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 * Internal data structure. 58 * For more information check mkl_pardiso manual. 59 */ 60 typedef struct { 61 62 /* Configuration vector*/ 63 INT_TYPE iparm[IPARM_SIZE]; 64 65 /* 66 * Internal mkl_pardiso memory location. 67 * After the first call to mkl_pardiso do not modify pt, as that could cause a serious memory leak. 68 */ 69 void *pt[IPARM_SIZE]; 70 71 /* Basic mkl_pardiso info*/ 72 INT_TYPE phase, maxfct, mnum, mtype, n, nrhs, msglvl, err; 73 74 /* Matrix structure*/ 75 void *a; 76 INT_TYPE *ia, *ja; 77 78 /* Number of non-zero elements*/ 79 INT_TYPE nz; 80 81 /* Row permutaton vector*/ 82 INT_TYPE *perm; 83 84 /* Define if matrix preserves sparse structure.*/ 85 MatStructure matstruc; 86 87 PetscBool needsym; 88 PetscBool freeaij; 89 90 /* Schur complement */ 91 PetscScalar *schur; 92 PetscInt schur_size; 93 PetscInt *schur_idxs; 94 PetscScalar *schur_work; 95 PetscBLASInt schur_work_size; 96 PetscBool solve_interior; 97 98 /* True if mkl_pardiso function have been used.*/ 99 PetscBool CleanUp; 100 101 /* Conversion to a format suitable for MKL */ 102 PetscErrorCode (*Convert)(Mat, PetscBool, MatReuse, PetscBool*, INT_TYPE*, INT_TYPE**, INT_TYPE**, PetscScalar**); 103 } Mat_MKL_PARDISO; 104 105 PetscErrorCode MatMKLPardiso_Convert_seqsbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 106 { 107 Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)A->data; 108 PetscInt bs = A->rmap->bs,i; 109 PetscErrorCode ierr; 110 111 PetscFunctionBegin; 112 if (!sym) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 113 *v = aa->a; 114 if (bs == 1) { /* already in the correct format */ 115 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 116 *r = (INT_TYPE*)aa->i; 117 *c = (INT_TYPE*)aa->j; 118 *nnz = (INT_TYPE)aa->nz; 119 *free = PETSC_FALSE; 120 } else if (reuse == MAT_INITIAL_MATRIX) { 121 PetscInt m = A->rmap->n,nz = aa->nz; 122 PetscInt *row,*col; 123 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 124 for (i=0; i<m+1; i++) { 125 row[i] = aa->i[i]+1; 126 } 127 for (i=0; i<nz; i++) { 128 col[i] = aa->j[i]+1; 129 } 130 *r = (INT_TYPE*)row; 131 *c = (INT_TYPE*)col; 132 *nnz = (INT_TYPE)nz; 133 *free = PETSC_TRUE; 134 } 135 PetscFunctionReturn(0); 136 } 137 138 PetscErrorCode MatMKLPardiso_Convert_seqbaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 139 { 140 Mat_SeqBAIJ *aa = (Mat_SeqBAIJ*)A->data; 141 PetscInt bs = A->rmap->bs,i; 142 PetscErrorCode ierr; 143 144 PetscFunctionBegin; 145 if (!sym) { 146 *v = aa->a; 147 if (bs == 1) { /* already in the correct format */ 148 /* though PetscInt and INT_TYPE are of the same size since they are defined differently the Intel compiler requires a cast */ 149 *r = (INT_TYPE*)aa->i; 150 *c = (INT_TYPE*)aa->j; 151 *nnz = (INT_TYPE)aa->nz; 152 *free = PETSC_FALSE; 153 PetscFunctionReturn(0); 154 } else if (reuse == MAT_INITIAL_MATRIX) { 155 PetscInt m = A->rmap->n,nz = aa->nz; 156 PetscInt *row,*col; 157 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 158 for (i=0; i<m+1; i++) { 159 row[i] = aa->i[i]+1; 160 } 161 for (i=0; i<nz; i++) { 162 col[i] = aa->j[i]+1; 163 } 164 *r = (INT_TYPE*)row; 165 *c = (INT_TYPE*)col; 166 *nnz = (INT_TYPE)nz; 167 } 168 *free = PETSC_TRUE; 169 } else { 170 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_PLIB,"This should not happen"); 171 } 172 PetscFunctionReturn(0); 173 } 174 175 PetscErrorCode MatMKLPardiso_Convert_seqaij(Mat A,PetscBool sym,MatReuse reuse,PetscBool *free,INT_TYPE *nnz,INT_TYPE **r,INT_TYPE **c,PetscScalar **v) 176 { 177 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data; 178 PetscScalar *aav; 179 PetscErrorCode ierr; 180 181 PetscFunctionBegin; 182 ierr = MatSeqAIJGetArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 183 if (!sym) { /* already in the correct format */ 184 *v = aav; 185 *r = (INT_TYPE*)aa->i; 186 *c = (INT_TYPE*)aa->j; 187 *nnz = (INT_TYPE)aa->nz; 188 *free = PETSC_FALSE; 189 } else if (reuse == MAT_INITIAL_MATRIX) { /* need to get the triangular part */ 190 PetscScalar *vals,*vv; 191 PetscInt *row,*col,*jj; 192 PetscInt m = A->rmap->n,nz,i; 193 194 nz = 0; 195 for (i=0; i<m; i++) nz += aa->i[i+1] - aa->diag[i]; 196 ierr = PetscMalloc2(m+1,&row,nz,&col);CHKERRQ(ierr); 197 ierr = PetscMalloc1(nz,&vals);CHKERRQ(ierr); 198 jj = col; 199 vv = vals; 200 201 row[0] = 0; 202 for (i=0; i<m; i++) { 203 PetscInt *aj = aa->j + aa->diag[i]; 204 PetscScalar *av = aav + aa->diag[i]; 205 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 206 207 for (j=0; j<rl; j++) { 208 *jj = *aj; jj++; aj++; 209 *vv = *av; vv++; av++; 210 } 211 row[i+1] = row[i] + rl; 212 } 213 *v = vals; 214 *r = (INT_TYPE*)row; 215 *c = (INT_TYPE*)col; 216 *nnz = (INT_TYPE)nz; 217 *free = PETSC_TRUE; 218 } else { 219 PetscScalar *vv; 220 PetscInt m = A->rmap->n,i; 221 222 vv = *v; 223 for (i=0; i<m; i++) { 224 PetscScalar *av = aav + aa->diag[i]; 225 PetscInt rl = aa->i[i+1] - aa->diag[i],j; 226 for (j=0; j<rl; j++) { 227 *vv = *av; vv++; av++; 228 } 229 } 230 *free = PETSC_TRUE; 231 } 232 ierr = MatSeqAIJRestoreArrayRead(A,(const PetscScalar**)&aav);CHKERRQ(ierr); 233 PetscFunctionReturn(0); 234 } 235 236 static PetscErrorCode MatMKLPardisoSolveSchur_Private(Mat F, PetscScalar *B, PetscScalar *X) 237 { 238 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 239 Mat S,Xmat,Bmat; 240 MatFactorSchurStatus schurstatus; 241 