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) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 114 *v = aa->a; 115 if (bs == 1) { /* already in the correct format */ 116 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 117 *r = (INT_TYPE*)aa->i; 118 *c = (INT_TYPE*)aa->j; 119 *nnz = (INT_TYPE)aa->nz; 120 *free = PETSC_FALSE; 121 } else if (reuse == MAT_INITIAL_MATRIX) { 122 PetscInt m = A->rmap->n,nz = aa->nz; 123 PetscInt *row,*col; 124 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 125 for (i=0; i<m+1; i++) { 126 row[i] = aa->i[i]+1; 127 } 128 for (i=0; i<nz; i++) { 129 col[i] = aa->j[i]+1; 130 } 131 *r = (INT_TYPE*)row; 132 *c = (INT_TYPE*)col; 133 *nnz = (INT_TYPE)nz; 134 *free = PETSC_TRUE; 135 } 136 PetscFunctionReturn(0); 137 } 138 139 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 140 { 141 Mat_SeqBAIJ *aa = (Mat_SeqBAIJ*)A->data; 142 PetscInt bs = A->rmap->bs,i; 143 PetscErrorCode ierr; 144 145 PetscFunctionBegin; 146 if (!sym) { 147 *v = aa->a; 148 if (bs == 1) { /* already in the correct format */ 149 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 150 *r = (INT_TYPE*)aa->i; 151 *c = (INT_TYPE*)aa->j; 152 *nnz = (INT_TYPE)aa->nz; 153 *free = PETSC_FALSE; 154 PetscFunctionReturn(0); 155 } else if (reuse == MAT_INITIAL_MATRIX) { 156 PetscInt m = A->rmap->n,nz = aa->nz; 157 PetscInt *row,*col; 158 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 159 for (i=0; i<m+1; i++) { 160 row[i] = aa->i[i]+1; 161 } 162 for (i=0; i<nz; i++) { 163 col[i] = aa->j[i]+1; 164 } 165 *r = (INT_TYPE*)row; 166 *c = (INT_TYPE*)col; 167 *nnz = (INT_TYPE)nz; 168 } 169 *free = PETSC_TRUE; 170 } else { 171 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 172 } 173 PetscFunctionReturn(0); 174 } 175 176 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 177 { 178 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data; 179 PetscScalar *aav; 180 PetscErrorCode ierr; 181 182 PetscFunctionBegin; 183 ierr = MatSeqAIJGetArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 184 if (!sym) { /* already in the correct format */ 185 *v = aav; 186 *r = (INT_TYPE*)aa->i; 187 *c = (INT_TYPE*)aa->j; 188 *nnz = (INT_TYPE)aa->nz; 189 *free = PETSC_FALSE; 190 } else if (reuse == MAT_INITIAL_MATRIX) { /* need to get the triangular part */ 191 PetscScalar *vals,*vv; 192 PetscInt *row,*col,*jj; 193 PetscInt m = A->rmap->n,nz,i; 194 195 nz = 0; 196 for (i=0; i<m; i++) nz += aa->i[i+1] - aa->diag[i]; 197 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 198 ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr); 199 jj = col; 200 vv = vals; 201 202 row[0] = 0; 203 for (i=0; i<m; i++) { 204 PetscInt *aj = aa->j + aa->diag[i]; 205 PetscScalar *av = aav + aa->diag[i]; 206 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 207 208 for (j=0; j<rl; j++) { 209 *jj = *aj; jj++; aj++; 210 *vv = *av; vv++; av++; 211 } 212 row[i+1] = row[i] + rl; 213 } 214 *v = vals; 215 *r = (INT_TYPE*)row; 216 *c = (INT_TYPE*)col; 217 *nnz = (INT_TYPE)nz; 218 *free = PETSC_TRUE; 219 } else { 220 PetscScalar *vv; 221 PetscInt m = A->rmap->n,i; 222 223 vv = *v; 224 for (i=0; i<m; i++) { 225 PetscScalar *av = aav + aa->diag[i]; 226 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 227 for (j=0; j<rl; j++) { 228 *vv = *av; vv++; av++; 229 } 230 } 231 *free = PETSC_TRUE; 232 } 233 ierr = MatSeqAIJRestoreArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 234 PetscFunctionReturn(0); 235 } 236 237 238 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X) 239 { 240 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 241 Mat S,Xmat,Bmat; 242 MatFactorSchurStatus schurstatus; 243 PetscErrorCode ierr; 244 245 PetscFunctionBegin; 246 ierr = MatFactorFactorizeSchurComplement(F);CHKERRQ(ierr); 247 ierr = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr); 248 if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 249 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr); 250 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr); 251 ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 252 ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 253 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 254 ierr = MatPinToCPU(Xmat,S->pinnedtocpu);CHKERRQ(ierr); 255 ierr = MatPinToCPU(Bmat,S->pinnedtocpu);CHKERRQ(ierr); 256 #endif 257 258 #if defined(PETSC_USE_COMPLEX) 259 if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet"); 260 #endif 261 262 switch (schurstatus) { 263 case MAT_FACTOR_SCHUR_FACTORED: 264 if (!mpardiso->iparm[12-1]) { 265 ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr); 266 } else { /* transpose solve */ 267 ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr); 268 } 269 break; 270 case MAT_FACTOR_SCHUR_INVERTED: 271 if (!mpardiso->iparm[12-1]) { 272 ierr = MatMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr); 273 } else { /* transpose solve */ 274 ierr = MatTransposeMatMult(S,Bmat,MAT_REUSE_MATRIX,PETSC_DEFAULT,&Xmat);CHKERRQ(ierr); 275 } 276 break; 277 default: 278 SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status); 279 break; 280 } 281 ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr); 282 ierr = MatDestroy(&Bmat);CHKERRQ(ierr); 283 ierr = MatDestroy(&Xmat);CHKERRQ(ierr); 284 PetscFunctionReturn(0); 285 } 286 287 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 288 { 289 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 290 const PetscScalar *arr; 291 const PetscInt *idxs; 292 PetscInt size,i; 293 PetscMPIInt csize; 294 PetscBool sorted; 295 PetscErrorCode ierr; 296 297 PetscFunctionBegin; 298 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRQ(ierr); 299 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc"); 300 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 301 if (!sorted) { 302 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted"); 303 } 304 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 305 ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr); 306 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 307 ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 308 ierr = MatDestroy(&F->schur);CHKERRQ(ierr); 309 ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr); 310 ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr); 311 mpardiso->schur = (PetscScalar*)arr; 312 mpardiso->schur_size = size; 313 ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr); 314 if (mpardiso->mtype == 2) { 315 ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr); 316 } 317 318 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 319 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 320 ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr); 321 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 322 ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr); 323 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 324 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 325 if (size) { /* turn on Schur switch if the set of indices is not empty */ 326 mpardiso->iparm[36-1] = 2; 327 } 328 PetscFunctionReturn(0); 329 } 330 331 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 332 { 333 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 334 PetscErrorCode ierr; 335 336 PetscFunctionBegin; 337 if (mat_mkl_pardiso->CleanUp) { 338 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 339 340 MKL_PARDISO (mat_mkl_pardiso->pt, 341 &mat_mkl_pardiso->maxfct, 342 &mat_mkl_pardiso->mnum, 343 &mat_mkl_pardiso->mtype, 344 &mat_mkl_pardiso->phase, 345 &mat_mkl_pardiso->n, 346 NULL, 347 NULL, 348 NULL, 349 NULL, 350 &mat_mkl_pardiso->nrhs, 351 mat_mkl_pardiso->iparm, 352 &mat_mkl_pardiso->msglvl, 353 NULL, 354 NULL, 355 &mat_mkl_pardiso->err); 356 } 357 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 358 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 359 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 360 if (mat_mkl_pardiso->freeaij) { 361 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 362 if (mat_mkl_pardiso->iparm[34] == 1) { 363 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 364 } 365 } 366 ierr = PetscFree(A->data);CHKERRQ(ierr); 367 368 /* clear composed functions */ 369 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); 370 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 371 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 372 PetscFunctionReturn(0); 373 } 374 375 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce) 376 { 377 PetscFunctionBegin; 378 if (reduce) { /* data given for the whole matrix */ 379 PetscInt i,m=0,p=0; 380 for (i=0;i<mpardiso->nrhs;i++) { 381 PetscInt j; 382 for (j=0;j<mpardiso->schur_size;j++) { 383 schur[p+j] = whole[m+mpardiso->schur_idxs[j]]; 384 } 385 m += mpardiso->n; 386 p += mpardiso->schur_size; 387 } 388 } else { /* from Schur to whole */ 389 PetscInt i,m=0,p=0; 390 for (i=0;i<mpardiso->nrhs;i++) { 391 PetscInt j; 392 for (j=0;j<mpardiso->schur_size;j++) { 393 whole[m+mpardiso->schur_idxs[j]] = schur[p+j]; 394 } 395 m += mpardiso->n; 396 p += mpardiso->schur_size; 397 } 398 } 399 PetscFunctionReturn(0); 400 } 401 402 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 403 { 404 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 405 PetscErrorCode ierr; 406 PetscScalar *xarray; 407 const PetscScalar *barray; 408 409 PetscFunctionBegin; 410 mat_mkl_pardiso->nrhs = 1; 411 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 412 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 413 414 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 415 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 416 417 if (barray == xarray) { /* if the two vectors share the same memory */ 418 PetscScalar *work; 419 if (!mat_mkl_pardiso->schur_work) { 420 ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr); 421 } else { 422 work = mat_mkl_pardiso->schur_work; 423 } 424 mat_mkl_pardiso->iparm[6-1] = 1; 425 MKL_PARDISO (mat_mkl_pardiso->pt, 426 &mat_mkl_pardiso->maxfct, 427 &mat_mkl_pardiso->mnum, 428 &mat_mkl_pardiso->mtype, 429 &mat_mkl_pardiso->phase, 430 &mat_mkl_pardiso->n, 431 mat_mkl_pardiso->a, 432 mat_mkl_pardiso->ia, 433 mat_mkl_pardiso->ja, 434 NULL, 435 &mat_mkl_pardiso->nrhs, 436 mat_mkl_pardiso->iparm, 437 &mat_mkl_pardiso->msglvl, 438 (void*)xarray, 439 (void*)work, 440 &mat_mkl_pardiso->err); 441 if (!mat_mkl_pardiso->schur_work) { 442 ierr = PetscFree(work);CHKERRQ(ierr); 443 } 444 } else { 445 mat_mkl_pardiso->iparm[6-1] = 0; 446 MKL_PARDISO (mat_mkl_pardiso->pt, 447 &mat_mkl_pardiso->maxfct, 448 &mat_mkl_pardiso->mnum, 449 &mat_mkl_pardiso->mtype, 450 &mat_mkl_pardiso->phase, 451 &mat_mkl_pardiso->n, 452 mat_mkl_pardiso->a, 453 mat_mkl_pardiso->ia, 454 mat_mkl_pardiso->ja, 455 mat_mkl_pardiso->perm, 456 &mat_mkl_pardiso->nrhs, 457 mat_mkl_pardiso->iparm, 458 &mat_mkl_pardiso->msglvl, 459 (void*)barray, 460 (void*)xarray, 461 &mat_mkl_pardiso->err); 462 } 463 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 464 465 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); 466 467 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 468 PetscInt shift = mat_mkl_pardiso->schur_size; 469 470 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 471 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 472 473 if (!mat_mkl_pardiso->solve_interior) { 474 /* solve Schur complement */ 475 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 476 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 477 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 478 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */ 479 PetscInt i; 480 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 481 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 482 } 483 } 484 485 /* expansion phase */ 486 mat_mkl_pardiso->iparm[6-1] = 1; 487 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 488 MKL_PARDISO (mat_mkl_pardiso->pt, 489 &mat_mkl_pardiso->maxfct, 490 &mat_mkl_pardiso->mnum, 491 &mat_mkl_pardiso->mtype, 492 &mat_mkl_pardiso->phase, 493 &mat_mkl_pardiso->n, 494 mat_mkl_pardiso->a, 495 mat_mkl_pardiso->ia, 496 mat_mkl_pardiso->ja, 497 mat_mkl_pardiso->perm, 498 &mat_mkl_pardiso->nrhs, 499 mat_mkl_pardiso->iparm, 500 &mat_mkl_pardiso->msglvl, 501 (void*)xarray, 502 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 503 &mat_mkl_pardiso->err); 504 505 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); 506 mat_mkl_pardiso->iparm[6-1] = 0; 507 } 508 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 509 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 510 PetscFunctionReturn(0); 511 } 512 513 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 514 { 515 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 516 PetscInt oiparm12; 517 PetscErrorCode ierr; 518 519 PetscFunctionBegin; 520 oiparm12 = mat_mkl_pardiso->iparm[12 - 1]; 521 mat_mkl_pardiso->iparm[12 - 1] = 2; 522 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 523 mat_mkl_pardiso->iparm[12 - 1] = oiparm12; 524 PetscFunctionReturn(0); 525 } 526 527 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 528 { 529 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 530 PetscErrorCode ierr; 531 const PetscScalar *barray; 532 PetscScalar *xarray; 533 PetscBool flg; 534 535 PetscFunctionBegin; 536 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 537 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 538 ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 539 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 540 541 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 542 543 if (mat_mkl_pardiso->nrhs > 0) { 544 ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr); 545 ierr = MatDenseGetArray(X,&xarray);CHKERRQ(ierr); 546 547 if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location"); 548 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 549 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 550 mat_mkl_pardiso->iparm[6-1] = 0; 551 552 MKL_PARDISO (mat_mkl_pardiso->pt, 553 &mat_mkl_pardiso->maxfct, 554 &mat_mkl_pardiso->mnum, 555 &mat_mkl_pardiso->mtype, 556 &mat_mkl_pardiso->phase, 557 &mat_mkl_pardiso->n, 558 mat_mkl_pardiso->a, 559 mat_mkl_pardiso->ia, 560 mat_mkl_pardiso->ja, 561 mat_mkl_pardiso->perm, 562 &mat_mkl_pardiso->nrhs, 563 mat_mkl_pardiso->iparm, 564 &mat_mkl_pardiso->msglvl, 565 (void*)barray, 566 (void*)xarray, 567 &mat_mkl_pardiso->err); 568 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); 569 570 ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr); 571 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 572 PetscScalar *o_schur_work = NULL; 573 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 574 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 575 576 /* allocate extra memory if it is needed */ 577 scale = 1; 578 if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2; 579 580 mem *= scale; 581 if (mem > mat_mkl_pardiso->schur_work_size) { 582 o_schur_work = mat_mkl_pardiso->schur_work; 583 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 584 } 585 586 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 587 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 588 589 /* solve Schur complement */ 590 if (!mat_mkl_pardiso->solve_interior) { 591 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 592 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 593 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 594 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */ 595 PetscInt i,n,m=0; 596 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 597 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 598 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 599 } 600 m += mat_mkl_pardiso->n; 601 } 602 } 603 604 /* expansion phase */ 605 mat_mkl_pardiso->iparm[6-1] = 1; 606 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 607 MKL_PARDISO (mat_mkl_pardiso->pt, 608 &mat_mkl_pardiso->maxfct, 609 &mat_mkl_pardiso->mnum, 610 &mat_mkl_pardiso->mtype, 611 &mat_mkl_pardiso->phase, 612 &mat_mkl_pardiso->n, 613 mat_mkl_pardiso->a, 614 mat_mkl_pardiso->ia, 615 mat_mkl_pardiso->ja, 616 mat_mkl_pardiso->perm, 617 &mat_mkl_pardiso->nrhs, 618 mat_mkl_pardiso->iparm, 619 &mat_mkl_pardiso->msglvl, 620 (void*)xarray, 621 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 622 &mat_mkl_pardiso->err); 623 if (o_schur_work) { /* restore original schur_work (minimal size) */ 624 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 625 mat_mkl_pardiso->schur_work = o_schur_work; 626 } 627 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); 628 mat_mkl_pardiso->iparm[6-1] = 0; 629 } 630 } 631 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 632 PetscFunctionReturn(0); 633 } 634 635 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 636 { 637 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data; 638 PetscErrorCode ierr; 639 640 PetscFunctionBegin; 641 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 642 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); 643 644 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 645 MKL_PARDISO (mat_mkl_pardiso->pt, 646 &mat_mkl_pardiso->maxfct, 647 &mat_mkl_pardiso->mnum, 648 &mat_mkl_pardiso->mtype, 649 &mat_mkl_pardiso->phase, 650 &mat_mkl_pardiso->n, 651 mat_mkl_pardiso->a, 652 mat_mkl_pardiso->ia, 653 mat_mkl_pardiso->ja, 654 mat_mkl_pardiso->perm, 655 &mat_mkl_pardiso->nrhs, 656 mat_mkl_pardiso->iparm, 657 &mat_mkl_pardiso->msglvl, 658 NULL, 659 (void*)mat_mkl_pardiso->schur, 660 &mat_mkl_pardiso->err); 661 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); 662 663 /* report flops */ 664 if (mat_mkl_pardiso->iparm[18] > 0) { 665 ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr); 666 } 667 668 if (F->schur) { /* schur output from pardiso is in row major format */ 669 #if defined(PETSC_HAVE_CUDA) 670 F->schur->offloadmask = PETSC_OFFLOAD_CPU; 671 #endif 672 ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr); 673 ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr); 674 } 675 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 676 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 677 PetscFunctionReturn(0); 678 } 679 680 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 681 { 682 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 683 PetscErrorCode ierr; 684 PetscInt icntl,threads=1; 685 PetscBool flg; 686 687 PetscFunctionBegin; 688 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 689 690 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 691 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 692 693 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); 694 if (flg) mat_mkl_pardiso->maxfct = icntl; 695 696 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 697 if (flg) mat_mkl_pardiso->mnum = icntl; 698 699 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 700 if (flg) mat_mkl_pardiso->msglvl = icntl; 701 702 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 703 if (flg) { 704 void *pt[IPARM_SIZE]; 705 mat_mkl_pardiso->mtype = icntl; 706 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 707 #if defined(PETSC_USE_REAL_SINGLE) 708 mat_mkl_pardiso->iparm[27] = 1; 709 #else 710 mat_mkl_pardiso->iparm[27] = 0; 711 #endif 712 mat_mkl_pardiso->iparm[34] = 1; /* use 0-based indexing */ 713 } 714 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 715 716 if (flg && icntl != 0) { 717 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 718 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 719 720 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 721 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 722 723 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 724 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 725 726 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 727 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 728 729 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 