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 = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr); 247 if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 248 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr); 249 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr); 250 ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 251 ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 252 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 253 ierr = MatBindToCPU(Xmat,S->boundtocpu);CHKERRQ(ierr); 254 ierr = MatBindToCPU(Bmat,S->boundtocpu);CHKERRQ(ierr); 255 #endif 256 257 #if defined(PETSC_USE_COMPLEX) 258 if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet"); 259 #endif 260 261 switch (schurstatus) { 262 case MAT_FACTOR_SCHUR_FACTORED: 263 if (!mpardiso->iparm[12-1]) { 264 ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr); 265 } else { /* transpose solve */ 266 ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr); 267 } 268 break; 269 case MAT_FACTOR_SCHUR_INVERTED: 270 ierr = MatProductCreateWithMat(S,Bmat,NULL,Xmat);CHKERRQ(ierr); 271 if (!mpardiso->iparm[12-1]) { 272 ierr = MatProductSetType(Xmat,MATPRODUCT_AB);CHKERRQ(ierr); 273 } else { /* transpose solve */ 274 ierr = MatProductSetType(Xmat,MATPRODUCT_AtB);CHKERRQ(ierr); 275 } 276 ierr = MatProductSetFromOptions(Xmat);CHKERRQ(ierr); 277 ierr = MatProductSymbolic(Xmat);CHKERRQ(ierr); 278 ierr = MatProductNumeric(Xmat);CHKERRQ(ierr); 279 ierr = MatProductClear(Xmat);CHKERRQ(ierr); 280 break; 281 default: 282 SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status); 283 break; 284 } 285 ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr); 286 ierr = MatDestroy(&Bmat);CHKERRQ(ierr); 287 ierr = MatDestroy(&Xmat);CHKERRQ(ierr); 288 PetscFunctionReturn(0); 289 } 290 291 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 292 { 293 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 294 const PetscScalar *arr; 295 const PetscInt *idxs; 296 PetscInt size,i; 297 PetscMPIInt csize; 298 PetscBool sorted; 299 PetscErrorCode ierr; 300 301 PetscFunctionBegin; 302 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRMPI(ierr); 303 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc"); 304 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 305 if (!sorted) { 306 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted"); 307 } 308 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 309 ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr); 310 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 311 ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 312 ierr = MatDestroy(&F->schur);CHKERRQ(ierr); 313 ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr); 314 ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr); 315 mpardiso->schur = (PetscScalar*)arr; 316 mpardiso->schur_size = size; 317 ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr); 318 if (mpardiso->mtype == 2) { 319 ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr); 320 } 321 322 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 323 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 324 ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr); 325 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 326 ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr); 327 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 328 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 329 if (size) { /* turn on Schur switch if the set of indices is not empty */ 330 mpardiso->iparm[36-1] = 2; 331 } 332 PetscFunctionReturn(0); 333 } 334 335 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 336 { 337 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 338 PetscErrorCode ierr; 339 340 PetscFunctionBegin; 341 if (mat_mkl_pardiso->CleanUp) { 342 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 343 344 MKL_PARDISO (mat_mkl_pardiso->pt, 345 &mat_mkl_pardiso->maxfct, 346 &mat_mkl_pardiso->mnum, 347 &mat_mkl_pardiso->mtype, 348 &mat_mkl_pardiso->phase, 349 &mat_mkl_pardiso->n, 350 NULL, 351 NULL, 352 NULL, 353 NULL, 354 &mat_mkl_pardiso->nrhs, 355 mat_mkl_pardiso->iparm, 356 &mat_mkl_pardiso->msglvl, 357 NULL, 358 NULL, 359 &mat_mkl_pardiso->err); 360 } 361 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 362 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 363 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 364 if (mat_mkl_pardiso->freeaij) { 365 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 366 if (mat_mkl_pardiso->iparm[34] == 1) { 367 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 368 } 369 } 370 ierr = PetscFree(A->data);CHKERRQ(ierr); 371 372 /* clear composed functions */ 373 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); 374 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 375 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 376 PetscFunctionReturn(0); 377 } 378 379 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce) 380 { 381 PetscFunctionBegin; 382 if (reduce) { /* data given for the whole matrix */ 383 PetscInt i,m=0,p=0; 384 for (i=0;i<mpardiso->nrhs;i++) { 385 PetscInt j; 386 for (j=0;j<mpardiso->schur_size;j++) { 387 schur[p+j] = whole[m+mpardiso->schur_idxs[j]]; 388 } 389 m += mpardiso->n; 390 p += mpardiso->schur_size; 391 } 392 } else { /* from