xref: /petsc/src/mat/impls/aij/seq/mkl_pardiso/mkl_pardiso.c (revision 609bdbee21ea3be08735c64dbe00a9ab27759925)
1 #if defined(PETSC_HAVE_LIBMKL_INTEL_ILP64)
2 #define MKL_ILP64
3 #endif
4 
5 #include <../src/mat/impls/aij/seq/aij.h>        /*I "petscmat.h" I*/
6 #include <../src/mat/impls/sbaij/seq/sbaij.h>
7 #include <../src/mat/impls/dense/seq/dense.h>
8 #include <petscblaslapack.h>
9 
10 #include <stdio.h>
11 #include <stdlib.h>
12 #include <math.h>
13 #include <mkl_pardiso.h>
14 
15 PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int);
16 
17 /*
18  *  Possible mkl_pardiso phases that controls the execution of the solver.
19  *  For more information check mkl_pardiso manual.
20  */
21 #define JOB_ANALYSIS 11
22 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION 12
23 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 13
24 #define JOB_NUMERICAL_FACTORIZATION 22
25 #define JOB_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 23
26 #define JOB_SOLVE_ITERATIVE_REFINEMENT 33
27 #define JOB_SOLVE_FORWARD_SUBSTITUTION 331
28 #define JOB_SOLVE_DIAGONAL_SUBSTITUTION 332
29 #define JOB_SOLVE_BACKWARD_SUBSTITUTION 333
30 #define JOB_RELEASE_OF_LU_MEMORY 0
31 #define JOB_RELEASE_OF_ALL_MEMORY -1
32 
33 #define IPARM_SIZE 64
34 
35 #if defined(PETSC_USE_64BIT_INDICES)
36  #if defined(PETSC_HAVE_LIBMKL_INTEL_ILP64)
37   /* sizeof(MKL_INT) == sizeof(long long int) if ilp64*/
38   #define INT_TYPE long long int
39   #define MKL_PARDISO pardiso
40   #define MKL_PARDISO_INIT pardisoinit
41  #else
42   #define INT_TYPE long long int
43   #define MKL_PARDISO pardiso_64
44   #define MKL_PARDISO_INIT pardiso_64init
45  #endif
46 #else
47  #define INT_TYPE int
48  #define MKL_PARDISO pardiso
49  #define MKL_PARDISO_INIT pardisoinit
50 #endif
51 
52 
53 /*
54  *  Internal data structure.
55  *  For more information check mkl_pardiso manual.
56  */
57 typedef struct {
58 
59   /* Configuration vector*/
60   INT_TYPE     iparm[IPARM_SIZE];
61 
62   /*
63    * Internal mkl_pardiso memory location.
64    * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak.
65    */
66   void         *pt[IPARM_SIZE];
67 
68   /* Basic mkl_pardiso info*/
69   INT_TYPE     phase, maxfct, mnum, mtype, n, nrhs, msglvl, err;
70 
71   /* Matrix structure*/
72   void         *a;
73   INT_TYPE     *ia, *ja;
74 
75   /* Number of non-zero elements*/
76   INT_TYPE     nz;
77 
78   /* Row permutaton vector*/
79   INT_TYPE     *perm;
80 
81   /* Define if matrix preserves sparse structure.*/
82   MatStructure matstruc;
83 
84   PetscBool    needsym;
85   PetscBool    freeaij;
86 
87   /* Schur complement */
88   PetscScalar  *schur;
89   PetscInt     schur_size;
90   PetscInt     *schur_idxs;
91   PetscScalar  *schur_work;
92   PetscBLASInt schur_work_size;
93   PetscInt     schur_solver_type;
94   PetscInt     *schur_pivots;
95   PetscBool    schur_factored;
96   PetscBool    schur_inverted;
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;
110 
111   PetscFunctionBegin;
112   if (!sym) {
113     SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen");
114   }
115   if (bs == 1) { /* already in the correct format */
116     *v    = aa->a;
117     *r    = aa->i;
118     *c    = aa->j;
119     *nnz  = aa->nz;
120     *free = PETSC_FALSE;
121   } else {
122     SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqSBAIJ to MKL Pardiso format still need to be implemented");
123   }
124   PetscFunctionReturn(0);
125 }
126 
127 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
128 {
129   PetscFunctionBegin;
130   SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqBAIJ to MKL Pardiso format still need to be implemented");
131   PetscFunctionReturn(0);
132 }
133 
134 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
135 {
136   Mat_SeqAIJ     *aa = (Mat_SeqAIJ*)A->data;
137   PetscErrorCode ierr;
138 
139   PetscFunctionBegin;
140   if (!sym) { /* already in the correct format */
141     *v    = aa->a;
142     *r    = aa->i;
143     *c    = aa->j;
144     *nnz  = aa->nz;
145     *free = PETSC_FALSE;
146     PetscFunctionReturn(0);
147   }
148   /* need to get the triangular part */
149   if (reuse == MAT_INITIAL_MATRIX) {
150     PetscScalar *vals,*vv;
151     PetscInt    *row,*col,*jj;
152     PetscInt    m = A->rmap->n,nz,i;
153 
154     nz = 0;
155     for (i=0; i<m; i++) {
156       nz += aa->i[i+1] - aa->diag[i];
157     }
158     ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr);
159     ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr);
160     jj = col;
161     vv = vals;
162 
163     row[0] = 0;
164     for (i=0; i<m; i++) {
165       PetscInt    *aj = aa->j + aa->diag[i];
166       PetscScalar *av = aa->a + aa->diag[i];
167       PetscInt    rl = aa->i[i+1] - aa->diag[i],j;
168       for (j=0; j<rl; j++) {
169         *jj = *aj; jj++; aj++;
170         *vv = *av; vv++; av++;
171       }
172       row[i+1]    = row[i] + rl;
173     }
174     *v    = vals;
175     *r    = row;
176     *c    = col;
177     *nnz  = nz;
178     *free = PETSC_TRUE;
179   } else {
180     PetscScalar *vv;
181     PetscInt    m = A->rmap->n,i;
182 
183     vv = *v;
184     for (i=0; i<m; i++) {
185       PetscScalar *av = aa->a + aa->diag[i];
186       PetscInt    rl = aa->i[i+1] - aa->diag[i],j;
187       for (j=0; j<rl; j++) {
188         *vv = *av; vv++; av++;
189       }
190     }
191     *free = PETSC_TRUE;
192   }
193   PetscFunctionReturn(0);
194 }
195 
196 void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm [])
197 {
198   int iparm_copy[IPARM_SIZE], mtype_copy, i;
199 
200   mtype_copy = *mtype;
201   pardisoinit(pt, &mtype_copy, iparm_copy);
202   for(i = 0; i < IPARM_SIZE; i++){
203     iparm[i] = iparm_copy[i];
204   }
205 }
206 
207 static PetscErrorCode MatMKLPardisoFactorSchur_Private(Mat_MKL_PARDISO* mpardiso)
208 {
209   PetscBLASInt   B_N,B_ierr;
210   PetscScalar    *work,val;
211   PetscBLASInt   lwork = -1;
212   PetscErrorCode ierr;
213 
214   PetscFunctionBegin;
215   if (mpardiso->schur_factored) {
216     PetscFunctionReturn(0);
217   }
218   ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr);
219   switch (mpardiso->schur_solver_type) {
220     case 1: /* hermitian solver */
221       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
222       PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,mpardiso->schur,&B_N,&B_ierr));
223       ierr = PetscFPTrapPop();CHKERRQ(ierr);
224       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr);
225       break;
226     case 2: /* symmetric */
