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) && (defined(PETSC_USE_REAL_SINGLE) || defined(PETSC_USE_REAL_DOUBLE))
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: MatGetDiagonalMarkers(SeqSBAIJ, A->rmap->bs)
38: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *inia[], const PetscInt *inja[], PetscBool *done)
39: {
40: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
41: PetscInt i, j, n = a->mbs, nz = a->i[n], *tia, *tja, bs = A->rmap->bs, k, l, cnt;
42: PetscInt **ia = (PetscInt **)inia, **ja = (PetscInt **)inja;
44: PetscFunctionBegin;
45: *nn = n;
46: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
47: if (symmetric) {
48: PetscCall(MatToSymmetricIJ_SeqAIJ(n, a->i, a->j, PETSC_FALSE, 0, 0, &tia, &tja));
49: nz = tia[n];
50: } else {
51: tia = a->i;
52: tja = a->j;
53: }
55: if (!blockcompressed && bs > 1) {
56: (*nn) *= bs;
57: /* malloc & create the natural set of indices */
58: PetscCall(PetscMalloc1((n + 1) * bs, ia));
59: if (n) {
60: (*ia)[0] = oshift;
61: for (j = 1; j < bs; j++) (*ia)[j] = (tia[1] - tia[0]) * bs + (*ia)[j - 1];
62: }
64: for (i = 1; i < n; i++) {
65: (*ia)[i * bs] = (tia[i] - tia[i - 1]) * bs + (*ia)[i * bs - 1];
66: for (j = 1; j < bs; j++) (*ia)[i * bs + j] = (tia[i + 1] - tia[i]) * bs + (*ia)[i * bs + j - 1];
67: }
68: if (n) (*ia)[n * bs] = (tia[n] - tia[n - 1]) * bs + (*ia)[n * bs - 1];
70: if (inja) {
71: PetscCall(PetscMalloc1(nz * bs * bs, ja));
72: cnt = 0;
73: for (i = 0; i < n; i++) {
74: for (j = 0; j < bs; j++) {
75: for (k = tia[i]; k < tia[i + 1]; k++) {
76: for (l = 0; l < bs; l++) (*ja)[cnt++] = bs * tja[k] + l;
77: }
78: }
79: }
80: }
82: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
83: PetscCall(PetscFree(tia));
84: PetscCall(PetscFree(tja));
85: }
86: } else if (oshift == 1) {
87: if (symmetric) {
88: nz = tia[A->rmap->n / bs];
89: /* add 1 to i and j indices */
90: for (i = 0; i < A->rmap->n / bs + 1; i++) tia[i] = tia[i] + 1;
91: *ia = tia;
92: if (ja) {
93: for (i = 0; i < nz; i++) tja[i] = tja[i] + 1;
94: *ja = tja;
95: }
96: } else {
97: nz = a->i[A->rmap->n / bs];
98: /* malloc space and add 1 to i and j indices */
99: PetscCall(PetscMalloc1(A->rmap->n / bs + 1, ia));
100: for (i = 0; i < A->rmap->n / bs + 1; i++) (*ia)[i] = a->i[i] + 1;
101: if (ja) {
102: PetscCall(PetscMalloc1(nz, ja));
103: for (i = 0; i < nz; i++) (*ja)[i] = a->j[i] + 1;
104: }
105: }
106: } else {
107: *ia = tia;
108: if (ja) *ja = tja;
109: }
110: PetscFunctionReturn(PETSC_SUCCESS);
111: }
113: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done)
114: {
115: PetscFunctionBegin;
116: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
117: if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
118: PetscCall(PetscFree(*ia));
119: if (ja) PetscCall(PetscFree(*ja));
120: }
121: PetscFunctionReturn(PETSC_SUCCESS);
122: }
124: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
125: {
126: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
128: PetscFunctionBegin;
129: if (A->hash_active) {
130: PetscInt bs;
131: A->ops[0] = a->cops;
132: PetscCall(PetscHMapIJVDestroy(&a->ht));
133: PetscCall(MatGetBlockSize(A, &bs));
134: if (bs > 1) PetscCall(PetscHSetIJDestroy(&a->bht));
135: PetscCall(PetscFree(a->dnz));
136: PetscCall(PetscFree(a->bdnz));
137: A->hash_active = PETSC_FALSE;
138: }
139: PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, a->nz));
140: PetscCall(MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i));
141: PetscCall(PetscFree(a->diag));
142: PetscCall(ISDestroy(&a->row));
143: PetscCall(ISDestroy(&a->col));
144: PetscCall(ISDestroy(&a->icol));
145: PetscCall(PetscFree(a->idiag));
146: PetscCall(PetscFree(a->inode.size_csr));
147: if (a->free_imax_ilen) PetscCall(PetscFree2(a->imax, a->ilen));
148: PetscCall(PetscFree(a->solve_work));
149: PetscCall(PetscFree(a->sor_work));
150: PetscCall(PetscFree(a->solves_work));
151: PetscCall(PetscFree(a->mult_work));
152: PetscCall(PetscFree(a->saved_values));
153: if (a->free_jshort) PetscCall(PetscFree(a->jshort));
154: PetscCall(PetscFree(a->inew));
155: PetscCall(MatDestroy(&a->parent));
156: PetscCall(PetscFree(A->data));
158: PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL));
159: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJGetArray_C", NULL));
160: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJRestoreArray_C", NULL));
161: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL));
162: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL));
163: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetColumnIndices_C", NULL));
164: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqaij_C", NULL));
165: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqbaij_C", NULL));
166: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocation_C", NULL));
167: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocationCSR_C", NULL));
168: #if defined(PETSC_HAVE_ELEMENTAL)
169: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_elemental_C", NULL));
170: #endif
171: #if defined(PETSC_HAVE_SCALAPACK) && (defined(PETSC_USE_REAL_SINGLE) || defined(PETSC_USE_REAL_DOUBLE))
172: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_scalapack_C", NULL));
173: #endif
174: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
175: PetscFunctionReturn(PETSC_SUCCESS);
176: }
178: static PetscErrorCode MatSetOption_SeqSBAIJ(Mat A, MatOption op, PetscBool flg)
179: {
180: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
181: #if defined(PETSC_USE_COMPLEX)
182: PetscInt bs;
183: #endif
185: PetscFunctionBegin;
186: #if defined(PETSC_USE_COMPLEX)
187: PetscCall(MatGetBlockSize(A, &bs));
188: #endif
189: switch (op) {
190: case MAT_ROW_ORIENTED:
191: a->roworiented = flg;
192: break;
193: case MAT_KEEP_NONZERO_PATTERN:
194: a->keepnonzeropattern = flg;
195: break;
196: case MAT_NEW_NONZERO_LOCATIONS:
197: a->nonew = (flg ? 0 : 1);
198: break;
199: case MAT_NEW_NONZERO_LOCATION_ERR:
200: a->nonew = (flg ? -1 : 0);
201: break;
202: case MAT_NEW_NONZERO_ALLOCATION_ERR:
203: a->nonew = (flg ? -2 : 0);
204: break;
205: case MAT_UNUSED_NONZERO_LOCATION_ERR:
206: a->nounused = (flg ? -1 : 0);
207: break;
208: case MAT_HERMITIAN:
209: #if defined(PETSC_USE_COMPLEX)
210: if (flg) { /* disable transpose ops */
211: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for Hermitian with block size greater than 1");
212: A->ops->multtranspose = NULL;
213: A->ops->multtransposeadd = NULL;
214: }
215: #endif
216: break;
217: case MAT_SYMMETRIC:
218: case MAT_SPD:
219: #if defined(PETSC_USE_COMPLEX)
220: if (flg) { /* An Hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
221: A->ops->multtranspose = A->ops->mult;
222: A->ops->multtransposeadd = A->ops->multadd;
223: }
224: #endif
225: break;
226: case MAT_IGNORE_LOWER_TRIANGULAR:
227: a->ignore_ltriangular = flg;
228: break;
229: case MAT_ERROR_LOWER_TRIANGULAR:
230: a->ignore_ltriangular = flg;
231: break;
232: case MAT_GETROW_UPPERTRIANGULAR:
233: a->getrow_utriangular = flg;
234: break;
235: default:
236: break;
237: }
238: PetscFunctionReturn(PETSC_SUCCESS);
239: }
241: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
242: {
243: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
245: PetscFunctionBegin;
246: 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()");
248: /* Get the upper triangular part of the row */
249: PetscCall(MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a));
250: PetscFunctionReturn(PETSC_SUCCESS);
251: }
253: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
254: {
255: PetscFunctionBegin;
256: if (idx) PetscCall(PetscFree(*idx));
257: if (v) PetscCall(PetscFree(*v));
258: PetscFunctionReturn(PETSC_SUCCESS);
259: }
261: static PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
262: {
263: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
265: PetscFunctionBegin;
266: a->getrow_utriangular = PETSC_TRUE;
267: PetscFunctionReturn(PETSC_SUCCESS);
268: }
270: static PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
271: {
272: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
274: PetscFunctionBegin;
275: a->getrow_utriangular = PETSC_FALSE;
276: PetscFunctionReturn(PETSC_SUCCESS);
277: }
279: static PetscErrorCode MatTranspose_SeqSBAIJ(Mat A, MatReuse reuse, Mat *B)
280: {
281: PetscFunctionBegin;
282: if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B));
283: if (reuse == MAT_INITIAL_MATRIX) {
284: PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B));
285: } else if (reuse == MAT_REUSE_MATRIX) {
286: PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN));
287: }
288: PetscFunctionReturn(PETSC_SUCCESS);
289: }
291: static PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A, PetscViewer viewer)
292: {
293: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
294: PetscInt i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2;
295: PetscViewerFormat format;
296: const PetscInt *diag;
297: const char *matname;
299: PetscFunctionBegin;
300: PetscCall(PetscViewerGetFormat(viewer, &format));
301: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
302: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
303: Mat aij;
305: if (A->factortype && bs > 1) {
306: PetscCall(PetscPrintf(PETSC_COMM_SELF, "Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n"));
307: PetscFunctionReturn(PETSC_SUCCESS);
308: }
309: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij));
310: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
311: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)aij, matname));
312: PetscCall(MatView_SeqAIJ(aij, viewer));
313: PetscCall(MatDestroy(&aij));
314: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
315: Mat B;
317: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
318: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
