Actual source code: dense.c
1: /*
2: Defines the basic matrix operations for sequential dense.
3: Portions of this code are under:
4: Copyright (c) 2022 Advanced Micro Devices, Inc. All rights reserved.
5: */
7: #include <../src/mat/impls/dense/seq/dense.h>
8: #include <../src/mat/impls/dense/mpi/mpidense.h>
9: #include <petscblaslapack.h>
10: #include <../src/mat/impls/aij/seq/aij.h>
11: #include <petsc/private/vecimpl.h>
13: PetscErrorCode MatSeqDenseSymmetrize_Private(Mat A, PetscBool hermitian)
14: {
15: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
16: PetscInt j, k, n = A->rmap->n;
17: PetscScalar *v;
19: PetscFunctionBegin;
20: PetscCheck(A->rmap->n == A->cmap->n, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Cannot symmetrize a rectangular matrix");
21: PetscCall(MatDenseGetArray(A, &v));
22: if (!hermitian) {
23: for (k = 0; k < n; k++) {
24: for (j = k; j < n; j++) v[j * mat->lda + k] = v[k * mat->lda + j];
25: }
26: } else {
27: for (k = 0; k < n; k++) {
28: for (j = k; j < n; j++) v[j * mat->lda + k] = PetscConj(v[k * mat->lda + j]);
29: }
30: }
31: PetscCall(MatDenseRestoreArray(A, &v));
32: PetscFunctionReturn(PETSC_SUCCESS);
33: }
35: PetscErrorCode MatSeqDenseInvertFactors_Private(Mat A)
36: {
37: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
38: PetscBLASInt info, n;
40: PetscFunctionBegin;
41: if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
42: PetscCall(PetscBLASIntCast(A->cmap->n, &n));
43: if (A->factortype == MAT_FACTOR_LU) {
44: PetscCheck(mat->pivots, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Pivots not present");
45: if (!mat->fwork) {
46: mat->lfwork = n;
47: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
48: }
49: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
50: PetscCallBLAS("LAPACKgetri", LAPACKgetri_(&n, mat->v, &mat->lda, mat->pivots, mat->fwork, &mat->lfwork, &info));
51: PetscCall(PetscFPTrapPop());
52: PetscCall(PetscLogFlops((1.0 * A->cmap->n * A->cmap->n * A->cmap->n) / 3.0));
53: } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
54: if (A->spd == PETSC_BOOL3_TRUE) {
55: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
56: PetscCallBLAS("LAPACKpotri", LAPACKpotri_("L", &n, mat->v, &mat->lda, &info));
57: PetscCall(PetscFPTrapPop());
58: PetscCall(MatSeqDenseSymmetrize_Private(A, PETSC_TRUE));
59: #if defined(PETSC_USE_COMPLEX)
60: } else if (A->hermitian == PETSC_BOOL3_TRUE) {
61: PetscCheck(mat->pivots, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Pivots not present");
62: PetscCheck(mat->fwork, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Fwork not present");
63: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
64: PetscCallBLAS("LAPACKhetri", LAPACKhetri_("L", &n, mat->v, &mat->lda, mat->pivots, mat->fwork, &info));
65: PetscCall(PetscFPTrapPop());
66: PetscCall(MatSeqDenseSymmetrize_Private(A, PETSC_TRUE));
67: #endif
68: } else { /* symmetric case */
69: PetscCheck(mat->pivots, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Pivots not present");
70: PetscCheck(mat->fwork, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Fwork not present");
71: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
72: PetscCallBLAS("LAPACKsytri", LAPACKsytri_("L", &n, mat->v, &mat->lda, mat->pivots, mat->fwork, &info));
73: PetscCall(PetscFPTrapPop());
74: PetscCall(MatSeqDenseSymmetrize_Private(A, PETSC_FALSE));
75: }
76: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_MAT_CH_ZRPVT, "Bad Inversion: zero pivot in row %" PetscInt_FMT, (PetscInt)info - 1);
77: PetscCall(PetscLogFlops((1.0 * A->cmap->n * A->cmap->n * A->cmap->n) / 3.0));
78: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Matrix must be factored to solve");
80: A->ops->solve = NULL;
81: A->ops->matsolve = NULL;
82: A->ops->solvetranspose = NULL;
83: A->ops->matsolvetranspose = NULL;
84: A->ops->solveadd = NULL;
85: A->ops->solvetransposeadd = NULL;
86: A->factortype = MAT_FACTOR_NONE;
87: PetscCall(PetscFree(A->solvertype));
88: PetscFunctionReturn(PETSC_SUCCESS);
89: }
91: static PetscErrorCode MatZeroRowsColumns_SeqDense(Mat A, PetscInt N, const PetscInt rows[], PetscScalar diag, Vec x, Vec b)
92: {
93: Mat_SeqDense *l = (Mat_SeqDense *)A->data;
94: PetscInt m = l->lda, n = A->cmap->n, r = A->rmap->n, i, j;
95: PetscScalar *slot, *bb, *v;
96: const PetscScalar *xx;
98: PetscFunctionBegin;
99: if (PetscDefined(USE_DEBUG)) {
100: for (i = 0; i < N; i++) {
101: PetscCheck(rows[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row requested to be zeroed");
102: PetscCheck(rows[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " requested to be zeroed greater than or equal number of rows %" PetscInt_FMT, rows[i], A->rmap->n);
103: PetscCheck(rows[i] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Col %" PetscInt_FMT " requested to be zeroed greater than or equal number of cols %" PetscInt_FMT, rows[i], A->cmap->n);
104: }
105: }
106: if (!N) PetscFunctionReturn(PETSC_SUCCESS);
108: /* fix right-hand side if needed */
109: if (x && b) {
110: Vec xt;
112: PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only coded for square matrices");
113: PetscCall(VecDuplicate(x, &xt));
114: PetscCall(VecCopy(x, xt));
115: PetscCall(VecScale(xt, -1.0));
116: PetscCall(MatMultAdd(A, xt, b, b));
117: PetscCall(VecDestroy(&xt));
118: PetscCall(VecGetArrayRead(x, &xx));
119: PetscCall(VecGetArray(b, &bb));
120: for (i = 0; i < N; i++) bb[rows[i]] = diag * xx[rows[i]];
121: PetscCall(VecRestoreArrayRead(x, &xx));
122: PetscCall(VecRestoreArray(b, &bb));
123: }
125: PetscCall(MatDenseGetArray(A, &v));
126: for (i = 0; i < N; i++) {
127: slot = v + rows[i] * m;
128: PetscCall(PetscArrayzero(slot, r));
129: }
130: for (i = 0; i < N; i++) {
131: slot = v + rows[i];
132: for (j = 0; j < n; j++) {
133: *slot = 0.0;
134: slot += m;
135: }
136: }
137: if (diag != 0.0) {
138: PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only coded for square matrices");
139: for (i = 0; i < N; i++) {
140: slot = v + (m + 1) * rows[i];
141: *slot = diag;
142: }
143: }
144: PetscCall(MatDenseRestoreArray(A, &v));
145: PetscFunctionReturn(PETSC_SUCCESS);
146: }
148: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
149: {
150: Mat B = NULL;
151: Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data;
152: Mat_SeqDense *b;
153: PetscInt *ai = a->i, *aj = a->j, m = A->rmap->N, n = A->cmap->N, i;
154: const MatScalar *av;
155: PetscBool isseqdense;
157: PetscFunctionBegin;
158: if (reuse == MAT_REUSE_MATRIX) {
159: PetscCall(PetscObjectTypeCompare((PetscObject)*newmat, MATSEQDENSE, &isseqdense));
160: PetscCheck(isseqdense, PetscObjectComm((PetscObject)*newmat), PETSC_ERR_USER, "Cannot reuse matrix of type %s", ((PetscObject)*newmat)->type_name);
161: }
162: if (reuse != MAT_REUSE_MATRIX) {
163: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
164: PetscCall(MatSetSizes(B, m, n, m, n));
165: PetscCall(MatSetType(B, MATSEQDENSE));
166: PetscCall(MatSeqDenseSetPreallocation(B, NULL));
167: b = (Mat_SeqDense *)B->data;
168: } else {
169: b = (Mat_SeqDense *)((*newmat)->data);
170: for (i = 0; i < n; i++) PetscCall(PetscArrayzero(b->v + i * b->lda, m));
171: }
172: PetscCall(MatSeqAIJGetArrayRead(A, &av));
173: for (i = 0; i < m; i++) {
174: PetscInt j;
175: for (j = 0; j < ai[1] - ai[0]; j++) {
176: b->v[*aj * b->lda + i] = *av;
177: aj++;
178: av++;
179: }
180: ai++;
181: }
182: PetscCall(MatSeqAIJRestoreArrayRead(A, &av));
184: if (reuse == MAT_INPLACE_MATRIX) {
185: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
186: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
187: PetscCall(MatHeaderReplace(A, &B));
188: } else {
189: if (B) *newmat = B;
190: PetscCall(MatAssemblyBegin(*newmat, MAT_FINAL_ASSEMBLY));
191: PetscCall(MatAssemblyEnd(*newmat, MAT_FINAL_ASSEMBLY));
192: }
193: PetscFunctionReturn(PETSC_SUCCESS);
194: }
196: PETSC_INTERN PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
197: {
198: Mat B = NULL;
199: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
200: PetscInt i, j;
201: PetscInt *rows, *nnz;
202: MatScalar *aa = a->v, *vals;
204: PetscFunctionBegin;
205: PetscCall(PetscCalloc3(A->rmap->n, &rows, A->rmap->n, &nnz, A->rmap->n, &vals));
206: if (reuse != MAT_REUSE_MATRIX) {
207: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
208: PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N));
209: PetscCall(MatSetType(B, MATSEQAIJ));
210: for (j = 0; j < A->cmap->n; j++) {
211: for (i = 0; i < A->rmap->n; i++)
212: if (aa[i] != 0.0 || (i == j && A->cmap->n == A->rmap->n)) ++nnz[i];
213: aa += a->lda;
214: }
215: PetscCall(MatSeqAIJSetPreallocation(B, PETSC_DETERMINE, nnz));
216: } else B = *newmat;
217: aa = a->v;
218: for (j = 0; j < A->cmap->n; j++) {
219: PetscInt numRows = 0;
220: for (i = 0; i < A->rmap->n; i++)
221: if (aa[i] != 0.0 || (i == j && A->cmap->n == A->rmap->n)) {
222: rows[numRows] = i;
223: vals[numRows++] = aa[i];
224: }
225: PetscCall(MatSetValues(B, numRows, rows, 1, &j, vals, INSERT_VALUES));
226: aa += a->lda;
227: }
228: PetscCall(PetscFree3(rows, nnz, vals));
229: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
230: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
232: if (reuse == MAT_INPLACE_MATRIX) {
233: PetscCall(MatHeaderReplace(A, &B));
234: } else if (reuse != MAT_REUSE_MATRIX) *newmat = B;
235: PetscFunctionReturn(PETSC_SUCCESS);
236: }
238: PetscErrorCode MatAXPY_SeqDense(Mat Y, PetscScalar alpha, Mat X, MatStructure str)
239: {
240: Mat_SeqDense *x = (Mat_SeqDense *)X->data, *y = (Mat_SeqDense *)Y->data;
241: const PetscScalar *xv;
242: PetscScalar *yv;
243: PetscBLASInt N, m, ldax = 0, lday = 0, one = 1;
245: PetscFunctionBegin;
246: PetscCall(MatDenseGetArrayRead(X, &xv));
247: PetscCall(MatDenseGetArray(Y, &yv));
248: PetscCall(PetscBLASIntCast(X->rmap->n * X->cmap->n, &N));
249: PetscCall(PetscBLASIntCast(X->rmap->n, &m));
250: PetscCall(PetscBLASIntCast(x->lda, &ldax));
251: PetscCall(PetscBLASIntCast(y->lda, &lday));
252: if (ldax > m || lday > m) {
253: for (PetscInt j = 0; j < X->cmap->n; j++) PetscCallBLAS("BLASaxpy", BLASaxpy_(&m, &alpha, PetscSafePointerPlusOffset(xv, j * ldax), &one, PetscSafePointerPlusOffset(yv, j * lday), &one));
254: } else {
255: PetscCallBLAS("BLASaxpy", BLASaxpy_(&N, &alpha, xv, &one, yv, &one));
256: }
257: PetscCall(MatDenseRestoreArrayRead(X, &xv));
258: PetscCall(MatDenseRestoreArray(Y, &yv));
259: PetscCall(PetscLogFlops(PetscMax(2.0 * N - 1, 0)));
260: PetscFunctionReturn(PETSC_SUCCESS);
261: }
263: static PetscErrorCode MatGetInfo_SeqDense(Mat A, MatInfoType flag, MatInfo *info)
264: {
265: PetscLogDouble N = A->rmap->n * A->cmap->n;
267: PetscFunctionBegin;
268: info->block_size = 1.0;
269: info->nz_allocated = N;
270: info->nz_used = N;
271: info->nz_unneeded = 0;
272: info->assemblies = A->num_ass;
273: info->mallocs = 0;
274: info->memory = 0; /* REVIEW ME */
275: info->fill_ratio_given = 0;
276: info->fill_ratio_needed = 0;
277: info->factor_mallocs = 0;
278: PetscFunctionReturn(PETSC_SUCCESS);
279: }
281: PetscErrorCode MatScale_SeqDense(Mat A, PetscScalar alpha)
282: {
283: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
284: PetscScalar *v;
285: PetscBLASInt one = 1, j, nz, lda = 0;
287: PetscFunctionBegin;
288: PetscCall(MatDenseGetArray(A, &v));
289: PetscCall(PetscBLASIntCast(a->lda, &lda));
290: if (lda > A->rmap->n) {
291: PetscCall(PetscBLASIntCast(A->rmap->n, &nz));
292: for (j = 0; j < A->cmap->n; j++) PetscCallBLAS("BLASscal", BLASscal_(&nz, &alpha, v + j * lda, &one));
293: } else {
294: PetscCall(PetscBLASIntCast(A->rmap->n * A->cmap->n, &nz));
295: PetscCallBLAS("BLASscal", BLASscal_(&nz, &alpha, v, &one));
296: }
297: PetscCall(PetscLogFlops(A->rmap->n * A->cmap->n));
298: PetscCall(MatDenseRestoreArray(A, &v));
299: PetscFunctionReturn(PETSC_SUCCESS);
300: }
302: PetscErrorCode MatShift_SeqDense(Mat A, PetscScalar alpha)
303: {
304: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
305: PetscScalar *v;
306: PetscInt j, k;
308: PetscFunctionBegin;
309: PetscCall(MatDenseGetArray(A, &v));
310: k = PetscMin(A->rmap->n, A->cmap->n);
311: for (j = 0; j < k; j++) v[j + j * a->lda] += alpha;
312: PetscCall(PetscLogFlops(k));
313: PetscCall(MatDenseRestoreArray(A, &v));
314: PetscFunctionReturn(PETSC_SUCCESS);
315: }
317: static PetscErrorCode MatIsHermitian_SeqDense(Mat A, PetscReal rtol, PetscBool *fl)
318: {
319: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
320: PetscInt i, j, m = A->rmap->n, N = a->lda;
321: const PetscScalar *v;
323: PetscFunctionBegin;
324: *fl = PETSC_FALSE;
325: if (A->rmap->n != A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
326: PetscCall(MatDenseGetArrayRead(A, &v));
327: for (i = 0; i < m; i++) {
328: for (j = i; j < m; j++) {
329: if (PetscAbsScalar(v[i + j * N] - PetscConj(v[j + i * N])) > rtol) goto restore;
330: }
331: }
332: *fl = PETSC_TRUE;
333: restore:
334: PetscCall(MatDenseRestoreArrayRead(A, &v));
335: PetscFunctionReturn(PETSC_SUCCESS);
336: }
338: static PetscErrorCode MatIsSymmetric_SeqDense(Mat A, PetscReal rtol, PetscBool *fl)
339: {
340: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
341: PetscInt i, j, m = A->rmap->n, N = a->lda;
342: const PetscScalar *v;
344: PetscFunctionBegin;
345: *fl = PETSC_FALSE;
346: if (A->rmap->n != A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
347: PetscCall(MatDenseGetArrayRead(A, &v));
348: for (i = 0; i < m; i++) {
349: for (j = i; j < m; j++) {
350: if (PetscAbsScalar(v[i + j * N] - v[j + i * N]) > rtol) goto restore;
351: }
352: }
353: *fl = PETSC_TRUE;
354: restore:
355: PetscCall(MatDenseRestoreArrayRead(A, &v));
356: PetscFunctionReturn(PETSC_SUCCESS);
357: }
359: PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi, Mat A, MatDuplicateOption cpvalues)
360: {
361: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
362: PetscInt lda = (PetscInt)mat->lda, j, m, nlda = lda;
363: PetscBool isdensecpu;
365: PetscFunctionBegin;
366: PetscCall(PetscLayoutReference(A->rmap, &newi->rmap));
367: PetscCall(PetscLayoutReference(A->cmap, &newi->cmap));
368: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { /* propagate LDA */
369: PetscCall(MatDenseSetLDA(newi, lda));
370: }
371: PetscCall(PetscObjectTypeCompare((PetscObject)newi, MATSEQDENSE, &isdensecpu));
372: if (isdensecpu) PetscCall(MatSeqDenseSetPreallocation(newi, NULL));
373: if (cpvalues == MAT_COPY_VALUES) {
374: const PetscScalar *av;
375: PetscScalar *v;
377: PetscCall(MatDenseGetArrayRead(A, &av));
378: PetscCall(MatDenseGetArrayWrite(newi, &v));
379: PetscCall(MatDenseGetLDA(newi, &nlda));
380: m = A->rmap->n;
381: if (lda > m || nlda > m) {
382: for (j = 0; j < A->cmap->n; j++) PetscCall(PetscArraycpy(PetscSafePointerPlusOffset(v, j * nlda), PetscSafePointerPlusOffset(av, j * lda), m));
383: } else {
384: PetscCall(PetscArraycpy(v, av, A->rmap->n * A->cmap->n));
385: }
386: PetscCall(MatDenseRestoreArrayWrite(newi, &v));
387: PetscCall(MatDenseRestoreArrayRead(A, &av));
388: PetscCall(MatPropagateSymmetryOptions(A, newi));
389: }
390: PetscFunctionReturn(PETSC_SUCCESS);
391: }
393: PetscErrorCode MatDuplicate_SeqDense(Mat A, MatDuplicateOption cpvalues, Mat *newmat)
394: {
395: PetscFunctionBegin;
396: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), newmat));
397: PetscCall(MatSetSizes(*newmat, A->rmap->n, A->cmap->n, A->rmap->n, A->cmap->n));
398: PetscCall(MatSetType(*newmat, ((PetscObject)A)->type_name));
399: PetscCall(MatDuplicateNoCreate_SeqDense(*newmat, A, cpvalues));
400: PetscFunctionReturn(PETSC_SUCCESS);
401: }
403: static PetscErrorCode MatSolve_SeqDense_Internal_LU(Mat A, PetscScalar *x, PetscBLASInt ldx, PetscBLASInt m, PetscBLASInt nrhs, PetscBLASInt k, PetscBool T)
404: {
405: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
406: PetscBLASInt info;
408: PetscFunctionBegin;
409: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
410: PetscCallBLAS("LAPACKgetrs", LAPACKgetrs_(T ? "T" : "N", &m, &nrhs, mat->v, &mat->lda, mat->pivots, x, &m, &info));
411: PetscCall(PetscFPTrapPop());
412: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "GETRS - Bad solve %d", (int)info);
413: PetscCall(PetscLogFlops(nrhs * (2.0 * m * m - m)));
414: PetscFunctionReturn(PETSC_SUCCESS);
415: }
417: static PetscErrorCode MatConjugate_SeqDense(Mat);
419: static PetscErrorCode MatSolve_SeqDense_Internal_Cholesky(Mat A, PetscScalar *x, PetscBLASInt ldx, PetscBLASInt m, PetscBLASInt nrhs, PetscBLASInt k, PetscBool T)
420: {
421: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
422: PetscBLASInt info;
424: PetscFunctionBegin;
425: if (A->spd == PETSC_BOOL3_TRUE) {
426: if (PetscDefined(USE_COMPLEX) && T) PetscCall(MatConjugate_SeqDense(A));
427: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
428: PetscCallBLAS("LAPACKpotrs", LAPACKpotrs_("L", &m, &nrhs, mat->v, &mat->lda, x, &m, &info));
429: PetscCall(PetscFPTrapPop());
430: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "POTRS Bad solve %d", (int)info);
431: if (PetscDefined(USE_COMPLEX) && T) PetscCall(MatConjugate_SeqDense(A));
432: #if defined(PETSC_USE_COMPLEX)
433: } else if (A->hermitian == PETSC_BOOL3_TRUE) {
434: if (T) PetscCall(MatConjugate_SeqDense(A));
435: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
436: PetscCallBLAS("LAPACKhetrs", LAPACKhetrs_("L", &m, &nrhs, mat->v, &mat->lda, mat->pivots, x, &m, &info));
437: PetscCall(PetscFPTrapPop());
438: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "HETRS Bad solve %d", (int)info);
439: if (T) PetscCall(MatConjugate_SeqDense(A));
440: #endif
441: } else { /* symmetric case */
442: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
443: PetscCallBLAS("LAPACKsytrs", LAPACKsytrs_("L", &m, &nrhs, mat->v, &mat->lda, mat->pivots, x, &m, &info));
444: PetscCall(PetscFPTrapPop());
445: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "SYTRS Bad solve %d", (int)info);
446: }
447: PetscCall(PetscLogFlops(nrhs * (2.0 * m * m - m)));
448: PetscFunctionReturn(PETSC_SUCCESS);
449: }
451: static PetscErrorCode MatSolve_SeqDense_Internal_QR(Mat A, PetscScalar *x, PetscBLASInt ldx, PetscBLASInt m, PetscBLASInt nrhs, PetscBLASInt k)
452: {
453: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
454: PetscBLASInt info;
455: char trans;
457: PetscFunctionBegin;
458: if (PetscDefined(USE_COMPLEX)) {
459: trans = 'C';
460: } else {
461: trans = 'T';
462: }
463: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
464: { /* lwork depends on the number of right-hand sides */
465: PetscBLASInt nlfwork, lfwork = -1;
466: PetscScalar fwork;
468: PetscCallBLAS("LAPACKormqr", LAPACKormqr_("L", &trans, &m, &nrhs, &mat->rank, mat->v, &mat->lda, mat->tau, x, &ldx, &fwork, &lfwork, &info));
469: nlfwork = (PetscBLASInt)PetscRealPart(fwork);
470: if (nlfwork > mat->lfwork) {
471: mat->lfwork = nlfwork;
472: PetscCall(PetscFree(mat->fwork));
473: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
474: }
475: }
476: PetscCallBLAS("LAPACKormqr", LAPACKormqr_("L", &trans, &m, &nrhs, &mat->rank, mat->v, &mat->lda, mat->tau, x, &ldx, mat->fwork, &mat->lfwork, &info));
477: PetscCall(PetscFPTrapPop());
478: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "ORMQR - Bad orthogonal transform %d", (int)info);
479: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
480: PetscCallBLAS("LAPACKtrtrs", LAPACKtrtrs_("U", "N", "N", &mat->rank, &nrhs, mat->v, &mat->lda, x, &ldx, &info));
481: PetscCall(PetscFPTrapPop());
482: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "TRTRS - Bad triangular solve %d", (int)info);
483: for (PetscInt j = 0; j < nrhs; j++) {