PetscErrorCode ierr; 242 243 PetscFunctionBegin; 244 ierr = MatFactorGetSchurComplement(F,&S,&schurstatus);CHKERRQ(ierr); 245 if (X == B && schurstatus == MAT_FACTOR_SCHUR_INVERTED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"X and B cannot point to the same address"); 246 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,B,&Bmat);CHKERRQ(ierr); 247 ierr = MatCreateSeqDense(PETSC_COMM_SELF,mpardiso->schur_size,mpardiso->nrhs,X,&Xmat);CHKERRQ(ierr); 248 ierr = MatSetType(Bmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 249 ierr = MatSetType(Xmat,((PetscObject)S)->type_name);CHKERRQ(ierr); 250 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 251 ierr = MatBindToCPU(Xmat,S->boundtocpu);CHKERRQ(ierr); 252 ierr = MatBindToCPU(Bmat,S->boundtocpu);CHKERRQ(ierr); 253 #endif 254 255 #if defined(PETSC_USE_COMPLEX) 256 if (mpardiso->iparm[12-1] == 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Hermitian solve not implemented yet"); 257 #endif 258 259 switch (schurstatus) { 260 case MAT_FACTOR_SCHUR_FACTORED: 261 if (!mpardiso->iparm[12-1]) { 262 ierr = MatMatSolve(S,Bmat,Xmat);CHKERRQ(ierr); 263 } else { /* transpose solve */ 264 ierr = MatMatSolveTranspose(S,Bmat,Xmat);CHKERRQ(ierr); 265 } 266 break; 267 case MAT_FACTOR_SCHUR_INVERTED: 268 ierr = MatProductCreateWithMat(S,Bmat,NULL,Xmat);CHKERRQ(ierr); 269 if (!mpardiso->iparm[12-1]) { 270 ierr = MatProductSetType(Xmat,MATPRODUCT_AB);CHKERRQ(ierr); 271 } else { /* transpose solve */ 272 ierr = MatProductSetType(Xmat,MATPRODUCT_AtB);CHKERRQ(ierr); 273 } 274 ierr = MatProductSetFromOptions(Xmat);CHKERRQ(ierr); 275 ierr = MatProductSymbolic(Xmat);CHKERRQ(ierr); 276 ierr = MatProductNumeric(Xmat);CHKERRQ(ierr); 277 ierr = MatProductClear(Xmat);CHKERRQ(ierr); 278 break; 279 default: 280 SETERRQ1(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Unhandled MatFactorSchurStatus %D",F->schur_status); 281 break; 282 } 283 ierr = MatFactorRestoreSchurComplement(F,&S,schurstatus);CHKERRQ(ierr); 284 ierr = MatDestroy(&Bmat);CHKERRQ(ierr); 285 ierr = MatDestroy(&Xmat);CHKERRQ(ierr); 286 PetscFunctionReturn(0); 287 } 288 289 PetscErrorCode MatFactorSetSchurIS_MKL_PARDISO(Mat F, IS is) 290 { 291 Mat_MKL_PARDISO *mpardiso = (Mat_MKL_PARDISO*)F->data; 292 const PetscScalar *arr; 293 const PetscInt *idxs; 294 PetscInt size,i; 295 PetscMPIInt csize; 296 PetscBool sorted; 297 PetscErrorCode ierr; 298 299 PetscFunctionBegin; 300 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&csize);CHKERRMPI(ierr); 301 if (csize > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MKL_PARDISO parallel Schur complements not yet supported from PETSc"); 302 ierr = ISSorted(is,&sorted);CHKERRQ(ierr); 303 if (!sorted) { 304 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS for MKL_PARDISO Schur complements needs to be sorted"); 305 } 306 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 307 ierr = PetscFree(mpardiso->schur_work);CHKERRQ(ierr); 308 ierr = PetscBLASIntCast(PetscMax(mpardiso->n,2*size),&mpardiso->schur_work_size);CHKERRQ(ierr); 309 ierr = PetscMalloc1(mpardiso->schur_work_size,&mpardiso->schur_work);CHKERRQ(ierr); 310 ierr = MatDestroy(&F->schur);CHKERRQ(ierr); 311 ierr = MatCreateSeqDense(PETSC_COMM_SELF,size,size,NULL,&F->schur);CHKERRQ(ierr); 312 ierr = MatDenseGetArrayRead(F->schur,&arr);CHKERRQ(ierr); 313 mpardiso->schur = (PetscScalar*)arr; 314 mpardiso->schur_size = size; 315 ierr = MatDenseRestoreArrayRead(F->schur,&arr);CHKERRQ(ierr); 316 if (mpardiso->mtype == 2) { 317 ierr = MatSetOption(F->schur,MAT_SPD,PETSC_TRUE);CHKERRQ(ierr); 318 } 319 320 ierr = PetscFree(mpardiso->schur_idxs);CHKERRQ(ierr); 321 ierr = PetscMalloc1(size,&mpardiso->schur_idxs);CHKERRQ(ierr); 322 ierr = PetscArrayzero(mpardiso->perm,mpardiso->n);CHKERRQ(ierr); 323 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 324 ierr = PetscArraycpy(mpardiso->schur_idxs,idxs,size);CHKERRQ(ierr); 325 for (i=0;i<size;i++) mpardiso->perm[idxs[i]] = 1; 326 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 327 if (size) { /* turn on Schur switch if the set of indices is not empty */ 328 mpardiso->iparm[36-1] = 2; 329 } 330 PetscFunctionReturn(0); 331 } 332 333 PetscErrorCode MatDestroy_MKL_PARDISO(Mat A) 334 { 335 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 336 PetscErrorCode ierr; 337 338 PetscFunctionBegin; 339 if (mat_mkl_pardiso->CleanUp) { 340 mat_mkl_pardiso->phase = JOB_RELEASE_OF_ALL_MEMORY; 341 342 MKL_PARDISO (mat_mkl_pardiso->pt, 343 &mat_mkl_pardiso->maxfct, 344 &mat_mkl_pardiso->mnum, 345 &mat_mkl_pardiso->mtype, 346 &mat_mkl_pardiso->phase, 347 &mat_mkl_pardiso->n, 348 NULL, 349 NULL, 350 NULL, 351 NULL, 352 &mat_mkl_pardiso->nrhs, 353 mat_mkl_pardiso->iparm, 354 &mat_mkl_pardiso->msglvl, 355 NULL, 356 NULL, 357 &mat_mkl_pardiso->err); 358 } 359 ierr = PetscFree(mat_mkl_pardiso->perm);CHKERRQ(ierr); 360 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 361 ierr = PetscFree(mat_mkl_pardiso->schur_idxs);CHKERRQ(ierr); 362 if (mat_mkl_pardiso->freeaij) { 363 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 364 if (mat_mkl_pardiso->iparm[34] == 1) { 365 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 366 } 367 } 368 ierr = PetscFree(A->data);CHKERRQ(ierr); 369 370 /* clear composed functions */ 371 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); 372 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 