319: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
320: PetscCall(MatView_SeqAIJ(B, viewer));
321: PetscCall(MatDestroy(&B));
322: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
323: PetscFunctionReturn(PETSC_SUCCESS);
324: } else {
325: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
326: if (A->factortype) { /* for factored matrix */
327: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "matrix is factored with bs>1. Not implemented yet");
328: PetscCall(MatGetDiagonalMarkers_SeqSBAIJ(A, &diag, NULL));
329: for (i = 0; i < a->mbs; i++) { /* for row block i */
330: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i));
331: /* diagonal entry */
332: #if defined(PETSC_USE_COMPLEX)
333: if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
334: 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]])));
335: } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
336: 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]])));
337: } else {
338: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]])));
339: }
340: #else
341: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)(1 / a->a[diag[i]])));
342: #endif
343: /* off-diagonal entries */
344: for (k = a->i[i]; k < a->i[i + 1] - 1; k++) {
345: #if defined(PETSC_USE_COMPLEX)
346: if (PetscImaginaryPart(a->a[k]) > 0.0) {
347: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), (double)PetscImaginaryPart(a->a[k])));
348: } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
349: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), -(double)PetscImaginaryPart(a->a[k])));
350: } else {
351: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k], (double)PetscRealPart(a->a[k])));
352: }
353: #else
354: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[k], (double)a->a[k]));
355: #endif
356: }
357: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
358: }
360: } else { /* for non-factored matrix */
361: for (i = 0; i < a->mbs; i++) { /* for row block i */
362: for (j = 0; j < bs; j++) { /* for row bs*i + j */
363: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j));
364: for (k = a->i[i]; k < a->i[i + 1]; k++) { /* for column block */
365: for (l = 0; l < bs; l++) { /* for column */
366: #if defined(PETSC_USE_COMPLEX)
367: if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) {
368: 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])));
369: } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) {
370: 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])));
371: } else {
372: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j])));
373: }
374: #else
375: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]));
376: #endif
377: }
378: }
379: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
380: }
381: }
382: }
383: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
384: }
385: PetscCall(PetscViewerFlush(viewer));
386: PetscFunctionReturn(PETSC_SUCCESS);
387: }
389: #include <petscdraw.h>
390: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw, void *Aa)
391: {
392: Mat A = (Mat)Aa;
393: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
394: PetscInt row, i, j, k, l, mbs = a->mbs, bs = A->rmap->bs, bs2 = a->bs2;
395: PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r;
396: MatScalar *aa;
397: PetscViewer viewer;
398: int color;
400: PetscFunctionBegin;
401: PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer));
402: PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr));
404: /* loop over matrix elements drawing boxes */
406: PetscDrawCollectiveBegin(draw);
407: PetscCall(PetscDrawString(draw, .3 * (xl + xr), .3 * (yl + yr), PETSC_DRAW_BLACK, "symmetric"));
408: /* Blue for negative, Cyan for zero and Red for positive */
409: color = PETSC_DRAW_BLUE;
410: for (i = 0, row = 0; i < mbs; i++, row += bs) {
411: for (j = a->i[i]; j < a->i[i + 1]; j++) {
412: y_l = A->rmap->N - row - 1.0;
413: y_r = y_l + 1.0;
414: x_l = a->j[j] * bs;
415: x_r = x_l + 1.0;
416: aa = a->a + j * bs2;
417: for (k = 0; k < bs; k++) {
418: for (l = 0; l < bs; l++) {
419: if (PetscRealPart(*aa++) >= 0.) continue;
420: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
421: }
422: }
423: }
424: }
425: color = PETSC_DRAW_CYAN;
426: for (i = 0, row = 0; i < mbs; i++, row += bs) {
427: for (j = a->i[i]; j < a->i[i + 1]; j++) {
428: y_l = A->rmap->N - row - 1.0;
429: y_r = y_l + 1.0;
430: x_l = a->j[j] * bs;
431: x_r = x_l + 1.0;
432: aa = a->a + j * bs2;
433: for (k = 0; k < bs; k++) {
434: for (l = 0; l < bs; l++) {
435: if (PetscRealPart(*aa++) != 0.) continue;
436: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
437: }
438: }
439: }
440: }
441: color = PETSC_DRAW_RED;
442: for (i = 0, row = 0; i < mbs; i++, row += bs) {
443: for (j = a->i[i]; j < a->i[i + 1]; j++) {
444: y_l = A->rmap->N - row - 1.0;
445: y_r = y_l + 1.0;
446: x_l = a->j[j] * bs;
447: x_r = x_l + 1.0;
448: aa = a->a + j * bs2;
449: for (k = 0; k < bs; k++) {
450: for (l = 0; l < bs; l++) {
451: if (PetscRealPart(*aa++) <= 0.) continue;
452: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
453: }
454: }
455: }
456: }
457: PetscDrawCollectiveEnd(draw);
458: PetscFunctionReturn(PETSC_SUCCESS);
459: }
461: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A, PetscViewer viewer)
462: {
463: PetscReal xl, yl, xr, yr, w, h;
464: PetscDraw draw;
465: PetscBool isnull;
467: PetscFunctionBegin;
468: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
469: PetscCall(PetscDrawIsNull(draw, &isnull));
470: if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
472: xr = A->rmap->N;
473: yr = A->rmap->N;
474: h = yr / 10.0;
475: w = xr / 10.0;
476: xr += w;
477: yr += h;
478: xl = -w;
479: yl = -h;
480: PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr));
481: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer));
482: PetscCall(PetscDrawZoom(draw, MatView_SeqSBAIJ_Draw_Zoom, A));
483: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL));
484: PetscCall(PetscDrawSave(draw));
485: PetscFunctionReturn(PETSC_SUCCESS);
486: }
488: /* Used for both MPIBAIJ and MPISBAIJ matrices */
489: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary
491: PetscErrorCode MatView_SeqSBAIJ(Mat A, PetscViewer viewer)
492: {
493: PetscBool isascii, isbinary, isdraw;
495: PetscFunctionBegin;
496: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
497: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
498: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
499: if (isascii) {
500: PetscCall(MatView_SeqSBAIJ_ASCII(A, viewer));
501: } else if (isbinary) {
502: PetscCall(MatView_SeqSBAIJ_Binary(A, viewer));
503: } else if (isdraw) {
504: PetscCall(MatView_SeqSBAIJ_Draw(A, viewer));
505: } else {
506: Mat B;
507: const char *matname;
508: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
509: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
510: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
511: PetscCall(MatView(B, viewer));
512: PetscCall(MatDestroy(&B));
513: }
514: PetscFunctionReturn(PETSC_SUCCESS);
515: }
517: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[])
518: {
519: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
520: PetscInt *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j;
521: PetscInt *ai = a->i, *ailen = a->ilen;
522: PetscInt brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2;
523: MatScalar *ap, *aa = a->a;
525: PetscFunctionBegin;
526: for (k = 0; k < m; k++) { /* loop over rows */
527: row = im[k];
528: brow = row / bs;
529: if (row < 0) {
530: v += n;
531: continue;
532: } /* negative row */
533: 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);
534: rp = aj + ai[brow];
535: ap = aa + bs2 * ai[brow];
536: nrow = ailen[brow];
537: for (l = 0; l < n; l++) { /* loop over columns */
538: if (in[l] < 0) {
539: v++;
540: continue;
541: } /* negative column */
542: 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);
543: col = in[l];
544: bcol = col / bs;
545: cidx = col % bs;
546: ridx = row % bs;
547: high = nrow;
548: low = 0; /* assume unsorted */
549: while (high - low > 5) {
550: t = (low + high) / 2;
551: if (rp[t] > bcol) high = t;
552: else low = t;
553: }
554: for (i = low; i < high; i++) {
555: if (rp[i] > bcol) break;
556: if (rp[i] == bcol) {
557: *v++ = ap[bs2 * i + bs * cidx + ridx];
558: goto finished;
559: }
560: }
561: *v++ = 0.0;
562: finished:;
563: }
564: }
565: PetscFunctionReturn(PETSC_SUCCESS);
566: }
568: static PetscErrorCode MatPermute_SeqSBAIJ(Mat A, IS rowp, IS colp, Mat *B)
569: {
570: Mat C;
571: PetscBool flg = (PetscBool)(rowp == colp);
573: PetscFunctionBegin;
574: PetscCall(MatConvert(A, MATSEQBAIJ, MAT_INITIAL_MATRIX, &C));
575: PetscCall(MatPermute(C, rowp, colp, B));
576: PetscCall(MatDestroy(&C));
577: if (!flg) PetscCall(ISEqual(rowp, colp, &flg));
578: if (flg) PetscCall(MatConvert(*B, MATSEQSBAIJ, MAT_INPLACE_MATRIX, B));
579: PetscFunctionReturn(PETSC_SUCCESS);
580: }
582: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
583: {
584: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
585: PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1;
586: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
587: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval;
588: PetscBool roworiented = a->roworiented;
589: const PetscScalar *value = v;
590: MatScalar *ap, *aa = a->a, *bap;
592: PetscFunctionBegin;
593: if (roworiented) stepval = (n - 1) * bs;
594: else stepval = (m - 1) * bs;
595: for (k = 0; k < m; k++) { /* loop over added rows */
596: row = im[k];
597: if (row < 0) continue;
598: 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);
599: rp = aj + ai[row];
600: ap = aa + bs2 * ai[row];
601: rmax = imax[row];
602: nrow = ailen[row];
603: low = 0;
604: high = nrow;