484: for (PetscInt i = mat->rank; i < k; i++) x[j * ldx + i] = 0.;
485: }
486: PetscCall(PetscLogFlops(nrhs * (4.0 * m * mat->rank - PetscSqr(mat->rank))));
487: PetscFunctionReturn(PETSC_SUCCESS);
488: }
490: static PetscErrorCode MatSolveTranspose_SeqDense_Internal_QR(Mat A, PetscScalar *x, PetscBLASInt ldx, PetscBLASInt m, PetscBLASInt nrhs, PetscBLASInt k)
491: {
492: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
493: PetscBLASInt info;
495: PetscFunctionBegin;
496: if (A->rmap->n == A->cmap->n && mat->rank == A->rmap->n) {
497: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
498: PetscCallBLAS("LAPACKtrtrs", LAPACKtrtrs_("U", "T", "N", &m, &nrhs, mat->v, &mat->lda, x, &ldx, &info));
499: PetscCall(PetscFPTrapPop());
500: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "TRTRS - Bad triangular solve %d", (int)info);
501: if (PetscDefined(USE_COMPLEX)) PetscCall(MatConjugate_SeqDense(A));
502: { /* lwork depends on the number of right-hand sides */
503: PetscBLASInt nlfwork, lfwork = -1;
504: PetscScalar fwork;
506: PetscCallBLAS("LAPACKormqr", LAPACKormqr_("L", "N", &m, &nrhs, &mat->rank, mat->v, &mat->lda, mat->tau, x, &ldx, &fwork, &lfwork, &info));
507: nlfwork = (PetscBLASInt)PetscRealPart(fwork);
508: if (nlfwork > mat->lfwork) {
509: mat->lfwork = nlfwork;
510: PetscCall(PetscFree(mat->fwork));
511: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
512: }
513: }
514: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
515: PetscCallBLAS("LAPACKormqr", LAPACKormqr_("L", "N", &m, &nrhs, &mat->rank, mat->v, &mat->lda, mat->tau, x, &ldx, mat->fwork, &mat->lfwork, &info));
516: PetscCall(PetscFPTrapPop());
517: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "ORMQR - Bad orthogonal transform %d", (int)info);
518: if (PetscDefined(USE_COMPLEX)) PetscCall(MatConjugate_SeqDense(A));
519: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "QR factored matrix cannot be used for transpose solve");
520: PetscCall(PetscLogFlops(nrhs * (4.0 * m * mat->rank - PetscSqr(mat->rank))));
521: PetscFunctionReturn(PETSC_SUCCESS);
522: }
524: static PetscErrorCode MatSolve_SeqDense_SetUp(Mat A, Vec xx, Vec yy, PetscScalar **_y, PetscBLASInt *_m, PetscBLASInt *_k)
525: {
526: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
527: PetscScalar *y;
528: PetscBLASInt m = 0, k = 0;
530: PetscFunctionBegin;
531: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
532: PetscCall(PetscBLASIntCast(A->cmap->n, &k));
533: if (k < m) {
534: PetscCall(VecCopy(xx, mat->qrrhs));
535: PetscCall(VecGetArray(mat->qrrhs, &y));
536: } else {
537: PetscCall(VecCopy(xx, yy));
538: PetscCall(VecGetArray(yy, &y));
539: }
540: *_y = y;
541: *_k = k;
542: *_m = m;
543: PetscFunctionReturn(PETSC_SUCCESS);
544: }
546: static PetscErrorCode MatSolve_SeqDense_TearDown(Mat A, Vec xx, Vec yy, PetscScalar **_y, PetscBLASInt *_m, PetscBLASInt *_k)
547: {
548: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
549: PetscScalar *y = NULL;
550: PetscBLASInt m, k;
552: PetscFunctionBegin;
553: y = *_y;
554: *_y = NULL;
555: k = *_k;
556: m = *_m;
557: if (k < m) {
558: PetscScalar *yv;
559: PetscCall(VecGetArray(yy, &yv));
560: PetscCall(PetscArraycpy(yv, y, k));
561: PetscCall(VecRestoreArray(yy, &yv));
562: PetscCall(VecRestoreArray(mat->qrrhs, &y));
563: } else {
564: PetscCall(VecRestoreArray(yy, &y));
565: }
566: PetscFunctionReturn(PETSC_SUCCESS);
567: }
569: static PetscErrorCode MatSolve_SeqDense_LU(Mat A, Vec xx, Vec yy)
570: {
571: PetscScalar *y = NULL;
572: PetscBLASInt m = 0, k = 0;
574: PetscFunctionBegin;
575: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
576: PetscCall(MatSolve_SeqDense_Internal_LU(A, y, m, m, 1, k, PETSC_FALSE));
577: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
578: PetscFunctionReturn(PETSC_SUCCESS);
579: }
581: static PetscErrorCode MatSolveTranspose_SeqDense_LU(Mat A, Vec xx, Vec yy)
582: {
583: PetscScalar *y = NULL;
584: PetscBLASInt m = 0, k = 0;
586: PetscFunctionBegin;
587: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
588: PetscCall(MatSolve_SeqDense_Internal_LU(A, y, m, m, 1, k, PETSC_TRUE));
589: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
590: PetscFunctionReturn(PETSC_SUCCESS);
591: }
593: static PetscErrorCode MatSolve_SeqDense_Cholesky(Mat A, Vec xx, Vec yy)
594: {
595: PetscScalar *y = NULL;
596: PetscBLASInt m = 0, k = 0;
598: PetscFunctionBegin;
599: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
600: PetscCall(MatSolve_SeqDense_Internal_Cholesky(A, y, m, m, 1, k, PETSC_FALSE));
601: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
602: PetscFunctionReturn(PETSC_SUCCESS);
603: }
605: static PetscErrorCode MatSolveTranspose_SeqDense_Cholesky(Mat A, Vec xx, Vec yy)
606: {
607: PetscScalar *y = NULL;
608: PetscBLASInt m = 0, k = 0;
610: PetscFunctionBegin;
611: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
612: PetscCall(MatSolve_SeqDense_Internal_Cholesky(A, y, m, m, 1, k, PETSC_TRUE));
613: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
614: PetscFunctionReturn(PETSC_SUCCESS);
615: }
617: static PetscErrorCode MatSolve_SeqDense_QR(Mat A, Vec xx, Vec yy)
618: {
619: PetscScalar *y = NULL;
620: PetscBLASInt m = 0, k = 0;
622: PetscFunctionBegin;
623: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
624: PetscCall(MatSolve_SeqDense_Internal_QR(A, y, PetscMax(m, k), m, 1, k));
625: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
626: PetscFunctionReturn(PETSC_SUCCESS);
627: }
629: static PetscErrorCode MatSolveTranspose_SeqDense_QR(Mat A, Vec xx, Vec yy)
630: {
631: PetscScalar *y = NULL;
632: PetscBLASInt m = 0, k = 0;
634: PetscFunctionBegin;
635: PetscCall(MatSolve_SeqDense_SetUp(A, xx, yy, &y, &m, &k));
636: PetscCall(MatSolveTranspose_SeqDense_Internal_QR(A, y, PetscMax(m, k), m, 1, k));
637: PetscCall(MatSolve_SeqDense_TearDown(A, xx, yy, &y, &m, &k));
638: PetscFunctionReturn(PETSC_SUCCESS);
639: }
641: static PetscErrorCode MatMatSolve_SeqDense_SetUp(Mat A, Mat B, Mat X, PetscScalar **_y, PetscBLASInt *_ldy, PetscBLASInt *_m, PetscBLASInt *_nrhs, PetscBLASInt *_k)
642: {
643: const PetscScalar *b;
644: PetscScalar *y;
645: PetscInt n, _ldb, _ldx;
646: PetscBLASInt nrhs = 0, m = 0, k = 0, ldb = 0, ldx = 0, ldy = 0;
648: PetscFunctionBegin;
649: *_ldy = 0;
650: *_m = 0;
651: *_nrhs = 0;
652: *_k = 0;
653: *_y = NULL;
654: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
655: PetscCall(PetscBLASIntCast(A->cmap->n, &k));
656: PetscCall(MatGetSize(B, NULL, &n));
657: PetscCall(PetscBLASIntCast(n, &nrhs));
658: PetscCall(MatDenseGetLDA(B, &_ldb));
659: PetscCall(PetscBLASIntCast(_ldb, &ldb));
660: PetscCall(MatDenseGetLDA(X, &_ldx));
661: PetscCall(PetscBLASIntCast(_ldx, &ldx));
662: if (ldx < m) {
663: PetscCall(MatDenseGetArrayRead(B, &b));
664: PetscCall(PetscMalloc1(nrhs * m, &y));
665: if (ldb == m) {
666: PetscCall(PetscArraycpy(y, b, ldb * nrhs));
667: } else {
668: for (PetscInt j = 0; j < nrhs; j++) PetscCall(PetscArraycpy(&y[j * m], &b[j * ldb], m));
669: }
670: ldy = m;
671: PetscCall(MatDenseRestoreArrayRead(B, &b));
672: } else {
673: if (ldb == ldx) {
674: PetscCall(MatCopy(B, X, SAME_NONZERO_PATTERN));
675: PetscCall(MatDenseGetArray(X, &y));
676: } else {
677: PetscCall(MatDenseGetArray(X, &y));
678: PetscCall(MatDenseGetArrayRead(B, &b));
679: for (PetscInt j = 0; j < nrhs; j++) PetscCall(PetscArraycpy(&y[j * ldx], &b[j * ldb], m));
680: PetscCall(MatDenseRestoreArrayRead(B, &b));
681: }
682: ldy = ldx;
683: }
684: *_y = y;
685: *_ldy = ldy;
686: *_k = k;
687: *_m = m;
688: *_nrhs = nrhs;
689: PetscFunctionReturn(PETSC_SUCCESS);
690: }
692: static PetscErrorCode MatMatSolve_SeqDense_TearDown(Mat A, Mat B, Mat X, PetscScalar **_y, PetscBLASInt *_ldy, PetscBLASInt *_m, PetscBLASInt *_nrhs, PetscBLASInt *_k)
693: {
694: PetscScalar *y;
695: PetscInt _ldx;
696: PetscBLASInt k, ldy, nrhs, ldx = 0;
698: PetscFunctionBegin;
699: y = *_y;
700: *_y = NULL;
701: k = *_k;
702: ldy = *_ldy;
703: nrhs = *_nrhs;
704: PetscCall(MatDenseGetLDA(X, &_ldx));
705: PetscCall(PetscBLASIntCast(_ldx, &ldx));
706: if (ldx != ldy) {
707: PetscScalar *xv;
708: PetscCall(MatDenseGetArray(X, &xv));
709: for (PetscInt j = 0; j < nrhs; j++) PetscCall(PetscArraycpy(&xv[j * ldx], &y[j * ldy], k));
710: PetscCall(MatDenseRestoreArray(X, &xv));
711: PetscCall(PetscFree(y));
712: } else {
713: PetscCall(MatDenseRestoreArray(X, &y));
714: }
715: PetscFunctionReturn(PETSC_SUCCESS);
716: }
718: static PetscErrorCode MatMatSolve_SeqDense_LU(Mat A, Mat B, Mat X)
719: {
720: PetscScalar *y;
721: PetscBLASInt m, k, ldy, nrhs;
723: PetscFunctionBegin;
724: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
725: PetscCall(MatSolve_SeqDense_Internal_LU(A, y, ldy, m, nrhs, k, PETSC_FALSE));
726: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
727: PetscFunctionReturn(PETSC_SUCCESS);
728: }
730: static PetscErrorCode MatMatSolveTranspose_SeqDense_LU(Mat A, Mat B, Mat X)
731: {
732: PetscScalar *y;
733: PetscBLASInt m, k, ldy, nrhs;
735: PetscFunctionBegin;
736: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
737: PetscCall(MatSolve_SeqDense_Internal_LU(A, y, ldy, m, nrhs, k, PETSC_TRUE));
738: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
739: PetscFunctionReturn(PETSC_SUCCESS);
740: }
742: static PetscErrorCode MatMatSolve_SeqDense_Cholesky(Mat A, Mat B, Mat X)
743: {
744: PetscScalar *y;
745: PetscBLASInt m, k, ldy, nrhs;
747: PetscFunctionBegin;
748: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
749: PetscCall(MatSolve_SeqDense_Internal_Cholesky(A, y, ldy, m, nrhs, k, PETSC_FALSE));
750: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
751: PetscFunctionReturn(PETSC_SUCCESS);
752: }
754: static PetscErrorCode MatMatSolveTranspose_SeqDense_Cholesky(Mat A, Mat B, Mat X)
755: {
756: PetscScalar *y;
757: PetscBLASInt m, k, ldy, nrhs;
759: PetscFunctionBegin;
760: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
761: PetscCall(MatSolve_SeqDense_Internal_Cholesky(A, y, ldy, m, nrhs, k, PETSC_TRUE));
762: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
763: PetscFunctionReturn(PETSC_SUCCESS);
764: }
766: static PetscErrorCode MatMatSolve_SeqDense_QR(Mat A, Mat B, Mat X)
767: {
768: PetscScalar *y;
769: PetscBLASInt m, k, ldy, nrhs;
771: PetscFunctionBegin;
772: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
773: PetscCall(MatSolve_SeqDense_Internal_QR(A, y, ldy, m, nrhs, k));
774: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
775: PetscFunctionReturn(PETSC_SUCCESS);
776: }
778: static PetscErrorCode MatMatSolveTranspose_SeqDense_QR(Mat A, Mat B, Mat X)
779: {
780: PetscScalar *y;
781: PetscBLASInt m, k, ldy, nrhs;
783: PetscFunctionBegin;
784: PetscCall(MatMatSolve_SeqDense_SetUp(A, B, X, &y, &ldy, &m, &nrhs, &k));
785: PetscCall(MatSolveTranspose_SeqDense_Internal_QR(A, y, ldy, m, nrhs, k));
786: PetscCall(MatMatSolve_SeqDense_TearDown(A, B, X, &y, &ldy, &m, &nrhs, &k));
787: PetscFunctionReturn(PETSC_SUCCESS);
788: }
790: /* COMMENT: I have chosen to hide row permutation in the pivots,
791: rather than put it in the Mat->row slot.*/
792: PetscErrorCode MatLUFactor_SeqDense(Mat A, IS row, IS col, const MatFactorInfo *minfo)
793: {
794: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
795: PetscBLASInt n, m, info;
797: PetscFunctionBegin;
798: PetscCall(PetscBLASIntCast(A->cmap->n, &n));
799: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
800: if (!mat->pivots) { PetscCall(PetscMalloc1(A->rmap->n, &mat->pivots)); }
801: if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
802: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
803: PetscCallBLAS("LAPACKgetrf", LAPACKgetrf_(&m, &n, mat->v, &mat->lda, mat->pivots, &info));
804: PetscCall(PetscFPTrapPop());
806: PetscCheck(info >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Bad argument to LU factorization %d", (int)info);
807: PetscCheck(info <= 0, PETSC_COMM_SELF, PETSC_ERR_MAT_LU_ZRPVT, "Bad LU factorization %d", (int)info);
809: A->ops->solve = MatSolve_SeqDense_LU;
810: A->ops->matsolve = MatMatSolve_SeqDense_LU;
811: A->ops->solvetranspose = MatSolveTranspose_SeqDense_LU;
812: A->ops->matsolvetranspose = MatMatSolveTranspose_SeqDense_LU;
813: A->factortype = MAT_FACTOR_LU;
815: PetscCall(PetscFree(A->solvertype));
816: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &A->solvertype));
818: PetscCall(PetscLogFlops((2.0 * A->cmap->n * A->cmap->n * A->cmap->n) / 3));
819: PetscFunctionReturn(PETSC_SUCCESS);
820: }
822: static PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact, Mat A, const MatFactorInfo *info_dummy)
823: {
824: MatFactorInfo info;
826: PetscFunctionBegin;
827: PetscCall(MatDuplicateNoCreate_SeqDense(fact, A, MAT_COPY_VALUES));
828: PetscUseTypeMethod(fact, lufactor, NULL, NULL, &info);
829: PetscFunctionReturn(PETSC_SUCCESS);
830: }
832: PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact, Mat A, IS row, IS col, const MatFactorInfo *info)
833: {
834: PetscFunctionBegin;
835: fact->preallocated = PETSC_TRUE;
836: fact->assembled = PETSC_TRUE;
837: fact->ops->lufactornumeric = MatLUFactorNumeric_SeqDense;
838: PetscFunctionReturn(PETSC_SUCCESS);
839: }
841: /* Cholesky as L*L^T or L*D*L^T and the symmetric/hermitian complex variants */
842: PetscErrorCode MatCholeskyFactor_SeqDense(Mat A, IS perm, const MatFactorInfo *factinfo)
843: {
844: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
845: PetscBLASInt info, n;
847: PetscFunctionBegin;
848: PetscCall(PetscBLASIntCast(A->cmap->n, &n));
849: if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
850: if (A->spd == PETSC_BOOL3_TRUE) {
851: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
852: PetscCallBLAS("LAPACKpotrf", LAPACKpotrf_("L", &n, mat->v, &mat->lda, &info));
853: PetscCall(PetscFPTrapPop());
854: #if defined(PETSC_USE_COMPLEX)
855: } else if (A->hermitian == PETSC_BOOL3_TRUE) {
856: if (!mat->pivots) { PetscCall(PetscMalloc1(A->rmap->n, &mat->pivots)); }
857: if (!mat->fwork) {
858: PetscScalar dummy;
860: mat->lfwork = -1;
861: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
862: PetscCallBLAS("LAPACKhetrf", LAPACKhetrf_("L", &n, mat->v, &mat->lda, mat->pivots, &dummy, &mat->lfwork, &info));
863: PetscCall(PetscFPTrapPop());
864: mat->lfwork = (PetscInt)PetscRealPart(dummy);
865: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
866: }
867: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
868: PetscCallBLAS("LAPACKhetrf", LAPACKhetrf_("L", &n, mat->v, &mat->lda, mat->pivots, mat->fwork, &mat->lfwork, &info));
869: PetscCall(PetscFPTrapPop());
870: #endif
871: } else { /* symmetric case */
872: if (!mat->pivots) { PetscCall(PetscMalloc1(A->rmap->n, &mat->pivots)); }
873: if (!mat->fwork) {
874: PetscScalar dummy;
876: mat->lfwork = -1;
877: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
878: PetscCallBLAS("LAPACKsytrf", LAPACKsytrf_("L", &n, mat->v, &mat->lda, mat->pivots, &dummy, &mat->lfwork, &info));
879: PetscCall(PetscFPTrapPop());
880: mat->lfwork = (PetscInt)PetscRealPart(dummy);
881: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
882: }
883: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
884: PetscCallBLAS("LAPACKsytrf", LAPACKsytrf_("L", &n, mat->v, &mat->lda, mat->pivots, mat->fwork, &mat->lfwork, &info));
885: PetscCall(PetscFPTrapPop());
886: }
887: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_MAT_CH_ZRPVT, "Bad factorization: zero pivot in row %" PetscInt_FMT, (PetscInt)info - 1);
889: A->ops->solve = MatSolve_SeqDense_Cholesky;
890: A->ops->matsolve = MatMatSolve_SeqDense_Cholesky;
891: A->ops->solvetranspose = MatSolveTranspose_SeqDense_Cholesky;
892: A->ops->matsolvetranspose = MatMatSolveTranspose_SeqDense_Cholesky;
893: A->factortype = MAT_FACTOR_CHOLESKY;
895: PetscCall(PetscFree(A->solvertype));
896: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &A->solvertype));
898: PetscCall(PetscLogFlops((1.0 * A->cmap->n * A->cmap->n * A->cmap->n) / 3.0));
899: PetscFunctionReturn(PETSC_SUCCESS);
900: }
902: static PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact, Mat A, const MatFactorInfo *info_dummy)
903: {
904: MatFactorInfo info;
906: PetscFunctionBegin;
907: info.fill = 1.0;
909: PetscCall(MatDuplicateNoCreate_SeqDense(fact, A, MAT_COPY_VALUES));
910: PetscUseTypeMethod(fact, choleskyfactor, NULL, &info);
911: PetscFunctionReturn(PETSC_SUCCESS);
912: }
914: PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact, Mat A, IS row, const MatFactorInfo *info)
915: {
916: PetscFunctionBegin;
917: fact->assembled = PETSC_TRUE;
918: fact->preallocated = PETSC_TRUE;
919: fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense;
920: PetscFunctionReturn(PETSC_SUCCESS);
921: }
923: PetscErrorCode MatQRFactor_SeqDense(Mat A, IS col, const MatFactorInfo *minfo)
924: {
925: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
926: PetscBLASInt n, m, info, min, max;
928: PetscFunctionBegin;
929: PetscCall(PetscBLASIntCast(A->cmap->n, &n));
930: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
931: max = PetscMax(m, n);
932: min = PetscMin(m, n);
933: if (!mat->tau) { PetscCall(PetscMalloc1(min, &mat->tau)); }
934: if (!mat->pivots) { PetscCall(PetscMalloc1(n, &mat->pivots)); }
935: if (!mat->qrrhs) PetscCall(MatCreateVecs(A, NULL, &mat->qrrhs));
936: if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(PETSC_SUCCESS);
937: if (!mat->fwork) {
938: PetscScalar dummy;
940: mat->lfwork = -1;
941: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
942: PetscCallBLAS("LAPACKgeqrf", LAPACKgeqrf_(&m, &n, mat->v, &mat->lda, mat->tau, &dummy, &mat->lfwork, &info));
943: PetscCall(PetscFPTrapPop());
944: mat->lfwork = (PetscInt)PetscRealPart(dummy);
945: PetscCall(PetscMalloc1(mat->lfwork, &mat->fwork));
946: }
947: PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
948: PetscCallBLAS("LAPACKgeqrf", LAPACKgeqrf_(&m, &n, mat->v, &mat->lda, mat->tau, mat->fwork, &mat->lfwork, &info));
949: PetscCall(PetscFPTrapPop());
950: PetscCheck(!info, PETSC_COMM_SELF, PETSC_ERR_LIB, "Bad argument to QR factorization %d", (int)info);
951: // TODO: try to estimate rank or test for and use geqp3 for rank revealing QR. For now just say rank is min of m and n
952: mat->rank = min;
954: A->ops->solve = MatSolve_SeqDense_QR;
955: A->ops->matsolve = MatMatSolve_SeqDense_QR;
956: A->factortype = MAT_FACTOR_QR;
957: if (m == n) {
958: A->ops->solvetranspose = MatSolveTranspose_SeqDense_QR;
959: A->ops->matsolvetranspose = MatMatSolveTranspose_SeqDense_QR;
960: }
962: PetscCall(PetscFree(A->solvertype));
963: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &A->solvertype));
965: PetscCall(PetscLogFlops(2.0 * min * min * (max - min / 3.0)));
966: PetscFunctionReturn(PETSC_SUCCESS);
967: }
969: static PetscErrorCode MatQRFactorNumeric_SeqDense(Mat fact, Mat A, const MatFactorInfo *info_dummy)
970: {
971: MatFactorInfo info;
973: PetscFunctionBegin;
974: info.fill = 1.0;
976: PetscCall(MatDuplicateNoCreate_SeqDense(fact, A, MAT_COPY_VALUES));
977: PetscUseMethod(fact, "MatQRFactor_C", (Mat, IS, const MatFactorInfo *), (fact, NULL, &info));
978: PetscFunctionReturn(PETSC_SUCCESS);
979: }
981: PetscErrorCode MatQRFactorSymbolic_SeqDense(Mat fact, Mat A, IS row, const MatFactorInfo *info)
982: {
983: PetscFunctionBegin;
984: fact->assembled = PETSC_TRUE;
985: fact->preallocated = PETSC_TRUE;
986: PetscCall(PetscObjectComposeFunction((PetscObject)fact, "MatQRFactorNumeric_C", MatQRFactorNumeric_SeqDense));
987: PetscFunctionReturn(PETSC_SUCCESS);
988: }
990: /* uses LAPACK */
991: PETSC_INTERN PetscErrorCode MatGetFactor_seqdense_petsc(Mat A, MatFactorType ftype, Mat *fact)
