xref: /petsc/src/mat/impls/aij/seq/mkl_pardiso/mkl_pardiso.c (revision 117ef88edefbfc12e7c19efe87a19a2e1b0acd4f)
1 #include <../src/mat/impls/aij/seq/aij.h>        /*I "petscmat.h" I*/
2 #include <../src/mat/impls/sbaij/seq/sbaij.h>
3 #include <../src/mat/impls/dense/seq/dense.h>
4 
5 #if defined(PETSC_HAVE_MKL_INTEL_ILP64)
6 #define MKL_ILP64
7 #endif
8 #include <mkl_pardiso.h>
9 
10 PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int);
11 
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
27 
28 #define IPARM_SIZE 64
29 
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;
44 
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
55 
56 
57 /*
58  *  Internal data structure.
59  *  For more information check mkl_pardiso manual.
60  */
61 typedef struct {
62 
63   /* Configuration vector*/
64   INT_TYPE     iparm[IPARM_SIZE];
65 
66   /*
67    * Internal mkl_pardiso memory location.
68    * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak.
69    */
70   void         *pt[IPARM_SIZE];
71 
72   /* Basic mkl_pardiso info*/
73   INT_TYPE     phase, maxfct, mnum, mtype, n, nrhs, msglvl, err;
74 
75   /* Matrix structure*/
76   void         *a;
77   INT_TYPE     *ia, *ja;
78 
79   /* Number of non-zero elements*/
80   INT_TYPE     nz;
81 
82   /* Row permutaton vector*/
83   INT_TYPE     *perm;
84 
85   /* Define if matrix preserves sparse structure.*/
86   MatStructure matstruc;
87 
88   PetscBool    needsym;
89   PetscBool    freeaij;
90 
91   /* Schur complement */
92   PetscScalar  *schur;
93   PetscInt     schur_size;
94   PetscInt     *schur_idxs;
95   PetscScalar  *schur_work;
96   PetscBLASInt schur_work_size;
97   PetscBool    solve_interior;
98 
99   /* True if mkl_pardiso function have been used.*/
100   PetscBool CleanUp;
101 
102   /* Conversion to a format suitable for MKL */
103   PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool*, INT_TYPE*, INT_TYPE**, INT_TYPE**, PetscScalar**);
104 } Mat_MKL_PARDISO;
105 
106 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
107 {
108   Mat_SeqSBAIJ   *aa = (Mat_SeqSBAIJ*)A->data;
109   PetscInt       bs  = A->rmap->bs,i;
110   PetscErrorCode ierr;
111 
112   PetscFunctionBegin;
113   if (!sym) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen");
114   *v      = aa->a;
115   if (bs == 1) { /* already in the correct format */
116     /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */
117     *r    = (INT_TYPE*)aa->i;
118     *c    = (INT_TYPE*)aa->j;
119     *nnz  = (INT_TYPE)aa->nz;
120     *free = PETSC_FALSE;
121   } else if (reuse == MAT_INITIAL_MATRIX) {
122     PetscInt m = A->rmap->n,nz = aa->nz;
123     PetscInt *row,*col;
124     ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr);
125     for (i=0; i<m+1; i++) {
126       row[i] = aa->i[i]+1;
127     }
128     for (i=0; i<nz; i++) {
129       col[i] = aa->j[i]+1;
130     }
131     *r    = (INT_TYPE*)row;
132     *c    = (INT_TYPE*)col;
133     *nnz  = (INT_TYPE)nz;
134     *free = PETSC_TRUE;
135   }
136   PetscFunctionReturn(0);
137 }
138 
139 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
140 {
141   Mat_SeqBAIJ    *aa = (Mat_SeqBAIJ*)A->data;
142   PetscInt       bs  = A->rmap->bs,i;
143   PetscErrorCode ierr;
144 
145   PetscFunctionBegin;
146   if (!sym) {
147     *v      = aa->a;
148     if (bs == 1) { /* already in the correct format */
149       /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */
150       *r    = (INT_TYPE*)aa->i;
151       *c    = (INT_TYPE*)aa->j;
152       *nnz  = (INT_TYPE)aa->nz;
153       *free = PETSC_FALSE;
154       PetscFunctionReturn(0);
155     } else if (reuse == MAT_INITIAL_MATRIX) {
156       PetscInt m = A->rmap->n,nz = aa->nz;
157       PetscInt *row,*col;
158       ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr);
159       for (i=0; i<m+1; i++) {
160         row[i] = aa->i[i]+1;
161       }
162       for (i=0; i<nz; i++) {
163         col[i] = aa->j[i]+1;
164       }
165       *r    = (INT_TYPE*)row;
166       *c    = (INT_TYPE*)col;
167       *nnz  = (INT_TYPE)nz;
168     }
169     *free = PETSC_TRUE;
170   } else {
171     SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen");
172   }
173   PetscFunctionReturn(0);
174 }
175 
176 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
177 {
178   Mat_SeqAIJ     *aa = (Mat_SeqAIJ*)A->data;
179   PetscScalar    *aav;
180   PetscErrorCode ierr;
181 
182   PetscFunctionBegin;
183   ierr = MatSeqAIJGetArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr);
184   if (!sym) { /* already in the correct format */
185     *v    = aav;
186     *r    = (INT_TYPE*)aa->i;
187     *c    = (INT_TYPE*)aa->j;
188     *nnz  = (INT_TYPE)aa->nz;
189     *free = PETSC_FALSE;
190   } else if (reuse == MAT_INITIAL_MATRIX) { /* need to get the triangular part */
191     PetscScalar *vals,*vv;
192     PetscInt    *row,*col,*jj;
193     PetscInt    m = A->rmap->n,nz,i;
194 
195     nz = 0;
196     for (i=0; i<m; i++) nz += aa->i[i+1] - aa->diag[i];
197     ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr);
198     ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr);
199     jj = col;
200     vv = vals;
201 
202     row[0] = 0;
203     for (i=0; i<m; i++) {
204       PetscInt    *aj = aa->j + aa->diag[i];
205       PetscScalar *av = aav + aa->diag[i];