Schur to whole */ 393 PetscInt i,m=0,p=0; 394 for (i=0;i<mpardiso->nrhs;i++) { 395 PetscInt j; 396 for (j=0;j<mpardiso->schur_size;j++) { 397 whole[m+mpardiso->schur_idxs[j]] = schur[p+j]; 398 } 399 m += mpardiso->n; 400 p += mpardiso->schur_size; 401 } 402 } 403 PetscFunctionReturn(0); 404 } 405 406 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 407 { 408 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 409 PetscErrorCode ierr; 410 PetscScalar *xarray; 411 const PetscScalar *barray; 412 413 PetscFunctionBegin; 414 mat_mkl_pardiso->nrhs = 1; 415 ierr = VecGetArrayWrite(x,&xarray);CHKERRQ(ierr); 416 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 417 418 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 419 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 420 421 if (barray == xarray) { /* if the two vectors share the same memory */ 422 PetscScalar *work; 423 if (!mat_mkl_pardiso->schur_work) { 424 ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr); 425 } else { 426 work = mat_mkl_pardiso->schur_work; 427 } 428 mat_mkl_pardiso->iparm[6-1] = 1; 429 MKL_PARDISO (mat_mkl_pardiso->pt, 430 &mat_mkl_pardiso->maxfct, 431 &mat_mkl_pardiso->mnum, 432 &mat_mkl_pardiso->mtype, 433 &mat_mkl_pardiso->phase, 434 &mat_mkl_pardiso->n, 435 mat_mkl_pardiso->a, 436 mat_mkl_pardiso->ia, 437 mat_mkl_pardiso->ja, 438 NULL, 439 &mat_mkl_pardiso->nrhs, 440 mat_mkl_pardiso->iparm, 441 &mat_mkl_pardiso->msglvl, 442 (void*)xarray, 443 (void*)work, 444 &mat_mkl_pardiso->err); 445 if (!mat_mkl_pardiso->schur_work) { 446 ierr = PetscFree(work);CHKERRQ(ierr); 447 } 448 } else { 449 mat_mkl_pardiso->iparm[6-1] = 0; 450 MKL_PARDISO (mat_mkl_pardiso->pt, 451 &mat_mkl_pardiso->maxfct, 452 &mat_mkl_pardiso->mnum, 453 &mat_mkl_pardiso->mtype, 454 &mat_mkl_pardiso->phase, 455 &mat_mkl_pardiso->n, 456 mat_mkl_pardiso->a, 457 mat_mkl_pardiso->ia, 458 mat_mkl_pardiso->ja, 459 mat_mkl_pardiso->perm, 460 &mat_mkl_pardiso->nrhs, 461 mat_mkl_pardiso->iparm, 462 &mat_mkl_pardiso->msglvl, 463 (void*)barray, 464 (void*)xarray, 465 &mat_mkl_pardiso->err); 466 } 467 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 468 469 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); 470 471 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 472 if (!mat_mkl_pardiso->solve_interior) { 473 PetscInt shift = mat_mkl_pardiso->schur_size; 474 475 ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr); 476 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 477 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 478 479 /* solve Schur complement */ 480 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 481 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 482 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 483 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */ 484 PetscInt i; 485 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 486 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 487 } 488 } 489 490 /* expansion phase */ 491 mat_mkl_pardiso->iparm[6-1] = 1; 492 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 493 MKL_PARDISO (mat_mkl_pardiso->pt, 494 &mat_mkl_pardiso->maxfct, 495 &mat_mkl_pardiso->mnum, 496 &mat_mkl_pardiso->mtype, 497 &mat_mkl_pardiso->phase, 498 &mat_mkl_pardiso->n, 499 mat_mkl_pardiso->a, 500 mat_mkl_pardiso->ia, 501 mat_mkl_pardiso->ja, 502 mat_mkl_pardiso->perm, 503 &mat_mkl_pardiso->nrhs, 504 mat_mkl_pardiso->iparm, 505 &mat_mkl_pardiso->msglvl, 506 (void*)xarray, 507 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 508 &mat_mkl_pardiso->err); 509 510 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); 511 mat_mkl_pardiso->iparm[6-1] = 0; 512 } 513 ierr = VecRestoreArrayWrite(x,&xarray);CHKERRQ(ierr); 514 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 515 PetscFunctionReturn(0); 516 } 517 518 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 519 { 520 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 521 PetscInt oiparm12; 522 PetscErrorCode ierr; 523 524 PetscFunctionBegin; 525 oiparm12 = mat_mkl_pardiso->iparm[12 - 1]; 526 mat_mkl_pardiso->iparm[12 - 1] = 2; 527 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 528 mat_mkl_pardiso->iparm[12 - 1] = oiparm12; 529 PetscFunctionReturn(0); 530 } 531 532 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 533 { 534 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 535 PetscErrorCode ierr; 536 const PetscScalar *barray; 537 PetscScalar *xarray; 538 PetscBool flg; 539 540 PetscFunctionBegin; 541 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 542 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 543 if (X != B) { 544 ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 545 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 546 } 547 548 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 549 550 if (mat_mkl_pardiso->nrhs > 0) { 551 ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr); 552 ierr = MatDenseGetArrayWrite(X,&xarray);CHKERRQ(ierr); 553 554 if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location"); 555 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 556 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 557 558 MKL_PARDISO (mat_mkl_pardiso->pt, 559 &mat_mkl_pardiso->maxfct, 560 &mat_mkl_pardiso->mnum, 561 &mat_mkl_pardiso->mtype, 