Actual source code: mkl_pardiso.c
1: #include <../src/mat/impls/aij/seq/aij.h>
2: #include <../src/mat/impls/sbaij/seq/sbaij.h>
3: #include <../src/mat/impls/dense/seq/dense.h>
5: #if defined(PETSC_HAVE_MKL_INTEL_ILP64)
6: #define MKL_ILP64
7: #endif
8: #include <mkl_pardiso.h>
10: PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int);
12: /*
13: * Possible mkl_pardiso phases that controls the execution of the solver.
14: * For more information check mkl_pardiso manual.
15: */
16: #define JOB_ANALYSIS 11
17: #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION 12
18: #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 13
19: #define JOB_NUMERICAL_FACTORIZATION 22
20: #define JOB_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 23
21: #define JOB_SOLVE_ITERATIVE_REFINEMENT 33
22: #define JOB_SOLVE_FORWARD_SUBSTITUTION 331
23: #define JOB_SOLVE_DIAGONAL_SUBSTITUTION 332
24: #define JOB_SOLVE_BACKWARD_SUBSTITUTION 333
25: #define JOB_RELEASE_OF_LU_MEMORY 0
26: #define JOB_RELEASE_OF_ALL_MEMORY -1
28: #define IPARM_SIZE 64
30: #if defined(PETSC_USE_64BIT_INDICES)
31: #if defined(PETSC_HAVE_MKL_INTEL_ILP64)
32: #define INT_TYPE long long int
33: #define MKL_PARDISO pardiso
34: #define MKL_PARDISO_INIT pardisoinit
35: #else
36: /* this is the case where the MKL BLAS/LAPACK are 32-bit integers but the 64-bit integer version of
37: of PARDISO code is used; hence the need for the 64 below*/
38: #define INT_TYPE long long int
39: #define MKL_PARDISO pardiso_64
40: #define MKL_PARDISO_INIT pardiso_64init
41: void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm[])
42: {
43: int iparm_copy[IPARM_SIZE], mtype_copy, i;
45: mtype_copy = *mtype;
46: pardisoinit(pt, &mtype_copy, iparm_copy);
47: for (i = 0; i < IPARM_SIZE; i++) iparm[i] = iparm_copy[i];
48: }
49: #endif
50: #else
51: #define INT_TYPE int
52: #define MKL_PARDISO pardiso
53: #define MKL_PARDISO_INIT pardisoinit
54: #endif
56: /*
57: Internal data structure.
58: */
59: typedef struct {
60: /* Configuration vector*/
61: INT_TYPE iparm[IPARM_SIZE];
63: /*
64: Internal MKL PARDISO memory location.
65: After the first call to MKL PARDISO do not modify pt, as that could cause a serious memory leak.
66: */
67: void *pt[IPARM_SIZE];
69: /* Basic MKL PARDISO info */
70: INT_TYPE phase, maxfct, mnum, mtype, n, nrhs, msglvl, err;
72: /* Matrix structure*/
73: void *a;
74: INT_TYPE *ia, *ja;
76: /* Number of non-zero elements*/
77: INT_TYPE nz;
79: /* Row permutaton vector*/
80: INT_TYPE *perm;
82: /* Define if matrix preserves sparse structure.*/
83: MatStructure matstruc;
85: PetscBool needsym;
86: PetscBool freeaij;
88: /* Schur complement */
89: PetscScalar *schur;
90: PetscInt schur_size;
91: PetscInt *schur_idxs;
92: PetscScalar *schur_work;
93: PetscBLASInt schur_work_size;
94: PetscBool solve_interior;
96: /* True if MKL PARDISO function have been used. */
97: PetscBool CleanUp;
99: /* Conversion to a format suitable for MKL */
100: PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool *, INT_TYPE *, INT_TYPE **, INT_TYPE **, PetscScalar **);
101: } Mat_MKL_PARDISO;
103: static PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A, PetscBool sym, MatReuse reuse, PetscBool *free, INT_TYPE *nnz, INT_TYPE **r, INT_TYPE **c, PetscScalar **v)
104: {
105: Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ *)A->data;
106: PetscInt bs = A->rmap->bs, i;
108: PetscFunctionBegin;
109: PetscCheck(sym, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "This should not happen");
110: *v = aa->a;
111: if (bs == 1) { /* already in the correct format */
112: /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */
113: *r = (INT_TYPE *)aa->i;
114: *c = (INT_TYPE *)aa->j;
115: *nnz = (INT_TYPE)aa->nz;
116: *free = PETSC_FALSE;
117: } else if (reuse == MAT_INITIAL_MATRIX) {
118: PetscInt m = A->rmap->n, nz = aa->nz;
119: PetscInt *row, *col;
120: PetscCall(PetscMalloc2(m + 1, &row, nz, &col));
121: for (i = 0; i < m + 1; i++) row[i] = aa->i[i] + 1;
122: for (i = 0; i < nz; i++) col[i] = aa->j[i] + 1;
123: *r = (INT_TYPE *)row;
124: *c = (INT_TYPE *)col;
125: *nnz = (INT_TYPE)nz;
126: *free = PETSC_TRUE;
127: }
128: PetscFunctionReturn(PETSC_SUCCESS);
129: }
131: static PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A, PetscBool sym, MatReuse reuse, PetscBool *free, INT_TYPE *nnz, INT_TYPE **r, INT_TYPE **c, PetscScalar **v)
132: {
133: Mat_SeqBAIJ *aa = (Mat_SeqBAIJ *)A->data;
134: PetscInt bs = A->rmap->bs, i;
136: PetscFunctionBegin;
137: if (!sym) {
138: *v = aa->a;
139: if (bs == 1) { /* already in the correct format */
140: /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */
141: *r = (INT_TYPE *)aa->i;
142: *c = (INT_TYPE *)aa->j;
143: *nnz = (INT_TYPE)aa->nz;
144: *free = PETSC_FALSE;
145: PetscFunctionReturn(PETSC_SUCCESS);
146: } else if (reuse == MAT_INITIAL_MATRIX) {
147: PetscInt m = A->rmap->n, nz = aa->nz;
148: PetscInt *row, *col;
149: PetscCall(PetscMalloc2(m + 1, &row, nz, &col));
150: for (i = 0; i < m + 1; i++) row[i] = aa->i[i] + 1;
151: for (i = 0; i < nz; i++) col[i] = aa->j[i] + 1;
152: *r = (INT_TYPE *)row;
153: *c = (INT_TYPE *)col;
154: *nnz = (INT_TYPE)nz;
155: }
156: *free = PETSC_TRUE;
157: } else {
158: SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "This should not happen");
159: }
160: PetscFunctionReturn(PETSC_SUCCESS);
161: }
163: static PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A, PetscBool sym, MatReuse reuse, PetscBool *free, INT_TYPE *nnz, INT_TYPE **r, INT_TYPE **c, PetscScalar **v)
164: {
165: Mat_SeqAIJ *aa = (Mat_SeqAIJ *)A->data;
166: PetscScalar *aav;
168: PetscFunctionBegin;