373 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMkl_PardisoSetCntl_C",NULL);CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376 377 static PetscErrorCode MatMKLPardisoScatterSchur_Private(Mat_MKL_PARDISO *mpardiso, PetscScalar *whole, PetscScalar *schur, PetscBool reduce) 378 { 379 PetscFunctionBegin; 380 if (reduce) { /* data given for the whole matrix */ 381 PetscInt i,m=0,p=0; 382 for (i=0;i<mpardiso->nrhs;i++) { 383 PetscInt j; 384 for (j=0;j<mpardiso->schur_size;j++) { 385 schur[p+j] = whole[m+mpardiso->schur_idxs[j]]; 386 } 387 m += mpardiso->n; 388 p += mpardiso->schur_size; 389 } 390 } else { /* from Schur to whole */ 391 PetscInt i,m=0,p=0; 392 for (i=0;i<mpardiso->nrhs;i++) { 393 PetscInt j; 394 for (j=0;j<mpardiso->schur_size;j++) { 395 whole[m+mpardiso->schur_idxs[j]] = schur[p+j]; 396 } 397 m += mpardiso->n; 398 p += mpardiso->schur_size; 399 } 400 } 401 PetscFunctionReturn(0); 402 } 403 404 PetscErrorCode MatSolve_MKL_PARDISO(Mat A,Vec b,Vec x) 405 { 406 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 407 PetscErrorCode ierr; 408 PetscScalar *xarray; 409 const PetscScalar *barray; 410 411 PetscFunctionBegin; 412 mat_mkl_pardiso->nrhs = 1; 413 ierr = VecGetArrayWrite(x,&xarray);CHKERRQ(ierr); 414 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 415 416 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 417 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 418 419 if (barray == xarray) { /* if the two vectors share the same memory */ 420 PetscScalar *work; 421 if (!mat_mkl_pardiso->schur_work) { 422 ierr = PetscMalloc1(mat_mkl_pardiso->n,&work);CHKERRQ(ierr); 423 } else { 424 work = mat_mkl_pardiso->schur_work; 425 } 426 mat_mkl_pardiso->iparm[6-1] = 1; 427 MKL_PARDISO (mat_mkl_pardiso->pt, 428 &mat_mkl_pardiso->maxfct, 429 &mat_mkl_pardiso->mnum, 430 &mat_mkl_pardiso->mtype, 431 &mat_mkl_pardiso->phase, 432 &mat_mkl_pardiso->n, 433 mat_mkl_pardiso->a, 434 mat_mkl_pardiso->ia, 435 mat_mkl_pardiso->ja, 436 NULL, 437 &mat_mkl_pardiso->nrhs, 438 mat_mkl_pardiso->iparm, 439 &mat_mkl_pardiso->msglvl, 440 (void*)xarray, 441 (void*)work, 442 &mat_mkl_pardiso->err); 443 if (!mat_mkl_pardiso->schur_work) { 444 ierr = PetscFree(work);CHKERRQ(ierr); 445 } 446 } else { 447 mat_mkl_pardiso->iparm[6-1] = 0; 448 MKL_PARDISO (mat_mkl_pardiso->pt, 449 &mat_mkl_pardiso->maxfct, 450 &mat_mkl_pardiso->mnum, 451 &mat_mkl_pardiso->mtype, 452 &mat_mkl_pardiso->phase, 453 &mat_mkl_pardiso->n, 454 mat_mkl_pardiso->a, 455 mat_mkl_pardiso->ia, 456 mat_mkl_pardiso->ja, 457 mat_mkl_pardiso->perm, 458 &mat_mkl_pardiso->nrhs, 459 mat_mkl_pardiso->iparm, 460 &mat_mkl_pardiso->msglvl, 461 (void*)barray, 462 (void*)xarray, 463 &mat_mkl_pardiso->err); 464 } 465 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 466 467 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 468 469 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 470 if (!mat_mkl_pardiso->solve_interior) { 471 PetscInt shift = mat_mkl_pardiso->schur_size; 472 473 ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr); 474 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 475 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 476 477 /* solve Schur complement */ 478 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 479 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 480 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 481 } else { /* if we are solving for the interior problem, any value in barray[schur] forward-substituted to xarray[schur] will be neglected */ 482 PetscInt i; 483 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 484 xarray[mat_mkl_pardiso->schur_idxs[i]] = 0.; 485 } 486 } 487 488 /* expansion phase */ 489 mat_mkl_pardiso->iparm[6-1] = 1; 490 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 491 MKL_PARDISO (mat_mkl_pardiso->pt, 492 &mat_mkl_pardiso->maxfct, 493 &mat_mkl_pardiso->mnum, 494 &mat_mkl_pardiso->mtype, 495 &mat_mkl_pardiso->phase, 496 &mat_mkl_pardiso->n, 497 mat_mkl_pardiso->a, 498 mat_mkl_pardiso->ia, 499 mat_mkl_pardiso->ja, 500 mat_mkl_pardiso->perm, 501 &mat_mkl_pardiso->nrhs, 502 mat_mkl_pardiso->iparm, 503 &mat_mkl_pardiso->msglvl, 504 (void*)xarray, 505 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 506 &mat_mkl_pardiso->err); 507 508 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); 509 mat_mkl_pardiso->iparm[6-1] = 0; 510 } 511 ierr = VecRestoreArrayWrite(x,&xarray);CHKERRQ(ierr); 512 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 513 PetscFunctionReturn(0); 514 } 515 516 PetscErrorCode MatSolveTranspose_MKL_PARDISO(Mat A,Vec b,Vec x) 517 { 518 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 519 PetscInt oiparm12; 520 PetscErrorCode ierr; 521 522 PetscFunctionBegin; 523 oiparm12 = mat_mkl_pardiso->iparm[12 - 1]; 524 mat_mkl_pardiso->iparm[12 - 1] = 2; 525 ierr = MatSolve_MKL_PARDISO(A,b,x);CHKERRQ(ierr); 526 mat_mkl_pardiso->iparm[12 - 1] = oiparm12; 527 PetscFunctionReturn(0); 528 } 529 530 PetscErrorCode MatMatSolve_MKL_PARDISO(Mat A,Mat B,Mat X) 531 { 532 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(A)->data; 533 PetscErrorCode ierr; 534 const PetscScalar *barray; 535 PetscScalar *xarray; 536 PetscBool flg; 537 538 PetscFunctionBegin; 539 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 540 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATSEQDENSE matrix"); 541 if (X != B) { 542 ierr = PetscObjectBaseTypeCompare((PetscObject)X,MATSEQDENSE,&flg);CHKERRQ(ierr); 543 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATSEQDENSE matrix"); 544 } 545 546 ierr = MatGetSize(B,NULL,(PetscInt*)&mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 547 548 if (mat_mkl_pardiso->nrhs > 0) { 549 ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr); 550 ierr = MatDenseGetArrayWrite(X,&xarray);CHKERRQ(ierr); 551 552 if (barray == xarray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"B and X cannot share the same memory location"); 553 if (!mat_mkl_pardiso->schur) mat_mkl_pardiso->phase = JOB_SOLVE_ITERATIVE_REFINEMENT; 554 else mat_mkl_pardiso->phase = JOB_SOLVE_FORWARD_SUBSTITUTION; 555 556 MKL_PARDISO (mat_mkl_pardiso->pt, 557 &mat_mkl_pardiso->maxfct, 558 &mat_mkl_pardiso->mnum, 559 &mat_mkl_pardiso->mtype, 560 &mat_mkl_pardiso->phase, 561 &mat_mkl_pardiso->n, 562 mat_mkl_pardiso->a, 563 mat_mkl_pardiso->ia, 564 mat_mkl_pardiso->ja, 565 mat_mkl_pardiso->perm, 566 &mat_mkl_pardiso->nrhs, 567 mat_mkl_pardiso->iparm, 568 &mat_mkl_pardiso->msglvl, 569 (void*)barray, 570 (void*)xarray, 571 &mat_mkl_pardiso->err); 572 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); 573 574 ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr); 575 if (mat_mkl_pardiso->schur) { /* solve Schur complement and expand solution */ 576 PetscScalar *o_schur_work = NULL; 577 578 /* solve Schur complement */ 579 if (!mat_mkl_pardiso->solve_interior) { 580 PetscInt shift = mat_mkl_pardiso->schur_size*mat_mkl_pardiso->nrhs,scale; 581 PetscInt mem = mat_mkl_pardiso->n*mat_mkl_pardiso->nrhs; 582 583 ierr = MatFactorFactorizeSchurComplement(A);CHKERRQ(ierr); 584 /* allocate extra memory if it is needed */ 585 scale = 1; 586 if (A->schur_status == MAT_FACTOR_SCHUR_INVERTED) scale = 2; 587 mem *= scale; 588 if (mem > mat_mkl_pardiso->schur_work_size) { 589 o_schur_work = mat_mkl_pardiso->schur_work; 590 ierr = PetscMalloc1(mem,&mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 591 } 592 /* if inverted, uses BLAS *MM subroutines, otherwise LAPACK *TRS */ 593 if (A->schur_status != MAT_FACTOR_SCHUR_INVERTED) shift = 0; 594 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work,PETSC_TRUE);CHKERRQ(ierr); 595 ierr = MatMKLPardisoSolveSchur_Private(A,mat_mkl_pardiso->schur_work,mat_mkl_pardiso->schur_work+shift);CHKERRQ(ierr); 596 ierr = MatMKLPardisoScatterSchur_Private(mat_mkl_pardiso,xarray,mat_mkl_pardiso->schur_work+shift,PETSC_FALSE);CHKERRQ(ierr); 597 } else { /* if we are solving for the interior problem, any value in barray[schur,n] forward-substituted to xarray[schur,n] will be neglected */ 598 PetscInt i,n,m=0; 599 for (n=0;n<mat_mkl_pardiso->nrhs;n++) { 600 for (i=0;i<mat_mkl_pardiso->schur_size;i++) { 601 xarray[mat_mkl_pardiso->schur_idxs[i]+m] = 0.; 602 } 603 m += mat_mkl_pardiso->n; 604 } 605 } 606 607 /* expansion phase */ 608 mat_mkl_pardiso->iparm[6-1] = 1; 609 mat_mkl_pardiso->phase = JOB_SOLVE_BACKWARD_SUBSTITUTION; 610 MKL_PARDISO (mat_mkl_pardiso->pt, 611 &mat_mkl_pardiso->maxfct, 612 &mat_mkl_pardiso->mnum, 613 &mat_mkl_pardiso->mtype, 614 &mat_mkl_pardiso->phase, 615 &mat_mkl_pardiso->n, 616 mat_mkl_pardiso->a, 617 mat_mkl_pardiso->ia, 618 mat_mkl_pardiso->ja, 619 mat_mkl_pardiso->perm, 620 &mat_mkl_pardiso->nrhs, 621 mat_mkl_pardiso->iparm, 622 &mat_mkl_pardiso->msglvl, 623 (void*)xarray, 624 (void*)mat_mkl_pardiso->schur_work, /* according to the specs, the solution vector is always used */ 625 &mat_mkl_pardiso->err); 626 if (o_schur_work) { /* restore original schur_work (minimal size) */ 627 ierr = PetscFree(mat_mkl_pardiso->schur_work);CHKERRQ(ierr); 628 mat_mkl_pardiso->schur_work = o_schur_work; 629 } 630 if (mat_mkl_pardiso->err < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MKL_PARDISO: err=%d. Please check manual",mat_mkl_pardiso->err); 631 mat_mkl_pardiso->iparm[6-1] = 0; 632 } 633 ierr = MatDenseRestoreArrayWrite(X,&xarray);CHKERRQ(ierr); 634 } 635 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 636 PetscFunctionReturn(0); 637 } 638 639 PetscErrorCode MatFactorNumeric_MKL_PARDISO(Mat F,Mat A,const MatFactorInfo *info) 640 { 641 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)(F)->data; 642 PetscErrorCode ierr; 643 644 PetscFunctionBegin; 645 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 646 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); 647 648 mat_mkl_pardiso->phase = JOB_NUMERICAL_FACTORIZATION; 649 MKL_PARDISO (mat_mkl_pardiso->pt, 650 &mat_mkl_pardiso->maxfct, 651 &mat_mkl_pardiso->mnum, 652 &mat_mkl_pardiso->mtype, 653 &mat_mkl_pardiso->phase, 654 &mat_mkl_pardiso->n, 655 mat_mkl_pardiso->a, 656 mat_mkl_pardiso->ia, 657 mat_mkl_pardiso->ja, 658 mat_mkl_pardiso->perm, 659 &mat_mkl_pardiso->nrhs, 660 mat_mkl_pardiso->iparm, 661 &mat_mkl_pardiso->msglvl, 662 NULL, 663 (void*)mat_mkl_pardiso->schur, 664 &mat_mkl_pardiso->err); 665 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); 666 667 /* report flops */ 668 if (mat_mkl_pardiso->iparm[18] > 0) { 669 ierr = PetscLogFlops(PetscPowRealInt(10.,6)*mat_mkl_pardiso->iparm[18]);CHKERRQ(ierr); 670 } 671 672 if (F->schur) { /* schur output from pardiso is in row major format */ 673 #if defined(PETSC_HAVE_CUDA) 674 F->schur->offloadmask = PETSC_OFFLOAD_CPU; 675 #endif 676 ierr = MatFactorRestoreSchurComplement(F,NULL,MAT_FACTOR_SCHUR_UNFACTORED);CHKERRQ(ierr); 677 