xref: /petsc/src/mat/impls/aij/seq/mkl_pardiso/mkl_pardiso.c (revision efa12513287cff49a2b9648ae83199dcbfaad71a)
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 = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr);
247   if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address");
248   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr);
249   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr);
250   ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr);
251   ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr);
252 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
253   ierr = MatBindToCPU(Xmat,S->boundtocpu);CHKERRQ(ierr);
254   ierr = MatBindToCPU(Bmat,S->boundtocpu);CHKERRQ(ierr);
255 #endif
256 
257 #if defined(PETSC_USE_COMPLEX)
258   if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet");
259 #endif
260 
261   switch (schurstatus) {
262   case MAT_FACTOR_SCHUR_FACTORED:
263     if (!mpardiso->iparm[12-1]) {
264       ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr);
265     } else { /* transpose solve */
266       ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr);
267     }
268     break;
269   case MAT_FACTOR_SCHUR_INVERTED:
270     ierr = MatProductCreateWithMat(S,Bmat,NULL,Xmat);CHKERRQ(ierr);
271     if (!mpardiso->iparm[12-1]) {
272       ierr = MatProductSetType(Xmat,MATPRODUCT_AB);CHKERRQ(ierr);
273     } else { /* transpose solve */
274       ierr = MatProductSetType(Xmat,MATPRODUCT_AtB);CHKERRQ(ierr);
275     }
276     ierr = MatProductSetFromOptions(Xmat);CHKERRQ(ierr);
277     ierr = MatProductSymbolic(Xmat);CHKERRQ(ierr);
278     ierr = MatProductNumeric(Xmat);CHKERRQ(ierr);
279     ierr = MatProductClear(Xmat);CHKERRQ(ierr);
280     break;
281   default:
282     SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status);
283     break;
284   }
285   ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr);
286   ierr = MatDestroy(&Bmat);CHKERRQ(ierr);
287   ierr = MatDestroy(&Xmat);CHKERRQ(ierr);
288   PetscFunctionReturn(0);
289 }
290 
291 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is)
292 {
293   Mat_MKL_PARDISO   *mpardiso = (Mat_MKL_PARDISO*)F->data;
294   const PetscScalar *arr;
295   const PetscInt    *idxs;
296   PetscInt          size,i;
297   PetscMPIInt       csize;
298   PetscBool         sorted;
299   PetscErrorCode    ierr;
300 
301   PetscFunctionBegin;
302   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRMPI(ierr);
303   if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc");
304   ierr = ISSorted(is,&sorted);CHKERRQ(ierr);
305   if (!sorted) {
306     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted");
307   }
308   ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr);
309   ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr);
310   ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr);
311   ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr);
312   ierr = MatDestroy(&F->schur);CHKERRQ(ierr);
313   ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr);
314   ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr);
315   mpardiso->schur      = (PetscScalar*)arr;
316   mpardiso->schur_size = size;
317   ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr);
318   if (mpardiso->mtype == 2) {
319     ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr);
320   }
321 
322   ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr);
323   ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr);
324   ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr);
325   ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr);
326   ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr);
327   for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1;
328   ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr);
329   if (size) { /* turn on Schur switch if the set of indices is not empty */
330     mpardiso->iparm[36-1] = 2;
331   }
332   PetscFunctionReturn(0);
333 }
334 
335 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A)
336 {
337   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
338   PetscErrorCode  ierr;
339 
340   PetscFunctionBegin;
341   if (mat_mkl_pardiso->CleanUp) {
342     mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY;
343 
344     MKL_PARDISO (mat_mkl_pardiso->pt,
345       &mat_mkl_pardiso->maxfct,
346       &mat_mkl_pardiso->mnum,