169: PetscCall(MatSeqAIJGetArrayRead(A, (const PetscScalar **)&aav));
170: if (!sym) { /* already in the correct format */
171: *v = aav;
172: *r = (INT_TYPE *)aa->i;
173: *c = (INT_TYPE *)aa->j;
174: *nnz = (INT_TYPE)aa->nz;
175: *free = PETSC_FALSE;
176: } else if (reuse == MAT_INITIAL_MATRIX) { /* need to get the triangular part */
177: PetscScalar *vals, *vv;
178: PetscInt *row, *col, *jj;
179: PetscInt m = A->rmap->n, nz, i;
181: nz = 0;
182: for (i = 0; i < m; i++) nz += aa->i[i + 1] - aa->diag[i];
183: PetscCall(PetscMalloc2(m + 1, &row, nz, &col));
184: PetscCall(PetscMalloc1(nz, &vals));
185: jj = col;
186: vv = vals;
188: row[0] = 0;
189: for (i = 0; i < m; i++) {
190: PetscInt *aj = aa->j + aa->diag[i];
191: PetscScalar *av = aav + aa->diag[i];
192: PetscInt rl = aa->i[i + 1] - aa->diag[i], j;
194: for (j = 0; j < rl; j++) {
195: *jj = *aj;
196: jj++;
197: aj++;
198: *vv = *av;
199: vv++;
200: av++;
201: }
202: row[i + 1] = row[i] + rl;
203: }
204: *v = vals;
205: *r = (INT_TYPE *)row;
206: *c = (INT_TYPE *)col;
207: *nnz = (INT_TYPE)nz;
208: *free = PETSC_TRUE;
209: } else {
210: PetscScalar *vv;
211: PetscInt m = A->rmap->n, i;
213: vv = *v;
214: for (i = 0; i < m; i++) {
215: PetscScalar *av = aav + aa->diag[i];
216: PetscInt rl = aa->i[i + 1] - aa->diag[i], j;
217: for (j = 0; j < rl; j++) {
218: *vv = *av;
219: vv++;
220: av++;
221: }
222: }
223: *free = PETSC_TRUE;
224: }
225: PetscCall(MatSeqAIJRestoreArrayRead(A, (const PetscScalar **)&aav));
226: PetscFunctionReturn(PETSC_SUCCESS);
227: }
229: static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X)
230: {
231: Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO *)F->data;
232: Mat S, Xmat, Bmat;
233: MatFactorSchurStatus schurstatus;
235: PetscFunctionBegin;
236: PetscCall(MatFactorGetSchurComplement(F, &S, &schurstatus));
237: PetscCheck(X != B || schurstatus != MAT_FACTOR_SCHUR_INVERTED, PETSC_COMM_SELF, PETSC_ERR_SUP, "X and B cannot point to the same address");
238: PetscCall(MatCreateSeqDense(PETSC_COMM_SELF, mpardiso->schur_size, mpardiso->nrhs, B, &Bmat));
239: PetscCall(MatCreateSeqDense(PETSC_COMM_SELF, mpardiso->schur_size, mpardiso->nrhs, X, &Xmat));
240: PetscCall(MatSetType(Bmat, ((PetscObject)S)->type_name));
241: PetscCall(MatSetType(Xmat, ((PetscObject)S)->type_name));
242: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
243: PetscCall(MatBindToCPU(Xmat, S->boundtocpu));
244: PetscCall(MatBindToCPU(Bmat, S->boundtocpu));
245: #endif
247: #if defined(PETSC_USE_COMPLEX)
248: PetscCheck(mpardiso->iparm[12 - 1] != 1, PetscObjectComm((PetscObject)F), PETSC_ERR_SUP, "Hermitian solve not implemented yet");
249: #endif
251: switch (schurstatus) {
252: case MAT_FACTOR_SCHUR_FACTORED:
253: if (!mpardiso->iparm[12 - 1]) {
254: PetscCall(MatMatSolve(S, Bmat, Xmat));
255: } else { /* transpose solve */
256: PetscCall(MatMatSolveTranspose(S, Bmat, Xmat));
257: }
258: break;
259: case MAT_FACTOR_SCHUR_INVERTED:
260: PetscCall(MatProductCreateWithMat(S, Bmat, NULL, Xmat));
261: if (!mpardiso->iparm[12 - 1]) {
262: PetscCall(MatProductSetType(Xmat, MATPRODUCT_AB));
263: } else { /* transpose solve */
264: PetscCall(MatProductSetType(Xmat, MATPRODUCT_AtB));
265: }
266: PetscCall(MatProductSetFromOptions(Xmat));
267: PetscCall(MatProductSymbolic(Xmat));
268: PetscCall(MatProductNumeric(Xmat));
269: PetscCall(MatProductClear(Xmat));
270: break;
271: default:
272: SETERRQ(PetscObjectComm((PetscObject)F), PETSC_ERR_SUP, "Unhandled MatFactorSchurStatus %" PetscInt_FMT, F->schur_status);
273: break;
274: }
275: PetscCall(MatFactorRestoreSchurComplement(F, &S, schurstatus));
276: PetscCall(MatDestroy(&Bmat));
277: PetscCall(MatDestroy(&Xmat));
278: PetscFunctionReturn(PETSC_SUCCESS);
279: }
281: static PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is)
282: {
283: Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO *)F->data;
284: const PetscScalar *arr;
285: const PetscInt *idxs;
286: PetscInt size, i;
287: PetscMPIInt csize;
288: PetscBool sorted;
290: PetscFunctionBegin;
291: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)F), &csize));
292: PetscCheck(csize <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "MKL PARDISO parallel Schur complements not yet supported from PETSc");
293: PetscCall(ISSorted(is, &sorted));
294: PetscCheck(sorted, PETSC_COMM_SELF, PETSC_ERR_SUP, "IS for MKL PARDISO Schur complements needs to be sorted");
295: PetscCall(ISGetLocalSize(is, &size));
296: PetscCall(PetscFree(mpardiso->schur_work));
297: PetscCall(PetscBLASIntCast(PetscMax(mpardiso->n, 2 * size), &mpardiso->schur_work_size));
298: PetscCall(PetscMalloc1(mpardiso->schur_work_size, &mpardiso->schur_work));
299: PetscCall(MatDestroy(&F->schur));
300: PetscCall(MatCreateSeqDense(PETSC_COMM_SELF, size, size, NULL, &F->schur));
301: PetscCall(MatDenseGetArrayRead(F->schur, &arr));
302: mpardiso->schur = (PetscScalar *)arr;
303: mpardiso->schur_size = size;
304: PetscCall(MatDenseRestoreArrayRead(F->schur, &arr));
305: if (mpardiso->mtype == 2) PetscCall(MatSetOption(F->schur, MAT_SPD, PETSC_TRUE));
307: PetscCall(PetscFree(mpardiso->schur_idxs));
308: PetscCall(PetscMalloc1(size, &mpardiso->schur_idxs));
309: PetscCall(PetscArrayzero(mpardiso->perm, mpardiso->n));
310: PetscCall(ISGetIndices(is, &idxs));
311: PetscCall(PetscArraycpy(mpardiso->schur_idxs, idxs, size));
312: for (i = 0; i < size; i++) mpardiso->perm[idxs[i]] = 1;
313: PetscCall(ISRestoreIndices(is, &idxs));
314: if (size) { /* turn on Schur switch if the set of indices is not empty */
315: mpardiso->iparm[36 - 1] = 2;
316: }
317: PetscFunctionReturn(PETSC_SUCCESS);
318: }
320: static PetscErrorCode MatDestroy_MKL_PARDISO(Mat A)