227       if (!mpardiso->schur_pivots) {
228         ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr);
229       }
230       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
231       PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&val,&lwork,&B_ierr));
232       ierr = PetscBLASIntCast((PetscInt)PetscRealPart(val),&lwork);CHKERRQ(ierr);
233       ierr = PetscMalloc1(lwork,&work);CHKERRQ(ierr);
234       PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,work,&lwork,&B_ierr));
235       ierr = PetscFree(work);CHKERRQ(ierr);
236       ierr = PetscFPTrapPop();CHKERRQ(ierr);
237       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr);
238       break;
239     default: /* general */
240       if (!mpardiso->schur_pivots) {
241         ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr);
242       }
243       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
244       PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&B_ierr));
245       ierr = PetscFPTrapPop();CHKERRQ(ierr);
246       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr);
247       break;
248   }
249   mpardiso->schur_factored = PETSC_TRUE;
250   PetscFunctionReturn(0);
251 }
252 
253 static PetscErrorCode MatMKLPardisoInvertSchur_Private(Mat_MKL_PARDISO* mpardiso)
254 {
255   PetscBLASInt   B_N,B_ierr;
256   PetscErrorCode ierr;
257 
258   PetscFunctionBegin;
259   ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr);
260   ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr);
261   switch (mpardiso->schur_solver_type) {
262     case 1: /* hermitian solver */
263       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
264       PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,mpardiso->schur,&B_N,&B_ierr));
265       ierr = PetscFPTrapPop();CHKERRQ(ierr);
266       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr);
267       break;
268     case 2: /* symmetric */
269       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
270       PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&B_ierr));
271       ierr = PetscFPTrapPop();CHKERRQ(ierr);
272       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr);
273       break;
274     default: /* general */
275       ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
276       PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&mpardiso->schur_work_size,&B_ierr));
277       ierr = PetscFPTrapPop();CHKERRQ(ierr);
278       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr);
279       break;
280   }
281   mpardiso->schur_inverted = PETSC_TRUE;
282   PetscFunctionReturn(0);
283 }
284 
285 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat_MKL_PARDISO* mpardiso, PetscScalar *B, PetscScalar *X)
286 {
287   PetscScalar    one=1.,zero=0.,*schur_rhs,*schur_sol;
288   PetscBLASInt   B_N,B_Nrhs,B_ierr;
289   char           type[2];
290   PetscErrorCode ierr;
291 
292   PetscFunctionBegin;
293   ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr);
294   ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr);
295   ierr = PetscBLASIntCast(mpardiso->nrhs,&B_Nrhs);CHKERRQ(ierr);
296   if (X == B && mpardiso->schur_inverted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address");
297   if (X != B) { /* using LAPACK *TRS subroutines */
298     ierr = PetscMemcpy(X,B,B_N*B_Nrhs*sizeof(PetscScalar));CHKERRQ(ierr);
299   }
300   schur_rhs = B;
301   schur_sol = X;
302   switch (mpardiso->schur_solver_type) {
303     case 1: /* hermitian solver */
304       if (mpardiso->schur_inverted) { /* BLAShemm should go here */
305         PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N));
306       } else {
307         ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
308         PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,schur_sol,&B_N,&B_ierr));
309         ierr = PetscFPTrapPop();CHKERRQ(ierr);
310         if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRS Lapack routine %d",(int)B_ierr);
311       }
312       break;
313     case 2: /* symmetric solver */
314       if (mpardiso->schur_inverted) {
315         PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N));
316       } else {
317         ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
318         PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr));
319         ierr = PetscFPTrapPop();CHKERRQ(ierr);
320         if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRS Lapack routine %d",(int)B_ierr);
321       }
322       break;
323     default: /* general */
324       switch (mpardiso->iparm[12-1]) {
325         case 1:
326           sprintf(type,"C");
327           break;
328         case 2:
329           sprintf(type,"T");
330           break;
331         default:
332           sprintf(type,"N");
333           break;
334       }
335       if (mpardiso->schur_inverted) {
336         PetscStackCallBLAS("BLASgemm",BLASgemm_(type,"N",&B_N,&B_Nrhs,&B_N,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N));
337       } else {
338         ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr);
339         PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_(type,&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr));
340         ierr = PetscFPTrapPop();CHKERRQ(ierr);
341         if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRS Lapack routine %d",(int)B_ierr);
342       }
343       break;
344   }
345   PetscFunctionReturn(0);
346 }
347 
348 
349 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is)
350 {
351   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
352   const PetscInt  *idxs;
353   PetscInt        size,i;
354   PetscMPIInt     csize;
355   PetscBool       sorted;
356   PetscErrorCode  ierr;
357 
358   PetscFunctionBegin;
359   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr);
360   if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc\n");
361   ierr = ISSorted(is,&sorted);CHKERRQ(ierr);
362   if (!sorted) {
363     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted\n");
364   }
365   ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr);
366   if (mpardiso->schur_size != size) {
367     mpardiso->schur_size = size;
368     ierr = PetscFree2(mpardiso->schur,mpardiso->schur_work);CHKERRQ(ierr);
369     ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr);
370     ierr = PetscFree(mpardiso->schur_pivots);CHKERRQ(ierr);
371     ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr);
372     ierr = PetscMalloc2(size*size,&mpardiso->schur,mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr);
