1 #if defined(PETSC_HAVE_LIBMKL_INTEL_ILP64) 2 #define MKL_ILP64 3 #endif 4 5 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 6 #include <../src/mat/impls/sbaij/seq/sbaij.h> 7 #include <../src/mat/impls/dense/seq/dense.h> 8 #include <petscblaslapack.h> 9 10 #include <stdio.h> 11 #include <stdlib.h> 12 #include <math.h> 13 #include <mkl_pardiso.h> 14 15 PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int); 16 17 /* 18 * Possible mkl_pardiso phases that controls the execution of the solver. 19 * For more information check mkl_pardiso manual. 20 */ 21 #define JOB_ANALYSIS 11 22 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION 12 23 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 13 24 #define JOB_NUMERICAL_FACTORIZATION 22 25 #define JOB_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 23 26 #define JOB_SOLVE_ITERATIVE_REFINEMENT 33 27 #define JOB_SOLVE_FORWARD_SUBSTITUTION 331 28 #define JOB_SOLVE_DIAGONAL_SUBSTITUTION 332 29 #define JOB_SOLVE_BACKWARD_SUBSTITUTION 333 30 #define JOB_RELEASE_OF_LU_MEMORY 0 31 #define JOB_RELEASE_OF_ALL_MEMORY -1 32 33 #define IPARM_SIZE 64 34 35 #if defined(PETSC_USE_64BIT_INDICES) 36 #if defined(PETSC_HAVE_LIBMKL_INTEL_ILP64) 37 /* sizeof(MKL_INT) == sizeof(long long int) if ilp64*/ 38 #define INT_TYPE long long int 39 #define MKL_PARDISO pardiso 40 #define MKL_PARDISO_INIT pardisoinit 41 #else 42 #define INT_TYPE long long int 43 #define MKL_PARDISO pardiso_64 44 #define MKL_PARDISO_INIT pardiso_64init 45 #endif 46 #else 47 #define INT_TYPE int 48 #define MKL_PARDISO pardiso 49 #define MKL_PARDISO_INIT pardisoinit 50 #endif 51 52 53 /* 54 * Internal data structure. 55 * For more information check mkl_pardiso manual. 56 */ 57 typedef struct { 58 59 /* Configuration vector*/ 60 INT_TYPE iparm[IPARM_SIZE]; 61 62 /* 63 * Internal mkl_pardiso memory location. 64 * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak. 65 */ 66 void *pt[IPARM_SIZE]; 67 68 /* Basic mkl_pardiso info*/ 69 INT_TYPE phase, maxfct, mnum, mtype, n, nrhs, msglvl, err; 70 71 /* Matrix structure*/ 72 void *a; 73 INT_TYPE *ia, *ja; 74 75 /* Number of non-zero elements*/ 76 INT_TYPE nz; 77 78 /* Row permutaton vector*/ 79 INT_TYPE *perm; 80 81 /* Define if matrix preserves sparse structure.*/ 82 MatStructure matstruc; 83 84 PetscBool needsym; 85 PetscBool freeaij; 86 87 /* Schur complement */ 88 PetscScalar *schur; 89 PetscInt schur_size; 90 PetscInt *schur_idxs; 91 PetscScalar *schur_work; 92 PetscBLASInt schur_work_size; 93 PetscInt schur_solver_type; 94 PetscInt *schur_pivots; 95 PetscBool schur_factored; 96 PetscBool schur_inverted; 97 PetscBool solve_interior; 98 99 /* True if mkl_pardiso function have been used.*/ 100 PetscBool CleanUp; 101 102 /* Conversion to a format suitable for MKL */ 103 PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool*, INT_TYPE*, INT_TYPE**, INT_TYPE**, PetscScalar**); 104 } Mat_MKL_PARDISO; 105 106 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 107 { 108 Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)A->data; 109 PetscInt bs = A->rmap->bs; 110 111 PetscFunctionBegin; 112 if (!sym) { 113 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 114 } 115 if (bs == 1) { /* already in the correct format */ 116 *v = aa->a; 117 *r = aa->i; 118 *c = aa->j; 119 *nnz = aa->nz; 120 *free = PETSC_FALSE; 121 } else { 122 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqSBAIJ to MKL Pardiso format still need to be implemented"); 123 } 124 PetscFunctionReturn(0); 125 } 126 127 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 128 { 129 PetscFunctionBegin; 130 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqBAIJ to MKL Pardiso format still need to be implemented"); 131 PetscFunctionReturn(0); 132 } 133 134 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 135 { 136 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data; 137 PetscErrorCode ierr; 138 139 PetscFunctionBegin; 140 if (!sym) { /* already in the correct format */ 141 *v = aa->a; 142 *r = aa->i; 143 *c = aa->j; 144 *nnz = aa->nz; 145 *free = PETSC_FALSE; 146 PetscFunctionReturn(0); 147 } 148 /* need to get the triangular part */ 149 if (reuse == MAT_INITIAL_MATRIX) { 150 PetscScalar *vals,*vv; 151 PetscInt *row,*col,*jj; 152 PetscInt m = A->rmap->n,nz,i; 153 154 nz = 0; 155 for (i=0; i<m; i++) { 156 nz += aa->i[i+1] - aa->diag[i]; 157 } 158 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 159 ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr); 160 jj = col; 161 vv = vals; 162 163 row[0] = 0; 164 for (i=0; i<m; i++) { 165 PetscInt *aj = aa->j + aa->diag[i]; 166 PetscScalar *av = aa->a + aa->diag[i]; 167 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 168 for (j=0; j<rl; j++) { 169 *jj = *aj; jj++; aj++; 170 *vv = *av; vv++; av++; 171 } 172 row[i+1] = row[i] + rl; 173 } 174 *v = vals; 175 *r = row; 176 *c = col; 177 *nnz = nz; 178 *free = PETSC_TRUE; 179 } else { 180 PetscScalar *vv; 181 PetscInt m = A->rmap->n,i; 182 183 vv = *v; 184 for (i=0; i<m; i++) { 185 PetscScalar *av = aa->a + aa->diag[i]; 186 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 187 for (j=0; j<rl; j++) { 188 *vv = *av; vv++; av++; 189 } 190 } 191 *free = PETSC_TRUE; 192 } 193 PetscFunctionReturn(0); 194 } 195 196 void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm []) 197 { 198 int iparm_copy[IPARM_SIZE], mtype_copy, i; 199 200 mtype_copy = *mtype; 201 pardisoinit(pt, &mtype_copy, iparm_copy); 202 for(i = 0; i < IPARM_SIZE; i++){ 203 iparm[i] = iparm_copy[i]; 204 } 205 } 206 207 static PetscErrorCode MatMKLPardisoFactorSchur_Private(Mat_MKL_PARDISO* mpardiso) 208 { 209 PetscBLASInt B_N,B_ierr; 210 PetscScalar *work,val; 211 PetscBLASInt lwork = -1; 212 PetscErrorCode ierr; 213 214 PetscFunctionBegin; 215 if (mpardiso->schur_factored) { 216 PetscFunctionReturn(0); 217 } 218 