321: {
322: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
324: PetscFunctionBegin;
325: if (mat_mkl_pardiso->CleanUp) {
326: mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY;
328: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, NULL, NULL, NULL, NULL, &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, NULL, NULL,
329: &mat_mkl_pardiso->err);
330: }
331: PetscCall(PetscFree(mat_mkl_pardiso->perm));
332: PetscCall(PetscFree(mat_mkl_pardiso->schur_work));
333: PetscCall(PetscFree(mat_mkl_pardiso->schur_idxs));
334: if (mat_mkl_pardiso->freeaij) {
335: PetscCall(PetscFree2(mat_mkl_pardiso->ia, mat_mkl_pardiso->ja));
336: if (mat_mkl_pardiso->iparm[34] == 1) PetscCall(PetscFree(mat_mkl_pardiso->a));
337: }
338: PetscCall(PetscFree(A->data));
340: /* clear composed functions */
341: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
342: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorSetSchurIS_C", NULL));
343: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatMkl_PardisoSetCntl_C", NULL));
344: PetscFunctionReturn(PETSC_SUCCESS);
345: }
347: static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce)
348: {
349: PetscFunctionBegin;
350: if (reduce) { /* data given for the whole matrix */
351: PetscInt i, m = 0, p = 0;
352: for (i = 0; i < mpardiso->nrhs; i++) {
353: PetscInt j;
354: for (j = 0; j < mpardiso->schur_size; j++) schur[p + j] = whole[m + mpardiso->schur_idxs[j]];
355: m += mpardiso->n;
356: p += mpardiso->schur_size;
357: }
358: } else { /* from Schur to whole */
359: PetscInt i, m = 0, p = 0;
360: for (i = 0; i < mpardiso->nrhs; i++) {
361: PetscInt j;
362: for (j = 0; j < mpardiso->schur_size; j++) whole[m + mpardiso->schur_idxs[j]] = schur[p + j];
363: m += mpardiso->n;
364: p += mpardiso->schur_size;
365: }
366: }
367: PetscFunctionReturn(PETSC_SUCCESS);
368: }
370: static PetscErrorCode MatSolve_MKL_PARDISO(Mat A, Vec b, Vec x)
371: {
372: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
373: PetscScalar *xarray;
374: const PetscScalar *barray;
376: PetscFunctionBegin;
377: mat_mkl_pardiso->nrhs = 1;
378: PetscCall(VecGetArrayWrite(x, &xarray));
379: PetscCall(VecGetArrayRead(b, &barray));
381: if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
382: else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
384: if (barray == xarray) { /* if the two vectors share the same memory */
385: PetscScalar *work;
386: if (!mat_mkl_pardiso->schur_work) {
387: PetscCall(PetscMalloc1(mat_mkl_pardiso->n, &work));
388: } else {
389: work = mat_mkl_pardiso->schur_work;
390: }
391: mat_mkl_pardiso->iparm[6 - 1] = 1;
392: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, NULL, &mat_mkl_pardiso->nrhs,
393: mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)xarray, (void *)work, &mat_mkl_pardiso->err);
394: if (!mat_mkl_pardiso->schur_work) PetscCall(PetscFree(work));
395: } else {
396: mat_mkl_pardiso->iparm[6 - 1] = 0;
397: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
398: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)barray, (void *)xarray, &mat_mkl_pardiso->err);
399: }
400: PetscCall(VecRestoreArrayRead(b, &barray));
402: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
404: if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
405: if (!mat_mkl_pardiso->solve_interior) {
406: PetscInt shift = mat_mkl_pardiso->schur_size;
408: PetscCall(MatFactorFactorizeSchurComplement(A));
409: /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
410: if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
412: /* solve Schur complement */
413: PetscCall(MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso, xarray, mat_mkl_pardiso->schur_work, PETSC_TRUE));
414: PetscCall(MatMKLPardisoSolveSchur_Private(A, mat_mkl_pardiso->schur_work, mat_mkl_pardiso->schur_work + shift));
415: PetscCall(MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso, xarray, mat_mkl_pardiso->schur_work + shift, PETSC_FALSE));
416: } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */
417: PetscInt i;
418: for (i = 0; i < mat_mkl_pardiso->schur_size; i++) xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
419: }
421: /* expansion phase */
422: mat_mkl_pardiso->iparm[6 - 1] = 1;
423: mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
424: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
425: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)xarray, (void *)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
426: &mat_mkl_pardiso->err);
428: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
429: mat_mkl_pardiso->iparm[6 - 1] = 0;
430: }
431: PetscCall(VecRestoreArrayWrite(x, &xarray));
432: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
433: PetscFunctionReturn(PETSC_SUCCESS);
434: }
436: static PetscErrorCode MatForwardSolve_MKL_PARDISO(Mat A, Vec b, Vec x)
437: {
438: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
439: PetscScalar *xarray;
440: const PetscScalar *barray;
442: PetscFunctionBegin;
443: PetscCheck(!mat_mkl_pardiso->schur, PETSC_COMM_SELF, PETSC_ERR_SUP, "Forward substitution not supported with Schur complement");
445: mat_mkl_pardiso->nrhs = 1;
446: PetscCall(VecGetArrayWrite(x, &xarray));
447: PetscCall(VecGetArrayRead(b, &barray));
449: mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
451: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
452: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)barray, (void *)xarray, &mat_mkl_pardiso->err);
454: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
456: PetscCall(VecRestoreArrayRead(b, &barray));
457: PetscCall(VecRestoreArrayWrite(x, &xarray));
458: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
