1 2 /* 3 Provides an interface to the SuperLU_DIST sparse solver 4 */ 5 6 #include <../src/mat/impls/aij/seq/aij.h> 7 #include <../src/mat/impls/aij/mpi/mpiaij.h> 8 #if defined(PETSC_HAVE_STDLIB_H) /* This is to get around weird problem with SuperLU on cray */ 9 #include <stdlib.h> 10 #endif 11 12 EXTERN_C_BEGIN 13 #if defined(PETSC_USE_COMPLEX) 14 #include <superlu_zdefs.h> 15 #else 16 #include <superlu_ddefs.h> 17 #endif 18 EXTERN_C_END 19 20 /* 21 GLOBAL - The sparse matrix and right hand side are all stored initially on process 0. Should be called centralized 22 DISTRIBUTED - The sparse matrix and right hand size are initially stored across the entire MPI communicator. 23 */ 24 typedef enum {GLOBAL,DISTRIBUTED} SuperLU_MatInputMode; 25 const char *SuperLU_MatInputModes[] = {"GLOBAL","DISTRIBUTED","SuperLU_MatInputMode","PETSC_",0}; 26 27 typedef struct { 28 int_t nprow,npcol,*row,*col; 29 gridinfo_t grid; 30 superlu_dist_options_t options; 31 SuperMatrix A_sup; 32 ScalePermstruct_t ScalePermstruct; 33 LUstruct_t LUstruct; 34 int StatPrint; 35 SuperLU_MatInputMode MatInputMode; 36 SOLVEstruct_t SOLVEstruct; 37 fact_t FactPattern; 38 MPI_Comm comm_superlu; 39 #if defined(PETSC_USE_COMPLEX) 40 doublecomplex *val; 41 #else 42 double *val; 43 #endif 44 PetscBool matsolve_iscalled,matmatsolve_iscalled; 45 PetscBool CleanUpSuperLU_Dist; /* Flag to clean up (non-global) SuperLU objects during Destroy */ 46 } Mat_SuperLU_DIST; 47 48 49 PetscErrorCode MatSuperluDistGetDiagU_SuperLU_DIST(Mat F,PetscScalar *diagU) 50 { 51 Mat_SuperLU_DIST *lu= (Mat_SuperLU_DIST*)F->data; 52 53 PetscFunctionBegin; 54 #if defined(PETSC_USE_COMPLEX) 55 PetscStackCall("SuperLU_DIST:pzGetDiagU",pzGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,(doublecomplex*)diagU)); 56 #else 57 PetscStackCall("SuperLU_DIST:pdGetDiagU",pdGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,diagU)); 58 #endif 59 PetscFunctionReturn(0); 60 } 61 62 PetscErrorCode MatSuperluDistGetDiagU(Mat F,PetscScalar *diagU) 63 { 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 PetscValidHeaderSpecific(F,MAT_CLASSID,1); 68 ierr = PetscTryMethod(F,"MatSuperluDistGetDiagU_C",(Mat,PetscScalar*),(F,diagU));CHKERRQ(ierr); 69 PetscFunctionReturn(0); 70 } 71 72 static PetscErrorCode MatDestroy_SuperLU_DIST(Mat A) 73 { 74 PetscErrorCode ierr; 75 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; 76 77 PetscFunctionBegin; 78 if (lu->CleanUpSuperLU_Dist) { 79 /* Deallocate SuperLU_DIST storage */ 80 if (lu->MatInputMode == GLOBAL) { 81 PetscStackCall("SuperLU_DIST:Destroy_CompCol_Matrix_dist",Destroy_CompCol_Matrix_dist(&lu->A_sup)); 82 } else { 83 PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup)); 84 if (lu->options.SolveInitialized) { 85 #if defined(PETSC_USE_COMPLEX) 86 PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); 87 #else 88 PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); 89 #endif 90 } 91 } 92 PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(A->cmap->N, &lu->grid, &lu->LUstruct)); 93 PetscStackCall("SuperLU_DIST:ScalePermstructFree",ScalePermstructFree(&lu->ScalePermstruct)); 94 PetscStackCall("SuperLU_DIST:LUstructFree",LUstructFree(&lu->LUstruct)); 95 96 /* Release the SuperLU_DIST process grid. */ 97 PetscStackCall("SuperLU_DIST:superlu_gridexit",superlu_gridexit(&lu->grid)); 98 ierr = MPI_Comm_free(&(lu->comm_superlu));CHKERRQ(ierr); 99 } 100 ierr = PetscFree(A->data);CHKERRQ(ierr); 101 /* clear composed functions */ 102 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); 103 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSuperluDistGetDiagU_C",NULL);CHKERRQ(ierr); 104 105 PetscFunctionReturn(0); 106 } 107 108 static PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x) 109 { 110 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; 111 PetscErrorCode ierr; 112 PetscMPIInt size; 113 PetscInt m=A->rmap->n,M=A->rmap->N,N=A->cmap->N; 114 SuperLUStat_t stat; 115 double berr[1]; 116 PetscScalar *bptr=NULL; 117 PetscInt nrhs=1; 118 Vec x_seq; 119 IS iden; 120 VecScatter scat; 121 int info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */ 122 static PetscBool cite = PETSC_FALSE; 123 124 PetscFunctionBegin; 125 