605: for (l = 0; l < n; l++) { /* loop over added columns */
606: if (in[l] < 0) continue;
607: col = in[l];
608: 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);
609: if (col < row) {
610: PetscCheck(a->ignore_ltriangular, 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)");
611: continue; /* ignore lower triangular block */
612: }
613: if (roworiented) value = v + k * (stepval + bs) * bs + l * bs;
614: else value = v + l * (stepval + bs) * bs + k * bs;
616: if (col <= lastcol) low = 0;
617: else high = nrow;
619: lastcol = col;
620: while (high - low > 7) {
621: t = (low + high) / 2;
622: if (rp[t] > col) high = t;
623: else low = t;
624: }
625: for (i = low; i < high; i++) {
626: if (rp[i] > col) break;
627: if (rp[i] == col) {
628: bap = ap + bs2 * i;
629: if (roworiented) {
630: if (is == ADD_VALUES) {
631: for (ii = 0; ii < bs; ii++, value += stepval) {
632: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
633: }
634: } else {
635: for (ii = 0; ii < bs; ii++, value += stepval) {
636: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
637: }
638: }
639: } else {
640: if (is == ADD_VALUES) {
641: for (ii = 0; ii < bs; ii++, value += stepval) {
642: for (jj = 0; jj < bs; jj++) *bap++ += *value++;
643: }
644: } else {
645: for (ii = 0; ii < bs; ii++, value += stepval) {
646: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
647: }
648: }
649: }
650: goto noinsert2;
651: }
652: }
653: if (nonew == 1) goto noinsert2;
654: 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);
655: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
656: N = nrow++ - 1;
657: high++;
658: /* shift up all the later entries in this row */
659: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
660: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
661: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
662: rp[i] = col;
663: bap = ap + bs2 * i;
664: if (roworiented) {
665: for (ii = 0; ii < bs; ii++, value += stepval) {
666: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
667: }
668: } else {
669: for (ii = 0; ii < bs; ii++, value += stepval) {
670: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
671: }
672: }
673: noinsert2:;
674: low = i;
675: }
676: ailen[row] = nrow;
677: }
678: PetscFunctionReturn(PETSC_SUCCESS);
679: }
681: static PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A, MatAssemblyType mode)
682: {
683: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
684: PetscInt fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax;
685: PetscInt m = A->rmap->N, *ip, N, *ailen = a->ilen;
686: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
687: MatScalar *aa = a->a, *ap;
689: PetscFunctionBegin;
690: if (mode == MAT_FLUSH_ASSEMBLY || (A->was_assembled && A->ass_nonzerostate == A->nonzerostate)) PetscFunctionReturn(PETSC_SUCCESS);
692: if (m) rmax = ailen[0];
693: for (i = 1; i < mbs; i++) {
694: /* move each row back by the amount of empty slots (fshift) before it*/
695: fshift += imax[i - 1] - ailen[i - 1];
696: rmax = PetscMax(rmax, ailen[i]);
697: if (fshift) {
698: ip = aj + ai[i];
699: ap = aa + bs2 * ai[i];
700: N = ailen[i];
701: PetscCall(PetscArraymove(ip - fshift, ip, N));
702: PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2 * N));
703: }
704: ai[i] = ai[i - 1] + ailen[i - 1];
705: }
706: if (mbs) {
707: fshift += imax[mbs - 1] - ailen[mbs - 1];
708: ai[mbs] = ai[mbs - 1] + ailen[mbs - 1];
709: }
710: /* reset ilen and imax for each row */
711: for (i = 0; i < mbs; i++) ailen[i] = imax[i] = ai[i + 1] - ai[i];
712: a->nz = ai[mbs];
714: 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);
716: 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));
717: PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs));
718: PetscCall(PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax));
720: A->info.mallocs += a->reallocs;
721: a->reallocs = 0;
722: A->info.nz_unneeded = (PetscReal)fshift * bs2;
723: a->idiagvalid = PETSC_FALSE;
724: a->rmax = rmax;
726: if (A->cmap->n < 65536 && A->cmap->bs == 1) {
727: if (a->jshort && a->free_jshort) {
728: /* when matrix data structure is changed, previous jshort must be replaced */
729: PetscCall(PetscFree(a->jshort));
730: }
731: PetscCall(PetscMalloc1(a->i[A->rmap->n], &a->jshort));
732: for (i = 0; i < a->i[A->rmap->n]; i++) a->jshort[i] = (short)a->j[i];
733: A->ops->mult = MatMult_SeqSBAIJ_1_ushort;
734: A->ops->sor = MatSOR_SeqSBAIJ_ushort;
735: a->free_jshort = PETSC_TRUE;
736: }
737: PetscFunctionReturn(PETSC_SUCCESS);
738: }
740: /* Only add/insert a(i,j) with i<=j (blocks).
741: Any a(i,j) with i>j input by user is ignored.
742: */
744: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
745: {
746: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
747: PetscInt *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1;
748: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen, roworiented = a->roworiented;
749: PetscInt *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol;
750: PetscInt ridx, cidx, bs2 = a->bs2;
751: MatScalar *ap, value, *aa = a->a, *bap;
753: PetscFunctionBegin;
754: for (k = 0; k < m; k++) { /* loop over added rows */
755: row = im[k]; /* row number */
756: brow = row / bs; /* block row number */
757: if (row < 0) continue;
758: 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);
759: rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
760: ap = aa + bs2 * ai[brow]; /*ptr to beginning of element value of the row block*/
761: rmax = imax[brow]; /* maximum space allocated for this row */
762: nrow = ailen[brow]; /* actual length of this row */
763: low = 0;
764: high = nrow;
765: for (l = 0; l < n; l++) { /* loop over added columns */
766: if (in[l] < 0) continue;
767: 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);
768: col = in[l];
769: bcol = col / bs; /* block col number */
771: if (brow > bcol) {
772: PetscCheck(a->ignore_ltriangular, 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)");
773: continue; /* ignore lower triangular values */
774: }
776: ridx = row % bs;
777: cidx = col % bs; /*row and col index inside the block */
778: if ((brow == bcol && ridx <= cidx) || (brow < bcol)) {
779: /* element value a(k,l) */
780: if (roworiented) value = v[l + k * n];
781: else value = v[k + l * m];
783: /* move pointer bap to a(k,l) quickly and add/insert value */
784: if (col <= lastcol) low = 0;
785: else high = nrow;
787: lastcol = col;
788: while (high - low > 7) {
789: t = (low + high) / 2;
790: if (rp[t] > bcol) high = t;
791: else low = t;
792: }
793: for (i = low; i < high; i++) {
794: if (rp[i] > bcol) break;
795: if (rp[i] == bcol) {
796: bap = ap + bs2 * i + bs * cidx + ridx;
797: if (is == ADD_VALUES) *bap += value;
798: else *bap = value;
799: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
800: if (brow == bcol && ridx < cidx) {
801: bap = ap + bs2 * i + bs * ridx + cidx;
802: if (is == ADD_VALUES) *bap += value;
803: else *bap = value;
804: }
805: goto noinsert1;
806: }
807: }
809: if (nonew == 1) goto noinsert1;
810: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
811: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
813: N = nrow++ - 1;
814: high++;
815: /* shift up all the later entries in this row */
816: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
817: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
818: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
819: rp[i] = bcol;
820: ap[bs2 * i + bs * cidx + ridx] = value;
821: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
822: if (brow == bcol && ridx < cidx) ap[bs2 * i + bs * ridx + cidx] = value;
823: noinsert1:;
824: low = i;
825: }
826: } /* end of loop over added columns */
827: ailen[brow] = nrow;
828: } /* end of loop over added rows */
829: PetscFunctionReturn(PETSC_SUCCESS);
830: }
832: static PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA, IS row, const MatFactorInfo *info)
833: {
834: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inA->data;
835: Mat outA;
836: PetscBool row_identity;
838: PetscFunctionBegin;
839: PetscCheck(info->levels == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only levels=0 is supported for in-place icc");
840: PetscCall(ISIdentity(row, &row_identity));
841: PetscCheck(row_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported");
842: 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()! */
844: outA = inA;
845: PetscCall(PetscFree(inA->solvertype));
846: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype));
848: inA->factortype = MAT_FACTOR_ICC;
849: PetscCall(MatSeqSBAIJSetNumericFactorization_inplace(inA, row_identity));
851: PetscCall(PetscObjectReference((PetscObject)row));
852: PetscCall(ISDestroy(&a->row));
853: a->row = row;
854: PetscCall(PetscObjectReference((PetscObject)row));
855: PetscCall(ISDestroy(&a->col));
856: a->col = row;
858: /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
859: if (a->icol) PetscCall(ISInvertPermutation(row, PETSC_DECIDE, &a->icol));
861: if (!a->solve_work) PetscCall(PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work));
863: PetscCall(MatCholeskyFactorNumeric(outA, inA, info));
864: PetscFunctionReturn(PETSC_SUCCESS);
865: }
867: static PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat, PetscInt *indices)
868: {
869: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
870: PetscInt i, nz, n;
872: PetscFunctionBegin;
873: nz = baij->maxnz;
874: n = mat->cmap->n;
875: for (i = 0; i < nz; i++) baij->j[i] = indices[i];
877: baij->nz = nz;
878: for (i = 0; i < n; i++) baij->ilen[i] = baij->imax[i];
880: PetscCall(MatSetOption(mat, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
881: PetscFunctionReturn(PETSC_SUCCESS);
882: }
884: /*@
885: MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
886: in a `MATSEQSBAIJ` matrix.
