1 2 /* 3 Provides an interface to the MUMPS sparse solver 4 */ 5 6 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 7 #include <../src/mat/impls/sbaij/mpi/mpisbaij.h> 8 #include <petscblaslapack.h> 9 10 EXTERN_C_BEGIN 11 #if defined(PETSC_USE_COMPLEX) 12 #if defined(PETSC_USE_REAL_SINGLE) 13 #include <cmumps_c.h> 14 #else 15 #include <zmumps_c.h> 16 #endif 17 #else 18 #if defined(PETSC_USE_REAL_SINGLE) 19 #include <smumps_c.h> 20 #else 21 #include <dmumps_c.h> 22 #endif 23 #endif 24 EXTERN_C_END 25 #define JOB_INIT -1 26 #define JOB_FACTSYMBOLIC 1 27 #define JOB_FACTNUMERIC 2 28 #define JOB_SOLVE 3 29 #define JOB_END -2 30 31 /* calls to MUMPS */ 32 #if defined(PETSC_USE_COMPLEX) 33 #if defined(PETSC_USE_REAL_SINGLE) 34 #define PetscMUMPS_c cmumps_c 35 #else 36 #define PetscMUMPS_c zmumps_c 37 #endif 38 #else 39 #if defined(PETSC_USE_REAL_SINGLE) 40 #define PetscMUMPS_c smumps_c 41 #else 42 #define PetscMUMPS_c dmumps_c 43 #endif 44 #endif 45 46 /* declare MumpsScalar */ 47 #if defined(PETSC_USE_COMPLEX) 48 #if defined(PETSC_USE_REAL_SINGLE) 49 #define MumpsScalar mumps_complex 50 #else 51 #define MumpsScalar mumps_double_complex 52 #endif 53 #else 54 #define MumpsScalar PetscScalar 55 #endif 56 57 /* macros s.t. indices match MUMPS documentation */ 58 #define ICNTL(I) icntl[(I)-1] 59 #define CNTL(I) cntl[(I)-1] 60 #define INFOG(I) infog[(I)-1] 61 #define INFO(I) info[(I)-1] 62 #define RINFOG(I) rinfog[(I)-1] 63 #define RINFO(I) rinfo[(I)-1] 64 65 typedef struct { 66 #if defined(PETSC_USE_COMPLEX) 67 #if defined(PETSC_USE_REAL_SINGLE) 68 CMUMPS_STRUC_C id; 69 #else 70 ZMUMPS_STRUC_C id; 71 #endif 72 #else 73 #if defined(PETSC_USE_REAL_SINGLE) 74 SMUMPS_STRUC_C id; 75 #else 76 DMUMPS_STRUC_C id; 77 #endif 78 #endif 79 80 MatStructure matstruc; 81 PetscMPIInt myid,size; 82 PetscInt *irn,*jcn,nz,sym; 83 PetscScalar *val; 84 MPI_Comm comm_mumps; 85 PetscBool isAIJ; 86 PetscInt ICNTL9_pre; /* check if ICNTL(9) is changed from previous MatSolve */ 87 VecScatter scat_rhs, scat_sol; /* used by MatSolve() */ 88 Vec b_seq,x_seq; 89 PetscInt ninfo,*info; /* display INFO */ 90 PetscInt sizeredrhs; 91 PetscInt *schur_pivots; 92 PetscInt schur_B_lwork; 93 PetscScalar *schur_work; 94 PetscScalar *schur_sol; 95 PetscInt schur_sizesol; 96 PetscBool schur_factored; 97 PetscBool schur_inverted; 98 99 PetscErrorCode (*ConvertToTriples)(Mat, int, MatReuse, int*, int**, int**, PetscScalar**); 100 } Mat_MUMPS; 101 102 extern PetscErrorCode MatDuplicate_MUMPS(Mat,MatDuplicateOption,Mat*); 103 104 #undef __FUNCT__ 105 #define __FUNCT__ "MatMumpsResetSchur_Private" 106 static PetscErrorCode MatMumpsResetSchur_Private(Mat_MUMPS* mumps) 107 { 108 PetscErrorCode ierr; 109 110 PetscFunctionBegin; 111 ierr = PetscFree2(mumps->id.listvar_schur,mumps->id.schur);CHKERRQ(ierr); 112 ierr = PetscFree(mumps->id.redrhs);CHKERRQ(ierr); 113 ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); 114 ierr = PetscFree(mumps->schur_pivots);CHKERRQ(ierr); 115 ierr = PetscFree(mumps->schur_work);CHKERRQ(ierr); 116 mumps->id.size_schur = 0; 117 mumps->id.ICNTL(19) = 0; 118 PetscFunctionReturn(0); 119 } 120 121 #undef __FUNCT__ 122 #define __FUNCT__ "MatMumpsFactorSchur_Private" 123 static PetscErrorCode MatMumpsFactorSchur_Private(Mat_MUMPS* mumps) 124 { 125 PetscBLASInt B_N,B_ierr,B_slda; 126 PetscErrorCode ierr; 127 128 PetscFunctionBegin; 129 if (mumps->schur_factored) { 130 PetscFunctionReturn(0); 131 } 132 ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); 133 ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); 134 if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ 135 if (!mumps->schur_pivots) { 136 ierr = PetscMalloc1(B_N,&mumps->schur_pivots);CHKERRQ(ierr); 137 } 138 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 139 PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,&B_ierr)); 140 ierr = PetscFPTrapPop();CHKERRQ(ierr); 141 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr); 142 } else { /* either full or lower-triangular (not packed) */ 143 char ord[2]; 144 if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ 145 sprintf(ord,"L"); 146 } else { /* ICNTL(19) == 1 lower triangular stored by rows */ 147 sprintf(ord,"U"); 148 } 149 if (mumps->id.sym == 2) { 150 if (!mumps->schur_pivots) { 151 PetscScalar lwork; 152 153 ierr = PetscMalloc1(B_N,&mumps->schur_pivots);CHKERRQ(ierr); 154 mumps->schur_B_lwork=-1; 155 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 156 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,&lwork,&mumps->schur_B_lwork,&B_ierr)); 157 ierr = PetscFPTrapPop();CHKERRQ(ierr); 158 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to SYTRF Lapack routine %d",(int)B_ierr); 159 ierr = PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&mumps->schur_B_lwork);CHKERRQ(ierr); 160 ierr = PetscMalloc1(mumps->schur_B_lwork,&mumps->schur_work);CHKERRQ(ierr); 161 } 162 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 163 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,mumps->schur_work,&mumps->schur_B_lwork,&B_ierr)); 164 ierr = PetscFPTrapPop();CHKERRQ(ierr); 165 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr); 166 } else { 167 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 168 PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,&B_ierr)); 169 ierr = PetscFPTrapPop();CHKERRQ(ierr); 170 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr); 171 } 172 } 173 mumps->schur_factored = PETSC_TRUE; 174 PetscFunctionReturn(0); 175 } 176 177 #undef __FUNCT__ 178 #define __FUNCT__ "MatMumpsInvertSchur_Private" 179 static PetscErrorCode MatMumpsInvertSchur_Private(Mat_MUMPS* mumps) 180 { 181 PetscBLASInt B_N,B_ierr,B_slda; 182 PetscErrorCode ierr; 183 184 PetscFunctionBegin; 185 ierr = MatMumpsFactorSchur_Private(mumps);CHKERRQ(ierr); 186 ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); 187 ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); 188 if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ 189 if (!mumps->schur_work) { 190 PetscScalar lwork; 191 192 mumps->schur_B_lwork = -1; 193 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 194 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,&lwork,&mumps->schur_B_lwork,&B_ierr)); 195 ierr = PetscFPTrapPop();CHKERRQ(ierr); 196 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to GETRI Lapack routine %d",(int)B_ierr); 197 ierr = PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&mumps->schur_B_lwork);CHKERRQ(ierr); 198 ierr = PetscMalloc1(mumps->schur_B_lwork,&mumps->schur_work);CHKERRQ(ierr); 199 } 200 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 201 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,mumps->schur_work,&mumps->schur_B_lwork,&B_ierr)); 202 ierr = PetscFPTrapPop();CHKERRQ(ierr); 203 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr); 204 } else { /* either full or lower-triangular (not packed) */ 205 char ord[2]; 206 if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ 207 sprintf(ord,"L"); 208 } else { /* ICNTL(19) == 1 lower triangular stored by rows */ 209 sprintf(ord,"U"); 210 } 211 if (mumps->id.sym == 2) { 212 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 213 PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,mumps->schur_work,&B_ierr)); 214 ierr = PetscFPTrapPop();CHKERRQ(ierr); 215 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr); 216 } else { 217 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 218 PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_N,&B_ierr)); 219 ierr = PetscFPTrapPop();CHKERRQ(ierr); 220 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr); 221 } 222 } 223 mumps->schur_inverted = PETSC_TRUE; 224 PetscFunctionReturn(0); 225 } 226 227 #undef __FUNCT__ 228 #define __FUNCT__ "MatMumpsSolveSchur_Private" 229 static PetscErrorCode MatMumpsSolveSchur_Private(Mat_MUMPS* mumps, PetscBool sol_in_redrhs) 230 { 231 PetscBLASInt B_N,B_Nrhs,B_ierr,B_slda,B_rlda; 232 PetscScalar one=1.,zero=0.; 233 PetscErrorCode ierr; 234 235 PetscFunctionBegin; 236 ierr = MatMumpsFactorSchur_Private(mumps);CHKERRQ(ierr); 237 ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); 238 ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); 239 ierr = PetscBLASIntCast(mumps->id.nrhs,&B_Nrhs);CHKERRQ(ierr); 240 