xref: /petsc/src/mat/impls/aij/seq/mkl_pardiso/mkl_pardiso.c (revision 9ef679b9b397ea7f8b0ffa0e16e2dbe668d3f68d)
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 = VecGetArrayWrite(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     if (!mat_mkl_pardiso->solve_interior) {
473       PetscInt shift = mat_mkl_pardiso->schur_size;
474 
475       ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr);
476       /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
477       if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
478 
479       /* solve Schur complement */
480       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
481       ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
482       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
483     } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */
484       PetscInt i;
485       for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
486         xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
487       }
488     }
489 
490     /* expansion phase */
491     mat_mkl_pardiso->iparm[6-1] = 1;
492     mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
493     MKL_PARDISO (mat_mkl_pardiso->pt,
494       &mat_mkl_pardiso->maxfct,
495       &mat_mkl_pardiso->mnum,
496       &mat_mkl_pardiso->mtype,
497       &mat_mkl_pardiso->phase,
498       &mat_mkl_pardiso->n,
499       mat_mkl_pardiso->a,
500       mat_mkl_pardiso->ia,
501       mat_mkl_pardiso->ja,
502       mat_mkl_pardiso->perm,
503       &mat_mkl_pardiso->nrhs,
504       mat_mkl_pardiso->iparm,
505       &mat_mkl_pardiso->msglvl,
506       (void*)xarray,
507       (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
508       &mat_mkl_pardiso->err);
509 
510     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
511     mat_mkl_pardiso->iparm[6-1] = 0;
512   }
513   ierr = VecRestoreArrayWrite(x,&xarray);CHKERRQ(ierr);
514   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
515   PetscFunctionReturn(0);
516 }
517 
518 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x)
519 {
520   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
521   PetscInt        oiparm12;
522   PetscErrorCode  ierr;
523 
524   PetscFunctionBegin;
525   oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
526   mat_mkl_pardiso->iparm[12 - 1] = 2;
527   ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr);
528   mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
529   PetscFunctionReturn(0);
530 }
531 
532 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X)
533 {
534   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
535   PetscErrorCode    ierr;
536   const PetscScalar *barray;
537   PetscScalar       *xarray;
538   PetscBool         flg;
539 
540   PetscFunctionBegin;
541   ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr);
542   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix");
543   if (X != B) {
544     ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr);
545     if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix");
546   }
547 
548   ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
549 
550   if (mat_mkl_pardiso->nrhs > 0) {
551     ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr);
552     ierr = MatDenseGetArrayWrite(X,&xarray);CHKERRQ(ierr);
553 
554     if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location");
555     if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
556     else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
557 
558     MKL_PARDISO (mat_mkl_pardiso->pt,
559       &mat_mkl_pardiso->maxfct,
560       &mat_mkl_pardiso->mnum,
561       &mat_mkl_pardiso->mtype,
562       &mat_mkl_pardiso->phase,
563       &mat_mkl_pardiso->n,
564       mat_mkl_pardiso->a,
565       mat_mkl_pardiso->ia,
566       mat_mkl_pardiso->ja,
567       mat_mkl_pardiso->perm,
568       &mat_mkl_pardiso->nrhs,
569       mat_mkl_pardiso->iparm,
570       &mat_mkl_pardiso->msglvl,
571       (void*)barray,
572       (void*)xarray,
573       &mat_mkl_pardiso->err);
574     if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
575 
576     ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr);
577     if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
578       PetscScalar *o_schur_work = NULL;
579 
580       /* solve Schur complement */
581       if (!mat_mkl_pardiso->solve_interior) {
582         PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale;
583         PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs;
