xref: /petsc/src/mat/impls/aij/seq/mkl_pardiso/mkl_pardiso.c (revision 5e71baeff2f3138f93cd4f5927dfd596eb8325cc)
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 
9 #include <stdio.h>
10 #include <stdlib.h>
11 #include <math.h>
12 #include <mkl_pardiso.h>
13 
14 PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int);
15 
16 /*
17  *  Possible mkl_pardiso phases that controls the execution of the solver.
18  *  For more information check mkl_pardiso manual.
19  */
20 #define JOB_ANALYSIS 11
21 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION 12
22 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 13
23 #define JOB_NUMERICAL_FACTORIZATION 22
24 #define JOB_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 23
25 #define JOB_SOLVE_ITERATIVE_REFINEMENT 33
26 #define JOB_SOLVE_FORWARD_SUBSTITUTION 331
27 #define JOB_SOLVE_DIAGONAL_SUBSTITUTION 332
28 #define JOB_SOLVE_BACKWARD_SUBSTITUTION 333
29 #define JOB_RELEASE_OF_LU_MEMORY 0
30 #define JOB_RELEASE_OF_ALL_MEMORY -1
31 
32 #define IPARM_SIZE 64
33 
34 #if defined(PETSC_USE_64BIT_INDICES)
35  #if defined(PETSC_HAVE_LIBMKL_INTEL_ILP64)
36   /* sizeof(MKL_INT) == sizeof(long long int) if ilp64*/
37   #define INT_TYPE long long int
38   #define MKL_PARDISO pardiso
39   #define MKL_PARDISO_INIT pardisoinit
40  #else
41   #define INT_TYPE long long int
42   #define MKL_PARDISO pardiso_64
43   #define MKL_PARDISO_INIT pardiso_64init
44  #endif
45 #else
46  #define INT_TYPE int
47  #define MKL_PARDISO pardiso
48  #define MKL_PARDISO_INIT pardisoinit
49 #endif
50 
51 
52 /*
53  *  Internal data structure.
54  *  For more information check mkl_pardiso manual.
55  */
56 typedef struct {
57 
58   /* Configuration vector*/
59   INT_TYPE     iparm[IPARM_SIZE];
60 
61   /*
62    * Internal mkl_pardiso memory location.
63    * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak.
64    */
65   void         *pt[IPARM_SIZE];
66 
67   /* Basic mkl_pardiso info*/
68   INT_TYPE     phase, maxfct, mnum, mtype, n, nrhs, msglvl, err;
69 
70   /* Matrix structure*/
71   void         *a;
72   INT_TYPE     *ia, *ja;
73 
74   /* Number of non-zero elements*/
75   INT_TYPE     nz;
76 
77   /* Row permutaton vector*/
78   INT_TYPE     *perm;
79 
80   /* Define if matrix preserves sparse structure.*/
81   MatStructure matstruc;
82 
83   PetscBool    needsym;
84   PetscBool    freeaij;
85 
86   /* Schur complement */
87   PetscScalar  *schur;
88   PetscInt     schur_size;
89   PetscInt     *schur_idxs;
90   PetscScalar  *schur_work;
91   PetscBLASInt schur_work_size;
92   PetscBool    solve_interior;
93 
94   /* True if mkl_pardiso function have been used.*/
95   PetscBool CleanUp;
96 
97   /* Conversion to a format suitable for MKL */
98   PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool*, INT_TYPE*, INT_TYPE**, INT_TYPE**, PetscScalar**);
99 } Mat_MKL_PARDISO;
100 
101 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
102 {
103   Mat_SeqSBAIJ   *aa = (Mat_SeqSBAIJ*)A->data;
104   PetscInt       bs  = A->rmap->bs;
105 
106   PetscFunctionBegin;
107   if (!sym) {
108     SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen");
109   }
110   if (bs == 1) { /* already in the correct format */
111     *v    = aa->a;
112     *r    = aa->i;
113     *c    = aa->j;
114     *nnz  = aa->nz;
115     *free = PETSC_FALSE;
116   } else {
117     SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqSBAIJ to MKL Pardiso format still need to be implemented");
118   }
119   PetscFunctionReturn(0);
120 }
121 
122 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
123 {
124   PetscFunctionBegin;
125   SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqBAIJ to MKL Pardiso format still need to be implemented");
126   PetscFunctionReturn(0);
127 }
128 
129 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v)
130 {
131   Mat_SeqAIJ     *aa = (Mat_SeqAIJ*)A->data;
132   PetscErrorCode ierr;
133 
134   PetscFunctionBegin;
135   if (!sym) { /* already in the correct format */
136     *v    = aa->a;
137     *r    = aa->i;
138     *c    = aa->j;
139     *nnz  = aa->nz;
140     *free = PETSC_FALSE;
141     PetscFunctionReturn(0);
142   }
143   /* need to get the triangular part */
144   if (reuse == MAT_INITIAL_MATRIX) {
145     PetscScalar *vals,*vv;
146     PetscInt    *row,*col,*jj;
147     PetscInt    m = A->rmap->n,nz,i;
148 
149     nz = 0;
150     for (i=0; i<m; i++) {
151       nz += aa->i[i+1] - aa->diag[i];
152     }
153     ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr);
154     ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr);
155     jj = col;
156     vv = vals;
157 
158     row[0] = 0;
159     for (i=0; i<m; i++) {
160       PetscInt    *aj = aa->j + aa->diag[i];
161       PetscScalar *av = aa->a + aa->diag[i];
162       PetscInt    rl = aa->i[i+1] - aa->diag[i],j;
163       for (j=0; j<rl; j++) {
164         *jj = *aj; jj++; aj++;
165         *vv = *av; vv++; av++;
166       }
167       row[i+1]    = row[i] + rl;
168     }