992: {
993: PetscFunctionBegin;
994: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), fact));
995: PetscCall(MatSetSizes(*fact, A->rmap->n, A->cmap->n, A->rmap->n, A->cmap->n));
996: PetscCall(MatSetType(*fact, MATDENSE));
997: (*fact)->trivialsymbolic = PETSC_TRUE;
998: if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU) {
999: (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense;
1000: (*fact)->ops->ilufactorsymbolic = MatLUFactorSymbolic_SeqDense;
1001: } else if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1002: (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense;
1003: } else if (ftype == MAT_FACTOR_QR) {
1004: PetscCall(PetscObjectComposeFunction((PetscObject)*fact, "MatQRFactorSymbolic_C", MatQRFactorSymbolic_SeqDense));
1005: }
1006: (*fact)->factortype = ftype;
1008: PetscCall(PetscFree((*fact)->solvertype));
1009: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &(*fact)->solvertype));
1010: PetscCall(PetscStrallocpy(MATORDERINGEXTERNAL, (char **)&(*fact)->preferredordering[MAT_FACTOR_LU]));
1011: PetscCall(PetscStrallocpy(MATORDERINGEXTERNAL, (char **)&(*fact)->preferredordering[MAT_FACTOR_ILU]));
1012: PetscCall(PetscStrallocpy(MATORDERINGEXTERNAL, (char **)&(*fact)->preferredordering[MAT_FACTOR_CHOLESKY]));
1013: PetscCall(PetscStrallocpy(MATORDERINGEXTERNAL, (char **)&(*fact)->preferredordering[MAT_FACTOR_ICC]));
1014: PetscFunctionReturn(PETSC_SUCCESS);
1015: }
1017: static PetscErrorCode MatSOR_SeqDense(Mat A, Vec bb, PetscReal omega, MatSORType flag, PetscReal shift, PetscInt its, PetscInt lits, Vec xx)
1018: {
1019: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1020: PetscScalar *x, *v = mat->v, zero = 0.0, xt;
1021: const PetscScalar *b;
1022: PetscInt m = A->rmap->n, i;
1023: PetscBLASInt o = 1, bm = 0;
1025: PetscFunctionBegin;
1026: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1027: PetscCheck(A->offloadmask != PETSC_OFFLOAD_GPU, PETSC_COMM_SELF, PETSC_ERR_SUP, "Not implemented");
1028: #endif
1029: if (shift == -1) shift = 0.0; /* negative shift indicates do not error on zero diagonal; this code never zeros on zero diagonal */
1030: PetscCall(PetscBLASIntCast(m, &bm));
1031: if (flag & SOR_ZERO_INITIAL_GUESS) {
1032: /* this is a hack fix, should have another version without the second BLASdotu */
1033: PetscCall(VecSet(xx, zero));
1034: }
1035: PetscCall(VecGetArray(xx, &x));
1036: PetscCall(VecGetArrayRead(bb, &b));
1037: its = its * lits;
1038: PetscCheck(its > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Relaxation requires global its %" PetscInt_FMT " and local its %" PetscInt_FMT " both positive", its, lits);
1039: while (its--) {
1040: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
1041: for (i = 0; i < m; i++) {
1042: PetscCallBLAS("BLASdotu", xt = b[i] - BLASdotu_(&bm, v + i, &bm, x, &o));
1043: x[i] = (1. - omega) * x[i] + omega * (xt + v[i + i * m] * x[i]) / (v[i + i * m] + shift);
1044: }
1045: }
1046: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
1047: for (i = m - 1; i >= 0; i--) {
1048: PetscCallBLAS("BLASdotu", xt = b[i] - BLASdotu_(&bm, v + i, &bm, x, &o));
1049: x[i] = (1. - omega) * x[i] + omega * (xt + v[i + i * m] * x[i]) / (v[i + i * m] + shift);
1050: }
1051: }
1052: }
1053: PetscCall(VecRestoreArrayRead(bb, &b));
1054: PetscCall(VecRestoreArray(xx, &x));
1055: PetscFunctionReturn(PETSC_SUCCESS);
1056: }
1058: static PetscErrorCode MatMultColumnRangeKernel_SeqDense(Mat A, Vec xx, Vec yy, PetscInt c_start, PetscInt c_end, PetscBool trans, PetscBool herm)
1059: {
1060: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1061: PetscScalar *y, _DOne = 1.0, _DZero = 0.0;
1062: PetscBLASInt m, n, _One = 1;
1063: const PetscScalar *v = mat->v, *x;
1065: PetscFunctionBegin;
1066: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
1067: PetscCall(PetscBLASIntCast(c_end - c_start, &n));
1068: PetscCall(VecGetArrayRead(xx, &x));
1069: PetscCall(VecGetArrayWrite(yy, &y));
1070: if (!m || !n) {
1071: PetscBLASInt i;
1072: if (trans)
1073: for (i = 0; i < n; i++) y[i] = 0.0;
1074: else
1075: for (i = 0; i < m; i++) y[i] = 0.0;
1076: } else {
1077: if (trans) {
1078: if (herm) PetscCallBLAS("BLASgemv", BLASgemv_("C", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x, &_One, &_DZero, y + c_start, &_One));
1079: else PetscCallBLAS("BLASgemv", BLASgemv_("T", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x, &_One, &_DZero, y + c_start, &_One));
1080: } else {
1081: PetscCallBLAS("BLASgemv", BLASgemv_("N", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x + c_start, &_One, &_DZero, y, &_One));
1082: }
1083: PetscCall(PetscLogFlops(2.0 * m * n - n));
1084: }
1085: PetscCall(VecRestoreArrayRead(xx, &x));
1086: PetscCall(VecRestoreArrayWrite(yy, &y));
1087: PetscFunctionReturn(PETSC_SUCCESS);
1088: }
1090: PetscErrorCode MatMultHermitianTransposeColumnRange_SeqDense(Mat A, Vec xx, Vec yy, PetscInt c_start, PetscInt c_end)
1091: {
1092: PetscFunctionBegin;
1093: PetscCall(MatMultColumnRangeKernel_SeqDense(A, xx, yy, c_start, c_end, PETSC_TRUE, PETSC_TRUE));
1094: PetscFunctionReturn(PETSC_SUCCESS);
1095: }
1097: PetscErrorCode MatMult_SeqDense(Mat A, Vec xx, Vec yy)
1098: {
1099: PetscFunctionBegin;
1100: PetscCall(MatMultColumnRangeKernel_SeqDense(A, xx, yy, 0, A->cmap->n, PETSC_FALSE, PETSC_FALSE));
1101: PetscFunctionReturn(PETSC_SUCCESS);
1102: }
1104: PetscErrorCode MatMultTranspose_SeqDense(Mat A, Vec xx, Vec yy)
1105: {
1106: PetscFunctionBegin;
1107: PetscCall(MatMultColumnRangeKernel_SeqDense(A, xx, yy, 0, A->cmap->n, PETSC_TRUE, PETSC_FALSE));
1108: PetscFunctionReturn(PETSC_SUCCESS);
1109: }
1111: PetscErrorCode MatMultHermitianTranspose_SeqDense(Mat A, Vec xx, Vec yy)
1112: {
1113: PetscFunctionBegin;
1114: PetscCall(MatMultColumnRangeKernel_SeqDense(A, xx, yy, 0, A->cmap->n, PETSC_TRUE, PETSC_TRUE));
1115: PetscFunctionReturn(PETSC_SUCCESS);
1116: }
1118: static PetscErrorCode MatMultAddColumnRangeKernel_SeqDense(Mat A, Vec xx, Vec zz, Vec yy, PetscInt c_start, PetscInt c_end, PetscBool trans, PetscBool herm)
1119: {
1120: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1121: const PetscScalar *v = mat->v, *x;
1122: PetscScalar *y, _DOne = 1.0;
1123: PetscBLASInt m, n, _One = 1;
1125: PetscFunctionBegin;
1126: PetscCall(PetscBLASIntCast(A->rmap->n, &m));
1127: PetscCall(PetscBLASIntCast(c_end - c_start, &n));
1128: PetscCall(VecCopy(zz, yy));
1129: if (!m || !n) PetscFunctionReturn(PETSC_SUCCESS);
1130: PetscCall(VecGetArray(yy, &y));
1131: PetscCall(VecGetArrayRead(xx, &x));
1132: if (trans) {
1133: if (herm) PetscCallBLAS("BLASgemv", BLASgemv_("C", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x, &_One, &_DOne, y + c_start, &_One));
1134: else PetscCallBLAS("BLASgemv", BLASgemv_("T", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x, &_One, &_DOne, y + c_start, &_One));
1135: } else {
1136: PetscCallBLAS("BLASgemv", BLASgemv_("N", &m, &n, &_DOne, v + c_start * mat->lda, &mat->lda, x + c_start, &_One, &_DOne, y, &_One));
1137: }
1138: PetscCall(VecRestoreArrayRead(xx, &x));
1139: PetscCall(VecRestoreArray(yy, &y));
1140: PetscCall(PetscLogFlops(2.0 * m * n));
1141: PetscFunctionReturn(PETSC_SUCCESS);
1142: }
1144: PetscErrorCode MatMultAddColumnRange_SeqDense(Mat A, Vec xx, Vec zz, Vec yy, PetscInt c_start, PetscInt c_end)
1145: {
1146: PetscFunctionBegin;
1147: PetscCall(MatMultAddColumnRangeKernel_SeqDense(A, xx, zz, yy, c_start, c_end, PETSC_FALSE, PETSC_FALSE));
1148: PetscFunctionReturn(PETSC_SUCCESS);
1149: }
1151: PetscErrorCode MatMultHermitianTransposeAddColumnRange_SeqDense(Mat A, Vec xx, Vec zz, Vec yy, PetscInt c_start, PetscInt c_end)
1152: {
1153: PetscFunctionBegin;
1154: PetscMPIInt rank;
1155: PetscCallMPI(MPI_Comm_rank(MPI_COMM_WORLD, &rank));
1156: PetscCall(MatMultAddColumnRangeKernel_SeqDense(A, xx, zz, yy, c_start, c_end, PETSC_TRUE, PETSC_TRUE));
1157: PetscFunctionReturn(PETSC_SUCCESS);
1158: }
1160: PetscErrorCode MatMultAdd_SeqDense(Mat A, Vec xx, Vec zz, Vec yy)
1161: {
1162: PetscFunctionBegin;
1163: PetscCall(MatMultAddColumnRangeKernel_SeqDense(A, xx, zz, yy, 0, A->cmap->n, PETSC_FALSE, PETSC_FALSE));
1164: PetscFunctionReturn(PETSC_SUCCESS);
1165: }
1167: PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A, Vec xx, Vec zz, Vec yy)
1168: {
1169: PetscFunctionBegin;
1170: PetscCall(MatMultAddColumnRangeKernel_SeqDense(A, xx, zz, yy, 0, A->cmap->n, PETSC_TRUE, PETSC_FALSE));
1171: PetscFunctionReturn(PETSC_SUCCESS);
1172: }
1174: PetscErrorCode MatMultHermitianTransposeAdd_SeqDense(Mat A, Vec xx, Vec zz, Vec yy)
1175: {
1176: PetscFunctionBegin;
1177: PetscCall(MatMultAddColumnRangeKernel_SeqDense(A, xx, zz, yy, 0, A->cmap->n, PETSC_TRUE, PETSC_TRUE));
1178: PetscFunctionReturn(PETSC_SUCCESS);
1179: }
1181: static PetscErrorCode MatGetRow_SeqDense(Mat A, PetscInt row, PetscInt *ncols, PetscInt **cols, PetscScalar **vals)
1182: {
1183: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1184: PetscInt i;
1186: PetscFunctionBegin;
1187: if (ncols) *ncols = A->cmap->n;
1188: if (cols) {
1189: PetscCall(PetscMalloc1(A->cmap->n, cols));
1190: for (i = 0; i < A->cmap->n; i++) (*cols)[i] = i;
1191: }
1192: if (vals) {
1193: const PetscScalar *v;
1195: PetscCall(MatDenseGetArrayRead(A, &v));
1196: PetscCall(PetscMalloc1(A->cmap->n, vals));
1197: v += row;
1198: for (i = 0; i < A->cmap->n; i++) {
1199: (*vals)[i] = *v;
1200: v += mat->lda;
1201: }
1202: PetscCall(MatDenseRestoreArrayRead(A, &v));
1203: }
1204: PetscFunctionReturn(PETSC_SUCCESS);
1205: }
1207: static PetscErrorCode MatRestoreRow_SeqDense(Mat A, PetscInt row, PetscInt *ncols, PetscInt **cols, PetscScalar **vals)
1208: {
1209: PetscFunctionBegin;
1210: if (cols) PetscCall(PetscFree(*cols));
1211: if (vals) PetscCall(PetscFree(*vals));
1212: PetscFunctionReturn(PETSC_SUCCESS);
1213: }
1215: static PetscErrorCode MatSetValues_SeqDense(Mat A, PetscInt m, const PetscInt indexm[], PetscInt n, const PetscInt indexn[], const PetscScalar v[], InsertMode addv)
1216: {
1217: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1218: PetscScalar *av;
1219: PetscInt i, j, idx = 0;
1220: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1221: PetscOffloadMask oldf;
1222: #endif
1224: PetscFunctionBegin;
1225: PetscCall(MatDenseGetArray(A, &av));
1226: if (!mat->roworiented) {
1227: if (addv == INSERT_VALUES) {
1228: for (j = 0; j < n; j++) {
1229: if (indexn[j] < 0) {
1230: idx += m;
1231: continue;
1232: }
1233: PetscCheck(indexn[j] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, indexn[j], A->cmap->n - 1);
1234: for (i = 0; i < m; i++) {
1235: if (indexm[i] < 0) {
1236: idx++;
1237: continue;
1238: }
1239: PetscCheck(indexm[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, indexm[i], A->rmap->n - 1);
1240: av[indexn[j] * mat->lda + indexm[i]] = v ? v[idx++] : (idx++, 0.0);
1241: }
1242: }
1243: } else {
1244: for (j = 0; j < n; j++) {
1245: if (indexn[j] < 0) {
1246: idx += m;
1247: continue;
1248: }
1249: PetscCheck(indexn[j] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, indexn[j], A->cmap->n - 1);
1250: for (i = 0; i < m; i++) {
1251: if (indexm[i] < 0) {
1252: idx++;
1253: continue;
1254: }
1255: PetscCheck(indexm[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, indexm[i], A->rmap->n - 1);
1256: av[indexn[j] * mat->lda + indexm[i]] += v ? v[idx++] : (idx++, 0.0);
1257: }
1258: }
1259: }
1260: } else {
1261: if (addv == INSERT_VALUES) {
1262: for (i = 0; i < m; i++) {
1263: if (indexm[i] < 0) {
1264: idx += n;
1265: continue;
1266: }
1267: PetscCheck(indexm[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, indexm[i], A->rmap->n - 1);
1268: for (j = 0; j < n; j++) {
1269: if (indexn[j] < 0) {
1270: idx++;
1271: continue;
1272: }
1273: PetscCheck(indexn[j] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, indexn[j], A->cmap->n - 1);
1274: av[indexn[j] * mat->lda + indexm[i]] = v ? v[idx++] : (idx++, 0.0);
1275: }
1276: }
1277: } else {
1278: for (i = 0; i < m; i++) {
1279: if (indexm[i] < 0) {
1280: idx += n;
1281: continue;
1282: }
1283: PetscCheck(indexm[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, indexm[i], A->rmap->n - 1);
1284: for (j = 0; j < n; j++) {
1285: if (indexn[j] < 0) {
1286: idx++;
1287: continue;
1288: }
1289: PetscCheck(indexn[j] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, indexn[j], A->cmap->n - 1);
1290: av[indexn[j] * mat->lda + indexm[i]] += v ? v[idx++] : (idx++, 0.0);
1291: }
1292: }
1293: }
1294: }
1295: /* hack to prevent unneeded copy to the GPU while returning the array */
1296: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1297: oldf = A->offloadmask;
1298: A->offloadmask = PETSC_OFFLOAD_GPU;
1299: #endif
1300: PetscCall(MatDenseRestoreArray(A, &av));
1301: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1302: A->offloadmask = (oldf == PETSC_OFFLOAD_UNALLOCATED ? PETSC_OFFLOAD_UNALLOCATED : PETSC_OFFLOAD_CPU);
1303: #endif
1304: PetscFunctionReturn(PETSC_SUCCESS);
1305: }
1307: static PetscErrorCode MatGetValues_SeqDense(Mat A, PetscInt m, const PetscInt indexm[], PetscInt n, const PetscInt indexn[], PetscScalar v[])
1308: {
1309: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1310: const PetscScalar *vv;
1311: PetscInt i, j;
1313: PetscFunctionBegin;
1314: PetscCall(MatDenseGetArrayRead(A, &vv));
1315: /* row-oriented output */
1316: for (i = 0; i < m; i++) {
1317: if (indexm[i] < 0) {
1318: v += n;
1319: continue;
1320: }
1321: PetscCheck(indexm[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " requested larger than number rows %" PetscInt_FMT, indexm[i], A->rmap->n);
1322: for (j = 0; j < n; j++) {
1323: if (indexn[j] < 0) {
1324: v++;
1325: continue;
1326: }
1327: PetscCheck(indexn[j] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column %" PetscInt_FMT " requested larger than number columns %" PetscInt_FMT, indexn[j], A->cmap->n);
1328: *v++ = vv[indexn[j] * mat->lda + indexm[i]];
1329: }
1330: }
1331: PetscCall(MatDenseRestoreArrayRead(A, &vv));
1332: PetscFunctionReturn(PETSC_SUCCESS);
1333: }
1335: PetscErrorCode MatView_Dense_Binary(Mat mat, PetscViewer viewer)
1336: {
1337: PetscBool skipHeader;
1338: PetscViewerFormat format;
1339: PetscInt header[4], M, N, m, lda, i, j, k;
1340: const PetscScalar *v;
1341: PetscScalar *vwork;
1343: PetscFunctionBegin;
1344: PetscCall(PetscViewerSetUp(viewer));
1345: PetscCall(PetscViewerBinaryGetSkipHeader(viewer, &skipHeader));
1346: PetscCall(PetscViewerGetFormat(viewer, &format));
1347: if (skipHeader) format = PETSC_VIEWER_NATIVE;
1349: PetscCall(MatGetSize(mat, &M, &N));
1351: /* write matrix header */
1352: header[0] = MAT_FILE_CLASSID;
1353: header[1] = M;
1354: header[2] = N;
1355: header[3] = (format == PETSC_VIEWER_NATIVE) ? MATRIX_BINARY_FORMAT_DENSE : M * N;
1356: if (!skipHeader) PetscCall(PetscViewerBinaryWrite(viewer, header, 4, PETSC_INT));
1358: PetscCall(MatGetLocalSize(mat, &m, NULL));
1359: if (format != PETSC_VIEWER_NATIVE) {
1360: PetscInt nnz = m * N, *iwork;
1361: /* store row lengths for each row */
1362: PetscCall(PetscMalloc1(nnz, &iwork));
1363: for (i = 0; i < m; i++) iwork[i] = N;
1364: PetscCall(PetscViewerBinaryWriteAll(viewer, iwork, m, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_INT));
1365: /* store column indices (zero start index) */
1366: for (k = 0, i = 0; i < m; i++)
1367: for (j = 0; j < N; j++, k++) iwork[k] = j;
1368: PetscCall(PetscViewerBinaryWriteAll(viewer, iwork, nnz, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_INT));
1369: PetscCall(PetscFree(iwork));
1370: }
1371: /* store matrix values as a dense matrix in row major order */
1372: PetscCall(PetscMalloc1(m * N, &vwork));
1373: PetscCall(MatDenseGetArrayRead(mat, &v));
1374: PetscCall(MatDenseGetLDA(mat, &lda));
1375: for (k = 0, i = 0; i < m; i++)
1376: for (j = 0; j < N; j++, k++) vwork[k] = v[i + lda * j];
1377: PetscCall(MatDenseRestoreArrayRead(mat, &v));
1378: PetscCall(PetscViewerBinaryWriteAll(viewer, vwork, m * N, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_SCALAR));
1379: PetscCall(PetscFree(vwork));
1380: PetscFunctionReturn(PETSC_SUCCESS);
1381: }
1383: PetscErrorCode MatLoad_Dense_Binary(Mat mat, PetscViewer viewer)
1384: {
1385: PetscBool skipHeader;
1386: PetscInt header[4], M, N, m, nz, lda, i, j, k;
1387: PetscInt rows, cols;
1388: PetscScalar *v, *vwork;
1390: PetscFunctionBegin;
1391: PetscCall(PetscViewerSetUp(viewer));
1392: PetscCall(PetscViewerBinaryGetSkipHeader(viewer, &skipHeader));
1394: if (!skipHeader) {
1395: PetscCall(PetscViewerBinaryRead(viewer, header, 4, NULL, PETSC_INT));
1396: PetscCheck(header[0] == MAT_FILE_CLASSID, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Not a matrix object in file");
1397: M = header[1];
1398: N = header[2];
1399: PetscCheck(M >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix row size (%" PetscInt_FMT ") in file is negative", M);
1400: PetscCheck(N >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix column size (%" PetscInt_FMT ") in file is negative", N);
1401: nz = header[3];
1402: PetscCheck(nz == MATRIX_BINARY_FORMAT_DENSE || nz >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Unknown matrix format %" PetscInt_FMT " in file", nz);
1403: } else {
1404: PetscCall(MatGetSize(mat, &M, &N));
1405: PetscCheck(M >= 0 && N >= 0, PETSC_COMM_SELF, PETSC_ERR_USER, "Matrix binary file header was skipped, thus the user must specify the global sizes of input matrix");
1406: nz = MATRIX_BINARY_FORMAT_DENSE;
1407: }
1409: /* setup global sizes if not set */
1410: if (mat->rmap->N < 0) mat->rmap->N = M;
1411: if (mat->cmap->N < 0) mat->cmap->N = N;
1412: PetscCall(MatSetUp(mat));
1413: /* check if global sizes are correct */
1414: PetscCall(MatGetSize(mat, &rows, &cols));
1415: PetscCheck(M == rows && N == cols, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%" PetscInt_FMT ", %" PetscInt_FMT ") than the input matrix (%" PetscInt_FMT ", %" PetscInt_FMT ")", M, N, rows, cols);
1417: PetscCall(MatGetSize(mat, NULL, &N));
1418: PetscCall(MatGetLocalSize(mat, &m, NULL));
1419: PetscCall(MatDenseGetArray(mat, &v));
1420: PetscCall(MatDenseGetLDA(mat, &lda));
1421: if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense format */
1422: PetscInt nnz = m * N;
1423: /* read in matrix values */
1424: PetscCall(PetscMalloc1(nnz, &vwork));
1425: PetscCall(PetscViewerBinaryReadAll(viewer, vwork, nnz, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_SCALAR));
1426: /* store values in column major order */
1427: for (j = 0; j < N; j++)
1428: for (i = 0; i < m; i++) v[i + lda * j] = vwork[i * N + j];
1429: PetscCall(PetscFree(vwork));
1430: } else { /* matrix in file is sparse format */
1431: PetscInt nnz = 0, *rlens, *icols;
1432: /* read in row lengths */
1433: PetscCall(PetscMalloc1(m, &rlens));
1434: PetscCall(PetscViewerBinaryReadAll(viewer, rlens, m, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_INT));
1435: for (i = 0; i < m; i++) nnz += rlens[i];
1436: /* read in column indices and values */
1437: PetscCall(PetscMalloc2(nnz, &icols, nnz, &vwork));
1438: PetscCall(PetscViewerBinaryReadAll(viewer, icols, nnz, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_INT));
1439: PetscCall(PetscViewerBinaryReadAll(viewer, vwork, nnz, PETSC_DETERMINE, PETSC_DETERMINE, PETSC_SCALAR));
1440: /* store values in column major order */
1441: for (k = 0, i = 0; i < m; i++)
1442: for (j = 0; j < rlens[i]; j++, k++) v[i + lda * icols[k]] = vwork[k];
1443: PetscCall(PetscFree(rlens));
1444: PetscCall(PetscFree2(icols, vwork));
1445: }
1446: PetscCall(MatDenseRestoreArray(mat, &v));