888: Input Parameters:
889: + mat - the `MATSEQSBAIJ` matrix
890: - indices - the column indices
892: Level: advanced
894: Notes:
895: This can be called if you have precomputed the nonzero structure of the
896: matrix and want to provide it to the matrix object to improve the performance
897: of the `MatSetValues()` operation.
899: You MUST have set the correct numbers of nonzeros per row in the call to
900: `MatCreateSeqSBAIJ()`, and the columns indices MUST be sorted.
902: MUST be called before any calls to `MatSetValues()`
904: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ`
905: @*/
906: PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat, PetscInt *indices)
907: {
908: PetscFunctionBegin;
910: PetscAssertPointer(indices, 2);
911: PetscUseMethod(mat, "MatSeqSBAIJSetColumnIndices_C", (Mat, PetscInt *), (mat, indices));
912: PetscFunctionReturn(PETSC_SUCCESS);
913: }
915: static PetscErrorCode MatCopy_SeqSBAIJ(Mat A, Mat B, MatStructure str)
916: {
917: PetscBool isbaij;
919: PetscFunctionBegin;
920: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, ""));
921: PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name);
922: /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
923: if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
924: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
925: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
927: PetscCheck(a->i[a->mbs] == b->i[b->mbs], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzeros in two matrices are different");
928: PetscCheck(a->mbs == b->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of rows in two matrices are different");
929: PetscCheck(a->bs2 == b->bs2, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Different block size");
930: PetscCall(PetscArraycpy(b->a, a->a, a->bs2 * a->i[a->mbs]));
931: PetscCall(PetscObjectStateIncrease((PetscObject)B));
932: } else {
933: PetscCall(MatGetRowUpperTriangular(A));
934: PetscCall(MatCopy_Basic(A, B, str));
935: PetscCall(MatRestoreRowUpperTriangular(A));
936: }
937: PetscFunctionReturn(PETSC_SUCCESS);
938: }
940: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A, PetscScalar *array[])
941: {
942: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
944: PetscFunctionBegin;
945: *array = a->a;
946: PetscFunctionReturn(PETSC_SUCCESS);
947: }
949: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A, PetscScalar *array[])
950: {
951: PetscFunctionBegin;
952: *array = NULL;
953: PetscFunctionReturn(PETSC_SUCCESS);
954: }
956: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y, Mat X, PetscInt *nnz)
957: {
958: PetscInt bs = Y->rmap->bs, mbs = Y->rmap->N / bs;
959: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data;
960: Mat_SeqSBAIJ *y = (Mat_SeqSBAIJ *)Y->data;
962: PetscFunctionBegin;
963: /* Set the number of nonzeros in the new matrix */
964: PetscCall(MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz));
965: PetscFunctionReturn(PETSC_SUCCESS);
966: }
968: static PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
969: {
970: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data, *y = (Mat_SeqSBAIJ *)Y->data;
971: PetscInt bs = Y->rmap->bs, bs2 = bs * bs;
972: PetscBLASInt one = 1;
974: PetscFunctionBegin;
975: if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
976: PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
977: if (e) {
978: PetscCall(PetscArraycmp(x->i, y->i, x->mbs + 1, &e));
979: if (e) {
980: PetscCall(PetscArraycmp(x->j, y->j, x->i[x->mbs], &e));
981: if (e) str = SAME_NONZERO_PATTERN;
982: }
983: }
984: if (!e) PetscCheck(str != SAME_NONZERO_PATTERN, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "MatStructure is not SAME_NONZERO_PATTERN");
985: }
986: if (str == SAME_NONZERO_PATTERN) {
987: PetscScalar alpha = a;
988: PetscBLASInt bnz;
989: PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
990: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
991: PetscCall(PetscObjectStateIncrease((PetscObject)Y));
992: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
993: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
994: PetscCall(MatAXPY_Basic(Y, a, X, str));
995: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
996: } else {
997: Mat B;
998: PetscInt *nnz;
999: PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size");
1000: PetscCall(MatGetRowUpperTriangular(X));
1001: PetscCall(MatGetRowUpperTriangular(Y));
1002: PetscCall(PetscMalloc1(Y->rmap->N, &nnz));
1003: PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1004: PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1005: PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1006: PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1007: PetscCall(MatSetType(B, ((PetscObject)Y)->type_name));
1008: PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(Y, X, nnz));
1009: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1011: PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
1013: PetscCall(MatHeaderMerge(Y, &B));
1014: PetscCall(PetscFree(nnz));
1015: PetscCall(MatRestoreRowUpperTriangular(X));
1016: PetscCall(MatRestoreRowUpperTriangular(Y));
1017: }
1018: PetscFunctionReturn(PETSC_SUCCESS);
1019: }
1021: static PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A, PetscBool *flg)
1022: {
1023: PetscFunctionBegin;
1024: *flg = PETSC_TRUE;
1025: PetscFunctionReturn(PETSC_SUCCESS);
1026: }
1028: static PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
1029: {
1030: #if defined(PETSC_USE_COMPLEX)
1031: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1032: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1033: MatScalar *aa = a->a;
1035: PetscFunctionBegin;
1036: for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]);
1037: #else
1038: PetscFunctionBegin;
1039: #endif
1040: PetscFunctionReturn(PETSC_SUCCESS);
1041: }
1043: static PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1044: {
1045: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1046: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1047: MatScalar *aa = a->a;
1049: PetscFunctionBegin;
1050: for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]);
1051: PetscFunctionReturn(PETSC_SUCCESS);
1052: }
1054: static PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1055: {
1056: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1057: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1058: MatScalar *aa = a->a;
1060: PetscFunctionBegin;
1061: for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1062: PetscFunctionReturn(PETSC_SUCCESS);
1063: }
1065: static PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b)
1066: {
1067: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)A->data;
1068: PetscInt i, j, k, count;
1069: PetscInt bs = A->rmap->bs, bs2 = baij->bs2, row, col;
1070: PetscScalar zero = 0.0;
1071: MatScalar *aa;
1072: const PetscScalar *xx;
1073: PetscScalar *bb;
1074: PetscBool *zeroed, vecs = PETSC_FALSE;
1076: PetscFunctionBegin;
1077: /* fix right-hand side if needed */
1078: if (x && b) {
1079: PetscCall(VecGetArrayRead(x, &xx));
1080: PetscCall(VecGetArray(b, &bb));
1081: vecs = PETSC_TRUE;
1082: }
1084: /* zero the columns */
1085: PetscCall(PetscCalloc1(A->rmap->n, &zeroed));
1086: for (i = 0; i < is_n; i++) {
1087: 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]);
1088: zeroed[is_idx[i]] = PETSC_TRUE;
1089: }
1090: if (vecs) {
1091: for (i = 0; i < A->rmap->N; i++) {
1092: row = i / bs;
1093: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1094: for (k = 0; k < bs; k++) {
1095: col = bs * baij->j[j] + k;
1096: if (col <= i) continue;
1097: aa = baij->a + j * bs2 + (i % bs) + bs * k;
1098: if (!zeroed[i] && zeroed[col]) bb[i] -= aa[0] * xx[col];
1099: if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0] * xx[i];
1100: }
1101: }
1102: }
1103: for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]];
1104: }
1106: for (i = 0; i < A->rmap->N; i++) {
1107: if (!zeroed[i]) {
1108: row = i / bs;
1109: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1110: for (k = 0; k < bs; k++) {
1111: col = bs * baij->j[j] + k;
1112: if (zeroed[col]) {
1113: aa = baij->a + j * bs2 + (i % bs) + bs * k;
1114: aa[0] = 0.0;
1115: }
1116: }
1117: }
1118: }
1119: }
1120: PetscCall(PetscFree(zeroed));
1121: if (vecs) {
1122: PetscCall(VecRestoreArrayRead(x, &xx));
1123: PetscCall(VecRestoreArray(b, &bb));
1124: }
1126: /* zero the rows */
1127: for (i = 0; i < is_n; i++) {
1128: row = is_idx[i];
1129: count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1130: aa = baij->a + baij->i[row / bs] * bs2 + (row % bs);
1131: for (k = 0; k < count; k++) {
1132: aa[0] = zero;
1133: aa += bs;
1134: }
1135: if (diag != 0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES);
1136: }
1137: PetscCall(MatAssemblyEnd_SeqSBAIJ(A, MAT_FINAL_ASSEMBLY));
1138: PetscFunctionReturn(PETSC_SUCCESS);
1139: }
1141: static PetscErrorCode MatShift_SeqSBAIJ(Mat Y, PetscScalar a)
1142: {
1143: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)Y->data;
1145: PetscFunctionBegin;
1146: if (!Y->preallocated || !aij->nz) PetscCall(MatSeqSBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL));
1147: PetscCall(MatShift_Basic(Y, a));
1148: PetscFunctionReturn(PETSC_SUCCESS);
1149: }