ierr = PetscBLASIntCast(mumps->id.lredrhs,&B_rlda);CHKERRQ(ierr); 241 if (mumps->schur_inverted) { 242 PetscInt sizesol = B_Nrhs*B_N; 243 if (!mumps->schur_sol || sizesol > mumps->schur_sizesol) { 244 ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); 245 ierr = PetscMalloc1(sizesol,&mumps->schur_sol);CHKERRQ(ierr); 246 mumps->schur_sizesol = sizesol; 247 } 248 if (!mumps->sym) { 249 char type[2]; 250 if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ 251 if (!mumps->id.ICNTL(9)) { /* transpose solve */ 252 sprintf(type,"N"); 253 } else { 254 sprintf(type,"T"); 255 } 256 } else { /* stored by columns */ 257 if (!mumps->id.ICNTL(9)) { /* transpose solve */ 258 sprintf(type,"T"); 259 } else { 260 sprintf(type,"N"); 261 } 262 } 263 PetscStackCallBLAS("BLASgemm",BLASgemm_(type,"N",&B_N,&B_Nrhs,&B_N,&one,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&zero,mumps->schur_sol,&B_rlda)); 264 } else { 265 char ord[2]; 266 if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ 267 sprintf(ord,"L"); 268 } else { /* ICNTL(19) == 1 lower triangular stored by rows */ 269 sprintf(ord,"U"); 270 } 271 PetscStackCallBLAS("BLASsymm",BLASsymm_("L",ord,&B_N,&B_Nrhs,&one,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&zero,mumps->schur_sol,&B_rlda)); 272 } 273 if (sol_in_redrhs) { 274 ierr = PetscMemcpy(mumps->id.redrhs,mumps->schur_sol,sizesol*sizeof(PetscScalar));CHKERRQ(ierr); 275 } 276 } else { /* Schur complement has not been inverted */ 277 MumpsScalar *orhs=NULL; 278 279 if (!sol_in_redrhs) { 280 PetscInt sizesol = B_Nrhs*B_N; 281 if (!mumps->schur_sol || sizesol > mumps->schur_sizesol) { 282 ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); 283 ierr = PetscMalloc1(sizesol,&mumps->schur_sol);CHKERRQ(ierr); 284 mumps->schur_sizesol = sizesol; 285 } 286 orhs = mumps->id.redrhs; 287 ierr = PetscMemcpy(mumps->schur_sol,mumps->id.redrhs,sizesol*sizeof(PetscScalar));CHKERRQ(ierr); 288 mumps->id.redrhs = (MumpsScalar*)mumps->schur_sol; 289 } 290 if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ 291 char type[2]; 292 if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ 293 if (!mumps->id.ICNTL(9)) { /* transpose solve */ 294 sprintf(type,"N"); 295 } else { 296 sprintf(type,"T"); 297 } 298 } else { /* stored by columns */ 299 if (!mumps->id.ICNTL(9)) { /* transpose solve */ 300 sprintf(type,"T"); 301 } else { 302 sprintf(type,"N"); 303 } 304 } 305 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 306 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_(type,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); 307 ierr = PetscFPTrapPop();CHKERRQ(ierr); 308 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRS Lapack routine %d",(int)B_ierr); 309 } else { /* either full or lower-triangular (not packed) */ 310 char ord[2]; 311 if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ 312 sprintf(ord,"L"); 313 } else { /* ICNTL(19) == 1 lower triangular stored by rows */ 314 sprintf(ord,"U"); 315 } 316 if (mumps->id.sym == 2) { 317 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 318 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_(ord,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); 319 ierr = PetscFPTrapPop();CHKERRQ(ierr); 320 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRS Lapack routine %d",(int)B_ierr); 321 } else { 322 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 323 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_(ord,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); 324 ierr = PetscFPTrapPop();CHKERRQ(ierr); 325 if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRS Lapack routine %d",(int)B_ierr); 326 } 327 } 328 if (!sol_in_redrhs) { 329 mumps->id.redrhs = orhs; 330 } 331 } 332 PetscFunctionReturn(0); 333 } 334 335 #undef __FUNCT__ 336 #define __FUNCT__ "MatMumpsHandleSchur_Private" 337 static PetscErrorCode MatMumpsHandleSchur_Private(Mat_MUMPS* mumps, PetscBool expansion) 338 { 339 PetscErrorCode ierr; 340 341 PetscFunctionBegin; 342 if (!mumps->id.ICNTL(19)) { /* do nothing when Schur complement has not been computed */ 343 PetscFunctionReturn(0); 344 } 345 if (!expansion) { /* prepare for the condensation step */ 346 PetscInt sizeredrhs = mumps->id.nrhs*mumps->id.size_schur; 347 /* allocate MUMPS internal array to store reduced right-hand sides */ 348 if (!mumps->id.redrhs || sizeredrhs > mumps->sizeredrhs) { 349 ierr = PetscFree(mumps->id.redrhs);CHKERRQ(ierr); 350 mumps->id.lredrhs = mumps->id.size_schur; 351 ierr = PetscMalloc1(mumps->id.nrhs*mumps->id.lredrhs,&mumps->id.redrhs);CHKERRQ(ierr); 352 mumps->sizeredrhs = mumps->id.nrhs*mumps->id.lredrhs; 353 } 354 mumps->id.ICNTL(26) = 1; /* condensation phase */ 355 } else { /* prepare for the expansion step */ 356 /* solve Schur complement (this has to be done by the MUMPS user, so basically us) */ 357 ierr = MatMumpsSolveSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); 358 mumps->id.ICNTL(26) = 2; /* expansion phase */ 359 PetscMUMPS_c(&mumps->id); 360 if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in solve phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); 361 /* restore defaults */ 362 mumps->id.ICNTL(26) = -1; 363 } 364 PetscFunctionReturn(0); 365 } 366 367 /* 368 MatConvertToTriples_A_B - convert Petsc matrix to triples: row[nz], col[nz], val[nz] 369 370 input: 371 A - matrix in aij,baij or sbaij (bs=1) format 372 shift - 0: C style output triple; 1: Fortran style output triple. 373 reuse - MAT_INITIAL_MATRIX: spaces are allocated and values are set for the triple 374 MAT_REUSE_MATRIX: only the values in v array are updated 375 output: 376 nnz - dim of r, c, and v (number of local nonzero entries of A) 377 r, c, v - row and col index, matrix values (matrix triples) 378 379 The returned values r, c, and sometimes v are obtained in a single PetscMalloc(). Then in MatDestroy_MUMPS() it is 380 freed with PetscFree((mumps->irn); This is not ideal code, the fact that v is ONLY sometimes part of mumps->irn means 381 that the PetscMalloc() cannot easily be replaced with a PetscMalloc3(). 382 383 */ 384 385 #undef __FUNCT__ 386 #define __FUNCT__ "MatConvertToTriples_seqaij_seqaij" 387 PetscErrorCode MatConvertToTriples_seqaij_seqaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 388 { 389 const PetscInt *ai,*aj,*ajj,M=A->rmap->n; 390 PetscInt nz,rnz,i,j; 391 PetscErrorCode ierr; 392 PetscInt *row,*col; 393 Mat_SeqAIJ *aa=(Mat_SeqAIJ*)A->data; 394 395 PetscFunctionBegin; 396 *v=aa->a; 397 if (reuse == MAT_INITIAL_MATRIX) { 398 nz = aa->nz; 399 ai = aa->i; 400 aj = aa->j; 401 *nnz = nz; 402 ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); 403 col = row + nz; 404 405 nz = 0; 406 for (i=0; i<M; i++) { 407 rnz = ai[i+1] - ai[i]; 408 ajj = aj + ai[i]; 409 for (j=0; j<rnz; j++) { 410 row[nz] = i+shift; col[nz++] = ajj[j] + shift; 411 } 412 } 413 *r = row; *c = col; 414 } 415 PetscFunctionReturn(0); 416 } 417 418 #undef __FUNCT__ 419 #define __FUNCT__ "MatConvertToTriples_seqbaij_seqaij" 420 PetscErrorCode MatConvertToTriples_seqbaij_seqaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 421 { 422 Mat_SeqBAIJ *aa=(Mat_SeqBAIJ*)A->data; 423 const PetscInt *ai,*aj,*ajj,bs2 = aa->bs2; 424 PetscInt bs,M,nz,idx=0,rnz,i,j,k,m; 425 PetscErrorCode ierr; 426 PetscInt *row,*col; 427 428 PetscFunctionBegin; 429 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 430 M = A->rmap->N/bs; 431 *v = aa->a; 432 if (reuse == MAT_INITIAL_MATRIX) { 433 ai = aa->i; aj = aa->j; 434 nz = bs2*aa->nz; 435 *nnz = nz; 436 ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); 437 col = row + nz; 438 439 for (i=0; i<M; i++) { 440 ajj = aj + ai[i]; 441 rnz = ai[i+1] - ai[i]; 442 for (k=0; k<rnz; k++) { 443 for (j=0; j<bs; j++) { 444 for (m=0; m<bs; m++) { 445 row[idx] = i*bs + m + shift; 446 col[idx++] = bs*(ajj[k]) + j + shift; 447 } 448 } 449 } 450 } 451 *r = row; *c = col; 452 } 453 PetscFunctionReturn(0); 454 } 455 456 #undef __FUNCT__ 457 #define __FUNCT__ "MatConvertToTriples_seqsbaij_seqsbaij" 458 PetscErrorCode MatConvertToTriples_seqsbaij_seqsbaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 459 { 460 const PetscInt *ai, *aj,*ajj,M=A->rmap->n; 461 PetscInt nz,rnz,i,j; 462 PetscErrorCode ierr; 463 PetscInt *row,*col; 464 Mat_SeqSBAIJ *aa=(Mat_SeqSBAIJ*)A->data; 465 466 PetscFunctionBegin; 467 *v = aa->a; 468 if (reuse == MAT_INITIAL_MATRIX) { 469 nz = aa->nz; 470 ai = aa->i; 471 aj = aa->j; 472 *v = aa->a; 473 *nnz = nz; 474 ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); 475 col = row + nz; 476 477 nz = 0; 478 for (i=0; i<M; i++) { 479 rnz = ai[i+1] - ai[i]; 480 ajj = aj + ai[i]; 481 for (j=0; j<rnz; j++) { 482 row[nz] = i+shift; col[nz++] = ajj[j] + shift; 483 } 484 } 485 *r = row; *c = col; 486 } 487 PetscFunctionReturn(0); 488 } 489 490 #undef __FUNCT__ 491 #define __FUNCT__ "MatConvertToTriples_seqaij_seqsbaij" 492 PetscErrorCode MatConvertToTriples_seqaij_seqsbaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 493 { 494 const PetscInt *ai,*aj,*ajj,*adiag,M=A->rmap->n; 495 PetscInt nz,rnz,i,j; 496 const PetscScalar *av,*v1; 497 PetscScalar *val; 498 PetscErrorCode ierr; 499 PetscInt *row,*col; 500 Mat_SeqAIJ *aa=(Mat_SeqAIJ*)A->data; 501 PetscBool missing; 502 503 PetscFunctionBegin; 504 ai =aa->i; aj=aa->j;av=aa->a; 505 adiag=aa->diag; 506 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&i);CHKERRQ(ierr); 507 if (reuse == MAT_INITIAL_MATRIX) { 508 /* count nz in the uppper triangular part of A */ 509 nz = 0; 510 if (missing) { 511 for (i=0; i<M; i++) { 512 if (PetscUnlikely(adiag[i] >= ai[i+1])) { 513 for (j=ai[i];j<ai[i+1];j++) { 514 if (aj[j] < i) continue; 515 nz++; 516 } 517 } else { 518 nz += ai[i+1] - adiag[i]; 519 } 520 } 521 } else { 522 for (i=0; i<M; i++) nz += ai[i+1] - adiag[i]; 523 } 524 *nnz = nz; 525 526 ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); 527 col = row + nz; 528 val = (PetscScalar*)(col + nz); 529 530 nz = 0; 531 if (missing) { 532 for (i=0; i<M; i++) { 533 if (PetscUnlikely(adiag[i] >= ai[i+1])) { 534 for (j=ai[i];j<ai[i+1];j++) { 535 if (aj[j] < i) continue; 536 row[nz] = i+shift; 537 col[nz] = aj[j]+shift; 538 val[nz] = av[j]; 539 nz++; 540 } 541 } else { 542 rnz = ai[i+1] - adiag[i]; 543 ajj = aj + adiag[i]; 544 v1 = av + adiag[i]; 545 for (j=0; j<rnz; j++) { 546 row[nz] = i+shift; col[nz] = ajj[j] + shift; val[nz++] = v1[j]; 547 } 548 } 549 } 550 } else { 551 for (i=0; i<M; i++) { 552 rnz = ai[i+1] - adiag[i]; 553 ajj = aj + adiag[i]; 554 v1 = av + adiag[i]; 555 for (j=0; j<rnz; j++) { 556 row[nz] = i+shift; col[nz] = ajj[j] + shift; val[nz++] = v1[j]; 557 } 558 } 559 } 560 *r = row; *c = col; *v = val; 561 } else { 562 nz = 0; val = *v; 563 if (missing) { 564 for (i=0; i <M; i++) { 565 if (PetscUnlikely(adiag[i] >= ai[i+1])) { 566 for (j=ai[i];j<ai[i+1];j++) { 567 if (aj[j] < i) continue; 568 val[nz++] = av[j]; 569 } 570 } else { 571 rnz = ai[i+1] - adiag[i]; 572 v1 = av + adiag[i]; 573 for (j=0; j<rnz; j++) { 574 val[nz++] = v1[j]; 575 } 576 } 577 } 578 } else { 579 for (i=0; i <M; i++) { 580 rnz = ai[i+1] - adiag[i]; 581 v1 = av + adiag[i]; 582 for (j=0; j<rnz; j++) { 583 val[nz++] = v1[j]; 584 } 585 } 586 } 587 } 588 PetscFunctionReturn(0); 589 } 590 591 #undef __FUNCT__ 592 #define __FUNCT__ "MatConvertToTriples_mpisbaij_mpisbaij" 593 PetscErrorCode MatConvertToTriples_mpisbaij_mpisbaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 594 { 595 const PetscInt *ai, *aj, *bi, *bj,*garray,m=A->rmap->n,*ajj,*bjj; 596 PetscErrorCode ierr; 597 PetscInt rstart,nz,i,j,jj,irow,countA,countB; 598 PetscInt *row,*col; 599 const PetscScalar *av, *bv,*v1,*v2; 600 PetscScalar *val; 601 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)A->data; 602 Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)(mat->A)->data; 603 Mat_SeqBAIJ *bb = (Mat_SeqBAIJ*)(mat->B)->data; 604 605 PetscFunctionBegin; 606 ai=aa->i; aj=aa->j; bi=bb->i; bj=bb->j; rstart= A->rmap->rstart; 607 av=aa->a; bv=bb->a; 608 609 garray = mat->garray; 610 611 if (reuse == MAT_INITIAL_MATRIX) { 612 nz = aa->nz + bb->nz; 613 *nnz = nz; 614 ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); 615 col = row + nz; 616 val = (PetscScalar*)(col + nz); 617 618 *r = row; *c = col; *v = val; 619 } else { 620 row = *r; col = *c; val = *v; 621 } 622 623 jj = 0; irow = rstart; 624 for (i=0; i<m; i++) { 625 ajj = aj + ai[i]; /* ptr to the beginning of this row */ 626 