1447: PetscCall(MatAssemblyBegin(mat, MAT_FINAL_ASSEMBLY));
1448: PetscCall(MatAssemblyEnd(mat, MAT_FINAL_ASSEMBLY));
1449: PetscFunctionReturn(PETSC_SUCCESS);
1450: }
1452: static PetscErrorCode MatLoad_SeqDense(Mat newMat, PetscViewer viewer)
1453: {
1454: PetscBool isbinary, ishdf5;
1456: PetscFunctionBegin;
1459: /* force binary viewer to load .info file if it has not yet done so */
1460: PetscCall(PetscViewerSetUp(viewer));
1461: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1462: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERHDF5, &ishdf5));
1463: if (isbinary) {
1464: PetscCall(MatLoad_Dense_Binary(newMat, viewer));
1465: } else if (ishdf5) {
1466: #if defined(PETSC_HAVE_HDF5)
1467: PetscCall(MatLoad_Dense_HDF5(newMat, viewer));
1468: #else
1469: SETERRQ(PetscObjectComm((PetscObject)newMat), PETSC_ERR_SUP, "HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5");
1470: #endif
1471: } else {
1472: SETERRQ(PetscObjectComm((PetscObject)newMat), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)newMat)->type_name);
1473: }
1474: PetscFunctionReturn(PETSC_SUCCESS);
1475: }
1477: static PetscErrorCode MatView_SeqDense_ASCII(Mat A, PetscViewer viewer)
1478: {
1479: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
1480: PetscInt i, j;
1481: const char *name;
1482: PetscScalar *v, *av;
1483: PetscViewerFormat format;
1484: #if defined(PETSC_USE_COMPLEX)
1485: PetscBool allreal = PETSC_TRUE;
1486: #endif
1488: PetscFunctionBegin;
1489: PetscCall(MatDenseGetArrayRead(A, (const PetscScalar **)&av));
1490: PetscCall(PetscViewerGetFormat(viewer, &format));
1491: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1492: PetscFunctionReturn(PETSC_SUCCESS); /* do nothing for now */
1493: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1494: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
1495: for (i = 0; i < A->rmap->n; i++) {
1496: v = av + i;
1497: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i));
1498: for (j = 0; j < A->cmap->n; j++) {
1499: #if defined(PETSC_USE_COMPLEX)
1500: if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) {
1501: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", j, (double)PetscRealPart(*v), (double)PetscImaginaryPart(*v)));
1502: } else if (PetscRealPart(*v)) {
1503: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", j, (double)PetscRealPart(*v)));
1504: }
1505: #else
1506: if (*v) PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", j, (double)*v));
1507: #endif
1508: v += a->lda;
1509: }
1510: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
1511: }
1512: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
1513: } else {
1514: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
1515: #if defined(PETSC_USE_COMPLEX)
1516: /* determine if matrix has all real values */
1517: for (j = 0; j < A->cmap->n; j++) {
1518: v = av + j * a->lda;
1519: for (i = 0; i < A->rmap->n; i++) {
1520: if (PetscImaginaryPart(v[i])) {
1521: allreal = PETSC_FALSE;
1522: break;
1523: }
1524: }
1525: }
1526: #endif
1527: if (format == PETSC_VIEWER_ASCII_MATLAB) {
1528: PetscCall(PetscObjectGetName((PetscObject)A, &name));
1529: PetscCall(PetscViewerASCIIPrintf(viewer, "%% Size = %" PetscInt_FMT " %" PetscInt_FMT " \n", A->rmap->n, A->cmap->n));
1530: PetscCall(PetscViewerASCIIPrintf(viewer, "%s = zeros(%" PetscInt_FMT ",%" PetscInt_FMT ");\n", name, A->rmap->n, A->cmap->n));
1531: PetscCall(PetscViewerASCIIPrintf(viewer, "%s = [\n", name));
1532: }
1534: for (i = 0; i < A->rmap->n; i++) {
1535: v = av + i;
1536: for (j = 0; j < A->cmap->n; j++) {
1537: #if defined(PETSC_USE_COMPLEX)
1538: if (allreal) {
1539: PetscCall(PetscViewerASCIIPrintf(viewer, "%18.16e ", (double)PetscRealPart(*v)));
1540: } else {
1541: PetscCall(PetscViewerASCIIPrintf(viewer, "%18.16e + %18.16ei ", (double)PetscRealPart(*v), (double)PetscImaginaryPart(*v)));
1542: }
1543: #else
1544: PetscCall(PetscViewerASCIIPrintf(viewer, "%18.16e ", (double)*v));
1545: #endif
1546: v += a->lda;
1547: }
1548: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
1549: }
1550: if (format == PETSC_VIEWER_ASCII_MATLAB) PetscCall(PetscViewerASCIIPrintf(viewer, "];\n"));
1551: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
1552: }
1553: PetscCall(MatDenseRestoreArrayRead(A, (const PetscScalar **)&av));
1554: PetscCall(PetscViewerFlush(viewer));
1555: PetscFunctionReturn(PETSC_SUCCESS);
1556: }
1558: #include <petscdraw.h>
1559: static PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw, void *Aa)
1560: {
1561: Mat A = (Mat)Aa;
1562: PetscInt m = A->rmap->n, n = A->cmap->n, i, j;
1563: int color = PETSC_DRAW_WHITE;
1564: const PetscScalar *v;
1565: PetscViewer viewer;
1566: PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r;
1567: PetscViewerFormat format;
1569: PetscFunctionBegin;
1570: PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer));
1571: PetscCall(PetscViewerGetFormat(viewer, &format));
1572: PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr));
1574: /* Loop over matrix elements drawing boxes */
1575: PetscCall(MatDenseGetArrayRead(A, &v));
1576: if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1577: PetscDrawCollectiveBegin(draw);
1578: /* Blue for negative and Red for positive */
1579: for (j = 0; j < n; j++) {
1580: x_l = j;
1581: x_r = x_l + 1.0;
1582: for (i = 0; i < m; i++) {
1583: y_l = m - i - 1.0;
1584: y_r = y_l + 1.0;
1585: if (PetscRealPart(v[j * m + i]) > 0.) color = PETSC_DRAW_RED;
1586: else if (PetscRealPart(v[j * m + i]) < 0.) color = PETSC_DRAW_BLUE;
1587: else continue;
1588: PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color));
1589: }
1590: }
1591: PetscDrawCollectiveEnd(draw);
1592: } else {
1593: /* use contour shading to indicate magnitude of values */
1594: /* first determine max of all nonzero values */
1595: PetscReal minv = 0.0, maxv = 0.0;
1596: PetscDraw popup;
1598: for (i = 0; i < m * n; i++) {
1599: if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]);
1600: }
1601: if (minv >= maxv) maxv = minv + PETSC_SMALL;
1602: PetscCall(PetscDrawGetPopup(draw, &popup));
1603: PetscCall(PetscDrawScalePopup(popup, minv, maxv));
1605: PetscDrawCollectiveBegin(draw);
1606: for (j = 0; j < n; j++) {
1607: x_l = j;
1608: x_r = x_l + 1.0;
1609: for (i = 0; i < m; i++) {
1610: y_l = m - i - 1.0;
1611: y_r = y_l + 1.0;
1612: color = PetscDrawRealToColor(PetscAbsScalar(v[j * m + i]), minv, maxv);
1613: PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color));
1614: }
1615: }
1616: PetscDrawCollectiveEnd(draw);
1617: }
1618: PetscCall(MatDenseRestoreArrayRead(A, &v));
1619: PetscFunctionReturn(PETSC_SUCCESS);
1620: }
1622: static PetscErrorCode MatView_SeqDense_Draw(Mat A, PetscViewer viewer)
1623: {
1624: PetscDraw draw;
1625: PetscBool isnull;
1626: PetscReal xr, yr, xl, yl, h, w;
1628: PetscFunctionBegin;
1629: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
1630: PetscCall(PetscDrawIsNull(draw, &isnull));
1631: if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
1633: xr = A->cmap->n;
1634: yr = A->rmap->n;
1635: h = yr / 10.0;
1636: w = xr / 10.0;
1637: xr += w;
1638: yr += h;
1639: xl = -w;
1640: yl = -h;
1641: PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr));
1642: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer));
1643: PetscCall(PetscDrawZoom(draw, MatView_SeqDense_Draw_Zoom, A));
1644: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL));
1645: PetscCall(PetscDrawSave(draw));
1646: PetscFunctionReturn(PETSC_SUCCESS);
1647: }
1649: PetscErrorCode MatView_SeqDense(Mat A, PetscViewer viewer)
1650: {
1651: PetscBool iascii, isbinary, isdraw;
1653: PetscFunctionBegin;
1654: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
1655: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1656: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1657: if (iascii) PetscCall(MatView_SeqDense_ASCII(A, viewer));
1658: else if (isbinary) PetscCall(MatView_Dense_Binary(A, viewer));
1659: else if (isdraw) PetscCall(MatView_SeqDense_Draw(A, viewer));
1660: PetscFunctionReturn(PETSC_SUCCESS);
1661: }
1663: static PetscErrorCode MatDensePlaceArray_SeqDense(Mat A, const PetscScalar *array)
1664: {
1665: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
1667: PetscFunctionBegin;
1668: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
1669: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
1670: PetscCheck(!a->unplacedarray, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreArray() first");
1671: a->unplacedarray = a->v;
1672: a->unplaced_user_alloc = a->user_alloc;
1673: a->v = (PetscScalar *)array;
1674: a->user_alloc = PETSC_TRUE;
1675: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1676: A->offloadmask = PETSC_OFFLOAD_CPU;
1677: #endif
1678: PetscFunctionReturn(PETSC_SUCCESS);
1679: }
1681: static PetscErrorCode MatDenseResetArray_SeqDense(Mat A)
1682: {
1683: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
1685: PetscFunctionBegin;
1686: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
1687: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
1688: a->v = a->unplacedarray;
1689: a->user_alloc = a->unplaced_user_alloc;
1690: a->unplacedarray = NULL;
1691: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1692: A->offloadmask = PETSC_OFFLOAD_CPU;
1693: #endif
1694: PetscFunctionReturn(PETSC_SUCCESS);
1695: }
1697: static PetscErrorCode MatDenseReplaceArray_SeqDense(Mat A, const PetscScalar *array)
1698: {
1699: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
1701: PetscFunctionBegin;
1702: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
1703: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
1704: if (!a->user_alloc) PetscCall(PetscFree(a->v));
1705: a->v = (PetscScalar *)array;
1706: a->user_alloc = PETSC_FALSE;
1707: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
1708: A->offloadmask = PETSC_OFFLOAD_CPU;
1709: #endif
1710: PetscFunctionReturn(PETSC_SUCCESS);
1711: }
1713: PetscErrorCode MatDestroy_SeqDense(Mat mat)
1714: {
1715: Mat_SeqDense *l = (Mat_SeqDense *)mat->data;
1717: PetscFunctionBegin;
1718: PetscCall(PetscLogObjectState((PetscObject)mat, "Rows %" PetscInt_FMT " Cols %" PetscInt_FMT, mat->rmap->n, mat->cmap->n));
1719: PetscCall(VecDestroy(&l->qrrhs));
1720: PetscCall(PetscFree(l->tau));
1721: PetscCall(PetscFree(l->pivots));
1722: PetscCall(PetscFree(l->fwork));
1723: if (!l->user_alloc) PetscCall(PetscFree(l->v));
1724: if (!l->unplaced_user_alloc) PetscCall(PetscFree(l->unplacedarray));
1725: PetscCheck(!l->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
1726: PetscCheck(!l->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
1727: PetscCall(VecDestroy(&l->cvec));
1728: PetscCall(MatDestroy(&l->cmat));
1729: PetscCall(PetscFree(mat->data));
1731: PetscCall(PetscObjectChangeTypeName((PetscObject)mat, NULL));
1732: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatQRFactor_C", NULL));
1733: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatQRFactorSymbolic_C", NULL));
1734: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatQRFactorNumeric_C", NULL));
1735: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetLDA_C", NULL));
1736: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseSetLDA_C", NULL));
1737: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetArray_C", NULL));
1738: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreArray_C", NULL));
1739: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDensePlaceArray_C", NULL));
1740: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseResetArray_C", NULL));
1741: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseReplaceArray_C", NULL));
1742: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetArrayRead_C", NULL));
1743: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreArrayRead_C", NULL));
1744: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetArrayWrite_C", NULL));
1745: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreArrayWrite_C", NULL));
1746: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_seqdense_seqaij_C", NULL));
1747: #if defined(PETSC_HAVE_ELEMENTAL)
1748: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_seqdense_elemental_C", NULL));
1749: #endif
1750: #if defined(PETSC_HAVE_SCALAPACK)
1751: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_seqdense_scalapack_C", NULL));
1752: #endif
1753: #if defined(PETSC_HAVE_CUDA)
1754: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_seqdense_seqdensecuda_C", NULL));
1755: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdensecuda_seqdensecuda_C", NULL));
1756: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdensecuda_seqdense_C", NULL));
1757: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdense_seqdensecuda_C", NULL));
1758: #endif
1759: #if defined(PETSC_HAVE_HIP)
1760: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_seqdense_seqdensehip_C", NULL));
1761: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdensehip_seqdensehip_C", NULL));
1762: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdensehip_seqdense_C", NULL));
1763: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdense_seqdensehip_C", NULL));
1764: #endif
1765: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatSeqDenseSetPreallocation_C", NULL));
1766: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqaij_seqdense_C", NULL));
1767: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqdense_seqdense_C", NULL));
1768: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqbaij_seqdense_C", NULL));
1769: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatProductSetFromOptions_seqsbaij_seqdense_C", NULL));
1771: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetColumn_C", NULL));
1772: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreColumn_C", NULL));
1773: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetColumnVec_C", NULL));
1774: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreColumnVec_C", NULL));
1775: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetColumnVecRead_C", NULL));
1776: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreColumnVecRead_C", NULL));
1777: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetColumnVecWrite_C", NULL));
1778: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreColumnVecWrite_C", NULL));
1779: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseGetSubMatrix_C", NULL));
1780: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDenseRestoreSubMatrix_C", NULL));
1781: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMultAddColumnRange_C", NULL));
1782: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMultHermitianTransposeColumnRange_C", NULL));
1783: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMultHermitianTransposeAddColumnRange_C", NULL));
1784: PetscFunctionReturn(PETSC_SUCCESS);
1785: }
1787: static PetscErrorCode MatTranspose_SeqDense(Mat A, MatReuse reuse, Mat *matout)
1788: {
1789: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1790: PetscInt k, j, m = A->rmap->n, M = mat->lda, n = A->cmap->n;
1791: PetscScalar *v, tmp;
1793: PetscFunctionBegin;
1794: if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *matout));
1795: if (reuse == MAT_INPLACE_MATRIX) {
1796: if (m == n) { /* in place transpose */
1797: PetscCall(MatDenseGetArray(A, &v));
1798: for (j = 0; j < m; j++) {
1799: for (k = 0; k < j; k++) {
1800: tmp = v[j + k * M];
1801: v[j + k * M] = v[k + j * M];
1802: v[k + j * M] = tmp;
1803: }
1804: }
1805: PetscCall(MatDenseRestoreArray(A, &v));
1806: } else { /* reuse memory, temporary allocates new memory */
1807: PetscScalar *v2;
1808: PetscLayout tmplayout;
1810: PetscCall(PetscMalloc1((size_t)m * n, &v2));
1811: PetscCall(MatDenseGetArray(A, &v));
1812: for (j = 0; j < n; j++) {
1813: for (k = 0; k < m; k++) v2[j + (size_t)k * n] = v[k + (size_t)j * M];
1814: }
1815: PetscCall(PetscArraycpy(v, v2, (size_t)m * n));
1816: PetscCall(PetscFree(v2));
1817: PetscCall(MatDenseRestoreArray(A, &v));
1818: /* cleanup size dependent quantities */
1819: PetscCall(VecDestroy(&mat->cvec));
1820: PetscCall(MatDestroy(&mat->cmat));
1821: PetscCall(PetscFree(mat->pivots));
1822: PetscCall(PetscFree(mat->fwork));
1823: /* swap row/col layouts */
1824: mat->lda = n;
1825: tmplayout = A->rmap;
1826: A->rmap = A->cmap;
1827: A->cmap = tmplayout;
1828: }
1829: } else { /* out-of-place transpose */
1830: Mat tmat;
1831: Mat_SeqDense *tmatd;
1832: PetscScalar *v2;
1833: PetscInt M2;
1835: if (reuse == MAT_INITIAL_MATRIX) {
1836: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &tmat));
1837: PetscCall(MatSetSizes(tmat, A->cmap->n, A->rmap->n, A->cmap->n, A->rmap->n));
1838: PetscCall(MatSetType(tmat, ((PetscObject)A)->type_name));
1839: PetscCall(MatSeqDenseSetPreallocation(tmat, NULL));
1840: } else tmat = *matout;
1842: PetscCall(MatDenseGetArrayRead(A, (const PetscScalar **)&v));
1843: PetscCall(MatDenseGetArray(tmat, &v2));
1844: tmatd = (Mat_SeqDense *)tmat->data;
1845: M2 = tmatd->lda;
1846: for (j = 0; j < n; j++) {
1847: for (k = 0; k < m; k++) v2[j + k * M2] = v[k + j * M];
1848: }
1849: PetscCall(MatDenseRestoreArray(tmat, &v2));
1850: PetscCall(MatDenseRestoreArrayRead(A, (const PetscScalar **)&v));
1851: PetscCall(MatAssemblyBegin(tmat, MAT_FINAL_ASSEMBLY));
1852: PetscCall(MatAssemblyEnd(tmat, MAT_FINAL_ASSEMBLY));
1853: *matout = tmat;
1854: }
1855: PetscFunctionReturn(PETSC_SUCCESS);
1856: }
1858: static PetscErrorCode MatEqual_SeqDense(Mat A1, Mat A2, PetscBool *flg)
1859: {
1860: Mat_SeqDense *mat1 = (Mat_SeqDense *)A1->data;
1861: Mat_SeqDense *mat2 = (Mat_SeqDense *)A2->data;
1862: PetscInt i;
1863: const PetscScalar *v1, *v2;
1865: PetscFunctionBegin;
1866: if (A1->rmap->n != A2->rmap->n) {
1867: *flg = PETSC_FALSE;
1868: PetscFunctionReturn(PETSC_SUCCESS);
1869: }
1870: if (A1->cmap->n != A2->cmap->n) {
1871: *flg = PETSC_FALSE;
1872: PetscFunctionReturn(PETSC_SUCCESS);
1873: }
1874: PetscCall(MatDenseGetArrayRead(A1, &v1));
1875: PetscCall(MatDenseGetArrayRead(A2, &v2));
1876: for (i = 0; i < A1->cmap->n; i++) {
1877: PetscCall(PetscArraycmp(v1, v2, A1->rmap->n, flg));
1878: if (*flg == PETSC_FALSE) PetscFunctionReturn(PETSC_SUCCESS);
1879: v1 += mat1->lda;
1880: v2 += mat2->lda;
1881: }
1882: PetscCall(MatDenseRestoreArrayRead(A1, &v1));
1883: PetscCall(MatDenseRestoreArrayRead(A2, &v2));
1884: *flg = PETSC_TRUE;
1885: PetscFunctionReturn(PETSC_SUCCESS);
1886: }
1888: PetscErrorCode MatGetDiagonal_SeqDense(Mat A, Vec v)
1889: {
1890: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1891: PetscInt i, n, len;
1892: PetscScalar *x;
1893: const PetscScalar *vv;
1895: PetscFunctionBegin;
1896: PetscCall(VecGetSize(v, &n));
1897: PetscCall(VecGetArray(v, &x));
1898: len = PetscMin(A->rmap->n, A->cmap->n);
1899: PetscCall(MatDenseGetArrayRead(A, &vv));
1900: PetscCheck(n == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming mat and vec");
1901: for (i = 0; i < len; i++) x[i] = vv[i * mat->lda + i];
1902: PetscCall(MatDenseRestoreArrayRead(A, &vv));
1903: PetscCall(VecRestoreArray(v, &x));
1904: PetscFunctionReturn(PETSC_SUCCESS);
1905: }
1907: static PetscErrorCode MatDiagonalScale_SeqDense(Mat A, Vec ll, Vec rr)
1908: {
1909: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1910: const PetscScalar *l, *r;
1911: PetscScalar x, *v, *vv;
1912: PetscInt i, j, m = A->rmap->n, n = A->cmap->n;
1914: PetscFunctionBegin;
1915: PetscCall(MatDenseGetArray(A, &vv));
1916: if (ll) {
1917: PetscCall(VecGetSize(ll, &m));
1918: PetscCall(VecGetArrayRead(ll, &l));
1919: PetscCheck(m == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Left scaling vec wrong size");