562 &mat_mkl_pardiso->phase, 563 &mat_mkl_pardiso->n, 564 mat_mkl_pardiso->a, 565 mat_mkl_pardiso->ia, 566 mat_mkl_pardiso->ja, 567 mat_mkl_pardiso->perm, 568 &mat_mkl_pardiso->nrhs, 569 mat_mkl_pardiso->iparm, 570 &mat_mkl_pardiso->msglvl, 571 (void*)barray, 572 (void*)xarray, 573 &mat_mkl_pardiso->err); 574 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); 575 576 ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr); 577 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 578 PetscScalar *o_schur_work = NULL; 579 580 /* solve Schur complement */ 581 if (!mat_mkl_pardiso->solve_interior) { 582 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 583 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 584 585 ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr); 586 /* allocate extra memory if it is needed */ 587 scale = 1; 588 if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2; 589 mem *= scale; 590 if (mem > mat_mkl_pardiso->schur_work_size) { 591 o_schur_work = mat_mkl_pardiso->schur_work; 592 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 593 } 594 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 595 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 596 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 597 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 598 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 599 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */ 600 PetscInt i,n,m=0; 601 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 602 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 603 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 604 } 605 m += mat_mkl_pardiso->n; 606 } 607 } 608 609 /* expansion phase */ 610 mat_mkl_pardiso->iparm[6-1] = 1; 611 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 612 MKL_PARDISO (mat_mkl_pardiso->pt, 613 &mat_mkl_pardiso->maxfct, 614 &mat_mkl_pardiso->mnum, 615 &mat_mkl_pardiso->mtype, 616 &mat_mkl_pardiso->phase, 617 &mat_mkl_pardiso->n, 618 mat_mkl_pardiso->a, 619 mat_mkl_pardiso->ia, 620 mat_mkl_pardiso->ja, 621 mat_mkl_pardiso->perm, 622 &mat_mkl_pardiso->nrhs, 623 mat_mkl_pardiso->iparm, 624 &mat_mkl_pardiso->msglvl, 625 (void*)xarray, 626 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 627 &mat_mkl_pardiso->err); 628 if (o_schur_work) { /* restore original schur_work (minimal size) */ 629 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 630 mat_mkl_pardiso->schur_work = o_schur_work; 631 } 632 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); 633 mat_mkl_pardiso->iparm[6-1] = 0; 634 } 635 ierr = MatDenseRestoreArrayWrite(X,&xarray);CHKERRQ(ierr); 636 } 637 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 638 PetscFunctionReturn(0); 639 } 640 641 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 642 { 643 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data; 644 PetscErrorCode ierr; 645 646 PetscFunctionBegin; 647 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 648 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); 649 650 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 651 MKL_PARDISO (mat_mkl_pardiso->pt, 652 &mat_mkl_pardiso->maxfct, 653 &mat_mkl_pardiso->mnum, 654 &mat_mkl_pardiso->mtype, 655 &mat_mkl_pardiso->phase, 656 &mat_mkl_pardiso->n, 657 mat_mkl_pardiso->a, 658 mat_mkl_pardiso->ia, 659 mat_mkl_pardiso->ja, 660 mat_mkl_pardiso->perm, 661 &mat_mkl_pardiso->nrhs, 662 mat_mkl_pardiso->iparm, 663 &mat_mkl_pardiso->msglvl, 664 NULL, 665 (void*)mat_mkl_pardiso->schur, 666 &mat_mkl_pardiso->err); 667 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); 668 669 /* report flops */ 670 if (mat_mkl_pardiso->iparm[18] > 0) { 671 ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr); 672 } 673 674 if (F->schur) { /* schur output from pardiso is in row major format */ 675 #if defined(PETSC_HAVE_CUDA) 676 F->schur->offloadmask = PETSC_OFFLOAD_CPU; 677 #endif 678 ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr); 679 ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr); 680 } 681 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 682 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 683 PetscFunctionReturn(0); 684 } 685 686 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 687 { 688 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 689 PetscErrorCode ierr; 690 PetscInt icntl,bs,threads=1; 691 PetscBool flg; 692 693 PetscFunctionBegin; 694 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 695 696 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 697 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 698 699 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); 700 if (flg) mat_mkl_pardiso->maxfct = icntl; 701 702 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 703 if (flg) mat_mkl_pardiso->mnum = icntl; 704 705 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 706 if (flg) mat_mkl_pardiso->msglvl = icntl; 707 708 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 709 if (flg) { 710 void *pt[IPARM_SIZE]; 711 mat_mkl_pardiso->mtype = icntl; 712 icntl = mat_mkl_pardiso->iparm[34]; 713 bs = mat_mkl_pardiso->iparm[36]; 714 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 715 #if defined(PETSC_USE_REAL_SINGLE) 716 mat_mkl_pardiso->iparm[27] = 1; 717 #else 718 mat_mkl_pardiso->iparm[27] = 