1151: PetscErrorCode MatEliminateZeros_SeqSBAIJ(Mat A, PetscBool keep)
1152: {
1153: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1154: PetscInt fshift = 0, fshift_prev = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax, j, k;
1155: PetscInt m = A->rmap->N, *ailen = a->ilen;
1156: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
1157: MatScalar *aa = a->a, *ap;
1158: PetscBool zero;
1160: PetscFunctionBegin;
1161: PetscCheck(A->assembled, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Cannot eliminate zeros for unassembled matrix");
1162: if (m) rmax = ailen[0];
1163: for (i = 1; i <= mbs; i++) {
1164: for (k = ai[i - 1]; k < ai[i]; k++) {
1165: zero = PETSC_TRUE;
1166: ap = aa + bs2 * k;
1167: for (j = 0; j < bs2 && zero; j++) {
1168: if (ap[j] != 0.0) zero = PETSC_FALSE;
1169: }
1170: if (zero && (aj[k] != i - 1 || !keep)) fshift++;
1171: else {
1172: if (zero && aj[k] == i - 1) PetscCall(PetscInfo(A, "Keep the diagonal block at row %" PetscInt_FMT "\n", i - 1));
1173: aj[k - fshift] = aj[k];
1174: PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2));
1175: }
1176: }
1177: ai[i - 1] -= fshift_prev;
1178: fshift_prev = fshift;
1179: ailen[i - 1] = imax[i - 1] = ai[i] - fshift - ai[i - 1];
1180: a->nonzerorowcnt += ((ai[i] - fshift - ai[i - 1]) > 0);
1181: rmax = PetscMax(rmax, ailen[i - 1]);
1182: }
1183: if (fshift) {
1184: if (mbs) {
1185: ai[mbs] -= fshift;
1186: a->nz = ai[mbs];
1187: }
1188: 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));
1189: A->nonzerostate++;
1190: A->info.nz_unneeded += (PetscReal)fshift;
1191: a->rmax = rmax;
1192: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
1193: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
1194: }
1195: PetscFunctionReturn(PETSC_SUCCESS);
1196: }
1198: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1199: MatGetRow_SeqSBAIJ,
1200: MatRestoreRow_SeqSBAIJ,
1201: MatMult_SeqSBAIJ_N,
1202: /* 4*/ MatMultAdd_SeqSBAIJ_N,
1203: MatMult_SeqSBAIJ_N, /* transpose versions are same as non-transpose versions */
1204: MatMultAdd_SeqSBAIJ_N,
1205: NULL,
1206: NULL,
1207: NULL,
1208: /* 10*/ NULL,
1209: NULL,
1210: MatCholeskyFactor_SeqSBAIJ,
1211: MatSOR_SeqSBAIJ,
1212: MatTranspose_SeqSBAIJ,
1213: /* 15*/ MatGetInfo_SeqSBAIJ,
1214: MatEqual_SeqSBAIJ,
1215: MatGetDiagonal_SeqSBAIJ,
1216: MatDiagonalScale_SeqSBAIJ,
1217: MatNorm_SeqSBAIJ,
1218: /* 20*/ NULL,
1219: MatAssemblyEnd_SeqSBAIJ,
1220: MatSetOption_SeqSBAIJ,
1221: MatZeroEntries_SeqSBAIJ,
1222: /* 24*/ NULL,
1223: NULL,
1224: NULL,
1225: NULL,
1226: NULL,
1227: /* 29*/ MatSetUp_Seq_Hash,
1228: NULL,
1229: NULL,
1230: NULL,
1231: NULL,
1232: /* 34*/ MatDuplicate_SeqSBAIJ,
1233: NULL,
1234: NULL,
1235: NULL,
1236: MatICCFactor_SeqSBAIJ,
1237: /* 39*/ MatAXPY_SeqSBAIJ,
1238: MatCreateSubMatrices_SeqSBAIJ,
1239: MatIncreaseOverlap_SeqSBAIJ,
1240: MatGetValues_SeqSBAIJ,
1241: MatCopy_SeqSBAIJ,
1242: /* 44*/ NULL,
1243: MatScale_SeqSBAIJ,
1244: MatShift_SeqSBAIJ,
1245: NULL,
1246: MatZeroRowsColumns_SeqSBAIJ,
1247: /* 49*/ NULL,
1248: MatGetRowIJ_SeqSBAIJ,
1249: MatRestoreRowIJ_SeqSBAIJ,
1250: NULL,
1251: NULL,
1252: /* 54*/ NULL,
1253: NULL,
1254: NULL,
1255: MatPermute_SeqSBAIJ,
1256: MatSetValuesBlocked_SeqSBAIJ,
1257: /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
1258: NULL,
1259: NULL,
1260: NULL,
1261: NULL,
1262: /* 64*/ NULL,
1263: NULL,
1264: NULL,
1265: NULL,
1266: MatGetRowMaxAbs_SeqSBAIJ,
1267: /* 69*/ NULL,
1268: MatConvert_MPISBAIJ_Basic,
1269: NULL,
1270: NULL,
1271: NULL,
1272: /* 74*/ NULL,
1273: NULL,
1274: NULL,
1275: MatGetInertia_SeqSBAIJ,
1276: MatLoad_SeqSBAIJ,
1277: /* 79*/ NULL,
1278: NULL,
1279: MatIsStructurallySymmetric_SeqSBAIJ,
1280: NULL,
1281: NULL,
1282: /* 84*/ NULL,
1283: NULL,
1284: NULL,
1285: NULL,
1286: NULL,
1287: /* 89*/ NULL,
1288: NULL,
1289: NULL,
1290: NULL,
1291: MatConjugate_SeqSBAIJ,
1292: /* 94*/ NULL,
1293: NULL,
1294: MatRealPart_SeqSBAIJ,
1295: MatImaginaryPart_SeqSBAIJ,
1296: MatGetRowUpperTriangular_SeqSBAIJ,
1297: /* 99*/ MatRestoreRowUpperTriangular_SeqSBAIJ,
1298: NULL,
1299: NULL,
1300: NULL,
1301: NULL,
1302: /*104*/ NULL,
1303: NULL,
1304: NULL,
1305: NULL,
1306: NULL,
1307: /*109*/ NULL,
1308: NULL,
1309: NULL,
1310: NULL,
1311: NULL,
1312: /*114*/ NULL,
1313: NULL,
1314: NULL,
1315: NULL,
1316: NULL,
1317: /*119*/ NULL,
1318: NULL,
1319: NULL,
1320: NULL,
1321: NULL,
1322: /*124*/ NULL,
1323: NULL,
1324: MatSetBlockSizes_Default,
1325: NULL,
1326: NULL,
1327: /*129*/ NULL,
1328: MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
1329: NULL,
1330: NULL,
1331: NULL,
1332: /*134*/ NULL,
1333: NULL,
1334: MatEliminateZeros_SeqSBAIJ,
1335: NULL,
1336: NULL,
1337: /*139*/ NULL,
1338: NULL,
1339: MatCopyHashToXAIJ_Seq_Hash,
1340: NULL,
1341: NULL};
1343: static PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat)
1344: {
1345: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1346: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1348: PetscFunctionBegin;
1349: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1351: /* allocate space for values if not already there */
1352: if (!aij->saved_values) PetscCall(PetscMalloc1(nz + 1, &aij->saved_values));
1354: /* copy values over */
1355: PetscCall(PetscArraycpy(aij->saved_values, aij->a, nz));
1356: PetscFunctionReturn(PETSC_SUCCESS);
1357: }
1359: static PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat)
1360: {
1361: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1362: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1364: PetscFunctionBegin;
1365: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1366: PetscCheck(aij->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first");
1368: /* copy values over */
1369: PetscCall(PetscArraycpy(aij->a, aij->saved_values, nz));
1370: PetscFunctionReturn(PETSC_SUCCESS);
1371: }
1373: static PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
1374: {
1375: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1376: PetscInt i, mbs, nbs, bs2;
1377: PetscBool skipallocation = PETSC_FALSE, flg = PETSC_FALSE, realalloc = PETSC_FALSE;
1379: PetscFunctionBegin;
1380: if (B->hash_active) {
1381: PetscInt bs;
1382: B->ops[0] = b->cops;
1383: PetscCall(PetscHMapIJVDestroy(&b->ht));
1384: PetscCall(MatGetBlockSize(B, &bs));
1385: if (bs > 1) PetscCall(PetscHSetIJDestroy(&b->bht));
1386: PetscCall(PetscFree(b->dnz));
1387: PetscCall(PetscFree(b->bdnz));
1388: B->hash_active = PETSC_FALSE;
1389: }
1390: if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
1392: PetscCall(MatSetBlockSize(B, bs));
1393: PetscCall(PetscLayoutSetUp(B->rmap));
1394: PetscCall(PetscLayoutSetUp(B->cmap));
1395: 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);
1396: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1398: B->preallocated = PETSC_TRUE;
1400: mbs = B->rmap->N / bs;
1401: nbs = B->cmap->n / bs;
1402: bs2 = bs * bs;
1404: 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");
1406: if (nz == MAT_SKIP_ALLOCATION) {
1407: skipallocation = PETSC_TRUE;
1408: nz = 0;
1409: }
1411: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1412: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nz cannot be less than 0: value %" PetscInt_FMT, nz);
1413: if (nnz) {
1414: for (i = 0; i < mbs; i++) {
1415: 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]);
1416: 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);
1417: }
1418: }
1420: B->ops->mult = MatMult_SeqSBAIJ_N;
1421: B->ops->multadd = MatMultAdd_SeqSBAIJ_N;
1422: B->ops->multtranspose = MatMult_SeqSBAIJ_N;
1423: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;
1425: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1426: if (!flg) {
1427: switch (bs) {
1428: case 1:
1429: B->ops->mult = MatMult_SeqSBAIJ_1;
1430: B->ops->multadd = MatMultAdd_SeqSBAIJ_1;
1431: B->ops->multtranspose = MatMult_SeqSBAIJ_1;
1432: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1433: break;
1434: case 2:
1435: B->ops->mult = MatMult_SeqSBAIJ_2;
1436: B->ops->multadd = MatMultAdd_SeqSBAIJ_2;
1437: B->ops->multtranspose = MatMult_SeqSBAIJ_2;
1438: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1439: break;
1440: case 3:
1441: B->ops->mult = MatMult_SeqSBAIJ_3;
1442: B->ops->multadd = MatMultAdd_SeqSBAIJ_3;
1443: B->ops->multtranspose = MatMult_SeqSBAIJ_3;
1444: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1445: break;
1446: case 4:
1447: B->ops->mult = MatMult_SeqSBAIJ_4;
1448: B->ops->multadd = MatMultAdd_SeqSBAIJ_4;
1449: B->ops->multtranspose = MatMult_SeqSBAIJ_4;
1450: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1451: break;
1452: case 5:
1453: B->ops->mult = MatMult_SeqSBAIJ_5;
1454: B->ops->multadd = MatMultAdd_SeqSBAIJ_5;
1455: B->ops->multtranspose = MatMult_SeqSBAIJ_5;
1456: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1457: break;
1458: case 6:
1459: B->ops->mult = MatMult_SeqSBAIJ_6;
1460: B->ops->multadd = MatMultAdd_SeqSBAIJ_6;
1461: B->ops->multtranspose = MatMult_SeqSBAIJ_6;
1462: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1463: break;
1464: case 7:
1465: B->ops->mult = MatMult_SeqSBAIJ_7;
1466: B->ops->multadd = MatMultAdd_SeqSBAIJ_7;
1467: B->ops->multtranspose = MatMult_SeqSBAIJ_7;
1468: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1469: break;