730 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 731 732 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 733 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 734 735 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 736 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 737 738 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 739 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 740 741 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 742 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 743 744 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 745 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 746 747 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); 748 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 749 750 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 751 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 752 753 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 754 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 755 756 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 757 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 758 759 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 760 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 761 762 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); 763 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 764 765 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); 766 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 767 768 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 769 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 770 } 771 PetscOptionsEnd(); 772 PetscFunctionReturn(0); 773 } 774 775 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 776 { 777 PetscErrorCode ierr; 778 PetscInt i,bs; 779 PetscBool match; 780 781 PetscFunctionBegin; 782 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0; 783 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0; 784 /* Default options for both sym and unsym */ 785 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 786 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 787 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 788 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 789 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 790 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 791 #if 0 792 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 793 #endif 794 ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr); 795 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 796 if (!match || bs == 1) { 797 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 798 mat_mkl_pardiso->n = A->rmap->N; 799 } else { 800 mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */ 801 mat_mkl_pardiso->iparm[36] = bs; 802 mat_mkl_pardiso->n = A->rmap->N/bs; 803 } 804 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on master */ 805 806 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 807 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 808 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 809 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 810 mat_mkl_pardiso->phase = -1; 811 mat_mkl_pardiso->err = 0; 812 813 mat_mkl_pardiso->nrhs = 1; 814 mat_mkl_pardiso->err = 0; 815 mat_mkl_pardiso->phase = -1; 816 817 if (ftype == MAT_FACTOR_LU) { 818 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 819 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 820 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 821 } else { 822 mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */ 823 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 824 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 825 #if defined(PETSC_USE_DEBUG) 826 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 827 #endif 828 } 829 ierr = PetscMalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 830 for (i=0; i<A->rmap->N; i++) { 831 mat_mkl_pardiso->perm[i] = 0; 832 } 833 mat_mkl_pardiso->schur_size = 0; 834 PetscFunctionReturn(0); 835 } 836 837 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 838 { 839 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 840 PetscErrorCode ierr; 841 842 PetscFunctionBegin; 843 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 844 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 845 846 /* throw away any previously computed structure */ 847 if (mat_mkl_pardiso->freeaij) { 848 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 849 if (mat_mkl_pardiso->iparm[34] == 1) { 850 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 851 } 852 } 853 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); 854 if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N; 855 else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs; 856 857 mat_mkl_pardiso->phase = JOB_ANALYSIS; 858 859 /* reset flops counting if requested */ 860 if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1; 