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**, void**); 104 PetscErrorCode (*Destroy)(Mat); 105 } Mat_MKL_PARDISO; 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatMKLPardiso_Convert_seqsbaij" 109 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,void **v) 110 { 111 Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)A->data; 112 PetscInt bs = A->rmap->bs; 113 114 PetscFunctionBegin; 115 if (!sym) { 116 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 117 } 118 if (bs == 1) { /* already in the correct format */ 119 *v = aa->a; 120 *r = aa->i; 121 *c = aa->j; 122 *nnz = aa->nz; 123 *free = PETSC_FALSE; 124 } else { 125 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqSBAIJ to MKL Pardiso format still need to be implemented"); 126 } 127 PetscFunctionReturn(0); 128 } 129 130 #undef __FUNCT__ 131 #define __FUNCT__ "MatMKLPardiso_Convert_seqbaij" 132 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,void **v) 133 { 134 PetscFunctionBegin; 135 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Conversion from SeqBAIJ to MKL Pardiso format still need to be implemented"); 136 PetscFunctionReturn(0); 137 } 138 139 #undef __FUNCT__ 140 #define __FUNCT__ "MatMKLPardiso_Convert_seqaij" 141 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,void **v) 142 { 143 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data; 144 PetscErrorCode ierr; 145 146 PetscFunctionBegin; 147 if (!sym) { /* already in the correct format */ 148 *v = aa->a; 149 *r = aa->i; 150 *c = aa->j; 151 *nnz = aa->nz; 152 *free = PETSC_FALSE; 153 PetscFunctionReturn(0); 154 } 155 /* need to get the triangular part */ 156 if (reuse == MAT_INITIAL_MATRIX) { 157 PetscScalar *vals,*vv; 158 PetscInt *row,*col,*jj; 159 PetscInt m = A->rmap->n,nz,i; 160 161 nz = 0; 162 for (i=0; i<m; i++) { 163 nz += aa->i[i+1] - aa->diag[i]; 164 } 165 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 166 ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr); 167 jj = col; 168 vv = vals; 169 170 row[0] = 0; 171 for (i=0; i<m; i++) { 172 PetscInt *aj = aa->j + aa->diag[i]; 173 PetscScalar *av = aa->a + aa->diag[i]; 174 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 175 for (j=0; j<rl; j++) { 176 *jj = *aj; jj++; aj++; 177 *vv = *av; vv++; av++; 178 } 179 row[i+1] = row[i] + rl; 180 } 181 *v = vals; 182 *r = row; 183 *c = col; 184 *nnz = nz; 185 *free = PETSC_TRUE; 186 } else { 187 PetscScalar *vv; 188 PetscInt m = A->rmap->n,i; 189 190 vv = *v; 191 for (i=0; i<m; i++) { 192 PetscScalar *av = aa->a + aa->diag[i]; 193 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 194 for (j=0; j<rl; j++) { 195 *vv = *av; vv++; av++; 196 } 197 } 198 *free = PETSC_TRUE; 199 } 200 PetscFunctionReturn(0); 201 } 202 203 void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm []) 204 { 205 int iparm_copy[IPARM_SIZE], mtype_copy, i; 206 207 mtype_copy = *mtype; 208 pardisoinit(pt, &mtype_copy, iparm_copy); 209 for(i = 0; i < IPARM_SIZE; i++){ 210 iparm[i] = iparm_copy[i]; 211 } 212 } 213 214 #undef __FUNCT__ 215 #define __FUNCT__ "MatMKLPardisoFactorSchur_Private" 216 static PetscErrorCode MatMKLPardisoFactorSchur_Private(Mat_MKL_PARDISO* mpardiso) 217 { 218 PetscBLASInt B_N,B_ierr; 219 PetscScalar *work,val; 220 PetscBLASInt lwork = -1; 221 PetscErrorCode ierr; 222 223 PetscFunctionBegin; 224 if (mpardiso->schur_factored) { 225 PetscFunctionReturn(0); 226 } 227 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 228 switch (mpardiso->schur_solver_type) { 229 case 1: /* hermitian solver */ 230 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 231 PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,mpardiso->schur,&B_N,&B_ierr)); 232 ierr = PetscFPTrapPop();CHKERRQ(ierr); 233 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr); 234 break; 235 case 2: /* symmetric */ 236 if (!mpardiso->schur_pivots) { 237 ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr); 238 } 239 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 240 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&val,&lwork,&B_ierr)); 241 ierr = PetscBLASIntCast((PetscInt)val,&lwork);CHKERRQ(ierr); 242 ierr = PetscMalloc1(lwork,&work);CHKERRQ(ierr); 243 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,work,&lwork,&B_ierr)); 244 ierr = PetscFree(work);CHKERRQ(ierr); 245 ierr = PetscFPTrapPop();CHKERRQ(ierr); 246 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr); 247 break; 248 default: /* general */ 249 if (!mpardiso->schur_pivots) { 250 ierr = PetscMalloc1(B_N,&mpardiso->schur_pivots);CHKERRQ(ierr); 251 } 252 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 253 PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,&B_ierr)); 254 ierr = PetscFPTrapPop();CHKERRQ(ierr); 255 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr); 256 break; 257 } 258 mpardiso->schur_factored = PETSC_TRUE; 259 PetscFunctionReturn(0); 260 } 261 262 #undef __FUNCT__ 263 #define __FUNCT__ "MatMKLPardisoInvertSchur_Private" 264 static PetscErrorCode MatMKLPardisoInvertSchur_Private(Mat_MKL_PARDISO* mpardiso) 265 { 266 PetscBLASInt B_N,B_ierr; 267 PetscErrorCode ierr; 268 269 PetscFunctionBegin; 270 ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr); 271 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 272 switch (mpardiso->schur_solver_type) { 273 case 1: /* hermitian solver */ 274 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 