584 
585         ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr);
586         /* allocate extra memory if it is needed */
587         scale = 1;
588         if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2;
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         /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
595         if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
596         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
597         ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
598         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
599       } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */
600         PetscInt i,n,m=0;
601         for (n=0;n<mat_mkl_pardiso->nrhs;n++) {
602           for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
603             xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.;
604           }
605           m += mat_mkl_pardiso->n;
606         }
607       }
608 
609       /* expansion phase */
610       mat_mkl_pardiso->iparm[6-1] = 1;
611       mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
612       MKL_PARDISO (mat_mkl_pardiso->pt,
613         &mat_mkl_pardiso->maxfct,
614         &mat_mkl_pardiso->mnum,
615         &mat_mkl_pardiso->mtype,
616         &mat_mkl_pardiso->phase,
617         &mat_mkl_pardiso->n,
618         mat_mkl_pardiso->a,
619         mat_mkl_pardiso->ia,
620         mat_mkl_pardiso->ja,
621         mat_mkl_pardiso->perm,
622         &mat_mkl_pardiso->nrhs,
623         mat_mkl_pardiso->iparm,
624         &mat_mkl_pardiso->msglvl,
625         (void*)xarray,
626         (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
627         &mat_mkl_pardiso->err);
628       if (o_schur_work) { /* restore original schur_work (minimal size) */
629         ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
630         mat_mkl_pardiso->schur_work = o_schur_work;
631       }
632       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);
633       mat_mkl_pardiso->iparm[6-1] = 0;
634     }
635     ierr = MatDenseRestoreArrayWrite(X,&xarray);CHKERRQ(ierr);
636   }
637   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
638   PetscFunctionReturn(0);
639 }
640 
641 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info)
642 {
643   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data;
644   PetscErrorCode  ierr;
645 
646   PetscFunctionBegin;
647   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
648   ierr = (*mat_mkl_pardiso->Convert)(A,mat_mkl_pardiso->needsym,MAT_REUSE_MATRIX,&mat_mkl_pardiso->freeaij,&mat_mkl_pardiso->nz,&mat_mkl_pardiso->ia,&mat_mkl_pardiso->ja,(PetscScalar**)&mat_mkl_pardiso->a);CHKERRQ(ierr);
649 
650   mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
651   MKL_PARDISO (mat_mkl_pardiso->pt,
652     &mat_mkl_pardiso->maxfct,
653     &mat_mkl_pardiso->mnum,
654     &mat_mkl_pardiso->mtype,
655     &mat_mkl_pardiso->phase,
656     &mat_mkl_pardiso->n,
657     mat_mkl_pardiso->a,
658     mat_mkl_pardiso->ia,
659     mat_mkl_pardiso->ja,
660     mat_mkl_pardiso->perm,
661     &mat_mkl_pardiso->nrhs,
662     mat_mkl_pardiso->iparm,
663     &mat_mkl_pardiso->msglvl,
664     NULL,
665     (void*)mat_mkl_pardiso->schur,
666     &mat_mkl_pardiso->err);
667   if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err);
668 
669   /* report flops */
670   if (mat_mkl_pardiso->iparm[18] > 0) {
671     ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr);
672   }
673 
674   if (F->schur) { /* schur output from pardiso is in row major format */
675 #if defined(PETSC_HAVE_CUDA)
676     F->schur->offloadmask = PETSC_OFFLOAD_CPU;
677 #endif
678     ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr);
679     ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr);
680   }
681   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
682   mat_mkl_pardiso->CleanUp  = PETSC_TRUE;
683   PetscFunctionReturn(0);
684 }
685 
686 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A)
687 {
688   Mat_MKL_PARDISO     *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
689   PetscErrorCode      ierr;
690   PetscInt            icntl,bs,threads=1;
691   PetscBool           flg;
692 
693   PetscFunctionBegin;
694   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr);
695 
696   ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr);
697   if (flg) PetscSetMKL_PARDISOThreads((int)threads);
698 