373     ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr);
374   }
375   ierr = PetscMemzero(mpardiso->perm,mpardiso->n*sizeof(INT_TYPE));CHKERRQ(ierr);
376   ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr);
377   ierr = PetscMemcpy(mpardiso->schur_idxs,idxs,size*sizeof(PetscInt));CHKERRQ(ierr);
378   for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1;
379   ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr);
380   if (size) { /* turn on Schur switch if we the set of indices is not empty */
381     mpardiso->iparm[36-1] = 2;
382   }
383   mpardiso->schur_factored = PETSC_FALSE;
384   mpardiso->schur_inverted = PETSC_FALSE;
385   PetscFunctionReturn(0);
386 }
387 
388 PetscErrorCode MatFactorCreateSchurComplement_MKL_PARDISO(Mat F,Mat* S)
389 {
390   Mat             St;
391   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
392   PetscScalar     *array;
393   PetscErrorCode  ierr;
394 
395   PetscFunctionBegin;
396   if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it");
397   else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
398 
399   ierr = MatCreate(PetscObjectComm((PetscObject)F),&St);CHKERRQ(ierr);
400   ierr = MatSetSizes(St,PETSC_DECIDE,PETSC_DECIDE,mpardiso->schur_size,mpardiso->schur_size);CHKERRQ(ierr);
401   ierr = MatSetType(St,MATDENSE);CHKERRQ(ierr);
402   ierr = MatSetUp(St);CHKERRQ(ierr);
403   ierr = MatDenseGetArray(St,&array);CHKERRQ(ierr);
404   ierr = PetscMemcpy(array,mpardiso->schur,mpardiso->schur_size*mpardiso->schur_size*sizeof(PetscScalar));CHKERRQ(ierr);
405   ierr = MatDenseRestoreArray(St,&array);CHKERRQ(ierr);
406   *S = St;
407   PetscFunctionReturn(0);
408 }
409 
410 PetscErrorCode MatFactorGetSchurComplement_MKL_PARDISO(Mat F,Mat* S)
411 {
412   Mat             St;
413   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
414   PetscErrorCode  ierr;
415 
416   PetscFunctionBegin;
417   if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it");
418   else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
419 
420   ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)F),mpardiso->schur_size,mpardiso->schur_size,mpardiso->schur,&St);CHKERRQ(ierr);
421   *S = St;
422   PetscFunctionReturn(0);
423 }
424 
425 PetscErrorCode MatFactorInvertSchurComplement_MKL_PARDISO(Mat F)
426 {
427   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
428   PetscErrorCode  ierr;
429 
430   PetscFunctionBegin;
431   if (!mpardiso->iparm[36-1]) { /* do nothing */
432     PetscFunctionReturn(0);
433   }
434   if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
435   ierr = MatMKLPardisoInvertSchur_Private(mpardiso);CHKERRQ(ierr);
436   PetscFunctionReturn(0);
437 }
438 
439 PetscErrorCode MatFactorFactorizeSchurComplement_MKL_PARDISO(Mat F)
440 {
441   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
442   PetscErrorCode  ierr;
443 
444   PetscFunctionBegin;
445   if (!mpardiso->iparm[36-1]) { /* do nothing */
446     PetscFunctionReturn(0);
447   }
448   if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
449   ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr);
450   PetscFunctionReturn(0);
451 }
452 
453 PetscErrorCode MatFactorSolveSchurComplement_MKL_PARDISO(Mat F, Vec rhs, Vec sol)
454 {
455   Mat_MKL_PARDISO   *mpardiso =(Mat_MKL_PARDISO*)F->data;
456   PetscScalar       *asol,*arhs;
457   PetscErrorCode ierr;
458 
459   PetscFunctionBegin;
460   if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it");
461   else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
462 
463   mpardiso->nrhs = 1;
464   ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr);
465   ierr = VecGetArray(sol,&asol);CHKERRQ(ierr);
466   ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr);
467   ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr);
468   ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr);
469   PetscFunctionReturn(0);
470 }
471 
472 PetscErrorCode MatFactorSolveSchurComplementTranspose_MKL_PARDISO(Mat F, Vec rhs, Vec sol)
473 {
474   Mat_MKL_PARDISO   *mpardiso =(Mat_MKL_PARDISO*)F->data;
475   PetscScalar       *asol,*arhs;
476   PetscInt          oiparm12;
477   PetscErrorCode    ierr;
478 
479   PetscFunctionBegin;
480   if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it");
481   else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before");
482 
483   mpardiso->nrhs = 1;
484   ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr);
485   ierr = VecGetArray(sol,&asol);CHKERRQ(ierr);
486   oiparm12 = mpardiso->iparm[12 - 1];
487   mpardiso->iparm[12 - 1] = 2;
488   ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr);
489   mpardiso->iparm[12 - 1] = oiparm12;
490   ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr);
491   ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr);
492   PetscFunctionReturn(0);
493 }
494 
495 PetscErrorCode MatFactorSetSchurComplementSolverType_MKL_PARDISO(Mat F, PetscInt sym)
496 {
497   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
498 
499   PetscFunctionBegin;
500   if (mpardiso->schur_factored && sym != mpardiso->schur_solver_type) {
501     SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONG,"Cannot change the Schur solver! Schur complement data has been already factored");
502   }
503   mpardiso->schur_solver_type = sym;
504   PetscFunctionReturn(0);
505 }
506 
507 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A)
508 {
509   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
510   PetscErrorCode  ierr;
511 
512   PetscFunctionBegin;
513   if (mat_mkl_pardiso->CleanUp) {
514     mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY;
515 
516     MKL_PARDISO (mat_mkl_pardiso->pt,
517       &mat_mkl_pardiso->maxfct,
518       &mat_mkl_pardiso->mnum,
519       &mat_mkl_pardiso->mtype,
520       &mat_mkl_pardiso->phase,
521       &mat_mkl_pardiso->n,
522       NULL,
523       NULL,
524       NULL,
525       NULL,
526       &mat_mkl_pardiso->nrhs,
527       mat_mkl_pardiso->iparm,
528       &mat_mkl_pardiso->msglvl,
529       NULL,
530       NULL,
531       &mat_mkl_pardiso->err);
532   }
533   ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr);
534   ierr = PetscFree2(mat_mkl_pardiso->schur,mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
535   ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr);
536   ierr = PetscFree(mat_mkl_pardiso->schur_pivots);CHKERRQ(ierr);
537   if (mat_mkl_pardiso->freeaij) {
538     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
539     ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
540   }