countA = ai[i+1] - ai[i]; 627 countB = bi[i+1] - bi[i]; 628 bjj = bj + bi[i]; 629 v1 = av + ai[i]; 630 v2 = bv + bi[i]; 631 632 /* A-part */ 633 for (j=0; j<countA; j++) { 634 if (reuse == MAT_INITIAL_MATRIX) { 635 row[jj] = irow + shift; col[jj] = rstart + ajj[j] + shift; 636 } 637 val[jj++] = v1[j]; 638 } 639 640 /* B-part */ 641 for (j=0; j < countB; j++) { 642 if (reuse == MAT_INITIAL_MATRIX) { 643 row[jj] = irow + shift; col[jj] = garray[bjj[j]] + shift; 644 } 645 val[jj++] = v2[j]; 646 } 647 irow++; 648 } 649 PetscFunctionReturn(0); 650 } 651 652 #undef __FUNCT__ 653 #define __FUNCT__ "MatConvertToTriples_mpiaij_mpiaij" 654 PetscErrorCode MatConvertToTriples_mpiaij_mpiaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 655 { 656 const PetscInt *ai, *aj, *bi, *bj,*garray,m=A->rmap->n,*ajj,*bjj; 657 PetscErrorCode ierr; 658 PetscInt rstart,nz,i,j,jj,irow,countA,countB; 659 PetscInt *row,*col; 660 const PetscScalar *av, *bv,*v1,*v2; 661 PetscScalar *val; 662 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 663 Mat_SeqAIJ *aa = (Mat_SeqAIJ*)(mat->A)->data; 664 Mat_SeqAIJ *bb = (Mat_SeqAIJ*)(mat->B)->data; 665 666 PetscFunctionBegin; 667 ai=aa->i; aj=aa->j; bi=bb->i; bj=bb->j; rstart= A->rmap->rstart; 668 av=aa->a; bv=bb->a; 669 670 garray = mat->garray; 671 672 if (reuse == MAT_INITIAL_MATRIX) { 673 nz = aa->nz + bb->nz; 674 *nnz = nz; 675 ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); 676 col = row + nz; 677 val = (PetscScalar*)(col + nz); 678 679 *r = row; *c = col; *v = val; 680 } else { 681 row = *r; col = *c; val = *v; 682 } 683 684 jj = 0; irow = rstart; 685 for (i=0; i<m; i++) { 686 ajj = aj + ai[i]; /* ptr to the beginning of this row */ 687 countA = ai[i+1] - ai[i]; 688 countB = bi[i+1] - bi[i]; 689 bjj = bj + bi[i]; 690 v1 = av + ai[i]; 691 v2 = bv + bi[i]; 692 693 /* A-part */ 694 for (j=0; j<countA; j++) { 695 if (reuse == MAT_INITIAL_MATRIX) { 696 row[jj] = irow + shift; col[jj] = rstart + ajj[j] + shift; 697 } 698 val[jj++] = v1[j]; 699 } 700 701 /* B-part */ 702 for (j=0; j < countB; j++) { 703 if (reuse == MAT_INITIAL_MATRIX) { 704 row[jj] = irow + shift; col[jj] = garray[bjj[j]] + shift; 705 } 706 val[jj++] = v2[j]; 707 } 708 irow++; 709 } 710 PetscFunctionReturn(0); 711 } 712 713 #undef __FUNCT__ 714 #define __FUNCT__ "MatConvertToTriples_mpibaij_mpiaij" 715 PetscErrorCode MatConvertToTriples_mpibaij_mpiaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 716 { 717 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)A->data; 718 Mat_SeqBAIJ *aa = (Mat_SeqBAIJ*)(mat->A)->data; 719 Mat_SeqBAIJ *bb = (Mat_SeqBAIJ*)(mat->B)->data; 720 const PetscInt *ai = aa->i, *bi = bb->i, *aj = aa->j, *bj = bb->j,*ajj, *bjj; 721 const PetscInt *garray = mat->garray,mbs=mat->mbs,rstart=A->rmap->rstart; 722 const PetscInt bs2=mat->bs2; 723 PetscErrorCode ierr; 724 PetscInt bs,nz,i,j,k,n,jj,irow,countA,countB,idx; 725 PetscInt *row,*col; 726 const PetscScalar *av=aa->a, *bv=bb->a,*v1,*v2; 727 PetscScalar *val; 728 729 PetscFunctionBegin; 730 ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); 731 if (reuse == MAT_INITIAL_MATRIX) { 732 nz = bs2*(aa->nz + bb->nz); 733 *nnz = nz; 734 ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); 735 col = row + nz; 736 val = (PetscScalar*)(col + nz); 737 738 *r = row; *c = col; *v = val; 739 } else { 740 row = *r; col = *c; val = *v; 741 } 742 743 jj = 0; irow = rstart; 744 for (i=0; i<mbs; i++) { 745 countA = ai[i+1] - ai[i]; 746 countB = bi[i+1] - bi[i]; 747 ajj = aj + ai[i]; 748 bjj = bj + bi[i]; 749 v1 = av + bs2*ai[i]; 750 v2 = bv + bs2*bi[i]; 751 752 idx = 0; 753 /* A-part */ 754 for (k=0; k<countA; k++) { 755 for (j=0; j<bs; j++) { 756 for (n=0; n<bs; n++) { 757 if (reuse == MAT_INITIAL_MATRIX) { 758 row[jj] = irow + n + shift; 759 col[jj] = rstart + bs*ajj[k] + j + shift; 760 } 761 val[jj++] = v1[idx++]; 762 } 763 } 764 } 765 766 idx = 0; 767 /* B-part */ 768 for (k=0; k<countB; k++) { 769 for (j=0; j<bs; j++) { 770 for (n=0; n<bs; n++) { 771 if (reuse == MAT_INITIAL_MATRIX) { 772 row[jj] = irow + n + shift; 773 col[jj] = bs*garray[bjj[k]] + j + shift; 774 } 775 val[jj++] = v2[idx++]; 