if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); 126 ierr = PetscCitationsRegister("@article{lidemmel03,\n author = {Xiaoye S. Li and James W. Demmel},\n title = {{SuperLU_DIST}: A Scalable Distributed-Memory Sparse Direct\n Solver for Unsymmetric Linear Systems},\n journal = {ACM Trans. Mathematical Software},\n volume = {29},\n number = {2},\n pages = {110-140},\n year = 2003\n}\n",&cite);CHKERRQ(ierr); 127 128 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 129 if (size > 1 && lu->MatInputMode == GLOBAL) { 130 /* global mat input, convert b to x_seq */ 131 ierr = VecCreateSeq(PETSC_COMM_SELF,N,&x_seq);CHKERRQ(ierr); 132 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iden);CHKERRQ(ierr); 133 ierr = VecScatterCreate(b_mpi,iden,x_seq,iden,&scat);CHKERRQ(ierr); 134 ierr = ISDestroy(&iden);CHKERRQ(ierr); 135 136 ierr = VecScatterBegin(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 137 ierr = VecScatterEnd(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 138 ierr = VecGetArray(x_seq,&bptr);CHKERRQ(ierr); 139 } else { /* size==1 || distributed mat input */ 140 if (lu->options.SolveInitialized && !lu->matsolve_iscalled) { 141 /* see comments in MatMatSolve() */ 142 #if defined(PETSC_USE_COMPLEX) 143 PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); 144 #else 145 PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); 146 #endif 147 lu->options.SolveInitialized = NO; 148 } 149 ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); 150 ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); 151 } 152 153 PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ 154 if (lu->MatInputMode == GLOBAL) { 155 #if defined(PETSC_USE_COMPLEX) 156 PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,M,nrhs,&lu->grid,&lu->LUstruct,berr,&stat,&info)); 157 #else 158 PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr,M,nrhs,&lu->grid,&lu->LUstruct,berr,&stat,&info)); 159 #endif 160 } else { /* distributed mat input */ 161 #if defined(PETSC_USE_COMPLEX) 162 PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); 163 #else 164 PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); 165 #endif 166 } 167 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info); 168 169 if (lu->options.PrintStat) PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 170 PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); 171 172 if (size > 1 && lu->MatInputMode == GLOBAL) { 173 /* convert seq x to mpi x */ 174 ierr = VecRestoreArray(x_seq,&bptr);CHKERRQ(ierr); 175 ierr = VecScatterBegin(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 176 ierr = VecScatterEnd(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 177 ierr = VecScatterDestroy(&scat);CHKERRQ(ierr); 178 ierr = VecDestroy(&x_seq);CHKERRQ(ierr); 179 } else { 180 ierr = VecRestoreArray(x,&bptr);CHKERRQ(ierr); 181 182 lu->matsolve_iscalled = PETSC_TRUE; 183 lu->matmatsolve_iscalled = PETSC_FALSE; 184 } 185 PetscFunctionReturn(0); 186 } 187 188 static PetscErrorCode MatMatSolve_SuperLU_DIST(Mat A,Mat B_mpi,Mat X) 189 { 190 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; 191 PetscErrorCode ierr; 192 PetscMPIInt size; 193 PetscInt M=A->rmap->N,m=A->rmap->n,nrhs; 194 SuperLUStat_t stat; 195 double berr[1]; 196 PetscScalar *bptr; 197 int info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */ 198 PetscBool flg; 199 200 PetscFunctionBegin; 201 if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); 202 ierr = PetscObjectTypeCompareAny((PetscObject)B_mpi,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 203 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 204 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 205 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 206 207 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 208 if (size > 1 && lu->MatInputMode == GLOBAL) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatInputMode=GLOBAL for nproc %d>1 is not supported",size); 209 /* size==1 or distributed mat input */ 210 if (lu->options.SolveInitialized && !lu->matmatsolve_iscalled) { 211 /* communication pattern of SOLVEstruct is unlikely created for matmatsolve, 212 thus destroy it and create a new SOLVEstruct. 