1920: for (i = 0; i < m; i++) {
1921: x = l[i];
1922: v = vv + i;
1923: for (j = 0; j < n; j++) {
1924: (*v) *= x;
1925: v += mat->lda;
1926: }
1927: }
1928: PetscCall(VecRestoreArrayRead(ll, &l));
1929: PetscCall(PetscLogFlops(1.0 * n * m));
1930: }
1931: if (rr) {
1932: PetscCall(VecGetSize(rr, &n));
1933: PetscCall(VecGetArrayRead(rr, &r));
1934: PetscCheck(n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Right scaling vec wrong size");
1935: for (i = 0; i < n; i++) {
1936: x = r[i];
1937: v = vv + i * mat->lda;
1938: for (j = 0; j < m; j++) (*v++) *= x;
1939: }
1940: PetscCall(VecRestoreArrayRead(rr, &r));
1941: PetscCall(PetscLogFlops(1.0 * n * m));
1942: }
1943: PetscCall(MatDenseRestoreArray(A, &vv));
1944: PetscFunctionReturn(PETSC_SUCCESS);
1945: }
1947: PetscErrorCode MatNorm_SeqDense(Mat A, NormType type, PetscReal *nrm)
1948: {
1949: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
1950: PetscScalar *v, *vv;
1951: PetscReal sum = 0.0;
1952: PetscInt lda, m = A->rmap->n, i, j;
1954: PetscFunctionBegin;
1955: PetscCall(MatDenseGetArrayRead(A, (const PetscScalar **)&vv));
1956: PetscCall(MatDenseGetLDA(A, &lda));
1957: v = vv;
1958: if (type == NORM_FROBENIUS) {
1959: if (lda > m) {
1960: for (j = 0; j < A->cmap->n; j++) {
1961: v = vv + j * lda;
1962: for (i = 0; i < m; i++) {
1963: sum += PetscRealPart(PetscConj(*v) * (*v));
1964: v++;
1965: }
1966: }
1967: } else {
1968: #if defined(PETSC_USE_REAL___FP16)
1969: PetscBLASInt one = 1, cnt = A->cmap->n * A->rmap->n;
1970: PetscCallBLAS("BLASnrm2", *nrm = BLASnrm2_(&cnt, v, &one));
1971: }
1972: #else
1973: for (i = 0; i < A->cmap->n * A->rmap->n; i++) {
1974: sum += PetscRealPart(PetscConj(*v) * (*v));
1975: v++;
1976: }
1977: }
1978: *nrm = PetscSqrtReal(sum);
1979: #endif
1980: PetscCall(PetscLogFlops(2.0 * A->cmap->n * A->rmap->n));
1981: } else if (type == NORM_1) {
1982: *nrm = 0.0;
1983: for (j = 0; j < A->cmap->n; j++) {
1984: v = vv + j * mat->lda;
1985: sum = 0.0;
1986: for (i = 0; i < A->rmap->n; i++) {
1987: sum += PetscAbsScalar(*v);
1988: v++;
1989: }
1990: if (sum > *nrm) *nrm = sum;
1991: }
1992: PetscCall(PetscLogFlops(1.0 * A->cmap->n * A->rmap->n));
1993: } else if (type == NORM_INFINITY) {
1994: *nrm = 0.0;
1995: for (j = 0; j < A->rmap->n; j++) {
1996: v = vv + j;
1997: sum = 0.0;
1998: for (i = 0; i < A->cmap->n; i++) {
1999: sum += PetscAbsScalar(*v);
2000: v += mat->lda;
2001: }
2002: if (sum > *nrm) *nrm = sum;
2003: }
2004: PetscCall(PetscLogFlops(1.0 * A->cmap->n * A->rmap->n));
2005: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No two norm");
2006: PetscCall(MatDenseRestoreArrayRead(A, (const PetscScalar **)&vv));
2007: PetscFunctionReturn(PETSC_SUCCESS);
2008: }
2010: static PetscErrorCode MatSetOption_SeqDense(Mat A, MatOption op, PetscBool flg)
2011: {
2012: Mat_SeqDense *aij = (Mat_SeqDense *)A->data;
2014: PetscFunctionBegin;
2015: switch (op) {
2016: case MAT_ROW_ORIENTED:
2017: aij->roworiented = flg;
2018: break;
2019: case MAT_NEW_NONZERO_LOCATIONS:
2020: case MAT_NEW_NONZERO_LOCATION_ERR:
2021: case MAT_NEW_NONZERO_ALLOCATION_ERR:
2022: case MAT_FORCE_DIAGONAL_ENTRIES:
2023: case MAT_KEEP_NONZERO_PATTERN:
2024: case MAT_IGNORE_OFF_PROC_ENTRIES:
2025: case MAT_USE_HASH_TABLE:
2026: case MAT_IGNORE_ZERO_ENTRIES:
2027: case MAT_IGNORE_LOWER_TRIANGULAR:
2028: case MAT_SORTED_FULL:
2029: PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op]));
2030: break;
2031: case MAT_SPD:
2032: case MAT_SYMMETRIC:
2033: case MAT_STRUCTURALLY_SYMMETRIC:
2034: case MAT_HERMITIAN:
2035: case MAT_SYMMETRY_ETERNAL:
2036: case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
2037: case MAT_SPD_ETERNAL:
2038: break;
2039: default:
2040: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %s", MatOptions[op]);
2041: }
2042: PetscFunctionReturn(PETSC_SUCCESS);
2043: }
2045: PetscErrorCode MatZeroEntries_SeqDense(Mat A)
2046: {
2047: Mat_SeqDense *l = (Mat_SeqDense *)A->data;
2048: PetscInt lda = l->lda, m = A->rmap->n, n = A->cmap->n, j;
2049: PetscScalar *v;
2051: PetscFunctionBegin;
2052: PetscCall(MatDenseGetArrayWrite(A, &v));
2053: if (lda > m) {
2054: for (j = 0; j < n; j++) PetscCall(PetscArrayzero(v + j * lda, m));
2055: } else {
2056: PetscCall(PetscArrayzero(v, PetscInt64Mult(m, n)));
2057: }
2058: PetscCall(MatDenseRestoreArrayWrite(A, &v));
2059: PetscFunctionReturn(PETSC_SUCCESS);
2060: }
2062: static PetscErrorCode MatZeroRows_SeqDense(Mat A, PetscInt N, const PetscInt rows[], PetscScalar diag, Vec x, Vec b)
2063: {
2064: Mat_SeqDense *l = (Mat_SeqDense *)A->data;
2065: PetscInt m = l->lda, n = A->cmap->n, i, j;
2066: PetscScalar *slot, *bb, *v;
2067: const PetscScalar *xx;
2069: PetscFunctionBegin;
2070: if (PetscDefined(USE_DEBUG)) {
2071: for (i = 0; i < N; i++) {
2072: PetscCheck(rows[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row requested to be zeroed");
2073: PetscCheck(rows[i] < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " requested to be zeroed greater than or equal number of rows %" PetscInt_FMT, rows[i], A->rmap->n);
2074: }
2075: }
2076: if (!N) PetscFunctionReturn(PETSC_SUCCESS);
2078: /* fix right-hand side if needed */
2079: if (x && b) {
2080: PetscCall(VecGetArrayRead(x, &xx));
2081: PetscCall(VecGetArray(b, &bb));
2082: for (i = 0; i < N; i++) bb[rows[i]] = diag * xx[rows[i]];
2083: PetscCall(VecRestoreArrayRead(x, &xx));
2084: PetscCall(VecRestoreArray(b, &bb));
2085: }
2087: PetscCall(MatDenseGetArray(A, &v));
2088: for (i = 0; i < N; i++) {
2089: slot = v + rows[i];
2090: for (j = 0; j < n; j++) {
2091: *slot = 0.0;
2092: slot += m;
2093: }
2094: }
2095: if (diag != 0.0) {
2096: PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only coded for square matrices");
2097: for (i = 0; i < N; i++) {
2098: slot = v + (m + 1) * rows[i];
2099: *slot = diag;
2100: }
2101: }
2102: PetscCall(MatDenseRestoreArray(A, &v));
2103: PetscFunctionReturn(PETSC_SUCCESS);
2104: }
2106: static PetscErrorCode MatDenseGetLDA_SeqDense(Mat A, PetscInt *lda)
2107: {
2108: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2110: PetscFunctionBegin;
2111: *lda = mat->lda;
2112: PetscFunctionReturn(PETSC_SUCCESS);
2113: }
2115: PetscErrorCode MatDenseGetArray_SeqDense(Mat A, PetscScalar **array)
2116: {
2117: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2119: PetscFunctionBegin;
2120: PetscCheck(!mat->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
2121: *array = mat->v;
2122: PetscFunctionReturn(PETSC_SUCCESS);
2123: }
2125: PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A, PetscScalar **array)
2126: {
2127: PetscFunctionBegin;
2128: if (array) *array = NULL;
2129: PetscFunctionReturn(PETSC_SUCCESS);
2130: }
2132: /*@
2133: MatDenseGetLDA - gets the leading dimension of the array returned from `MatDenseGetArray()`
2135: Not Collective
2137: Input Parameter:
2138: . A - a `MATDENSE` or `MATDENSECUDA` matrix
2140: Output Parameter:
2141: . lda - the leading dimension
2143: Level: intermediate
2145: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseSetLDA()`
2146: @*/
2147: PetscErrorCode MatDenseGetLDA(Mat A, PetscInt *lda)
2148: {
2149: PetscFunctionBegin;
2151: PetscAssertPointer(lda, 2);
2152: MatCheckPreallocated(A, 1);
2153: PetscUseMethod(A, "MatDenseGetLDA_C", (Mat, PetscInt *), (A, lda));
2154: PetscFunctionReturn(PETSC_SUCCESS);
2155: }
2157: /*@
2158: MatDenseSetLDA - Sets the leading dimension of the array used by the `MATDENSE` matrix
2160: Collective if the matrix layouts have not yet been setup
2162: Input Parameters:
2163: + A - a `MATDENSE` or `MATDENSECUDA` matrix
2164: - lda - the leading dimension
2166: Level: intermediate
2168: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetLDA()`
2169: @*/
2170: PetscErrorCode MatDenseSetLDA(Mat A, PetscInt lda)
2171: {
2172: PetscFunctionBegin;
2174: PetscTryMethod(A, "MatDenseSetLDA_C", (Mat, PetscInt), (A, lda));
2175: PetscFunctionReturn(PETSC_SUCCESS);
2176: }
2178: /*@C
2179: MatDenseGetArray - gives read-write access to the array where the data for a `MATDENSE` matrix is stored
2181: Logically Collective
2183: Input Parameter:
2184: . A - a dense matrix
2186: Output Parameter:
2187: . array - pointer to the data
2189: Level: intermediate
2191: Fortran Notes:
2192: `MatDenseGetArray()` Fortran binding is deprecated (since PETSc 3.19), use `MatDenseGetArrayF90()`
2194: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2195: @*/
2196: PetscErrorCode MatDenseGetArray(Mat A, PetscScalar *array[])
2197: {
2198: PetscFunctionBegin;
2200: PetscAssertPointer(array, 2);
2201: PetscUseMethod(A, "MatDenseGetArray_C", (Mat, PetscScalar **), (A, array));
2202: PetscFunctionReturn(PETSC_SUCCESS);
2203: }
2205: /*@C
2206: MatDenseRestoreArray - returns access to the array where the data for a `MATDENSE` matrix is stored obtained by `MatDenseGetArray()`
2208: Logically Collective
2210: Input Parameters:
2211: + A - a dense matrix
2212: - array - pointer to the data (may be `NULL`)
2214: Level: intermediate
2216: Fortran Notes:
2217: `MatDenseRestoreArray()` Fortran binding is deprecated (since PETSc 3.19), use `MatDenseRestoreArrayF90()`
2219: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2220: @*/
2221: PetscErrorCode MatDenseRestoreArray(Mat A, PetscScalar *array[])
2222: {
2223: PetscFunctionBegin;
2225: if (array) PetscAssertPointer(array, 2);
2226: PetscUseMethod(A, "MatDenseRestoreArray_C", (Mat, PetscScalar **), (A, array));
2227: PetscCall(PetscObjectStateIncrease((PetscObject)A));
2228: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
2229: A->offloadmask = PETSC_OFFLOAD_CPU;
2230: #endif
2231: PetscFunctionReturn(PETSC_SUCCESS);
2232: }
2234: /*@C
2235: MatDenseGetArrayRead - gives read-only access to the array where the data for a `MATDENSE` matrix is stored
2237: Not Collective
2239: Input Parameter:
2240: . A - a dense matrix
2242: Output Parameter:
2243: . array - pointer to the data
2245: Level: intermediate
2247: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArrayRead()`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2248: @*/
2249: PetscErrorCode MatDenseGetArrayRead(Mat A, const PetscScalar *array[])
2250: {
2251: PetscFunctionBegin;
2253: PetscAssertPointer(array, 2);
2254: PetscUseMethod(A, "MatDenseGetArrayRead_C", (Mat, PetscScalar **), (A, (PetscScalar **)array));
2255: PetscFunctionReturn(PETSC_SUCCESS);
2256: }
2258: /*@C
2259: MatDenseRestoreArrayRead - returns access to the array where the data for a `MATDENSE` matrix is stored obtained by `MatDenseGetArrayRead()`
2261: Not Collective
2263: Input Parameters:
2264: + A - a dense matrix
2265: - array - pointer to the data (may be `NULL`)
2267: Level: intermediate
2269: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArrayRead()`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2270: @*/
2271: PetscErrorCode MatDenseRestoreArrayRead(Mat A, const PetscScalar *array[])
2272: {
2273: PetscFunctionBegin;
2275: if (array) PetscAssertPointer(array, 2);
2276: PetscUseMethod(A, "MatDenseRestoreArrayRead_C", (Mat, PetscScalar **), (A, (PetscScalar **)array));
2277: PetscFunctionReturn(PETSC_SUCCESS);
2278: }
2280: /*@C
2281: MatDenseGetArrayWrite - gives write-only access to the array where the data for a `MATDENSE` matrix is stored
2283: Not Collective
2285: Input Parameter:
2286: . A - a dense matrix
2288: Output Parameter:
2289: . array - pointer to the data
2291: Level: intermediate
2293: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArrayWrite()`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`
2294: @*/
2295: PetscErrorCode MatDenseGetArrayWrite(Mat A, PetscScalar *array[])
2296: {
2297: PetscFunctionBegin;
2299: PetscAssertPointer(array, 2);
2300: PetscUseMethod(A, "MatDenseGetArrayWrite_C", (Mat, PetscScalar **), (A, array));
2301: PetscFunctionReturn(PETSC_SUCCESS);
2302: }
2304: /*@C
2305: MatDenseRestoreArrayWrite - returns access to the array where the data for a `MATDENSE` matrix is stored obtained by `MatDenseGetArrayWrite()`
2307: Not Collective
2309: Input Parameters:
2310: + A - a dense matrix
2311: - array - pointer to the data (may be `NULL`)
2313: Level: intermediate
2315: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArrayWrite()`, `MatDenseGetArray()`, `MatDenseRestoreArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`
2316: @*/
2317: PetscErrorCode MatDenseRestoreArrayWrite(Mat A, PetscScalar *array[])
2318: {
2319: PetscFunctionBegin;
2321: if (array) PetscAssertPointer(array, 2);
2322: PetscUseMethod(A, "MatDenseRestoreArrayWrite_C", (Mat, PetscScalar **), (A, array));
2323: PetscCall(PetscObjectStateIncrease((PetscObject)A));
2324: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
2325: A->offloadmask = PETSC_OFFLOAD_CPU;
2326: #endif
2327: PetscFunctionReturn(PETSC_SUCCESS);
2328: }
2330: /*@C
2331: MatDenseGetArrayAndMemType - gives read-write access to the array where the data for a `MATDENSE` matrix is stored
2333: Logically Collective
2335: Input Parameter:
2336: . A - a dense matrix
2338: Output Parameters:
2339: + array - pointer to the data
2340: - mtype - memory type of the returned pointer
2342: Level: intermediate
2344: Note:
2345: If the matrix is of a device type such as `MATDENSECUDA`, `MATDENSEHIP`, etc.,
2346: an array on device is always returned and is guaranteed to contain the matrix's latest data.
2348: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArrayAndMemType()`, `MatDenseGetArrayReadAndMemType()`, `MatDenseGetArrayWriteAndMemType()`, `MatDenseGetArrayRead()`,
2349: `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`, `MatSeqAIJGetCSRAndMemType()`
2350: @*/
2351: PetscErrorCode MatDenseGetArrayAndMemType(Mat A, PetscScalar *array[], PetscMemType *mtype)
2352: {
2353: PetscBool isMPI;
2355: PetscFunctionBegin;
2357: PetscAssertPointer(array, 2);
2358: PetscCall(MatBindToCPU(A, PETSC_FALSE)); /* We want device matrices to always return device arrays, so we unbind the matrix if it is bound to CPU */
2359: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2360: if (isMPI) {
2361: /* Dispatch here so that the code can be reused for all subclasses of MATDENSE */
2362: PetscCall(MatDenseGetArrayAndMemType(((Mat_MPIDense *)A->data)->A, array, mtype));
2363: } else {
2364: PetscErrorCode (*fptr)(Mat, PetscScalar **, PetscMemType *);
2366: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseGetArrayAndMemType_C", &fptr));
2367: if (fptr) {
2368: PetscCall((*fptr)(A, array, mtype));
2369: } else {
2370: PetscUseMethod(A, "MatDenseGetArray_C", (Mat, PetscScalar **), (A, array));
2371: if (mtype) *mtype = PETSC_MEMTYPE_HOST;
2372: }
2373: }
2374: PetscFunctionReturn(PETSC_SUCCESS);
2375: }
2377: /*@C
2378: MatDenseRestoreArrayAndMemType - returns access to the array that is obtained by `MatDenseGetArrayAndMemType()`
2380: Logically Collective
2382: Input Parameters:
2383: + A - a dense matrix
2384: - array - pointer to the data
2386: Level: intermediate
2388: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArrayAndMemType()`, `MatDenseGetArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2389: @*/
2390: PetscErrorCode MatDenseRestoreArrayAndMemType(Mat A, PetscScalar *array[])
2391: {
2392: PetscBool isMPI;
2394: PetscFunctionBegin;
2396: PetscAssertPointer(array, 2);
2397: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2398: if (isMPI) {
2399: PetscCall(MatDenseRestoreArrayAndMemType(((Mat_MPIDense *)A->data)->A, array));
2400: } else {
2401: PetscErrorCode (*fptr)(Mat, PetscScalar **);
2403: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseRestoreArrayAndMemType_C", &fptr));
2404: if (fptr) {
2405: PetscCall((*fptr)(A, array));
2406: } else {
2407: PetscUseMethod(A, "MatDenseRestoreArray_C", (Mat, PetscScalar **), (A, array));
2408: }
2409: *array = NULL;
2410: }
2411: PetscCall(PetscObjectStateIncrease((PetscObject)A));
2412: PetscFunctionReturn(PETSC_SUCCESS);
2413: }
2415: /*@C
2416: MatDenseGetArrayReadAndMemType - gives read-only access to the array where the data for a `MATDENSE` matrix is stored
2418: Logically Collective
2420: Input Parameter:
2421: . A - a dense matrix
2423: Output Parameters:
2424: + array - pointer to the data
2425: - mtype - memory type of the returned pointer
2427: Level: intermediate
2429: Note:
2430: If the matrix is of a device type such as `MATDENSECUDA`, `MATDENSEHIP`, etc.,
2431: an array on device is always returned and is guaranteed to contain the matrix's latest data.
2433: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArrayReadAndMemType()`, `MatDenseGetArrayWriteAndMemType()`,
2434: `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`, `MatSeqAIJGetCSRAndMemType()`
2435: @*/
2436: PetscErrorCode MatDenseGetArrayReadAndMemType(Mat A, const PetscScalar *array[], PetscMemType *mtype)
2437: {
2438: PetscBool isMPI;
2440: PetscFunctionBegin;
2442: PetscAssertPointer(array, 2);
2443: PetscCall(MatBindToCPU(A, PETSC_FALSE)); /* We want device matrices to always return device arrays, so we unbind the matrix if it is bound to CPU */
2444: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2445: if (isMPI) { /* Dispatch here so that the code can be reused for all subclasses of MATDENSE */
2446: PetscCall(MatDenseGetArrayReadAndMemType(((Mat_MPIDense *)A->data)->A, array, mtype));
2447: } else {
2448: PetscErrorCode (*fptr)(Mat, const PetscScalar **, PetscMemType *);
2450: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseGetArrayReadAndMemType_C", &fptr));
2451: if (fptr) {
2452: PetscCall((*fptr)(A, array, mtype));
2453: } else {
2454: PetscUseMethod(A, "MatDenseGetArrayRead_C", (Mat, PetscScalar **), (A, (PetscScalar **)array));
2455: if (mtype) *mtype = PETSC_MEMTYPE_HOST;
2456: }
2457: }
2458: PetscFunctionReturn(PETSC_SUCCESS);
2459: }
2461: /*@C
2462: MatDenseRestoreArrayReadAndMemType - returns access to the array that is obtained by `MatDenseGetArrayReadAndMemType()`
2464: Logically Collective
2466: Input Parameters:
2467: + A - a dense matrix
2468: - array - pointer to the data
2470: Level: intermediate
2472: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArrayReadAndMemType()`, `MatDenseGetArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2473: @*/
2474: PetscErrorCode MatDenseRestoreArrayReadAndMemType(Mat A, const PetscScalar *array[])
2475: {
2476: PetscBool isMPI;
2478: PetscFunctionBegin;
2480: PetscAssertPointer(array, 2);
2481: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2482: if (isMPI) {
2483: PetscCall(MatDenseRestoreArrayReadAndMemType(((Mat_MPIDense *)A->data)->A, array));
2484: } else {
2485: PetscErrorCode (*fptr)(Mat, const PetscScalar **);
2487: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseRestoreArrayReadAndMemType_C", &fptr));
2488: if (fptr) {
2489: PetscCall((*fptr)(A, array));
2490: } else {
2491: PetscUseMethod(A, "MatDenseRestoreArrayRead_C", (Mat, PetscScalar **), (A, (PetscScalar **)array));
2492: }
2493: *array = NULL;
2494: }
2495: PetscFunctionReturn(PETSC_SUCCESS);
2496: }
2498: /*@C
2499: MatDenseGetArrayWriteAndMemType - gives write-only access to the array where the data for a `MATDENSE` matrix is stored
2501: Logically Collective
2503: Input Parameter:
2504: . A - a dense matrix
2506: Output Parameters:
2507: + array - pointer to the data
2508: - mtype - memory type of the returned pointer
2510: Level: intermediate
2512: Note:
2513: If the matrix is of a device type such as `MATDENSECUDA`, `MATDENSEHIP`, etc.,
2514: an array on device is always returned and is guaranteed to contain the matrix's latest data.