541   ierr = PetscFree(A->data);CHKERRQ(ierr);
542 
543   /* clear composed functions */
544   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr);
545   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr);
546   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorCreateSchurComplement_C",NULL);CHKERRQ(ierr);
547   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSchurComplement_C",NULL);CHKERRQ(ierr);
548   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorInvertSchurComplement_C",NULL);CHKERRQ(ierr);
549   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorFactorizeSchurComplement_C",NULL);CHKERRQ(ierr);
550   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplement_C",NULL);CHKERRQ(ierr);
551   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplementTranspose_C",NULL);CHKERRQ(ierr);
552   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurComplementSolverType_C",NULL);CHKERRQ(ierr);
553   ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr);
554   PetscFunctionReturn(0);
555 }
556 
557 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce)
558 {
559   PetscFunctionBegin;
560   if (reduce) { /* data given for the whole matrix */
561     PetscInt i,m=0,p=0;
562     for (i=0;i<mpardiso->nrhs;i++) {
563       PetscInt j;
564       for (j=0;j<mpardiso->schur_size;j++) {
565         schur[p+j] = whole[m+mpardiso->schur_idxs[j]];
566       }
567       m += mpardiso->n;
568       p += mpardiso->schur_size;
569     }
570   } else { /* from Schur to whole */
571     PetscInt i,m=0,p=0;
572     for (i=0;i<mpardiso->nrhs;i++) {
573       PetscInt j;
574       for (j=0;j<mpardiso->schur_size;j++) {
575         whole[m+mpardiso->schur_idxs[j]] = schur[p+j];
576       }
577       m += mpardiso->n;
578       p += mpardiso->schur_size;
579     }
580   }
581   PetscFunctionReturn(0);
582 }
583 
584 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x)
585 {
586   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
587   PetscErrorCode    ierr;
588   PetscScalar       *xarray;
589   const PetscScalar *barray;
590 
591   PetscFunctionBegin;
592   mat_mkl_pardiso->nrhs = 1;
593   ierr = VecGetArray(x,&xarray);CHKERRQ(ierr);
594   ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr);
595 
596   if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
597   else  mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
598 
599   if (barray == xarray) { /* if the two vectors share the same memory */
600     PetscScalar *work;
601     if (!mat_mkl_pardiso->schur_work) {
602       ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr);
603     } else {
604       work = mat_mkl_pardiso->schur_work;
605     }
606     mat_mkl_pardiso->iparm[6-1] = 1;
607     MKL_PARDISO (mat_mkl_pardiso->pt,
608       &mat_mkl_pardiso->maxfct,
609       &mat_mkl_pardiso->mnum,
610       &mat_mkl_pardiso->mtype,
611       &mat_mkl_pardiso->phase,
612       &mat_mkl_pardiso->n,
613       mat_mkl_pardiso->a,
614       mat_mkl_pardiso->ia,
615       mat_mkl_pardiso->ja,
616       NULL,
617       &mat_mkl_pardiso->nrhs,
618       mat_mkl_pardiso->iparm,
619       &mat_mkl_pardiso->msglvl,
620       (void*)xarray,
621       (void*)work,
622       &mat_mkl_pardiso->err);
623     if (!mat_mkl_pardiso->schur_work) {
624       ierr = PetscFree(work);CHKERRQ(ierr);
625     }
626   } else {
627     mat_mkl_pardiso->iparm[6-1] = 0;
628     MKL_PARDISO (mat_mkl_pardiso->pt,
629       &mat_mkl_pardiso->maxfct,
630       &mat_mkl_pardiso->mnum,
631       &mat_mkl_pardiso->mtype,
632       &mat_mkl_pardiso->phase,
633       &mat_mkl_pardiso->n,
634       mat_mkl_pardiso->a,
635       mat_mkl_pardiso->ia,
636       mat_mkl_pardiso->ja,
637       mat_mkl_pardiso->perm,
638       &mat_mkl_pardiso->nrhs,
639       mat_mkl_pardiso->iparm,
640       &mat_mkl_pardiso->msglvl,
641       (void*)barray,
642       (void*)xarray,
643       &mat_mkl_pardiso->err);
644   }
645   ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr);
646 
647   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual\n",mat_mkl_pardiso->err);
648 
649   if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
650     PetscInt shift = mat_mkl_pardiso->schur_size;
651 
652     /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
653     if (!mat_mkl_pardiso->schur_inverted) {
654       shift = 0;
655     }
656 
657     if (!mat_mkl_pardiso->solve_interior) {
658       /* solve Schur complement */
659       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
660       ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
661       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
662     } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substitued to xarray[schur] will be neglected */
663       PetscInt i;
664       for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
665         xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
666       }
667     }
668 
669     /* expansion phase */
670     mat_mkl_pardiso->iparm[6-1] = 1;
671     mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
672     MKL_PARDISO (mat_mkl_pardiso->pt,
673       &mat_mkl_pardiso->maxfct,
674       &mat_mkl_pardiso->mnum,
675       &mat_mkl_pardiso->mtype,
676       &mat_mkl_pardiso->phase,
677       &mat_mkl_pardiso->n,
678       mat_mkl_pardiso->a,
679       mat_mkl_pardiso->ia,
680       mat_mkl_pardiso->ja,
681       mat_mkl_pardiso->perm,
682       &mat_mkl_pardiso->nrhs,
683       mat_mkl_pardiso->iparm,
684       &mat_mkl_pardiso->msglvl,
685       (void*)xarray,
686       (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
687       &mat_mkl_pardiso->err);
688 
689     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual\n",mat_mkl_pardiso->err);
690     mat_mkl_pardiso->iparm[6-1] = 0;
691   }
692   ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr);
693   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
694   PetscFunctionReturn(0);
695 }
696 
697 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x)
698 {
699   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
700   PetscInt        oiparm12;
701   PetscErrorCode  ierr;
702 
703   PetscFunctionBegin;
704   oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
705   mat_mkl_pardiso->iparm[12 - 1] = 2;
706   ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr);
707   mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
708   PetscFunctionReturn(0);
709 }
710 
711 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X)
712 {
713   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
714   PetscErrorCode    ierr;