459: PetscFunctionReturn(PETSC_SUCCESS);
460: }
462: static PetscErrorCode MatBackwardSolve_MKL_PARDISO(Mat A, Vec b, Vec x)
463: {
464: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
465: PetscScalar *xarray;
466: const PetscScalar *barray;
468: PetscFunctionBegin;
469: PetscCheck(!mat_mkl_pardiso->schur, PETSC_COMM_SELF, PETSC_ERR_SUP, "Backward substitution not supported with Schur complement");
471: mat_mkl_pardiso->nrhs = 1;
472: PetscCall(VecGetArrayWrite(x, &xarray));
473: PetscCall(VecGetArrayRead(b, &barray));
475: mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
477: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
478: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)barray, (void *)xarray, &mat_mkl_pardiso->err);
480: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
482: PetscCall(VecRestoreArrayRead(b, &barray));
483: PetscCall(VecRestoreArrayWrite(x, &xarray));
484: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
485: PetscFunctionReturn(PETSC_SUCCESS);
486: }
488: static PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A, Vec b, Vec x)
489: {
490: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
491: PetscInt oiparm12;
493: PetscFunctionBegin;
494: oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
495: mat_mkl_pardiso->iparm[12 - 1] = 2;
496: PetscCall(MatSolve_MKL_PARDISO(A, b, x));
497: mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
498: PetscFunctionReturn(PETSC_SUCCESS);
499: }
501: static PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A, Mat B, Mat X)
502: {
503: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
504: const PetscScalar *barray;
505: PetscScalar *xarray;
506: PetscBool flg;
508: PetscFunctionBegin;
509: PetscCall(PetscObjectBaseTypeCompare((PetscObject)B, MATSEQDENSE, &flg));
510: PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Matrix B must be MATSEQDENSE matrix");
511: if (X != B) {
512: PetscCall(PetscObjectBaseTypeCompare((PetscObject)X, MATSEQDENSE, &flg));
513: PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Matrix X must be MATSEQDENSE matrix");
514: }
516: PetscCall(MatGetSize(B, NULL, (PetscInt *)&mat_mkl_pardiso->nrhs));
518: if (mat_mkl_pardiso->nrhs > 0) {
519: PetscCall(MatDenseGetArrayRead(B, &barray));
520: PetscCall(MatDenseGetArrayWrite(X, &xarray));
522: PetscCheck(barray != xarray, PETSC_COMM_SELF, PETSC_ERR_SUP, "B and X cannot share the same memory location");
523: if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
524: else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
526: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
527: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)barray, (void *)xarray, &mat_mkl_pardiso->err);
528: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
530: PetscCall(MatDenseRestoreArrayRead(B, &barray));
531: if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
532: PetscScalar *o_schur_work = NULL;
534: /* solve Schur complement */
535: if (!mat_mkl_pardiso->solve_interior) {
536: PetscInt shift = mat_mkl_pardiso->schur_size * mat_mkl_pardiso->nrhs, scale;
537: PetscInt mem = mat_mkl_pardiso->n * mat_mkl_pardiso->nrhs;
539: PetscCall(MatFactorFactorizeSchurComplement(A));
540: /* allocate extra memory if it is needed */
541: scale = 1;
542: if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2;
543: mem *= scale;
544: if (mem > mat_mkl_pardiso->schur_work_size) {
545: o_schur_work = mat_mkl_pardiso->schur_work;
546: PetscCall(PetscMalloc1(mem, &mat_mkl_pardiso->schur_work));
547: }
548: /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
549: if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
550: PetscCall(MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso, xarray, mat_mkl_pardiso->schur_work, PETSC_TRUE));
551: PetscCall(MatMKLPardisoSolveSchur_Private(A, mat_mkl_pardiso->schur_work, mat_mkl_pardiso->schur_work + shift));
552: PetscCall(MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso, xarray, mat_mkl_pardiso->schur_work + shift, PETSC_FALSE));
553: } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */
554: PetscInt i, n, m = 0;
555: for (n = 0; n < mat_mkl_pardiso->nrhs; n++) {
556: for (i = 0; i < mat_mkl_pardiso->schur_size; i++) xarray[mat_mkl_pardiso->schur_idxs[i] + m] = 0.;
557: m += mat_mkl_pardiso->n;
558: }
559: }
561: /* expansion phase */
562: mat_mkl_pardiso->iparm[6 - 1] = 1;
563: mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
564: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
565: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, (void *)xarray, (void *)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
566: &mat_mkl_pardiso->err);
567: if (o_schur_work) { /* restore original Schur_work (minimal size) */
568: PetscCall(PetscFree(mat_mkl_pardiso->schur_work));
569: mat_mkl_pardiso->schur_work = o_schur_work;
570: }
571: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
572: mat_mkl_pardiso->iparm[6 - 1] = 0;
573: }
574: PetscCall(MatDenseRestoreArrayWrite(X, &xarray));
575: }
576: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
577: PetscFunctionReturn(PETSC_SUCCESS);
578: }
580: static PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F, Mat A, const MatFactorInfo *info)
581: {
582: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)F->data;
584: PetscFunctionBegin;
585: mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
586: PetscCall((*mat_mkl_pardiso->Convert)(A, mat_mkl_pardiso->needsym, MAT_REUSE_MATRIX, &mat_mkl_pardiso->freeaij, &mat_mkl_pardiso->nz, &mat_mkl_pardiso->ia, &mat_mkl_pardiso->ja, (PetscScalar **)&mat_mkl_pardiso->a));