347       &mat_mkl_pardiso->mtype,
348       &mat_mkl_pardiso->phase,
349       &mat_mkl_pardiso->n,
350       NULL,
351       NULL,
352       NULL,
353       NULL,
354       &mat_mkl_pardiso->nrhs,
355       mat_mkl_pardiso->iparm,
356       &mat_mkl_pardiso->msglvl,
357       NULL,
358       NULL,
359       &mat_mkl_pardiso->err);
360   }
361   ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr);
362   ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
363   ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr);
364   if (mat_mkl_pardiso->freeaij) {
365     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
366     if (mat_mkl_pardiso->iparm[34] == 1) {
367       ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
368     }
369   }
370   ierr = PetscFree(A->data);CHKERRQ(ierr);
371 
372   /* clear composed functions */
373   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr);
374   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr);
375   ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr);
376   PetscFunctionReturn(0);
377 }
378 
379 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce)
380 {
381   PetscFunctionBegin;
382   if (reduce) { /* data given for the whole matrix */
383     PetscInt i,m=0,p=0;
384     for (i=0;i<mpardiso->nrhs;i++) {
385       PetscInt j;
386       for (j=0;j<mpardiso->schur_size;j++) {
387         schur[p+j] = whole[m+mpardiso->schur_idxs[j]];
388       }
389       m += mpardiso->n;
390       p += mpardiso->schur_size;
391     }
392   } else { /* from Schur to whole */
393     PetscInt i,m=0,p=0;
394     for (i=0;i<mpardiso->nrhs;i++) {
395       PetscInt j;
396       for (j=0;j<mpardiso->schur_size;j++) {
397         whole[m+mpardiso->schur_idxs[j]] = schur[p+j];
398       }
399       m += mpardiso->n;
400       p += mpardiso->schur_size;
401     }
402   }
403   PetscFunctionReturn(0);
404 }
405 
406 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x)
407 {
408   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
409   PetscErrorCode    ierr;
410   PetscScalar       *xarray;
411   const PetscScalar *barray;
412 
413   PetscFunctionBegin;
414   mat_mkl_pardiso->nrhs = 1;
415   ierr = VecGetArray(x,&xarray);CHKERRQ(ierr);
416   ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr);
417 
418   if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
419   else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
420 
421   if (barray == xarray) { /* if the two vectors share the same memory */
422     PetscScalar *work;
423     if (!mat_mkl_pardiso->schur_work) {
424       ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr);
425     } else {
426       work = mat_mkl_pardiso->schur_work;
427     }
428     mat_mkl_pardiso->iparm[6-1] = 1;
429     MKL_PARDISO (mat_mkl_pardiso->pt,
430       &mat_mkl_pardiso->maxfct,
431       &mat_mkl_pardiso->mnum,
432       &mat_mkl_pardiso->mtype,
433       &mat_mkl_pardiso->phase,
434       &mat_mkl_pardiso->n,
435       mat_mkl_pardiso->a,
436       mat_mkl_pardiso->ia,
437       mat_mkl_pardiso->ja,
438       NULL,
439       &mat_mkl_pardiso->nrhs,
440       mat_mkl_pardiso->iparm,
441       &mat_mkl_pardiso->msglvl,
442       (void*)xarray,
443       (void*)work,
444       &mat_mkl_pardiso->err);
445     if (!mat_mkl_pardiso->schur_work) {
446       ierr = PetscFree(work);CHKERRQ(ierr);
447     }
448   } else {
449     mat_mkl_pardiso->iparm[6-1] = 0;
450     MKL_PARDISO (mat_mkl_pardiso->pt,
451       &mat_mkl_pardiso->maxfct,
452       &mat_mkl_pardiso->mnum,
453       &mat_mkl_pardiso->mtype,
454       &mat_mkl_pardiso->phase,
455       &mat_mkl_pardiso->n,
456       mat_mkl_pardiso->a,
457       mat_mkl_pardiso->ia,
458       mat_mkl_pardiso->ja,
459       mat_mkl_pardiso->perm,
460       &mat_mkl_pardiso->nrhs,
461       mat_mkl_pardiso->iparm,
462       &mat_mkl_pardiso->msglvl,
463       (void*)barray,
464       (void*)xarray,
465       &mat_mkl_pardiso->err);
466   }
467   ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr);
468 
469   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);
470 
471   if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
472     PetscInt shift = mat_mkl_pardiso->schur_size;
473 
474     ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr);
475 
476     /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
477     if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