213 Otherwise it may result in memory corruption or incorrect solution 214 See src/mat/examples/tests/ex125.c */ 215 #if defined(PETSC_USE_COMPLEX) 216 PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); 217 #else 218 PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); 219 #endif 220 lu->options.SolveInitialized = NO; 221 } 222 ierr = MatCopy(B_mpi,X,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 223 224 ierr = MatGetSize(B_mpi,NULL,&nrhs);CHKERRQ(ierr); 225 226 PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ 227 ierr = MatDenseGetArray(X,&bptr);CHKERRQ(ierr); 228 if (lu->MatInputMode == GLOBAL) { /* size == 1 */ 229 #if defined(PETSC_USE_COMPLEX) 230 PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,(doublecomplex*)bptr, M, nrhs,&lu->grid, &lu->LUstruct, berr, &stat, &info)); 231 #else 232 PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr, M, nrhs, &lu->grid, &lu->LUstruct, berr, &stat, &info)); 233 #endif 234 } else { /* distributed mat input */ 235 #if defined(PETSC_USE_COMPLEX) 236 PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid, &lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); 237 #else 238 PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); 239 #endif 240 } 241 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info); 242 ierr = MatDenseRestoreArray(X,&bptr);CHKERRQ(ierr); 243 244 if (lu->options.PrintStat) PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 245 PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); 246 lu->matsolve_iscalled = PETSC_FALSE; 247 lu->matmatsolve_iscalled = PETSC_TRUE; 248 PetscFunctionReturn(0); 249 } 250 251 /* 252 input: 253 F: numeric Cholesky factor 254 output: 255 nneg: total number of negative pivots 256 nzero: total number of zero pivots 257 npos: (global dimension of F) - nneg - nzero 258 */ 259 static PetscErrorCode MatGetInertia_SuperLU_DIST(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) 260 { 261 PetscErrorCode ierr; 262 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data; 263 PetscScalar *diagU=NULL; 264 PetscInt M,i,neg=0,zero=0,pos=0; 265 PetscReal r; 266 267 PetscFunctionBegin; 268 if (!F->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Matrix factor F is not assembled"); 269 if (lu->options.RowPerm != NOROWPERM) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must set NOROWPERM"); 270 ierr = MatGetSize(F,&M,NULL);CHKERRQ(ierr); 271 ierr = PetscMalloc1(M,&diagU);CHKERRQ(ierr); 272 ierr = MatSuperluDistGetDiagU(F,diagU);CHKERRQ(ierr); 273 for (i=0; i<M; i++) { 274 #if defined(PETSC_USE_COMPLEX) 275 r = PetscImaginaryPart(diagU[i])/10.0; 276 if (r< -PETSC_MACHINE_EPSILON || r>PETSC_MACHINE_EPSILON) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"diagU[%d]=%g + i %g is non-real",i,PetscRealPart(diagU[i]),r*10.0); 277 r = PetscRealPart(diagU[i]); 278 #else 279 r = diagU[i]; 280 #endif 281 if (r > 0) { 282 pos++; 283 } else if (r < 0) { 284 neg++; 285 } else zero++; 286 } 287 288 ierr = PetscFree(diagU);CHKERRQ(ierr); 289 if (nneg) *nneg = neg; 290 if (nzero) *nzero = zero; 291 if (npos) *npos = pos; 292 PetscFunctionReturn(0); 293 } 294 295 static PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat F,Mat A,const MatFactorInfo *info) 296 { 297 Mat *tseq,A_seq = NULL; 298 Mat_SeqAIJ *aa,*bb; 299 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data; 300 PetscErrorCode ierr; 301 PetscInt M=A->rmap->N,N=A->cmap->N,i,*ai,*aj,*bi,*bj,nz,rstart,*garray, 302 m=A->rmap->n, colA_start,j,jcol,jB,countA,countB,*bjj,*ajj=NULL; 303 int sinfo; /* SuperLU_Dist info flag is always an int even with long long indices */ 304 PetscMPIInt size; 305 SuperLUStat_t stat; 306 double *berr=0; 307 IS isrow; 308 #if defined(PETSC_USE_COMPLEX) 309 doublecomplex *av, *bv; 310 #else 311 double *av, *bv; 312 #endif 313 314 PetscFunctionBegin; 315 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 316 317 if (lu->MatInputMode == GLOBAL) { /* global mat input */ 318 if (size > 1) { /* convert mpi A to seq mat A */ 319 ierr = ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);CHKERRQ(ierr); 320 ierr = MatCreateSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);CHKERRQ(ierr); 321 ierr = ISDestroy(&isrow);CHKERRQ(ierr); 