206       PetscInt    rl  = aa->i[i+1] - aa->diag[i],j;
207 
208       for (j=0; j<rl; j++) {
209         *jj = *aj; jj++; aj++;
210         *vv = *av; vv++; av++;
211       }
212       row[i+1] = row[i] + rl;
213     }
214     *v    = vals;
215     *r    = (INT_TYPE*)row;
216     *c    = (INT_TYPE*)col;
217     *nnz  = (INT_TYPE)nz;
218     *free = PETSC_TRUE;
219   } else {
220     PetscScalar *vv;
221     PetscInt    m = A->rmap->n,i;
222 
223     vv = *v;
224     for (i=0; i<m; i++) {
225       PetscScalar *av = aav + aa->diag[i];
226       PetscInt    rl  = aa->i[i+1] - aa->diag[i],j;
227       for (j=0; j<rl; j++) {
228         *vv = *av; vv++; av++;
229       }
230     }
231     *free = PETSC_TRUE;
232   }
233   ierr = MatSeqAIJRestoreArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr);
234   PetscFunctionReturn(0);
235 }
236 
237 
238 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X)
239 {
240   Mat_MKL_PARDISO      *mpardiso = (Mat_MKL_PARDISO*)F->data;
241   Mat                  S,Xmat,Bmat;
242   MatFactorSchurStatus schurstatus;
243   PetscErrorCode       ierr;
244 
245   PetscFunctionBegin;
246   ierr = MatFactorFactorizeSchurComplement(F);CHKERRQ(ierr);
247   ierr = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr);
248   if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address");
249   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr);
250   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr);
251   ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr);
252   ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr);
253 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
254   ierr = MatBindToCPU(Xmat,S->boundtocpu);CHKERRQ(ierr);
255   ierr = MatBindToCPU(Bmat,S->boundtocpu);CHKERRQ(ierr);
256 #endif
257 
258 #if defined(PETSC_USE_COMPLEX)
259   if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet");
260 #endif
261 
262   switch (schurstatus) {
263   case MAT_FACTOR_SCHUR_FACTORED:
264     if (!mpardiso->iparm[12-1]) {
265       ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr);
266     } else { /* transpose solve */
267       ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr);
268     }
269     break;
270   case MAT_FACTOR_SCHUR_INVERTED:
271     ierr = MatProductCreateWithMat(S,Bmat,NULL,Xmat);CHKERRQ(ierr);
272     if (!mpardiso->iparm[12-1]) {
273       ierr = MatProductSetType(Xmat,MATPRODUCT_AB);CHKERRQ(ierr);
274     } else { /* transpose solve */
275       ierr = MatProductSetType(Xmat,MATPRODUCT_AtB);CHKERRQ(ierr);
276     }
277     ierr = MatProductSetFromOptions(Xmat);CHKERRQ(ierr);
278     ierr = MatProductSymbolic(Xmat);CHKERRQ(ierr);
279     ierr = MatProductNumeric(Xmat);CHKERRQ(ierr);
280     ierr = MatProductClear(Xmat);CHKERRQ(ierr);
281     break;
282   default:
283     SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status);
284     break;
285   }
286   ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr);
287   ierr = MatDestroy(&Bmat);CHKERRQ(ierr);
288   ierr = MatDestroy(&Xmat);CHKERRQ(ierr);
289   PetscFunctionReturn(0);
290 }
291 
292 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is)
293 {
294   Mat_MKL_PARDISO   *mpardiso = (Mat_MKL_PARDISO*)F->data;
295   const PetscScalar *arr;
296   const PetscInt    *idxs;
297   PetscInt          size,i;
298   PetscMPIInt       csize;
299   PetscBool         sorted;
300   PetscErrorCode    ierr;
301 
302   PetscFunctionBegin;
303   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr);
304   if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc");
305   ierr = ISSorted(is,&sorted);CHKERRQ(ierr);
306   if (!sorted) {
307     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted");
308   }
309   ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr);
310   ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr);
311   ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr);
312   ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr);
313   ierr = MatDestroy(&F->schur);CHKERRQ(ierr);
314   ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr);
315   ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr);
316   mpardiso->schur      = (PetscScalar*)arr;
317   mpardiso->schur_size = size;
318   ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr);
319   if (mpardiso->mtype == 2) {
320     ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr);
321   }
322 
323   ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr);
324   ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr);
325   ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr);
326   ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr);
327   ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr);
328   for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1;
329   ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr);
330   if (size) { /* turn on Schur switch if the set of indices is not empty */
331     mpardiso->iparm[36-1] = 2;
332   }
333   PetscFunctionReturn(0);
334 }
335 
336 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A)
337 {
338   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
339   PetscErrorCode  ierr;
340 
341   PetscFunctionBegin;
342   if (mat_mkl_pardiso->CleanUp) {
343     mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY;
344 
345     MKL_PARDISO (mat_mkl_pardiso->pt,
346       &mat_mkl_pardiso->maxfct,