169     *v    = vals;
170     *r    = row;
171     *c    = col;
172     *nnz  = nz;
173     *free = PETSC_TRUE;
174   } else {
175     PetscScalar *vv;
176     PetscInt    m = A->rmap->n,i;
177 
178     vv = *v;
179     for (i=0; i<m; i++) {
180       PetscScalar *av = aa->a + aa->diag[i];
181       PetscInt    rl = aa->i[i+1] - aa->diag[i],j;
182       for (j=0; j<rl; j++) {
183         *vv = *av; vv++; av++;
184       }
185     }
186     *free = PETSC_TRUE;
187   }
188   PetscFunctionReturn(0);
189 }
190 
191 void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm [])
192 {
193   int iparm_copy[IPARM_SIZE], mtype_copy, i;
194 
195   mtype_copy = *mtype;
196   pardisoinit(pt, &mtype_copy, iparm_copy);
197   for(i = 0; i < IPARM_SIZE; i++){
198     iparm[i] = iparm_copy[i];
199   }
200 }
201 
202 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X)
203 {
204   Mat_MKL_PARDISO      *mpardiso =(Mat_MKL_PARDISO*)F->data;
205   Mat                  S,Xmat,Bmat;
206   MatFactorSchurStatus schurstatus;
207   PetscErrorCode       ierr;
208 
209   PetscFunctionBegin;
210   ierr = MatFactorFactorizeSchurComplement(F);CHKERRQ(ierr);
211   ierr = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr);
212   if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address");
213   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr);
214   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr);
215   if (X != B) { /* using MatMatSolve */
216     ierr = MatCopy(Bmat,Xmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
217   }
218 
219 #if defined(PETSC_USE_COMPLEX)
220   if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet");
221 #endif
222 
223   switch (schurstatus) {
224   case MAT_FACTOR_SCHUR_FACTORED:
225     if (!mpardiso->iparm[12-1]) {
226       ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr);
227     } else { /* transpose solve */
228       ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr);
229     }
230     break;
231   case MAT_FACTOR_SCHUR_INVERTED:
232     if (!mpardiso->iparm[12-1]) {
233       ierr = MatMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr);
234     } else { /* transpose solve */
235       ierr = MatTransposeMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr);
236     }
237     break;
238   default:
239     SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status);
240     break;
241   }
242   ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr);
243   ierr = MatDestroy(&Bmat);CHKERRQ(ierr);
244   ierr = MatDestroy(&Xmat);CHKERRQ(ierr);
245   PetscFunctionReturn(0);
246 }
247 
248 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is)
249 {
250   Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data;
251   const PetscInt  *idxs;
252   PetscInt        size,i;
253   PetscMPIInt     csize;
254   PetscBool       sorted;
255   PetscErrorCode  ierr;
256 
257   PetscFunctionBegin;
258   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr);
259   if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc\n");
260   ierr = ISSorted(is,&sorted);CHKERRQ(ierr);
261   if (!sorted) {
262     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted\n");
263   }
264   ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr);
265   if (mpardiso->schur_size != size) {
266     mpardiso->schur_size = size;
267     ierr = PetscFree2(mpardiso->schur,mpardiso->schur_work);CHKERRQ(ierr);
268     ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr);
269     ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr);
270     ierr = PetscMalloc2(size*size,&mpardiso->schur,mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr);
271     ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr);
272   }
273   ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->schur_size,mpardiso->schur,&F->schur);CHKERRQ(ierr);
274   if (mpardiso->mtype == 2) {
275     ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr);
276   }
277 
278   ierr = PetscMemzero(mpardiso->perm,mpardiso->n*sizeof(INT_TYPE));CHKERRQ(ierr);
279   ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr);
280   ierr = PetscMemcpy(mpardiso->schur_idxs,idxs,size*sizeof(PetscInt));CHKERRQ(ierr);
281   for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1;
282   ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr);
283   if (size) { /* turn on Schur switch if the set of indices is not empty */
284     mpardiso->iparm[36-1] = 2;
285   }
286   PetscFunctionReturn(0);
287 }
288 
289 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A)
290 {
291   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
292   PetscErrorCode  ierr;
293 
294   PetscFunctionBegin;
295   if (mat_mkl_pardiso->CleanUp) {
296     mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY;
297 
298     MKL_PARDISO (mat_mkl_pardiso->pt,
299       &mat_mkl_pardiso->maxfct,
300       &mat_mkl_pardiso->mnum,
301       &mat_mkl_pardiso->mtype,
302       &mat_mkl_pardiso->phase,
303       &mat_mkl_pardiso->n,
304       NULL,
305       NULL,