275 PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,mpardiso->schur,&B_N,&B_ierr)); 276 ierr = PetscFPTrapPop();CHKERRQ(ierr); 277 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr); 278 break; 279 case 2: /* symmetric */ 280 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 281 PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&B_ierr)); 282 ierr = PetscFPTrapPop();CHKERRQ(ierr); 283 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr); 284 break; 285 default: /* general */ 286 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 287 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,mpardiso->schur,&B_N,mpardiso->schur_pivots,mpardiso->schur_work,&mpardiso->schur_work_size,&B_ierr)); 288 ierr = PetscFPTrapPop();CHKERRQ(ierr); 289 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr); 290 break; 291 } 292 mpardiso->schur_inverted = PETSC_TRUE; 293 PetscFunctionReturn(0); 294 } 295 296 #undef __FUNCT__ 297 #define __FUNCT__ "MatMKLPardisoSolveSchur_Private" 298 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat_MKL_PARDISO* mpardiso, PetscScalar *B, PetscScalar *X) 299 { 300 PetscScalar one=1.,zero=0.,*schur_rhs,*schur_sol; 301 PetscBLASInt B_N,B_Nrhs,B_ierr; 302 char type[2]; 303 PetscErrorCode ierr; 304 305 PetscFunctionBegin; 306 ierr = MatMKLPardisoFactorSchur_Private(mpardiso);CHKERRQ(ierr); 307 ierr = PetscBLASIntCast(mpardiso->schur_size,&B_N);CHKERRQ(ierr); 308 ierr = PetscBLASIntCast(mpardiso->nrhs,&B_Nrhs);CHKERRQ(ierr); 309 if (X == B && mpardiso->schur_inverted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 310 if (X != B) { /* using LAPACK *TRS subroutines */ 311 ierr = PetscMemcpy(X,B,B_N*B_Nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 312 } 313 schur_rhs = B; 314 schur_sol = X; 315 switch (mpardiso->schur_solver_type) { 316 case 1: /* hermitian solver */ 317 if (mpardiso->schur_inverted) { /* BLAShemm should go here */ 318 PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N)); 319 } else { 320 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 321 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,schur_sol,&B_N,&B_ierr)); 322 ierr = PetscFPTrapPop();CHKERRQ(ierr); 323 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRS Lapack routine %d",(int)B_ierr); 324 } 325 break; 326 case 2: /* symmetric solver */ 327 if (mpardiso->schur_inverted) { 328 PetscStackCallBLAS("BLASsymm",BLASsymm_("L","L",&B_N,&B_Nrhs,&one,mpardiso->schur,&B_N,schur_rhs,&B_N,&zero,schur_sol,&B_N)); 329 } else { 330 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 331 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr)); 332 ierr = PetscFPTrapPop();CHKERRQ(ierr); 333 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRS Lapack routine %d",(int)B_ierr); 334 } 335 break; 336 default: /* general */ 337 switch (mpardiso->iparm[12-1]) { 338 case 1: 339 sprintf(type,"C"); 340 break; 341 case 2: 342 sprintf(type,"T"); 343 break; 344 default: 345 sprintf(type,"N"); 346 break; 347 } 348 if (mpardiso->schur_inverted) { 349 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)); 350 } else { 351 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 352 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_(type,&B_N,&B_Nrhs,mpardiso->schur,&B_N,mpardiso->schur_pivots,schur_sol,&B_N,&B_ierr)); 353 ierr = PetscFPTrapPop();CHKERRQ(ierr); 354 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRS Lapack routine %d",(int)B_ierr); 355 } 356 break; 357 } 358 PetscFunctionReturn(0); 359 } 360 361 362 #undef __FUNCT__ 363 #define __FUNCT__ "MatFactorSetSchurIS_MKL_PARDISO" 364 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 365 { 366 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 367 const PetscInt *idxs; 368 PetscInt size,i; 369 PetscMPIInt csize; 370 PetscBool sorted; 371 PetscErrorCode ierr; 372 373 PetscFunctionBegin; 374 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr); 375 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc\n"); 376 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 377 if (!sorted) { 378 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted\n"); 379 } 380 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 381 if (mpardiso->schur_size != size) { 382 mpardiso->schur_size = size; 383 ierr = PetscFree2(mpardiso->schur,mpardiso->schur_work);CHKERRQ(ierr); 384 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 385 ierr = PetscFree(mpardiso->schur_pivots);CHKERRQ(ierr); 386 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 387 ierr = PetscMalloc2(size*size,&mpardiso->schur,mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 388 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 389 } 390 ierr = PetscMemzero(mpardiso->perm,mpardiso->n*sizeof(INT_TYPE));CHKERRQ(ierr); 391 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 392 ierr = PetscMemcpy(mpardiso->schur_idxs,idxs,size*sizeof(PetscInt));CHKERRQ(ierr); 393 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 394 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 395 if (size) { /* turn on Schur switch if we the set of indices is not empty */ 396 mpardiso->iparm[36-1] = 2; 397 } 398 mpardiso->schur_factored = PETSC_FALSE; 399 mpardiso->schur_inverted = PETSC_FALSE; 400 PetscFunctionReturn(0); 401 } 402 403 #undef __FUNCT__ 404 #define __FUNCT__ "MatFactorCreateSchurComplement_MKL_PARDISO" 405 PetscErrorCode