322 323 A_seq = *tseq; 324 ierr = PetscFree(tseq);CHKERRQ(ierr); 325 aa = (Mat_SeqAIJ*)A_seq->data; 326 } else { 327 PetscBool flg; 328 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 329 if (flg) { 330 Mat_MPIAIJ *At = (Mat_MPIAIJ*)A->data; 331 A = At->A; 332 } 333 aa = (Mat_SeqAIJ*)A->data; 334 } 335 336 /* Convert Petsc NR matrix to SuperLU_DIST NC. 337 Note: memories of lu->val, col and row are allocated by CompRow_to_CompCol_dist()! */ 338 if (lu->options.Fact != DOFACT) {/* successive numeric factorization, sparsity pattern is reused. */ 339 PetscStackCall("SuperLU_DIST:Destroy_CompCol_Matrix_dist",Destroy_CompCol_Matrix_dist(&lu->A_sup)); 340 if (lu->FactPattern == SamePattern_SameRowPerm) { 341 lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ 342 } else { /* lu->FactPattern == SamePattern */ 343 PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); 344 lu->options.Fact = SamePattern; 345 } 346 } 347 #if defined(PETSC_USE_COMPLEX) 348 PetscStackCall("SuperLU_DIST:zCompRow_to_CompCol_dist",zCompRow_to_CompCol_dist(M,N,aa->nz,(doublecomplex*)aa->a,(int_t*)aa->j,(int_t*)aa->i,&lu->val,&lu->col, &lu->row)); 349 #else 350 PetscStackCall("SuperLU_DIST:dCompRow_to_CompCol_dist",dCompRow_to_CompCol_dist(M,N,aa->nz,aa->a,(int_t*)aa->j,(int_t*)aa->i,&lu->val, &lu->col, &lu->row)); 351 #endif 352 353 /* Create compressed column matrix A_sup. */ 354 #if defined(PETSC_USE_COMPLEX) 355 PetscStackCall("SuperLU_DIST:zCreate_CompCol_Matrix_dist",zCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_Z, SLU_GE)); 356 #else 357 PetscStackCall("SuperLU_DIST:dCreate_CompCol_Matrix_dist",dCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_D, SLU_GE)); 358 #endif 359 } else { /* distributed mat input */ 360 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 361 aa=(Mat_SeqAIJ*)(mat->A)->data; 362 bb=(Mat_SeqAIJ*)(mat->B)->data; 363 ai=aa->i; aj=aa->j; 364 bi=bb->i; bj=bb->j; 365 #if defined(PETSC_USE_COMPLEX) 366 av=(doublecomplex*)aa->a; 367 bv=(doublecomplex*)bb->a; 368 #else 369 av=aa->a; 370 bv=bb->a; 371 #endif 372 rstart = A->rmap->rstart; 373 nz = aa->nz + bb->nz; 374 garray = mat->garray; 375 376 if (lu->options.Fact == DOFACT) { /* first numeric factorization */ 377 #if defined(PETSC_USE_COMPLEX) 378 PetscStackCall("SuperLU_DIST:zallocateA_dist",zallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); 379 #else 380 PetscStackCall("SuperLU_DIST:dallocateA_dist",dallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); 381 #endif 382 } else { /* successive numeric factorization, sparsity pattern and perm_c are reused. */ 383 if (lu->FactPattern == SamePattern_SameRowPerm) { 384 lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ 385 } else if (lu->FactPattern == SamePattern) { 386 PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); /* Deallocate L and U matrices. */ 387 lu->options.Fact = SamePattern; 388 } else if (lu->FactPattern == DOFACT) { 389 PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup)); 390 PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); 391 lu->options.Fact = DOFACT; 392 393 #if defined(PETSC_USE_COMPLEX) 394 PetscStackCall("SuperLU_DIST:zallocateA_dist",zallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); 395 #else 396 PetscStackCall("SuperLU_DIST:dallocateA_dist",dallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); 397 #endif 398 } else { 399 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"options.Fact must be one of SamePattern SamePattern_SameRowPerm DOFACT"); 400 } 401 } 402 nz = 0; 403 for (i=0; i<m; i++) { 404 lu->row[i] = nz; 405 countA = ai[i+1] - ai[i]; 406 countB = bi[i+1] - bi[i]; 407 if (aj) { 408 ajj = aj + ai[i]; /* ptr to the beginning of this row */ 409 } else { 410 ajj = NULL; 411 } 412 bjj = bj + bi[i]; 413 414 /* B part, smaller col index */ 415 if (aj) { 416 colA_start = rstart + ajj[0]; /* the smallest global col index of A */ 417 } else { /* superlu_dist does not require matrix has diagonal entries, thus aj=NULL would work */ 418 colA_start = rstart; 419 } 420 jB = 0; 421 for (j=0; j<countB; j++) { 422 jcol = garray[bjj[j]]; 423 if (jcol > colA_start) { 424 jB = j; 425 break; 426 } 427 lu->col[nz] = jcol; 