1470: }
1471: }
1473: b->mbs = mbs;
1474: b->nbs = nbs;
1475: if (!skipallocation) {
1476: if (!b->imax) {
1477: PetscCall(PetscMalloc2(mbs, &b->imax, mbs, &b->ilen));
1479: b->free_imax_ilen = PETSC_TRUE;
1480: }
1481: if (!nnz) {
1482: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1483: else if (nz <= 0) nz = 1;
1484: nz = PetscMin(nbs, nz);
1485: for (i = 0; i < mbs; i++) b->imax[i] = nz;
1486: PetscCall(PetscIntMultError(nz, mbs, &nz));
1487: } else {
1488: PetscInt64 nz64 = 0;
1489: for (i = 0; i < mbs; i++) {
1490: b->imax[i] = nnz[i];
1491: nz64 += nnz[i];
1492: }
1493: PetscCall(PetscIntCast(nz64, &nz));
1494: }
1495: /* b->ilen will count nonzeros in each block row so far. */
1496: for (i = 0; i < mbs; i++) b->ilen[i] = 0;
1497: /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */
1499: /* allocate the matrix space */
1500: PetscCall(MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i));
1501: PetscCall(PetscShmgetAllocateArray(bs2 * nz, sizeof(PetscScalar), (void **)&b->a));
1502: PetscCall(PetscShmgetAllocateArray(nz, sizeof(PetscInt), (void **)&b->j));
1503: PetscCall(PetscShmgetAllocateArray(B->rmap->n + 1, sizeof(PetscInt), (void **)&b->i));
1504: b->free_a = PETSC_TRUE;
1505: b->free_ij = PETSC_TRUE;
1506: PetscCall(PetscArrayzero(b->a, nz * bs2));
1507: PetscCall(PetscArrayzero(b->j, nz));
1508: b->free_a = PETSC_TRUE;
1509: b->free_ij = PETSC_TRUE;
1511: /* pointer to beginning of each row */
1512: b->i[0] = 0;
1513: for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1];
1515: } else {
1516: b->free_a = PETSC_FALSE;
1517: b->free_ij = PETSC_FALSE;
1518: }
1520: b->bs2 = bs2;
1521: b->nz = 0;
1522: b->maxnz = nz;
1523: b->inew = NULL;
1524: b->jnew = NULL;
1525: b->anew = NULL;
1526: b->a2anew = NULL;
1527: b->permute = PETSC_FALSE;
1529: B->was_assembled = PETSC_FALSE;
1530: B->assembled = PETSC_FALSE;
1531: if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE));
1532: PetscFunctionReturn(PETSC_SUCCESS);
1533: }
1535: static PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
1536: {
1537: PetscInt i, j, m, nz, anz, nz_max = 0, *nnz;
1538: PetscScalar *values = NULL;
1539: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1540: PetscBool roworiented = b->roworiented;
1541: PetscBool ilw = b->ignore_ltriangular;
1543: PetscFunctionBegin;
1544: PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs);
1545: PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
1546: PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
1547: PetscCall(PetscLayoutSetUp(B->rmap));
1548: PetscCall(PetscLayoutSetUp(B->cmap));
1549: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1550: m = B->rmap->n / bs;
1552: PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
1553: PetscCall(PetscMalloc1(m + 1, &nnz));
1554: for (i = 0; i < m; i++) {
1555: nz = ii[i + 1] - ii[i];
1556: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
1557: PetscCheckSorted(nz, jj + ii[i]);
1558: anz = 0;
1559: for (j = 0; j < nz; j++) {
1560: /* count only values on the diagonal or above */
1561: if (jj[ii[i] + j] >= i) {
1562: anz = nz - j;
1563: break;
1564: }
1565: }
1566: nz_max = PetscMax(nz_max, nz);
1567: nnz[i] = anz;
1568: }
1569: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1570: PetscCall(PetscFree(nnz));
1572: values = (PetscScalar *)V;
1573: if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
1574: b->ignore_ltriangular = PETSC_TRUE;
1575: for (i = 0; i < m; i++) {
1576: PetscInt ncols = ii[i + 1] - ii[i];
1577: const PetscInt *icols = jj + ii[i];
1579: if (!roworiented || bs == 1) {
1580: const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
1581: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES));
1582: } else {
1583: for (j = 0; j < ncols; j++) {
1584: const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
1585: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES));
1586: }
1587: }
1588: }
1589: if (!V) PetscCall(PetscFree(values));
1590: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
1591: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
1592: PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1593: b->ignore_ltriangular = ilw;
1594: PetscFunctionReturn(PETSC_SUCCESS);
1595: }
1597: /*
1598: This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1599: */
1600: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B, PetscBool natural)
1601: {
1602: PetscBool flg = PETSC_FALSE;
1603: PetscInt bs = B->rmap->bs;
1605: PetscFunctionBegin;
1606: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1607: if (flg) bs = 8;
1609: if (!natural) {
1610: switch (bs) {
1611: case 1:
1612: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
1613: break;
1614: case 2:
1615: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1616: break;
1617: case 3:
1618: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1619: break;
1620: case 4:
1621: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1622: break;
1623: case 5:
1624: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1625: break;
1626: case 6:
1627: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1628: break;
1629: case 7:
1630: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1631: break;
1632: default:
1633: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1634: break;
1635: }
1636: } else {
1637: switch (bs) {
1638: case 1:
1639: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
1640: break;
1641: case 2:
1642: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1643: break;
1644: case 3:
1645: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1646: break;
1647: case 4:
1648: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1649: break;
1650: case 5:
1651: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1652: break;
1653: case 6:
1654: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1655: break;
1656: case 7:
1657: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1658: break;
1659: default:
1660: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1661: break;
1662: }
1663: }
1664: PetscFunctionReturn(PETSC_SUCCESS);
1665: }
1667: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
1668: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
1669: static PetscErrorCode MatFactorGetSolverType_petsc(Mat A, MatSolverType *type)
1670: {
1671: PetscFunctionBegin;
1672: *type = MATSOLVERPETSC;
1673: PetscFunctionReturn(PETSC_SUCCESS);
1674: }
1676: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A, MatFactorType ftype, Mat *B)
1677: {
1678: PetscInt n = A->rmap->n;
1680: PetscFunctionBegin;
1681: #if defined(PETSC_USE_COMPLEX)
1682: if ((ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) && A->hermitian == PETSC_BOOL3_TRUE && A->symmetric != PETSC_BOOL3_TRUE) {
1683: PetscCall(PetscInfo(A, "Hermitian MAT_FACTOR_CHOLESKY or MAT_FACTOR_ICC are not supported. Use MAT_FACTOR_LU instead.\n"));
1684: *B = NULL;
1685: PetscFunctionReturn(PETSC_SUCCESS);
1686: }
1687: #endif
1689: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B));
1690: PetscCall(MatSetSizes(*B, n, n, n, n));
1691: PetscCheck(ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC, PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
1692: PetscCall(MatSetType(*B, MATSEQSBAIJ));
1693: PetscCall(MatSeqSBAIJSetPreallocation(*B, A->rmap->bs, MAT_SKIP_ALLOCATION, NULL));
1695: (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1696: (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;
1697: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]));
1698: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]));
1700: (*B)->factortype = ftype;
1701: (*B)->canuseordering = PETSC_TRUE;
1702: PetscCall(PetscFree((*B)->solvertype));
1703: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &(*B)->solvertype));
1704: PetscCall(PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_petsc));
1705: PetscFunctionReturn(PETSC_SUCCESS);
1706: }
1708: /*@C
1709: MatSeqSBAIJGetArray - gives access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored
1711: Not Collective
1713: Input Parameter:
1714: . A - a `MATSEQSBAIJ` matrix
1716: Output Parameter:
1717: . array - pointer to the data
1719: Level: intermediate
1721: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1722: @*/
1723: PetscErrorCode MatSeqSBAIJGetArray(Mat A, PetscScalar *array[])
1724: {
1725: PetscFunctionBegin;
1726: PetscUseMethod(A, "MatSeqSBAIJGetArray_C", (Mat, PetscScalar **), (A, array));
1727: PetscFunctionReturn(PETSC_SUCCESS);
1728: }
1730: /*@C
1731: MatSeqSBAIJRestoreArray - returns access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored obtained by `MatSeqSBAIJGetArray()`
1733: Not Collective
1735: Input Parameters:
1736: + A - a `MATSEQSBAIJ` matrix
1737: - array - pointer to the data
1739: Level: intermediate
1741: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1742: @*/
1743: PetscErrorCode MatSeqSBAIJRestoreArray(Mat A, PetscScalar *array[])
1744: {
1745: PetscFunctionBegin;
1746: PetscUseMethod(A, "MatSeqSBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array));
1747: PetscFunctionReturn(PETSC_SUCCESS);
1748: }
1750: /*MC
1751: MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
1752: based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored.