306       NULL,
307       NULL,
308       &mat_mkl_pardiso->nrhs,
309       mat_mkl_pardiso->iparm,
310       &mat_mkl_pardiso->msglvl,
311       NULL,
312       NULL,
313       &mat_mkl_pardiso->err);
314   }
315   ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr);
316   ierr = PetscFree2(mat_mkl_pardiso->schur,mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
317   ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr);
318   if (mat_mkl_pardiso->freeaij) {
319     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
320     ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
321   }
322   ierr = PetscFree(A->data);CHKERRQ(ierr);
323 
324   /* clear composed functions */
325   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr);
326   ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr);
327   ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr);
328   PetscFunctionReturn(0);
329 }
330 
331 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce)
332 {
333   PetscFunctionBegin;
334   if (reduce) { /* data given for the whole matrix */
335     PetscInt i,m=0,p=0;
336     for (i=0;i<mpardiso->nrhs;i++) {
337       PetscInt j;
338       for (j=0;j<mpardiso->schur_size;j++) {
339         schur[p+j] = whole[m+mpardiso->schur_idxs[j]];
340       }
341       m += mpardiso->n;
342       p += mpardiso->schur_size;
343     }
344   } else { /* from Schur to whole */
345     PetscInt i,m=0,p=0;
346     for (i=0;i<mpardiso->nrhs;i++) {
347       PetscInt j;
348       for (j=0;j<mpardiso->schur_size;j++) {
349         whole[m+mpardiso->schur_idxs[j]] = schur[p+j];
350       }
351       m += mpardiso->n;
352       p += mpardiso->schur_size;
353     }
354   }
355   PetscFunctionReturn(0);
356 }
357 
358 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x)
359 {
360   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
361   PetscErrorCode    ierr;
362   PetscScalar       *xarray;
363   const PetscScalar *barray;
364 
365   PetscFunctionBegin;
366   mat_mkl_pardiso->nrhs = 1;
367   ierr = VecGetArray(x,&xarray);CHKERRQ(ierr);
368   ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr);
369 
370   if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
371   else  mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
372 
373   if (barray == xarray) { /* if the two vectors share the same memory */
374     PetscScalar *work;
375     if (!mat_mkl_pardiso->schur_work) {
376       ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr);
377     } else {
378       work = mat_mkl_pardiso->schur_work;
379     }
380     mat_mkl_pardiso->iparm[6-1] = 1;
381     MKL_PARDISO (mat_mkl_pardiso->pt,
382       &mat_mkl_pardiso->maxfct,
383       &mat_mkl_pardiso->mnum,
384       &mat_mkl_pardiso->mtype,
385       &mat_mkl_pardiso->phase,
386       &mat_mkl_pardiso->n,
387       mat_mkl_pardiso->a,
388       mat_mkl_pardiso->ia,
389       mat_mkl_pardiso->ja,
390       NULL,
391       &mat_mkl_pardiso->nrhs,
392       mat_mkl_pardiso->iparm,
393       &mat_mkl_pardiso->msglvl,
394       (void*)xarray,
395       (void*)work,
396       &mat_mkl_pardiso->err);
397     if (!mat_mkl_pardiso->schur_work) {
398       ierr = PetscFree(work);CHKERRQ(ierr);
399     }
400   } else {
401     mat_mkl_pardiso->iparm[6-1] = 0;
402     MKL_PARDISO (mat_mkl_pardiso->pt,
403       &mat_mkl_pardiso->maxfct,
404       &mat_mkl_pardiso->mnum,
405       &mat_mkl_pardiso->mtype,
406       &mat_mkl_pardiso->phase,
407       &mat_mkl_pardiso->n,
408       mat_mkl_pardiso->a,
409       mat_mkl_pardiso->ia,
410       mat_mkl_pardiso->ja,
411       mat_mkl_pardiso->perm,
412       &mat_mkl_pardiso->nrhs,
413       mat_mkl_pardiso->iparm,
414       &mat_mkl_pardiso->msglvl,
415       (void*)barray,
416       (void*)xarray,
417       &mat_mkl_pardiso->err);
418   }
419   ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr);
420 
421   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);
422 
423   if (A->schur) { /* solve Schur complement and expand solution */
424     PetscInt shift = mat_mkl_pardiso->schur_size;
425 
426     /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
427     if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) {
428       shift = 0;
429     }
430 
431     if (!mat_mkl_pardiso->solve_interior) {
432       /* solve Schur complement */
433       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
434       ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
435       ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
436     } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */
437       PetscInt i;
438       for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
439         xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.;
440       }
441     }
442 
443     /* expansion phase */
444     mat_mkl_pardiso->iparm[6-1] = 1;
445     mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
446     MKL_PARDISO (mat_mkl_pardiso->pt,
447       &mat_mkl_pardiso->maxfct,
448       &mat_mkl_pardiso->mnum,