428 lu->val[nz++] = *bv++; 429 if (j==countB-1) jB = countB; 430 } 431 432 /* A part */ 433 for (j=0; j<countA; j++) { 434 lu->col[nz] = rstart + ajj[j]; 435 lu->val[nz++] = *av++; 436 } 437 438 /* B part, larger col index */ 439 for (j=jB; j<countB; j++) { 440 lu->col[nz] = garray[bjj[j]]; 441 lu->val[nz++] = *bv++; 442 } 443 } 444 lu->row[m] = nz; 445 446 if (lu->options.Fact == DOFACT) { 447 #if defined(PETSC_USE_COMPLEX) 448 PetscStackCall("SuperLU_DIST:zCreate_CompRowLoc_Matrix_dist",zCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart,lu->val, lu->col, lu->row, SLU_NR_loc, SLU_Z, SLU_GE)); 449 #else 450 PetscStackCall("SuperLU_DIST:dCreate_CompRowLoc_Matrix_dist",dCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart,lu->val, lu->col, lu->row, SLU_NR_loc, SLU_D, SLU_GE)); 451 #endif 452 } 453 } 454 455 /* Factor the matrix. */ 456 PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ 457 if (lu->MatInputMode == GLOBAL) { /* global mat input */ 458 #if defined(PETSC_USE_COMPLEX) 459 PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0,&lu->grid, &lu->LUstruct, berr, &stat, &sinfo)); 460 #else 461 PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0,&lu->grid, &lu->LUstruct, berr, &stat, &sinfo)); 462 #endif 463 } else { /* distributed mat input */ 464 #if defined(PETSC_USE_COMPLEX) 465 PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, m, 0, &lu->grid,&lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo)); 466 #else 467 PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, m, 0, &lu->grid,&lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo)); 468 #endif 469 } 470 471 if (sinfo > 0) { 472 if (A->erroriffailure) { 473 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot in row %D",sinfo); 474 } else { 475 if (sinfo <= lu->A_sup.ncol) { 476 F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 477 ierr = PetscInfo1(F,"U(i,i) is exactly zero, i= %D\n",sinfo);CHKERRQ(ierr); 478 } else if (sinfo > lu->A_sup.ncol) { 479 /* 480 number of bytes allocated when memory allocation 481 failure occurred, plus A->ncol. 482 */ 483 F->factorerrortype = MAT_FACTOR_OUTMEMORY; 484 ierr = PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);CHKERRQ(ierr); 485 } 486 } 487 } else if (sinfo < 0) { 488 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, argument in p*gssvx() had an illegal value", sinfo); 489 } 490 491 if (lu->MatInputMode == GLOBAL && size > 1) { 492 ierr = MatDestroy(&A_seq);CHKERRQ(ierr); 493 } 494 495 if (lu->options.PrintStat) { 496 PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 497 } 498 PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); 499 F->assembled = PETSC_TRUE; 500 F->preallocated = PETSC_TRUE; 501 lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */ 502 PetscFunctionReturn(0); 503 } 504 505 /* Note the Petsc r and c permutations are ignored */ 506 static PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 507 { 508 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data; 509 PetscInt M = A->rmap->N,N=A->cmap->N; 510 511 PetscFunctionBegin; 512 /* Initialize the SuperLU process grid. */ 513 PetscStackCall("SuperLU_DIST:superlu_gridinit",superlu_gridinit(lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid)); 514 515 /* Initialize ScalePermstruct and LUstruct. */ 516 PetscStackCall("SuperLU_DIST:ScalePermstructInit",ScalePermstructInit(M, N, &lu->ScalePermstruct)); 517 PetscStackCall("SuperLU_DIST:LUstructInit",LUstructInit(N, &lu->LUstruct)); 518 F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST; 519 F->ops->solve = MatSolve_SuperLU_DIST; 520 F->ops->matsolve = MatMatSolve_SuperLU_DIST; 521 F->ops->getinertia = NULL; 522 523 if (A->symmetric || A->hermitian) { 524 F->ops->getinertia = MatGetInertia_SuperLU_DIST; 525 } 526 lu->CleanUpSuperLU_Dist = PETSC_TRUE; 527 PetscFunctionReturn(0); 528 } 529 530 static PetscErrorCode MatCholeskyFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,const MatFactorInfo *info) 531 { 532 PetscErrorCode ierr; 533 534 PetscFunctionBegin; 535 if (!A->symmetric) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Input matrix must be symmetric\n"); 536 ierr = MatLUFactorSymbolic_SuperLU_DIST(F,A,r,r,info);CHKERRQ(ierr); 