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 219 switch (mpardiso->schur_solver_type) { 220 case 1: /* hermitian solver */ 221 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 222 PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,mpardiso->schur,&B_N,&B_ierr)); 223 ierr = PetscFPTrapPop();CHKERRQ(ierr); 224 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr); 225 break; 226 case 2: /* symmetric */ 227 if (!mpardiso->schur_pivots) { 228 ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr); 229 } 230 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 231 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&val,&lwork,&B_ierr)); 232 ierr = PetscBLASIntCast((PetscInt)PetscRealPart(val),&lwork);CHKERRQ(ierr); 233 ierr = PetscMalloc1(lwork,&work);CHKERRQ(ierr); 234 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,work,&lwork,&B_ierr)); 235 ierr = PetscFree(work);CHKERRQ(ierr); 236 ierr = PetscFPTrapPop();CHKERRQ(ierr); 237 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr); 238 break; 239 default: /* general */ 240 if (!mpardiso->schur_pivots) { 241 ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr); 242 } 243 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 244 PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&B_ierr)); 245 ierr = PetscFPTrapPop();CHKERRQ(ierr); 246 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr); 247 break; 248 } 249 mpardiso->schur_factored = PETSC_TRUE; 250 PetscFunctionReturn(0); 251 } 252 253 static PetscErrorCode MatMKLPardisoInvertSchur_Private(Mat_MKL_PARDISO* mpardiso) 254 { 255 PetscBLASInt B_N,B_ierr; 256 PetscErrorCode ierr; 257 258 PetscFunctionBegin; 259 ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr); 260 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 261 switch (mpardiso->schur_solver_type) { 262 case 1: /* hermitian solver */ 263 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 264 PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,mpardiso->schur,&B_N,&B_ierr)); 265 ierr = PetscFPTrapPop();CHKERRQ(ierr); 266 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr); 267 break; 268 case 2: /* symmetric */ 269 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 270 PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&B_ierr)); 271 ierr = PetscFPTrapPop();CHKERRQ(ierr); 272 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr); 273 break; 274 default: /* general */ 275 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 276 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&mpardiso->schur_work_size,&B_ierr)); 277 ierr = PetscFPTrapPop();CHKERRQ(ierr); 278 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr); 279 break; 280 } 281 mpardiso->schur_inverted = PETSC_TRUE; 282 PetscFunctionReturn(0); 283 } 284 285 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat_MKL_PARDISO* mpardiso, PetscScalar *B, PetscScalar *X) 286 { 287 PetscScalar one=1.,zero=0.,*schur_rhs,*schur_sol; 288 PetscBLASInt B_N,B_Nrhs,B_ierr; 289 char type[2]; 290 PetscErrorCode ierr; 291 292 PetscFunctionBegin; 293 ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr); 294 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 295 ierr = PetscBLASIntCast(mpardiso->nrhs,&B_Nrhs);CHKERRQ(ierr); 296 if (X == B && mpardiso->schur_inverted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 297 if (X != B) { /* using LAPACK *TRS subroutines */ 298 ierr = PetscMemcpy(X,B,B_N*B_Nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 299 } 300 schur_rhs = B; 301 schur_sol = X; 302 switch (mpardiso->schur_solver_type) { 303 case 1: /* hermitian solver */ 304 if (mpardiso->schur_inverted) { /* BLAShemm should go here */ 305 PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N)); 306 } else { 307 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 308 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,schur_sol,&B_N,&B_ierr)); 309 ierr = PetscFPTrapPop();CHKERRQ(ierr); 310 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRS Lapack routine %d",(int)B_ierr); 311 } 312 break; 313 case 2: /* symmetric solver */ 314 if (mpardiso->schur_inverted) { 315 PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N)); 316 } else { 317 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 318 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr)); 319 ierr = PetscFPTrapPop();CHKERRQ(ierr); 320 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRS Lapack routine %d",(int)B_ierr); 321 } 322 break; 323 default: /* general */ 324 switch (mpardiso->iparm[12-1]) { 325 case 1: 326 sprintf(type,"C"); 327 break; 328 case 2: 329 sprintf(type,"T"); 330 break; 331 default: 332 sprintf(type,"N"); 333 break; 334 } 335 if (mpardiso->schur_inverted) { 336 PetscStackCallBLAS("BLASgemm",BLASgemm_(type,"N",&B_N,&B_Nrhs,&B_N,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N)); 337 } else { 338 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 339 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_(type,&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr)); 340 ierr = PetscFPTrapPop();CHKERRQ(ierr); 341 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRS Lapack routine %d",(int)B_ierr); 342 } 343 break; 344 } 345 PetscFunctionReturn(0); 346 } 347 348 349 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 350 { 351 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 352 const PetscInt *idxs; 353 PetscInt size,i; 354 PetscMPIInt csize; 355 PetscBool sorted; 356 PetscErrorCode ierr; 357 358 PetscFunctionBegin; 359 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr); 360 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc\n"); 361 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 362 if (!sorted) { 363 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted\n"); 364 } 365 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 366 if (mpardiso->schur_size != size) { 367 mpardiso->schur_size = size; 368 ierr = PetscFree2(mpardiso->schur,mpardiso->schur_work);CHKERRQ(ierr); 369 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 370 ierr = PetscFree(mpardiso->schur_pivots);CHKERRQ(ierr); 371 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 372 ierr = PetscMalloc2(size*size,&mpardiso->schur,mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 373 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 374 } 375 ierr = PetscMemzero(mpardiso->perm,mpardiso->n*sizeof(INT_TYPE));CHKERRQ(ierr); 376 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 377 ierr = PetscMemcpy(mpardiso->schur_idxs,idxs,size*sizeof(PetscInt));CHKERRQ(ierr); 378 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 379 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 380 if (size) { /* turn on Schur switch if the set of indices is not empty */ 381 mpardiso->iparm[36-1] = 2; 382 } 383 mpardiso->schur_factored = PETSC_FALSE; 384 mpardiso->schur_inverted = PETSC_FALSE; 385 PetscFunctionReturn(0); 386 } 387 388 PetscErrorCode MatFactorCreateSchurComplement_MKL_PARDISO(Mat F,Mat* S,MatFactorSchurStatus *st) 389 { 390 Mat St; 391 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 392 PetscScalar *array; 393 PetscErrorCode ierr; 394 395 PetscFunctionBegin; 396 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 397 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 398 399 ierr = MatCreate(PetscObjectComm((PetscObject)F),&St);CHKERRQ(ierr); 400 ierr = MatSetSizes(St,PETSC_DECIDE,PETSC_DECIDE,mpardiso->schur_size,mpardiso->schur_size);CHKERRQ(ierr); 401 ierr = MatSetType(St,MATDENSE);CHKERRQ(ierr); 402 ierr = MatSetUp(St);CHKERRQ(ierr); 403 ierr = MatDenseGetArray(St,&array);CHKERRQ(ierr); 404 ierr = PetscMemcpy(array,mpardiso->schur,mpardiso->schur_size*mpardiso->schur_size*sizeof(PetscScalar));CHKERRQ(ierr); 405 ierr = MatDenseRestoreArray(St,&array);CHKERRQ(ierr); 406 *S = St; 407 *st = F->schur_status; 408 PetscFunctionReturn(0); 409 } 410 411 PetscErrorCode MatFactorGetSchurComplement_MKL_PARDISO(Mat F,Mat* S,MatFactorSchurStatus *st) 412 { 413 Mat St; 414 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 415 PetscErrorCode ierr; 416 417 PetscFunctionBegin; 418 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 419 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 420 421 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)F),mpardiso->schur_size,mpardiso->schur_size,mpardiso->schur,&St);CHKERRQ(ierr); 422 *S = St; 423 *st = F->schur_status; 424 PetscFunctionReturn(0); 425 } 426 427 PetscErrorCode MatFactorInvertSchurComplement_MKL_PARDISO(Mat F) 428 { 429 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 430 PetscErrorCode ierr; 431 432 PetscFunctionBegin; 433 if (!mpardiso->iparm[36-1]) { /* do nothing */ 434 PetscFunctionReturn(0); 435 } 436 if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 437 ierr = MatMKLPardisoInvertSchur_Private(mpardiso);CHKERRQ(ierr); 438 PetscFunctionReturn(0); 439 } 440 441 PetscErrorCode MatFactorFactorizeSchurComplement_MKL_PARDISO(Mat F) 442 { 443 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 444 PetscErrorCode ierr; 445 446 PetscFunctionBegin; 447 if (!mpardiso->iparm[36-1]) { /* do nothing */ 448 PetscFunctionReturn(0); 449 } 450 if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 451 ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr); 452 PetscFunctionReturn(0); 453 } 454 455 PetscErrorCode MatFactorSolveSchurComplement_MKL_PARDISO(Mat F, Vec rhs, Vec sol) 456 { 457 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 458 PetscScalar *asol,*arhs; 459 PetscErrorCode ierr; 460 461 PetscFunctionBegin; 462 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 463 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 464 465 mpardiso->nrhs = 1; 466 ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 467 ierr = VecGetArray(sol,&asol);CHKERRQ(ierr); 468 ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr); 469 ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 470 ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr); 471 PetscFunctionReturn(0); 472 } 473 474 PetscErrorCode MatFactorSolveSchurComplementTranspose_MKL_PARDISO(Mat F, Vec rhs, Vec sol) 475 { 476 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 477 PetscScalar *asol,*arhs; 478 PetscInt oiparm12; 479 PetscErrorCode ierr; 480 481 PetscFunctionBegin; 482 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 483 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 484 485 mpardiso->nrhs = 1; 486 ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 487 ierr = VecGetArray(sol,&asol);CHKERRQ(ierr); 488 oiparm12 = mpardiso->iparm[12 - 1]; 489 mpardiso->iparm[12 - 1] = 2; 490 ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr); 491 mpardiso->iparm[12 - 1] = oiparm12; 492 ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 493 ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr); 494 PetscFunctionReturn(0); 495 } 496 497 PetscErrorCode MatFactorSetSchurComplementSolverType_MKL_PARDISO(Mat F, PetscInt sym) 498 { 499 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->data; 500 501 PetscFunctionBegin; 502 if (mpardiso->schur_factored && sym != mpardiso->schur_solver_type) { 503 SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONG,"Cannot change the Schur solver! Schur complement data has been already factored"); 504 } 505 mpardiso->schur_solver_type = sym; 506 PetscFunctionReturn(0); 507 } 508 509 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 510 { 511 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 512 PetscErrorCode ierr; 513 514 PetscFunctionBegin; 515 if (mat_mkl_pardiso->CleanUp) { 516 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 517 518 MKL_PARDISO (mat_mkl_pardiso->pt, 519 &mat_mkl_pardiso->maxfct, 520 &mat_mkl_pardiso->mnum, 521 &mat_mkl_pardiso->mtype, 522 &mat_mkl_pardiso->phase, 523 &mat_mkl_pardiso->n, 524 NULL, 525 NULL, 526 NULL, 527 NULL, 528 &mat_mkl_pardiso->nrhs, 529 mat_mkl_pardiso->iparm, 530 &mat_mkl_pardiso->msglvl, 531 NULL, 532 NULL, 533 &mat_mkl_pardiso->err); 534 } 535 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 536 ierr = PetscFree2(mat_mkl_pardiso->schur,mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 537 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 538 ierr = PetscFree(mat_mkl_pardiso->schur_pivots);CHKERRQ(ierr); 539 if (mat_mkl_pardiso->freeaij) { 540 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 541 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 542 } 543 ierr = PetscFree(A->data);CHKERRQ(ierr); 544 545 /* clear composed functions */ 546 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr); 547 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 548 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorCreateSchurComplement_C",NULL);CHKERRQ(ierr); 549 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSchurComplement_C",NULL);CHKERRQ(ierr); 550 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorInvertSchurComplement_C",NULL);CHKERRQ(ierr); 551 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorFactorizeSchurComplement_C",NULL);CHKERRQ(ierr); 552 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplement_C",NULL);CHKERRQ(ierr); 553 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplementTranspose_C",NULL);CHKERRQ(ierr); 554 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurComplementSolverType_C",NULL);CHKERRQ(ierr); 555 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 556 PetscFunctionReturn(0); 557 } 558 559 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce) 560 { 561 PetscFunctionBegin; 562 if (reduce) { /* data given for the whole matrix */ 563 PetscInt i,m=0,p=0; 564 for (i=0;i<mpardiso->nrhs;i++) { 565 PetscInt j; 566 for (j=0;j<mpardiso->schur_size;j++) { 567 schur[p+j] = whole[m+mpardiso->schur_idxs[j]]; 568 } 569 m += mpardiso->n; 570 p += mpardiso->schur_size; 571 } 572 } else { /* from Schur to whole */ 573 PetscInt i,m=0,p=0; 574 for (i=0;i<mpardiso->nrhs;i++) { 575 PetscInt j; 576 for (j=0;j<mpardiso->schur_size;j++) { 577 whole[m+mpardiso->schur_idxs[j]] = schur[p+j]; 578 } 579 m += mpardiso->n; 580 p += mpardiso->schur_size; 581 } 582 } 583 PetscFunctionReturn(0); 584 } 585 586 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 587 { 588 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 589 PetscErrorCode ierr; 590 PetscScalar *xarray; 591 const PetscScalar *barray; 592 593 PetscFunctionBegin; 594 mat_mkl_pardiso->nrhs = 1; 595 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 596 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 597 598 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 599 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 600 601 if (barray == xarray) { /* if the two vectors share the same memory */ 602 PetscScalar *work; 603 if (!mat_mkl_pardiso->schur_work) { 604 ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr); 605 } else { 606 work = mat_mkl_pardiso->schur_work; 607 } 608 mat_mkl_pardiso->iparm[6-1] = 1; 609 MKL_PARDISO (mat_mkl_pardiso->pt, 610 &mat_mkl_pardiso->maxfct, 611 &mat_mkl_pardiso->mnum, 612 &mat_mkl_pardiso->mtype, 613 &mat_mkl_pardiso->phase, 614 &mat_mkl_pardiso->n, 615 mat_mkl_pardiso->a, 616 mat_mkl_pardiso->ia, 617 mat_mkl_pardiso->ja, 618 NULL, 619 &mat_mkl_pardiso->nrhs, 620 mat_mkl_pardiso->iparm, 621 &mat_mkl_pardiso->msglvl, 622 (void*)xarray, 623 (void*)work, 624 &mat_mkl_pardiso->err); 625 if (!mat_mkl_pardiso->schur_work) { 626 ierr = PetscFree(work);CHKERRQ(ierr); 627 } 628 } else { 629 mat_mkl_pardiso->iparm[6-1] = 0; 630 MKL_PARDISO (mat_mkl_pardiso->pt, 631 &mat_mkl_pardiso->maxfct, 632 &mat_mkl_pardiso->mnum, 633 &mat_mkl_pardiso->mtype, 634 &mat_mkl_pardiso->phase, 635 &mat_mkl_pardiso->n, 636 mat_mkl_pardiso->a, 637 mat_mkl_pardiso->ia, 638 mat_mkl_pardiso->ja, 639 mat_mkl_pardiso->perm, 640 &mat_mkl_pardiso->nrhs, 641 mat_mkl_pardiso->iparm, 642 &mat_mkl_pardiso->msglvl, 643 (void*)barray, 644 (void*)xarray, 645 &mat_mkl_pardiso->err); 646 } 647 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 648 649 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); 650 651 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 652 PetscInt shift = mat_mkl_pardiso->schur_size; 653 654 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 655 if (!mat_mkl_pardiso->schur_inverted) { 656 shift = 0; 657 } 658 659 if (!mat_mkl_pardiso->solve_interior) { 660 /* solve Schur complement */ 661 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 662 ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 663 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 664 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substitued to xarray[schur] will be neglected */ 665 PetscInt i; 666 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 667 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 668 } 669 } 670 671 /* expansion phase */ 672 mat_mkl_pardiso->iparm[6-1] = 1; 673 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 674 MKL_PARDISO (mat_mkl_pardiso->pt, 675 &mat_mkl_pardiso->maxfct, 676 &mat_mkl_pardiso->mnum, 677 &mat_mkl_pardiso->mtype, 678 &mat_mkl_pardiso->phase, 679 &mat_mkl_pardiso->n, 680 mat_mkl_pardiso->a, 681 mat_mkl_pardiso->ia, 682 mat_mkl_pardiso->ja, 683 mat_mkl_pardiso->perm, 684 &mat_mkl_pardiso->nrhs, 685 mat_mkl_pardiso->iparm, 686 &mat_mkl_pardiso->msglvl, 687 (void*)xarray, 688 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 689 &mat_mkl_pardiso->err); 690 691 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); 692 mat_mkl_pardiso->iparm[6-1] = 0; 693 } 694 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 