478 
479     if (!mat_mkl_pardiso->solve_interior) {
480       /* solve Schur complement */
481       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
482       ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
483       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
484     } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */
485       PetscInt i;
486       for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
487         xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
488       }
489     }
490 
491     /* expansion phase */
492     mat_mkl_pardiso->iparm[6-1] = 1;
493     mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
494     MKL_PARDISO (mat_mkl_pardiso->pt,
495       &mat_mkl_pardiso->maxfct,
496       &mat_mkl_pardiso->mnum,
497       &mat_mkl_pardiso->mtype,
498       &mat_mkl_pardiso->phase,
499       &mat_mkl_pardiso->n,
500       mat_mkl_pardiso->a,
501       mat_mkl_pardiso->ia,
502       mat_mkl_pardiso->ja,
503       mat_mkl_pardiso->perm,
504       &mat_mkl_pardiso->nrhs,
505       mat_mkl_pardiso->iparm,
506       &mat_mkl_pardiso->msglvl,
507       (void*)xarray,
508       (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
509       &mat_mkl_pardiso->err);
510 
511     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);
512     mat_mkl_pardiso->iparm[6-1] = 0;
513   }
514   ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr);
515   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
516   PetscFunctionReturn(0);
517 }
518 
519 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x)
520 {
521   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
522   PetscInt        oiparm12;
523   PetscErrorCode  ierr;
524 
525   PetscFunctionBegin;
526   oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
527   mat_mkl_pardiso->iparm[12 - 1] = 2;
528   ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr);
529   mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
530   PetscFunctionReturn(0);
531 }
532 
533 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X)
534 {
535   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
536   PetscErrorCode    ierr;
537   const PetscScalar *barray;
538   PetscScalar       *xarray;
539   PetscBool         flg;
540 
541   PetscFunctionBegin;
542   ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr);
543   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix");
544   if (X != B) {
545     ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr);
546     if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix");
547   }
548 
549   ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
550 
551   if (mat_mkl_pardiso->nrhs > 0) {
552     ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr);
553     ierr = MatDenseGetArray(X,&xarray);CHKERRQ(ierr);
554 
555     if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location");
556     if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
557     else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
558 
559     MKL_PARDISO (mat_mkl_pardiso->pt,
560       &mat_mkl_pardiso->maxfct,
561       &mat_mkl_pardiso->mnum,
562       &mat_mkl_pardiso->mtype,
563       &mat_mkl_pardiso->phase,
564       &mat_mkl_pardiso->n,
565       mat_mkl_pardiso->a,
566       mat_mkl_pardiso->ia,
567       mat_mkl_pardiso->ja,
568       mat_mkl_pardiso->perm,
569       &mat_mkl_pardiso->nrhs,
570       mat_mkl_pardiso->iparm,
571       &mat_mkl_pardiso->msglvl,
572       (void*)barray,
573       (void*)xarray,
574       &mat_mkl_pardiso->err);
575     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);
576 
577     ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr);
578     if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
579       PetscScalar *o_schur_work = NULL;
580       PetscInt    shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale;
581       PetscInt    mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs;
582 
583       ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr);
584 
585       /* allocate extra memory if it is needed */
586       scale = 1;
587       if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2;
588 
589       mem *= scale;
590       if (mem > mat_mkl_pardiso->schur_work_size) {
591         o_schur_work = mat_mkl_pardiso->schur_work;
592         ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
593       }
