1 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 2 #include <../src/mat/impls/sbaij/seq/sbaij.h> 3 #include <../src/mat/impls/dense/seq/dense.h> 4 5 #if defined(PETSC_HAVE_MKL_INTEL_ILP64) 6 #define MKL_ILP64 7 #endif 8 #include <mkl_pardiso.h> 9 10 PETSC_EXTERN void PetscSetMKL_PARDISOThreads(int); 11 12 /* 13 * Possible mkl_pardiso phases that controls the execution of the solver. 14 * For more information check mkl_pardiso manual. 15 */ 16 #define JOB_ANALYSIS 11 17 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION 12 18 #define JOB_ANALYSIS_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 13 19 #define JOB_NUMERICAL_FACTORIZATION 22 20 #define JOB_NUMERICAL_FACTORIZATION_SOLVE_ITERATIVE_REFINEMENT 23 21 #define JOB_SOLVE_ITERATIVE_REFINEMENT 33 22 #define JOB_SOLVE_FORWARD_SUBSTITUTION 331 23 #define JOB_SOLVE_DIAGONAL_SUBSTITUTION 332 24 #define JOB_SOLVE_BACKWARD_SUBSTITUTION 333 25 #define JOB_RELEASE_OF_LU_MEMORY 0 26 #define JOB_RELEASE_OF_ALL_MEMORY -1 27 28 #define IPARM_SIZE 64 29 30 #if defined(PETSC_USE_64BIT_INDICES) 31 #if defined(PETSC_HAVE_MKL_INTEL_ILP64) 32 #define INT_TYPE long long int 33 #define MKL_PARDISO pardiso 34 #define MKL_PARDISO_INIT pardisoinit 35 #else 36 /* this is the case where the MKL BLAS/LAPACK are 32 bit integers but the 64 bit integer version of 37 of Pardiso code is used; hence the need for the 64 below*/ 38 #define INT_TYPE long long int 39 #define MKL_PARDISO pardiso_64 40 #define MKL_PARDISO_INIT pardiso_64init 41 void pardiso_64init(void *pt, INT_TYPE *mtype, INT_TYPE iparm []) 42 { 43 int iparm_copy[IPARM_SIZE], mtype_copy, i; 44 45 mtype_copy = *mtype; 46 pardisoinit(pt, &mtype_copy, iparm_copy); 47 for (i=0; i<IPARM_SIZE; i++) iparm[i] = iparm_copy[i]; 48 } 49 #endif 50 #else 51 #define INT_TYPE int 52 #define MKL_PARDISO pardiso 53 #define MKL_PARDISO_INIT pardisoinit 54 #endif 55 56 57 /* 58 * Internal data structure. 59 * For more information check mkl_pardiso manual. 60 */ 61 typedef struct { 62 63 /* Configuration vector*/ 64 INT_TYPE iparm[IPARM_SIZE]; 65 66 /* 67 * Internal mkl_pardiso memory location. 68 * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak. 69 */ 70 void *pt[IPARM_SIZE]; 71 72 /* Basic mkl_pardiso info*/ 73 INT_TYPE phase, maxfct, mnum, mtype, n, nrhs, msglvl, err; 74 75 /* Matrix structure*/ 76 void *a; 77 INT_TYPE *ia, *ja; 78 79 /* Number of non-zero elements*/ 80 INT_TYPE nz; 81 82 /* Row permutaton vector*/ 83 INT_TYPE *perm; 84 85 /* Define if matrix preserves sparse structure.*/ 86 MatStructure matstruc; 87 88 PetscBool needsym; 89 PetscBool freeaij; 90 91 /* Schur complement */ 92 PetscScalar *schur; 93 PetscInt schur_size; 94 PetscInt *schur_idxs; 95 PetscScalar *schur_work; 96 PetscBLASInt schur_work_size; 97 PetscBool solve_interior; 98 99 /* True if mkl_pardiso function have been used.*/ 100 PetscBool CleanUp; 101 102 /* Conversion to a format suitable for MKL */ 103 PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool*, INT_TYPE*, INT_TYPE**, INT_TYPE**, PetscScalar**); 104 } Mat_MKL_PARDISO; 105 106 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 107 { 108 Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)A->data; 109 PetscInt bs = A->rmap->bs,i; 110 PetscErrorCode ierr; 111 112 PetscFunctionBegin; 113 if (!sym) { 114 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 115 } 116 *v = aa->a; 117 if (bs == 1) { /* already in the correct format */ 118 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 119 *r = (INT_TYPE*)aa->i; 120 *c = (INT_TYPE*)aa->j; 121 *nnz = (INT_TYPE)aa->nz; 122 *free = PETSC_FALSE; 123 } else if (reuse == MAT_INITIAL_MATRIX) { 124 PetscInt m = A->rmap->n,nz = aa->nz; 125 PetscInt *row,*col; 126 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 127 for (i=0; i<m+1; i++) { 128 row[i] = aa->i[i]+1; 129 } 130 for (i=0; i<nz; i++) { 131 col[i] = aa->j[i]+1; 132 } 133 *r = (INT_TYPE*)row; 134 *c = (INT_TYPE*)col; 135 *nnz = (INT_TYPE)nz; 136 *free = PETSC_TRUE; 137 } 138 PetscFunctionReturn(0); 139 } 140 141 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 142 { 143 Mat_SeqBAIJ *aa = (Mat_SeqBAIJ*)A->data; 144 PetscInt bs = A->rmap->bs,i; 145 PetscErrorCode ierr; 146 147 PetscFunctionBegin; 148 if (!sym) { 149 *v = aa->a; 150 if (bs == 1) { /* already in the correct format */ 151 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 152 *r = (INT_TYPE*)aa->i; 153 *c = (INT_TYPE*)aa->j; 154 *nnz = (INT_TYPE)aa->nz; 155 *free = PETSC_FALSE; 156 PetscFunctionReturn(0); 157 } else if (reuse == MAT_INITIAL_MATRIX) { 158 PetscInt m = A->rmap->n,nz = aa->nz; 159 PetscInt *row,*col; 160 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 161 for (i=0; i<m+1; i++) { 162 