699   ierr = PetscOptionsInt("-mat_mkl_pardiso_66","Maximum number of factors with identical sparsity structure that must be kept in memory at the same time","None",mat_mkl_pardiso->maxfct,&icntl,&flg);CHKERRQ(ierr);
700   if (flg) mat_mkl_pardiso->maxfct = icntl;
701 
702   ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr);
703   if (flg) mat_mkl_pardiso->mnum = icntl;
704 
705   ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr);
706   if (flg) mat_mkl_pardiso->msglvl = icntl;
707 
708   ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr);
709   if (flg) {
710     void *pt[IPARM_SIZE];
711     mat_mkl_pardiso->mtype = icntl;
712     icntl = mat_mkl_pardiso->iparm[34];
713     bs = mat_mkl_pardiso->iparm[36];
714     MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
715 #if defined(PETSC_USE_REAL_SINGLE)
716     mat_mkl_pardiso->iparm[27] = 1;
717 #else
718     mat_mkl_pardiso->iparm[27] = 0;
719 #endif
720     mat_mkl_pardiso->iparm[34] = icntl;
721     mat_mkl_pardiso->iparm[36] = bs;
722   }
723 
724   ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr);
725   if (flg) mat_mkl_pardiso->iparm[0] = icntl;
726 
727   ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr);
728   if (flg) mat_mkl_pardiso->iparm[1] = icntl;
729 
730   ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr);
731   if (flg) mat_mkl_pardiso->iparm[3] = icntl;
732 
733   ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr);
734   if (flg) mat_mkl_pardiso->iparm[4] = icntl;
735 
736   ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr);
737   if (flg) mat_mkl_pardiso->iparm[5] = icntl;
738 
739   ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr);
740   if (flg) mat_mkl_pardiso->iparm[7] = icntl;
741 
742   ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr);
743   if (flg) mat_mkl_pardiso->iparm[9] = icntl;
744 
745   ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr);
746   if (flg) mat_mkl_pardiso->iparm[10] = icntl;
747 
748   ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr);
749   if (flg) mat_mkl_pardiso->iparm[11] = icntl;
750 
751   ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr);
752   if (flg) mat_mkl_pardiso->iparm[12] = icntl;
753 
754   ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr);
755   if (flg) mat_mkl_pardiso->iparm[17] = icntl;
756 
757   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);
758   if (flg) mat_mkl_pardiso->iparm[18] = icntl;
759 
760   ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr);
761   if (flg) mat_mkl_pardiso->iparm[20] = icntl;
762 
763   ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr);
764   if (flg) mat_mkl_pardiso->iparm[23] = icntl;
765 
766   ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr);
767   if (flg) mat_mkl_pardiso->iparm[24] = icntl;
768 
769   ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr);
770   if (flg) mat_mkl_pardiso->iparm[26] = icntl;
771 
772   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);
773   if (flg) mat_mkl_pardiso->iparm[30] = icntl;
774 
775   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);
776   if (flg) mat_mkl_pardiso->iparm[33] = icntl;
777 
778   ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr);
779   if (flg) mat_mkl_pardiso->iparm[59] = icntl;
780   PetscOptionsEnd();
781   PetscFunctionReturn(0);
782 }
783 
784 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
785 {
786   PetscErrorCode ierr;
787   PetscInt       i,bs;
788   PetscBool      match;
789 
790   PetscFunctionBegin;
791   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0;
792   for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0;
793 #if defined(PETSC_USE_REAL_SINGLE)
794   mat_mkl_pardiso->iparm[27] = 1;
795 #else
796   mat_mkl_pardiso->iparm[27] = 0;
797 #endif
798   /* Default options for both sym and unsym */
799   mat_mkl_pardiso->iparm[ 0] =  1; /* Solver default parameters overriden with provided by iparm */
800   mat_mkl_pardiso->iparm[ 1] =  2; /* Metis reordering */
801   mat_mkl_pardiso->iparm[ 5] =  0; /* Write solution into x */
802   mat_mkl_pardiso->iparm[ 7] =  0; /* Max number of iterative refinement steps */
803   mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
804   mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
805 #if 0
806   mat_mkl_pardiso->iparm[23] =  1; /* Parallel factorization control*/
807 #endif
808   ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr);
809   ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr);
810   if (!match || bs == 1) {
