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