695 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 696 PetscFunctionReturn(0); 697 } 698 699 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 700 { 701 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 702 PetscInt oiparm12; 703 PetscErrorCode ierr; 704 705 PetscFunctionBegin; 706 oiparm12 = mat_mkl_pardiso->iparm[12 - 1]; 707 mat_mkl_pardiso->iparm[12 - 1] = 2; 708 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 709 mat_mkl_pardiso->iparm[12 - 1] = oiparm12; 710 PetscFunctionReturn(0); 711 } 712 713 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 714 { 715 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 716 PetscErrorCode ierr; 717 PetscScalar *barray, *xarray; 718 PetscBool flg; 719 720 PetscFunctionBegin; 721 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 722 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 723 ierr = PetscObjectTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 724 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 725 726 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 727 728 if (mat_mkl_pardiso->nrhs > 0) { 729 ierr = MatDenseGetArray(B,&barray); 730 ierr = MatDenseGetArray(X,&xarray); 731 732 if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location"); 733 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 734 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 735 mat_mkl_pardiso->iparm[6-1] = 0; 736 737 MKL_PARDISO (mat_mkl_pardiso->pt, 738 &mat_mkl_pardiso->maxfct, 739 &mat_mkl_pardiso->mnum, 740 &mat_mkl_pardiso->mtype, 741 &mat_mkl_pardiso->phase, 742 &mat_mkl_pardiso->n, 743 mat_mkl_pardiso->a, 744 mat_mkl_pardiso->ia, 745 mat_mkl_pardiso->ja, 746 mat_mkl_pardiso->perm, 747 &mat_mkl_pardiso->nrhs, 748 mat_mkl_pardiso->iparm, 749 &mat_mkl_pardiso->msglvl, 750 (void*)barray, 751 (void*)xarray, 752 &mat_mkl_pardiso->err); 753 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); 754 755 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 756 PetscScalar *o_schur_work = NULL; 757 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 758 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 759 760 /* allocate extra memory if it is needed */ 761 scale = 1; 762 if (mat_mkl_pardiso->schur_inverted) { 763 scale = 2; 764 } 765 mem *= scale; 766 if (mem > mat_mkl_pardiso->schur_work_size) { 767 o_schur_work = mat_mkl_pardiso->schur_work; 768 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 769 } 770 771 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 772 if (!mat_mkl_pardiso->schur_inverted) shift = 0; 773 774 /* solve Schur complement */ 775 if (!mat_mkl_pardiso->solve_interior) { 776 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 777 ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 778 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 779 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substitued to xarray[schur,n] will be neglected */ 780 PetscInt i,n,m=0; 781 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 782 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 783 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 784 } 785 m += mat_mkl_pardiso->n; 786 } 787 } 788 789 /* expansion phase */ 790 mat_mkl_pardiso->iparm[6-1] = 1; 791 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 792 MKL_PARDISO (mat_mkl_pardiso->pt, 793 &mat_mkl_pardiso->maxfct, 794 &mat_mkl_pardiso->mnum, 795 &mat_mkl_pardiso->mtype, 796 &mat_mkl_pardiso->phase, 797 &mat_mkl_pardiso->n, 798 mat_mkl_pardiso->a, 799 mat_mkl_pardiso->ia, 800 mat_mkl_pardiso->ja, 801 mat_mkl_pardiso->perm, 802 &mat_mkl_pardiso->nrhs, 803 mat_mkl_pardiso->iparm, 804 &mat_mkl_pardiso->msglvl, 805 (void*)xarray, 806 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 807 &mat_mkl_pardiso->err); 808 if (o_schur_work) { /* restore original schur_work (minimal size) */ 809 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 810 mat_mkl_pardiso->schur_work = o_schur_work; 811 } 812 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); 813 mat_mkl_pardiso->iparm[6-1] = 0; 814 } 815 } 816 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 817 PetscFunctionReturn(0); 818 } 819 820 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 821 { 822 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data; 823 PetscErrorCode ierr; 824 825 PetscFunctionBegin; 826 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 827 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); 828 829 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 830 MKL_PARDISO (mat_mkl_pardiso->pt, 831 &mat_mkl_pardiso->maxfct, 832 &mat_mkl_pardiso->mnum, 833 &mat_mkl_pardiso->mtype, 834 &mat_mkl_pardiso->phase, 835 &mat_mkl_pardiso->n, 836 mat_mkl_pardiso->a, 837 mat_mkl_pardiso->ia, 838 mat_mkl_pardiso->ja, 839 mat_mkl_pardiso->perm, 840 &mat_mkl_pardiso->nrhs, 841 mat_mkl_pardiso->iparm, 842 &mat_mkl_pardiso->msglvl, 843 NULL, 844 (void*)mat_mkl_pardiso->schur, 845 &mat_mkl_pardiso->err); 846 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); 847 848 if (mat_mkl_pardiso->schur) { /* schur output from pardiso is in row major format */ 849 PetscInt j,k,n=mat_mkl_pardiso->schur_size; 850 if (!mat_mkl_pardiso->schur_solver_type) { 851 for (j=0; j<n; j++) { 852 for (k=0; k<j; k++) { 853 PetscScalar tmp = mat_mkl_pardiso->schur[j + k*n]; 854 mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n]; 855 mat_mkl_pardiso->schur[k + j*n] = tmp; 856 } 857 } 858 } else { /* we could use row-major in LAPACK routines (e.g. use 'U' instead of 'L'; instead, I prefer consistency between data structures and swap to column major */ 859 for (j=0; j<n; j++) { 860 for (k=0; k<j; k++) { 861 mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n]; 862 } 863 } 864 } 865 } 866 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 867 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 