811     mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
812     mat_mkl_pardiso->n         = A->rmap->N;
813   } else {
814     mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */
815     mat_mkl_pardiso->iparm[36] = bs;
816     mat_mkl_pardiso->n         = A->rmap->N/bs;
817   }
818   mat_mkl_pardiso->iparm[39] =  0; /* Input: matrix/rhs/solution stored on master */
819 
820   mat_mkl_pardiso->CleanUp   = PETSC_FALSE;
821   mat_mkl_pardiso->maxfct    = 1; /* Maximum number of numerical factorizations. */
822   mat_mkl_pardiso->mnum      = 1; /* Which factorization to use. */
823   mat_mkl_pardiso->msglvl    = 0; /* 0: do not print 1: Print statistical information in file */
824   mat_mkl_pardiso->phase     = -1;
825   mat_mkl_pardiso->err       = 0;
826 
827   mat_mkl_pardiso->nrhs      = 1;
828   mat_mkl_pardiso->err       = 0;
829   mat_mkl_pardiso->phase     = -1;
830 
831   if (ftype == MAT_FACTOR_LU) {
832     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
833     mat_mkl_pardiso->iparm[10] =  1; /* Use nonsymmetric permutation and scaling MPS */
834     mat_mkl_pardiso->iparm[12] =  1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
835   } else {
836     mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */
837     mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
838     mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
839 #if defined(PETSC_USE_DEBUG)
840     mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
841 #endif
842   }
843   ierr = PetscCalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr);
844   mat_mkl_pardiso->schur_size = 0;
845   PetscFunctionReturn(0);
846 }
847 
848 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info)
849 {
850   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
851   PetscErrorCode  ierr;
852 
853   PetscFunctionBegin;
854   mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
855   ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr);
856   /* throw away any previously computed structure */
857   if (mat_mkl_pardiso->freeaij) {
858     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
859     if (mat_mkl_pardiso->iparm[34] == 1) {
860       ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
861     }
862   }
863   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);
864   if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N;
865   else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs;
866 
867   mat_mkl_pardiso->phase = JOB_ANALYSIS;
868 
869   /* reset flops counting if requested */
870   if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1;
871 
872   MKL_PARDISO (mat_mkl_pardiso->pt,
873     &mat_mkl_pardiso->maxfct,
874     &mat_mkl_pardiso->mnum,
875     &mat_mkl_pardiso->mtype,
876     &mat_mkl_pardiso->phase,
877     &mat_mkl_pardiso->n,
878     mat_mkl_pardiso->a,
879     mat_mkl_pardiso->ia,
880     mat_mkl_pardiso->ja,
881     mat_mkl_pardiso->perm,
882     &mat_mkl_pardiso->nrhs,
883     mat_mkl_pardiso->iparm,
884     &mat_mkl_pardiso->msglvl,
885     NULL,
886     NULL,
887     &mat_mkl_pardiso->err);
888   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);
889 
890   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
891 
892   if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
893   else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
894 
895   F->ops->solve           = MatSolve_MKL_PARDISO;
896   F->ops->solvetranspose  = MatSolveTranspose_MKL_PARDISO;
897   F->ops->matsolve        = MatMatSolve_MKL_PARDISO;
898   PetscFunctionReturn(0);
899 }
900 
901 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
902 {
903   PetscErrorCode ierr;
904 
905   PetscFunctionBegin;
906   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
907   PetscFunctionReturn(0);
908 }
909 
910 #if !defined(PETSC_USE_COMPLEX)
911 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos)
912 {
913   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data;
914 
915   PetscFunctionBegin;
916   if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
917   if (npos) *npos = mat_mkl_pardiso->iparm[21];
918   if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
919   PetscFunctionReturn(0);
920 }
921 #endif
922 
923 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info)
924 {
925   PetscErrorCode ierr;
926 
927   PetscFunctionBegin;
928   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
929 #if defined(PETSC_USE_COMPLEX)
930   F->ops->getinertia = NULL;
931 #else
932   F->ops->getinertia = MatGetInertia_MKL_PARDISO;