1754: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1755: can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`).
1757: Options Database Key:
1758: . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to `MatSetFromOptions()`
1760: Level: beginner
1762: Notes:
1763: By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
1764: stored and it is assumed they symmetric to the upper triangular). If you call `MatSetOption`(`Mat`,`MAT_IGNORE_LOWER_TRIANGULAR`,`PETSC_FALSE`) or use
1765: 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.
1767: The number of rows in the matrix must be less than or equal to the number of columns
1769: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ()`, `MatType`, `MATMPISBAIJ`
1770: M*/
1771: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
1772: {
1773: Mat_SeqSBAIJ *b;
1774: PetscMPIInt size;
1775: PetscBool no_unroll = PETSC_FALSE, no_inode = PETSC_FALSE;
1777: PetscFunctionBegin;
1778: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
1779: PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1");
1781: PetscCall(PetscNew(&b));
1782: B->data = (void *)b;
1783: B->ops[0] = MatOps_Values;
1785: B->ops->destroy = MatDestroy_SeqSBAIJ;
1786: B->ops->view = MatView_SeqSBAIJ;
1787: b->row = NULL;
1788: b->icol = NULL;
1789: b->reallocs = 0;
1790: b->saved_values = NULL;
1791: b->inode.limit = 5;
1792: b->inode.max_limit = 5;
1794: b->roworiented = PETSC_TRUE;
1795: b->nonew = 0;
1796: b->diag = NULL;
1797: b->solve_work = NULL;
1798: b->mult_work = NULL;
1799: B->spptr = NULL;
1800: B->info.nz_unneeded = (PetscReal)b->maxnz * b->bs2;
1801: b->keepnonzeropattern = PETSC_FALSE;
1803: b->inew = NULL;
1804: b->jnew = NULL;
1805: b->anew = NULL;
1806: b->a2anew = NULL;
1807: b->permute = PETSC_FALSE;
1809: b->ignore_ltriangular = PETSC_TRUE;
1811: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_ignore_lower_triangular", &b->ignore_ltriangular, NULL));
1813: b->getrow_utriangular = PETSC_FALSE;
1815: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_getrow_uppertriangular", &b->getrow_utriangular, NULL));
1817: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJGetArray_C", MatSeqSBAIJGetArray_SeqSBAIJ));
1818: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJRestoreArray_C", MatSeqSBAIJRestoreArray_SeqSBAIJ));
1819: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSBAIJ));
1820: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSBAIJ));
1821: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetColumnIndices_C", MatSeqSBAIJSetColumnIndices_SeqSBAIJ));
1822: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqaij_C", MatConvert_SeqSBAIJ_SeqAIJ));
1823: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqbaij_C", MatConvert_SeqSBAIJ_SeqBAIJ));
1824: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocation_C", MatSeqSBAIJSetPreallocation_SeqSBAIJ));
1825: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocationCSR_C", MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ));
1826: #if defined(PETSC_HAVE_ELEMENTAL)
1827: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_elemental_C", MatConvert_SeqSBAIJ_Elemental));
1828: #endif
1829: #if defined(PETSC_HAVE_SCALAPACK) && (defined(PETSC_USE_REAL_SINGLE) || defined(PETSC_USE_REAL_DOUBLE))
1830: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK));
1831: #endif
1833: B->symmetry_eternal = PETSC_TRUE;
1834: B->structural_symmetry_eternal = PETSC_TRUE;
1835: B->symmetric = PETSC_BOOL3_TRUE;
1836: B->structurally_symmetric = PETSC_BOOL3_TRUE;
1837: #if !defined(PETSC_USE_COMPLEX)
1838: B->hermitian = PETSC_BOOL3_TRUE;
1839: #endif
1841: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQSBAIJ));
1843: PetscOptionsBegin(PetscObjectComm((PetscObject)B), ((PetscObject)B)->prefix, "Options for SEQSBAIJ matrix", "Mat");
1844: PetscCall(PetscOptionsBool("-mat_no_unroll", "Do not optimize for inodes (slower)", NULL, no_unroll, &no_unroll, NULL));
1845: if (no_unroll) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_unroll\n"));
1846: PetscCall(PetscOptionsBool("-mat_no_inode", "Do not optimize for inodes (slower)", NULL, no_inode, &no_inode, NULL));
1847: if (no_inode) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_inode\n"));
1848: PetscCall(PetscOptionsInt("-mat_inode_limit", "Do not use inodes larger than this value", NULL, b->inode.limit, &b->inode.limit, NULL));
1849: PetscOptionsEnd();
1850: b->inode.use = (PetscBool)(!(no_unroll || no_inode));
1851: if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
1852: PetscFunctionReturn(PETSC_SUCCESS);
1853: }
1855: /*@
1856: MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
1857: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
1858: user should preallocate the matrix storage by setting the parameter `nz`
1859: (or the array `nnz`).
1861: Collective
1863: Input Parameters:
1864: + B - the symmetric matrix
1865: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
1866: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
1867: . nz - number of block nonzeros per block row (same for all rows)
1868: - nnz - array containing the number of block nonzeros in the upper triangular plus
1869: diagonal portion of each block (possibly different for each block row) or `NULL`
1871: Options Database Keys:
1872: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower)
1873: - -mat_block_size - size of the blocks to use (only works if a negative bs is passed in
1875: Level: intermediate
1877: Notes:
1878: Specify the preallocated storage with either `nz` or `nnz` (not both).
1879: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
1880: allocation. See [Sparse Matrices](sec_matsparse) for details.
1882: You can call `MatGetInfo()` to get information on how effective the preallocation was;
1883: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1884: You can also run with the option `-info` and look for messages with the string
1885: malloc in them to see if additional memory allocation was needed.
1887: If the `nnz` parameter is given then the `nz` parameter is ignored
1889: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
1890: @*/
1891: PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
1892: {
1893: PetscFunctionBegin;
1897: PetscTryMethod(B, "MatSeqSBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz));
1898: PetscFunctionReturn(PETSC_SUCCESS);
1899: }
1901: /*@C
1902: MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATSEQSBAIJ` format using the given nonzero structure and (optional) numerical values
1904: Input Parameters:
1905: + B - the matrix
1906: . bs - size of block, the blocks are ALWAYS square.
1907: . i - the indices into `j` for the start of each local row (indices start with zero)
1908: . j - the column indices for each local row (indices start with zero) these must be sorted for each row
1909: - v - optional values in the matrix, use `NULL` if not provided
1911: Level: advanced
1913: Notes:
1914: The `i`,`j`,`v` values are COPIED with this routine; to avoid the copy use `MatCreateSeqSBAIJWithArrays()`
1916: The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`. For example, C programs
1917: may want to use the default `MAT_ROW_ORIENTED` = `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
1918: over rows within a block and the last index is over columns within a block row. Fortran programs will likely set
1919: `MAT_ROW_ORIENTED` = `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
1920: block column and the second index is over columns within a block.
