668: MatSeqSBAIJSetPreallocation(B, bs, 0, nnz);
1669: PetscFree(nnz);
1671: values = (PetscScalar *)V;
1672: if (!values) PetscCalloc1(bs * bs * nz_max, &values);
1673: for (i = 0; i < m; i++) {
1674: PetscInt ncols = ii[i + 1] - ii[i];
1675: const PetscInt *icols = jj + ii[i];
1676: if (!roworiented || bs == 1) {
1677: const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
1678: MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES);
1679: } else {
1680: for (j = 0; j < ncols; j++) {
1681: const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
1682: MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES);
1683: }
1684: }
1685: }
1686: if (!V) PetscFree(values);
1687: MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY);
1688: MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY);
1689: MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE);
1690: return 0;
1691: }
1693: /*
1694: This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1695: */
1696: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B, PetscBool natural)
1697: {
1698: PetscBool flg = PETSC_FALSE;
1699: PetscInt bs = B->rmap->bs;
1701: PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL);
1702: if (flg) bs = 8;
1704: if (!natural) {
1705: switch (bs) {
1706: case 1:
1707: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
1708: break;
1709: case 2:
1710: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1711: break;
1712: case 3:
1713: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1714: break;
1715: case 4:
1716: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1717: break;
1718: case 5:
1719: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1720: break;
1721: case 6:
1722: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1723: break;
1724: case 7:
1725: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1726: break;
1727: default:
1728: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1729: break;
1730: }
1731: } else {
1732: switch (bs) {
1733: case 1:
1734: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
1735: break;
1736: case 2:
1737: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1738: break;
1739: case 3:
1740: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1741: break;
1742: case 4:
1743: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1744: break;
1745: case 5:
1746: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1747: break;
1748: case 6:
1749: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1750: break;
1751: case 7:
1752: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1753: break;
1754: default:
1755: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1756: break;
1757: }
1758: }
1759: return 0;
1760: }
1762: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
1763: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
1764: static PetscErrorCode MatFactorGetSolverType_petsc(Mat A, MatSolverType *type)
1765: {
1766: *type = MATSOLVERPETSC;
1767: return 0;
1768: }
1770: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A, MatFactorType ftype, Mat *B)
1771: {
1772: PetscInt n = A->rmap->n;
1774: #if defined(PETSC_USE_COMPLEX)
1776: #endif
1778: MatCreate(PetscObjectComm((PetscObject)A), B);
1779: MatSetSizes(*B, n, n, n, n);
1780: if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1781: MatSetType(*B, MATSEQSBAIJ);
1782: MatSeqSBAIJSetPreallocation(*B, A->rmap->bs, MAT_SKIP_ALLOCATION, NULL);
1784: (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1785: (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;
1786: PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]);
1787: PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]);
1788: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
1790: (*B)->factortype = ftype;
1791: (*B)->canuseordering = PETSC_TRUE;
1792: PetscFree((*B)->solvertype);
1793: PetscStrallocpy(MATSOLVERPETSC, &(*B)->solvertype);
1794: PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_petsc);
1795: return 0;
1796: }
1798: /*@C
1799: MatSeqSBAIJGetArray - gives access to the array where the data for a `MATSEQSBAIJ` matrix is stored
1801: Not Collective
1803: Input Parameter:
1804: . mat - a `MATSEQSBAIJ` matrix
1806: Output Parameter:
1807: . array - pointer to the data
1809: Level: intermediate
1811: .seealso: `MATSEQSBAIJ`, `MatSeqSBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1812: @*/
1813: PetscErrorCode MatSeqSBAIJGetArray(Mat A, PetscScalar **array)
1814: {
1815: PetscUseMethod(A, "MatSeqSBAIJGetArray_C", (Mat, PetscScalar **), (A, array));
1816: return 0;
1817: }
1819: /*@C
1820: MatSeqSBAIJRestoreArray - returns access to the array where the data for a `MATSEQSBAIJ` matrix is stored obtained by `MatSeqSBAIJGetArray()`
1822: Not Collective
1824: Input Parameters:
1825: + mat - a MATSEQSBAIJ matrix
1826: - array - pointer to the data
1828: Level: intermediate
1830: .seealso: `MATSEQSBAIJ`, `MatSeqSBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1831: @*/
1832: PetscErrorCode MatSeqSBAIJRestoreArray(Mat A, PetscScalar **array)
1833: {
1834: PetscUseMethod(A, "MatSeqSBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array));
1835: return 0;
1836: }
1838: /*MC
1839: MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
1840: based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored.