MatFactorCreateSchurComplement_MKL_PARDISO(Mat F,Mat* S) 406 { 407 Mat St; 408 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 409 PetscScalar *array; 410 PetscErrorCode ierr; 411 412 PetscFunctionBegin; 413 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 414 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 415 416 ierr = MatCreate(PetscObjectComm((PetscObject)F),&St);CHKERRQ(ierr); 417 ierr = MatSetSizes(St,PETSC_DECIDE,PETSC_DECIDE,mpardiso->schur_size,mpardiso->schur_size);CHKERRQ(ierr); 418 ierr = MatSetType(St,MATDENSE);CHKERRQ(ierr); 419 ierr = MatSetUp(St);CHKERRQ(ierr); 420 ierr = MatDenseGetArray(St,&array);CHKERRQ(ierr); 421 ierr = PetscMemcpy(array,mpardiso->schur,mpardiso->schur_size*mpardiso->schur_size*sizeof(PetscScalar));CHKERRQ(ierr); 422 ierr = MatDenseRestoreArray(St,&array);CHKERRQ(ierr); 423 *S = St; 424 PetscFunctionReturn(0); 425 } 426 427 #undef __FUNCT__ 428 #define __FUNCT__ "MatFactorGetSchurComplement_MKL_PARDISO" 429 PetscErrorCode MatFactorGetSchurComplement_MKL_PARDISO(Mat F,Mat* S) 430 { 431 Mat St; 432 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 433 PetscErrorCode ierr; 434 435 PetscFunctionBegin; 436 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 437 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 438 439 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)F),mpardiso->schur_size,mpardiso->schur_size,mpardiso->schur,&St);CHKERRQ(ierr); 440 *S = St; 441 PetscFunctionReturn(0); 442 } 443 444 #undef __FUNCT__ 445 #define __FUNCT__ "MatFactorInvertSchurComplement_MKL_PARDISO" 446 PetscErrorCode MatFactorInvertSchurComplement_MKL_PARDISO(Mat F) 447 { 448 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 449 PetscErrorCode ierr; 450 451 PetscFunctionBegin; 452 if (!mpardiso->iparm[36-1]) { /* do nothing */ 453 PetscFunctionReturn(0); 454 } 455 if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 456 ierr = MatMKLPardisoInvertSchur_Private(mpardiso);CHKERRQ(ierr); 457 PetscFunctionReturn(0); 458 } 459 460 #undef __FUNCT__ 461 #define __FUNCT__ "MatFactorSolveSchurComplement_MKL_PARDISO" 462 PetscErrorCode MatFactorSolveSchurComplement_MKL_PARDISO(Mat F, Vec rhs, Vec sol) 463 { 464 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 465 PetscScalar *asol,*arhs; 466 PetscErrorCode ierr; 467 468 PetscFunctionBegin; 469 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 470 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 471 472 mpardiso->nrhs = 1; 473 ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 474 ierr = VecGetArray(sol,&asol);CHKERRQ(ierr); 475 ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr); 476 ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 477 ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr); 478 PetscFunctionReturn(0); 479 } 480 481 #undef __FUNCT__ 482 #define __FUNCT__ "MatFactorSolveSchurComplementTranspose_MKL_PARDISO" 483 PetscErrorCode MatFactorSolveSchurComplementTranspose_MKL_PARDISO(Mat F, Vec rhs, Vec sol) 484 { 485 Mat_MKL_PARDISO *mpardiso =(Mat_MKL_PARDISO*)F->spptr; 486 PetscScalar *asol,*arhs; 487 PetscErrorCode ierr; 488 489 PetscFunctionBegin; 490 if (!mpardiso->iparm[36-1]) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 491 else if (!mpardiso->schur_size) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 492 493 mpardiso->nrhs = 1; 494 ierr = VecGetArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 495 ierr = VecGetArray(sol,&asol);CHKERRQ(ierr); 496 mpardiso->iparm[12 - 1] = 2; 497 ierr = MatMKLPardisoSolveSchur_Private(mpardiso,arhs,asol);CHKERRQ(ierr); 498 mpardiso->iparm[12 - 1] = 0; 499 ierr = VecRestoreArrayRead(rhs,(const PetscScalar**)&arhs);CHKERRQ(ierr); 500 ierr = VecRestoreArray(sol,&asol);CHKERRQ(ierr); 501 PetscFunctionReturn(0); 502 } 503 504 #undef __FUNCT__ 505 #define __FUNCT__ "MatDestroy_MKL_PARDISO" 506 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 507 { 508 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->spptr; 509 PetscErrorCode ierr; 510 511 PetscFunctionBegin; 512 if (mat_mkl_pardiso->CleanUp) { 513 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 514 515 MKL_PARDISO (mat_mkl_pardiso->pt, 516 &mat_mkl_pardiso->maxfct, 517 &mat_mkl_pardiso->mnum, 518 &mat_mkl_pardiso->mtype, 519 &mat_mkl_pardiso->phase, 520 &mat_mkl_pardiso->n, 521 NULL, 522 NULL, 523 NULL, 524 mat_mkl_pardiso->perm, 525 &mat_mkl_pardiso->nrhs, 526 mat_mkl_pardiso->iparm, 527 &mat_mkl_pardiso->msglvl, 528 NULL, 529 NULL, 530 &mat_mkl_pardiso->err); 531 } 532 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 533 ierr = PetscFree2(mat_mkl_pardiso->schur,mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 534 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 535 ierr = PetscFree(mat_mkl_pardiso->schur_pivots);CHKERRQ(ierr); 536 if (mat_mkl_pardiso->freeaij) { 537 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 538 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 539 } 540 if (mat_mkl_pardiso->Destroy) { 541 ierr = (mat_mkl_pardiso->Destroy)(A);CHKERRQ(ierr); 542 } 543 ierr = PetscFree(A->spptr);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,"MatFactorSolveSchurComplement_C",NULL);CHKERRQ(ierr); 552 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplementTranspose_C",NULL);CHKERRQ(ierr); 553 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 554 PetscFunctionReturn(0); 555 } 556 557 #undef __FUNCT__ 558 #define __FUNCT__ "MatMKLPardisoScatterSchur_Private" 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 #undef __FUNCT__ 587 #define __FUNCT__ "MatSolve_MKL_PARDISO" 588 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 589 { 590 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->spptr; 591 PetscErrorCode ierr; 592 PetscScalar *xarray; 593 const PetscScalar *barray; 594 595 PetscFunctionBegin; 596 mat_mkl_pardiso->nrhs = 1; 597 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 598 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 599 600 if (!mat_mkl_pardiso->schur) { 601 mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 602 } else { 603 mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 604 } 605 mat_mkl_pardiso->iparm[6-1] = 0; 606 607 MKL_PARDISO (mat_mkl_pardiso->pt, 608 &mat_mkl_pardiso->maxfct, 609 &mat_mkl_pardiso->mnum, 610 &mat_mkl_pardiso->mtype, 611 &mat_mkl_pardiso->phase, 612 &mat_mkl_pardiso->n, 613 mat_mkl_pardiso->a, 614 mat_mkl_pardiso->ia, 615 mat_mkl_pardiso->ja, 616 mat_mkl_pardiso->perm, 617 &mat_mkl_pardiso->nrhs, 618 mat_mkl_pardiso->iparm, 619 &mat_mkl_pardiso->msglvl, 620 (void*)barray, 621 (void*)xarray, 622 &mat_mkl_pardiso->err); 623 624 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); 625 626 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 627 PetscInt shift = mat_mkl_pardiso->schur_size; 628 629 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 630 if (!mat_mkl_pardiso->schur_inverted) { 631 shift = 0; 632 } 633 634 if (!mat_mkl_pardiso->solve_interior) { 635 /* solve Schur complement */ 636 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 637 ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 638 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 639 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substitued to xarray[schur] will be neglected */ 640 PetscInt i; 641 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 642 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 643 } 644 } 645 /* expansion phase */ 646 mat_mkl_pardiso->iparm[6-1] = 1; 647 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 648 MKL_PARDISO (mat_mkl_pardiso->pt, 649 &mat_mkl_pardiso->maxfct, 650 &mat_mkl_pardiso->mnum, 651 &mat_mkl_pardiso->mtype, 652 &mat_mkl_pardiso->phase, 653 &mat_mkl_pardiso->n, 654 mat_mkl_pardiso->a, 655 mat_mkl_pardiso->ia, 656 mat_mkl_pardiso->ja, 657 mat_mkl_pardiso->perm, 658 &mat_mkl_pardiso->nrhs, 659 mat_mkl_pardiso->iparm, 660 &mat_mkl_pardiso->msglvl, 661 (void*)xarray, 662 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 663 &mat_mkl_pardiso->err); 664 665 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); 666 mat_mkl_pardiso->iparm[6-1] = 0; 667 } 668 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 669 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 670 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 671 PetscFunctionReturn(0); 672 } 673 674 #undef __FUNCT__ 675 #define __FUNCT__ "MatSolveTranspose_MKL_PARDISO" 676 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 677 { 678 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->spptr; 679 PetscErrorCode ierr; 680 681 PetscFunctionBegin; 682 #if defined(PETSC_USE_COMPLEX) 683 mat_mkl_pardiso->iparm[12 - 1] = 1; 684 #else 685 mat_mkl_pardiso->iparm[12 - 1] = 2; 686 #endif 687 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 688 mat_mkl_pardiso->iparm[12 - 1] = 0; 689 PetscFunctionReturn(0); 690 } 691 692 #undef __FUNCT__ 693 #define __FUNCT__ "MatMatSolve_MKL_PARDISO" 694 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 695 { 696 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->spptr; 697 PetscErrorCode ierr; 698 PetscScalar *barray, *xarray; 699 PetscBool flg; 700 701 PetscFunctionBegin; 702 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 703 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 704 ierr = PetscObjectTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 705 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 706 707 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 708 709 if(mat_mkl_pardiso->nrhs > 0){ 710 ierr = MatDenseGetArray(B,&barray); 711 ierr = MatDenseGetArray(X,&xarray); 712 713 if (!mat_mkl_pardiso->schur) { 714 mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 715 } else { 716 mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 717 } 718 mat_mkl_pardiso->iparm[6-1] = 0; 719 720 MKL_PARDISO (mat_mkl_pardiso->pt, 721 &mat_mkl_pardiso->maxfct, 722 &mat_mkl_pardiso->mnum, 723 &mat_mkl_pardiso->mtype, 724 &mat_mkl_pardiso->phase, 725 &mat_mkl_pardiso->n, 726 mat_mkl_pardiso->a, 727 mat_mkl_pardiso->ia, 728 mat_mkl_pardiso->ja, 729 mat_mkl_pardiso->perm, 730 &mat_mkl_pardiso->nrhs, 731 mat_mkl_pardiso->iparm, 732 &mat_mkl_pardiso->msglvl, 733 (void*)barray, 734 (void*)xarray, 735 &mat_mkl_pardiso->err); 736 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); 737 738 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 739 PetscScalar *o_schur_work = NULL; 740 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 741 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 742 743 /* allocate extra memory if it is needed */ 744 scale = 1; 745 if (mat_mkl_pardiso->schur_inverted) { 746 scale = 2; 747 } 748 mem *= scale; 749 if (mem > mat_mkl_pardiso->schur_work_size) { 750 o_schur_work = mat_mkl_pardiso->schur_work; 751 