row[i] = aa->i[i]+1; 163 } 164 for (i=0; i<nz; i++) { 165 col[i] = aa->j[i]+1; 166 } 167 *r = (INT_TYPE*)row; 168 *c = (INT_TYPE*)col; 169 *nnz = (INT_TYPE)nz; 170 } 171 *free = PETSC_TRUE; 172 } else { 173 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 174 } 175 PetscFunctionReturn(0); 176 } 177 178 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 179 { 180 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data; 181 PetscScalar *aav; 182 PetscErrorCode ierr; 183 184 PetscFunctionBegin; 185 ierr = MatSeqAIJGetArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 186 if (!sym) { /* already in the correct format */ 187 *v = aav; 188 *r = (INT_TYPE*)aa->i; 189 *c = (INT_TYPE*)aa->j; 190 *nnz = (INT_TYPE)aa->nz; 191 *free = PETSC_FALSE; 192 } else if (reuse == MAT_INITIAL_MATRIX) { /* need to get the triangular part */ 193 PetscScalar *vals,*vv; 194 PetscInt *row,*col,*jj; 195 PetscInt m = A->rmap->n,nz,i; 196 197 nz = 0; 198 for (i=0; i<m; i++) nz += aa->i[i+1] - aa->diag[i]; 199 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 200 ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr); 201 jj = col; 202 vv = vals; 203 204 row[0] = 0; 205 for (i=0; i<m; i++) { 206 PetscInt *aj = aa->j + aa->diag[i]; 207 PetscScalar *av = aav + aa->diag[i]; 208 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 209 210 for (j=0; j<rl; j++) { 211 *jj = *aj; jj++; aj++; 212 *vv = *av; vv++; av++; 213 } 214 row[i+1] = row[i] + rl; 215 } 216 *v = vals; 217 *r = (INT_TYPE*)row; 218 *c = (INT_TYPE*)col; 219 *nnz = (INT_TYPE)nz; 220 *free = PETSC_TRUE; 221 } else { 222 PetscScalar *vv; 223 PetscInt m = A->rmap->n,i; 224 225 vv = *v; 226 for (i=0; i<m; i++) { 227 PetscScalar *av = aav + aa->diag[i]; 228 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 229 for (j=0; j<rl; j++) { 230 *vv = *av; vv++; av++; 231 } 232 } 233 *free = PETSC_TRUE; 234 } 235 ierr = MatSeqAIJRestoreArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 236 PetscFunctionReturn(0); 237 } 238 239 240 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X) 241 { 242 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 243 Mat S,Xmat,Bmat; 244 MatFactorSchurStatus schurstatus; 245 PetscErrorCode ierr; 246 247 PetscFunctionBegin; 248 ierr = MatFactorFactorizeSchurComplement(F);CHKERRQ(ierr); 249 ierr = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr); 250 if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 251 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr); 252 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr); 253 ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 254 ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 255 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 256 ierr = MatPinToCPU(Xmat,S->pinnedtocpu);CHKERRQ(ierr); 257 ierr = MatPinToCPU(Bmat,S->pinnedtocpu);CHKERRQ(ierr); 258 #endif 259 260 #if defined(PETSC_USE_COMPLEX) 261 if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet"); 262 #endif 263 264 switch (schurstatus) { 265 case MAT_FACTOR_SCHUR_FACTORED: 266 if (!mpardiso->iparm[12-1]) { 267 ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr); 268 } else { /* transpose solve */ 269 ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr); 270 } 271 break; 272 case MAT_FACTOR_SCHUR_INVERTED: 273 if (!mpardiso->iparm[12-1]) { 274 ierr = MatMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr); 275 } else { /* transpose solve */ 276 ierr = MatTransposeMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr); 277 } 278 break; 279 default: 280 SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status); 281 break; 282 } 283 ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr); 284 ierr = MatDestroy(&Bmat);CHKERRQ(ierr); 285 ierr = MatDestroy(&Xmat);CHKERRQ(ierr); 286 PetscFunctionReturn(0); 287 } 288 289 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 290 { 291 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 292 const PetscScalar *arr; 293 const PetscInt *idxs; 294 PetscInt size,i; 295 PetscMPIInt csize; 296 PetscBool sorted; 297 PetscErrorCode ierr; 298 299 PetscFunctionBegin; 300 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr); 301 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc"); 302 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 303 if (!sorted) { 304 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted"); 305 } 306 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 307 ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr); 308 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 309 ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 310 ierr = MatDestroy(&F->schur);CHKERRQ(ierr); 311 ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr); 312 ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr); 313 mpardiso->schur = (PetscScalar*)arr; 314 mpardiso->schur_size = size; 315 ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr); 316 if (mpardiso->mtype == 2) { 317 ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr); 318 } 319 320 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 321 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 322 ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr); 323 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 324 ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr); 325 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 326 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 327 if (size) { /* turn on Schur switch if the set of indices is not empty */ 328 mpardiso->iparm[36-1] = 2; 329 } 330 PetscFunctionReturn(0); 331 } 332 333 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 334 { 335 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 336 PetscErrorCode ierr; 337 338 PetscFunctionBegin; 339 if (mat_mkl_pardiso->CleanUp) { 340 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 341 342 MKL_PARDISO (mat_mkl_pardiso->pt, 343 &mat_mkl_pardiso->maxfct, 344 &mat_mkl_pardiso->mnum, 345 &mat_mkl_pardiso->mtype, 346 &mat_mkl_pardiso->phase, 347 &mat_mkl_pardiso->n, 348 NULL, 349 NULL, 350 NULL, 351 NULL, 352 &mat_mkl_pardiso->nrhs, 353 mat_mkl_pardiso->iparm, 354 &mat_mkl_pardiso->msglvl, 355 NULL, 356 NULL, 357 &mat_mkl_pardiso->err); 358 } 359 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 360 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 361 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 362 if (mat_mkl_pardiso->freeaij) { 363 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 364 if (mat_mkl_pardiso->iparm[34] == 1) { 365 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 366 } 367 } 368 ierr = PetscFree(A->data);CHKERRQ(ierr); 369 370 /* clear composed functions */ 371 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); 372 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 373 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376 377 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce) 378 { 379 PetscFunctionBegin; 380 if (reduce) { /* data given for the whole matrix */ 381 PetscInt i,m=0,p=0; 382 for (i=0;i<mpardiso->nrhs;i++) { 383 PetscInt j; 384 for (j=0;j<mpardiso->schur_size;j++) { 385 schur[p+j] = whole[m+mpardiso->schur_idxs[j]]; 386 } 387 m += mpardiso->n; 388 p += mpardiso->schur_size; 389 } 390 } else { /* from Schur to whole */ 391 PetscInt i,m=0,p=0; 392 for (i=0;i<mpardiso->nrhs;i++) { 393 PetscInt j; 394 for (j=0;j<mpardiso->schur_size;j++) { 395 whole[m+mpardiso->schur_idxs[j]] = schur[p+j]; 396 } 397 m += mpardiso->n; 398 p += mpardiso->schur_size; 399 } 400 } 401 PetscFunctionReturn(0); 402 } 403 404 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 405 { 406 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 407 PetscErrorCode ierr; 408 PetscScalar *xarray; 409 const PetscScalar *barray; 410 411 PetscFunctionBegin; 412 mat_mkl_pardiso->nrhs = 1; 413 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 414 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 415 416 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 417 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 418 419 if (barray == xarray) { /* if the two vectors share the same memory */ 420 PetscScalar *work; 421 if (!mat_mkl_pardiso->schur_work) { 422 ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr); 423 } else { 424 work = mat_mkl_pardiso->schur_work; 425 } 426 mat_mkl_pardiso->iparm[6-1] = 1; 427 MKL_PARDISO (mat_mkl_pardiso->pt, 428 &mat_mkl_pardiso->maxfct, 429 &mat_mkl_pardiso->mnum, 430 &mat_mkl_pardiso->mtype, 431 &mat_mkl_pardiso->phase, 432 &mat_mkl_pardiso->n, 433 mat_mkl_pardiso->a, 434 mat_mkl_pardiso->ia, 435 mat_mkl_pardiso->ja, 436 NULL, 437 &mat_mkl_pardiso->nrhs, 438 mat_mkl_pardiso->iparm, 439 &mat_mkl_pardiso->msglvl, 440 (void*)xarray, 441 (void*)work, 442 &mat_mkl_pardiso->err); 443 if (!mat_mkl_pardiso->schur_work) { 444 ierr = PetscFree(work);CHKERRQ(ierr); 445 } 446 } else { 447 mat_mkl_pardiso->iparm[6-1] = 0; 448 MKL_PARDISO (mat_mkl_pardiso->pt, 449 &mat_mkl_pardiso->maxfct, 450 &mat_mkl_pardiso->mnum, 451 &mat_mkl_pardiso->mtype, 452 &mat_mkl_pardiso->phase, 453 &mat_mkl_pardiso->n, 454 mat_mkl_pardiso->a, 455 mat_mkl_pardiso->ia, 456 mat_mkl_pardiso->ja, 457 mat_mkl_pardiso->perm, 458 &mat_mkl_pardiso->nrhs, 459 mat_mkl_pardiso->iparm, 460 &mat_mkl_pardiso->msglvl, 461 (void*)barray, 462 (void*)xarray, 463 &mat_mkl_pardiso->err); 464 } 465 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 466 467 