347       &mat_mkl_pardiso->mnum,
348       &mat_mkl_pardiso->mtype,
349       &mat_mkl_pardiso->phase,
350       &mat_mkl_pardiso->n,
351       NULL,
352       NULL,
353       NULL,
354       NULL,
355       &mat_mkl_pardiso->nrhs,
356       mat_mkl_pardiso->iparm,
357       &mat_mkl_pardiso->msglvl,
358       NULL,
359       NULL,
360       &mat_mkl_pardiso->err);
361   }
362   ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr);
363   ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
364   ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr);
365   if (mat_mkl_pardiso->freeaij) {
366     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
367     if (mat_mkl_pardiso->iparm[34] == 1) {
368       ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
369     }
370   }
371   ierr = PetscFree(A->data);CHKERRQ(ierr);
372 
373   /* clear composed functions */
374   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr);
375   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr);
376   ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr);
377   PetscFunctionReturn(0);
378 }
379 
380 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce)
381 {
382   PetscFunctionBegin;
383   if (reduce) { /* data given for the whole matrix */
384     PetscInt i,m=0,p=0;
385     for (i=0;i<mpardiso->nrhs;i++) {
386       PetscInt j;
387       for (j=0;j<mpardiso->schur_size;j++) {
388         schur[p+j] = whole[m+mpardiso->schur_idxs[j]];
389       }
390       m += mpardiso->n;
391       p += mpardiso->schur_size;
392     }
393   } else { /* from Schur to whole */
394     PetscInt i,m=0,p=0;
395     for (i=0;i<mpardiso->nrhs;i++) {
396       PetscInt j;
397       for (j=0;j<mpardiso->schur_size;j++) {
398         whole[m+mpardiso->schur_idxs[j]] = schur[p+j];
399       }
400       m += mpardiso->n;
401       p += mpardiso->schur_size;
402     }
403   }
404   PetscFunctionReturn(0);
405 }
406 
407 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x)
408 {
409   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
410   PetscErrorCode    ierr;
411   PetscScalar       *xarray;
412   const PetscScalar *barray;
413 
414   PetscFunctionBegin;
415   mat_mkl_pardiso->nrhs = 1;
416   ierr = VecGetArray(x,&xarray);CHKERRQ(ierr);
417   ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr);
418 
419   if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
420   else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
421 
422   if (barray == xarray) { /* if the two vectors share the same memory */
423     PetscScalar *work;
424     if (!mat_mkl_pardiso->schur_work) {
425       ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr);
426     } else {
427       work = mat_mkl_pardiso->schur_work;
428     }
429     mat_mkl_pardiso->iparm[6-1] = 1;
430     MKL_PARDISO (mat_mkl_pardiso->pt,
431       &mat_mkl_pardiso->maxfct,
432       &mat_mkl_pardiso->mnum,
433       &mat_mkl_pardiso->mtype,
434       &mat_mkl_pardiso->phase,
435       &mat_mkl_pardiso->n,
436       mat_mkl_pardiso->a,
437       mat_mkl_pardiso->ia,
438       mat_mkl_pardiso->ja,
439       NULL,
440       &mat_mkl_pardiso->nrhs,
441       mat_mkl_pardiso->iparm,
442       &mat_mkl_pardiso->msglvl,
443       (void*)xarray,
444       (void*)work,
445       &mat_mkl_pardiso->err);
446     if (!mat_mkl_pardiso->schur_work) {
447       ierr = PetscFree(work);CHKERRQ(ierr);
448     }
449   } else {
450     mat_mkl_pardiso->iparm[6-1] = 0;
451     MKL_PARDISO (mat_mkl_pardiso->pt,
452       &mat_mkl_pardiso->maxfct,
453       &mat_mkl_pardiso->mnum,
454       &mat_mkl_pardiso->mtype,
455       &mat_mkl_pardiso->phase,
456       &mat_mkl_pardiso->n,
457       mat_mkl_pardiso->a,
458       mat_mkl_pardiso->ia,
459       mat_mkl_pardiso->ja,
460       mat_mkl_pardiso->perm,
461       &mat_mkl_pardiso->nrhs,
462       mat_mkl_pardiso->iparm,
463       &mat_mkl_pardiso->msglvl,
464       (void*)barray,
465       (void*)xarray,
466       &mat_mkl_pardiso->err);
467   }
468   ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr);
469 
470   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
471 
472   if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
473     PetscInt shift = mat_mkl_pardiso->schur_size;
474 
475     /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
476     if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
477 
478     if (!mat_mkl_pardiso->solve_interior) {
479       /* solve Schur complement */
480       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
481       ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
482       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
483     } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */
484       PetscInt i;
485       for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
486         xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
487       }
488     }
489 
490     /* expansion phase */
491     mat_mkl_pardiso->iparm[6-1] = 1;
492     mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
493     MKL_PARDISO (mat_mkl_pardiso->pt,
494       &mat_mkl_pardiso->maxfct,
495       &mat_mkl_pardiso->mnum,
496       &mat_mkl_pardiso->mtype,
497       &mat_mkl_pardiso->phase,
498       &mat_mkl_pardiso->n,
499       mat_mkl_pardiso->a,
500       mat_mkl_pardiso->ia,