ierr = MatTranspose(F->schur,MAT_INPLACE_MATRIX,&F->schur);CHKERRQ(ierr); 678 } 679 mat_mkl_pardiso->matstruc = SAME_NONZERO_PATTERN; 680 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 681 PetscFunctionReturn(0); 682 } 683 684 PetscErrorCode PetscSetMKL_PARDISOFromOptions(Mat F, Mat A) 685 { 686 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 687 PetscErrorCode ierr; 688 PetscInt icntl,bs,threads=1; 689 PetscBool flg; 690 691 PetscFunctionBegin; 692 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MKL_PARDISO Options","Mat");CHKERRQ(ierr); 693 694 ierr = PetscOptionsInt("-mat_mkl_pardiso_65","Suggested number of threads to use within PARDISO","None",threads,&threads,&flg);CHKERRQ(ierr); 695 if (flg) PetscSetMKL_PARDISOThreads((int)threads); 696 697 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); 698 if (flg) mat_mkl_pardiso->maxfct = icntl; 699 700 ierr = PetscOptionsInt("-mat_mkl_pardiso_67","Indicates the actual matrix for the solution phase","None",mat_mkl_pardiso->mnum,&icntl,&flg);CHKERRQ(ierr); 701 if (flg) mat_mkl_pardiso->mnum = icntl; 702 703 ierr = PetscOptionsInt("-mat_mkl_pardiso_68","Message level information","None",mat_mkl_pardiso->msglvl,&icntl,&flg);CHKERRQ(ierr); 704 if (flg) mat_mkl_pardiso->msglvl = icntl; 705 706 ierr = PetscOptionsInt("-mat_mkl_pardiso_69","Defines the matrix type","None",mat_mkl_pardiso->mtype,&icntl,&flg);CHKERRQ(ierr); 707 if (flg) { 708 void *pt[IPARM_SIZE]; 709 mat_mkl_pardiso->mtype = icntl; 710 icntl = mat_mkl_pardiso->iparm[34]; 711 bs = mat_mkl_pardiso->iparm[36]; 712 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 713 #if defined(PETSC_USE_REAL_SINGLE) 714 mat_mkl_pardiso->iparm[27] = 1; 715 #else 716 mat_mkl_pardiso->iparm[27] = 0; 717 #endif 718 mat_mkl_pardiso->iparm[34] = icntl; 719 mat_mkl_pardiso->iparm[36] = bs; 720 } 721 722 ierr = PetscOptionsInt("-mat_mkl_pardiso_1","Use default values (if 0)","None",mat_mkl_pardiso->iparm[0],&icntl,&flg);CHKERRQ(ierr); 723 if (flg) mat_mkl_pardiso->iparm[0] = icntl; 724 725 ierr = PetscOptionsInt("-mat_mkl_pardiso_2","Fill-in reducing ordering for the input matrix","None",mat_mkl_pardiso->iparm[1],&icntl,&flg);CHKERRQ(ierr); 726 if (flg) mat_mkl_pardiso->iparm[1] = icntl; 727 728 ierr = PetscOptionsInt("-mat_mkl_pardiso_4","Preconditioned CGS/CG","None",mat_mkl_pardiso->iparm[3],&icntl,&flg);CHKERRQ(ierr); 729 if (flg) mat_mkl_pardiso->iparm[3] = icntl; 730 731 ierr = PetscOptionsInt("-mat_mkl_pardiso_5","User permutation","None",mat_mkl_pardiso->iparm[4],&icntl,&flg);CHKERRQ(ierr); 732 if (flg) mat_mkl_pardiso->iparm[4] = icntl; 733 734 ierr = PetscOptionsInt("-mat_mkl_pardiso_6","Write solution on x","None",mat_mkl_pardiso->iparm[5],&icntl,&flg);CHKERRQ(ierr); 735 if (flg) mat_mkl_pardiso->iparm[5] = icntl; 736 737 ierr = PetscOptionsInt("-mat_mkl_pardiso_8","Iterative refinement step","None",mat_mkl_pardiso->iparm[7],&icntl,&flg);CHKERRQ(ierr); 738 if (flg) mat_mkl_pardiso->iparm[7] = icntl; 739 740 ierr = PetscOptionsInt("-mat_mkl_pardiso_10","Pivoting perturbation","None",mat_mkl_pardiso->iparm[9],&icntl,&flg);CHKERRQ(ierr); 741 if (flg) mat_mkl_pardiso->iparm[9] = icntl; 742 743 ierr = PetscOptionsInt("-mat_mkl_pardiso_11","Scaling vectors","None",mat_mkl_pardiso->iparm[10],&icntl,&flg);CHKERRQ(ierr); 744 if (flg) mat_mkl_pardiso->iparm[10] = icntl; 745 746 ierr = PetscOptionsInt("-mat_mkl_pardiso_12","Solve with transposed or conjugate transposed matrix A","None",mat_mkl_pardiso->iparm[11],&icntl,&flg);CHKERRQ(ierr); 747 if (flg) mat_mkl_pardiso->iparm[11] = icntl; 748 749 ierr = PetscOptionsInt("-mat_mkl_pardiso_13","Improved accuracy using (non-) symmetric weighted matching","None",mat_mkl_pardiso->iparm[12],&icntl,&flg);CHKERRQ(ierr); 750 if (flg) mat_mkl_pardiso->iparm[12] = icntl; 751 752 ierr = PetscOptionsInt("-mat_mkl_pardiso_18","Numbers of non-zero elements","None",mat_mkl_pardiso->iparm[17],&icntl,&flg);CHKERRQ(ierr); 753 if (flg) mat_mkl_pardiso->iparm[17] = icntl; 754 755 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); 756 if (flg) mat_mkl_pardiso->iparm[18] = icntl; 757 758 ierr = PetscOptionsInt("-mat_mkl_pardiso_21","Pivoting for symmetric indefinite matrices","None",mat_mkl_pardiso->iparm[20],&icntl,&flg);CHKERRQ(ierr); 759 if (flg) mat_mkl_pardiso->iparm[20] = icntl; 760 761 ierr = PetscOptionsInt("-mat_mkl_pardiso_24","Parallel factorization control","None",mat_mkl_pardiso->iparm[23],&icntl,&flg);CHKERRQ(ierr); 762 if (flg) mat_mkl_pardiso->iparm[23] = icntl; 763 764 ierr = PetscOptionsInt("-mat_mkl_pardiso_25","Parallel forward/backward solve control","None",mat_mkl_pardiso->iparm[24],&icntl,&flg);CHKERRQ(ierr); 765 if (flg) mat_mkl_pardiso->iparm[24] = icntl; 766 767 ierr = PetscOptionsInt("-mat_mkl_pardiso_27","Matrix checker","None",mat_mkl_pardiso->iparm[26],&icntl,&flg);CHKERRQ(ierr); 768 if (flg) mat_mkl_pardiso->iparm[26] = icntl; 769 770 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); 771 if (flg) mat_mkl_pardiso->iparm[30] = icntl; 772 773 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); 774 if (flg) mat_mkl_pardiso->iparm[33] = icntl; 775 776 ierr = PetscOptionsInt("-mat_mkl_pardiso_60","Intel MKL_PARDISO mode","None",mat_mkl_pardiso->iparm[59],&icntl,&flg);CHKERRQ(ierr); 777 if (flg) mat_mkl_pardiso->iparm[59] = icntl; 778 PetscOptionsEnd(); 779 PetscFunctionReturn(0); 780 } 781 782 PetscErrorCode