449       &mat_mkl_pardiso->mtype,
450       &mat_mkl_pardiso->phase,
451       &mat_mkl_pardiso->n,
452       mat_mkl_pardiso->a,
453       mat_mkl_pardiso->ia,
454       mat_mkl_pardiso->ja,
455       mat_mkl_pardiso->perm,
456       &mat_mkl_pardiso->nrhs,
457       mat_mkl_pardiso->iparm,
458       &mat_mkl_pardiso->msglvl,
459       (void*)xarray,
460       (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
461       &mat_mkl_pardiso->err);
462 
463     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);
464     mat_mkl_pardiso->iparm[6-1] = 0;
465   }
466   ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr);
467   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
468   PetscFunctionReturn(0);
469 }
470 
471 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x)
472 {
473   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
474   PetscInt        oiparm12;
475   PetscErrorCode  ierr;
476 
477   PetscFunctionBegin;
478   oiparm12 = mat_mkl_pardiso->iparm[12 - 1];
479   mat_mkl_pardiso->iparm[12 - 1] = 2;
480   ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr);
481   mat_mkl_pardiso->iparm[12 - 1] = oiparm12;
482   PetscFunctionReturn(0);
483 }
484 
485 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X)
486 {
487   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data;
488   PetscErrorCode    ierr;
489   PetscScalar       *barray, *xarray;
490   PetscBool         flg;
491 
492   PetscFunctionBegin;
493   ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr);
494   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix");
495   ierr = PetscObjectTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr);
496   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix");
497 
498   ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
499 
500   if (mat_mkl_pardiso->nrhs > 0) {
501     ierr = MatDenseGetArray(B,&barray);
502     ierr = MatDenseGetArray(X,&xarray);
503 
504     if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location");
505     if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT;
506     else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION;
507     mat_mkl_pardiso->iparm[6-1] = 0;
508 
509     MKL_PARDISO (mat_mkl_pardiso->pt,
510       &mat_mkl_pardiso->maxfct,
511       &mat_mkl_pardiso->mnum,
512       &mat_mkl_pardiso->mtype,
513       &mat_mkl_pardiso->phase,
514       &mat_mkl_pardiso->n,
515       mat_mkl_pardiso->a,
516       mat_mkl_pardiso->ia,
517       mat_mkl_pardiso->ja,
518       mat_mkl_pardiso->perm,
519       &mat_mkl_pardiso->nrhs,
520       mat_mkl_pardiso->iparm,
521       &mat_mkl_pardiso->msglvl,
522       (void*)barray,
523       (void*)xarray,
524       &mat_mkl_pardiso->err);
525     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);
526 
527     if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */
528       PetscScalar *o_schur_work = NULL;
529       PetscInt    shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale;
530       PetscInt    mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs;
531 
532       /* allocate extra memory if it is needed */
533       scale = 1;
534       if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2;
535 
536       mem *= scale;
537       if (mem > mat_mkl_pardiso->schur_work_size) {
538         o_schur_work = mat_mkl_pardiso->schur_work;
539         ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
540       }
541 
542       /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */
543       if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0;
544 
545       /* solve Schur complement */
546       if (!mat_mkl_pardiso->solve_interior) {
547         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr);
548         ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr);
549         ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr);
550       } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */
551         PetscInt i,n,m=0;
552         for (n=0;n<mat_mkl_pardiso->nrhs;n++) {
553           for (i=0;i<mat_mkl_pardiso->schur_size;i++) {
554             xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.;
555           }
556           m += mat_mkl_pardiso->n;
557         }
558       }
559 
560       /* expansion phase */
561       mat_mkl_pardiso->iparm[6-1] = 1;
562       mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION;
563       MKL_PARDISO (mat_mkl_pardiso->pt,
564         &mat_mkl_pardiso->maxfct,
565         &mat_mkl_pardiso->mnum,
566         &mat_mkl_pardiso->mtype,
567         &mat_mkl_pardiso->phase,
568         &mat_mkl_pardiso->n,
569         mat_mkl_pardiso->a,
570         mat_mkl_pardiso->ia,
571         mat_mkl_pardiso->ja,
572         mat_mkl_pardiso->perm,
573         &mat_mkl_pardiso->nrhs,
574         mat_mkl_pardiso->iparm,
575         &mat_mkl_pardiso->msglvl,
576         (void*)xarray,
577         (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */
578         &mat_mkl_pardiso->err);