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 752 } 753 754 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 755 if (!mat_mkl_pardiso->schur_inverted) { 756 shift = 0; 757 } 758 759 /* solve Schur complement */ 760 if (!mat_mkl_pardiso->solve_interior) { 761 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 762 ierr = MatMKLPardisoSolveSchur_Private(mat_mkl_pardiso,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 763 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 764 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substitued to xarray[schur,n] will be neglected */ 765 PetscInt i,n,m=0; 766 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 767 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 768 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 769 } 770 m += mat_mkl_pardiso->n; 771 } 772 } 773 /* expansion phase */ 774 mat_mkl_pardiso->iparm[6-1] = 1; 775 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 776 MKL_PARDISO (mat_mkl_pardiso->pt, 777 &mat_mkl_pardiso->maxfct, 778 &mat_mkl_pardiso->mnum, 779 &mat_mkl_pardiso->mtype, 780 &mat_mkl_pardiso->phase, 781 &mat_mkl_pardiso->n, 782 mat_mkl_pardiso->a, 783 mat_mkl_pardiso->ia, 784 mat_mkl_pardiso->ja, 785 mat_mkl_pardiso->perm, 786 &mat_mkl_pardiso->nrhs, 787 mat_mkl_pardiso->iparm, 788 &mat_mkl_pardiso->msglvl, 789 (void*)xarray, 790 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 791 &mat_mkl_pardiso->err); 792 if (o_schur_work) { /* restore original schur_work (minimal size) */ 793 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 794 mat_mkl_pardiso->schur_work = o_schur_work; 795 } 796 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); 797 mat_mkl_pardiso->iparm[6-1] = 0; 798 } 799 } 800 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 801 PetscFunctionReturn(0); 802 } 803 804 #undef __FUNCT__ 805 #define __FUNCT__ "MatFactorNumeric_MKL_PARDISO" 806 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 807 { 808 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->spptr; 809 PetscErrorCode ierr; 810 811 PetscFunctionBegin; 812 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 813 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,&mat_mkl_pardiso->a);CHKERRQ(ierr); 814 815 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 816 MKL_PARDISO (mat_mkl_pardiso->pt, 817 &mat_mkl_pardiso->maxfct, 818 &mat_mkl_pardiso->mnum, 819 &mat_mkl_pardiso->mtype, 820 &mat_mkl_pardiso->phase, 821 &mat_mkl_pardiso->n, 822 mat_mkl_pardiso->a, 823 mat_mkl_pardiso->ia, 824 mat_mkl_pardiso->ja, 825 mat_mkl_pardiso->perm, 826 &mat_mkl_pardiso->nrhs, 827 mat_mkl_pardiso->iparm, 828 &mat_mkl_pardiso->msglvl, 829 NULL, 830 (void*)mat_mkl_pardiso->schur, 831 &mat_mkl_pardiso->err); 832 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); 833 834 if (mat_mkl_pardiso->schur) { /* schur output from pardiso is in row major format */ 835 PetscInt j,k,n=mat_mkl_pardiso->schur_size; 836 if (!mat_mkl_pardiso->schur_solver_type) { 837 for (j=0; j<n; j++) { 838 for (k=0; k<j; k++) { 839 PetscScalar tmp = mat_mkl_pardiso->schur[j + k*n]; 840 mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n]; 841 mat_mkl_pardiso->schur[k + j*n] = tmp; 842 } 843 } 844 } 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 */ 845 for (j=0; j<n; j++) { 846 for (k=0; k<j; k++) { 847 mat_mkl_pardiso->schur[j + k*n] = mat_mkl_pardiso->schur[k + j*n]; 848 } 849 } 850 } 851 } 852 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 853 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 854 mat_mkl_pardiso->schur_factored = PETSC_FALSE; 855 mat_mkl_pardiso->schur_inverted = PETSC_FALSE; 856 PetscFunctionReturn(0); 857 } 858 859 #undef __FUNCT__ 860 #define __FUNCT__ "PetscSetMKL_PARDISOFromOptions" 861 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 862 { 863 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->spptr; 864 PetscErrorCode ierr; 865 PetscInt icntl,threads=1; 866 PetscBool flg; 867 868 PetscFunctionBegin; 869 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 870 871 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 872 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 873 874 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); 875 if (flg) mat_mkl_pardiso->maxfct = icntl; 876 877 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 878 if (flg) mat_mkl_pardiso->mnum = icntl; 879 880 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 881 if (flg) mat_mkl_pardiso->msglvl = icntl; 882 883 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 884 if(flg){ 885 void *pt[IPARM_SIZE]; 886 mat_mkl_pardiso->mtype = icntl; 887 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 888 #if defined(PETSC_USE_REAL_SINGLE) 889 mat_mkl_pardiso->iparm[27] = 1; 890 #else 891 mat_mkl_pardiso->iparm[27] = 0; 892 #endif 893 mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */ 894 } 895 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 896 897 if(flg && icntl != 0){ 898 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 899 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 900 901 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 902 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 903 904 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 905 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 906 907 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 