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 468 469 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 470 PetscInt shift = mat_mkl_pardiso->schur_size; 471 472 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 473 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 474 475 if (!mat_mkl_pardiso->solve_interior) { 476 /* solve Schur complement */ 477 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 478 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 479 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 480 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */ 481 PetscInt i; 482 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 483 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 484 } 485 } 486 487 /* expansion phase */ 488 mat_mkl_pardiso->iparm[6-1] = 1; 489 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 490 MKL_PARDISO (mat_mkl_pardiso->pt, 491 &mat_mkl_pardiso->maxfct, 492 &mat_mkl_pardiso->mnum, 493 &mat_mkl_pardiso->mtype, 494 &mat_mkl_pardiso->phase, 495 &mat_mkl_pardiso->n, 496 mat_mkl_pardiso->a, 497 mat_mkl_pardiso->ia, 498 mat_mkl_pardiso->ja, 499 mat_mkl_pardiso->perm, 500 &mat_mkl_pardiso->nrhs, 501 mat_mkl_pardiso->iparm, 502 &mat_mkl_pardiso->msglvl, 503 (void*)xarray, 504 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 505 &mat_mkl_pardiso->err); 506 507 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 508 mat_mkl_pardiso->iparm[6-1] = 0; 509 } 510 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 511 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 512 PetscFunctionReturn(0); 513 } 514 515 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 516 { 517 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 518 PetscInt oiparm12; 519 PetscErrorCode ierr; 520 521 PetscFunctionBegin; 522 oiparm12 = mat_mkl_pardiso->iparm[12 - 1]; 523 mat_mkl_pardiso->iparm[12 - 1] = 2; 524 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 525 mat_mkl_pardiso->iparm[12 - 1] = oiparm12; 526 PetscFunctionReturn(0); 527 } 528 529 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 530 { 531 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 532 PetscErrorCode ierr; 533 const PetscScalar *barray; 534 PetscScalar *xarray; 535 PetscBool flg; 536 537 PetscFunctionBegin; 538 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 539 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 540 if (X != B) { 541 ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 542 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 543 } 544 545 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 546 547 if (mat_mkl_pardiso->nrhs > 0) { 548 ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr); 549 ierr = MatDenseGetArray(X,&xarray);CHKERRQ(ierr); 550 551 if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location"); 552 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 553 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 554 555 MKL_PARDISO (mat_mkl_pardiso->pt, 556 &mat_mkl_pardiso->maxfct, 557 &mat_mkl_pardiso->mnum, 558 &mat_mkl_pardiso->mtype, 559 &mat_mkl_pardiso->phase, 560 &mat_mkl_pardiso->n, 561 mat_mkl_pardiso->a, 562 mat_mkl_pardiso->ia, 563 mat_mkl_pardiso->ja, 564 mat_mkl_pardiso->perm, 565 &mat_mkl_pardiso->nrhs, 566 mat_mkl_pardiso->iparm, 567 &mat_mkl_pardiso->msglvl, 568 (void*)barray, 569 (void*)xarray, 570 &mat_mkl_pardiso->err); 571 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 572 573 ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr); 574 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 575 PetscScalar *o_schur_work = NULL; 576 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 577 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 578 579 /* allocate extra memory if it is needed */ 580 scale = 1; 581 if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2; 582 583 mem *= scale; 584 if (mem > mat_mkl_pardiso->schur_work_size) { 585 o_schur_work = mat_mkl_pardiso->schur_work; 586 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 587 } 588 589 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 590 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 591 592 /* solve Schur complement */ 593 if (!mat_mkl_pardiso->solve_interior) { 594 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 595 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 596 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 597 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */ 598 PetscInt i,n,m=0; 599 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 600 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 601 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 602 } 603 m += mat_mkl_pardiso->n; 604 } 605 } 606 607 /* expansion phase */ 