579       if (o_schur_work) { /* restore original schur_work (minimal size) */
580         ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr);
581         mat_mkl_pardiso->schur_work = o_schur_work;
582       }
583       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);
584       mat_mkl_pardiso->iparm[6-1] = 0;
585     }
586   }
587   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
588   PetscFunctionReturn(0);
589 }
590 
591 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info)
592 {
593   Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data;
594   PetscErrorCode  ierr;
595 
596   PetscFunctionBegin;
597   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
598   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);
599 
600   mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION;
601   MKL_PARDISO (mat_mkl_pardiso->pt,
602     &mat_mkl_pardiso->maxfct,
603     &mat_mkl_pardiso->mnum,
604     &mat_mkl_pardiso->mtype,
605     &mat_mkl_pardiso->phase,
606     &mat_mkl_pardiso->n,
607     mat_mkl_pardiso->a,
608     mat_mkl_pardiso->ia,
609     mat_mkl_pardiso->ja,
610     mat_mkl_pardiso->perm,
611     &mat_mkl_pardiso->nrhs,
612     mat_mkl_pardiso->iparm,
613     &mat_mkl_pardiso->msglvl,
614     NULL,
615     (void*)mat_mkl_pardiso->schur,
616     &mat_mkl_pardiso->err);
617   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);
618 
619   if (F->schur) { /* schur output from pardiso is in row major format */
620     ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr);
621     ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr);
622   }
623   mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN;
624   mat_mkl_pardiso->CleanUp  = PETSC_TRUE;
625   PetscFunctionReturn(0);
626 }
627 
628 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A)
629 {
630   Mat_MKL_PARDISO     *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
631   PetscErrorCode      ierr;
632   PetscInt            icntl,threads=1;
633   PetscBool           flg;
634 
635   PetscFunctionBegin;
636   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr);
637 
638   ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr);
639   if (flg) PetscSetMKL_PARDISOThreads((int)threads);
640 
641   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);
642   if (flg) mat_mkl_pardiso->maxfct = icntl;
643 
644   ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr);
645   if (flg) mat_mkl_pardiso->mnum = icntl;
646 
647   ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr);
648   if (flg) mat_mkl_pardiso->msglvl = icntl;
649 
650   ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr);
651   if(flg){
652     void *pt[IPARM_SIZE];
653     mat_mkl_pardiso->mtype = icntl;
654     MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
655 #if defined(PETSC_USE_REAL_SINGLE)
656     mat_mkl_pardiso->iparm[27] = 1;
657 #else
658     mat_mkl_pardiso->iparm[27] = 0;
659 #endif
660     mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */
661   }
662   ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr);
663 
664   if (flg && icntl != 0) {
665     ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr);
666     if (flg) mat_mkl_pardiso->iparm[1] = icntl;
667 
668     ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr);
669     if (flg) mat_mkl_pardiso->iparm[3] = icntl;
670 
671     ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr);
672     if (flg) mat_mkl_pardiso->iparm[4] = icntl;
673 
674     ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr);
675     if (flg) mat_mkl_pardiso->iparm[5] = icntl;
676 
677     ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr);
678     if (flg) mat_mkl_pardiso->iparm[7] = icntl;
679 
680     ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr);
681     if (flg) mat_mkl_pardiso->iparm[9] = icntl;
682 
683     ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr);
684     if (flg) mat_mkl_pardiso->iparm[10] = icntl;
685 
686     ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr);
687     if (flg) mat_mkl_pardiso->iparm[11] = icntl;
688 
689     ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr);
690     if (flg) mat_mkl_pardiso->iparm[12] = icntl;
691 
692     ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr);
693     if (flg) mat_mkl_pardiso->iparm[17] = icntl;
694 
695     ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr);
696     if (flg) mat_mkl_pardiso->iparm[18] = icntl;
697 
698     ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr);
699     if (flg) mat_mkl_pardiso->iparm[20] = icntl;
700 
701     ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr);
702     if (flg) mat_mkl_pardiso->iparm[23] = icntl;
703 
704     ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr);
705     if (flg) mat_mkl_pardiso->iparm[24] = icntl;
706 
707     ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr);
708     if (flg) mat_mkl_pardiso->iparm[26] = icntl;
709 
710     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);