715   PetscScalar       *barray, *xarray;
716   PetscBool         flg;
717 
718   PetscFunctionBegin;
719   ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr);
720   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix");
721   ierr = PetscObjectTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr);
722   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix");
723 
724   ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
725 
726   if (mat_mkl_pardiso->nrhs > 0) {
727     ierr = MatDenseGetArray(B,&barray);
728     ierr = MatDenseGetArray(X,&xarray);
729 
730     if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location");
731     if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
732     else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
733     mat_mkl_pardiso->iparm[6-1] = 0;
734 
735     MKL_PARDISO (mat_mkl_pardiso->pt,
736       &mat_mkl_pardiso->maxfct,
737       &mat_mkl_pardiso->mnum,
738       &mat_mkl_pardiso->mtype,
739       &mat_mkl_pardiso->phase,
740       &mat_mkl_pardiso->n,
741       mat_mkl_pardiso->a,
742       mat_mkl_pardiso->ia,
743       mat_mkl_pardiso->ja,
744       mat_mkl_pardiso->perm,
745       &mat_mkl_pardiso->nrhs,
746       mat_mkl_pardiso->iparm,
747       &mat_mkl_pardiso->msglvl,
748       (void*)barray,
749       (void*)xarray,
750       &mat_mkl_pardiso->err);
751     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual\n",mat_mkl_pardiso->err);
752 
753     if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
754       PetscScalar *o_schur_work = NULL;
755       PetscInt    shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale;
756       PetscInt    mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs;
757 
758       /* allocate extra memory if it is needed */
759       scale = 1;
760       if (mat_mkl_pardiso->schur_inverted) {
761         scale = 2;
762       }
763       mem *= scale;
764       if (mem > mat_mkl_pardiso->schur_work_size) {
765         o_schur_work = mat_mkl_pardiso->schur_work;
766         ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
767       }
768 
769       /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
770       if (!mat_mkl_pardiso->schur_inverted) shift = 0;
771 
772       /* solve Schur complement */
773       if (!mat_mkl_pardiso->solve_interior) {
774         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
775         ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
776         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
777       } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substitued to xarray[schur,n] will be neglected */
778         PetscInt i,n,m=0;
779         for (n=0;n<mat_mkl_pardiso->nrhs;n++) {
780           for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
781             xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.;
782           }
783           m += mat_mkl_pardiso->n;
784         }
785       }
786 
787       /* expansion phase */
788       mat_mkl_pardiso->iparm[6-1] = 1;
789       mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
790       MKL_PARDISO (mat_mkl_pardiso->pt,
791         &mat_mkl_pardiso->maxfct,
792         &mat_mkl_pardiso->mnum,
793         &mat_mkl_pardiso->mtype,
794         &mat_mkl_pardiso->phase,
795         &mat_mkl_pardiso->n,
796         mat_mkl_pardiso->a,
797         mat_mkl_pardiso->ia,
798         mat_mkl_pardiso->ja,
799         mat_mkl_pardiso->perm,
800         &mat_mkl_pardiso->nrhs,
801         mat_mkl_pardiso->iparm,
802         &mat_mkl_pardiso->msglvl,
803         (void*)xarray,
804         (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
805         &mat_mkl_pardiso->err);
806       if (o_schur_work) { /* restore original schur_work (minimal size) */
807         ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
808         mat_mkl_pardiso->schur_work = o_schur_work;
809       }
810       if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual\n",mat_mkl_pardiso->err);
811       mat_mkl_pardiso->iparm[6-1] = 0;
812     }
813   }
814   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
815   PetscFunctionReturn(0);
816 }
817 
818 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info)
819 {
820   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data;
821   PetscErrorCode  ierr;
822 
823   PetscFunctionBegin;
824   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
825   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);
826 
827   mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
828   MKL_PARDISO (mat_mkl_pardiso->pt,
829     &mat_mkl_pardiso->maxfct,
830     &mat_mkl_pardiso->mnum,
831     &mat_mkl_pardiso->mtype,
832     &mat_mkl_pardiso->phase,
833     &mat_mkl_pardiso->n,
834     mat_mkl_pardiso->a,
835     mat_mkl_pardiso->ia,
836     mat_mkl_pardiso->ja,
837     mat_mkl_pardiso->perm,
838     &mat_mkl_pardiso->nrhs,
839     mat_mkl_pardiso->iparm,
840     &mat_mkl_pardiso->msglvl,
841     NULL,
842     (void*)mat_mkl_pardiso->schur,
843     &mat_mkl_pardiso->err);
844   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual\n",mat_mkl_pardiso->err);
845 
846   if (mat_mkl_pardiso->schur) { /* schur output from pardiso is in row major format */
847     PetscInt j,k,n=mat_mkl_pardiso->schur_size;
848     if (!mat_mkl_pardiso->schur_solver_type) {
849       for (j=0; j<n; j++) {
850         for (k=0; k<j; k++) {
851           PetscScalar tmp = mat_mkl_pardiso->schur[j + k*n];
852           mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n];
853           mat_mkl_pardiso->schur[k + j*n] = tmp;
854         }
855       }
856     } else { /* we could use row-major in LAPACK routines (e.g. use 'U' instead of 'L'; instead, I prefer consistency between data structures and swap to column major */
857       for (j=0; j<n; j++) {
858         for (k=0; k<j; k++) {
859           mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n];
860         }
861       }
862     }
863   }
864   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
865   mat_mkl_pardiso->CleanUp  = PETSC_TRUE;
866   mat_mkl_pardiso->schur_factored = PETSC_FALSE;
867   mat_mkl_pardiso->schur_inverted = PETSC_FALSE;
868   PetscFunctionReturn(0);
869 }
870 
871 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A)
872 {
873   Mat_MKL_PARDISO     *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
874   PetscErrorCode      ierr;
875   PetscInt            icntl,threads=1;
876   PetscBool           flg;
877 
878   PetscFunctionBegin;
879   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr);