594 
595       /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
596       if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
597 
598       /* solve Schur complement */
599       if (!mat_mkl_pardiso->solve_interior) {
600         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
601         ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
602         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
603       } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */
604         PetscInt i,n,m=0;
605         for (n=0;n<mat_mkl_pardiso->nrhs;n++) {
606           for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
607             xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.;
608           }
609           m += mat_mkl_pardiso->n;
610         }
611       }
612 
613       /* expansion phase */
614       mat_mkl_pardiso->iparm[6-1] = 1;
615       mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
616       MKL_PARDISO (mat_mkl_pardiso->pt,
617         &mat_mkl_pardiso->maxfct,
618         &mat_mkl_pardiso->mnum,
619         &mat_mkl_pardiso->mtype,
620         &mat_mkl_pardiso->phase,
621         &mat_mkl_pardiso->n,
622         mat_mkl_pardiso->a,
623         mat_mkl_pardiso->ia,
624         mat_mkl_pardiso->ja,
625         mat_mkl_pardiso->perm,
626         &mat_mkl_pardiso->nrhs,
627         mat_mkl_pardiso->iparm,
628         &mat_mkl_pardiso->msglvl,
629         (void*)xarray,
630         (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
631         &mat_mkl_pardiso->err);
632       if (o_schur_work) { /* restore original schur_work (minimal size) */
633         ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
634         mat_mkl_pardiso->schur_work = o_schur_work;
635       }
636       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);
637       mat_mkl_pardiso->iparm[6-1] = 0;
638     }
639   }
640   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
641   PetscFunctionReturn(0);
642 }
643 
644 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info)
645 {
646   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data;
647   PetscErrorCode  ierr;
648 
649   PetscFunctionBegin;
650   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
651   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);
652 
653   mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
654   MKL_PARDISO (mat_mkl_pardiso->pt,
655     &mat_mkl_pardiso->maxfct,
656     &mat_mkl_pardiso->mnum,
657     &mat_mkl_pardiso->mtype,
658     &mat_mkl_pardiso->phase,
659     &mat_mkl_pardiso->n,
660     mat_mkl_pardiso->a,
661     mat_mkl_pardiso->ia,
662     mat_mkl_pardiso->ja,
663     mat_mkl_pardiso->perm,
664     &mat_mkl_pardiso->nrhs,
665     mat_mkl_pardiso->iparm,
666     &mat_mkl_pardiso->msglvl,
667     NULL,
668     (void*)mat_mkl_pardiso->schur,
669     &mat_mkl_pardiso->err);
670   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);
671 
672   /* report flops */
673   if (mat_mkl_pardiso->iparm[18] > 0) {
674     ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr);
675   }
676 
677   if (F->schur) { /* schur output from pardiso is in row major format */
678 #if defined(PETSC_HAVE_CUDA)
679     F->schur->offloadmask = PETSC_OFFLOAD_CPU;
680 #endif
681     ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr);
682     ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr);
683   }
684   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
685   mat_mkl_pardiso->CleanUp  = PETSC_TRUE;
686   PetscFunctionReturn(0);
687 }
688 
689 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A)
690 {
691   Mat_MKL_PARDISO     *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
692   PetscErrorCode      ierr;
693   PetscInt            icntl,bs,threads=1;
694   PetscBool           flg;
695 
696   PetscFunctionBegin;
697   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr);
698 
699   ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr);
700   if (flg) PetscSetMKL_PARDISOThreads((int)threads);
701 
702   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);
703   if (flg) mat_mkl_pardiso->maxfct = icntl;
704 
705   ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr);
706   if (flg) mat_mkl_pardiso->mnum = icntl;
707 
708   ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr);
709   if (flg) mat_mkl_pardiso->msglvl = icntl;
710 