711     if (flg) mat_mkl_pardiso->iparm[30] = icntl;
712 
713     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);
714     if (flg) mat_mkl_pardiso->iparm[33] = icntl;
715 
716     ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr);
717     if (flg) mat_mkl_pardiso->iparm[59] = icntl;
718   }
719   PetscOptionsEnd();
720   PetscFunctionReturn(0);
721 }
722 
723 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso)
724 {
725   PetscErrorCode ierr;
726   PetscInt       i;
727 
728   PetscFunctionBegin;
729   for ( i = 0; i < IPARM_SIZE; i++ ){
730     mat_mkl_pardiso->iparm[i] = 0;
731   }
732   for ( i = 0; i < IPARM_SIZE; i++ ){
733     mat_mkl_pardiso->pt[i] = 0;
734   }
735   /* Default options for both sym and unsym */
736   mat_mkl_pardiso->iparm[ 0] =  1; /* Solver default parameters overriden with provided by iparm */
737   mat_mkl_pardiso->iparm[ 1] =  2; /* Metis reordering */
738   mat_mkl_pardiso->iparm[ 5] =  0; /* Write solution into x */
739   mat_mkl_pardiso->iparm[ 7] =  0; /* Max number of iterative refinement steps */
740   mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
741   mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */
742 #if 0
743   mat_mkl_pardiso->iparm[23] =  1; /* Parallel factorization control*/
744 #endif
745   mat_mkl_pardiso->iparm[34] =  1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */
746   mat_mkl_pardiso->iparm[39] =  0; /* Input: matrix/rhs/solution stored on master */
747 
748   mat_mkl_pardiso->CleanUp   = PETSC_FALSE;
749   mat_mkl_pardiso->maxfct    = 1; /* Maximum number of numerical factorizations. */
750   mat_mkl_pardiso->mnum      = 1; /* Which factorization to use. */
751   mat_mkl_pardiso->msglvl    = 0; /* 0: do not print 1: Print statistical information in file */
752   mat_mkl_pardiso->phase     = -1;
753   mat_mkl_pardiso->err       = 0;
754 
755   mat_mkl_pardiso->n         = A->rmap->N;
756   mat_mkl_pardiso->nrhs      = 1;
757   mat_mkl_pardiso->err       = 0;
758   mat_mkl_pardiso->phase     = -1;
759 
760   if(ftype == MAT_FACTOR_LU){
761     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
762     mat_mkl_pardiso->iparm[10] =  1; /* Use nonsymmetric permutation and scaling MPS */
763     mat_mkl_pardiso->iparm[12] =  1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
764 
765   } else {
766     mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */
767     mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */
768     mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */
769 /*    mat_mkl_pardiso->iparm[20] =  1; */ /* Apply 1x1 and 2x2 Bunch-Kaufman pivoting during the factorization process */
770 #if defined(PETSC_USE_DEBUG)
771     mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */
772 #endif
773   }
774   ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr);
775   for(i = 0; i < A->rmap->N; i++){
776     mat_mkl_pardiso->perm[i] = 0;
777   }
778   mat_mkl_pardiso->schur_size = 0;
779   PetscFunctionReturn(0);
780 }
781 
782 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info)
783 {
784   Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data;
785   PetscErrorCode  ierr;
786 
787   PetscFunctionBegin;
788   mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN;
789   ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr);
790 
791   /* throw away any previously computed structure */
792   if (mat_mkl_pardiso->freeaij) {
793     ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr);
794     ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr);
795   }
796   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);
797   mat_mkl_pardiso->n = A->rmap->N;
798 
799   mat_mkl_pardiso->phase = JOB_ANALYSIS;
800 
801   MKL_PARDISO (mat_mkl_pardiso->pt,
802     &mat_mkl_pardiso->maxfct,
803     &mat_mkl_pardiso->mnum,
804     &mat_mkl_pardiso->mtype,
805     &mat_mkl_pardiso->phase,
806     &mat_mkl_pardiso->n,
807     mat_mkl_pardiso->a,
808     mat_mkl_pardiso->ia,
809     mat_mkl_pardiso->ja,
810     mat_mkl_pardiso->perm,
811     &mat_mkl_pardiso->nrhs,
812     mat_mkl_pardiso->iparm,
813     &mat_mkl_pardiso->msglvl,
814     NULL,
815     NULL,
816     &mat_mkl_pardiso->err);
817   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);
818 
819   mat_mkl_pardiso->CleanUp = PETSC_TRUE;
820 
821   if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO;
822   else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO;
823 
824   F->ops->solve           = MatSolve_MKL_PARDISO;
825   F->ops->solvetranspose  = MatSolveTranspose_MKL_PARDISO;
826   F->ops->matsolve        = MatMatSolve_MKL_PARDISO;
827   PetscFunctionReturn(0);
828 }
829 
830 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
831 {
832   PetscErrorCode ierr;
833 
834   PetscFunctionBegin;
835   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
836   PetscFunctionReturn(0);
837 }
838 
839 #if !defined(PETSC_USE_COMPLEX)
840 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,int *nneg,int *nzero,int *npos)
