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