880 
881   ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr);
882   if (flg) PetscSetMKL_PARDISOThreads((int)threads);
883 
884   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);
885   if (flg) mat_mkl_pardiso->maxfct = icntl;
886 
887   ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr);
888   if (flg) mat_mkl_pardiso->mnum = icntl;
889 
890   ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr);
891   if (flg) mat_mkl_pardiso->msglvl = icntl;
892 
893   ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr);
894   if(flg){
895     void *pt[IPARM_SIZE];
896     mat_mkl_pardiso->mtype = icntl;
897     MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
898 #if defined(PETSC_USE_REAL_SINGLE)
899     mat_mkl_pardiso->iparm[27] = 1;
900 #else
901     mat_mkl_pardiso->iparm[27] = 0;
902 #endif
903     mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */
904   }
905   ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr);
906 
907   if (flg && icntl != 0) {
908     ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr);
909     if (flg) mat_mkl_pardiso->iparm[1] = icntl;
910 
911     ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr);
912     if (flg) mat_mkl_pardiso->iparm[3] = icntl;
913 
914     ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr);
915     if (flg) mat_mkl_pardiso->iparm[4] = icntl;
916 
917     ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr);
918     if (flg) mat_mkl_pardiso->iparm[5] = icntl;
919 
920     ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr);
921     if (flg) mat_mkl_pardiso->iparm[7] = icntl;
922 
923     ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr);
924     if (flg) mat_mkl_pardiso->iparm[9] = icntl;
925 
926     ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr);
927     if (flg) mat_mkl_pardiso->iparm[10] = icntl;
928 
929     ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr);
930     if (flg) mat_mkl_pardiso->iparm[11] = icntl;
931 
932     ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr);
933     if (flg) mat_mkl_pardiso->iparm[12] = icntl;
934 
935     ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr);
936     if (flg) mat_mkl_pardiso->iparm[17] = icntl;
937 
938     ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr);
939     if (flg) mat_mkl_pardiso->iparm[18] = icntl;
940 
941     ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr);
942     if (flg) mat_mkl_pardiso->iparm[20] = icntl;
943 
944     ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr);
945     if (flg) mat_mkl_pardiso->iparm[23] = icntl;
946 
947     ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr);
948     if (flg) mat_mkl_pardiso->iparm[24] = icntl;
949 
950     ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr);
951     if (flg) mat_mkl_pardiso->iparm[26] = icntl;
952 
953     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);
954     if (flg) mat_mkl_pardiso->iparm[30] = icntl;
955 
956     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);
957     if (flg) mat_mkl_pardiso->iparm[33] = icntl;
958 
959     ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr);
960     if (flg) mat_mkl_pardiso->iparm[59] = icntl;
961   }
962   PetscOptionsEnd();
963   PetscFunctionReturn(0);
964 }
965 
966 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
967 {
968   PetscErrorCode ierr;
969   PetscInt       i;
970 
971   PetscFunctionBegin;
972   for ( i = 0; i < IPARM_SIZE; i++ ){
973     mat_mkl_pardiso->iparm[i] = 0;
974   }
975   for ( i = 0; i < IPARM_SIZE; i++ ){
976     mat_mkl_pardiso->pt[i] = 0;
977   }
978   /* Default options for both sym and unsym */
979   mat_mkl_pardiso->iparm[ 0] =  1; /* Solver default parameters overriden with provided by iparm */
980   mat_mkl_pardiso->iparm[ 1] =  2; /* Metis reordering */
981   mat_mkl_pardiso->iparm[ 5] =  0; /* Write solution into x */
982   mat_mkl_pardiso->iparm[ 7] =  0; /* Max number of iterative refinement steps */
983   mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
984   mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
985 #if 0
986   mat_mkl_pardiso->iparm[23] =  1; /* Parallel factorization control*/
987 #endif
988   mat_mkl_pardiso->iparm[34] =  1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
989   mat_mkl_pardiso->iparm[39] =  0; /* Input: matrix/rhs/solution stored on master */
990 
991   mat_mkl_pardiso->CleanUp   = PETSC_FALSE;
992   mat_mkl_pardiso->maxfct    = 1; /* Maximum number of numerical factorizations. */
993   mat_mkl_pardiso->mnum      = 1; /* Which factorization to use. */
994   mat_mkl_pardiso->msglvl    = 0; /* 0: do not print 1: Print statistical information in file */
995   mat_mkl_pardiso->phase     = -1;
996   mat_mkl_pardiso->err       = 0;
997 
998   mat_mkl_pardiso->n         = A->rmap->N;
999   mat_mkl_pardiso->nrhs      = 1;
1000   mat_mkl_pardiso->err       = 0;
1001   mat_mkl_pardiso->phase     = -1;
1002 
1003   if(ftype == MAT_FACTOR_LU){
1004     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
1005     mat_mkl_pardiso->iparm[10] =  1; /* Use nonsymmetric permutation and scaling MPS */
1006     mat_mkl_pardiso->iparm[12] =  1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
1007 
1008   } else {
1009     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
1010     mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
1011     mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
1012 /*    mat_mkl_pardiso->iparm[20] =  1; */ /* Apply 1x1 and 2x2 Bunch-Kaufman pivoting during the factorization process */
1013 #if defined(PETSC_USE_DEBUG)
1014     mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
1015 #endif
1016   }
1017   ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr);
1018   for(i = 0; i < A->rmap->N; i++){
1019     mat_mkl_pardiso->perm[i] = 0;
1020   }
1021   mat_mkl_pardiso->schur_size = 0;
1022   PetscFunctionReturn(0);
1023 }
1024 
1025 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info)
1026 {
1027   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
1028   PetscErrorCode  ierr;
1029 
1030   PetscFunctionBegin;
1031   mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
1032   ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr);
1033 
1034   /* throw away any previously computed structure */
1035   if (mat_mkl_pardiso->freeaij) {
1036     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
1037     ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
1038   }
1039   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);