537 F->ops->choleskyfactornumeric = MatLUFactorNumeric_SuperLU_DIST; 538 PetscFunctionReturn(0); 539 } 540 541 static PetscErrorCode MatFactorGetSolverType_aij_superlu_dist(Mat A,MatSolverType *type) 542 { 543 PetscFunctionBegin; 544 *type = MATSOLVERSUPERLU_DIST; 545 PetscFunctionReturn(0); 546 } 547 548 static PetscErrorCode MatView_Info_SuperLU_DIST(Mat A,PetscViewer viewer) 549 { 550 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->data; 551 superlu_dist_options_t options; 552 PetscErrorCode ierr; 553 554 PetscFunctionBegin; 555 /* check if matrix is superlu_dist type */ 556 if (A->ops->solve != MatSolve_SuperLU_DIST) PetscFunctionReturn(0); 557 558 options = lu->options; 559 ierr = PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");CHKERRQ(ierr); 560 ierr = PetscViewerASCIIPrintf(viewer," Process grid nprow %D x npcol %D \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 561 ierr = PetscViewerASCIIPrintf(viewer," Equilibrate matrix %s \n",PetscBools[options.Equil != NO]);CHKERRQ(ierr); 562 ierr = PetscViewerASCIIPrintf(viewer," Matrix input mode %d \n",lu->MatInputMode);CHKERRQ(ierr); 563 ierr = PetscViewerASCIIPrintf(viewer," Replace tiny pivots %s \n",PetscBools[options.ReplaceTinyPivot != NO]);CHKERRQ(ierr); 564 ierr = PetscViewerASCIIPrintf(viewer," Use iterative refinement %s \n",PetscBools[options.IterRefine == SLU_DOUBLE]);CHKERRQ(ierr); 565 ierr = PetscViewerASCIIPrintf(viewer," Processors in row %d col partition %d \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 566 567 switch (options.RowPerm) { 568 case NOROWPERM: 569 ierr = PetscViewerASCIIPrintf(viewer," Row permutation NOROWPERM\n");CHKERRQ(ierr); 570 break; 571 case LargeDiag_MC64: 572 ierr = PetscViewerASCIIPrintf(viewer," Row permutation LargeDiag_MC64\n");CHKERRQ(ierr); 573 break; 574 case LargeDiag_AWPM: 575 ierr = PetscViewerASCIIPrintf(viewer," Row permutation LargeDiag_AWPM\n");CHKERRQ(ierr); 576 break; 577 case MY_PERMR: 578 ierr = PetscViewerASCIIPrintf(viewer," Row permutation MY_PERMR\n");CHKERRQ(ierr); 579 break; 580 default: 581 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 582 } 583 584 switch (options.ColPerm) { 585 case NATURAL: 586 ierr = PetscViewerASCIIPrintf(viewer," Column permutation NATURAL\n");CHKERRQ(ierr); 587 break; 588 case MMD_AT_PLUS_A: 589 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_AT_PLUS_A\n");CHKERRQ(ierr); 590 break; 591 case MMD_ATA: 592 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_ATA\n");CHKERRQ(ierr); 593 break; 594 case METIS_AT_PLUS_A: 595 ierr = PetscViewerASCIIPrintf(viewer," Column permutation METIS_AT_PLUS_A\n");CHKERRQ(ierr); 596 break; 597 case PARMETIS: 598 ierr = PetscViewerASCIIPrintf(viewer," Column permutation PARMETIS\n");CHKERRQ(ierr); 599 break; 600 default: 601 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 602 } 603 604 ierr = PetscViewerASCIIPrintf(viewer," Parallel symbolic factorization %s \n",PetscBools[options.ParSymbFact != NO]);CHKERRQ(ierr); 605 606 if (lu->FactPattern == SamePattern) { 607 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern\n");CHKERRQ(ierr); 608 } else if (lu->FactPattern == SamePattern_SameRowPerm) { 609 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); 610 } else if (lu->FactPattern == DOFACT) { 611 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization DOFACT\n");CHKERRQ(ierr); 612 } else { 613 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown factorization pattern"); 614 } 615 PetscFunctionReturn(0); 616 } 617 618 static PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer) 619 { 620 PetscErrorCode ierr; 621 PetscBool iascii; 622 PetscViewerFormat format; 623 624 PetscFunctionBegin; 625 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 626 if (iascii) { 627 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 628 if (format == PETSC_VIEWER_ASCII_INFO) { 629 ierr = MatView_Info_SuperLU_DIST(A,viewer);CHKERRQ(ierr); 630 } 631 } 632 PetscFunctionReturn(0); 633 } 634 635 static PetscErrorCode MatGetFactor_aij_superlu_dist(Mat A,MatFactorType ftype,Mat *F) 636 { 637 Mat B; 638 Mat_SuperLU_DIST *lu; 639 PetscErrorCode ierr; 640 PetscInt M=A->rmap->N,N=A->cmap->N,indx; 