608 mat_mkl_pardiso->iparm[6-1] = 1; 609 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 610 MKL_PARDISO (mat_mkl_pardiso->pt, 611 &mat_mkl_pardiso->maxfct, 612 &mat_mkl_pardiso->mnum, 613 &mat_mkl_pardiso->mtype, 614 &mat_mkl_pardiso->phase, 615 &mat_mkl_pardiso->n, 616 mat_mkl_pardiso->a, 617 mat_mkl_pardiso->ia, 618 mat_mkl_pardiso->ja, 619 mat_mkl_pardiso->perm, 620 &mat_mkl_pardiso->nrhs, 621 mat_mkl_pardiso->iparm, 622 &mat_mkl_pardiso->msglvl, 623 (void*)xarray, 624 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 625 &mat_mkl_pardiso->err); 626 if (o_schur_work) { /* restore original schur_work (minimal size) */ 627 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 628 mat_mkl_pardiso->schur_work = o_schur_work; 629 } 630 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 631 mat_mkl_pardiso->iparm[6-1] = 0; 632 } 633 } 634 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 635 PetscFunctionReturn(0); 636 } 637 638 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 639 { 640 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data; 641 PetscErrorCode ierr; 642 643 PetscFunctionBegin; 644 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 645 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); 646 647 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 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 NULL, 662 (void*)mat_mkl_pardiso->schur, 663 &mat_mkl_pardiso->err); 664 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 665 666 /* report flops */ 667 if (mat_mkl_pardiso->iparm[18] > 0) { 668 ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr); 669 } 670 671 if (F->schur) { /* schur output from pardiso is in row major format */ 672 #if defined(PETSC_HAVE_CUDA) 673 F->schur->offloadmask = PETSC_OFFLOAD_CPU; 674 #endif 675 ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr); 676 ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr); 677 } 678 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 679 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 680 PetscFunctionReturn(0); 681 } 682 683 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 684 { 685 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 686 PetscErrorCode ierr; 687 PetscInt icntl,threads=1; 688 PetscBool flg; 689 690 PetscFunctionBegin; 691 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 692 693 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 694 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 695 696 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); 697 if (flg) mat_mkl_pardiso->maxfct = icntl; 698 699 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 700 if (flg) mat_mkl_pardiso->mnum = icntl; 701 702 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 703 if (flg) mat_mkl_pardiso->msglvl = icntl; 704 705 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 706 if (flg) { 707 void *pt[IPARM_SIZE]; 708 mat_mkl_pardiso->mtype = icntl; 709 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 710 #if defined(PETSC_USE_REAL_SINGLE) 711 mat_mkl_pardiso->iparm[27] = 1; 712 #else 713 mat_mkl_pardiso->iparm[27] = 0; 714 #endif 715 mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */ 716 } 717 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 718 719 if (flg && icntl != 0) { 720 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 721 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 722 723 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 724 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 725 726 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 727 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 728 729 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 730 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 731 732 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 733 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 734 735 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 736 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 737 738 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 739 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 740 741 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 742 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 743 744 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 745 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 746 747 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 748 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 749 750 ierr = PetscOptionsInt("-mat_mkl_pardiso_19","Report number of floating point operations (0 to disable)","None",mat_mkl_pardiso->iparm[18],&icntl,&flg);CHKERRQ(ierr); 751 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 