1040   mat_mkl_pardiso->n = A->rmap->N;
1041 
1042   mat_mkl_pardiso->phase = JOB_ANALYSIS;
1043 
1044   MKL_PARDISO (mat_mkl_pardiso->pt,
1045     &mat_mkl_pardiso->maxfct,
1046     &mat_mkl_pardiso->mnum,
1047     &mat_mkl_pardiso->mtype,
1048     &mat_mkl_pardiso->phase,
1049     &mat_mkl_pardiso->n,
1050     mat_mkl_pardiso->a,
1051     mat_mkl_pardiso->ia,
1052     mat_mkl_pardiso->ja,
1053     mat_mkl_pardiso->perm,
1054     &mat_mkl_pardiso->nrhs,
1055     mat_mkl_pardiso->iparm,
1056     &mat_mkl_pardiso->msglvl,
1057     NULL,
1058     NULL,
1059     &mat_mkl_pardiso->err);
1060   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d\n. Please check manual",mat_mkl_pardiso->err);
1061 
1062   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
1063 
1064   if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
1065   else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
1066 
1067   F->ops->solve           = MatSolve_MKL_PARDISO;
1068   F->ops->solvetranspose  = MatSolveTranspose_MKL_PARDISO;
1069   F->ops->matsolve        = MatMatSolve_MKL_PARDISO;
1070   PetscFunctionReturn(0);
1071 }
1072 
1073 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
1074 {
1075   PetscErrorCode ierr;
1076 
1077   PetscFunctionBegin;
1078   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
1079   PetscFunctionReturn(0);
1080 }
1081 
1082 #if !defined(PETSC_USE_COMPLEX)
1083 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,int *nneg,int *nzero,int *npos)
1084 {
1085   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data;
1086 
1087   PetscFunctionBegin;
1088   if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
1089   if (npos) *npos = mat_mkl_pardiso->iparm[21];
1090   if (nzero) *nzero = F->rmap->N -(mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
1091   PetscFunctionReturn(0);
1092 }
1093 #endif
1094 
1095 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info)
1096 {
1097   PetscErrorCode ierr;
1098 
1099   PetscFunctionBegin;
1100   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
1101 #if defined(PETSC_USE_COMPLEX)
1102   F->ops->getinertia = NULL;
1103 #else
1104   F->ops->getinertia = MatGetInertia_MKL_PARDISO;
1105 #endif
1106   PetscFunctionReturn(0);
1107 }
1108 
1109 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
1110 {
1111   PetscErrorCode    ierr;
1112   PetscBool         iascii;
1113   PetscViewerFormat format;
1114   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
1115   PetscInt          i;
1116 
1117   PetscFunctionBegin;
1118   if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0);
1119 
1120   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1121   if (iascii) {
1122     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
1123     if (format == PETSC_VIEWER_ASCII_INFO) {
1124       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr);
1125       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase:             %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr);
1126       for(i = 1; i <= 64; i++){
1127         ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]:     %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr);
1128       }
1129       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct:     %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr);
1130       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum:     %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr);
1131       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype:     %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr);
1132       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n:     %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr);
1133       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs:     %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
1134       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl:     %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr);
1135     }
1136   }
1137   PetscFunctionReturn(0);
1138 }
1139 
1140 
1141 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
1142 {
1143   Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)A->data;
1144 
1145   PetscFunctionBegin;
1146   info->block_size        = 1.0;
1147   info->nz_used           = mat_mkl_pardiso->nz;
1148   info->nz_allocated      = mat_mkl_pardiso->nz;
1149   info->nz_unneeded       = 0.0;
1150   info->assemblies        = 0.0;
1151   info->mallocs           = 0.0;
1152   info->memory            = 0.0;
1153   info->fill_ratio_given  = 0;
1154   info->fill_ratio_needed = 0;
1155   info->factor_mallocs    = 0;
1156   PetscFunctionReturn(0);
1157 }
1158 
1159 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival)
1160 {
1161   Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)F->data;
1162 
1163   PetscFunctionBegin;
1164   if(icntl <= 64){
1165     mat_mkl_pardiso->iparm[icntl - 1] = ival;
1166   } else {
1167     if(icntl == 65) PetscSetMKL_PARDISOThreads(ival);
1168     else if(icntl == 66) mat_mkl_pardiso->maxfct = ival;
1169     else if(icntl == 67) mat_mkl_pardiso->mnum = ival;
1170     else if(icntl == 68) mat_mkl_pardiso->msglvl = ival;
1171     else if(icntl == 69){
1172       void *pt[IPARM_SIZE];
1173       mat_mkl_pardiso->mtype = ival;
1174       MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
1175 #if defined(PETSC_USE_REAL_SINGLE)
1176       mat_mkl_pardiso->iparm[27] = 1;
1177 #else
1178       mat_mkl_pardiso->iparm[27] = 0;
1179 #endif
1180       mat_mkl_pardiso->iparm[34] = 1;
1181     } else if(icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival;
1182   }
1183   PetscFunctionReturn(0);
1184 }
1185 
1186 /*@
1187   MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters
1188 
1189    Logically Collective on Mat
1190 
1191    Input Parameters:
1192 +  F - the factored matrix obtained by calling MatGetFactor()
1193 .  icntl - index of Mkl_Pardiso parameter
1194 -  ival - value of Mkl_Pardiso parameter
1195 
1196   Options Database:
1197 .   -mat_mkl_pardiso_<icntl> <ival>
1198 
1199    Level: beginner
1200 
1201    References:
1202 .      Mkl_Pardiso Users' Guide
1203 
1204 .seealso: MatGetFactor()
1205 @*/
1206 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival)
1207 {
1208   PetscErrorCode ierr;
1209 
1210   PetscFunctionBegin;
1211   ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr);
1212   PetscFunctionReturn(0);
1213 }
1214 
1215 /*MC
1216   MATSOLVERMKL_PARDISO -  A matrix type providing direct solvers (LU) for
1217   sequential matrices via the external package MKL_PARDISO.