641 PetscMPIInt size; 642 superlu_dist_options_t options; 643 PetscBool flg; 644 const char *colperm[] = {"NATURAL","MMD_AT_PLUS_A","MMD_ATA","METIS_AT_PLUS_A","PARMETIS"}; 645 const char *rowperm[] = {"NOROWPERM","LargeDiag_MC64","LargeDiag_AWPM","MY_PERMR"}; 646 const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm","DOFACT"}; 647 PetscBool set; 648 649 PetscFunctionBegin; 650 /* Create the factorization matrix */ 651 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 652 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,M,N);CHKERRQ(ierr); 653 ierr = PetscStrallocpy("superlu_dist",&((PetscObject)B)->type_name);CHKERRQ(ierr); 654 ierr = MatSetUp(B);CHKERRQ(ierr); 655 B->ops->getinfo = MatGetInfo_External; 656 B->ops->view = MatView_SuperLU_DIST; 657 B->ops->destroy = MatDestroy_SuperLU_DIST; 658 659 if (ftype == MAT_FACTOR_LU) { 660 B->factortype = MAT_FACTOR_LU; 661 B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 662 } else { 663 B->factortype = MAT_FACTOR_CHOLESKY; 664 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SuperLU_DIST; 665 } 666 667 /* set solvertype */ 668 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 669 ierr = PetscStrallocpy(MATSOLVERSUPERLU_DIST,&B->solvertype);CHKERRQ(ierr); 670 671 ierr = PetscNewLog(B,&lu);CHKERRQ(ierr); 672 B->data = lu; 673 674 /* Set the default input options: 675 options.Fact = DOFACT; 676 options.Equil = YES; 677 options.ParSymbFact = NO; 678 options.ColPerm = METIS_AT_PLUS_A; 679 options.RowPerm = LargeDiag_MC64; 680 options.ReplaceTinyPivot = YES; 681 options.IterRefine = DOUBLE; 682 options.Trans = NOTRANS; 683 options.SolveInitialized = NO; -hold the communication pattern used MatSolve() and MatMatSolve() 684 options.RefineInitialized = NO; 685 options.PrintStat = YES; 686 */ 687 set_default_options_dist(&options); 688 689 ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->comm_superlu));CHKERRQ(ierr); 690 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 691 /* Default num of process columns and rows */ 692 lu->nprow = (int_t) (0.5 + PetscSqrtReal((PetscReal)size)); 693 if (!lu->nprow) lu->nprow = 1; 694 while (lu->nprow > 0) { 695 lu->npcol = (int_t) (size/lu->nprow); 696 if (size == lu->nprow * lu->npcol) break; 697 lu->nprow--; 698 } 699 700 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr); 701 ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,(PetscInt*)&lu->nprow,NULL);CHKERRQ(ierr); 702 ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,(PetscInt*)&lu->npcol,NULL);CHKERRQ(ierr); 703 if (size != lu->nprow * lu->npcol) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol); 704 705 lu->MatInputMode = DISTRIBUTED; 706 707 ierr = PetscOptionsEnum("-mat_superlu_dist_matinput","Matrix input mode (global or distributed)","None",SuperLU_MatInputModes,(PetscEnum)lu->MatInputMode,(PetscEnum*)&lu->MatInputMode,NULL);CHKERRQ(ierr); 708 if (lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL; 709 710 ierr = PetscOptionsBool("-mat_superlu_dist_equil","Equilibrate matrix","None",options.Equil ? PETSC_TRUE : PETSC_FALSE,&flg,&set);CHKERRQ(ierr); 711 if (set && !flg) options.Equil = NO; 712 713 ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",rowperm,4,rowperm[1],&indx,&flg);CHKERRQ(ierr); 714 if (flg) { 715 switch (indx) { 716 case 0: 717 options.RowPerm = NOROWPERM; 718 break; 719 case 1: 720 options.RowPerm = LargeDiag_MC64; 721 break; 722 case 2: 723 options.RowPerm = LargeDiag_AWPM; 724 break; 725 case 3: 726 options.RowPerm = MY_PERMR; 727 break; 728 default: 729 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown row permutation"); 730 } 731 } 732 733 ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",colperm,5,colperm[3],&indx,&flg);CHKERRQ(ierr); 734 if (flg) { 735 switch (indx) { 736 case 0: 737 options.ColPerm = NATURAL; 738 break; 739 case 1: 740 options.ColPerm = MMD_AT_PLUS_A; 741 break; 742 case 2: 743 options.ColPerm = MMD_ATA; 744 break; 745 case 3: 746 options.ColPerm = METIS_AT_PLUS_A; 747 break; 748 case 4: 749 options.ColPerm = PARMETIS; /* only works for np>1 */ 750 break; 751 default: 752 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 753 } 754 } 755 756 