752 753 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 754 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 755 756 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 757 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 758 759 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 760 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 761 762 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 763 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 764 765 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); 766 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 767 768 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); 769 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 770 771 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 772 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 773 } 774 PetscOptionsEnd(); 775 PetscFunctionReturn(0); 776 } 777 778 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 779 { 780 PetscErrorCode ierr; 781 PetscInt i,bs; 782 PetscBool match; 783 784 PetscFunctionBegin; 785 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0; 786 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0; 787 /* Default options for both sym and unsym */ 788 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 789 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 790 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 791 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 792 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 793 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 794 #if 0 795 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 796 #endif 797 ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr); 798 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 799 if (!match || bs == 1) { 800 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 801 mat_mkl_pardiso->n = A->rmap->N; 802 } else { 803 mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */ 804 mat_mkl_pardiso->iparm[36] = bs; 805 mat_mkl_pardiso->n = A->rmap->N/bs; 806 } 807 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on master */ 808 809 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 810 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 811 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 812 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 813 mat_mkl_pardiso->phase = -1; 814 mat_mkl_pardiso->err = 0; 815 816 mat_mkl_pardiso->nrhs = 1; 817 mat_mkl_pardiso->err = 0; 818 mat_mkl_pardiso->phase = -1; 819 820 if (ftype == MAT_FACTOR_LU) { 821 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 822 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 823 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 824 } else { 825 mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */ 826 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 827 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 828 #if defined(PETSC_USE_DEBUG) 829 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 830 #endif 831 } 832 ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 833 for (i=0; i<A->rmap->N; i++) { 834 mat_mkl_pardiso->perm[i] = 0; 835 } 836 mat_mkl_pardiso->schur_size = 0; 837 PetscFunctionReturn(0); 838 } 839 840 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 841 { 842 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 843 PetscErrorCode ierr; 844 845 PetscFunctionBegin; 846 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 847 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 848 849 /* throw away any previously computed structure */ 850 if (mat_mkl_pardiso->freeaij) { 851 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 852 if (mat_mkl_pardiso->iparm[34] == 1) { 853 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 854 } 855 } 856 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); 857 if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N; 858 else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs; 859 860 mat_mkl_pardiso->phase = JOB_ANALYSIS; 861 862 /* reset flops counting if requested */ 863 if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1; 864 865 MKL_PARDISO (mat_mkl_pardiso->pt, 866 &mat_mkl_pardiso->maxfct, 867 &mat_mkl_pardiso->mnum, 868 &mat_mkl_pardiso->mtype, 869 &mat_mkl_pardiso->phase, 870 &mat_mkl_pardiso->n, 871 mat_mkl_pardiso->a, 872 mat_mkl_pardiso->ia, 873 mat_mkl_pardiso->ja, 874 mat_mkl_pardiso->perm, 875 &mat_mkl_pardiso->nrhs, 876 mat_mkl_pardiso->iparm, 877 &mat_mkl_pardiso->msglvl, 878 NULL, 879 NULL, 880 &mat_mkl_pardiso->err); 881 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 882 883 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 884 885 