868 mat_mkl_pardiso->schur_factored = PETSC_FALSE; 869 mat_mkl_pardiso->schur_inverted = PETSC_FALSE; 870 PetscFunctionReturn(0); 871 } 872 873 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 874 { 875 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 876 PetscErrorCode ierr; 877 PetscInt icntl,threads=1; 878 PetscBool flg; 879 880 PetscFunctionBegin; 881 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 882 883 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 884 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 885 886 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); 887 if (flg) mat_mkl_pardiso->maxfct = icntl; 888 889 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 890 if (flg) mat_mkl_pardiso->mnum = icntl; 891 892 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 893 if (flg) mat_mkl_pardiso->msglvl = icntl; 894 895 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 896 if(flg){ 897 void *pt[IPARM_SIZE]; 898 mat_mkl_pardiso->mtype = icntl; 899 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 900 #if defined(PETSC_USE_REAL_SINGLE) 901 mat_mkl_pardiso->iparm[27] = 1; 902 #else 903 mat_mkl_pardiso->iparm[27] = 0; 904 #endif 905 mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */ 906 } 907 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 908 909 if (flg && icntl != 0) { 910 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 911 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 912 913 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 914 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 915 916 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 917 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 918 919 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 920 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 921 922 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 923 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 924 925 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 926 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 927 928 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 929 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 930 931 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 932 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 933 934 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 935 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 936 937 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 938 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 939 940 ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr); 941 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 942 943 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 944 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 945 946 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 947 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 948 949 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 950 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 951 952 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 953 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 954 955 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); 956 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 957 958 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); 959 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 960 961 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 962 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 963 } 964 PetscOptionsEnd(); 965 PetscFunctionReturn(0); 966 } 967 968 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 969 { 970 PetscErrorCode ierr; 971 PetscInt i; 972 973 PetscFunctionBegin; 974 for ( i = 0; i < IPARM_SIZE; i++ ){ 975 mat_mkl_pardiso->iparm[i] = 0; 976 } 977 for ( i = 0; i < IPARM_SIZE; i++ ){ 978 mat_mkl_pardiso->pt[i] = 0; 979 } 980 /* Default options for both sym and unsym */ 981 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 982 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 983 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 984 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 985 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 986 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 987 #if 0 988 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 989 #endif 990 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 991 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on master */ 992 993 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 994 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 995 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 996 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 997 mat_mkl_pardiso->phase = -1; 998 mat_mkl_pardiso->err = 0; 999 1000 mat_mkl_pardiso->n = A->rmap->N; 1001 mat_mkl_pardiso->nrhs = 1; 1002 mat_mkl_pardiso->err = 0; 1003 mat_mkl_pardiso->phase = -1; 1004 1005 if(ftype == MAT_FACTOR_LU){ 1006 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 1007 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 1008 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 1009 1010 } else { 1011 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 1012 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 1013 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 1014 /* mat_mkl_pardiso->iparm[20] = 1; */ /* Apply 1x1 and 2x2 Bunch-Kaufman pivoting during the factorization process */ 1015 #if defined(PETSC_USE_DEBUG) 1016 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 1017 #endif 1018 } 1019 ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 1020 for(i = 0; i < A->rmap->N; i++){ 1021 mat_mkl_pardiso->perm[i] = 0; 1022 } 1023 mat_mkl_pardiso->schur_size = 0; 1024 PetscFunctionReturn(0); 1025 } 1026 1027 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 1028 { 1029 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 1030 PetscErrorCode ierr; 1031 1032 PetscFunctionBegin; 1033 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 1034 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 1035 1036 /* throw away any previously computed structure */ 1037 if (mat_mkl_pardiso->freeaij) { 1038 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 1039 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 1040 } 1041 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); 1042 mat_mkl_pardiso->n = A->rmap->N; 1043 1044 mat_mkl_pardiso->phase = JOB_ANALYSIS; 1045 1046 MKL_PARDISO (mat_mkl_pardiso->pt, 1047 &mat_mkl_pardiso->maxfct, 1048 &mat_mkl_pardiso->mnum, 1049 &mat_mkl_pardiso->mtype, 1050 &mat_mkl_pardiso->phase, 1051 &mat_mkl_pardiso->n, 1052 mat_mkl_pardiso->a, 1053 mat_mkl_pardiso->ia, 1054 mat_mkl_pardiso->ja, 1055 mat_mkl_pardiso->perm, 1056 &mat_mkl_pardiso->nrhs, 1057 mat_mkl_pardiso->iparm, 1058 &mat_mkl_pardiso->msglvl, 1059 NULL, 1060 NULL, 1061 &mat_mkl_pardiso->err); 1062 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); 1063 1064 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 1065 1066 if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 1067 else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 1068 1069 F->ops->solve = MatSolve_MKL_PARDISO; 1070 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 1071 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 1072 PetscFunctionReturn(0); 1073 } 1074 1075 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 1076 { 1077 PetscErrorCode ierr; 1078 1079 PetscFunctionBegin; 1080 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 1081 PetscFunctionReturn(0); 1082 } 1083 1084 #if !defined(PETSC_USE_COMPLEX) 1085 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,int *nneg,int *nzero,int *npos) 1086 { 1087 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data; 1088 1089 PetscFunctionBegin; 1090 if (nneg) *nneg = mat_mkl_pardiso->iparm[22]; 1091 if (npos) *npos = mat_mkl_pardiso->iparm[21]; 1092 if (nzero) *nzero = F->rmap->N -(mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]); 1093 PetscFunctionReturn(0); 1094 } 1095 #endif 1096 1097 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 1098 { 1099 PetscErrorCode ierr; 1100 1101 PetscFunctionBegin; 1102 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 1103 #if defined(PETSC_USE_COMPLEX) 1104 F->ops->getinertia = NULL; 1105 #else 1106 F->ops->getinertia = MatGetInertia_MKL_PARDISO; 1107 #endif 1108 PetscFunctionReturn(0); 1109 } 1110 1111 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 1112 { 1113 PetscErrorCode ierr; 1114 PetscBool iascii; 1115 PetscViewerFormat format; 1116 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 1117 PetscInt i; 1118 1119 PetscFunctionBegin; 1120 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 1121 1122 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1123 if (iascii) { 1124 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1125 if (format == PETSC_VIEWER_ASCII_INFO) { 1126 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 1127 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 1128 for(i = 1; i <= 64; i++){ 1129 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 1130 } 1131 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 1132 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 1133 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 1134 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 1135 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 1136 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 1137 } 1138 } 1139 PetscFunctionReturn(0); 1140 } 1141 1142 1143 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 1144 { 1145 Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)A->data; 1146 1147 PetscFunctionBegin; 1148 info->block_size = 1.0; 1149 info->nz_used = mat_mkl_pardiso->nz; 1150 info->nz_allocated = mat_mkl_pardiso->nz; 1151 info->nz_unneeded = 0.0; 1152 info->assemblies = 0.0; 1153 info->mallocs = 0.0; 1154 info->memory = 0.0; 1155 info->fill_ratio_given = 0; 1156 info->fill_ratio_needed = 0; 1157 info->factor_mallocs = 0; 1158 PetscFunctionReturn(0); 1159 } 1160 1161 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 1162 { 1163 Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)F->data; 1164 1165 PetscFunctionBegin; 1166 if(icntl <= 64){ 1167 mat_mkl_pardiso->iparm[icntl - 1] = ival; 1168 } else { 1169 if(icntl == 65) PetscSetMKL_PARDISOThreads(ival); 1170 else if(icntl == 66) mat_mkl_pardiso->maxfct = ival; 1171 else if(icntl == 67) mat_mkl_pardiso->mnum = ival; 1172 else if(icntl == 68) mat_mkl_pardiso->msglvl = ival; 1173 else if(icntl == 69){ 1174 void *pt[IPARM_SIZE]; 1175 mat_mkl_pardiso->mtype = ival; 1176 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 1177 #if defined(PETSC_USE_REAL_SINGLE) 1178 mat_mkl_pardiso->iparm[27] = 1; 1179 #else 1180 mat_mkl_pardiso->iparm[27] = 0; 1181 #endif 1182 mat_mkl_pardiso->iparm[34] = 1; 1183 } else if(icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival; 1184 } 1185 PetscFunctionReturn(0); 1186 } 1187 1188 /*@ 1189 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1190 1191 Logically Collective on Mat 1192 1193 Input Parameters: 1194 + F - the factored matrix obtained by calling MatGetFactor() 1195 . icntl - index of Mkl_Pardiso parameter 1196 - ival - value of Mkl_Pardiso parameter 1197 1198 Options Database: 1199 . -mat_mkl_pardiso_<icntl> <ival> 1200 1201 Level: beginner 1202 1203 References: 1204 . Mkl_Pardiso Users' Guide 1205 1206 .seealso: MatGetFactor() 1207 @*/ 1208 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1209 { 1210 PetscErrorCode ierr; 1211 1212 PetscFunctionBegin; 1213 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1214 PetscFunctionReturn(0); 1215 } 1216 1217 /*MC 1218 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1219 sequential matrices via the external package MKL_PARDISO. 