1842: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1843: can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`).
1845: Options Database Keys:
1846: . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to `MatSetFromOptions()`
1848: Notes:
1849: By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
1850: stored and it is assumed they symmetric to the upper triangular). If you call `MatSetOption`(`Mat`,`MAT_IGNORE_LOWER_TRIANGULAR`,`PETSC_FALSE`) or use
1851: 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.
1853: The number of rows in the matrix must be less than or equal to the number of columns
1855: Level: beginner
1857: .seealso: `MATSEQSBAIJ`, `MatCreateSeqSBAIJ()`, `MatType`, `MATMPISBAIJ`
1858: M*/
1859: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
1860: {
1861: Mat_SeqSBAIJ *b;
1862: PetscMPIInt size;
1863: PetscBool no_unroll = PETSC_FALSE, no_inode = PETSC_FALSE;
1865: MPI_Comm_size(PetscObjectComm((PetscObject)B), &size);
1868: PetscNew(&b);
1869: B->data = (void *)b;
1870: PetscMemcpy(B->ops, &MatOps_Values, sizeof(struct _MatOps));
1872: B->ops->destroy = MatDestroy_SeqSBAIJ;
1873: B->ops->view = MatView_SeqSBAIJ;
1874: b->row = NULL;
1875: b->icol = NULL;
1876: b->reallocs = 0;
1877: b->saved_values = NULL;
1878: b->inode.limit = 5;
1879: b->inode.max_limit = 5;
1881: b->roworiented = PETSC_TRUE;
1882: b->nonew = 0;
1883: b->diag = NULL;
1884: b->solve_work = NULL;
1885: b->mult_work = NULL;
1886: B->spptr = NULL;
1887: B->info.nz_unneeded = (PetscReal)b->maxnz * b->bs2;
1888: b->keepnonzeropattern = PETSC_FALSE;
1890: b->inew = NULL;
1891: b->jnew = NULL;
1892: b->anew = NULL;
1893: b->a2anew = NULL;
1894: b->permute = PETSC_FALSE;
1896: b->ignore_ltriangular = PETSC_TRUE;
1898: PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_ignore_lower_triangular", &b->ignore_ltriangular, NULL);
1900: b->getrow_utriangular = PETSC_FALSE;
1902: PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_getrow_uppertriangular", &b->getrow_utriangular, NULL);
1904: PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJGetArray_C", MatSeqSBAIJGetArray_SeqSBAIJ);
1905: PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJRestoreArray_C", MatSeqSBAIJRestoreArray_SeqSBAIJ);
1906: PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSBAIJ);
1907: PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSBAIJ);
1908: PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetColumnIndices_C", MatSeqSBAIJSetColumnIndices_SeqSBAIJ);
1909: PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqaij_C", MatConvert_SeqSBAIJ_SeqAIJ);
1910: PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqbaij_C", MatConvert_SeqSBAIJ_SeqBAIJ);
1911: PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocation_C", MatSeqSBAIJSetPreallocation_SeqSBAIJ);
1912: PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocationCSR_C", MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ);
1913: #if defined(PETSC_HAVE_ELEMENTAL)
1914: PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_elemental_C", MatConvert_SeqSBAIJ_Elemental);
1915: #endif
1916: #if defined(PETSC_HAVE_SCALAPACK)
1917: PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK);
1918: #endif
1920: B->symmetry_eternal = PETSC_TRUE;
1921: B->structural_symmetry_eternal = PETSC_TRUE;
1922: B->symmetric = PETSC_BOOL3_TRUE;
1923: B->structurally_symmetric = PETSC_BOOL3_TRUE;
1924: #if defined(PETSC_USE_COMPLEX)
1925: B->hermitian = PETSC_BOOL3_FALSE;
1926: #else
1927: B->hermitian = PETSC_BOOL3_TRUE;
1928: #endif
1930: PetscObjectChangeTypeName((PetscObject)B, MATSEQSBAIJ);
1932: PetscOptionsBegin(PetscObjectComm((PetscObject)B), ((PetscObject)B)->prefix, "Options for SEQSBAIJ matrix", "Mat");
1933: PetscOptionsBool("-mat_no_unroll", "Do not optimize for inodes (slower)", NULL, no_unroll, &no_unroll, NULL);
1934: if (no_unroll) PetscInfo(B, "Not using Inode routines due to -mat_no_unroll\n");
1935: PetscOptionsBool("-mat_no_inode", "Do not optimize for inodes (slower)", NULL, no_inode, &no_inode, NULL);
1936: if (no_inode) PetscInfo(B, "Not using Inode routines due to -mat_no_inode\n");