2516: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreArrayWriteAndMemType()`, `MatDenseGetArrayReadAndMemType()`, `MatDenseGetArrayRead()`,
2517: `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`, `MatSeqAIJGetCSRAndMemType()`
2518: @*/
2519: PetscErrorCode MatDenseGetArrayWriteAndMemType(Mat A, PetscScalar *array[], PetscMemType *mtype)
2520: {
2521: PetscBool isMPI;
2523: PetscFunctionBegin;
2525: PetscAssertPointer(array, 2);
2526: PetscCall(MatBindToCPU(A, PETSC_FALSE)); /* We want device matrices to always return device arrays, so we unbind the matrix if it is bound to CPU */
2527: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2528: if (isMPI) {
2529: PetscCall(MatDenseGetArrayWriteAndMemType(((Mat_MPIDense *)A->data)->A, array, mtype));
2530: } else {
2531: PetscErrorCode (*fptr)(Mat, PetscScalar **, PetscMemType *);
2533: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseGetArrayWriteAndMemType_C", &fptr));
2534: if (fptr) {
2535: PetscCall((*fptr)(A, array, mtype));
2536: } else {
2537: PetscUseMethod(A, "MatDenseGetArrayWrite_C", (Mat, PetscScalar **), (A, array));
2538: if (mtype) *mtype = PETSC_MEMTYPE_HOST;
2539: }
2540: }
2541: PetscFunctionReturn(PETSC_SUCCESS);
2542: }
2544: /*@C
2545: MatDenseRestoreArrayWriteAndMemType - returns access to the array that is obtained by `MatDenseGetArrayReadAndMemType()`
2547: Logically Collective
2549: Input Parameters:
2550: + A - a dense matrix
2551: - array - pointer to the data
2553: Level: intermediate
2555: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetArrayWriteAndMemType()`, `MatDenseGetArray()`, `MatDenseGetArrayRead()`, `MatDenseRestoreArrayRead()`, `MatDenseGetArrayWrite()`, `MatDenseRestoreArrayWrite()`
2556: @*/
2557: PetscErrorCode MatDenseRestoreArrayWriteAndMemType(Mat A, PetscScalar *array[])
2558: {
2559: PetscBool isMPI;
2561: PetscFunctionBegin;
2563: PetscAssertPointer(array, 2);
2564: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATMPIDENSE, &isMPI));
2565: if (isMPI) {
2566: PetscCall(MatDenseRestoreArrayWriteAndMemType(((Mat_MPIDense *)A->data)->A, array));
2567: } else {
2568: PetscErrorCode (*fptr)(Mat, PetscScalar **);
2570: PetscCall(PetscObjectQueryFunction((PetscObject)A, "MatDenseRestoreArrayWriteAndMemType_C", &fptr));
2571: if (fptr) {
2572: PetscCall((*fptr)(A, array));
2573: } else {
2574: PetscUseMethod(A, "MatDenseRestoreArrayWrite_C", (Mat, PetscScalar **), (A, array));
2575: }
2576: *array = NULL;
2577: }
2578: PetscCall(PetscObjectStateIncrease((PetscObject)A));
2579: PetscFunctionReturn(PETSC_SUCCESS);
2580: }
2582: static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A, IS isrow, IS iscol, MatReuse scall, Mat *B)
2583: {
2584: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2585: PetscInt i, j, nrows, ncols, ldb;
2586: const PetscInt *irow, *icol;
2587: PetscScalar *av, *bv, *v = mat->v;
2588: Mat newmat;
2590: PetscFunctionBegin;
2591: PetscCall(ISGetIndices(isrow, &irow));
2592: PetscCall(ISGetIndices(iscol, &icol));
2593: PetscCall(ISGetLocalSize(isrow, &nrows));
2594: PetscCall(ISGetLocalSize(iscol, &ncols));
2596: /* Check submatrixcall */
2597: if (scall == MAT_REUSE_MATRIX) {
2598: PetscInt n_cols, n_rows;
2599: PetscCall(MatGetSize(*B, &n_rows, &n_cols));
2600: if (n_rows != nrows || n_cols != ncols) {
2601: /* resize the result matrix to match number of requested rows/columns */
2602: PetscCall(MatSetSizes(*B, nrows, ncols, nrows, ncols));
2603: }
2604: newmat = *B;
2605: } else {
2606: /* Create and fill new matrix */
2607: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &newmat));
2608: PetscCall(MatSetSizes(newmat, nrows, ncols, nrows, ncols));
2609: PetscCall(MatSetType(newmat, ((PetscObject)A)->type_name));
2610: PetscCall(MatSeqDenseSetPreallocation(newmat, NULL));
2611: }
2613: /* Now extract the data pointers and do the copy,column at a time */
2614: PetscCall(MatDenseGetArray(newmat, &bv));
2615: PetscCall(MatDenseGetLDA(newmat, &ldb));
2616: for (i = 0; i < ncols; i++) {
2617: av = v + mat->lda * icol[i];
2618: for (j = 0; j < nrows; j++) bv[j] = av[irow[j]];
2619: bv += ldb;
2620: }
2621: PetscCall(MatDenseRestoreArray(newmat, &bv));
2623: /* Assemble the matrices so that the correct flags are set */
2624: PetscCall(MatAssemblyBegin(newmat, MAT_FINAL_ASSEMBLY));
2625: PetscCall(MatAssemblyEnd(newmat, MAT_FINAL_ASSEMBLY));
2627: /* Free work space */
2628: PetscCall(ISRestoreIndices(isrow, &irow));
2629: PetscCall(ISRestoreIndices(iscol, &icol));
2630: *B = newmat;
2631: PetscFunctionReturn(PETSC_SUCCESS);
2632: }
2634: static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A, PetscInt n, const IS irow[], const IS icol[], MatReuse scall, Mat *B[])
2635: {
2636: PetscInt i;
2638: PetscFunctionBegin;
2639: if (scall == MAT_INITIAL_MATRIX) PetscCall(PetscCalloc1(n, B));
2641: for (i = 0; i < n; i++) PetscCall(MatCreateSubMatrix_SeqDense(A, irow[i], icol[i], scall, &(*B)[i]));
2642: PetscFunctionReturn(PETSC_SUCCESS);
2643: }
2645: static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat, MatAssemblyType mode)
2646: {
2647: PetscFunctionBegin;
2648: PetscFunctionReturn(PETSC_SUCCESS);
2649: }
2651: static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat, MatAssemblyType mode)
2652: {
2653: PetscFunctionBegin;
2654: PetscFunctionReturn(PETSC_SUCCESS);
2655: }
2657: PetscErrorCode MatCopy_SeqDense(Mat A, Mat B, MatStructure str)
2658: {
2659: Mat_SeqDense *a = (Mat_SeqDense *)A->data, *b = (Mat_SeqDense *)B->data;
2660: const PetscScalar *va;
2661: PetscScalar *vb;
2662: PetscInt lda1 = a->lda, lda2 = b->lda, m = A->rmap->n, n = A->cmap->n, j;
2664: PetscFunctionBegin;
2665: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2666: if (A->ops->copy != B->ops->copy) {
2667: PetscCall(MatCopy_Basic(A, B, str));
2668: PetscFunctionReturn(PETSC_SUCCESS);
2669: }
2670: PetscCheck(m == B->rmap->n && n == B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "size(B) != size(A)");
2671: PetscCall(MatDenseGetArrayRead(A, &va));
2672: PetscCall(MatDenseGetArray(B, &vb));
2673: if (lda1 > m || lda2 > m) {
2674: for (j = 0; j < n; j++) PetscCall(PetscArraycpy(vb + j * lda2, va + j * lda1, m));
2675: } else {
2676: PetscCall(PetscArraycpy(vb, va, A->rmap->n * A->cmap->n));
2677: }
2678: PetscCall(MatDenseRestoreArray(B, &vb));
2679: PetscCall(MatDenseRestoreArrayRead(A, &va));
2680: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
2681: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
2682: PetscFunctionReturn(PETSC_SUCCESS);
2683: }
2685: PetscErrorCode MatSetUp_SeqDense(Mat A)
2686: {
2687: PetscFunctionBegin;
2688: PetscCall(PetscLayoutSetUp(A->rmap));
2689: PetscCall(PetscLayoutSetUp(A->cmap));
2690: if (!A->preallocated) PetscCall(MatSeqDenseSetPreallocation(A, NULL));
2691: PetscFunctionReturn(PETSC_SUCCESS);
2692: }
2694: static PetscErrorCode MatConjugate_SeqDense(Mat A)
2695: {
2696: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2697: PetscInt i, j;
2698: PetscInt min = PetscMin(A->rmap->n, A->cmap->n);
2699: PetscScalar *aa;
2701: PetscFunctionBegin;
2702: PetscCall(MatDenseGetArray(A, &aa));
2703: for (j = 0; j < A->cmap->n; j++) {
2704: for (i = 0; i < A->rmap->n; i++) aa[i + j * mat->lda] = PetscConj(aa[i + j * mat->lda]);
2705: }
2706: PetscCall(MatDenseRestoreArray(A, &aa));
2707: if (mat->tau)
2708: for (i = 0; i < min; i++) mat->tau[i] = PetscConj(mat->tau[i]);
2709: PetscFunctionReturn(PETSC_SUCCESS);
2710: }
2712: static PetscErrorCode MatRealPart_SeqDense(Mat A)
2713: {
2714: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2715: PetscInt i, j;
2716: PetscScalar *aa;
2718: PetscFunctionBegin;
2719: PetscCall(MatDenseGetArray(A, &aa));
2720: for (j = 0; j < A->cmap->n; j++) {
2721: for (i = 0; i < A->rmap->n; i++) aa[i + j * mat->lda] = PetscRealPart(aa[i + j * mat->lda]);
2722: }
2723: PetscCall(MatDenseRestoreArray(A, &aa));
2724: PetscFunctionReturn(PETSC_SUCCESS);
2725: }
2727: static PetscErrorCode MatImaginaryPart_SeqDense(Mat A)
2728: {
2729: Mat_SeqDense *mat = (Mat_SeqDense *)A->data;
2730: PetscInt i, j;
2731: PetscScalar *aa;
2733: PetscFunctionBegin;
2734: PetscCall(MatDenseGetArray(A, &aa));
2735: for (j = 0; j < A->cmap->n; j++) {
2736: for (i = 0; i < A->rmap->n; i++) aa[i + j * mat->lda] = PetscImaginaryPart(aa[i + j * mat->lda]);
2737: }
2738: PetscCall(MatDenseRestoreArray(A, &aa));
2739: PetscFunctionReturn(PETSC_SUCCESS);
2740: }
2742: PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A, Mat B, PetscReal fill, Mat C)
2743: {
2744: PetscInt m = A->rmap->n, n = B->cmap->n;
2745: PetscBool cisdense = PETSC_FALSE;
2747: PetscFunctionBegin;
2748: PetscCall(MatSetSizes(C, m, n, m, n));
2749: #if defined(PETSC_HAVE_CUDA)
2750: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSECUDA, ""));
2751: #endif
2752: #if defined(PETSC_HAVE_HIP)
2753: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSEHIP, ""));
2754: #endif
2755: if (!cisdense) {
2756: PetscBool flg;
2758: PetscCall(PetscObjectTypeCompare((PetscObject)B, ((PetscObject)A)->type_name, &flg));
2759: PetscCall(MatSetType(C, flg ? ((PetscObject)A)->type_name : MATDENSE));
2760: }
2761: PetscCall(MatSetUp(C));
2762: PetscFunctionReturn(PETSC_SUCCESS);
2763: }
2765: PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A, Mat B, Mat C)
2766: {
2767: Mat_SeqDense *a = (Mat_SeqDense *)A->data, *b = (Mat_SeqDense *)B->data, *c = (Mat_SeqDense *)C->data;
2768: PetscBLASInt m, n, k;
2769: const PetscScalar *av, *bv;
2770: PetscScalar *cv;
2771: PetscScalar _DOne = 1.0, _DZero = 0.0;
2773: PetscFunctionBegin;
2774: PetscCall(PetscBLASIntCast(C->rmap->n, &m));
2775: PetscCall(PetscBLASIntCast(C->cmap->n, &n));
2776: PetscCall(PetscBLASIntCast(A->cmap->n, &k));
2777: if (!m || !n || !k) PetscFunctionReturn(PETSC_SUCCESS);
2778: PetscCall(MatDenseGetArrayRead(A, &av));
2779: PetscCall(MatDenseGetArrayRead(B, &bv));
2780: PetscCall(MatDenseGetArrayWrite(C, &cv));
2781: PetscCallBLAS("BLASgemm", BLASgemm_("N", "N", &m, &n, &k, &_DOne, av, &a->lda, bv, &b->lda, &_DZero, cv, &c->lda));
2782: PetscCall(PetscLogFlops(1.0 * m * n * k + 1.0 * m * n * (k - 1)));
2783: PetscCall(MatDenseRestoreArrayRead(A, &av));
2784: PetscCall(MatDenseRestoreArrayRead(B, &bv));
2785: PetscCall(MatDenseRestoreArrayWrite(C, &cv));
2786: PetscFunctionReturn(PETSC_SUCCESS);
2787: }
2789: PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A, Mat B, PetscReal fill, Mat C)
2790: {
2791: PetscInt m = A->rmap->n, n = B->rmap->n;
2792: PetscBool cisdense = PETSC_FALSE;
2794: PetscFunctionBegin;
2795: PetscCall(MatSetSizes(C, m, n, m, n));
2796: #if defined(PETSC_HAVE_CUDA)
2797: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSECUDA, ""));
2798: #endif
2799: #if defined(PETSC_HAVE_HIP)
2800: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSEHIP, ""));
2801: #endif
2802: if (!cisdense) {
2803: PetscBool flg;
2805: PetscCall(PetscObjectTypeCompare((PetscObject)B, ((PetscObject)A)->type_name, &flg));
2806: PetscCall(MatSetType(C, flg ? ((PetscObject)A)->type_name : MATDENSE));
2807: }
2808: PetscCall(MatSetUp(C));
2809: PetscFunctionReturn(PETSC_SUCCESS);
2810: }
2812: PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A, Mat B, Mat C)
2813: {
2814: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
2815: Mat_SeqDense *b = (Mat_SeqDense *)B->data;
2816: Mat_SeqDense *c = (Mat_SeqDense *)C->data;
2817: const PetscScalar *av, *bv;
2818: PetscScalar *cv;
2819: PetscBLASInt m, n, k;
2820: PetscScalar _DOne = 1.0, _DZero = 0.0;
2822: PetscFunctionBegin;
2823: PetscCall(PetscBLASIntCast(C->rmap->n, &m));
2824: PetscCall(PetscBLASIntCast(C->cmap->n, &n));
2825: PetscCall(PetscBLASIntCast(A->cmap->n, &k));
2826: if (!m || !n || !k) PetscFunctionReturn(PETSC_SUCCESS);
2827: PetscCall(MatDenseGetArrayRead(A, &av));
2828: PetscCall(MatDenseGetArrayRead(B, &bv));
2829: PetscCall(MatDenseGetArrayWrite(C, &cv));
2830: PetscCallBLAS("BLASgemm", BLASgemm_("N", "T", &m, &n, &k, &_DOne, av, &a->lda, bv, &b->lda, &_DZero, cv, &c->lda));
2831: PetscCall(MatDenseRestoreArrayRead(A, &av));
2832: PetscCall(MatDenseRestoreArrayRead(B, &bv));
2833: PetscCall(MatDenseRestoreArrayWrite(C, &cv));
2834: PetscCall(PetscLogFlops(1.0 * m * n * k + 1.0 * m * n * (k - 1)));
2835: PetscFunctionReturn(PETSC_SUCCESS);
2836: }
2838: PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A, Mat B, PetscReal fill, Mat C)
2839: {
2840: PetscInt m = A->cmap->n, n = B->cmap->n;
2841: PetscBool cisdense = PETSC_FALSE;
2843: PetscFunctionBegin;
2844: PetscCall(MatSetSizes(C, m, n, m, n));
2845: #if defined(PETSC_HAVE_CUDA)
2846: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSECUDA, ""));
2847: #endif
2848: #if defined(PETSC_HAVE_HIP)
2849: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATSEQDENSEHIP, ""));
2850: #endif
2851: if (!cisdense) {
2852: PetscBool flg;
2854: PetscCall(PetscObjectTypeCompare((PetscObject)B, ((PetscObject)A)->type_name, &flg));
2855: PetscCall(MatSetType(C, flg ? ((PetscObject)A)->type_name : MATDENSE));
2856: }
2857: PetscCall(MatSetUp(C));
2858: PetscFunctionReturn(PETSC_SUCCESS);
2859: }
2861: PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A, Mat B, Mat C)
2862: {
2863: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
2864: Mat_SeqDense *b = (Mat_SeqDense *)B->data;
2865: Mat_SeqDense *c = (Mat_SeqDense *)C->data;
2866: const PetscScalar *av, *bv;
2867: PetscScalar *cv;
2868: PetscBLASInt m, n, k;
2869: PetscScalar _DOne = 1.0, _DZero = 0.0;
2871: PetscFunctionBegin;
2872: PetscCall(PetscBLASIntCast(C->rmap->n, &m));
2873: PetscCall(PetscBLASIntCast(C->cmap->n, &n));
2874: PetscCall(PetscBLASIntCast(A->rmap->n, &k));
2875: if (!m || !n || !k) PetscFunctionReturn(PETSC_SUCCESS);
2876: PetscCall(MatDenseGetArrayRead(A, &av));
2877: PetscCall(MatDenseGetArrayRead(B, &bv));
2878: PetscCall(MatDenseGetArrayWrite(C, &cv));
2879: PetscCallBLAS("BLASgemm", BLASgemm_("T", "N", &m, &n, &k, &_DOne, av, &a->lda, bv, &b->lda, &_DZero, cv, &c->lda));
2880: PetscCall(MatDenseRestoreArrayRead(A, &av));
2881: PetscCall(MatDenseRestoreArrayRead(B, &bv));
2882: PetscCall(MatDenseRestoreArrayWrite(C, &cv));
2883: PetscCall(PetscLogFlops(1.0 * m * n * k + 1.0 * m * n * (k - 1)));
2884: PetscFunctionReturn(PETSC_SUCCESS);
2885: }
2887: static PetscErrorCode MatProductSetFromOptions_SeqDense_AB(Mat C)
2888: {
2889: PetscFunctionBegin;
2890: C->ops->matmultsymbolic = MatMatMultSymbolic_SeqDense_SeqDense;
2891: C->ops->productsymbolic = MatProductSymbolic_AB;
2892: PetscFunctionReturn(PETSC_SUCCESS);
2893: }
2895: static PetscErrorCode MatProductSetFromOptions_SeqDense_AtB(Mat C)
2896: {
2897: PetscFunctionBegin;
2898: C->ops->transposematmultsymbolic = MatTransposeMatMultSymbolic_SeqDense_SeqDense;
2899: C->ops->productsymbolic = MatProductSymbolic_AtB;
2900: PetscFunctionReturn(PETSC_SUCCESS);
2901: }
2903: static PetscErrorCode MatProductSetFromOptions_SeqDense_ABt(Mat C)
2904: {
2905: PetscFunctionBegin;
2906: C->ops->mattransposemultsymbolic = MatMatTransposeMultSymbolic_SeqDense_SeqDense;
2907: C->ops->productsymbolic = MatProductSymbolic_ABt;
2908: PetscFunctionReturn(PETSC_SUCCESS);
2909: }
2911: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqDense(Mat C)
2912: {
2913: Mat_Product *product = C->product;
2915: PetscFunctionBegin;
2916: switch (product->type) {
2917: case MATPRODUCT_AB:
2918: PetscCall(MatProductSetFromOptions_SeqDense_AB(C));
2919: break;
2920: case MATPRODUCT_AtB:
2921: PetscCall(MatProductSetFromOptions_SeqDense_AtB(C));
2922: break;
2923: case MATPRODUCT_ABt:
2924: PetscCall(MatProductSetFromOptions_SeqDense_ABt(C));
2925: break;
2926: default:
2927: break;
2928: }
2929: PetscFunctionReturn(PETSC_SUCCESS);
2930: }
2932: static PetscErrorCode MatGetRowMax_SeqDense(Mat A, Vec v, PetscInt idx[])
2933: {
2934: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
2935: PetscInt i, j, m = A->rmap->n, n = A->cmap->n, p;
2936: PetscScalar *x;
2937: const PetscScalar *aa;
2939: PetscFunctionBegin;
2940: PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
2941: PetscCall(VecGetArray(v, &x));
2942: PetscCall(VecGetLocalSize(v, &p));
2943: PetscCall(MatDenseGetArrayRead(A, &aa));
2944: PetscCheck(p == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector");
2945: for (i = 0; i < m; i++) {
2946: x[i] = aa[i];
2947: if (idx) idx[i] = 0;
2948: for (j = 1; j < n; j++) {
2949: if (PetscRealPart(x[i]) < PetscRealPart(aa[i + a->lda * j])) {
2950: x[i] = aa[i + a->lda * j];
2951: if (idx) idx[i] = j;
2952: }
2953: }
2954: }
2955: PetscCall(MatDenseRestoreArrayRead(A, &aa));
2956: PetscCall(VecRestoreArray(v, &x));
2957: PetscFunctionReturn(PETSC_SUCCESS);
2958: }
2960: static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A, Vec v, PetscInt idx[])
2961: {
2962: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
2963: PetscInt i, j, m = A->rmap->n, n = A->cmap->n, p;
2964: PetscScalar *x;
2965: PetscReal atmp;
2966: const PetscScalar *aa;
2968: PetscFunctionBegin;
2969: PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
2970: PetscCall(VecGetArray(v, &x));
2971: PetscCall(VecGetLocalSize(v, &p));
2972: PetscCall(MatDenseGetArrayRead(A, &aa));
2973: PetscCheck(p == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector");
2974: for (i = 0; i < m; i++) {
2975: x[i] = PetscAbsScalar(aa[i]);
2976: for (j = 1; j < n; j++) {
2977: atmp = PetscAbsScalar(aa[i + a->lda * j]);
2978: if (PetscAbsScalar(x[i]) < atmp) {
2979: x[i] = atmp;
2980: if (idx) idx[i] = j;
2981: }
2982: }
2983: }
2984: PetscCall(MatDenseRestoreArrayRead(A, &aa));
2985: PetscCall(VecRestoreArray(v, &x));
2986: PetscFunctionReturn(PETSC_SUCCESS);
2987: }
2989: static PetscErrorCode MatGetRowMin_SeqDense(Mat A, Vec v, PetscInt idx[])
2990: {
2991: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
2992: PetscInt i, j, m = A->rmap->n, n = A->cmap->n, p;
2993: PetscScalar *x;
2994: const PetscScalar *aa;
2996: PetscFunctionBegin;
2997: PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
2998: PetscCall(MatDenseGetArrayRead(A, &aa));
2999: PetscCall(VecGetArray(v, &x));
3000: PetscCall(VecGetLocalSize(v, &p));
3001: PetscCheck(p == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector");
3002: for (i = 0; i < m; i++) {
3003: x[i] = aa[i];
3004: if (idx) idx[i] = 0;
3005: for (j = 1; j < n; j++) {
3006: if (PetscRealPart(x[i]) > PetscRealPart(aa[i + a->lda * j])) {
3007: x[i] = aa[i + a->lda * j];
3008: if (idx) idx[i] = j;
3009: }
3010: }
3011: }
3012: PetscCall(VecRestoreArray(v, &x));
3013: PetscCall(MatDenseRestoreArrayRead(A, &aa));
3014: PetscFunctionReturn(PETSC_SUCCESS);
3015: }
3017: PetscErrorCode MatGetColumnVector_SeqDense(Mat A, Vec v, PetscInt col)
3018: {
3019: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3020: PetscScalar *x;
3021: const PetscScalar *aa;
3023: PetscFunctionBegin;
3024: PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
3025: PetscCall(MatDenseGetArrayRead(A, &aa));
3026: PetscCall(VecGetArray(v, &x));
3027: PetscCall(PetscArraycpy(x, aa + col * a->lda, A->rmap->n));
3028: PetscCall(VecRestoreArray(v, &x));
3029: PetscCall(MatDenseRestoreArrayRead(A, &aa));
3030: PetscFunctionReturn(PETSC_SUCCESS);
3031: }
3033: PETSC_INTERN PetscErrorCode MatGetColumnReductions_SeqDense(Mat A, PetscInt type, PetscReal *reductions)
3034: {
3035: PetscInt i, j, m, n;
3036: const PetscScalar *a;
3038: PetscFunctionBegin;
3039: PetscCall(MatGetSize(A, &m, &n));
3040: PetscCall(PetscArrayzero(reductions, n));
3041: PetscCall(MatDenseGetArrayRead(A, &a));
3042: if (type == NORM_2) {
3043: for (i = 0; i < n; i++) {
3044: for (j = 0; j < m; j++) reductions[i] += PetscAbsScalar(a[j] * a[j]);
3045: a = PetscSafePointerPlusOffset(a, m);
3046: }
3047: } else if (type == NORM_1) {
3048: for (i = 0; i < n; i++) {
3049: for (j = 0; j < m; j++) reductions[i] += PetscAbsScalar(a[j]);
3050: a = PetscSafePointerPlusOffset(a, m);
3051: }
3052: } else if (type == NORM_INFINITY) {