908 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 909 910 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 911 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 912 913 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 914 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 915 916 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 917 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 918 919 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 920 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 921 922 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 923 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 924 925 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 926 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 927 928 ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr); 929 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 930 931 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 932 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 933 934 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 935 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 936 937 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 938 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 939 940 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 941 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 942 943 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); 944 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 945 946 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); 947 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 948 949 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 950 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 951 } 952 PetscOptionsEnd(); 953 PetscFunctionReturn(0); 954 } 955 956 #undef __FUNCT__ 957 #define __FUNCT__ "MatFactorMKL_PARDISOInitialize_Private" 958 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 959 { 960 PetscErrorCode ierr; 961 PetscInt i; 962 963 PetscFunctionBegin; 964 for ( i = 0; i < IPARM_SIZE; i++ ){ 965 mat_mkl_pardiso->iparm[i] = 0; 966 } 967 for ( i = 0; i < IPARM_SIZE; i++ ){ 968 mat_mkl_pardiso->pt[i] = 0; 969 } 970 /* Default options for both sym and unsym */ 971 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 972 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 973 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 974 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 975 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 976 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 977 #if 0 978 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 979 #endif 980 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 981 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on master */ 982 983 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 984 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 985 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 986 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 987 mat_mkl_pardiso->phase = -1; 988 mat_mkl_pardiso->err = 0; 989 990 mat_mkl_pardiso->n = A->rmap->N; 991 mat_mkl_pardiso->nrhs = 1; 992 mat_mkl_pardiso->err = 0; 993 mat_mkl_pardiso->phase = -1; 994 995 if(ftype == MAT_FACTOR_LU){ 996 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 997 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 998 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 999 1000 } else { 1001 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 1002 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 1003 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 1004 /* mat_mkl_pardiso->iparm[20] = 1; */ /* Apply 1x1 and 2x2 Bunch-Kaufman pivoting during the factorization process */ 1005 #if defined(PETSC_USE_DEBUG) 1006 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 1007 #endif 1008 } 1009 ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 1010 for(i = 0; i < A->rmap->N; i++){ 1011 mat_mkl_pardiso->perm[i] = 0; 1012 } 1013 mat_mkl_pardiso->schur_size = 0; 1014 PetscFunctionReturn(0); 1015 } 1016 1017 #undef __FUNCT__ 1018 #define __FUNCT__ "MatFactorSymbolic_AIJMKL_PARDISO_Private" 1019 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 1020 { 1021 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->spptr; 1022 PetscErrorCode ierr; 1023 1024 PetscFunctionBegin; 1025 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 1026 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 1027 1028 /* throw away any previously computed structure */ 1029 if (mat_mkl_pardiso->freeaij) { 1030 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 1031 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 1032 } 1033 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,&mat_mkl_pardiso->a);CHKERRQ(ierr); 1034 mat_mkl_pardiso->n = A->rmap->N; 1035 1036 mat_mkl_pardiso->phase = JOB_ANALYSIS; 1037 1038 MKL_PARDISO (mat_mkl_pardiso->pt, 1039 &mat_mkl_pardiso->maxfct, 1040 &mat_mkl_pardiso->mnum, 1041 &mat_mkl_pardiso->mtype, 1042 &mat_mkl_pardiso->phase, 1043 &mat_mkl_pardiso->n, 1044 mat_mkl_pardiso->a, 1045 mat_mkl_pardiso->ia, 1046 mat_mkl_pardiso->ja, 1047 mat_mkl_pardiso->perm, 1048 &mat_mkl_pardiso->nrhs, 1049 mat_mkl_pardiso->iparm, 1050 &mat_mkl_pardiso->msglvl, 1051 NULL, 1052 NULL, 1053 &mat_mkl_pardiso->err); 1054 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); 