1937: PetscOptionsInt("-mat_inode_limit", "Do not use inodes larger then this value", NULL, b->inode.limit, &b->inode.limit, NULL);
1938: PetscOptionsEnd();
1939: b->inode.use = (PetscBool)(!(no_unroll || no_inode));
1940: if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
1941: return 0;
1942: }
1944: /*@C
1945: MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
1946: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
1947: user should preallocate the matrix storage by setting the parameter nz
1948: (or the array nnz). By setting these parameters accurately, performance
1949: during matrix assembly can be increased by more than a factor of 50.
1951: Collective
1953: Input Parameters:
1954: + B - the symmetric matrix
1955: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
1956: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
1957: . nz - number of block nonzeros per block row (same for all rows)
1958: - nnz - array containing the number of block nonzeros in the upper triangular plus
1959: diagonal portion of each block (possibly different for each block row) or NULL
1961: Options Database Keys:
1962: + -mat_no_unroll - uses code that does not unroll the loops in the
1963: block calculations (much slower)
1964: - -mat_block_size - size of the blocks to use (only works if a negative bs is passed in
1966: Level: intermediate
1968: Notes:
1969: Specify the preallocated storage with either nz or nnz (not both).
1970: Set nz = `PETSC_DEFAULT` and nnz = NULL for PETSc to control dynamic memory
1971: allocation. See [Sparse Matrices](sec_matsparse) for details.
1973: You can call `MatGetInfo()` to get information on how effective the preallocation was;
1974: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1975: You can also run with the option -info and look for messages with the string
1976: malloc in them to see if additional memory allocation was needed.
1978: If the nnz parameter is given then the nz parameter is ignored
1980: .seealso: [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
1981: @*/
1982: PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
1983: {
1987: PetscTryMethod(B, "MatSeqSBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz));
1988: return 0;
1989: }
1991: /*@C
1992: MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATSEQSBAIJ` format using the given nonzero structure and (optional) numerical values
1994: Input Parameters:
1995: + B - the matrix
1996: . bs - size of block, the blocks are ALWAYS square.
1997: . i - the indices into j for the start of each local row (starts with zero)
1998: . j - the column indices for each local row (starts with zero) these must be sorted for each row
1999: - v - optional values in the matrix
2001: Level: advanced
2003: Notes:
2004: The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`. For example, C programs
2005: may want to use the default `MAT_ROW_ORIENTED` = `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
2006: over rows within a block and the last index is over columns within a block row. Fortran programs will likely set
2007: `MAT_ROW_ORIENTED` = `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2008: block column and the second index is over columns within a block.
2010: Any entries below the diagonal are ignored
2012: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2013: and usually the numerical values as well
2015: .seealso: `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValuesBlocked()`, `MatSeqSBAIJSetPreallocation()`, `MATSEQSBAIJ`
2016: @*/
2017: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2018: {
2022: PetscTryMethod(B, "MatSeqSBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2023: return 0;
2024: }
2026: /*@C
2027: MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in block AIJ (block
2028: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
2029: user should preallocate the matrix storage by setting the parameter nz
2030: (or the array nnz). By setting these parameters accurately, performance
2031: during matrix assembly can be increased by more than a factor of 50.