1220 1221 Works with MATSEQAIJ matrices 1222 1223 Use -pc_type lu -pc_factor_mat_solver_package mkl_pardiso to us this direct solver 1224 1225 Options Database Keys: 1226 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO 1227 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1228 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1229 . -mat_mkl_pardiso_68 - Message level information 1230 . -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 1231 . -mat_mkl_pardiso_1 - Use default values 1232 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1233 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1234 . -mat_mkl_pardiso_5 - User permutation 1235 . -mat_mkl_pardiso_6 - Write solution on x 1236 . -mat_mkl_pardiso_8 - Iterative refinement step 1237 . -mat_mkl_pardiso_10 - Pivoting perturbation 1238 . -mat_mkl_pardiso_11 - Scaling vectors 1239 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1240 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1241 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1242 . -mat_mkl_pardiso_19 - Report number of floating point operations 1243 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1244 . -mat_mkl_pardiso_24 - Parallel factorization control 1245 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1246 . -mat_mkl_pardiso_27 - Matrix checker 1247 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1248 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1249 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1250 1251 Level: beginner 1252 1253 For more information please check mkl_pardiso manual 1254 1255 .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage 1256 1257 M*/ 1258 static PetscErrorCode MatFactorGetSolverPackage_mkl_pardiso(Mat A, const MatSolverPackage *type) 1259 { 1260 PetscFunctionBegin; 1261 *type = MATSOLVERMKL_PARDISO; 1262 PetscFunctionReturn(0); 1263 } 1264 1265 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1266 { 1267 Mat B; 1268 PetscErrorCode ierr; 1269 Mat_MKL_PARDISO *mat_mkl_pardiso; 1270 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1271 1272 PetscFunctionBegin; 1273 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1274 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1275 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1276 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1277 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1278 ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr); 1279 ierr = MatSetUp(B);CHKERRQ(ierr); 1280 1281 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1282 B->data = mat_mkl_pardiso; 1283 1284 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1285 if (ftype == MAT_FACTOR_LU) { 1286 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1287 B->factortype = MAT_FACTOR_LU; 1288 mat_mkl_pardiso->needsym = PETSC_FALSE; 1289 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1290 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1291 else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1292 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1293 mat_mkl_pardiso->schur_solver_type = 0; 1294 #if defined(PETSC_USE_COMPLEX) 1295 mat_mkl_pardiso->mtype = 13; 1296 #else 1297 if (A->structurally_symmetric) mat_mkl_pardiso->mtype = 1; 1298 else mat_mkl_pardiso->mtype = 11; 1299 #endif 1300 } else { 1301 #if defined(PETSC_USE_COMPLEX) 1302 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with complex scalars! Use MAT_FACTOR_LU instead",((PetscObject)A)->type_name); 1303 #endif 1304 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1305 B->factortype = MAT_FACTOR_CHOLESKY; 1306 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1307 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1308 else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1309 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1310 1311 mat_mkl_pardiso->needsym = PETSC_TRUE; 1312 if (A->spd_set && A->spd) { 1313 mat_mkl_pardiso->schur_solver_type = 1; 1314 mat_mkl_pardiso->mtype = 2; 1315 } else { 1316 mat_mkl_pardiso->schur_solver_type = 2; 1317 mat_mkl_pardiso->mtype = -2; 1318 } 1319 } 1320 B->ops->destroy = MatDestroy_MKL_PARDISO; 1321 B->ops->view = MatView_MKL_PARDISO; 1322 B->factortype = ftype; 1323 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1324 B->assembled = PETSC_TRUE; 1325 1326 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 1327 ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr); 1328 1329 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mkl_pardiso);CHKERRQ(ierr); 1330 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1331 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1332 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1333 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1334 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorFactorizeSchurComplement_C",MatFactorFactorizeSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1335 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1336 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MKL_PARDISO);CHKERRQ(ierr); 1337 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurComplementSolverType_C",MatFactorSetSchurComplementSolverType_MKL_PARDISO);CHKERRQ(ierr); 1338 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1339 1340 *F = B; 1341 PetscFunctionReturn(0); 1342 } 1343 1344 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MKL_Pardiso(void) 1345 { 1346 PetscErrorCode ierr; 1347 1348 PetscFunctionBegin; 1349 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1350 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1351 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1352 PetscFunctionReturn(0); 1353 } 1354 1355