588: mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
589: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
590: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, NULL, (void *)mat_mkl_pardiso->schur, &mat_mkl_pardiso->err);
591: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
593: /* report flops */
594: if (mat_mkl_pardiso->iparm[18] > 0) PetscCall(PetscLogFlops(PetscPowRealInt(10., 6) * mat_mkl_pardiso->iparm[18]));
596: if (F->schur) { /* schur output from pardiso is in row major format */
597: #if defined(PETSC_HAVE_CUDA)
598: F->schur->offloadmask = PETSC_OFFLOAD_CPU;
599: #endif
600: PetscCall(MatFactorRestoreSchurComplement(F, NULL, MAT_FACTOR_SCHUR_UNFACTORED));
601: PetscCall(MatTranspose(F->schur, MAT_INPLACE_MATRIX, &F->schur));
602: }
603: mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
604: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
605: PetscFunctionReturn(PETSC_SUCCESS);
606: }
608: static PetscErrorCode MatSetFromOptions_MKL_PARDISO(Mat F, Mat A)
609: {
610: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)F->data;
611: PetscInt icntl, bs, threads = 1;
612: PetscBool flg;
614: PetscFunctionBegin;
615: PetscOptionsBegin(PetscObjectComm((PetscObject)F), ((PetscObject)F)->prefix, "MKL_PARDISO Options", "Mat");
617: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_65", "Suggested number of threads to use within MKL PARDISO", "None", threads, &threads, &flg));
618: if (flg) PetscSetMKL_PARDISOThreads((int)threads);
620: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_66", "Maximum number of factors with identical sparsity structure that must be kept in memory at the same time", "None", mat_mkl_pardiso->maxfct, &icntl, &flg));
621: if (flg) mat_mkl_pardiso->maxfct = icntl;
623: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_67", "Indicates the actual matrix for the solution phase", "None", mat_mkl_pardiso->mnum, &icntl, &flg));
624: if (flg) mat_mkl_pardiso->mnum = icntl;
626: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_68", "Message level information", "None", mat_mkl_pardiso->msglvl, &icntl, &flg));
627: if (flg) mat_mkl_pardiso->msglvl = icntl;
629: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_69", "Defines the matrix type", "None", mat_mkl_pardiso->mtype, &icntl, &flg));
630: if (flg) {
631: void *pt[IPARM_SIZE];
632: mat_mkl_pardiso->mtype = icntl;
633: icntl = mat_mkl_pardiso->iparm[34];
634: bs = mat_mkl_pardiso->iparm[36];
635: MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
636: #if defined(PETSC_USE_REAL_SINGLE)
637: mat_mkl_pardiso->iparm[27] = 1;
638: #else
639: mat_mkl_pardiso->iparm[27] = 0;
640: #endif
641: mat_mkl_pardiso->iparm[34] = icntl;
642: mat_mkl_pardiso->iparm[36] = bs;
643: }
645: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_1", "Use default values (if 0)", "None", mat_mkl_pardiso->iparm[0], &icntl, &flg));
646: if (flg) mat_mkl_pardiso->iparm[0] = icntl;
648: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_2", "Fill-in reducing ordering for the input matrix", "None", mat_mkl_pardiso->iparm[1], &icntl, &flg));
649: if (flg) mat_mkl_pardiso->iparm[1] = icntl;
651: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_4", "Preconditioned CGS/CG", "None", mat_mkl_pardiso->iparm[3], &icntl, &flg));
652: if (flg) mat_mkl_pardiso->iparm[3] = icntl;
654: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_5", "User permutation", "None", mat_mkl_pardiso->iparm[4], &icntl, &flg));
655: if (flg) mat_mkl_pardiso->iparm[4] = icntl;
657: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_6", "Write solution on x", "None", mat_mkl_pardiso->iparm[5], &icntl, &flg));
658: if (flg) mat_mkl_pardiso->iparm[5] = icntl;
660: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_8", "Iterative refinement step", "None", mat_mkl_pardiso->iparm[7], &icntl, &flg));
661: if (flg) mat_mkl_pardiso->iparm[7] = icntl;
663: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_10", "Pivoting perturbation", "None", mat_mkl_pardiso->iparm[9], &icntl, &flg));
664: if (flg) mat_mkl_pardiso->iparm[9] = icntl;
666: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_11", "Scaling vectors", "None", mat_mkl_pardiso->iparm[10], &icntl, &flg));
667: if (flg) mat_mkl_pardiso->iparm[10] = icntl;
669: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_12", "Solve with transposed or conjugate transposed matrix A", "None", mat_mkl_pardiso->iparm[11], &icntl, &flg));
670: if (flg) mat_mkl_pardiso->iparm[11] = icntl;
672: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_13", "Improved accuracy using (non-) symmetric weighted matching", "None", mat_mkl_pardiso->iparm[12], &icntl, &flg));
673: if (flg) mat_mkl_pardiso->iparm[12] = icntl;
675: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_18", "Numbers of non-zero elements", "None", mat_mkl_pardiso->iparm[17], &icntl, &flg));
676: if (flg) mat_mkl_pardiso->iparm[17] = icntl;
678: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_19", "Report number of floating point operations (0 to disable)", "None", mat_mkl_pardiso->iparm[18], &icntl, &flg));
679: if (flg) mat_mkl_pardiso->iparm[18] = icntl;
681: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_21", "Pivoting for symmetric indefinite matrices", "None", mat_mkl_pardiso->iparm[20], &icntl, &flg));
682: if (flg) mat_mkl_pardiso->iparm[20] = icntl;
684: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_24", "Parallel factorization control", "None", mat_mkl_pardiso->iparm[23], &icntl, &flg));
685: if (flg) mat_mkl_pardiso->iparm[23] = icntl;
687: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_25", "Parallel forward/backward solve control", "None", mat_mkl_pardiso->iparm[24], &icntl, &flg));