776 } 777 } 778 } 779 irow += bs; 780 } 781 PetscFunctionReturn(0); 782 } 783 784 #undef __FUNCT__ 785 #define __FUNCT__ "MatConvertToTriples_mpiaij_mpisbaij" 786 PetscErrorCode MatConvertToTriples_mpiaij_mpisbaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) 787 { 788 const PetscInt *ai, *aj,*adiag, *bi, *bj,*garray,m=A->rmap->n,*ajj,*bjj; 789 PetscErrorCode ierr; 790 PetscInt rstart,nz,nza,nzb,i,j,jj,irow,countA,countB; 791 PetscInt *row,*col; 792 const PetscScalar *av, *bv,*v1,*v2; 793 PetscScalar *val; 794 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 795 Mat_SeqAIJ *aa =(Mat_SeqAIJ*)(mat->A)->data; 796 Mat_SeqAIJ *bb =(Mat_SeqAIJ*)(mat->B)->data; 797 798 PetscFunctionBegin; 799 ai=aa->i; aj=aa->j; adiag=aa->diag; 800 bi=bb->i; bj=bb->j; garray = mat->garray; 801 av=aa->a; bv=bb->a; 802 803 rstart = A->rmap->rstart; 804 805 if (reuse == MAT_INITIAL_MATRIX) { 806 nza = 0; /* num of upper triangular entries in mat->A, including diagonals */ 807 nzb = 0; /* num of upper triangular entries in mat->B */ 808 for (i=0; i<m; i++) { 809 nza += (ai[i+1] - adiag[i]); 810 countB = bi[i+1] - bi[i]; 811 bjj = bj + bi[i]; 812 for (j=0; j<countB; j++) { 813 if (garray[bjj[j]] > rstart) nzb++; 814 } 815 } 816 817 nz = nza + nzb; /* total nz of upper triangular part of mat */ 818 *nnz = nz; 819 ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); 820 col = row + nz; 821 val = (PetscScalar*)(col + nz); 822 823 *r = row; *c = col; *v = val; 824 } else { 825 row = *r; col = *c; val = *v; 826 } 827 828 jj = 0; irow = rstart; 829 for (i=0; i<m; i++) { 830 ajj = aj + adiag[i]; /* ptr to the beginning of the diagonal of this row */ 831 v1 = av + adiag[i]; 832 countA = ai[i+1] - adiag[i]; 833 countB = bi[i+1] - bi[i]; 834 bjj = bj + bi[i]; 835 v2 = bv + bi[i]; 836 837 /* A-part */ 838 for (j=0; j<countA; j++) { 839 if (reuse == MAT_INITIAL_MATRIX) { 840 row[jj] = irow + shift; col[jj] = rstart + ajj[j] + shift; 841 } 842 val[jj++] = v1[j]; 843 } 844 845 /* B-part */ 846 for (j=0; j < countB; j++) { 847 if (garray[bjj[j]] > rstart) { 848 if (reuse == MAT_INITIAL_MATRIX) { 849 row[jj] = irow + shift; col[jj] = garray[bjj[j]] + shift; 850 } 851 val[jj++] = v2[j]; 852 } 853 } 854 irow++; 855 } 856 PetscFunctionReturn(0); 857 } 858 859 #undef __FUNCT__ 860 #define __FUNCT__ "MatDestroy_MUMPS" 861 PetscErrorCode MatDestroy_MUMPS(Mat A) 862 { 863 Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 864 PetscErrorCode ierr; 865 866 PetscFunctionBegin; 867 ierr = PetscFree2(mumps->id.sol_loc,mumps->id.isol_loc);CHKERRQ(ierr); 868 ierr = VecScatterDestroy(&mumps->scat_rhs);CHKERRQ(ierr); 869 ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); 870 ierr = VecDestroy(&mumps->b_seq);CHKERRQ(ierr); 871 ierr = VecDestroy(&mumps->x_seq);CHKERRQ(ierr); 872 ierr = PetscFree(mumps->id.perm_in);CHKERRQ(ierr); 873 ierr = PetscFree(mumps->irn);CHKERRQ(ierr); 874 ierr = PetscFree(mumps->info);CHKERRQ(ierr); 875 ierr = MatMumpsResetSchur_Private(mumps);CHKERRQ(ierr); 876 mumps->id.job = JOB_END; 877 PetscMUMPS_c(&mumps->id); 878 ierr = MPI_Comm_free(&mumps->comm_mumps);CHKERRQ(ierr); 879 ierr = PetscFree(A->data);CHKERRQ(ierr); 880 881 /* clear composed functions */ 882 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr); 883 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); 884 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorInvertSchurComplement_C",NULL);CHKERRQ(ierr); 885 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorCreateSchurComplement_C",NULL);CHKERRQ(ierr); 886 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSchurComplement_C",NULL);CHKERRQ(ierr); 887 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplement_C",NULL);CHKERRQ(ierr); 888 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplementTranspose_C",NULL);CHKERRQ(ierr); 889 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetIcntl_C",NULL);CHKERRQ(ierr); 890 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetIcntl_C",NULL);CHKERRQ(ierr); 891 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetCntl_C",NULL);CHKERRQ(ierr); 892 