1055 1056 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 1057 1058 if (F->factortype == MAT_FACTOR_LU) { 1059 F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 1060 } else { 1061 F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 1062 } 1063 F->ops->solve = MatSolve_MKL_PARDISO; 1064 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 1065 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "MatLUFactorSymbolic_AIJMKL_PARDISO" 1071 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 1072 { 1073 PetscErrorCode ierr; 1074 1075 PetscFunctionBegin; 1076 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 1077 PetscFunctionReturn(0); 1078 } 1079 1080 #undef __FUNCT__ 1081 #define __FUNCT__ "MatCholeskyFactorSymbolic_AIJMKL_PARDISO" 1082 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 1083 { 1084 PetscErrorCode ierr; 1085 1086 PetscFunctionBegin; 1087 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 1088 PetscFunctionReturn(0); 1089 } 1090 1091 #undef __FUNCT__ 1092 #define __FUNCT__ "MatView_MKL_PARDISO" 1093 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 1094 { 1095 PetscErrorCode ierr; 1096 PetscBool iascii; 1097 PetscViewerFormat format; 1098 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->spptr; 1099 PetscInt i; 1100 1101 PetscFunctionBegin; 1102 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 1103 1104 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1105 if (iascii) { 1106 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1107 if (format == PETSC_VIEWER_ASCII_INFO) { 1108 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 1109 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 1110 for(i = 1; i <= 64; i++){ 1111 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 1112 } 1113 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 1114 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 1115 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 1116 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 1117 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 1118 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 1119 } 1120 } 1121 PetscFunctionReturn(0); 1122 } 1123 1124 1125 #undef __FUNCT__ 1126 #define __FUNCT__ "MatGetInfo_MKL_PARDISO" 1127 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 1128 { 1129 Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)A->spptr; 1130 1131 PetscFunctionBegin; 1132 info->block_size = 1.0; 1133 info->nz_used = mat_mkl_pardiso->nz; 1134 info->nz_allocated = mat_mkl_pardiso->nz; 1135 info->nz_unneeded = 0.0; 1136 info->assemblies = 0.0; 1137 info->mallocs = 0.0; 1138 info->memory = 0.0; 1139 info->fill_ratio_given = 0; 1140 info->fill_ratio_needed = 0; 1141 info->factor_mallocs = 0; 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMkl_PardisoSetCntl_MKL_PARDISO" 1147 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 1148 { 1149 Mat_MKL_PARDISO *mat_mkl_pardiso =(Mat_MKL_PARDISO*)F->spptr; 1150 1151 PetscFunctionBegin; 1152 if(icntl <= 64){ 1153 mat_mkl_pardiso->iparm[icntl - 1] = ival; 1154 } else { 1155 if(icntl == 65) 1156 PetscSetMKL_PARDISOThreads(ival); 1157 else if(icntl == 66) 1158 mat_mkl_pardiso->maxfct = ival; 1159 else if(icntl == 67) 1160 mat_mkl_pardiso->mnum = ival; 1161 else if(icntl == 68) 1162 mat_mkl_pardiso->msglvl = ival; 1163 else if(icntl == 69){ 1164 void *pt[IPARM_SIZE]; 1165 mat_mkl_pardiso->mtype = ival; 1166 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 1167 #if defined(PETSC_USE_REAL_SINGLE) 1168 mat_mkl_pardiso->iparm[27] = 1; 1169 #else 1170 mat_mkl_pardiso->iparm[27] = 0; 1171 #endif 1172 mat_mkl_pardiso->iparm[34] = 1; 1173 } else if(icntl==70) { 1174 mat_mkl_pardiso->solve_interior = !!ival; 1175 } 1176 } 1177 PetscFunctionReturn(0); 1178 } 1179 1180 #undef __FUNCT__ 1181 #define __FUNCT__ "MatMkl_PardisoSetCntl" 1182 /*@ 1183 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1184 1185 Logically Collective on Mat 1186 1187 Input Parameters: 1188 + F - the factored matrix obtained by calling MatGetFactor() 1189 . icntl - index of Mkl_Pardiso parameter 1190 - ival - value of Mkl_Pardiso parameter 1191 1192 Options Database: 1193 . -mat_mkl_pardiso_<icntl> <ival> 1194 1195 Level: beginner 1196 1197 References: Mkl_Pardiso Users' Guide 1198 1199 .seealso: MatGetFactor() 1200 @*/ 1201 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1202 { 1203 PetscErrorCode ierr; 1204 1205 PetscFunctionBegin; 1206 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1207 PetscFunctionReturn(0); 1208 } 1209 1210 /*MC 1211 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1212 sequential matrices via the external package MKL_PARDISO. 