2033: Collective
2035: Input Parameters:
2036: + comm - MPI communicator, set to `PETSC_COMM_SELF`
2037: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2038: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2039: . m - number of rows, or number of columns
2040: . nz - number of block nonzeros per block row (same for all rows)
2041: - nnz - array containing the number of block nonzeros in the upper triangular plus
2042: diagonal portion of each block (possibly different for each block row) or NULL
2044: Output Parameter:
2045: . A - the symmetric matrix
2047: Options Database Keys:
2048: + -mat_no_unroll - uses code that does not unroll the loops in the
2049: block calculations (much slower)
2050: - -mat_block_size - size of the blocks to use
2052: Level: intermediate
2054: It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
2055: MatXXXXSetPreallocation() paradigm instead of this routine directly.
2056: [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]
2058: Notes:
2059: The number of rows and columns must be divisible by blocksize.
2060: This matrix type does not support complex Hermitian operation.
2062: Specify the preallocated storage with either nz or nnz (not both).
2063: Set nz = `PETSC_DEFAULT` and nnz = NULL for PETSc to control dynamic memory
2064: allocation. See [Sparse Matrices](sec_matsparse) for details.
2066: If the nnz parameter is given then the nz parameter is ignored
2068: .seealso: [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2069: @*/
2070: PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
2071: {
2072: MatCreate(comm, A);
2073: MatSetSizes(*A, m, n, m, n);
2074: MatSetType(*A, MATSEQSBAIJ);
2075: MatSeqSBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz);
2076: return 0;
2077: }
2079: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B)
2080: {
2081: Mat C;
2082: Mat_SeqSBAIJ *c, *a = (Mat_SeqSBAIJ *)A->data;
2083: PetscInt i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2;
2087: *B = NULL;
2088: MatCreate(PetscObjectComm((PetscObject)A), &C);
2089: MatSetSizes(C, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n);
2090: MatSetBlockSizesFromMats(C, A, A);
2091: MatSetType(C, MATSEQSBAIJ);
2092: c = (Mat_SeqSBAIJ *)C->data;
2094: C->preallocated = PETSC_TRUE;
2095: C->factortype = A->factortype;
2096: c->row = NULL;
2097: c->icol = NULL;
2098: c->saved_values = NULL;
2099: c->keepnonzeropattern = a->keepnonzeropattern;
2100: C->assembled = PETSC_TRUE;
2102: PetscLayoutReference(A->rmap, &C->rmap);
2103: PetscLayoutReference(A->cmap, &C->cmap);
2104: c->bs2 = a->bs2;
2105: c->mbs = a->mbs;
2106: c->nbs = a->nbs;
2108: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2109: c->imax = a->imax;
2110: c->ilen = a->ilen;
2111: c->free_imax_ilen = PETSC_FALSE;
2112: } else {
2113: PetscMalloc2((mbs + 1), &c->imax, (mbs + 1), &c->ilen);
2114: for (i = 0; i < mbs; i++) {
2115: c->imax[i] = a->imax[i];
2116: c->ilen[i] = a->ilen[i];
2117: }
2118: c->free_imax_ilen = PETSC_TRUE;
2119: }
2121: /* allocate the matrix space */
2122: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2123: PetscMalloc1(bs2 * nz, &c->a);
2124: c->i = a->i;
2125: c->j = a->j;
2126: c->singlemalloc = PETSC_FALSE;
2127: c->free_a = PETSC_TRUE;
2128: c->free_ij = PETSC_FALSE;
2129: c->parent = A;
2130: PetscObjectReference((PetscObject)A);
2131: MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE);
2132: MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE);
2133: } else {
2134: PetscMalloc3(bs2 * nz, &c->a, nz, &c->j, mbs + 1, &c->i);
2135: PetscArraycpy(c->i, a->i, mbs + 1);
2136: c->singlemalloc = PETSC_TRUE;
2137: c->free_a = PETSC_TRUE;
2138: c->free_ij = PETSC_TRUE;
2139: }
2140: if (mbs > 0) {
2141: if (cpvalues != MAT_SHARE_NONZERO_PATTERN) PetscArraycpy(c->j, a->j, nz);