501       mat_mkl_pardiso->ja,
502       mat_mkl_pardiso->perm,
503       &mat_mkl_pardiso->nrhs,
504       mat_mkl_pardiso->iparm,
505       &mat_mkl_pardiso->msglvl,
506       (void*)xarray,
507       (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
508       &mat_mkl_pardiso->err);
509 
510     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
511     mat_mkl_pardiso->iparm[6-1] = 0;
512   }
513   ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr);
514   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
515   PetscFunctionReturn(0);
516 }
517 
518 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x)
519 {
520   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
521   PetscInt        oiparm12;
522   PetscErrorCode  ierr;
523 
524   PetscFunctionBegin;
525   oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
526   mat_mkl_pardiso->iparm[12 - 1] = 2;
527   ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr);
528   mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
529   PetscFunctionReturn(0);
530 }
531 
532 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X)
533 {
534   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
535   PetscErrorCode    ierr;
536   const PetscScalar *barray;
537   PetscScalar       *xarray;
538   PetscBool         flg;
539 
540   PetscFunctionBegin;
541   ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr);
542   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix");
543   if (X != B) {
544     ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr);
545     if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix");
546   }
547 
548   ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
549 
550   if (mat_mkl_pardiso->nrhs > 0) {
551     ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr);
552     ierr = MatDenseGetArray(X,&xarray);CHKERRQ(ierr);
553 
554     if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location");
555     if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
556     else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
557 
558     MKL_PARDISO (mat_mkl_pardiso->pt,
559       &mat_mkl_pardiso->maxfct,
560       &mat_mkl_pardiso->mnum,
561       &mat_mkl_pardiso->mtype,
562       &mat_mkl_pardiso->phase,
563       &mat_mkl_pardiso->n,
564       mat_mkl_pardiso->a,
565       mat_mkl_pardiso->ia,
566       mat_mkl_pardiso->ja,
567       mat_mkl_pardiso->perm,
568       &mat_mkl_pardiso->nrhs,
569       mat_mkl_pardiso->iparm,
570       &mat_mkl_pardiso->msglvl,
571       (void*)barray,
572       (void*)xarray,
573       &mat_mkl_pardiso->err);
574     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
575 
576     ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr);
577     if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
578       PetscScalar *o_schur_work = NULL;
579       PetscInt    shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale;
580       PetscInt    mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs;
581 
582       /* allocate extra memory if it is needed */
583       scale = 1;
584       if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2;
585 
586       mem *= scale;
587       if (mem > mat_mkl_pardiso->schur_work_size) {
588         o_schur_work = mat_mkl_pardiso->schur_work;
589         ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
590       }
591 
592       /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
593       if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
594 
595       /* solve Schur complement */
596       if (!mat_mkl_pardiso->solve_interior) {
597         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
598         ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
599         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
600       } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */
601         PetscInt i,n,m=0;
602         for (n=0;n<mat_mkl_pardiso->nrhs;n++) {
603           for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
604             xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.;
605           }
606           m += mat_mkl_pardiso->n;
607         }
608       }
609 
610       /* expansion phase */
611       mat_mkl_pardiso->iparm[6-1] = 1;
612       mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
613       MKL_PARDISO (mat_mkl_pardiso->pt,
614         &mat_mkl_pardiso->maxfct,
615         &mat_mkl_pardiso->mnum,
616         &mat_mkl_pardiso->mtype,
617         &mat_mkl_pardiso->phase,
618         &mat_mkl_pardiso->n,
619         mat_mkl_pardiso->a,
620         mat_mkl_pardiso->ia,
621         mat_mkl_pardiso->ja,
622         mat_mkl_pardiso->perm,
623         &mat_mkl_pardiso->nrhs,
624         mat_mkl_pardiso->iparm,
625         &mat_mkl_pardiso->msglvl,
626         (void*)xarray,
627         (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
628         &mat_mkl_pardiso->err);
629       if (o_schur_work) { /* restore original schur_work (minimal size) */
630         ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
631         mat_mkl_pardiso->schur_work = o_schur_work;
632       }
633       if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
634       mat_mkl_pardiso->iparm[6-1] = 0;
635     }
636   }
637   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
638   PetscFunctionReturn(0);