options.ReplaceTinyPivot = NO; 757 ierr = PetscOptionsBool("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",options.ReplaceTinyPivot ? PETSC_TRUE : PETSC_FALSE,&flg,&set);CHKERRQ(ierr); 758 if (set && flg) options.ReplaceTinyPivot = YES; 759 760 options.ParSymbFact = NO; 761 ierr = PetscOptionsBool("-mat_superlu_dist_parsymbfact","Parallel symbolic factorization","None",PETSC_FALSE,&flg,&set);CHKERRQ(ierr); 762 if (set && flg && size>1) { 763 if (lu->MatInputMode == GLOBAL) { 764 #if defined(PETSC_USE_INFO) 765 ierr = PetscInfo(A,"Warning: '-mat_superlu_dist_parsymbfact' is ignored because MatInputMode=GLOBAL\n");CHKERRQ(ierr); 766 #endif 767 } else { 768 #if defined(PETSC_HAVE_PARMETIS) 769 options.ParSymbFact = YES; 770 options.ColPerm = PARMETIS; /* in v2.2, PARMETIS is forced for ParSymbFact regardless of user ordering setting */ 771 #else 772 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"parsymbfact needs PARMETIS"); 773 #endif 774 } 775 } 776 777 lu->FactPattern = SamePattern; 778 ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,3,factPattern[0],&indx,&flg);CHKERRQ(ierr); 779 if (flg) { 780 switch (indx) { 781 case 0: 782 lu->FactPattern = SamePattern; 783 break; 784 case 1: 785 lu->FactPattern = SamePattern_SameRowPerm; 786 break; 787 case 2: 788 lu->FactPattern = DOFACT; 789 break; 790 } 791 } 792 793 options.IterRefine = NOREFINE; 794 ierr = PetscOptionsBool("-mat_superlu_dist_iterrefine","Use iterative refinement","None",options.IterRefine == NOREFINE ? PETSC_FALSE : PETSC_TRUE ,&flg,&set);CHKERRQ(ierr); 795 if (set) { 796 if (flg) options.IterRefine = SLU_DOUBLE; 797 else options.IterRefine = NOREFINE; 798 } 799 800 if (PetscLogPrintInfo) options.PrintStat = YES; 801 else options.PrintStat = NO; 802 ierr = PetscOptionsBool("-mat_superlu_dist_statprint","Print factorization information","None",(PetscBool)options.PrintStat,(PetscBool*)&options.PrintStat,NULL);CHKERRQ(ierr); 803 ierr = PetscOptionsEnd();CHKERRQ(ierr); 804 805 lu->options = options; 806 lu->options.Fact = DOFACT; 807 lu->matsolve_iscalled = PETSC_FALSE; 808 lu->matmatsolve_iscalled = PETSC_FALSE; 809 810 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_aij_superlu_dist);CHKERRQ(ierr); 811 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSuperluDistGetDiagU_C",MatSuperluDistGetDiagU_SuperLU_DIST);CHKERRQ(ierr); 812 813 *F = B; 814 PetscFunctionReturn(0); 815 } 816 817 PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_SuperLU_DIST(void) 818 { 819 PetscErrorCode ierr; 820 PetscFunctionBegin; 821 ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); 822 ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); 823 ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ, MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); 824 ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ, MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); 825 PetscFunctionReturn(0); 826 } 827 828 /*MC 829 MATSOLVERSUPERLU_DIST - Parallel direct solver package for LU factorization 830 831 Use ./configure --download-superlu_dist --download-parmetis --download-metis --download-ptscotch to have PETSc installed with SuperLU_DIST 832 833 Use -pc_type lu -pc_factor_mat_solver_type superlu_dist to use this direct solver 834 835 Works with AIJ matrices 836 837 Options Database Keys: 838 + -mat_superlu_dist_r <n> - number of rows in processor partition 839 . -mat_superlu_dist_c <n> - number of columns in processor partition 840 . -mat_superlu_dist_matinput <0,1> - matrix input mode; 0=global, 1=distributed 841 . -mat_superlu_dist_equil - equilibrate the matrix 842 . -mat_superlu_dist_rowperm <NOROWPERM,LargeDiag_MC64,LargeDiag_AWPM,MY_PERMR> - row permutation 843 . -mat_superlu_dist_colperm <MMD_AT_PLUS_A,MMD_ATA,NATURAL> - column permutation 844 . -mat_superlu_dist_replacetinypivot - replace tiny pivots 845 . -mat_superlu_dist_fact <SamePattern> - (choose one of) SamePattern SamePattern_SameRowPerm DOFACT 846 . -mat_superlu_dist_iterrefine - use iterative refinement 847 - -mat_superlu_dist_statprint - print factorization information 848 849 Level: beginner 850 851 .seealso: PCLU 852 853 .seealso: PCFactorSetMatSolverType(), MatSolverType 854 855 M*/ 856