if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 886 else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 887 888 F->ops->solve = MatSolve_MKL_PARDISO; 889 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 890 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 891 PetscFunctionReturn(0); 892 } 893 894 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 895 { 896 PetscErrorCode ierr; 897 898 PetscFunctionBegin; 899 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 900 PetscFunctionReturn(0); 901 } 902 903 #if !defined(PETSC_USE_COMPLEX) 904 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) 905 { 906 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data; 907 908 PetscFunctionBegin; 909 if (nneg) *nneg = mat_mkl_pardiso->iparm[22]; 910 if (npos) *npos = mat_mkl_pardiso->iparm[21]; 911 if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]); 912 PetscFunctionReturn(0); 913 } 914 #endif 915 916 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 917 { 918 PetscErrorCode ierr; 919 920 PetscFunctionBegin; 921 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 922 #if defined(PETSC_USE_COMPLEX) 923 F->ops->getinertia = NULL; 924 #else 925 F->ops->getinertia = MatGetInertia_MKL_PARDISO; 926 #endif 927 PetscFunctionReturn(0); 928 } 929 930 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 931 { 932 PetscErrorCode ierr; 933 PetscBool iascii; 934 PetscViewerFormat format; 935 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 936 PetscInt i; 937 938 PetscFunctionBegin; 939 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 940 941 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 942 if (iascii) { 943 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 944 if (format == PETSC_VIEWER_ASCII_INFO) { 945 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 946 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 947 for (i=1; i<=64; i++) { 948 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 949 } 950 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 951 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 952 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 953 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 954 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 955 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 956 } 957 } 958 PetscFunctionReturn(0); 959 } 960 961 962 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 963 { 964 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data; 965 966 PetscFunctionBegin; 967 info->block_size = 1.0; 968 info->nz_used = mat_mkl_pardiso->iparm[17]; 969 info->nz_allocated = mat_mkl_pardiso->iparm[17]; 970 info->nz_unneeded = 0.0; 971 info->assemblies = 0.0; 972 info->mallocs = 0.0; 973 info->memory = 0.0; 974 info->fill_ratio_given = 0; 975 info->fill_ratio_needed = 0; 976 info->factor_mallocs = 0; 977 PetscFunctionReturn(0); 978 } 979 980 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 981 { 982 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 983 984 PetscFunctionBegin; 985 if (icntl <= 64) { 986 mat_mkl_pardiso->iparm[icntl - 1] = ival; 987 } else { 988 if (icntl == 65) PetscSetMKL_PARDISOThreads(ival); 989 else if (icntl == 66) mat_mkl_pardiso->maxfct = ival; 990 else if (icntl == 67) mat_mkl_pardiso->mnum = ival; 991 else if (icntl == 68) mat_mkl_pardiso->msglvl = ival; 992 else if (icntl == 69) { 993 void *pt[IPARM_SIZE]; 994 mat_mkl_pardiso->mtype = ival; 995 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 996 #if defined(PETSC_USE_REAL_SINGLE) 997 mat_mkl_pardiso->iparm[27] = 1; 998 #else 999 mat_mkl_pardiso->iparm[27] = 0; 1000 #endif 1001 mat_mkl_pardiso->iparm[34] = 1; 1002 } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival; 1003 } 1004 PetscFunctionReturn(0); 1005 } 1006 1007 /*@ 1008 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1009 1010 Logically Collective on Mat 1011 1012 Input Parameters: 1013 + F - the factored matrix obtained by calling MatGetFactor() 1014 . icntl - index of Mkl_Pardiso parameter 1015 - ival - value of Mkl_Pardiso parameter 1016 1017 Options Database: 1018 . -mat_mkl_pardiso_<icntl> <ival> 1019 1020 Level: beginner 1021 1022 References: 1023 . Mkl_Pardiso Users' Guide 1024 1025 .seealso: MatGetFactor() 1026 @*/ 1027 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1028 { 1029 PetscErrorCode ierr; 1030 1031 PetscFunctionBegin; 1032 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1033 PetscFunctionReturn(0); 1034 } 1035 1036 /*MC 1037 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1038 sequential matrices via the external package MKL_PARDISO. 