711   ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr);
712   if (flg) {
713     void *pt[IPARM_SIZE];
714     mat_mkl_pardiso->mtype = icntl;
715     icntl = mat_mkl_pardiso->iparm[34];
716     bs = mat_mkl_pardiso->iparm[36];
717     MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
718 #if defined(PETSC_USE_REAL_SINGLE)
719     mat_mkl_pardiso->iparm[27] = 1;
720 #else
721     mat_mkl_pardiso->iparm[27] = 0;
722 #endif
723     mat_mkl_pardiso->iparm[34] = icntl;
724     mat_mkl_pardiso->iparm[36] = bs;
725   }
726   ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr);
727 
728   if (flg && icntl != 0) {
729     ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr);
730     if (flg) mat_mkl_pardiso->iparm[1] = icntl;
731 
732     ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr);
733     if (flg) mat_mkl_pardiso->iparm[3] = icntl;
734 
735     ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr);
736     if (flg) mat_mkl_pardiso->iparm[4] = icntl;
737 
738     ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr);
739     if (flg) mat_mkl_pardiso->iparm[5] = icntl;
740 
741     ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr);
742     if (flg) mat_mkl_pardiso->iparm[7] = icntl;
743 
744     ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr);
745     if (flg) mat_mkl_pardiso->iparm[9] = icntl;
746 
747     ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr);
748     if (flg) mat_mkl_pardiso->iparm[10] = icntl;
749 
750     ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr);
751     if (flg) mat_mkl_pardiso->iparm[11] = icntl;
752 
753     ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr);
754     if (flg) mat_mkl_pardiso->iparm[12] = icntl;
755 
756     ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr);
757     if (flg) mat_mkl_pardiso->iparm[17] = icntl;
758 
759     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);
760     if (flg) mat_mkl_pardiso->iparm[18] = icntl;
761 
762     ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr);
763     if (flg) mat_mkl_pardiso->iparm[20] = icntl;
764 
765     ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr);
766     if (flg) mat_mkl_pardiso->iparm[23] = icntl;
767 
768     ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr);
769     if (flg) mat_mkl_pardiso->iparm[24] = icntl;
770 
771     ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr);
772     if (flg) mat_mkl_pardiso->iparm[26] = icntl;
773 
774     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);
775     if (flg) mat_mkl_pardiso->iparm[30] = icntl;
776 
777     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);
778     if (flg) mat_mkl_pardiso->iparm[33] = icntl;
779 
780     ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr);
781     if (flg) mat_mkl_pardiso->iparm[59] = icntl;
782   }
783   PetscOptionsEnd();
784   PetscFunctionReturn(0);
785 }
786 
787 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
788 {
789   PetscErrorCode ierr;
790   PetscInt       i,bs;
791   PetscBool      match;
792 
793   PetscFunctionBegin;
794   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0;
795   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0;
796 #if defined(PETSC_USE_REAL_SINGLE)
797   mat_mkl_pardiso->iparm[27] = 1;
798 #else
799   mat_mkl_pardiso->iparm[27] = 0;
800 #endif
801   /* Default options for both sym and unsym */
802   mat_mkl_pardiso->iparm[ 0] =  1; /* Solver default parameters overriden with provided by iparm */
803   mat_mkl_pardiso->iparm[ 1] =  2; /* Metis reordering */
804   mat_mkl_pardiso->iparm[ 5] =  0; /* Write solution into x */
805   mat_mkl_pardiso->iparm[ 7] =  0; /* Max number of iterative refinement steps */
806   mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
807   mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
808 #if 0
809   mat_mkl_pardiso->iparm[23] =  1; /* Parallel factorization control*/
810 #endif
811   ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr);
812   ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr);
813   if (!match || bs == 1) {
814     mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
815     mat_mkl_pardiso->n         = A->rmap->N;
816   } else {
817     mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */
818     mat_mkl_pardiso->iparm[36] = bs;
819     mat_mkl_pardiso->n         = A->rmap->N/bs;
820   }