0; 719 #endif 720 mat_mkl_pardiso->iparm[34] = icntl; 721 mat_mkl_pardiso->iparm[36] = bs; 722 } 723 724 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 725 if (flg) mat_mkl_pardiso->iparm[0] = icntl; 726 727 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 728 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 729 730 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 731 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 732 733 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 734 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 735 736 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 737 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 738 739 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 740 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 741 742 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 743 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 744 745 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 746 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 747 748 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 749 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 750 751 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 752 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 753 754 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 755 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 756 757 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); 758 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 759 760 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 761 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 762 763 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 764 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 765 766 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 767 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 768 769 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 770 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 771 772 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); 773 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 774 775 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); 776 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 777 778 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 779 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 780 PetscOptionsEnd(); 781 PetscFunctionReturn(0); 782 } 783 784 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 785 { 786 PetscErrorCode ierr; 787 PetscInt i,bs; 788 PetscBool match; 789 790 PetscFunctionBegin; 791 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0; 792 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0; 793 #if defined(PETSC_USE_REAL_SINGLE) 794 mat_mkl_pardiso->iparm[27] = 1; 795 #else 796 mat_mkl_pardiso->iparm[27] = 0; 797 #endif 798 /* Default options for both sym and unsym */ 799 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 800 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 801 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 802 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 803 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 804 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 805 #if 0 806 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 807 #endif 808 ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr); 809 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 810 if (!match || bs == 1) { 811 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 812 mat_mkl_pardiso->n = A->rmap->N; 813 } else { 814 mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */ 815 mat_mkl_pardiso->iparm[36] = bs; 816 mat_mkl_pardiso->n = A->rmap->N/bs; 817 } 818 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on master */ 819 820 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 821 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 822 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 823 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 824 mat_mkl_pardiso->phase = -1; 825 mat_mkl_pardiso->err = 0; 826 827 mat_mkl_pardiso->nrhs = 1; 828 mat_mkl_pardiso->err = 0; 829 mat_mkl_pardiso->phase = -1; 830 831 if (ftype == MAT_FACTOR_LU) { 832 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 833 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 834 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 835 } else { 836 mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */ 837 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 838 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 839 #if defined(PETSC_USE_DEBUG) 840 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 841 #endif 842 } 843 ierr = PetscCalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 844 mat_mkl_pardiso->schur_size = 0; 845 PetscFunctionReturn(0); 846 } 847 848 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 849 { 850 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 851 PetscErrorCode ierr; 852 853 PetscFunctionBegin; 854 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 855 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 856 /* throw away any previously computed structure */ 857 if (mat_mkl_pardiso->freeaij) { 858 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 