933 #endif
934   PetscFunctionReturn(0);
935 }
936 
937 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
938 {
939   PetscErrorCode    ierr;
940   PetscBool         iascii;
941   PetscViewerFormat format;
942   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
943   PetscInt          i;
944 
945   PetscFunctionBegin;
946   if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0);
947 
948   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
949   if (iascii) {
950     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
951     if (format == PETSC_VIEWER_ASCII_INFO) {
952       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr);
953       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase:             %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr);
954       for (i=1; i<=64; i++) {
955         ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]:     %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr);
956       }
957       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct:     %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr);
958       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum:     %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr);
959       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype:     %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr);
960       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n:     %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr);
961       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs:     %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
962       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl:     %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr);
963     }
964   }
965   PetscFunctionReturn(0);
966 }
967 
968 
969 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
970 {
971   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data;
972 
973   PetscFunctionBegin;
974   info->block_size        = 1.0;
975   info->nz_used           = mat_mkl_pardiso->iparm[17];
976   info->nz_allocated      = mat_mkl_pardiso->iparm[17];
977   info->nz_unneeded       = 0.0;
978   info->assemblies        = 0.0;
979   info->mallocs           = 0.0;
980   info->memory            = 0.0;
981   info->fill_ratio_given  = 0;
982   info->fill_ratio_needed = 0;
983   info->factor_mallocs    = 0;
984   PetscFunctionReturn(0);
985 }
986 
987 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival)
988 {
989   PetscInt        backup,bs;
990   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
991 
992   PetscFunctionBegin;
993   if (icntl <= 64) {
994     mat_mkl_pardiso->iparm[icntl - 1] = ival;
995   } else {
996     if (icntl == 65) PetscSetMKL_PARDISOThreads(ival);
997     else if (icntl == 66) mat_mkl_pardiso->maxfct = ival;
998     else if (icntl == 67) mat_mkl_pardiso->mnum = ival;
999     else if (icntl == 68) mat_mkl_pardiso->msglvl = ival;
1000     else if (icntl == 69) {
1001       void *pt[IPARM_SIZE];
1002       backup = mat_mkl_pardiso->iparm[34];
1003       bs = mat_mkl_pardiso->iparm[36];
1004       mat_mkl_pardiso->mtype = ival;
1005       MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
1006 #if defined(PETSC_USE_REAL_SINGLE)
1007       mat_mkl_pardiso->iparm[27] = 1;
1008 #else
1009       mat_mkl_pardiso->iparm[27] = 0;
1010 #endif
1011       mat_mkl_pardiso->iparm[34] = backup;
1012       mat_mkl_pardiso->iparm[36] = bs;
1013     } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival;
1014   }
1015   PetscFunctionReturn(0);
1016 }
1017 
1018 /*@
1019   MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters
1020 
1021    Logically Collective on Mat
1022 
1023    Input Parameters:
1024 +  F - the factored matrix obtained by calling MatGetFactor()
1025 .  icntl - index of Mkl_Pardiso parameter
1026 -  ival - value of Mkl_Pardiso parameter
1027 
1028   Options Database:
1029 .   -mat_mkl_pardiso_<icntl> <ival>
1030 
1031    Level: beginner
1032 
1033    References:
1034 .      Mkl_Pardiso Users' Guide
1035 
1036 .seealso: MatGetFactor()
1037 @*/
1038 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival)
1039 {
1040   PetscErrorCode ierr;
1041 
1042   PetscFunctionBegin;
1043   ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr);
1044   PetscFunctionReturn(0);
1045 }
1046 
1047 /*MC
1048   MATSOLVERMKL_PARDISO -  A matrix type providing direct solvers (LU) for
1049   sequential matrices via the external package MKL_PARDISO.