1039 1040 Works with MATSEQAIJ matrices 1041 1042 Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver 1043 1044 Options Database Keys: 1045 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO 1046 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1047 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1048 . -mat_mkl_pardiso_68 - Message level information 1049 . -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 1050 . -mat_mkl_pardiso_1 - Use default values 1051 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1052 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1053 . -mat_mkl_pardiso_5 - User permutation 1054 . -mat_mkl_pardiso_6 - Write solution on x 1055 . -mat_mkl_pardiso_8 - Iterative refinement step 1056 . -mat_mkl_pardiso_10 - Pivoting perturbation 1057 . -mat_mkl_pardiso_11 - Scaling vectors 1058 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1059 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1060 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1061 . -mat_mkl_pardiso_19 - Report number of floating point operations 1062 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1063 . -mat_mkl_pardiso_24 - Parallel factorization control 1064 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1065 . -mat_mkl_pardiso_27 - Matrix checker 1066 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1067 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1068 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1069 1070 Level: beginner 1071 1072 For more information please check mkl_pardiso manual 1073 1074 .seealso: PCFactorSetMatSolverType(), MatSolverType 1075 1076 M*/ 1077 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type) 1078 { 1079 PetscFunctionBegin; 1080 *type = MATSOLVERMKL_PARDISO; 1081 PetscFunctionReturn(0); 1082 } 1083 1084 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1085 { 1086 Mat B; 1087 PetscErrorCode ierr; 1088 Mat_MKL_PARDISO *mat_mkl_pardiso; 1089 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1090 1091 PetscFunctionBegin; 1092 ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1093 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1094 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1095 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1096 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1097 ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr); 1098 ierr = MatSetUp(B);CHKERRQ(ierr); 1099 1100 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1101 B->data = mat_mkl_pardiso; 1102 1103 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1104 if (ftype == MAT_FACTOR_LU) { 1105 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1106 B->factortype = MAT_FACTOR_LU; 1107 mat_mkl_pardiso->needsym = PETSC_FALSE; 1108 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1109 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1110 else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1111 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1112 #if defined(PETSC_USE_COMPLEX) 1113 mat_mkl_pardiso->mtype = 13; 1114 #else 1115 mat_mkl_pardiso->mtype = 11; 1116 #endif 1117 } else { 1118 #if defined(PETSC_USE_COMPLEX) 1119 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with complex scalars! Use MAT_FACTOR_LU instead",((PetscObject)A)->type_name); 1120 #endif 1121 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1122 B->factortype = MAT_FACTOR_CHOLESKY; 1123 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1124 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1125 else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1126 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1127 1128 mat_mkl_pardiso->needsym = PETSC_TRUE; 1129 if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2; 1130 else mat_mkl_pardiso->mtype = -2; 1131 } 1132 B->ops->destroy = MatDestroy_MKL_PARDISO; 1133 B->ops->view = MatView_MKL_PARDISO; 1134 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1135 B->factortype = ftype; 1136 B->assembled = PETSC_TRUE; 1137 1138 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 1139 ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr); 1140 1141 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr); 1142 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1143 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1144 1145 *F = B; 1146 PetscFunctionReturn(0); 1147 } 1148 1149 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void) 1150 { 1151 PetscErrorCode ierr; 1152 1153 PetscFunctionBegin; 1154 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1155 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1156 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1157 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1158 PetscFunctionReturn(0); 1159 } 1160 1161