3053: for (i = 0; i < n; i++) {
3054: for (j = 0; j < m; j++) reductions[i] = PetscMax(PetscAbsScalar(a[j]), reductions[i]);
3055: a = PetscSafePointerPlusOffset(a, m);
3056: }
3057: } else if (type == REDUCTION_SUM_REALPART || type == REDUCTION_MEAN_REALPART) {
3058: for (i = 0; i < n; i++) {
3059: for (j = 0; j < m; j++) reductions[i] += PetscRealPart(a[j]);
3060: a = PetscSafePointerPlusOffset(a, m);
3061: }
3062: } else if (type == REDUCTION_SUM_IMAGINARYPART || type == REDUCTION_MEAN_IMAGINARYPART) {
3063: for (i = 0; i < n; i++) {
3064: for (j = 0; j < m; j++) reductions[i] += PetscImaginaryPart(a[j]);
3065: a = PetscSafePointerPlusOffset(a, m);
3066: }
3067: } else SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Unknown reduction type");
3068: PetscCall(MatDenseRestoreArrayRead(A, &a));
3069: if (type == NORM_2) {
3070: for (i = 0; i < n; i++) reductions[i] = PetscSqrtReal(reductions[i]);
3071: } else if (type == REDUCTION_MEAN_REALPART || type == REDUCTION_MEAN_IMAGINARYPART) {
3072: for (i = 0; i < n; i++) reductions[i] /= m;
3073: }
3074: PetscFunctionReturn(PETSC_SUCCESS);
3075: }
3077: PetscErrorCode MatSetRandom_SeqDense(Mat x, PetscRandom rctx)
3078: {
3079: PetscScalar *a;
3080: PetscInt lda, m, n, i, j;
3082: PetscFunctionBegin;
3083: PetscCall(MatGetSize(x, &m, &n));
3084: PetscCall(MatDenseGetLDA(x, &lda));
3085: PetscCall(MatDenseGetArrayWrite(x, &a));
3086: for (j = 0; j < n; j++) {
3087: for (i = 0; i < m; i++) PetscCall(PetscRandomGetValue(rctx, a + j * lda + i));
3088: }
3089: PetscCall(MatDenseRestoreArrayWrite(x, &a));
3090: PetscFunctionReturn(PETSC_SUCCESS);
3091: }
3093: static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A, PetscBool *missing, PetscInt *d)
3094: {
3095: PetscFunctionBegin;
3096: *missing = PETSC_FALSE;
3097: PetscFunctionReturn(PETSC_SUCCESS);
3098: }
3100: /* vals is not const */
3101: static PetscErrorCode MatDenseGetColumn_SeqDense(Mat A, PetscInt col, PetscScalar **vals)
3102: {
3103: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3104: PetscScalar *v;
3106: PetscFunctionBegin;
3107: PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
3108: PetscCall(MatDenseGetArray(A, &v));
3109: *vals = v + col * a->lda;
3110: PetscCall(MatDenseRestoreArray(A, &v));
3111: PetscFunctionReturn(PETSC_SUCCESS);
3112: }
3114: static PetscErrorCode MatDenseRestoreColumn_SeqDense(Mat A, PetscScalar **vals)
3115: {
3116: PetscFunctionBegin;
3117: if (vals) *vals = NULL; /* user cannot accidentally use the array later */
3118: PetscFunctionReturn(PETSC_SUCCESS);
3119: }
3121: static struct _MatOps MatOps_Values = {MatSetValues_SeqDense,
3122: MatGetRow_SeqDense,
3123: MatRestoreRow_SeqDense,
3124: MatMult_SeqDense,
3125: /* 4*/ MatMultAdd_SeqDense,
3126: MatMultTranspose_SeqDense,
3127: MatMultTransposeAdd_SeqDense,
3128: NULL,
3129: NULL,
3130: NULL,
3131: /* 10*/ NULL,
3132: MatLUFactor_SeqDense,
3133: MatCholeskyFactor_SeqDense,
3134: MatSOR_SeqDense,
3135: MatTranspose_SeqDense,
3136: /* 15*/ MatGetInfo_SeqDense,
3137: MatEqual_SeqDense,
3138: MatGetDiagonal_SeqDense,
3139: MatDiagonalScale_SeqDense,
3140: MatNorm_SeqDense,
3141: /* 20*/ MatAssemblyBegin_SeqDense,
3142: MatAssemblyEnd_SeqDense,
3143: MatSetOption_SeqDense,
3144: MatZeroEntries_SeqDense,
3145: /* 24*/ MatZeroRows_SeqDense,
3146: NULL,
3147: NULL,
3148: NULL,
3149: NULL,
3150: /* 29*/ MatSetUp_SeqDense,
3151: NULL,
3152: NULL,
3153: NULL,
3154: NULL,
3155: /* 34*/ MatDuplicate_SeqDense,
3156: NULL,
3157: NULL,
3158: NULL,
3159: NULL,
3160: /* 39*/ MatAXPY_SeqDense,
3161: MatCreateSubMatrices_SeqDense,
3162: NULL,
3163: MatGetValues_SeqDense,
3164: MatCopy_SeqDense,
3165: /* 44*/ MatGetRowMax_SeqDense,
3166: MatScale_SeqDense,
3167: MatShift_SeqDense,
3168: NULL,
3169: MatZeroRowsColumns_SeqDense,
3170: /* 49*/ MatSetRandom_SeqDense,
3171: NULL,
3172: NULL,
3173: NULL,
3174: NULL,
3175: /* 54*/ NULL,
3176: NULL,
3177: NULL,
3178: NULL,
3179: NULL,
3180: /* 59*/ MatCreateSubMatrix_SeqDense,
3181: MatDestroy_SeqDense,
3182: MatView_SeqDense,
3183: NULL,
3184: NULL,
3185: /* 64*/ NULL,
3186: NULL,
3187: NULL,
3188: NULL,
3189: NULL,
3190: /* 69*/ MatGetRowMaxAbs_SeqDense,
3191: NULL,
3192: NULL,
3193: NULL,
3194: NULL,
3195: /* 74*/ NULL,
3196: NULL,
3197: NULL,
3198: NULL,
3199: NULL,
3200: /* 79*/ NULL,
3201: NULL,
3202: NULL,
3203: NULL,
3204: /* 83*/ MatLoad_SeqDense,
3205: MatIsSymmetric_SeqDense,
3206: MatIsHermitian_SeqDense,
3207: NULL,
3208: NULL,
3209: NULL,
3210: /* 89*/ NULL,
3211: NULL,
3212: MatMatMultNumeric_SeqDense_SeqDense,
3213: NULL,
3214: NULL,
3215: /* 94*/ NULL,
3216: NULL,
3217: NULL,
3218: MatMatTransposeMultNumeric_SeqDense_SeqDense,
3219: NULL,
3220: /* 99*/ MatProductSetFromOptions_SeqDense,
3221: NULL,
3222: NULL,
3223: MatConjugate_SeqDense,
3224: NULL,
3225: /*104*/ NULL,
3226: MatRealPart_SeqDense,
3227: MatImaginaryPart_SeqDense,
3228: NULL,
3229: NULL,
3230: /*109*/ NULL,
3231: NULL,
3232: MatGetRowMin_SeqDense,
3233: MatGetColumnVector_SeqDense,
3234: MatMissingDiagonal_SeqDense,
3235: /*114*/ NULL,
3236: NULL,
3237: NULL,
3238: NULL,
3239: NULL,
3240: /*119*/ NULL,
3241: NULL,
3242: MatMultHermitianTranspose_SeqDense,
3243: MatMultHermitianTransposeAdd_SeqDense,
3244: NULL,
3245: /*124*/ NULL,
3246: MatGetColumnReductions_SeqDense,
3247: NULL,
3248: NULL,
3249: NULL,
3250: /*129*/ NULL,
3251: NULL,
3252: NULL,
3253: MatTransposeMatMultNumeric_SeqDense_SeqDense,
3254: NULL,
3255: /*134*/ NULL,
3256: NULL,
3257: NULL,
3258: NULL,
3259: NULL,
3260: /*139*/ NULL,
3261: NULL,
3262: NULL,
3263: NULL,
3264: NULL,
3265: MatCreateMPIMatConcatenateSeqMat_SeqDense,
3266: /*145*/ NULL,
3267: NULL,
3268: NULL,
3269: NULL,
3270: NULL,
3271: /*150*/ NULL,
3272: NULL,
3273: NULL,
3274: NULL};
3276: /*@
3277: MatCreateSeqDense - Creates a `MATSEQDENSE` that
3278: is stored in column major order (the usual Fortran format).
3280: Collective
3282: Input Parameters:
3283: + comm - MPI communicator, set to `PETSC_COMM_SELF`
3284: . m - number of rows
3285: . n - number of columns
3286: - data - optional location of matrix data in column major order. Use `NULL` for PETSc
3287: to control all matrix memory allocation.
3289: Output Parameter:
3290: . A - the matrix
3292: Level: intermediate
3294: Note:
3295: The data input variable is intended primarily for Fortran programmers
3296: who wish to allocate their own matrix memory space. Most users should
3297: set `data` = `NULL`.
3299: Developer Note:
3300: Many of the matrix operations for this variant use the BLAS and LAPACK routines.
3302: .seealso: [](ch_matrices), `Mat`, `MATSEQDENSE`, `MatCreate()`, `MatCreateDense()`, `MatSetValues()`
3303: @*/
3304: PetscErrorCode MatCreateSeqDense(MPI_Comm comm, PetscInt m, PetscInt n, PetscScalar data[], Mat *A)
3305: {
3306: PetscFunctionBegin;
3307: PetscCall(MatCreate(comm, A));
3308: PetscCall(MatSetSizes(*A, m, n, m, n));
3309: PetscCall(MatSetType(*A, MATSEQDENSE));
3310: PetscCall(MatSeqDenseSetPreallocation(*A, data));
3311: PetscFunctionReturn(PETSC_SUCCESS);
3312: }
3314: /*@
3315: MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements of a `MATSEQDENSE` matrix
3317: Collective
3319: Input Parameters:
3320: + B - the matrix
3321: - data - the array (or `NULL`)
3323: Level: intermediate
3325: Note:
3326: The data input variable is intended primarily for Fortran programmers
3327: who wish to allocate their own matrix memory space. Most users should
3328: need not call this routine.
3330: .seealso: [](ch_matrices), `Mat`, `MATSEQDENSE`, `MatCreate()`, `MatCreateDense()`, `MatSetValues()`, `MatDenseSetLDA()`
3331: @*/
3332: PetscErrorCode MatSeqDenseSetPreallocation(Mat B, PetscScalar data[])
3333: {
3334: PetscFunctionBegin;
3336: PetscTryMethod(B, "MatSeqDenseSetPreallocation_C", (Mat, PetscScalar[]), (B, data));
3337: PetscFunctionReturn(PETSC_SUCCESS);
3338: }
3340: PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B, PetscScalar *data)
3341: {
3342: Mat_SeqDense *b = (Mat_SeqDense *)B->data;
3344: PetscFunctionBegin;
3345: PetscCheck(!b->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
3346: B->preallocated = PETSC_TRUE;
3348: PetscCall(PetscLayoutSetUp(B->rmap));
3349: PetscCall(PetscLayoutSetUp(B->cmap));
3351: if (b->lda <= 0) b->lda = B->rmap->n;
3353: if (!data) { /* petsc-allocated storage */
3354: if (!b->user_alloc) PetscCall(PetscFree(b->v));
3355: PetscCall(PetscCalloc1((size_t)b->lda * B->cmap->n, &b->v));
3357: b->user_alloc = PETSC_FALSE;
3358: } else { /* user-allocated storage */
3359: if (!b->user_alloc) PetscCall(PetscFree(b->v));
3360: b->v = data;
3361: b->user_alloc = PETSC_TRUE;
3362: }
3363: B->assembled = PETSC_TRUE;
3364: PetscFunctionReturn(PETSC_SUCCESS);
3365: }
3367: #if defined(PETSC_HAVE_ELEMENTAL)
3368: PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
3369: {
3370: Mat mat_elemental;
3371: const PetscScalar *array;
3372: PetscScalar *v_colwise;
3373: PetscInt M = A->rmap->N, N = A->cmap->N, i, j, k, *rows, *cols;
3375: PetscFunctionBegin;
3376: PetscCall(PetscMalloc3(M * N, &v_colwise, M, &rows, N, &cols));
3377: PetscCall(MatDenseGetArrayRead(A, &array));
3378: /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */
3379: k = 0;
3380: for (j = 0; j < N; j++) {
3381: cols[j] = j;
3382: for (i = 0; i < M; i++) v_colwise[j * M + i] = array[k++];
3383: }
3384: for (i = 0; i < M; i++) rows[i] = i;
3385: PetscCall(MatDenseRestoreArrayRead(A, &array));
3387: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental));
3388: PetscCall(MatSetSizes(mat_elemental, PETSC_DECIDE, PETSC_DECIDE, M, N));
3389: PetscCall(MatSetType(mat_elemental, MATELEMENTAL));
3390: PetscCall(MatSetUp(mat_elemental));
3392: /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */
3393: PetscCall(MatSetValues(mat_elemental, M, rows, N, cols, v_colwise, ADD_VALUES));
3394: PetscCall(MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY));
3395: PetscCall(MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY));
3396: PetscCall(PetscFree3(v_colwise, rows, cols));
3398: if (reuse == MAT_INPLACE_MATRIX) {
3399: PetscCall(MatHeaderReplace(A, &mat_elemental));
3400: } else {
3401: *newmat = mat_elemental;
3402: }
3403: PetscFunctionReturn(PETSC_SUCCESS);
3404: }
3405: #endif
3407: PetscErrorCode MatDenseSetLDA_SeqDense(Mat B, PetscInt lda)
3408: {
3409: Mat_SeqDense *b = (Mat_SeqDense *)B->data;
3410: PetscBool data;
3412: PetscFunctionBegin;
3413: data = (PetscBool)((B->rmap->n > 0 && B->cmap->n > 0) ? (b->v ? PETSC_TRUE : PETSC_FALSE) : PETSC_FALSE);
3414: PetscCheck(b->user_alloc || !data || b->lda == lda, PETSC_COMM_SELF, PETSC_ERR_ORDER, "LDA cannot be changed after allocation of internal storage");
3415: PetscCheck(lda >= B->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "LDA %" PetscInt_FMT " must be at least matrix dimension %" PetscInt_FMT, lda, B->rmap->n);
3416: b->lda = lda;
3417: PetscFunctionReturn(PETSC_SUCCESS);
3418: }
3420: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqDense(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
3421: {
3422: PetscFunctionBegin;
3423: PetscCall(MatCreateMPIMatConcatenateSeqMat_MPIDense(comm, inmat, n, scall, outmat));
3424: PetscFunctionReturn(PETSC_SUCCESS);
3425: }
3427: PetscErrorCode MatDenseCreateColumnVec_Private(Mat A, Vec *v)
3428: {
3429: PetscBool isstd, iskok, iscuda, iship;
3430: PetscMPIInt size;
3431: #if PetscDefined(HAVE_CUDA) || PetscDefined(HAVE_HIP)
3432: /* we pass the data of A, to prevent allocating needless GPU memory the first time VecCUPMPlaceArray is called. */
3433: const PetscScalar *a;
3434: #endif
3436: PetscFunctionBegin;
3437: *v = NULL;
3438: PetscCall(PetscStrcmpAny(A->defaultvectype, &isstd, VECSTANDARD, VECSEQ, VECMPI, ""));
3439: PetscCall(PetscStrcmpAny(A->defaultvectype, &iskok, VECKOKKOS, VECSEQKOKKOS, VECMPIKOKKOS, ""));
3440: PetscCall(PetscStrcmpAny(A->defaultvectype, &iscuda, VECCUDA, VECSEQCUDA, VECMPICUDA, ""));
3441: PetscCall(PetscStrcmpAny(A->defaultvectype, &iship, VECHIP, VECSEQHIP, VECMPIHIP, ""));
3442: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
3443: if (isstd) {
3444: if (size > 1) PetscCall(VecCreateMPIWithArray(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, A->rmap->N, NULL, v));
3445: else PetscCall(VecCreateSeqWithArray(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, NULL, v));
3446: } else if (iskok) {
3447: PetscCheck(PetscDefined(HAVE_KOKKOS_KERNELS), PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Reconfigure using KOKKOS kernels support");
3448: #if PetscDefined(HAVE_KOKKOS_KERNELS)
3449: if (size > 1) PetscCall(VecCreateMPIKokkosWithArray(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, A->rmap->N, NULL, v));
3450: else PetscCall(VecCreateSeqKokkosWithArray(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, NULL, v));
3451: #endif
3452: } else if (iscuda) {
3453: PetscCheck(PetscDefined(HAVE_CUDA), PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Reconfigure using CUDA support");
3454: #if PetscDefined(HAVE_CUDA)
3455: PetscCall(MatDenseCUDAGetArrayRead(A, &a));
3456: if (size > 1) PetscCall(VecCreateMPICUDAWithArrays(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, A->rmap->N, NULL, a, v));
3457: else PetscCall(VecCreateSeqCUDAWithArrays(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, NULL, a, v));
3458: #endif
3459: } else if (iship) {
3460: PetscCheck(PetscDefined(HAVE_HIP), PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Reconfigure using HIP support");
3461: #if PetscDefined(HAVE_HIP)
3462: PetscCall(MatDenseHIPGetArrayRead(A, &a));
3463: if (size > 1) PetscCall(VecCreateMPIHIPWithArrays(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, A->rmap->N, NULL, a, v));
3464: else PetscCall(VecCreateSeqHIPWithArrays(PetscObjectComm((PetscObject)A), A->rmap->bs, A->rmap->n, NULL, a, v));
3465: #endif
3466: }
3467: PetscCheck(*v, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not coded for type %s", A->defaultvectype);
3468: PetscFunctionReturn(PETSC_SUCCESS);
3469: }
3471: PetscErrorCode MatDenseGetColumnVec_SeqDense(Mat A, PetscInt col, Vec *v)
3472: {
3473: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3475: PetscFunctionBegin;
3476: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
3477: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
3478: if (!a->cvec) PetscCall(MatDenseCreateColumnVec_Private(A, &a->cvec));
3479: a->vecinuse = col + 1;
3480: PetscCall(MatDenseGetArray(A, (PetscScalar **)&a->ptrinuse));
3481: PetscCall(VecPlaceArray(a->cvec, a->ptrinuse + (size_t)col * (size_t)a->lda));
3482: *v = a->cvec;
3483: PetscFunctionReturn(PETSC_SUCCESS);
3484: }
3486: PetscErrorCode MatDenseRestoreColumnVec_SeqDense(Mat A, PetscInt col, Vec *v)
3487: {
3488: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3490: PetscFunctionBegin;
3491: PetscCheck(a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseGetColumnVec() first");
3492: PetscCheck(a->cvec, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing internal column vector");
3493: VecCheckAssembled(a->cvec);
3494: a->vecinuse = 0;
3495: PetscCall(MatDenseRestoreArray(A, (PetscScalar **)&a->ptrinuse));
3496: PetscCall(VecResetArray(a->cvec));
3497: if (v) *v = NULL;
3498: PetscFunctionReturn(PETSC_SUCCESS);
3499: }
3501: PetscErrorCode MatDenseGetColumnVecRead_SeqDense(Mat A, PetscInt col, Vec *v)
3502: {
3503: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3505: PetscFunctionBegin;
3506: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
3507: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
3508: if (!a->cvec) PetscCall(MatDenseCreateColumnVec_Private(A, &a->cvec));
3509: a->vecinuse = col + 1;
3510: PetscCall(MatDenseGetArrayRead(A, &a->ptrinuse));
3511: PetscCall(VecPlaceArray(a->cvec, PetscSafePointerPlusOffset(a->ptrinuse, (size_t)col * (size_t)a->lda)));
3512: PetscCall(VecLockReadPush(a->cvec));
3513: *v = a->cvec;
3514: PetscFunctionReturn(PETSC_SUCCESS);
3515: }
3517: PetscErrorCode MatDenseRestoreColumnVecRead_SeqDense(Mat A, PetscInt col, Vec *v)
3518: {
3519: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3521: PetscFunctionBegin;
3522: PetscCheck(a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseGetColumnVec() first");
3523: PetscCheck(a->cvec, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing internal column vector");
3524: VecCheckAssembled(a->cvec);
3525: a->vecinuse = 0;
3526: PetscCall(MatDenseRestoreArrayRead(A, &a->ptrinuse));
3527: PetscCall(VecLockReadPop(a->cvec));
3528: PetscCall(VecResetArray(a->cvec));
3529: if (v) *v = NULL;
3530: PetscFunctionReturn(PETSC_SUCCESS);
3531: }
3533: PetscErrorCode MatDenseGetColumnVecWrite_SeqDense(Mat A, PetscInt col, Vec *v)
3534: {
3535: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3537: PetscFunctionBegin;
3538: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
3539: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
3540: if (!a->cvec) PetscCall(MatDenseCreateColumnVec_Private(A, &a->cvec));
3541: a->vecinuse = col + 1;
3542: PetscCall(MatDenseGetArrayWrite(A, (PetscScalar **)&a->ptrinuse));
3543: PetscCall(VecPlaceArray(a->cvec, PetscSafePointerPlusOffset(a->ptrinuse, (size_t)col * (size_t)a->lda)));
3544: *v = a->cvec;
3545: PetscFunctionReturn(PETSC_SUCCESS);
3546: }
3548: PetscErrorCode MatDenseRestoreColumnVecWrite_SeqDense(Mat A, PetscInt col, Vec *v)
3549: {
3550: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3552: PetscFunctionBegin;
3553: PetscCheck(a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseGetColumnVec() first");
3554: PetscCheck(a->cvec, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing internal column vector");
3555: VecCheckAssembled(a->cvec);
3556: a->vecinuse = 0;
3557: PetscCall(MatDenseRestoreArrayWrite(A, (PetscScalar **)&a->ptrinuse));
3558: PetscCall(VecResetArray(a->cvec));
3559: if (v) *v = NULL;
3560: PetscFunctionReturn(PETSC_SUCCESS);
3561: }
3563: PetscErrorCode MatDenseGetSubMatrix_SeqDense(Mat A, PetscInt rbegin, PetscInt rend, PetscInt cbegin, PetscInt cend, Mat *v)
3564: {
3565: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3567: PetscFunctionBegin;
3568: PetscCheck(!a->vecinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreColumnVec() first");
3569: PetscCheck(!a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseRestoreSubMatrix() first");
3570: if (a->cmat && (cend - cbegin != a->cmat->cmap->N || rend - rbegin != a->cmat->rmap->N)) PetscCall(MatDestroy(&a->cmat));
3571: if (!a->cmat) {
3572: PetscCall(MatCreateDense(PetscObjectComm((PetscObject)A), rend - rbegin, PETSC_DECIDE, rend - rbegin, cend - cbegin, PetscSafePointerPlusOffset(a->v, rbegin + (size_t)cbegin * a->lda), &a->cmat));
3573: } else {
3574: PetscCall(MatDensePlaceArray(a->cmat, PetscSafePointerPlusOffset(a->v, rbegin + (size_t)cbegin * a->lda)));
3575: }
3576: PetscCall(MatDenseSetLDA(a->cmat, a->lda));
3577: a->matinuse = cbegin + 1;
3578: *v = a->cmat;
3579: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
3580: A->offloadmask = PETSC_OFFLOAD_CPU;
3581: #endif
3582: PetscFunctionReturn(PETSC_SUCCESS);
3583: }
3585: PetscErrorCode MatDenseRestoreSubMatrix_SeqDense(Mat A, Mat *v)
3586: {
3587: Mat_SeqDense *a = (Mat_SeqDense *)A->data;
3589: PetscFunctionBegin;
3590: PetscCheck(a->matinuse, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Need to call MatDenseGetSubMatrix() first");
3591: PetscCheck(a->cmat, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing internal column matrix");
3592: PetscCheck(*v == a->cmat, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Not the matrix obtained from MatDenseGetSubMatrix()");
3593: a->matinuse = 0;
3594: PetscCall(MatDenseResetArray(a->cmat));
3595: if (v) *v = NULL;
3596: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_HIP)
3597: A->offloadmask = PETSC_OFFLOAD_CPU;
3598: #endif
3599: PetscFunctionReturn(PETSC_SUCCESS);
3600: }
3602: /*MC
3603: MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices.