861 862 MKL_PARDISO (mat_mkl_pardiso->pt, 863 &mat_mkl_pardiso->maxfct, 864 &mat_mkl_pardiso->mnum, 865 &mat_mkl_pardiso->mtype, 866 &mat_mkl_pardiso->phase, 867 &mat_mkl_pardiso->n, 868 mat_mkl_pardiso->a, 869 mat_mkl_pardiso->ia, 870 mat_mkl_pardiso->ja, 871 mat_mkl_pardiso->perm, 872 &mat_mkl_pardiso->nrhs, 873 mat_mkl_pardiso->iparm, 874 &mat_mkl_pardiso->msglvl, 875 NULL, 876 NULL, 877 &mat_mkl_pardiso->err); 878 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); 879 880 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 881 882 if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 883 else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 884 885 F->ops->solve = MatSolve_MKL_PARDISO; 886 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 887 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 888 PetscFunctionReturn(0); 889 } 890 891 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 892 { 893 PetscErrorCode ierr; 894 895 PetscFunctionBegin; 896 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 897 PetscFunctionReturn(0); 898 } 899 900 #if !defined(PETSC_USE_COMPLEX) 901 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) 902 { 903 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data; 904 905 PetscFunctionBegin; 906 if (nneg) *nneg = mat_mkl_pardiso->iparm[22]; 907 if (npos) *npos = mat_mkl_pardiso->iparm[21]; 908 if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]); 909 PetscFunctionReturn(0); 910 } 911 #endif 912 913 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 914 { 915 PetscErrorCode ierr; 916 917 PetscFunctionBegin; 918 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 919 #if defined(PETSC_USE_COMPLEX) 920 F->ops->getinertia = NULL; 921 #else 922 F->ops->getinertia = MatGetInertia_MKL_PARDISO; 923 #endif 924 PetscFunctionReturn(0); 925 } 926 927 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 928 { 929 PetscErrorCode ierr; 930 PetscBool iascii; 931 PetscViewerFormat format; 932 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 933 PetscInt i; 934 935 PetscFunctionBegin; 936 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 937 938 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 939 if (iascii) { 940 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 941 if (format == PETSC_VIEWER_ASCII_INFO) { 942 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 943 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 944 for (i=1; i<=64; i++) { 945 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 946 } 947 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 948 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 949 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 950 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 951 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 952 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 953 } 954 } 955 PetscFunctionReturn(0); 956 } 957 958 959 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 960 { 961 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data; 962 963 PetscFunctionBegin; 964 info->block_size = 1.0; 965 info->nz_used = mat_mkl_pardiso->iparm[17]; 966 info->nz_allocated = mat_mkl_pardiso->iparm[17]; 967 info->nz_unneeded = 0.0; 968 info->assemblies = 0.0; 969 info->mallocs = 0.0; 970 info->memory = 0.0; 971 info->fill_ratio_given = 0; 972 info->fill_ratio_needed = 0; 973 info->factor_mallocs = 0; 974 PetscFunctionReturn(0); 975 } 976 977 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 978 { 979 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 980 981 PetscFunctionBegin; 982 if (icntl <= 64) { 983 mat_mkl_pardiso->iparm[icntl - 1] = ival; 984 } else { 985 if (icntl == 65) PetscSetMKL_PARDISOThreads(ival); 986 else if (icntl == 66) mat_mkl_pardiso->maxfct = ival; 987 else if (icntl == 67) mat_mkl_pardiso->mnum = ival; 988 else if (icntl == 68) mat_mkl_pardiso->msglvl = ival; 989 else if (icntl == 69) { 990 void *pt[IPARM_SIZE]; 991 mat_mkl_pardiso->mtype = ival; 992 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 993 #if defined(PETSC_USE_REAL_SINGLE) 994 mat_mkl_pardiso->iparm[27] = 1; 995 #else 996 mat_mkl_pardiso->iparm[27] = 0; 997 #endif 998 mat_mkl_pardiso->iparm[34] = 1; 999 } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival; 1000 } 1001 PetscFunctionReturn(0); 1002 } 1003 1004 /*@ 1005 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1006 1007 Logically Collective on Mat 1008 1009 Input Parameters: 1010 + F - the factored matrix obtained by calling MatGetFactor() 1011 . icntl - index of Mkl_Pardiso parameter 1012 - ival - value of Mkl_Pardiso parameter 1013 1014 Options Database: 1015 . -mat_mkl_pardiso_<icntl> <ival> 1016 1017 Level: beginner 1018 1019 References: 1020 . Mkl_Pardiso Users' Guide 1021 1022 .seealso: MatGetFactor() 1023 @*/ 1024 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1025 { 1026 PetscErrorCode ierr; 1027 1028 PetscFunctionBegin; 1029 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1030 PetscFunctionReturn(0); 1031 } 1032 1033 /*MC 1034 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1035 sequential matrices via the external package MKL_PARDISO. 