821   mat_mkl_pardiso->iparm[39] =  0; /* Input: matrix/rhs/solution stored on master */
822 
823   mat_mkl_pardiso->CleanUp   = PETSC_FALSE;
824   mat_mkl_pardiso->maxfct    = 1; /* Maximum number of numerical factorizations. */
825   mat_mkl_pardiso->mnum      = 1; /* Which factorization to use. */
826   mat_mkl_pardiso->msglvl    = 0; /* 0: do not print 1: Print statistical information in file */
827   mat_mkl_pardiso->phase     = -1;
828   mat_mkl_pardiso->err       = 0;
829 
830   mat_mkl_pardiso->nrhs      = 1;
831   mat_mkl_pardiso->err       = 0;
832   mat_mkl_pardiso->phase     = -1;
833 
834   if (ftype == MAT_FACTOR_LU) {
835     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
836     mat_mkl_pardiso->iparm[10] =  1; /* Use nonsymmetric permutation and scaling MPS */
837     mat_mkl_pardiso->iparm[12] =  1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
838   } else {
839     mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */
840     mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
841     mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
842 #if defined(PETSC_USE_DEBUG)
843     mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
844 #endif
845   }
846   ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr);
847   for (i=0; i<A->rmap->N; i++) {
848     mat_mkl_pardiso->perm[i] = 0;
849   }
850   mat_mkl_pardiso->schur_size = 0;
851   PetscFunctionReturn(0);
852 }
853 
854 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info)
855 {
856   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
857   PetscErrorCode  ierr;
858 
859   PetscFunctionBegin;
860   mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
861   ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr);
862 
863   /* throw away any previously computed structure */
864   if (mat_mkl_pardiso->freeaij) {
865     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
866     if (mat_mkl_pardiso->iparm[34] == 1) {
867       ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
868     }
869   }
870   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);
871   if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N;
872   else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs;
873 
874   mat_mkl_pardiso->phase = JOB_ANALYSIS;
875 
876   /* reset flops counting if requested */
877   if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1;
878 
879   MKL_PARDISO (mat_mkl_pardiso->pt,
880     &mat_mkl_pardiso->maxfct,
881     &mat_mkl_pardiso->mnum,
882     &mat_mkl_pardiso->mtype,
883     &mat_mkl_pardiso->phase,
884     &mat_mkl_pardiso->n,
885     mat_mkl_pardiso->a,
886     mat_mkl_pardiso->ia,
887     mat_mkl_pardiso->ja,
888     mat_mkl_pardiso->perm,
889     &mat_mkl_pardiso->nrhs,
890     mat_mkl_pardiso->iparm,
891     &mat_mkl_pardiso->msglvl,
892     NULL,
893     NULL,
894     &mat_mkl_pardiso->err);
895   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);
896 
897   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
898 
899   if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
900   else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
901 
902   F->ops->solve           = MatSolve_MKL_PARDISO;
903   F->ops->solvetranspose  = MatSolveTranspose_MKL_PARDISO;
904   F->ops->matsolve        = MatMatSolve_MKL_PARDISO;
905   PetscFunctionReturn(0);
906 }
907 
908 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
909 {
910   PetscErrorCode ierr;
911 
912   PetscFunctionBegin;
913   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
914   PetscFunctionReturn(0);
915 }
916 
917 #if !defined(PETSC_USE_COMPLEX)
918 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos)
919 {
920   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data;
921 
922   PetscFunctionBegin;
923   if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
924   if (npos) *npos = mat_mkl_pardiso->iparm[21];
925   if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
926   PetscFunctionReturn(0);
927 }
928 #endif
929 
930 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info)
931 {
932   PetscErrorCode ierr;
933 
934   PetscFunctionBegin;
935   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
936 #if defined(PETSC_USE_COMPLEX)
937   F->ops->getinertia = NULL;
938 #else
939   F->ops->getinertia = MatGetInertia_MKL_PARDISO;
940 #endif
941   PetscFunctionReturn(0);
942 }
943 
944 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