688: if (flg) mat_mkl_pardiso->iparm[24] = icntl;
690: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_27", "Matrix checker", "None", mat_mkl_pardiso->iparm[26], &icntl, &flg));
691: if (flg) mat_mkl_pardiso->iparm[26] = icntl;
693: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_31", "Partial solve and computing selected components of the solution vectors", "None", mat_mkl_pardiso->iparm[30], &icntl, &flg));
694: if (flg) mat_mkl_pardiso->iparm[30] = icntl;
696: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_34", "Optimal number of threads for conditional numerical reproducibility (CNR) mode", "None", mat_mkl_pardiso->iparm[33], &icntl, &flg));
697: if (flg) mat_mkl_pardiso->iparm[33] = icntl;
699: PetscCall(PetscOptionsInt("-mat_mkl_pardiso_60", "Intel MKL PARDISO mode", "None", mat_mkl_pardiso->iparm[59], &icntl, &flg));
700: if (flg) mat_mkl_pardiso->iparm[59] = icntl;
701: PetscOptionsEnd();
702: PetscFunctionReturn(PETSC_SUCCESS);
703: }
705: static PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
706: {
707: PetscInt i, bs;
708: PetscBool match;
710: PetscFunctionBegin;
711: for (i = 0; i < IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0;
712: for (i = 0; i < IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0;
713: #if defined(PETSC_USE_REAL_SINGLE)
714: mat_mkl_pardiso->iparm[27] = 1;
715: #else
716: mat_mkl_pardiso->iparm[27] = 0;
717: #endif
718: /* Default options for both sym and unsym */
719: mat_mkl_pardiso->iparm[0] = 1; /* Solver default parameters overridden with provided by iparm */
720: mat_mkl_pardiso->iparm[1] = 2; /* Metis reordering */
721: mat_mkl_pardiso->iparm[5] = 0; /* Write solution into x */
722: mat_mkl_pardiso->iparm[7] = 0; /* Max number of iterative refinement steps */
723: mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
724: mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
725: #if 0
726: mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/
727: #endif
728: PetscCall(PetscObjectTypeCompareAny((PetscObject)A, &match, MATSEQBAIJ, MATSEQSBAIJ, ""));
729: PetscCall(MatGetBlockSize(A, &bs));
730: if (!match || bs == 1) {
731: mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
732: mat_mkl_pardiso->n = A->rmap->N;
733: } else {
734: mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */
735: mat_mkl_pardiso->iparm[36] = bs;
736: mat_mkl_pardiso->n = A->rmap->N / bs;
737: }
738: mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on rank-0 */
740: mat_mkl_pardiso->CleanUp = PETSC_FALSE;
741: mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */
742: mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */
743: mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */
744: mat_mkl_pardiso->phase = -1;
745: mat_mkl_pardiso->err = 0;
747: mat_mkl_pardiso->nrhs = 1;
748: mat_mkl_pardiso->err = 0;
749: mat_mkl_pardiso->phase = -1;
751: if (ftype == MAT_FACTOR_LU) {
752: mat_mkl_pardiso->iparm[9] = 13; /* Perturb the pivot elements with 1E-13 */
753: mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */
754: mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
755: } else {
756: mat_mkl_pardiso->iparm[9] = 8; /* Perturb the pivot elements with 1E-8 */
757: mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
758: mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
759: #if defined(PETSC_USE_DEBUG)
760: mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
761: #endif
762: }
763: PetscCall(PetscCalloc1(A->rmap->N * sizeof(INT_TYPE), &mat_mkl_pardiso->perm));
764: mat_mkl_pardiso->schur_size = 0;
765: PetscFunctionReturn(PETSC_SUCCESS);
766: }
768: static PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F, Mat A, const MatFactorInfo *info)
769: {
770: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)F->data;
772: PetscFunctionBegin;
773: mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
774: PetscCall(MatSetFromOptions_MKL_PARDISO(F, A));
775: /* throw away any previously computed structure */
776: if (mat_mkl_pardiso->freeaij) {
777: PetscCall(PetscFree2(mat_mkl_pardiso->ia, mat_mkl_pardiso->ja));
778: if (mat_mkl_pardiso->iparm[34] == 1) PetscCall(PetscFree(mat_mkl_pardiso->a));
779: }
780: PetscCall((*mat_mkl_pardiso->Convert)(A, mat_mkl_pardiso->needsym, MAT_INITIAL_MATRIX, &mat_mkl_pardiso->freeaij, &mat_mkl_pardiso->nz, &mat_mkl_pardiso->ia, &mat_mkl_pardiso->ja, (PetscScalar **)&mat_mkl_pardiso->a));
781: if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N;
782: else mat_mkl_pardiso->n = A->rmap->N / A->rmap->bs;
784: mat_mkl_pardiso->phase = JOB_ANALYSIS;
786: /* reset flops counting if requested */
787: if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1;
789: MKL_PARDISO(mat_mkl_pardiso->pt, &mat_mkl_pardiso->maxfct, &mat_mkl_pardiso->mnum, &mat_mkl_pardiso->mtype, &mat_mkl_pardiso->phase, &mat_mkl_pardiso->n, mat_mkl_pardiso->a, mat_mkl_pardiso->ia, mat_mkl_pardiso->ja, mat_mkl_pardiso->perm,
790: &mat_mkl_pardiso->nrhs, mat_mkl_pardiso->iparm, &mat_mkl_pardiso->msglvl, NULL, NULL, &mat_mkl_pardiso->err);
791: PetscCheck(mat_mkl_pardiso->err >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "Error reported by MKL PARDISO: err=%d. Please check manual", mat_mkl_pardiso->err);
793: mat_mkl_pardiso->CleanUp = PETSC_TRUE;
795: if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
796: else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
798: F->ops->solve = MatSolve_MKL_PARDISO;
799: F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO;
800: F->ops->matsolve = MatMatSolve_MKL_PARDISO;