3605: Options Database Key:
3606: . -mat_type seqdense - sets the matrix type to `MATSEQDENSE` during a call to `MatSetFromOptions()`
3608: Level: beginner
3610: .seealso: [](ch_matrices), `Mat`, `MATSEQDENSE`, `MatCreateSeqDense()`
3611: M*/
3612: PetscErrorCode MatCreate_SeqDense(Mat B)
3613: {
3614: Mat_SeqDense *b;
3615: PetscMPIInt size;
3617: PetscFunctionBegin;
3618: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
3619: PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1");
3621: PetscCall(PetscNew(&b));
3622: B->data = (void *)b;
3623: B->ops[0] = MatOps_Values;
3625: b->roworiented = PETSC_TRUE;
3627: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatQRFactor_C", MatQRFactor_SeqDense));
3628: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetLDA_C", MatDenseGetLDA_SeqDense));
3629: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseSetLDA_C", MatDenseSetLDA_SeqDense));
3630: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetArray_C", MatDenseGetArray_SeqDense));
3631: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreArray_C", MatDenseRestoreArray_SeqDense));
3632: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDensePlaceArray_C", MatDensePlaceArray_SeqDense));
3633: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseResetArray_C", MatDenseResetArray_SeqDense));
3634: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseReplaceArray_C", MatDenseReplaceArray_SeqDense));
3635: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetArrayRead_C", MatDenseGetArray_SeqDense));
3636: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreArrayRead_C", MatDenseRestoreArray_SeqDense));
3637: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetArrayWrite_C", MatDenseGetArray_SeqDense));
3638: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreArrayWrite_C", MatDenseRestoreArray_SeqDense));
3639: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqdense_seqaij_C", MatConvert_SeqDense_SeqAIJ));
3640: #if defined(PETSC_HAVE_ELEMENTAL)
3641: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqdense_elemental_C", MatConvert_SeqDense_Elemental));
3642: #endif
3643: #if defined(PETSC_HAVE_SCALAPACK)
3644: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqdense_scalapack_C", MatConvert_Dense_ScaLAPACK));
3645: #endif
3646: #if defined(PETSC_HAVE_CUDA)
3647: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqdense_seqdensecuda_C", MatConvert_SeqDense_SeqDenseCUDA));
3648: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdensecuda_seqdensecuda_C", MatProductSetFromOptions_SeqDense));
3649: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdensecuda_seqdense_C", MatProductSetFromOptions_SeqDense));
3650: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdense_seqdensecuda_C", MatProductSetFromOptions_SeqDense));
3651: #endif
3652: #if defined(PETSC_HAVE_HIP)
3653: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqdense_seqdensehip_C", MatConvert_SeqDense_SeqDenseHIP));
3654: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdensehip_seqdensehip_C", MatProductSetFromOptions_SeqDense));
3655: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdensehip_seqdense_C", MatProductSetFromOptions_SeqDense));
3656: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdense_seqdensehip_C", MatProductSetFromOptions_SeqDense));
3657: #endif
3658: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqDenseSetPreallocation_C", MatSeqDenseSetPreallocation_SeqDense));
3659: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqaij_seqdense_C", MatProductSetFromOptions_SeqAIJ_SeqDense));
3660: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqdense_seqdense_C", MatProductSetFromOptions_SeqDense));
3661: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqbaij_seqdense_C", MatProductSetFromOptions_SeqXBAIJ_SeqDense));
3662: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatProductSetFromOptions_seqsbaij_seqdense_C", MatProductSetFromOptions_SeqXBAIJ_SeqDense));
3664: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetColumn_C", MatDenseGetColumn_SeqDense));
3665: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreColumn_C", MatDenseRestoreColumn_SeqDense));
3666: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetColumnVec_C", MatDenseGetColumnVec_SeqDense));
3667: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreColumnVec_C", MatDenseRestoreColumnVec_SeqDense));
3668: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetColumnVecRead_C", MatDenseGetColumnVecRead_SeqDense));
3669: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreColumnVecRead_C", MatDenseRestoreColumnVecRead_SeqDense));
3670: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetColumnVecWrite_C", MatDenseGetColumnVecWrite_SeqDense));
3671: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreColumnVecWrite_C", MatDenseRestoreColumnVecWrite_SeqDense));
3672: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseGetSubMatrix_C", MatDenseGetSubMatrix_SeqDense));
3673: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDenseRestoreSubMatrix_C", MatDenseRestoreSubMatrix_SeqDense));
3674: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMultAddColumnRange_C", MatMultAddColumnRange_SeqDense));
3675: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMultHermitianTransposeColumnRange_C", MatMultHermitianTransposeColumnRange_SeqDense));
3676: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMultHermitianTransposeAddColumnRange_C", MatMultHermitianTransposeAddColumnRange_SeqDense));
3677: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQDENSE));
3678: PetscFunctionReturn(PETSC_SUCCESS);
3679: }
3681: /*@C
3682: MatDenseGetColumn - gives access to a column of a dense matrix. This is only the local part of the column. You MUST call `MatDenseRestoreColumn()` to avoid memory bleeding.
3684: Not Collective
3686: Input Parameters:
3687: + A - a `MATSEQDENSE` or `MATMPIDENSE` matrix
3688: - col - column index
3690: Output Parameter:
3691: . vals - pointer to the data
3693: Level: intermediate
3695: Note:
3696: Use `MatDenseGetColumnVec()` to get access to a column of a `MATDENSE` treated as a `Vec`
3698: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseRestoreColumn()`, `MatDenseGetColumnVec()`
3699: @*/
3700: PetscErrorCode MatDenseGetColumn(Mat A, PetscInt col, PetscScalar *vals[])
3701: {
3702: PetscFunctionBegin;
3705: PetscAssertPointer(vals, 3);
3706: PetscUseMethod(A, "MatDenseGetColumn_C", (Mat, PetscInt, PetscScalar **), (A, col, vals));
3707: PetscFunctionReturn(PETSC_SUCCESS);
3708: }
3710: /*@C
3711: MatDenseRestoreColumn - returns access to a column of a `MATDENSE` matrix which is returned by `MatDenseGetColumn()`.
3713: Not Collective
3715: Input Parameters:
3716: + A - a `MATSEQDENSE` or `MATMPIDENSE` matrix
3717: - vals - pointer to the data (may be `NULL`)
3719: Level: intermediate
3721: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MatDenseGetColumn()`
3722: @*/
3723: PetscErrorCode MatDenseRestoreColumn(Mat A, PetscScalar *vals[])
3724: {
3725: PetscFunctionBegin;
3727: PetscAssertPointer(vals, 2);
3728: PetscUseMethod(A, "MatDenseRestoreColumn_C", (Mat, PetscScalar **), (A, vals));
3729: PetscFunctionReturn(PETSC_SUCCESS);
3730: }
3732: /*@
3733: MatDenseGetColumnVec - Gives read-write access to a column of a `MATDENSE` matrix, represented as a `Vec`.
3735: Collective
3737: Input Parameters:
3738: + A - the `Mat` object
3739: - col - the column index
3741: Output Parameter:
3742: . v - the vector
3744: Level: intermediate
3746: Notes:
3747: The vector is owned by PETSc. Users need to call `MatDenseRestoreColumnVec()` when the vector is no longer needed.
3749: Use `MatDenseGetColumnVecRead()` to obtain read-only access or `MatDenseGetColumnVecWrite()` for write-only access.
3751: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVecRead()`, `MatDenseGetColumnVecWrite()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreColumnVecRead()`, `MatDenseRestoreColumnVecWrite()`, `MatDenseGetColumn()`
3752: @*/
3753: PetscErrorCode MatDenseGetColumnVec(Mat A, PetscInt col, Vec *v)
3754: {
3755: PetscFunctionBegin;
3759: PetscAssertPointer(v, 3);
3760: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3761: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3762: PetscUseMethod(A, "MatDenseGetColumnVec_C", (Mat, PetscInt, Vec *), (A, col, v));
3763: PetscFunctionReturn(PETSC_SUCCESS);
3764: }
3766: /*@
3767: MatDenseRestoreColumnVec - Returns access to a column of a dense matrix obtained from `MatDenseGetColumnVec()`.
3769: Collective
3771: Input Parameters:
3772: + A - the `Mat` object
3773: . col - the column index
3774: - v - the `Vec` object (may be `NULL`)
3776: Level: intermediate
3778: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseGetColumnVecRead()`, `MatDenseGetColumnVecWrite()`, `MatDenseRestoreColumnVecRead()`, `MatDenseRestoreColumnVecWrite()`
3779: @*/
3780: PetscErrorCode MatDenseRestoreColumnVec(Mat A, PetscInt col, Vec *v)
3781: {
3782: PetscFunctionBegin;
3786: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3787: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3788: PetscUseMethod(A, "MatDenseRestoreColumnVec_C", (Mat, PetscInt, Vec *), (A, col, v));
3789: PetscFunctionReturn(PETSC_SUCCESS);
3790: }
3792: /*@
3793: MatDenseGetColumnVecRead - Gives read-only access to a column of a dense matrix, represented as a `Vec`.
3795: Collective
3797: Input Parameters:
3798: + A - the `Mat` object
3799: - col - the column index
3801: Output Parameter:
3802: . v - the vector
3804: Level: intermediate
3806: Notes:
3807: The vector is owned by PETSc and users cannot modify it.
3809: Users need to call `MatDenseRestoreColumnVecRead()` when the vector is no longer needed.
3811: Use `MatDenseGetColumnVec()` to obtain read-write access or `MatDenseGetColumnVecWrite()` for write-only access.
3813: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseGetColumnVecWrite()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreColumnVecRead()`, `MatDenseRestoreColumnVecWrite()`
3814: @*/
3815: PetscErrorCode MatDenseGetColumnVecRead(Mat A, PetscInt col, Vec *v)
3816: {
3817: PetscFunctionBegin;
3821: PetscAssertPointer(v, 3);
3822: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3823: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3824: PetscUseMethod(A, "MatDenseGetColumnVecRead_C", (Mat, PetscInt, Vec *), (A, col, v));
3825: PetscFunctionReturn(PETSC_SUCCESS);
3826: }
3828: /*@
3829: MatDenseRestoreColumnVecRead - Returns access to a column of a dense matrix obtained from `MatDenseGetColumnVecRead()`.
3831: Collective
3833: Input Parameters:
3834: + A - the `Mat` object
3835: . col - the column index
3836: - v - the `Vec` object (may be `NULL`)
3838: Level: intermediate
3840: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseGetColumnVecRead()`, `MatDenseGetColumnVecWrite()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreColumnVecWrite()`
3841: @*/
3842: PetscErrorCode MatDenseRestoreColumnVecRead(Mat A, PetscInt col, Vec *v)
3843: {
3844: PetscFunctionBegin;
3848: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3849: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3850: PetscUseMethod(A, "MatDenseRestoreColumnVecRead_C", (Mat, PetscInt, Vec *), (A, col, v));
3851: PetscFunctionReturn(PETSC_SUCCESS);
3852: }
3854: /*@
3855: MatDenseGetColumnVecWrite - Gives write-only access to a column of a dense matrix, represented as a `Vec`.
3857: Collective
3859: Input Parameters:
3860: + A - the `Mat` object
3861: - col - the column index
3863: Output Parameter:
3864: . v - the vector
3866: Level: intermediate
3868: Notes:
3869: The vector is owned by PETSc. Users need to call `MatDenseRestoreColumnVecWrite()` when the vector is no longer needed.
3871: Use `MatDenseGetColumnVec()` to obtain read-write access or `MatDenseGetColumnVecRead()` for read-only access.
3873: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseGetColumnVecRead()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreColumnVecRead()`, `MatDenseRestoreColumnVecWrite()`
3874: @*/
3875: PetscErrorCode MatDenseGetColumnVecWrite(Mat A, PetscInt col, Vec *v)
3876: {
3877: PetscFunctionBegin;
3881: PetscAssertPointer(v, 3);
3882: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3883: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3884: PetscUseMethod(A, "MatDenseGetColumnVecWrite_C", (Mat, PetscInt, Vec *), (A, col, v));
3885: PetscFunctionReturn(PETSC_SUCCESS);
3886: }
3888: /*@
3889: MatDenseRestoreColumnVecWrite - Returns access to a column of a dense matrix obtained from `MatDenseGetColumnVecWrite()`.
3891: Collective
3893: Input Parameters:
3894: + A - the `Mat` object
3895: . col - the column index
3896: - v - the `Vec` object (may be `NULL`)
3898: Level: intermediate
3900: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseGetColumnVecRead()`, `MatDenseGetColumnVecWrite()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreColumnVecRead()`
3901: @*/
3902: PetscErrorCode MatDenseRestoreColumnVecWrite(Mat A, PetscInt col, Vec *v)
3903: {
3904: PetscFunctionBegin;
3908: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3909: PetscCheck(col >= 0 && col < A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid col %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT ")", col, A->cmap->N);
3910: PetscUseMethod(A, "MatDenseRestoreColumnVecWrite_C", (Mat, PetscInt, Vec *), (A, col, v));
3911: PetscFunctionReturn(PETSC_SUCCESS);
3912: }
3914: /*@
3915: MatDenseGetSubMatrix - Gives access to a block of rows and columns of a dense matrix, represented as a `Mat`.
3917: Collective
3919: Input Parameters:
3920: + A - the `Mat` object
3921: . rbegin - the first global row index in the block (if `PETSC_DECIDE`, is 0)
3922: . rend - the global row index past the last one in the block (if `PETSC_DECIDE`, is `M`)
3923: . cbegin - the first global column index in the block (if `PETSC_DECIDE`, is 0)
3924: - cend - the global column index past the last one in the block (if `PETSC_DECIDE`, is `N`)
3926: Output Parameter:
3927: . v - the matrix
3929: Level: intermediate
3931: Notes:
3932: The matrix is owned by PETSc. Users need to call `MatDenseRestoreSubMatrix()` when the matrix is no longer needed.
3934: The output matrix is not redistributed by PETSc, so depending on the values of `rbegin` and `rend`, some processes may have no local rows.
3936: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseRestoreColumnVec()`, `MatDenseRestoreSubMatrix()`
3937: @*/
3938: PetscErrorCode MatDenseGetSubMatrix(Mat A, PetscInt rbegin, PetscInt rend, PetscInt cbegin, PetscInt cend, Mat *v)
3939: {
3940: PetscFunctionBegin;
3947: PetscAssertPointer(v, 6);
3948: if (rbegin == PETSC_DECIDE) rbegin = 0;
3949: if (rend == PETSC_DECIDE) rend = A->rmap->N;
3950: if (cbegin == PETSC_DECIDE) cbegin = 0;
3951: if (cend == PETSC_DECIDE) cend = A->cmap->N;
3952: PetscCheck(A->preallocated, PetscObjectComm((PetscObject)A), PETSC_ERR_ORDER, "Matrix not preallocated");
3953: PetscCheck(rbegin >= 0 && rbegin <= A->rmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid rbegin %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT "]", rbegin, A->rmap->N);
3954: PetscCheck(rend >= rbegin && rend <= A->rmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid rend %" PetscInt_FMT ", should be in [%" PetscInt_FMT ",%" PetscInt_FMT "]", rend, rbegin, A->rmap->N);
3955: PetscCheck(cbegin >= 0 && cbegin <= A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid cbegin %" PetscInt_FMT ", should be in [0,%" PetscInt_FMT "]", cbegin, A->cmap->N);
3956: PetscCheck(cend >= cbegin && cend <= A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Invalid cend %" PetscInt_FMT ", should be in [%" PetscInt_FMT ",%" PetscInt_FMT "]", cend, cbegin, A->cmap->N);
3957: PetscUseMethod(A, "MatDenseGetSubMatrix_C", (Mat, PetscInt, PetscInt, PetscInt, PetscInt, Mat *), (A, rbegin, rend, cbegin, cend, v));
3958: PetscFunctionReturn(PETSC_SUCCESS);
3959: }
3961: /*@
3962: MatDenseRestoreSubMatrix - Returns access to a block of columns of a dense matrix obtained from `MatDenseGetSubMatrix()`.
3964: Collective
3966: Input Parameters:
3967: + A - the `Mat` object
3968: - v - the `Mat` object (may be `NULL`)
3970: Level: intermediate
3972: .seealso: [](ch_matrices), `Mat`, `MATDENSE`, `MATDENSECUDA`, `MATDENSEHIP`, `MatDenseGetColumnVec()`, `MatDenseRestoreColumnVec()`, `MatDenseGetSubMatrix()`
3973: @*/
3974: PetscErrorCode MatDenseRestoreSubMatrix(Mat A, Mat *v)
3975: {
3976: PetscFunctionBegin;
3979: PetscAssertPointer(v, 2);
3980: PetscUseMethod(A, "MatDenseRestoreSubMatrix_C", (Mat, Mat *), (A, v));
3981: PetscFunctionReturn(PETSC_SUCCESS);
3982: }
3984: #include <petscblaslapack.h>
3985: #include <petsc/private/kernels/blockinvert.h>
3987: PetscErrorCode MatSeqDenseInvert(Mat A)
3988: {
3989: PetscInt m;
3990: const PetscReal shift = 0.0;
3991: PetscBool allowzeropivot, zeropivotdetected = PETSC_FALSE;
3992: PetscScalar *values;
3994: PetscFunctionBegin;
3996: PetscCall(MatDenseGetArray(A, &values));
3997: PetscCall(MatGetLocalSize(A, &m, NULL));
3998: allowzeropivot = PetscNot(A->erroriffailure);
3999: /* factor and invert each block */
4000: switch (m) {
4001: case 1:
4002: values[0] = (PetscScalar)1.0 / (values[0] + shift);
4003: break;
4004: case 2:
4005: PetscCall(PetscKernel_A_gets_inverse_A_2(values, shift, allowzeropivot, &zeropivotdetected));
4006: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4007: break;
4008: case 3:
4009: PetscCall(PetscKernel_A_gets_inverse_A_3(values, shift, allowzeropivot, &zeropivotdetected));
4010: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4011: break;
4012: case 4:
4013: PetscCall(PetscKernel_A_gets_inverse_A_4(values, shift, allowzeropivot, &zeropivotdetected));
4014: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4015: break;
4016: case 5: {
4017: PetscScalar work[25];
4018: PetscInt ipvt[5];
4020: PetscCall(PetscKernel_A_gets_inverse_A_5(values, ipvt, work, shift, allowzeropivot, &zeropivotdetected));
4021: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4022: } break;
4023: case 6:
4024: PetscCall(PetscKernel_A_gets_inverse_A_6(values, shift, allowzeropivot, &zeropivotdetected));
4025: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4026: break;
4027: case 7:
4028: PetscCall(PetscKernel_A_gets_inverse_A_7(values, shift, allowzeropivot, &zeropivotdetected));
4029: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4030: break;
4031: default: {
4032: PetscInt *v_pivots, *IJ, j;
4033: PetscScalar *v_work;
4035: PetscCall(PetscMalloc3(m, &v_work, m, &v_pivots, m, &IJ));
4036: for (j = 0; j < m; j++) IJ[j] = j;
4037: PetscCall(PetscKernel_A_gets_inverse_A(m, values, v_pivots, v_work, allowzeropivot, &zeropivotdetected));
4038: if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
4039: PetscCall(PetscFree3(v_work, v_pivots, IJ));
4040: }
4041: }
4042: PetscCall(MatDenseRestoreArray(A, &values));
4043: PetscFunctionReturn(PETSC_SUCCESS);
4044: }