945 {
946   PetscErrorCode    ierr;
947   PetscBool         iascii;
948   PetscViewerFormat format;
949   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
950   PetscInt          i;
951 
952   PetscFunctionBegin;
953   if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0);
954 
955   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
956   if (iascii) {
957     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
958     if (format == PETSC_VIEWER_ASCII_INFO) {
959       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr);
960       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase:             %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr);
961       for (i=1; i<=64; i++) {
962         ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]:     %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr);
963       }
964       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct:     %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr);
965       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum:     %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr);
966       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype:     %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr);
967       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n:     %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr);
968       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs:     %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
969       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl:     %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr);
970     }
971   }
972   PetscFunctionReturn(0);
973 }
974 
975 
976 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
977 {
978   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data;
979 
980   PetscFunctionBegin;
981   info->block_size        = 1.0;
982   info->nz_used           = mat_mkl_pardiso->iparm[17];
983   info->nz_allocated      = mat_mkl_pardiso->iparm[17];
984   info->nz_unneeded       = 0.0;
985   info->assemblies        = 0.0;
986   info->mallocs           = 0.0;
987   info->memory            = 0.0;
988   info->fill_ratio_given  = 0;
989   info->fill_ratio_needed = 0;
990   info->factor_mallocs    = 0;
991   PetscFunctionReturn(0);
992 }
993 
994 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival)
995 {
996   PetscInt        backup,bs;
997   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
998 
999   PetscFunctionBegin;
1000   if (icntl <= 64) {
1001     mat_mkl_pardiso->iparm[icntl - 1] = ival;
1002   } else {
1003     if (icntl == 65) PetscSetMKL_PARDISOThreads(ival);
1004     else if (icntl == 66) mat_mkl_pardiso->maxfct = ival;
1005     else if (icntl == 67) mat_mkl_pardiso->mnum = ival;
1006     else if (icntl == 68) mat_mkl_pardiso->msglvl = ival;
1007     else if (icntl == 69) {
1008       void *pt[IPARM_SIZE];
1009       backup = mat_mkl_pardiso->iparm[34];
1010       bs = mat_mkl_pardiso->iparm[36];
1011       mat_mkl_pardiso->mtype = ival;
1012       MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
1013 #if defined(PETSC_USE_REAL_SINGLE)
1014       mat_mkl_pardiso->iparm[27] = 1;
1015 #else
1016       mat_mkl_pardiso->iparm[27] = 0;
1017 #endif
1018       mat_mkl_pardiso->iparm[34] = backup;
1019       mat_mkl_pardiso->iparm[36] = bs;
1020     } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival;
1021   }
1022   PetscFunctionReturn(0);
1023 }
1024 
1025 /*@
1026   MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters
1027 
1028    Logically Collective on Mat
1029 
1030    Input Parameters:
1031 +  F - the factored matrix obtained by calling MatGetFactor()
1032 .  icntl - index of Mkl_Pardiso parameter
1033 -  ival - value of Mkl_Pardiso parameter
1034 
1035   Options Database:
1036 .   -mat_mkl_pardiso_<icntl> <ival>
1037 
1038    Level: beginner
1039 
1040    References:
1041 .      Mkl_Pardiso Users' Guide
1042 
1043 .seealso: MatGetFactor()
1044 @*/
1045 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival)
1046 {
1047   PetscErrorCode ierr;
1048 
1049   PetscFunctionBegin;
1050   ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr);
1051   PetscFunctionReturn(0);
1052 }
1053 
1054 /*MC
1055   MATSOLVERMKL_PARDISO -  A matrix type providing direct solvers (LU) for
1056   sequential matrices via the external package MKL_PARDISO.