2142: if (cpvalues == MAT_COPY_VALUES) {
2143: PetscArraycpy(c->a, a->a, bs2 * nz);
2144: } else {
2145: PetscArrayzero(c->a, bs2 * nz);
2146: }
2147: if (a->jshort) {
2148: /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
2149: /* if the parent matrix is reassembled, this child matrix will never notice */
2150: PetscMalloc1(nz, &c->jshort);
2151: PetscArraycpy(c->jshort, a->jshort, nz);
2153: c->free_jshort = PETSC_TRUE;
2154: }
2155: }
2157: c->roworiented = a->roworiented;
2158: c->nonew = a->nonew;
2160: if (a->diag) {
2161: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2162: c->diag = a->diag;
2163: c->free_diag = PETSC_FALSE;
2164: } else {
2165: PetscMalloc1(mbs, &c->diag);
2166: for (i = 0; i < mbs; i++) c->diag[i] = a->diag[i];
2167: c->free_diag = PETSC_TRUE;
2168: }
2169: }
2170: c->nz = a->nz;
2171: c->maxnz = a->nz; /* Since we allocate exactly the right amount */
2172: c->solve_work = NULL;
2173: c->mult_work = NULL;
2175: *B = C;
2176: PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist);
2177: return 0;
2178: }
2180: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
2181: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary
2183: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat, PetscViewer viewer)
2184: {
2185: PetscBool isbinary;
2187: PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary);
2189: MatLoad_SeqSBAIJ_Binary(mat, viewer);
2190: return 0;
2191: }
2193: /*@
2194: MatCreateSeqSBAIJWithArrays - Creates an sequential `MATSEQSBAIJ` matrix using matrix elements
2195: (upper triangular entries in CSR format) provided by the user.
2197: Collective
2199: Input Parameters:
2200: + comm - must be an MPI communicator of size 1
2201: . bs - size of block
2202: . m - number of rows
2203: . n - number of columns
2204: . 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
2205: . j - column indices
2206: - a - matrix values
2208: Output Parameter:
2209: . mat - the matrix
2211: Level: advanced
2213: Notes:
2214: The i, j, and a arrays are not copied by this routine, the user must free these arrays
2215: once the matrix is destroyed
2217: You cannot set new nonzero locations into this matrix, that will generate an error.
2219: The i and j indices are 0 based
2221: When block size is greater than 1 the matrix values must be stored using the SBAIJ storage format (see the SBAIJ source code to determine this). For block size of 1
2222: it is the regular CSR format excluding the lower triangular elements.
2224: .seealso: `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSBAIJ()`, `MatCreateSeqSBAIJ()`
2225: @*/
2226: PetscErrorCode MatCreateSeqSBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat)
2227: {
2228: PetscInt ii;
2229: Mat_SeqSBAIJ *sbaij;
2234: MatCreate(comm, mat);
2235: MatSetSizes(*mat, m, n, m, n);
2236: MatSetType(*mat, MATSEQSBAIJ);
2237: MatSeqSBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL);
2238: sbaij = (Mat_SeqSBAIJ *)(*mat)->data;
2239: PetscMalloc2(m, &sbaij->imax, m, &sbaij->ilen);
2241: sbaij->i = i;
2242: sbaij->j = j;
2243: sbaij->a = a;
2245: sbaij->singlemalloc = PETSC_FALSE;
2246: sbaij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2247: sbaij->free_a = PETSC_FALSE;
2248: sbaij->free_ij = PETSC_FALSE;
2249: sbaij->free_imax_ilen = PETSC_TRUE;
2251: for (ii = 0; ii < m; ii++) {
2252: sbaij->ilen[ii] = sbaij->imax[ii] = i[ii + 1] - i[ii];
2254: }
2255: if (PetscDefined(USE_DEBUG)) {
2256: for (ii = 0; ii < sbaij->i[m]; ii++) {
2259: }
2260: }
2262: MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY);
2263: MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY);
2264: return 0;
2265: }
2267: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2268: {
2269: MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm, inmat, n, scall, outmat);
2270: return 0;
2271: }