639 }
640 
641 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info)
642 {
643   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data;
644   PetscErrorCode  ierr;
645 
646   PetscFunctionBegin;
647   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
648   ierr = (*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);CHKERRQ(ierr);
649 
650   mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
651   MKL_PARDISO (mat_mkl_pardiso->pt,
652     &mat_mkl_pardiso->maxfct,
653     &mat_mkl_pardiso->mnum,
654     &mat_mkl_pardiso->mtype,
655     &mat_mkl_pardiso->phase,
656     &mat_mkl_pardiso->n,
657     mat_mkl_pardiso->a,
658     mat_mkl_pardiso->ia,
659     mat_mkl_pardiso->ja,
660     mat_mkl_pardiso->perm,
661     &mat_mkl_pardiso->nrhs,
662     mat_mkl_pardiso->iparm,
663     &mat_mkl_pardiso->msglvl,
664     NULL,
665     (void*)mat_mkl_pardiso->schur,
666     &mat_mkl_pardiso->err);
667   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
668 
669   /* report flops */
670   if (mat_mkl_pardiso->iparm[18] > 0) {
671     ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr);
672   }
673 
674   if (F->schur) { /* schur output from pardiso is in row major format */
675 #if defined(PETSC_HAVE_CUDA)
676     F->schur->offloadmask = PETSC_OFFLOAD_CPU;
677 #endif
678     ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr);
679     ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr);
680   }
681   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
682   mat_mkl_pardiso->CleanUp  = PETSC_TRUE;
683   PetscFunctionReturn(0);
684 }
685 
686 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A)
687 {
688   Mat_MKL_PARDISO     *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
689   PetscErrorCode      ierr;
690   PetscInt            icntl,bs,threads=1;
691   PetscBool           flg;
692 
693   PetscFunctionBegin;
694   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr);
695 
696   ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr);
697   if (flg) PetscSetMKL_PARDISOThreads((int)threads);
698 
699   ierr = 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);CHKERRQ(ierr);
700   if (flg) mat_mkl_pardiso->maxfct = icntl;
701 
702   ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr);
703   if (flg) mat_mkl_pardiso->mnum = icntl;
704 
705   ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr);
706   if (flg) mat_mkl_pardiso->msglvl = icntl;
707 
708   ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr);
709   if (flg) {
710     void *pt[IPARM_SIZE];
711     mat_mkl_pardiso->mtype = icntl;
712     icntl = mat_mkl_pardiso->iparm[34];
713     bs = mat_mkl_pardiso->iparm[36];
714     MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
715 #if defined(PETSC_USE_REAL_SINGLE)
716     mat_mkl_pardiso->iparm[27] = 1;
717 #else
718     mat_mkl_pardiso->iparm[27] = 0;
719 #endif
720     mat_mkl_pardiso->iparm[34] = icntl;
721     mat_mkl_pardiso->iparm[36] = bs;
722   }
723   ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr);
724 
725   if (flg && icntl != 0) {
726     ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr);
727     if (flg) mat_mkl_pardiso->iparm[1] = icntl;
728 
729     ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr);
730     if (flg) mat_mkl_pardiso->iparm[3] = icntl;
731 
732     ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr);
733     if (flg) mat_mkl_pardiso->iparm[4] = icntl;
734 
735     ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr);
736     if (flg) mat_mkl_pardiso->iparm[5] = icntl;
737 
738     ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr);
739     if (flg) mat_mkl_pardiso->iparm[7] = icntl;
740 
741     ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr);
742     if (flg) mat_mkl_pardiso->iparm[9] = icntl;
743 
744     ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr);
745     if (flg) mat_mkl_pardiso->iparm[10] = icntl;
746 
747     ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr);
748     if (flg) mat_mkl_pardiso->iparm[11] = icntl;
749 
750     ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr);
751     if (flg) mat_mkl_pardiso->iparm[12] = icntl;
752 
753     ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr);
754     if (flg) mat_mkl_pardiso->iparm[17] = icntl;
755 
756     ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations (0 to disable)","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr);
757     if (flg) mat_mkl_pardiso->iparm[18] = icntl;
758 
759     ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr);
760     if (flg) mat_mkl_pardiso->iparm[20] = icntl;
761 
762     ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr);
763     if (flg) mat_mkl_pardiso->iparm[23] = icntl;
764 
765     ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr);
766     if (flg) mat_mkl_pardiso->iparm[24] = icntl;
767 
768     ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr);
769     if (flg) mat_mkl_pardiso->iparm[26] = icntl;
770 
771     ierr = PetscOptionsInt("-mat_mkl_pardiso_31","Partial solve and computing selected components of the solution vectors","None",mat_mkl_pardiso->iparm[30],&icntl,&flg);CHKERRQ(ierr);
772     if (flg) mat_mkl_pardiso->iparm[30] = icntl;
773 