1218 
1219   Works with MATSEQAIJ matrices
1220 
1221   Use -pc_type lu -pc_factor_mat_solver_package mkl_pardiso to us this direct solver
1222 
1223   Options Database Keys:
1224 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO
1225 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
1226 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
1227 . -mat_mkl_pardiso_68 - Message level information
1228 . -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
1229 . -mat_mkl_pardiso_1  - Use default values
1230 . -mat_mkl_pardiso_2  - Fill-in reducing ordering for the input matrix
1231 . -mat_mkl_pardiso_4  - Preconditioned CGS/CG
1232 . -mat_mkl_pardiso_5  - User permutation
1233 . -mat_mkl_pardiso_6  - Write solution on x
1234 . -mat_mkl_pardiso_8  - Iterative refinement step
1235 . -mat_mkl_pardiso_10 - Pivoting perturbation
1236 . -mat_mkl_pardiso_11 - Scaling vectors
1237 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
1238 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
1239 . -mat_mkl_pardiso_18 - Numbers of non-zero elements
1240 . -mat_mkl_pardiso_19 - Report number of floating point operations
1241 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
1242 . -mat_mkl_pardiso_24 - Parallel factorization control
1243 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
1244 . -mat_mkl_pardiso_27 - Matrix checker
1245 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
1246 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
1247 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode
1248 
1249   Level: beginner
1250 
1251   For more information please check  mkl_pardiso manual
1252 
1253 .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage
1254 
1255 M*/
1256 static PetscErrorCode MatFactorGetSolverPackage_mkl_pardiso(Mat A, const MatSolverPackage *type)
1257 {
1258   PetscFunctionBegin;
1259   *type = MATSOLVERMKL_PARDISO;
1260   PetscFunctionReturn(0);
1261 }
1262 
1263 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F)
1264 {
1265   Mat             B;
1266   PetscErrorCode  ierr;
1267   Mat_MKL_PARDISO *mat_mkl_pardiso;
1268   PetscBool       isSeqAIJ,isSeqBAIJ,isSeqSBAIJ;
1269 
1270   PetscFunctionBegin;
1271   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
1272   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr);
1273   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
1274   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1275   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
1276   ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr);
1277   ierr = MatSetUp(B);CHKERRQ(ierr);
1278 
1279   ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr);
1280   B->data = mat_mkl_pardiso;
1281 
1282   ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr);
1283   if (ftype == MAT_FACTOR_LU) {
1284     B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1285     B->factortype            = MAT_FACTOR_LU;
1286     mat_mkl_pardiso->needsym = PETSC_FALSE;
1287     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1288     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1289     else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1290     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name);
1291     mat_mkl_pardiso->schur_solver_type = 0;
1292 #if defined(PETSC_USE_COMPLEX)
1293     mat_mkl_pardiso->mtype = 13;
1294 #else
1295     if (A->structurally_symmetric) mat_mkl_pardiso->mtype = 1;
1296     else                           mat_mkl_pardiso->mtype = 11;
1297 #endif
1298   } else {
1299 #if defined(PETSC_USE_COMPLEX)
1300     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with complex scalars! Use MAT_FACTOR_LU instead",((PetscObject)A)->type_name);
1301 #endif
1302     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1303     B->factortype                  = MAT_FACTOR_CHOLESKY;
1304     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1305     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1306     else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1307     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name);
1308 
1309     mat_mkl_pardiso->needsym = PETSC_TRUE;
1310     if (A->spd_set && A->spd) {
1311       mat_mkl_pardiso->schur_solver_type = 1;
1312       mat_mkl_pardiso->mtype = 2;
1313     } else {
1314       mat_mkl_pardiso->schur_solver_type = 2;
1315       mat_mkl_pardiso->mtype = -2;
1316     }
1317   }
1318   B->ops->destroy          = MatDestroy_MKL_PARDISO;
1319   B->ops->view             = MatView_MKL_PARDISO;
1320   B->factortype            = ftype;
1321   B->ops->getinfo          = MatGetInfo_MKL_PARDISO;
1322   B->assembled             = PETSC_TRUE;
1323 
1324   ierr = PetscFree(B->solvertype);CHKERRQ(ierr);
1325   ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr);
1326 
1327   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mkl_pardiso);CHKERRQ(ierr);
1328   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr);
1329   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MKL_PARDISO);CHKERRQ(ierr);
1330   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MKL_PARDISO);CHKERRQ(ierr);
1331   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MKL_PARDISO);CHKERRQ(ierr);
1332   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorFactorizeSchurComplement_C",MatFactorFactorizeSchurComplement_MKL_PARDISO);CHKERRQ(ierr);
1333   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MKL_PARDISO);CHKERRQ(ierr);
1334   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MKL_PARDISO);CHKERRQ(ierr);
1335   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurComplementSolverType_C",MatFactorSetSchurComplementSolverType_MKL_PARDISO);CHKERRQ(ierr);
1336   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr);
1337 
1338   *F = B;
1339   PetscFunctionReturn(0);
1340 }
1341 
1342 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MKL_Pardiso(void)
1343 {
1344   PetscErrorCode ierr;
1345 
1346   PetscFunctionBegin;
1347   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1348   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1349   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1350   PetscFunctionReturn(0);
1351 }
1352 
1353