801: if (F->factortype == MAT_FACTOR_LU || (!PetscDefined(USE_COMPLEX) && F->factortype == MAT_FACTOR_CHOLESKY && A->spd == PETSC_BOOL3_TRUE)) {
802: F->ops->backwardsolve = MatBackwardSolve_MKL_PARDISO;
803: F->ops->forwardsolve = MatForwardSolve_MKL_PARDISO;
804: }
805: PetscFunctionReturn(PETSC_SUCCESS);
806: }
808: static PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F, Mat A, IS r, IS c, const MatFactorInfo *info)
809: {
810: PetscFunctionBegin;
811: PetscCall(MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info));
812: PetscFunctionReturn(PETSC_SUCCESS);
813: }
815: #if !defined(PETSC_USE_COMPLEX)
816: static PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F, PetscInt *nneg, PetscInt *nzero, PetscInt *npos)
817: {
818: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)F->data;
820: PetscFunctionBegin;
821: if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
822: if (npos) *npos = mat_mkl_pardiso->iparm[21];
823: if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
824: PetscFunctionReturn(PETSC_SUCCESS);
825: }
826: #endif
828: static PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F, Mat A, IS r, const MatFactorInfo *info)
829: {
830: PetscFunctionBegin;
831: PetscCall(MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info));
832: F->ops->getinertia = NULL;
833: #if !defined(PETSC_USE_COMPLEX)
834: F->ops->getinertia = MatGetInertia_MKL_PARDISO;
835: #endif
836: PetscFunctionReturn(PETSC_SUCCESS);
837: }
839: static PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
840: {
841: PetscBool iascii;
842: PetscViewerFormat format;
843: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
844: PetscInt i;
846: PetscFunctionBegin;
847: if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(PETSC_SUCCESS);
849: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
850: if (iascii) {
851: PetscCall(PetscViewerGetFormat(viewer, &format));
852: if (format == PETSC_VIEWER_ASCII_INFO) {
853: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO run parameters:\n"));
854: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO phase: %d \n", mat_mkl_pardiso->phase));
855: for (i = 1; i <= 64; i++) PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO iparm[%d]: %d \n", i, mat_mkl_pardiso->iparm[i - 1]));
856: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct));
857: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO mnum: %d \n", mat_mkl_pardiso->mnum));
858: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO mtype: %d \n", mat_mkl_pardiso->mtype));
859: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO n: %d \n", mat_mkl_pardiso->n));
860: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs));
861: PetscCall(PetscViewerASCIIPrintf(viewer, "MKL PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl));
862: }
863: }
864: PetscFunctionReturn(PETSC_SUCCESS);
865: }
867: static PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
868: {
869: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)A->data;
871: PetscFunctionBegin;
872: info->block_size = 1.0;
873: info->nz_used = mat_mkl_pardiso->iparm[17];
874: info->nz_allocated = mat_mkl_pardiso->iparm[17];
875: info->nz_unneeded = 0.0;
876: info->assemblies = 0.0;
877: info->mallocs = 0.0;
878: info->memory = 0.0;
879: info->fill_ratio_given = 0;
880: info->fill_ratio_needed = 0;
881: info->factor_mallocs = 0;
882: PetscFunctionReturn(PETSC_SUCCESS);
883: }
885: static PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F, PetscInt icntl, PetscInt ival)
886: {
887: PetscInt backup, bs;
888: Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO *)F->data;
890: PetscFunctionBegin;
891: if (icntl <= 64) {
892: mat_mkl_pardiso->iparm[icntl - 1] = ival;
893: } else {
894: if (icntl == 65) PetscSetMKL_PARDISOThreads(ival);
895: else if (icntl == 66) mat_mkl_pardiso->maxfct = ival;
896: else if (icntl == 67) mat_mkl_pardiso->mnum = ival;
897: else if (icntl == 68) mat_mkl_pardiso->msglvl = ival;
898: else if (icntl == 69) {
899: void *pt[IPARM_SIZE];
900: backup = mat_mkl_pardiso->iparm[34];
901: bs = mat_mkl_pardiso->iparm[36];
902: mat_mkl_pardiso->mtype = ival;
903: MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
904: #if defined(PETSC_USE_REAL_SINGLE)
905: mat_mkl_pardiso->iparm[27] = 1;
906: #else
907: mat_mkl_pardiso->iparm[27] = 0;
908: #endif
909: mat_mkl_pardiso->iparm[34] = backup;
910: mat_mkl_pardiso->iparm[36] = bs;
911: } else if (icntl == 70) mat_mkl_pardiso->solve_interior = (PetscBool) !!ival;
912: }
913: PetscFunctionReturn(PETSC_SUCCESS);
914: }
916: /*@
917: MatMkl_PardisoSetCntl - Set MKL PARDISO <https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2023-2/onemkl-pardiso-parallel-direct-sparse-solver-iface.html> parameters
919: Logically Collective
921: Input Parameters:
922: + F - the factored matrix obtained by calling `MatGetFactor()`
923: . icntl - index of MKL PARDISO parameter
924: - ival - value of MKL PARDISO parameter
926: Options Database Key:
927: . -mat_mkl_pardiso_<icntl> <ival> - change the option numbered icntl to the value ival
929: Level: beginner
931: .seealso: [](ch_matrices), `Mat`, `MATSOLVERMKL_PARDISO`, `MatGetFactor()`
932: @*/
933: PetscErrorCode MatMkl_PardisoSetCntl(Mat F, PetscInt icntl, PetscInt ival)
934: {
935: PetscFunctionBegin;
936: PetscTryMethod(F, "MatMkl_PardisoSetCntl_C", (Mat, PetscInt, PetscInt), (F, icntl, ival));
937: PetscFunctionReturn(PETSC_SUCCESS);
938: }
940: /*MC
941: MATSOLVERMKL_PARDISO - A matrix type providing direct solvers, LU, for
942: `MATSEQAIJ` matrices via the external package MKL PARDISO
943: <https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2024-0/onemkl-pardiso-parallel-direct-sparse-solver-iface.html>.