774     ierr = PetscOptionsInt("-mat_mkl_pardiso_34","Optimal number of threads for conditional numerical reproducibility (CNR) mode","None",mat_mkl_pardiso->iparm[33],&icntl,&flg);CHKERRQ(ierr);
775     if (flg) mat_mkl_pardiso->iparm[33] = icntl;
776 
777     ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr);
778     if (flg) mat_mkl_pardiso->iparm[59] = icntl;
779   }
780   PetscOptionsEnd();
781   PetscFunctionReturn(0);
782 }
783 
784 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
785 {
786   PetscErrorCode ierr;
787   PetscInt       i,bs;
788   PetscBool      match;
789 
790   PetscFunctionBegin;
791   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0;
792   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0;
793 #if defined(PETSC_USE_REAL_SINGLE)
794   mat_mkl_pardiso->iparm[27] = 1;
795 #else
796   mat_mkl_pardiso->iparm[27] = 0;
797 #endif
798   /* Default options for both sym and unsym */
799   mat_mkl_pardiso->iparm[ 0] =  1; /* Solver default parameters overriden with provided by iparm */
800   mat_mkl_pardiso->iparm[ 1] =  2; /* Metis reordering */
801   mat_mkl_pardiso->iparm[ 5] =  0; /* Write solution into x */
802   mat_mkl_pardiso->iparm[ 7] =  0; /* Max number of iterative refinement steps */
803   mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
804   mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
805 #if 0
806   mat_mkl_pardiso->iparm[23] =  1; /* Parallel factorization control*/
807 #endif
808   ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr);
809   ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr);
810   if (!match || bs == 1) {
811     mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
812     mat_mkl_pardiso->n         = A->rmap->N;
813   } else {
814     mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */
815     mat_mkl_pardiso->iparm[36] = bs;
816     mat_mkl_pardiso->n         = A->rmap->N/bs;
817   }
818   mat_mkl_pardiso->iparm[39] =  0; /* Input: matrix/rhs/solution stored on master */
819 
820   mat_mkl_pardiso->CleanUp   = PETSC_FALSE;
821   mat_mkl_pardiso->maxfct    = 1; /* Maximum number of numerical factorizations. */
822   mat_mkl_pardiso->mnum      = 1; /* Which factorization to use. */
823   mat_mkl_pardiso->msglvl    = 0; /* 0: do not print 1: Print statistical information in file */
824   mat_mkl_pardiso->phase     = -1;
825   mat_mkl_pardiso->err       = 0;
826 
827   mat_mkl_pardiso->nrhs      = 1;
828   mat_mkl_pardiso->err       = 0;
829   mat_mkl_pardiso->phase     = -1;
830 
831   if (ftype == MAT_FACTOR_LU) {
832     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
833     mat_mkl_pardiso->iparm[10] =  1; /* Use nonsymmetric permutation and scaling MPS */
834     mat_mkl_pardiso->iparm[12] =  1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
835   } else {
836     mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */
837     mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
838     mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
839 #if defined(PETSC_USE_DEBUG)
840     mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
841 #endif
842   }
843   ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr);
844   for (i=0; i<A->rmap->N; i++) {
845     mat_mkl_pardiso->perm[i] = 0;
846   }
847   mat_mkl_pardiso->schur_size = 0;
848   PetscFunctionReturn(0);
849 }
850 
851 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info)
852 {
853   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
854   PetscErrorCode  ierr;
855 
856   PetscFunctionBegin;
857   mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
858   ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr);
859 
860   /* throw away any previously computed structure */
861   if (mat_mkl_pardiso->freeaij) {
862     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
863     if (mat_mkl_pardiso->iparm[34] == 1) {
864       ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
865     }
866   }
867   ierr = (*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);CHKERRQ(ierr);
868   if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N;
869   else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs;
870 
871   mat_mkl_pardiso->phase = JOB_ANALYSIS;
872 
873   /* reset flops counting if requested */
874   if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1;
875 
876   MKL_PARDISO (mat_mkl_pardiso->pt,
877     &mat_mkl_pardiso->maxfct,
878     &mat_mkl_pardiso->mnum,
879     &mat_mkl_pardiso->mtype,
880     &mat_mkl_pardiso->phase,
881     &mat_mkl_pardiso->n,
882     mat_mkl_pardiso->a,
883     mat_mkl_pardiso->ia,
884     mat_mkl_pardiso->ja,
885     mat_mkl_pardiso->perm,
886     &mat_mkl_pardiso->nrhs,
887     mat_mkl_pardiso->iparm,
888     &mat_mkl_pardiso->msglvl,
889     NULL,
890     NULL,
891     &mat_mkl_pardiso->err);
892   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
893 
894   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
895 
896   if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
897   else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
898 
899   F->ops->solve           = MatSolve_MKL_PARDISO;
900   F->ops->solvetranspose  = MatSolveTranspose_MKL_PARDISO;
901   F->ops->matsolve        = MatMatSolve_MKL_PARDISO;
902   PetscFunctionReturn(0);
903 }
904 
905 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
906 {
907   PetscErrorCode ierr;
908 
909   PetscFunctionBegin;