1050 
1051   Works with MATSEQAIJ matrices
1052 
1053   Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver
1054 
1055   Options Database Keys:
1056 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO
1057 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
1058 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
1059 . -mat_mkl_pardiso_68 - Message level information
1060 . -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
1061 . -mat_mkl_pardiso_1  - Use default values
1062 . -mat_mkl_pardiso_2  - Fill-in reducing ordering for the input matrix
1063 . -mat_mkl_pardiso_4  - Preconditioned CGS/CG
1064 . -mat_mkl_pardiso_5  - User permutation
1065 . -mat_mkl_pardiso_6  - Write solution on x
1066 . -mat_mkl_pardiso_8  - Iterative refinement step
1067 . -mat_mkl_pardiso_10 - Pivoting perturbation
1068 . -mat_mkl_pardiso_11 - Scaling vectors
1069 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
1070 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
1071 . -mat_mkl_pardiso_18 - Numbers of non-zero elements
1072 . -mat_mkl_pardiso_19 - Report number of floating point operations
1073 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
1074 . -mat_mkl_pardiso_24 - Parallel factorization control
1075 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
1076 . -mat_mkl_pardiso_27 - Matrix checker
1077 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
1078 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
1079 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode
1080 
1081   Level: beginner
1082 
1083   For more information please check  mkl_pardiso manual
1084 
1085 .seealso: PCFactorSetMatSolverType(), MatSolverType
1086 
1087 M*/
1088 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type)
1089 {
1090   PetscFunctionBegin;
1091   *type = MATSOLVERMKL_PARDISO;
1092   PetscFunctionReturn(0);
1093 }
1094 
1095 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F)
1096 {
1097   Mat             B;
1098   PetscErrorCode  ierr;
1099   Mat_MKL_PARDISO *mat_mkl_pardiso;
1100   PetscBool       isSeqAIJ,isSeqBAIJ,isSeqSBAIJ;
1101 
1102   PetscFunctionBegin;
1103   ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
1104   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr);
1105   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
1106   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1107   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
1108   ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr);
1109   ierr = MatSetUp(B);CHKERRQ(ierr);
1110 
1111   ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr);
1112   B->data = mat_mkl_pardiso;
1113 
1114   ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr);
1115   if (ftype == MAT_FACTOR_LU) {
1116     B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1117     B->factortype            = MAT_FACTOR_LU;
1118     mat_mkl_pardiso->needsym = PETSC_FALSE;
1119     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1120     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1121     else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1122     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name);
1123 #if defined(PETSC_USE_COMPLEX)
1124     mat_mkl_pardiso->mtype = 13;
1125 #else
1126     mat_mkl_pardiso->mtype = 11;
1127 #endif
1128   } else {
1129     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1130     B->factortype                  = MAT_FACTOR_CHOLESKY;
1131     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1132     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1133     else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1134     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name);
1135 
1136     mat_mkl_pardiso->needsym = PETSC_TRUE;
1137 #if !defined(PETSC_USE_COMPLEX)
1138     if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2;
1139     else                      mat_mkl_pardiso->mtype = -2;
1140 #else
1141     mat_mkl_pardiso->mtype = 6;
1142     if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead");
1143 #endif
1144   }
1145   B->ops->destroy = MatDestroy_MKL_PARDISO;
1146   B->ops->view    = MatView_MKL_PARDISO;
1147   B->ops->getinfo = MatGetInfo_MKL_PARDISO;
1148   B->factortype   = ftype;
1149   B->assembled    = PETSC_TRUE;
1150 
1151   ierr = PetscFree(B->solvertype);CHKERRQ(ierr);
1152   ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr);
1153 
1154   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr);
1155   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr);
1156   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr);
1157 
1158   *F = B;
1159   PetscFunctionReturn(0);
1160 }
1161 
1162 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void)
1163 {
1164   PetscErrorCode ierr;
1165 
1166   PetscFunctionBegin;
1167   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1168   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1169   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1170   ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1171   PetscFunctionReturn(0);
1172 }
1173 
1174