MatFactorMKL_PARDISOInitialize_Private(Mat A, MatFactorType ftype, Mat_MKL_PARDISO *mat_mkl_pardiso) 783 { 784 PetscErrorCode ierr; 785 PetscInt i,bs; 786 PetscBool match; 787 788 PetscFunctionBegin; 789 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->iparm[i] = 0; 790 for (i=0; i<IPARM_SIZE; i++) mat_mkl_pardiso->pt[i] = 0; 791 #if defined(PETSC_USE_REAL_SINGLE) 792 mat_mkl_pardiso->iparm[27] = 1; 793 #else 794 mat_mkl_pardiso->iparm[27] = 0; 795 #endif 796 /* Default options for both sym and unsym */ 797 mat_mkl_pardiso->iparm[ 0] = 1; /* Solver default parameters overriden with provided by iparm */ 798 mat_mkl_pardiso->iparm[ 1] = 2; /* Metis reordering */ 799 mat_mkl_pardiso->iparm[ 5] = 0; /* Write solution into x */ 800 mat_mkl_pardiso->iparm[ 7] = 0; /* Max number of iterative refinement steps */ 801 mat_mkl_pardiso->iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ 802 mat_mkl_pardiso->iparm[18] = -1; /* Output: Mflops for LU factorization */ 803 #if 0 804 mat_mkl_pardiso->iparm[23] = 1; /* Parallel factorization control*/ 805 #endif 806 ierr = PetscObjectTypeCompareAny((PetscObject)A,&match,MATSEQBAIJ,MATSEQSBAIJ,"");CHKERRQ(ierr); 807 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 808 if (!match || bs == 1) { 809 mat_mkl_pardiso->iparm[34] = 1; /* Cluster Sparse Solver use C-style indexing for ia and ja arrays */ 810 mat_mkl_pardiso->n = A->rmap->N; 811 } else { 812 mat_mkl_pardiso->iparm[34] = 0; /* Cluster Sparse Solver use Fortran-style indexing for ia and ja arrays */ 813 mat_mkl_pardiso->iparm[36] = bs; 814 mat_mkl_pardiso->n = A->rmap->N/bs; 815 } 816 mat_mkl_pardiso->iparm[39] = 0; /* Input: matrix/rhs/solution stored on rank-0 */ 817 818 mat_mkl_pardiso->CleanUp = PETSC_FALSE; 819 mat_mkl_pardiso->maxfct = 1; /* Maximum number of numerical factorizations. */ 820 mat_mkl_pardiso->mnum = 1; /* Which factorization to use. */ 821 mat_mkl_pardiso->msglvl = 0; /* 0: do not print 1: Print statistical information in file */ 822 mat_mkl_pardiso->phase = -1; 823 mat_mkl_pardiso->err = 0; 824 825 mat_mkl_pardiso->nrhs = 1; 826 mat_mkl_pardiso->err = 0; 827 mat_mkl_pardiso->phase = -1; 828 829 if (ftype == MAT_FACTOR_LU) { 830 mat_mkl_pardiso->iparm[ 9] = 13; /* Perturb the pivot elements with 1E-13 */ 831 mat_mkl_pardiso->iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */ 832 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 833 } else { 834 mat_mkl_pardiso->iparm[ 9] = 8; /* Perturb the pivot elements with 1E-8 */ 835 mat_mkl_pardiso->iparm[10] = 0; /* Use nonsymmetric permutation and scaling MPS */ 836 mat_mkl_pardiso->iparm[12] = 1; /* Switch on Maximum Weighted Matching algorithm (default for non-symmetric) */ 837 #if defined(PETSC_USE_DEBUG) 838 mat_mkl_pardiso->iparm[26] = 1; /* Matrix checker */ 839 #endif 840 } 841 ierr = PetscCalloc1(A->rmap->N*sizeof(INT_TYPE), &mat_mkl_pardiso->perm);CHKERRQ(ierr); 842 mat_mkl_pardiso->schur_size = 0; 843 PetscFunctionReturn(0); 844 } 845 846 PetscErrorCode MatFactorSymbolic_AIJMKL_PARDISO_Private(Mat F,Mat A,const MatFactorInfo *info) 847 { 848 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 849 PetscErrorCode ierr; 850 851 PetscFunctionBegin; 852 mat_mkl_pardiso->matstruc = DIFFERENT_NONZERO_PATTERN; 853 ierr = PetscSetMKL_PARDISOFromOptions(F,A);CHKERRQ(ierr); 854 /* throw away any previously computed structure */ 855 if (mat_mkl_pardiso->freeaij) { 856 ierr = PetscFree2(mat_mkl_pardiso->ia,mat_mkl_pardiso->ja);CHKERRQ(ierr); 857 if (mat_mkl_pardiso->iparm[34] == 1) { 858 ierr = PetscFree(mat_mkl_pardiso->a);CHKERRQ(ierr); 859 } 860 } 861 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); 862 if (mat_mkl_pardiso->iparm[34] == 1) mat_mkl_pardiso->n = A->rmap->N; 863 else mat_mkl_pardiso->n = A->rmap->N/A->rmap->bs; 864 865 mat_mkl_pardiso->phase = JOB_ANALYSIS; 866 867 /* reset flops counting if requested */ 868 if (mat_mkl_pardiso->iparm[18]) mat_mkl_pardiso->iparm[18] = -1; 869 870 MKL_PARDISO (mat_mkl_pardiso->pt, 871 &mat_mkl_pardiso->maxfct, 872 &mat_mkl_pardiso->mnum, 873 &mat_mkl_pardiso->mtype, 874 &mat_mkl_pardiso->phase, 875 &mat_mkl_pardiso->n, 876 mat_mkl_pardiso->a, 877 mat_mkl_pardiso->ia, 878 mat_mkl_pardiso->ja, 879 mat_mkl_pardiso->perm, 880 &mat_mkl_pardiso->nrhs, 881 mat_mkl_pardiso->iparm, 882 &mat_mkl_pardiso->msglvl, 883 NULL, 884 NULL, 885 &mat_mkl_pardiso->err); 886 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); 887 888 mat_mkl_pardiso->CleanUp = PETSC_TRUE; 889 890 if (F->factortype == MAT_FACTOR_LU) F->ops->lufactornumeric = MatFactorNumeric_MKL_PARDISO; 891 else F->ops->choleskyfactornumeric = MatFactorNumeric_MKL_PARDISO; 892 893 F->ops->solve = MatSolve_MKL_PARDISO; 894 F->ops->solvetranspose = MatSolveTranspose_MKL_PARDISO; 895 F->ops->matsolve = MatMatSolve_MKL_PARDISO; 896 PetscFunctionReturn(0); 897 } 898 899 PetscErrorCode MatLUFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 900 { 901 PetscErrorCode ierr; 902 903 PetscFunctionBegin; 904 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 905 PetscFunctionReturn(0); 906 } 907 908 #if !defined(PETSC_USE_COMPLEX) 909 PetscErrorCode MatGetInertia_MKL_PARDISO(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) 910 { 911 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)F->data; 912 913 PetscFunctionBegin; 914 if (nneg) *nneg = mat_mkl_pardiso->iparm[22]; 915 if (npos) *npos = mat_mkl_pardiso->iparm[21]; 916 if (nzero) *nzero = F->rmap->N - (mat_mkl_pardiso->iparm[22] + mat_mkl_pardiso->iparm[21]); 917 PetscFunctionReturn(0); 918 } 919 #endif 920 921 PetscErrorCode MatCholeskyFactorSymbolic_AIJMKL_PARDISO(Mat F,Mat A,IS r,const MatFactorInfo *info) 922 { 923 PetscErrorCode ierr; 924 925 PetscFunctionBegin; 926 ierr = MatFactorSymbolic_AIJMKL_PARDISO_Private(F, A, info);CHKERRQ(ierr); 927 #if defined(PETSC_USE_COMPLEX) 928 F->ops->getinertia = NULL; 929 #else 930 F->ops->getinertia = MatGetInertia_MKL_PARDISO; 931 #endif 932 PetscFunctionReturn(0); 933 } 934 935 PetscErrorCode MatView_MKL_PARDISO(Mat A, PetscViewer viewer) 936 { 937 PetscErrorCode ierr; 938 PetscBool iascii; 939 PetscViewerFormat format; 940 Mat_MKL_PARDISO *mat_mkl_pardiso=(Mat_MKL_PARDISO*)A->data; 941 PetscInt i; 942 943 PetscFunctionBegin; 944 if (A->ops->solve != MatSolve_MKL_PARDISO) PetscFunctionReturn(0); 945 946 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 947 if (iascii) { 948 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 949 if (format == PETSC_VIEWER_ASCII_INFO) { 950 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO run parameters:\n");CHKERRQ(ierr); 951 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO phase: %d \n",mat_mkl_pardiso->phase);CHKERRQ(ierr); 952 for (i=1; i<=64; i++) { 953 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO iparm[%d]: %d \n",i, mat_mkl_pardiso->iparm[i - 1]);CHKERRQ(ierr); 954 } 955 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO maxfct: %d \n", mat_mkl_pardiso->maxfct);CHKERRQ(ierr); 956 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mnum: %d \n", mat_mkl_pardiso->mnum);CHKERRQ(ierr); 957 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO mtype: %d \n", mat_mkl_pardiso->mtype);CHKERRQ(ierr); 958 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO n: %d \n", mat_mkl_pardiso->n);CHKERRQ(ierr); 959 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO nrhs: %d \n", mat_mkl_pardiso->nrhs);CHKERRQ(ierr); 960 ierr = PetscViewerASCIIPrintf(viewer,"MKL_PARDISO msglvl: %d \n", mat_mkl_pardiso->msglvl);CHKERRQ(ierr); 961 } 962 } 963 PetscFunctionReturn(0); 964 } 965 966 PetscErrorCode MatGetInfo_MKL_PARDISO(Mat A, MatInfoType flag, MatInfo *info) 967 { 968 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)A->data; 969 970 PetscFunctionBegin; 971 info->block_size = 1.0; 972 info->nz_used = mat_mkl_pardiso->iparm[17]; 973 info->nz_allocated = mat_mkl_pardiso->iparm[17]; 974 info->nz_unneeded = 0.0; 975 info->assemblies = 0.0; 976 info->mallocs = 0.0; 977 info->memory = 0.0; 978 info->fill_ratio_given = 0; 979 info->fill_ratio_needed = 0; 980 info->factor_mallocs = 0; 981 PetscFunctionReturn(0); 982 } 983 984 PetscErrorCode MatMkl_PardisoSetCntl_MKL_PARDISO(Mat F,PetscInt icntl,PetscInt ival) 985 { 986 PetscInt backup,bs; 987 Mat_MKL_PARDISO *mat_mkl_pardiso = (Mat_MKL_PARDISO*)F->data; 988 989 PetscFunctionBegin; 990 if (icntl <= 64) { 991 mat_mkl_pardiso->iparm[icntl - 1] = ival; 992 } else { 993 if (icntl == 65) PetscSetMKL_PARDISOThreads(ival); 994 else if (icntl == 66) mat_mkl_pardiso->maxfct = ival; 995 else if (icntl == 67) mat_mkl_pardiso->mnum = ival; 996 else if (icntl == 68) mat_mkl_pardiso->msglvl = ival; 997 else if (icntl == 69) { 998 void *pt[IPARM_SIZE]; 999 backup = mat_mkl_pardiso->iparm[34]; 1000 bs = mat_mkl_pardiso->iparm[36]; 1001 mat_mkl_pardiso->mtype = ival; 1002 MKL_PARDISO_INIT(pt, &mat_mkl_pardiso->mtype, mat_mkl_pardiso->iparm); 1003 #if defined(PETSC_USE_REAL_SINGLE) 1004 mat_mkl_pardiso->iparm[27] = 1; 1005 #else 1006 mat_mkl_pardiso->iparm[27] = 0; 1007 #endif 1008 mat_mkl_pardiso->iparm[34] = backup; 1009 mat_mkl_pardiso->iparm[36] = bs; 1010 } else if (icntl==70) mat_mkl_pardiso->solve_interior = (PetscBool)!!ival; 1011 } 1012 PetscFunctionReturn(0); 1013 } 1014 1015 /*@ 1016 MatMkl_PardisoSetCntl - Set Mkl_Pardiso parameters 1017 1018 Logically Collective on Mat 1019 1020 Input Parameters: 1021 + F - the factored matrix obtained by calling MatGetFactor() 1022 . icntl - index of Mkl_Pardiso parameter 1023 - ival - value of Mkl_Pardiso parameter 1024 1025 Options Database: 1026 . -mat_mkl_pardiso_<icntl> <ival> 1027 1028 Level: beginner 1029 1030 References: 1031 . Mkl_Pardiso Users' Guide 1032 1033 .seealso: MatGetFactor() 1034 @*/ 1035 PetscErrorCode MatMkl_PardisoSetCntl(Mat F,PetscInt icntl,PetscInt ival) 1036 { 1037 PetscErrorCode ierr; 1038 1039 PetscFunctionBegin; 1040 ierr = PetscTryMethod(F,"MatMkl_PardisoSetCntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 1041 PetscFunctionReturn(0); 1042 } 1043 1044 /*MC 1045 MATSOLVERMKL_PARDISO - A matrix type providing direct solvers (LU) for 1046 sequential matrices via the external package MKL_PARDISO. 