841 {
842   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data;
843 
844   PetscFunctionBegin;
845   if (nneg) *nneg = mat_mkl_pardiso->iparm[22];
846   if (npos) *npos = mat_mkl_pardiso->iparm[21];
847   if (nzero) *nzero = F->rmap->N -(mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]);
848   PetscFunctionReturn(0);
849 }
850 #endif
851 
852 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info)
853 {
854   PetscErrorCode ierr;
855 
856   PetscFunctionBegin;
857   ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr);
858 #if defined(PETSC_USE_COMPLEX)
859   F->ops->getinertia = NULL;
860 #else
861   F->ops->getinertia = MatGetInertia_MKL_PARDISO;
862 #endif
863   PetscFunctionReturn(0);
864 }
865 
866 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer)
867 {
868   PetscErrorCode    ierr;
869   PetscBool         iascii;
870   PetscViewerFormat format;
871   Mat_MKL_PARDISO   *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data;
872   PetscInt          i;
873 
874   PetscFunctionBegin;
875   if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0);
876 
877   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
878   if (iascii) {
879     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
880     if (format == PETSC_VIEWER_ASCII_INFO) {
881       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr);
882       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase:             %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr);
883       for(i = 1; i <= 64; i++){
884         ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]:     %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr);
885       }
886       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct:     %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr);
887       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum:     %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr);
888       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype:     %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr);
889       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n:     %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr);
890       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs:     %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr);
891       ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl:     %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr);
892     }
893   }
894   PetscFunctionReturn(0);
895 }
896 
897 
898 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info)
899 {
900   Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)A->data;
901 
902   PetscFunctionBegin;
903   info->block_size        = 1.0;
904   info->nz_used           = mat_mkl_pardiso->nz;
905   info->nz_allocated      = mat_mkl_pardiso->nz;
906   info->nz_unneeded       = 0.0;
907   info->assemblies        = 0.0;
908   info->mallocs           = 0.0;
909   info->memory            = 0.0;
910   info->fill_ratio_given  = 0;
911   info->fill_ratio_needed = 0;
912   info->factor_mallocs    = 0;
913   PetscFunctionReturn(0);
914 }
915 
916 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival)
917 {
918   Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)F->data;
919 
920   PetscFunctionBegin;
921   if(icntl <= 64){
922     mat_mkl_pardiso->iparm[icntl - 1] = ival;
923   } else {
924     if(icntl == 65) PetscSetMKL_PARDISOThreads(ival);
925     else if(icntl == 66) mat_mkl_pardiso->maxfct = ival;
926     else if(icntl == 67) mat_mkl_pardiso->mnum = ival;
927     else if(icntl == 68) mat_mkl_pardiso->msglvl = ival;
928     else if(icntl == 69){
929       void *pt[IPARM_SIZE];
930       mat_mkl_pardiso->mtype = ival;
931       MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm);
932 #if defined(PETSC_USE_REAL_SINGLE)
933       mat_mkl_pardiso->iparm[27] = 1;
934 #else
935       mat_mkl_pardiso->iparm[27] = 0;
936 #endif
937       mat_mkl_pardiso->iparm[34] = 1;
938     } else if(icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival;
939   }
940   PetscFunctionReturn(0);
941 }
942 
943 /*@
944   MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters
945 
946    Logically Collective on Mat
947 
948    Input Parameters:
949 +  F - the factored matrix obtained by calling MatGetFactor()
950 .  icntl - index of Mkl_Pardiso parameter
951 -  ival - value of Mkl_Pardiso parameter
952 
953   Options Database:
954 .   -mat_mkl_pardiso_<icntl> <ival>
955 
956    Level: beginner
957 
958    References:
959 .      Mkl_Pardiso Users' Guide
960 
961 .seealso: MatGetFactor()
962 @*/
963 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival)
964 {
965   PetscErrorCode ierr;
966 
967   PetscFunctionBegin;
968   ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr);
969   PetscFunctionReturn(0);
970 }
971 
972 /*MC
973   MATSOLVERMKL_PARDISO -  A matrix type providing direct solvers (LU) for
974   sequential matrices via the external package MKL_PARDISO.