910   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
911   PetscFunctionReturn(0);
912 }
913 
914 #if !defined(PETSC_USE_COMPLEX)
915 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos)
916 {
917   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data;
918 
919   PetscFunctionBegin;
920   if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
921   if (npos) *npos = mat_mkl_pardiso->iparm[21];
922   if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
923   PetscFunctionReturn(0);
924 }
925 #endif
926 
927 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info)
928 {
929   PetscErrorCode ierr;
930 
931   PetscFunctionBegin;
932   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
933 #if defined(PETSC_USE_COMPLEX)
934   F->ops->getinertia = NULL;
935 #else
936   F->ops->getinertia = MatGetInertia_MKL_PARDISO;
937 #endif
938   PetscFunctionReturn(0);
939 }
940 
941 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
942 {
943   PetscErrorCode    ierr;
944   PetscBool         iascii;
945   PetscViewerFormat format;
946   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
947   PetscInt          i;
948 
949   PetscFunctionBegin;
950   if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0);
951 
952   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
953   if (iascii) {
954     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
955     if (format == PETSC_VIEWER_ASCII_INFO) {
956       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr);
957       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase:             %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr);
958       for (i=1; i<=64; i++) {
959         ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]:     %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr);
960       }
961       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct:     %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr);
962       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum:     %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr);
963       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype:     %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr);
964       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n:     %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr);
965       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs:     %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
966       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl:     %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr);
967     }
968   }
969   PetscFunctionReturn(0);
970 }
971 
972 
973 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
974 {
975   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data;
976 
977   PetscFunctionBegin;
978   info->block_size        = 1.0;
979   info->nz_used           = mat_mkl_pardiso->iparm[17];
980   info->nz_allocated      = mat_mkl_pardiso->iparm[17];
981   info->nz_unneeded       = 0.0;
982   info->assemblies        = 0.0;
983   info->mallocs           = 0.0;
984   info->memory            = 0.0;
985   info->fill_ratio_given  = 0;
986   info->fill_ratio_needed = 0;
987   info->factor_mallocs    = 0;
988   PetscFunctionReturn(0);
989 }
990 
991 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival)
992 {
993   PetscInt        backup,bs;
994   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
995 
996   PetscFunctionBegin;
997   if (icntl <= 64) {
998     mat_mkl_pardiso->iparm[icntl - 1] = ival;
999   } else {
1000     if (icntl == 65) PetscSetMKL_PARDISOThreads(ival);
1001     else if (icntl == 66) mat_mkl_pardiso->maxfct = ival;
1002     else if (icntl == 67) mat_mkl_pardiso->mnum = ival;
1003     else if (icntl == 68) mat_mkl_pardiso->msglvl = ival;
1004     else if (icntl == 69) {
1005       void *pt[IPARM_SIZE];
1006       backup = mat_mkl_pardiso->iparm[34];
1007       bs = mat_mkl_pardiso->iparm[36];
1008       mat_mkl_pardiso->mtype = ival;
1009       MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
1010 #if defined(PETSC_USE_REAL_SINGLE)
1011       mat_mkl_pardiso->iparm[27] = 1;
1012 #else
1013       mat_mkl_pardiso->iparm[27] = 0;
1014 #endif
1015       mat_mkl_pardiso->iparm[34] = backup;
1016       mat_mkl_pardiso->iparm[36] = bs;
1017     } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival;
1018   }
1019   PetscFunctionReturn(0);
1020 }
1021 
1022 /*@
1023   MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters
1024 
1025    Logically Collective on Mat
1026 
1027    Input Parameters:
1028 +  F - the factored matrix obtained by calling MatGetFactor()
1029 .  icntl - index of Mkl_Pardiso parameter
1030 -  ival - value of Mkl_Pardiso parameter
1031 
1032   Options Database:
1033 .   -mat_mkl_pardiso_<icntl> <ival>
1034 
1035    Level: beginner
1036 
1037    References:
1038 .      Mkl_Pardiso Users' Guide
1039 
1040 .seealso: MatGetFactor()
1041 @*/
1042 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival)
1043 {
1044   PetscErrorCode ierr;
1045 
1046   PetscFunctionBegin;
1047   ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr);
1048   PetscFunctionReturn(0);
1049 }
1050 
1051 /*MC
1052   MATSOLVERMKL_PARDISO -  A matrix type providing direct solvers (LU) for
1053   sequential matrices via the external package MKL_PARDISO.