945: Use `-pc_type lu` `-pc_factor_mat_solver_type mkl_pardiso` to use this direct solver
947: Options Database Keys:
948: + -mat_mkl_pardiso_65 - Suggested number of threads to use within MKL PARDISO
949: . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
950: . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
951: . -mat_mkl_pardiso_68 - Message level information, use 1 to get detailed information on the solver options
952: . -mat_mkl_pardiso_69 - Defines the matrix type. IMPORTANT: When you set this flag, iparm parameters are going to be set to the default ones for the matrix type
953: . -mat_mkl_pardiso_1 - Use default values
954: . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix
955: . -mat_mkl_pardiso_4 - Preconditioned CGS/CG
956: . -mat_mkl_pardiso_5 - User permutation
957: . -mat_mkl_pardiso_6 - Write solution on x
958: . -mat_mkl_pardiso_8 - Iterative refinement step
959: . -mat_mkl_pardiso_10 - Pivoting perturbation
960: . -mat_mkl_pardiso_11 - Scaling vectors
961: . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
962: . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
963: . -mat_mkl_pardiso_18 - Numbers of non-zero elements
964: . -mat_mkl_pardiso_19 - Report number of floating point operations
965: . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
966: . -mat_mkl_pardiso_24 - Parallel factorization control
967: . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
968: . -mat_mkl_pardiso_27 - Matrix checker
969: . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
970: . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
971: - -mat_mkl_pardiso_60 - Intel MKL PARDISO mode
973: Level: beginner
975: Notes:
976: Use `-mat_mkl_pardiso_68 1` to display the number of threads the solver is using. MKL does not provide a way to directly access this
977: information.
979: For more information on the options check the MKL PARDISO manual
981: .seealso: [](ch_matrices), `Mat`, `MATSEQAIJ`, `PCFactorSetMatSolverType()`, `MatSolverType`, `MatMkl_PardisoSetCntl()`, `MATSOLVERMKL_CPARDISO`
982: M*/
983: static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type)
984: {
985: PetscFunctionBegin;
986: *type = MATSOLVERMKL_PARDISO;
987: PetscFunctionReturn(PETSC_SUCCESS);
988: }
990: PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A, MatFactorType ftype, Mat *F)
991: {
992: Mat B;
993: Mat_MKL_PARDISO *mat_mkl_pardiso;
994: PetscBool isSeqAIJ, isSeqBAIJ, isSeqSBAIJ;
996: PetscFunctionBegin;
997: PetscCall(PetscObjectBaseTypeCompare((PetscObject)A, MATSEQAIJ, &isSeqAIJ));
998: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATSEQBAIJ, &isSeqBAIJ));
999: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATSEQSBAIJ, &isSeqSBAIJ));
1000: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
1001: PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N));
1002: PetscCall(PetscStrallocpy("mkl_pardiso", &((PetscObject)B)->type_name));
1003: PetscCall(MatSetUp(B));
1005: PetscCall(PetscNew(&mat_mkl_pardiso));
1006: B->data = mat_mkl_pardiso;
1008: PetscCall(MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso));
1009: if (ftype == MAT_FACTOR_LU) {
1010: B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1011: B->factortype = MAT_FACTOR_LU;
1012: mat_mkl_pardiso->needsym = PETSC_FALSE;
1013: if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1014: else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1015: else {
1016: PetscCheck(!isSeqSBAIJ, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "No support for MKL PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1017: SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "No support for MKL PARDISO LU with %s format", ((PetscObject)A)->type_name);
1018: }
1019: #if defined(PETSC_USE_COMPLEX)
1020: mat_mkl_pardiso->mtype = 13;
1021: #else
1022: mat_mkl_pardiso->mtype = 11;
1023: #endif
1024: } else {
1025: B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1026: B->factortype = MAT_FACTOR_CHOLESKY;
1027: if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1028: else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1029: else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1030: else SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "No support for PARDISO CHOLESKY with %s format", ((PetscObject)A)->type_name);
1032: mat_mkl_pardiso->needsym = PETSC_TRUE;
1033: #if !defined(PETSC_USE_COMPLEX)
1034: if (A->spd == PETSC_BOOL3_TRUE) mat_mkl_pardiso->mtype = 2;
1035: else mat_mkl_pardiso->mtype = -2;
1036: #else
1037: mat_mkl_pardiso->mtype = 6;
1038: PetscCheck(A->hermitian != PETSC_BOOL3_TRUE, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "No support for MKL PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead");
1039: #endif
1040: }
1041: B->ops->destroy = MatDestroy_MKL_PARDISO;
1042: B->ops->view = MatView_MKL_PARDISO;
1043: B->ops->getinfo = MatGetInfo_MKL_PARDISO;
1044: B->factortype = ftype;
1045: B->assembled = PETSC_TRUE;
1047: PetscCall(PetscFree(B->solvertype));
1048: PetscCall(PetscStrallocpy(MATSOLVERMKL_PARDISO, &B->solvertype));
1050: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatFactorGetSolverType_C", MatFactorGetSolverType_mkl_pardiso));
1051: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatFactorSetSchurIS_C", MatFactorSetSchurIS_MKL_PARDISO));
1052: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMkl_PardisoSetCntl_C", MatMkl_PardisoSetCntl_MKL_PARDISO));
1054: *F = B;
1055: PetscFunctionReturn(PETSC_SUCCESS);
1056: }
1058: PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void)
1059: {
1060: PetscFunctionBegin;
1061: PetscCall(MatSolverTypeRegister(MATSOLVERMKL_PARDISO, MATSEQAIJ, MAT_FACTOR_LU, MatGetFactor_aij_mkl_pardiso));
1062: PetscCall(MatSolverTypeRegister(MATSOLVERMKL_PARDISO, MATSEQAIJ, MAT_FACTOR_CHOLESKY, MatGetFactor_aij_mkl_pardiso));
1063: PetscCall(MatSolverTypeRegister(MATSOLVERMKL_PARDISO, MATSEQBAIJ, MAT_FACTOR_LU, MatGetFactor_aij_mkl_pardiso));
1064: PetscCall(MatSolverTypeRegister(MATSOLVERMKL_PARDISO, MATSEQSBAIJ, MAT_FACTOR_CHOLESKY, MatGetFactor_aij_mkl_pardiso));
1065: PetscFunctionReturn(PETSC_SUCCESS);
1066: }