1922: Any entries provided that lie below the diagonal are ignored
1924: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
1925: and usually the numerical values as well
1927: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValuesBlocked()`, `MatSeqSBAIJSetPreallocation()`
1928: @*/
1929: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
1930: {
1931: PetscFunctionBegin;
1935: PetscTryMethod(B, "MatSeqSBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
1936: PetscFunctionReturn(PETSC_SUCCESS);
1937: }
1939: /*@
1940: MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in (block
1941: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
1942: user should preallocate the matrix storage by setting the parameter `nz`
1943: (or the array `nnz`).
1945: Collective
1947: Input Parameters:
1948: + comm - MPI communicator, set to `PETSC_COMM_SELF`
1949: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
1950: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
1951: . m - number of rows
1952: . n - number of columns
1953: . nz - number of block nonzeros per block row (same for all rows)
1954: - nnz - array containing the number of block nonzeros in the upper triangular plus
1955: diagonal portion of each block (possibly different for each block row) or `NULL`
1957: Output Parameter:
1958: . A - the symmetric matrix
1960: Options Database Keys:
1961: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower)
1962: - -mat_block_size - size of the blocks to use
1964: Level: intermediate
1966: Notes:
1967: It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
1968: MatXXXXSetPreallocation() paradigm instead of this routine directly.
1969: [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]
1971: The number of rows and columns must be divisible by blocksize.
1972: This matrix type does not support complex Hermitian operation.
1974: Specify the preallocated storage with either `nz` or `nnz` (not both).
1975: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
1976: allocation. See [Sparse Matrices](sec_matsparse) for details.
1978: If the `nnz` parameter is given then the `nz` parameter is ignored
1980: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
1981: @*/
1982: PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
1983: {
1984: PetscFunctionBegin;
1985: PetscCall(MatCreate(comm, A));
1986: PetscCall(MatSetSizes(*A, m, n, m, n));
1987: PetscCall(MatSetType(*A, MATSEQSBAIJ));
1988: PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz));
1989: PetscFunctionReturn(PETSC_SUCCESS);
1990: }
1992: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B)
1993: {
1994: Mat C;
1995: Mat_SeqSBAIJ *c, *a = (Mat_SeqSBAIJ *)A->data;
1996: PetscInt i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2;
1998: PetscFunctionBegin;
1999: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Cannot duplicate unassembled matrix");
2000: PetscCheck(a->i[mbs] == nz, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupt matrix");
2002: *B = NULL;
2003: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &C));
2004: PetscCall(MatSetSizes(C, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n));
2005: PetscCall(MatSetBlockSizesFromMats(C, A, A));
2006: PetscCall(MatSetType(C, MATSEQSBAIJ));
2007: c = (Mat_SeqSBAIJ *)C->data;
2009: C->preallocated = PETSC_TRUE;
2010: C->factortype = A->factortype;
2011: c->row = NULL;
2012: c->icol = NULL;
2013: c->saved_values = NULL;
2014: c->keepnonzeropattern = a->keepnonzeropattern;
2015: C->assembled = PETSC_TRUE;
2017: PetscCall(PetscLayoutReference(A->rmap, &C->rmap));
2018: PetscCall(PetscLayoutReference(A->cmap, &C->cmap));
2019: c->bs2 = a->bs2;
2020: c->mbs = a->mbs;
2021: c->nbs = a->nbs;
2023: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2024: c->imax = a->imax;
2025: c->ilen = a->ilen;
2026: c->free_imax_ilen = PETSC_FALSE;
2027: } else {
2028: PetscCall(PetscMalloc2(mbs + 1, &c->imax, mbs + 1, &c->ilen));
2029: for (i = 0; i < mbs; i++) {
2030: c->imax[i] = a->imax[i];
2031: c->ilen[i] = a->ilen[i];
2032: }
2033: c->free_imax_ilen = PETSC_TRUE;
2034: }
2036: /* allocate the matrix space */
2037: PetscCall(PetscShmgetAllocateArray(bs2 * nz, sizeof(PetscScalar), (void **)&c->a));
2038: c->free_a = PETSC_TRUE;
2039: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2040: PetscCall(PetscArrayzero(c->a, bs2 * nz));
2041: c->i = a->i;
2042: c->j = a->j;
2043: c->free_ij = PETSC_FALSE;
2044: c->parent = A;
2045: PetscCall(PetscObjectReference((PetscObject)A));
2046: PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2047: PetscCall(MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2048: } else {
2049: PetscCall(PetscShmgetAllocateArray(nz, sizeof(PetscInt), (void **)&c->j));
2050: PetscCall(PetscShmgetAllocateArray(mbs + 1, sizeof(PetscInt), (void **)&c->i));
2051: PetscCall(PetscArraycpy(c->i, a->i, mbs + 1));
2052: c->free_ij = PETSC_TRUE;
2053: }
2054: if (mbs > 0) {
2055: if (cpvalues != MAT_SHARE_NONZERO_PATTERN) PetscCall(PetscArraycpy(c->j, a->j, nz));
2056: if (cpvalues == MAT_COPY_VALUES) {
2057: PetscCall(PetscArraycpy(c->a, a->a, bs2 * nz));
2058: } else {
2059: PetscCall(PetscArrayzero(c->a, bs2 * nz));
2060: }
2061: if (a->jshort) {
2062: /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
2063: /* if the parent matrix is reassembled, this child matrix will never notice */
2064: PetscCall(PetscMalloc1(nz, &c->jshort));
2065: PetscCall(PetscArraycpy(c->jshort, a->jshort, nz));
2067: c->free_jshort = PETSC_TRUE;
2068: }
2069: }
2071: c->roworiented = a->roworiented;
2072: c->nonew = a->nonew;
2073: c->nz = a->nz;
2074: c->maxnz = a->nz; /* Since we allocate exactly the right amount */
2075: c->solve_work = NULL;
2076: c->mult_work = NULL;
2078: *B = C;
2079: PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist));
2080: PetscFunctionReturn(PETSC_SUCCESS);
2081: }
2083: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
2084: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary
2086: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat, PetscViewer viewer)
2087: {
2088: PetscBool isbinary;
2090: PetscFunctionBegin;
2091: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
2092: 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);
2093: PetscCall(MatLoad_SeqSBAIJ_Binary(mat, viewer));
2094: PetscFunctionReturn(PETSC_SUCCESS);
2095: }
2097: /*@
2098: MatCreateSeqSBAIJWithArrays - Creates an sequential `MATSEQSBAIJ` matrix using matrix elements
2099: (upper triangular entries in CSR format) provided by the user.
2101: Collective
2103: Input Parameters:
2104: + comm - must be an MPI communicator of size 1
2105: . bs - size of block
2106: . m - number of rows
2107: . n - number of columns
2108: . 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
2109: . j - column indices
2110: - a - matrix values
2112: Output Parameter:
2113: . mat - the matrix
2115: Level: advanced
2117: Notes:
2118: The `i`, `j`, and `a` arrays are not copied by this routine, the user must free these arrays
2119: once the matrix is destroyed
2121: You cannot set new nonzero locations into this matrix, that will generate an error.
2123: The `i` and `j` indices are 0 based
2125: When block size is greater than 1 the matrix values must be stored using the `MATSBAIJ` storage format. For block size of 1
2126: it is the regular CSR format excluding the lower triangular elements.
2128: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSBAIJ()`, `MatCreateSeqSBAIJ()`
2129: @*/
2130: PetscErrorCode MatCreateSeqSBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat)
2131: {
2132: PetscInt ii;
2133: Mat_SeqSBAIJ *sbaij;
2135: PetscFunctionBegin;
2136: PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "block size %" PetscInt_FMT " > 1 is not supported yet", bs);
2137: PetscCheck(m == 0 || i[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");
2139: PetscCall(MatCreate(comm, mat));
2140: PetscCall(MatSetSizes(*mat, m, n, m, n));
2141: PetscCall(MatSetType(*mat, MATSEQSBAIJ));
2142: PetscCall(MatSeqSBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL));
2143: sbaij = (Mat_SeqSBAIJ *)(*mat)->data;
2144: PetscCall(PetscMalloc2(m, &sbaij->imax, m, &sbaij->ilen));
2146: sbaij->i = i;
2147: sbaij->j = j;
2148: sbaij->a = a;
2150: sbaij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2151: sbaij->free_a = PETSC_FALSE;
2152: sbaij->free_ij = PETSC_FALSE;
2153: sbaij->free_imax_ilen = PETSC_TRUE;
2155: for (ii = 0; ii < m; ii++) {
2156: sbaij->ilen[ii] = sbaij->imax[ii] = i[ii + 1] - i[ii];
2157: 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]);
2158: }
2159: if (PetscDefined(USE_DEBUG)) {
2160: for (ii = 0; ii < sbaij->i[m]; ii++) {
2161: PetscCheck(j[ii] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative column index at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2162: 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]);
2163: }
2164: }
2166: PetscCall(MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY));
2167: PetscCall(MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY));
2168: PetscFunctionReturn(PETSC_SUCCESS);
2169: }
2171: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2172: {
2173: PetscFunctionBegin;
2174: PetscCall(MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm, inmat, n, scall, outmat));
2175: PetscFunctionReturn(PETSC_SUCCESS);
2176: }