1057 
1058   Works with MATSEQAIJ matrices
1059 
1060   Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver
1061 
1062   Options Database Keys:
1063 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO
1064 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
1065 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
1066 . -mat_mkl_pardiso_68 - Message level information
1067 . -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
1068 . -mat_mkl_pardiso_1  - Use default values
1069 . -mat_mkl_pardiso_2  - Fill-in reducing ordering for the input matrix
1070 . -mat_mkl_pardiso_4  - Preconditioned CGS/CG
1071 . -mat_mkl_pardiso_5  - User permutation
1072 . -mat_mkl_pardiso_6  - Write solution on x
1073 . -mat_mkl_pardiso_8  - Iterative refinement step
1074 . -mat_mkl_pardiso_10 - Pivoting perturbation
1075 . -mat_mkl_pardiso_11 - Scaling vectors
1076 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
1077 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
1078 . -mat_mkl_pardiso_18 - Numbers of non-zero elements
1079 . -mat_mkl_pardiso_19 - Report number of floating point operations
1080 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
1081 . -mat_mkl_pardiso_24 - Parallel factorization control
1082 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
1083 . -mat_mkl_pardiso_27 - Matrix checker
1084 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
1085 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
1086 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode
1087 
1088   Level: beginner
1089 
1090   For more information please check  mkl_pardiso manual
1091 
1092 .seealso: PCFactorSetMatSolverType(), MatSolverType
1093 
1094 M*/
1095 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type)
1096 {
1097   PetscFunctionBegin;
1098   *type = MATSOLVERMKL_PARDISO;
1099   PetscFunctionReturn(0);
1100 }
1101 
1102 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F)
1103 {
1104   Mat             B;
1105   PetscErrorCode  ierr;
1106   Mat_MKL_PARDISO *mat_mkl_pardiso;
1107   PetscBool       isSeqAIJ,isSeqBAIJ,isSeqSBAIJ;
1108 
1109   PetscFunctionBegin;
1110   ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
1111   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr);
1112   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
1113   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1114   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
1115   ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr);
1116   ierr = MatSetUp(B);CHKERRQ(ierr);
1117 
1118   ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr);
1119   B->data = mat_mkl_pardiso;
1120 
1121   ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr);
1122   if (ftype == MAT_FACTOR_LU) {
1123     B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1124     B->factortype            = MAT_FACTOR_LU;
1125     mat_mkl_pardiso->needsym = PETSC_FALSE;
1126     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1127     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1128     else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1129     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name);
1130 #if defined(PETSC_USE_COMPLEX)
1131     mat_mkl_pardiso->mtype = 13;
1132 #else
1133     mat_mkl_pardiso->mtype = 11;
1134 #endif
1135   } else {
1136     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1137     B->factortype                  = MAT_FACTOR_CHOLESKY;
1138     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1139     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1140     else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1141     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name);
1142 
1143     mat_mkl_pardiso->needsym = PETSC_TRUE;
1144 #if !defined(PETSC_USE_COMPLEX)
1145     if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2;
1146     else                      mat_mkl_pardiso->mtype = -2;
1147 #else
1148     mat_mkl_pardiso->mtype = 6;
1149     if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead");
1150 #endif
1151   }
1152   B->ops->destroy = MatDestroy_MKL_PARDISO;
1153   B->ops->view    = MatView_MKL_PARDISO;
1154   B->ops->getinfo = MatGetInfo_MKL_PARDISO;
1155   B->factortype   = ftype;
1156   B->assembled    = PETSC_TRUE;
1157 
1158   ierr = PetscFree(B->solvertype);CHKERRQ(ierr);
1159   ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr);
1160 
1161   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr);
1162   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr);
1163   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr);
1164 
1165   *F = B;
1166   PetscFunctionReturn(0);
1167 }
1168 
1169 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void)
1170 {
1171   PetscErrorCode ierr;
1172 
1173   PetscFunctionBegin;
1174   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1175   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1176   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1177   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1178   PetscFunctionReturn(0);
1179 }
1180 
1181