859 if (mat_mkl_pardiso->iparm[34] == 1) { 860 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 861 } 862 } 863 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); 864 if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N; 865 else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs; 866 867 mat_mkl_pardiso->phase = JOB_ANALYSIS; 868 869 /* reset flops counting if requested */ 870 if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1; 871 872 MKL_PARDISO (mat_mkl_pardiso->pt, 873 &mat_mkl_pardiso->maxfct, 874 &mat_mkl_pardiso->mnum, 875 &mat_mkl_pardiso->mtype, 876 &mat_mkl_pardiso->phase, 877 &mat_mkl_pardiso->n, 878 mat_mkl_pardiso->a, 879 mat_mkl_pardiso->ia, 880 mat_mkl_pardiso->ja, 881 mat_mkl_pardiso->perm, 882 &mat_mkl_pardiso->nrhs, 883 mat_mkl_pardiso->iparm, 884 &mat_mkl_pardiso->msglvl, 885 NULL, 886 NULL, 887 &mat_mkl_pardiso->err); 888 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); 889 890 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 891 892 if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 893 else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 894 895 F->ops->solve = MatSolve_MKL_PARDISO; 896 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 897 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 898 PetscFunctionReturn(0); 899 } 900 901 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 902 { 903 PetscErrorCode ierr; 904 905 PetscFunctionBegin; 906 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 907 PetscFunctionReturn(0); 908 } 909 910 #if !defined(PETSC_USE_COMPLEX) 911 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) 912 { 913 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data; 914 915 PetscFunctionBegin; 916 if (nneg) *nneg = mat_mkl_pardiso->iparm[22]; 917 if (npos) *npos = mat_mkl_pardiso->iparm[21]; 918 if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]); 919 PetscFunctionReturn(0); 920 } 921 #endif 922 923 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 924 { 925 PetscErrorCode ierr; 926 927 PetscFunctionBegin; 928 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 929 #if defined(PETSC_USE_COMPLEX) 930 F->ops->getinertia = NULL; 931 #else 932 F->ops->getinertia = MatGetInertia_MKL_PARDISO; 933 #endif 934 PetscFunctionReturn(0); 935 } 936 937 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 938 { 939 PetscErrorCode ierr; 940 PetscBool iascii; 941 PetscViewerFormat format; 942 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 943 PetscInt i; 944 945 PetscFunctionBegin; 946 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 947 948 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 949 if (iascii) { 950 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 951 if (format == PETSC_VIEWER_ASCII_INFO) { 952 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 953 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 954 for (i=1; i<=64; i++) { 955 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 956 } 957 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 958 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 959 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 960 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 961 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 962 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 963 } 964 } 965 PetscFunctionReturn(0); 966 } 967 968 969 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 970 { 971 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data; 972 973 PetscFunctionBegin; 974 info->block_size = 1.0; 975 info->nz_used = mat_mkl_pardiso->iparm[17]; 976 info->nz_allocated = mat_mkl_pardiso->iparm[17]; 977 info->nz_unneeded = 0.0; 978 info->assemblies = 0.0; 979 info->mallocs = 0.0; 980 info->memory = 0.0; 981 info->fill_ratio_given = 0; 982 info->fill_ratio_needed = 0; 983 info->factor_mallocs = 0; 984 PetscFunctionReturn(0); 985 } 986 987 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 988 { 989 PetscInt backup,bs; 990 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 991 992 PetscFunctionBegin; 993 if (icntl <= 64) { 994 mat_mkl_pardiso->iparm[icntl - 1] = ival; 995 } else { 996 if (icntl == 65) PetscSetMKL_PARDISOThreads(ival); 997 else if (icntl == 66) mat_mkl_pardiso->maxfct = ival; 998 else if (icntl == 67) mat_mkl_pardiso->mnum = ival; 999 else if (icntl == 68) mat_mkl_pardiso->msglvl = ival; 1000 else if (icntl == 69) { 1001 void *pt[IPARM_SIZE]; 1002 backup = mat_mkl_pardiso->iparm[34]; 1003 bs = mat_mkl_pardiso->iparm[36]; 1004 mat_mkl_pardiso->mtype = ival; 1005 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 1006 #if defined(PETSC_USE_REAL_SINGLE) 1007 mat_mkl_pardiso->iparm[27] = 1; 1008 #else 1009 mat_mkl_pardiso->iparm[27] = 0; 1010 #endif 1011 mat_mkl_pardiso->iparm[34] = backup; 1012 mat_mkl_pardiso->iparm[36] = bs; 1013 } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival; 1014 } 1015 PetscFunctionReturn(0); 1016 } 1017 1018 /*@ 1019 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1020 1021 Logically Collective on Mat 1022 1023 Input Parameters: 1024 + F - the factored matrix obtained by calling MatGetFactor() 1025 . icntl - index of Mkl_Pardiso parameter 1026 - ival - value of Mkl_Pardiso parameter 1027 1028 Options Database: 1029 . -mat_mkl_pardiso_<icntl> <ival> 1030 1031 Level: beginner 1032 1033 References: 1034 . Mkl_Pardiso Users' Guide 1035 1036 .seealso: MatGetFactor() 1037 @*/ 1038 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1039 { 1040 PetscErrorCode ierr; 1041 1042 PetscFunctionBegin; 1043 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1044 PetscFunctionReturn(0); 1045 } 1046 1047 /*MC 1048 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1049 sequential matrices via the external package MKL_PARDISO. 