1036 1037 Works with MATSEQAIJ matrices 1038 1039 Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver 1040 1041 Options Database Keys: 1042 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO 1043 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1044 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1045 . -mat_mkl_pardiso_68 - Message level information 1046 . -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 1047 . -mat_mkl_pardiso_1 - Use default values 1048 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1049 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1050 . -mat_mkl_pardiso_5 - User permutation 1051 . -mat_mkl_pardiso_6 - Write solution on x 1052 . -mat_mkl_pardiso_8 - Iterative refinement step 1053 . -mat_mkl_pardiso_10 - Pivoting perturbation 1054 . -mat_mkl_pardiso_11 - Scaling vectors 1055 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1056 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1057 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1058 . -mat_mkl_pardiso_19 - Report number of floating point operations 1059 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1060 . -mat_mkl_pardiso_24 - Parallel factorization control 1061 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1062 . -mat_mkl_pardiso_27 - Matrix checker 1063 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1064 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1065 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1066 1067 Level: beginner 1068 1069 For more information please check mkl_pardiso manual 1070 1071 .seealso: PCFactorSetMatSolverType(), MatSolverType 1072 1073 M*/ 1074 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type) 1075 { 1076 PetscFunctionBegin; 1077 *type = MATSOLVERMKL_PARDISO; 1078 PetscFunctionReturn(0); 1079 } 1080 1081 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1082 { 1083 Mat B; 1084 PetscErrorCode ierr; 1085 Mat_MKL_PARDISO *mat_mkl_pardiso; 1086 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1087 1088 PetscFunctionBegin; 1089 ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1090 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1091 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1092 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1093 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1094 ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr); 1095 ierr = MatSetUp(B);CHKERRQ(ierr); 1096 1097 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1098 B->data = mat_mkl_pardiso; 1099 1100 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1101 if (ftype == MAT_FACTOR_LU) { 1102 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1103 B->factortype = MAT_FACTOR_LU; 1104 mat_mkl_pardiso->needsym = PETSC_FALSE; 1105 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1106 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1107 else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1108 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1109 #if defined(PETSC_USE_COMPLEX) 1110 mat_mkl_pardiso->mtype = 13; 1111 #else 1112 mat_mkl_pardiso->mtype = 11; 1113 #endif 1114 } else { 1115 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1116 B->factortype = MAT_FACTOR_CHOLESKY; 1117 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1118 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1119 else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1120 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1121 1122 mat_mkl_pardiso->needsym = PETSC_TRUE; 1123 #if !defined(PETSC_USE_COMPLEX) 1124 if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2; 1125 else mat_mkl_pardiso->mtype = -2; 1126 #else 1127 mat_mkl_pardiso->mtype = 6; 1128 if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead"); 1129 #endif 1130 } 1131 B->ops->destroy = MatDestroy_MKL_PARDISO; 1132 B->ops->view = MatView_MKL_PARDISO; 1133 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1134 B->factortype = ftype; 1135 B->assembled = PETSC_TRUE; 1136 1137 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 1138 ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr); 1139 1140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr); 1141 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1142 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1143 1144 *F = B; 1145 PetscFunctionReturn(0); 1146 } 1147 1148 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void) 1149 { 1150 PetscErrorCode ierr; 1151 1152 PetscFunctionBegin; 1153 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1154 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1155 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1156 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160