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