1050 1051 Works with MATSEQAIJ matrices 1052 1053 Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver 1054 1055 Options Database Keys: 1056 + -mat_mkl_pardiso_65 - Number of threads to use within MKL_PARDISO 1057 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1058 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1059 . -mat_mkl_pardiso_68 - Message level information 1060 . -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 1061 . -mat_mkl_pardiso_1 - Use default values 1062 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1063 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1064 . -mat_mkl_pardiso_5 - User permutation 1065 . -mat_mkl_pardiso_6 - Write solution on x 1066 . -mat_mkl_pardiso_8 - Iterative refinement step 1067 . -mat_mkl_pardiso_10 - Pivoting perturbation 1068 . -mat_mkl_pardiso_11 - Scaling vectors 1069 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1070 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1071 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1072 . -mat_mkl_pardiso_19 - Report number of floating point operations 1073 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1074 . -mat_mkl_pardiso_24 - Parallel factorization control 1075 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1076 . -mat_mkl_pardiso_27 - Matrix checker 1077 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1078 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1079 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1080 1081 Level: beginner 1082 1083 For more information please check mkl_pardiso manual 1084 1085 .seealso: PCFactorSetMatSolverType(), MatSolverType 1086 1087 M*/ 1088 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type) 1089 { 1090 PetscFunctionBegin; 1091 *type = MATSOLVERMKL_PARDISO; 1092 PetscFunctionReturn(0); 1093 } 1094 1095 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1096 { 1097 Mat B; 1098 PetscErrorCode ierr; 1099 Mat_MKL_PARDISO *mat_mkl_pardiso; 1100 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1101 1102 PetscFunctionBegin; 1103 ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1104 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1105 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1106 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1107 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1108 ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr); 1109 ierr = MatSetUp(B);CHKERRQ(ierr); 1110 1111 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1112 B->data = mat_mkl_pardiso; 1113 1114 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1115 if (ftype == MAT_FACTOR_LU) { 1116 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1117 B->factortype = MAT_FACTOR_LU; 1118 mat_mkl_pardiso->needsym = PETSC_FALSE; 1119 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1120 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1121 else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1122 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1123 #if defined(PETSC_USE_COMPLEX) 1124 mat_mkl_pardiso->mtype = 13; 1125 #else 1126 mat_mkl_pardiso->mtype = 11; 1127 #endif 1128 } else { 1129 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1130 B->factortype = MAT_FACTOR_CHOLESKY; 1131 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1132 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1133 else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1134 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1135 1136 mat_mkl_pardiso->needsym = PETSC_TRUE; 1137 #if !defined(PETSC_USE_COMPLEX) 1138 if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2; 1139 else mat_mkl_pardiso->mtype = -2; 1140 #else 1141 mat_mkl_pardiso->mtype = 6; 1142 if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead"); 1143 #endif 1144 } 1145 B->ops->destroy = MatDestroy_MKL_PARDISO; 1146 B->ops->view = MatView_MKL_PARDISO; 1147 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1148 B->factortype = ftype; 1149 B->assembled = PETSC_TRUE; 1150 1151 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 1152 ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr); 1153 1154 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr); 1155 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1156 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1157 1158 *F = B; 1159 PetscFunctionReturn(0); 1160 } 1161 1162 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void) 1163 { 1164 PetscErrorCode ierr; 1165 1166 PetscFunctionBegin; 1167 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1168 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1169 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1170 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1171 PetscFunctionReturn(0); 1172 } 1173 1174