1047 1048 Works with MATSEQAIJ matrices 1049 1050 Use -pc_type lu -pc_factor_mat_solver_type mkl_pardiso to use this direct solver 1051 1052 Options Database Keys: 1053 + -mat_mkl_pardiso_65 - Suggested number of threads to use within MKL_PARDISO 1054 . -mat_mkl_pardiso_66 - Maximum number of factors with identical sparsity structure that must be kept in memory at the same time 1055 . -mat_mkl_pardiso_67 - Indicates the actual matrix for the solution phase 1056 . -mat_mkl_pardiso_68 - Message level information, use 1 to get detailed information on the solver options 1057 . -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 1058 . -mat_mkl_pardiso_1 - Use default values 1059 . -mat_mkl_pardiso_2 - Fill-in reducing ordering for the input matrix 1060 . -mat_mkl_pardiso_4 - Preconditioned CGS/CG 1061 . -mat_mkl_pardiso_5 - User permutation 1062 . -mat_mkl_pardiso_6 - Write solution on x 1063 . -mat_mkl_pardiso_8 - Iterative refinement step 1064 . -mat_mkl_pardiso_10 - Pivoting perturbation 1065 . -mat_mkl_pardiso_11 - Scaling vectors 1066 . -mat_mkl_pardiso_12 - Solve with transposed or conjugate transposed matrix A 1067 . -mat_mkl_pardiso_13 - Improved accuracy using (non-) symmetric weighted matching 1068 . -mat_mkl_pardiso_18 - Numbers of non-zero elements 1069 . -mat_mkl_pardiso_19 - Report number of floating point operations 1070 . -mat_mkl_pardiso_21 - Pivoting for symmetric indefinite matrices 1071 . -mat_mkl_pardiso_24 - Parallel factorization control 1072 . -mat_mkl_pardiso_25 - Parallel forward/backward solve control 1073 . -mat_mkl_pardiso_27 - Matrix checker 1074 . -mat_mkl_pardiso_31 - Partial solve and computing selected components of the solution vectors 1075 . -mat_mkl_pardiso_34 - Optimal number of threads for conditional numerical reproducibility (CNR) mode 1076 - -mat_mkl_pardiso_60 - Intel MKL_PARDISO mode 1077 1078 Level: beginner 1079 1080 Notes: 1081 Use -mat_mkl_pardiso_68 1 to display the number of threads the solver is using. MKL does not provide a way to directly access this 1082 information. 1083 1084 For more information on the options check the MKL_Pardiso manual 1085 1086 .seealso: PCFactorSetMatSolverType(), MatSolverType 1087 1088 M*/ 1089 static PetscErrorCode MatFactorGetSolverType_mkl_pardiso(Mat A, MatSolverType *type) 1090 { 1091 PetscFunctionBegin; 1092 *type = MATSOLVERMKL_PARDISO; 1093 PetscFunctionReturn(0); 1094 } 1095 1096 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat A,MatFactorType ftype,Mat *F) 1097 { 1098 Mat B; 1099 PetscErrorCode ierr; 1100 Mat_MKL_PARDISO *mat_mkl_pardiso; 1101 PetscBool isSeqAIJ,isSeqBAIJ,isSeqSBAIJ; 1102 1103 PetscFunctionBegin; 1104 ierr = PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 1105 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 1106 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 1107 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1108 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1109 ierr = PetscStrallocpy("mkl_pardiso",&((PetscObject)B)->type_name);CHKERRQ(ierr); 1110 ierr = MatSetUp(B);CHKERRQ(ierr); 1111 1112 ierr = PetscNewLog(B,&mat_mkl_pardiso);CHKERRQ(ierr); 1113 B->data = mat_mkl_pardiso; 1114 1115 ierr = MatFactorMKL_PARDISOInitialize_Private(A, ftype, mat_mkl_pardiso);CHKERRQ(ierr); 1116 if (ftype == MAT_FACTOR_LU) { 1117 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMKL_PARDISO; 1118 B->factortype = MAT_FACTOR_LU; 1119 mat_mkl_pardiso->needsym = PETSC_FALSE; 1120 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1121 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1122 else if (isSeqSBAIJ) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU factor with SEQSBAIJ format! Use MAT_FACTOR_CHOLESKY instead"); 1123 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO LU with %s format",((PetscObject)A)->type_name); 1124 #if defined(PETSC_USE_COMPLEX) 1125 mat_mkl_pardiso->mtype = 13; 1126 #else 1127 mat_mkl_pardiso->mtype = 11; 1128 #endif 1129 } else { 1130 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_AIJMKL_PARDISO; 1131 B->factortype = MAT_FACTOR_CHOLESKY; 1132 if (isSeqAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqaij; 1133 else if (isSeqBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqbaij; 1134 else if (isSeqSBAIJ) mat_mkl_pardiso->Convert = MatMKLPardiso_Convert_seqsbaij; 1135 else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with %s format",((PetscObject)A)->type_name); 1136 1137 mat_mkl_pardiso->needsym = PETSC_TRUE; 1138 #if !defined(PETSC_USE_COMPLEX) 1139 if (A->spd_set && A->spd) mat_mkl_pardiso->mtype = 2; 1140 else mat_mkl_pardiso->mtype = -2; 1141 #else 1142 mat_mkl_pardiso->mtype = 6; 1143 if (A->hermitian) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for PARDISO CHOLESKY with Hermitian matrices! Use MAT_FACTOR_LU instead"); 1144 #endif 1145 } 1146 B->ops->destroy = MatDestroy_MKL_PARDISO; 1147 B->ops->view = MatView_MKL_PARDISO; 1148 B->ops->getinfo = MatGetInfo_MKL_PARDISO; 1149 B->factortype = ftype; 1150 B->assembled = PETSC_TRUE; 1151 1152 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 1153 ierr = PetscStrallocpy(MATSOLVERMKL_PARDISO,&B->solvertype);CHKERRQ(ierr); 1154 1155 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_mkl_pardiso);CHKERRQ(ierr); 1156 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MKL_PARDISO);CHKERRQ(ierr); 1157 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMkl_PardisoSetCntl_C",MatMkl_PardisoSetCntl_MKL_PARDISO);CHKERRQ(ierr); 1158 1159 *F = B; 1160 PetscFunctionReturn(0); 1161 } 1162 1163 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_MKL_Pardiso(void) 1164 { 1165 PetscErrorCode ierr; 1166 1167 PetscFunctionBegin; 1168 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1169 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1170 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1171 ierr = MatSolverTypeRegister(MATSOLVERMKL_PARDISO,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 1172 PetscFunctionReturn(0); 1173 } 1174 1175