975 
976   Works with MATSEQAIJ matrices
977 
978   Use -pc_type lu -pc_factor_mat_solver_package mkl_pardiso to us this direct solver
979 
980   Options Database Keys:
981 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO
982 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time
983 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase
984 . -mat_mkl_pardiso_68 - Message level information
985 . -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
986 . -mat_mkl_pardiso_1  - Use default values
987 . -mat_mkl_pardiso_2  - Fill-in reducing ordering for the input matrix
988 . -mat_mkl_pardiso_4  - Preconditioned CGS/CG
989 . -mat_mkl_pardiso_5  - User permutation
990 . -mat_mkl_pardiso_6  - Write solution on x
991 . -mat_mkl_pardiso_8  - Iterative refinement step
992 . -mat_mkl_pardiso_10 - Pivoting perturbation
993 . -mat_mkl_pardiso_11 - Scaling vectors
994 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A
995 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching
996 . -mat_mkl_pardiso_18 - Numbers of non-zero elements
997 . -mat_mkl_pardiso_19 - Report number of floating point operations
998 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices
999 . -mat_mkl_pardiso_24 - Parallel factorization control
1000 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control
1001 . -mat_mkl_pardiso_27 - Matrix checker
1002 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors
1003 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode
1004 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode
1005 
1006   Level: beginner
1007 
1008   For more information please check  mkl_pardiso manual
1009 
1010 .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage
1011 
1012 M*/
1013 static PetscErrorCode MatFactorGetSolverPackage_mkl_pardiso(Mat A, const MatSolverPackage *type)
1014 {
1015   PetscFunctionBegin;
1016   *type = MATSOLVERMKL_PARDISO;
1017   PetscFunctionReturn(0);
1018 }
1019 
1020 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F)
1021 {
1022   Mat             B;
1023   PetscErrorCode  ierr;
1024   Mat_MKL_PARDISO *mat_mkl_pardiso;
1025   PetscBool       isSeqAIJ,isSeqBAIJ,isSeqSBAIJ;
1026 
1027   PetscFunctionBegin;
1028   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
1029   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr);
1030   ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
1031   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1032   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
1033   ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr);
1034   ierr = MatSetUp(B);CHKERRQ(ierr);
1035 
1036   ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr);
1037   B->data = mat_mkl_pardiso;
1038 
1039   ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr);
1040   if (ftype == MAT_FACTOR_LU) {
1041     B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO;
1042     B->factortype            = MAT_FACTOR_LU;
1043     mat_mkl_pardiso->needsym = PETSC_FALSE;
1044     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1045     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1046     else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead");
1047     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name);
1048 #if defined(PETSC_USE_COMPLEX)
1049     mat_mkl_pardiso->mtype = 13;
1050 #else
1051     if (A->structurally_symmetric) mat_mkl_pardiso->mtype = 1;
1052     else                           mat_mkl_pardiso->mtype = 11;
1053 #endif
1054   } else {
1055 #if defined(PETSC_USE_COMPLEX)
1056     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with complex scalars! Use MAT_FACTOR_LU instead",((PetscObject)A)->type_name);
1057 #endif
1058     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO;
1059     B->factortype                  = MAT_FACTOR_CHOLESKY;
1060     if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij;
1061     else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij;
1062     else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij;
1063     else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name);
1064 
1065     mat_mkl_pardiso->needsym = PETSC_TRUE;
1066     if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2;
1067     else                      mat_mkl_pardiso->mtype = -2;
1068   }
1069   B->ops->destroy          = MatDestroy_MKL_PARDISO;
1070   B->ops->view             = MatView_MKL_PARDISO;
1071   B->factortype            = ftype;
1072   B->ops->getinfo          = MatGetInfo_MKL_PARDISO;
1073   B->assembled             = PETSC_TRUE;
1074 
1075   ierr = PetscFree(B->solvertype);CHKERRQ(ierr);
1076   ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr);
1077 
1078   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mkl_pardiso);CHKERRQ(ierr);
1079   ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr);
1080   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr);
1081 
1082   *F = B;
1083   PetscFunctionReturn(0);
1084 }
1085 
1086 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MKL_Pardiso(void)
1087 {
1088   PetscErrorCode ierr;
1089 
1090   PetscFunctionBegin;
1091   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1092   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1093   ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr);
1094   PetscFunctionReturn(0);
1095 }
1096 
1097