1054 
1055   Works with MATSEQAIJ matrices
1056 
1057   Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver
1058 
1059   Options Database Keys:
1060 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO
1061 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
1062 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
1063 . -mat_mkl_pardiso_68 - Message level information
1064 . -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
1065 . -mat_mkl_pardiso_1  - Use default values
1066 . -mat_mkl_pardiso_2  - Fill-in reducing ordering for the input matrix
1067 . -mat_mkl_pardiso_4  - Preconditioned CGS/CG
1068 . -mat_mkl_pardiso_5  - User permutation
1069 . -mat_mkl_pardiso_6  - Write solution on x
1070 . -mat_mkl_pardiso_8  - Iterative refinement step
1071 . -mat_mkl_pardiso_10 - Pivoting perturbation
1072 . -mat_mkl_pardiso_11 - Scaling vectors
1073 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
1074 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
1075 . -mat_mkl_pardiso_18 - Numbers of non-zero elements
1076 . -mat_mkl_pardiso_19 - Report number of floating point operations
1077 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
1078 . -mat_mkl_pardiso_24 - Parallel factorization control
1079 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
1080 . -mat_mkl_pardiso_27 - Matrix checker
1081 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
1082 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
1083 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode
1084 
1085   Level: beginner
1086 
1087   For more information please check  mkl_pardiso manual
1088 
1089 .seealso: PCFactorSetMatSolverType(), MatSolverType
1090 
1091 M*/
1092 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type)
1093 {
1094   PetscFunctionBegin;
1095   *type = MATSOLVERMKL_PARDISO;
1096   PetscFunctionReturn(0);
1097 }
1098 
1099 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F)
1100 {
1101   Mat             B;
1102   PetscErrorCode  ierr;
1103   Mat_MKL_PARDISO *mat_mkl_pardiso;
1104   PetscBool       isSeqAIJ,isSeqBAIJ,isSeqSBAIJ;
1105 
1106   PetscFunctionBegin;
1107   ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
1108   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr);
1109   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
1110   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1111   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
1112   ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr);
1113   ierr = MatSetUp(B);CHKERRQ(ierr);
1114 
1115   ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr);
1116   B->data = mat_mkl_pardiso;
1117 
1118   ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr);
1119   if (ftype == MAT_FACTOR_LU) {
1120     B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1121     B->factortype            = MAT_FACTOR_LU;
1122     mat_mkl_pardiso->needsym = PETSC_FALSE;
1123     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1124     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1125     else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1126     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name);
1127 #if defined(PETSC_USE_COMPLEX)
1128     mat_mkl_pardiso->mtype = 13;
1129 #else
1130     mat_mkl_pardiso->mtype = 11;
1131 #endif
1132   } else {
1133     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1134     B->factortype                  = MAT_FACTOR_CHOLESKY;
1135     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1136     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1137     else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1138     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name);
1139 
1140     mat_mkl_pardiso->needsym = PETSC_TRUE;
1141 #if !defined(PETSC_USE_COMPLEX)
1142     if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2;
1143     else                      mat_mkl_pardiso->mtype = -2;
1144 #else
1145     mat_mkl_pardiso->mtype = 6;
1146     if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead");
1147 #endif
1148   }
1149   B->ops->destroy = MatDestroy_MKL_PARDISO;
1150   B->ops->view    = MatView_MKL_PARDISO;
1151   B->ops->getinfo = MatGetInfo_MKL_PARDISO;
1152   B->factortype   = ftype;
1153   B->assembled    = PETSC_TRUE;
1154 
1155   ierr = PetscFree(B->solvertype);CHKERRQ(ierr);
1156   ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr);
1157 
1158   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr);
1159   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr);
1160   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr);
1161 
1162   *F = B;
1163   PetscFunctionReturn(0);
1164 }
1165 
1166 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void)
1167 {
1168   PetscErrorCode ierr;
1169 
1170   PetscFunctionBegin;
1171   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1172   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1173   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1174   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1175   PetscFunctionReturn(0);
1176 }
1177 
1178