1213 1214 Works with MATSEQAIJ matrices 1215 1216 Use -pc_type lu -pc_factor_mat_solver_package mkl_pardiso to us this direct solver 1217 1218 Options Database Keys: 1219 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO 1220 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1221 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1222 . -mat_mkl_pardiso_68 - Message level information 1223 . -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 1224 . -mat_mkl_pardiso_1 - Use default values 1225 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1226 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1227 . -mat_mkl_pardiso_5 - User permutation 1228 . -mat_mkl_pardiso_6 - Write solution on x 1229 . -mat_mkl_pardiso_8 - Iterative refinement step 1230 . -mat_mkl_pardiso_10 - Pivoting perturbation 1231 . -mat_mkl_pardiso_11 - Scaling vectors 1232 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1233 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1234 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1235 . -mat_mkl_pardiso_19 - Report number of floating point operations 1236 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1237 . -mat_mkl_pardiso_24 - Parallel factorization control 1238 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1239 . -mat_mkl_pardiso_27 - Matrix checker 1240 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1241 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1242 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1243 1244 Level: beginner 1245 1246 For more information please check mkl_pardiso manual 1247 1248 .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage 1249 1250 M*/ 1251 #undef __FUNCT__ 1252 #define __FUNCT__ "MatFactorGetSolverPackage_mkl_pardiso" 1253 static PetscErrorCode MatFactorGetSolverPackage_mkl_pardiso(Mat A, const MatSolverPackage *type) 1254 { 1255 PetscFunctionBegin; 1256 *type = MATSOLVERMKL_PARDISO; 1257 PetscFunctionReturn(0); 1258 } 1259 1260 #undef __FUNCT__ 1261 #define __FUNCT__ "MatGetFactor_aij_mkl_pardiso" 1262 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1263 { 1264 Mat B; 1265 PetscErrorCode ierr; 1266 Mat_MKL_PARDISO *mat_mkl_pardiso; 1267 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1268 1269 PetscFunctionBegin; 1270 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1271 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1272 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1273 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1274 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1275 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1276 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 1277 ierr = MatSeqBAIJSetPreallocation(B,A->rmap->bs,0,NULL);CHKERRQ(ierr); 1278 ierr = MatSeqSBAIJSetPreallocation(B,A->rmap->bs,0,NULL);CHKERRQ(ierr); 1279 1280 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1281 B->spptr = mat_mkl_pardiso; 1282 1283 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1284 if (ftype == MAT_FACTOR_LU) { 1285 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1286 B->factortype = MAT_FACTOR_LU; 1287 mat_mkl_pardiso->needsym = PETSC_FALSE; 1288 if (isSeqAIJ) { 1289 mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1290 } else if (isSeqBAIJ) { 1291 mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1292 } else if (isSeqSBAIJ) { 1293 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1294 } else { 1295 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1296 } 1297 #if defined(PETSC_USE_COMPLEX) 1298 mat_mkl_pardiso->schur_solver_type = 0; /* use a general solver for the moment */ 1299 mat_mkl_pardiso->mtype = 13; 1300 #else 1301 if (A->structurally_symmetric) { 1302 mat_mkl_pardiso->mtype = 1; 1303 } else { 1304 mat_mkl_pardiso->mtype = 11; 1305 } 1306 #endif 1307 mat_mkl_pardiso->schur_solver_type = 0; 1308 } else { 1309 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1310 B->factortype = MAT_FACTOR_CHOLESKY; 1311 if (isSeqAIJ) { 1312 mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1313 } else if (isSeqBAIJ) { 1314 mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1315 } else if (isSeqSBAIJ) { 1316 mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1317 } else { 1318 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1319 } 1320 mat_mkl_pardiso->needsym = PETSC_TRUE; 1321 #if defined(PETSC_USE_COMPLEX) 1322 mat_mkl_pardiso->schur_solver_type = 0; /* use a general solver for the moment */ 1323 mat_mkl_pardiso->mtype = 13; 1324 #else 1325 if (A->spd_set && A->spd) { 1326 mat_mkl_pardiso->schur_solver_type = 1; 1327 mat_mkl_pardiso->mtype = 2; 1328 } else { 1329 mat_mkl_pardiso->schur_solver_type = 2; 1330 mat_mkl_pardiso->mtype = -2; 1331 } 1332 #endif 1333 } 1334 mat_mkl_pardiso->Destroy = B->ops->destroy; 1335 B->ops->destroy = MatDestroy_MKL_PARDISO; 1336 B->ops->view = MatView_MKL_PARDISO; 1337 B->factortype = ftype; 1338 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1339 B->assembled = PETSC_TRUE; 1340 1341 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mkl_pardiso);CHKERRQ(ierr); 1342 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1343 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1344 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1345 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1346 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MKL_PARDISO);CHKERRQ(ierr); 1347 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MKL_PARDISO);CHKERRQ(ierr); 1348 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1349 1350 *F = B; 1351 PetscFunctionReturn(0); 1352 } 1353 1354 #undef __FUNCT__ 1355 #define __FUNCT__ "MatSolverPackageRegister_MKL_Pardiso" 1356 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MKL_Pardiso(void) 1357 { 1358 PetscErrorCode ierr; 1359 1360 PetscFunctionBegin; 1361 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1362 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1363 ierr = MatSolverPackageRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1364 PetscFunctionReturn(0); 1365 } 1366 1367