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetCntl_C",NULL);CHKERRQ(ierr); 893 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetInfo_C",NULL);CHKERRQ(ierr); 894 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetInfog_C",NULL);CHKERRQ(ierr); 895 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetRinfo_C",NULL);CHKERRQ(ierr); 896 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetRinfog_C",NULL);CHKERRQ(ierr); 897 PetscFunctionReturn(0); 898 } 899 900 #undef __FUNCT__ 901 #define __FUNCT__ "MatSolve_MUMPS" 902 PetscErrorCode MatSolve_MUMPS(Mat A,Vec b,Vec x) 903 { 904 Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 905 PetscScalar *array; 906 Vec b_seq; 907 IS is_iden,is_petsc; 908 PetscErrorCode ierr; 909 PetscInt i; 910 PetscBool second_solve = PETSC_FALSE; 911 static PetscBool cite1 = PETSC_FALSE,cite2 = PETSC_FALSE; 912 913 PetscFunctionBegin; 914 ierr = PetscCitationsRegister("@article{MUMPS01,\n author = {P.~R. Amestoy and I.~S. Duff and J.-Y. L'Excellent and J. Koster},\n title = {A fully asynchronous multifrontal solver using distributed dynamic scheduling},\n journal = {SIAM Journal on Matrix Analysis and Applications},\n volume = {23},\n number = {1},\n pages = {15--41},\n year = {2001}\n}\n",&cite1);CHKERRQ(ierr); 915 ierr = PetscCitationsRegister("@article{MUMPS02,\n author = {P.~R. Amestoy and A. Guermouche and J.-Y. L'Excellent and S. Pralet},\n title = {Hybrid scheduling for the parallel solution of linear systems},\n journal = {Parallel Computing},\n volume = {32},\n number = {2},\n pages = {136--156},\n year = {2006}\n}\n",&cite2);CHKERRQ(ierr); 916 917 if (A->factorerrortype) { 918 ierr = PetscInfo2(A,"MatSolve is called with singular matrix factor, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 919 ierr = VecSetInf(x);CHKERRQ(ierr); 920 PetscFunctionReturn(0); 921 } 922 923 mumps->id.nrhs = 1; 924 b_seq = mumps->b_seq; 925 if (mumps->size > 1) { 926 /* MUMPS only supports centralized rhs. Scatter b into a seqential rhs vector */ 927 ierr = VecScatterBegin(mumps->scat_rhs,b,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 928 ierr = VecScatterEnd(mumps->scat_rhs,b,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 929 if (!mumps->myid) {ierr = VecGetArray(b_seq,&array);CHKERRQ(ierr);} 930 } else { /* size == 1 */ 931 ierr = VecCopy(b,x);CHKERRQ(ierr); 932 ierr = VecGetArray(x,&array);CHKERRQ(ierr); 933 } 934 if (!mumps->myid) { /* define rhs on the host */ 935 mumps->id.nrhs = 1; 936 mumps->id.rhs = (MumpsScalar*)array; 937 } 938 939 /* 940 handle condensation step of Schur complement (if any) 941 We set by default ICNTL(26) == -1 when Schur indices have been provided by the user. 942 According to MUMPS (5.0.0) manual, any value should be harmful during the factorization phase 943 Unless the user provides a valid value for ICNTL(26), MatSolve and MatMatSolve routines solve the full system. 944 This requires an extra call to PetscMUMPS_c and the computation of the factors for S 945 */ 946 if (mumps->id.ICNTL(26) < 0 || mumps->id.ICNTL(26) > 2) { 947 second_solve = PETSC_TRUE; 948 ierr = MatMumpsHandleSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); 949 } 950 /* solve phase */ 951 /*-------------*/ 952 mumps->id.job = JOB_SOLVE; 953 PetscMUMPS_c(&mumps->id); 954 if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in solve phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); 955 956 /* handle expansion step of Schur complement (if any) */ 957 if (second_solve) { 958 ierr = MatMumpsHandleSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); 959 } 960 961 if (mumps->size > 1) { /* convert mumps distributed solution to petsc mpi x */ 962 if (mumps->scat_sol && mumps->ICNTL9_pre != mumps->id.ICNTL(9)) { 963 /* when id.ICNTL(9) changes, the contents of lsol_loc may change (not its size, lsol_loc), recreates scat_sol */ 964 ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); 965 } 966 if (!mumps->scat_sol) { /* create scatter scat_sol */ 967 ierr = ISCreateStride(PETSC_COMM_SELF,mumps->id.lsol_loc,0,1,&is_iden);CHKERRQ(ierr); /* from */ 968 for (i=0; i<mumps->id.lsol_loc; i++) { 969 mumps->id.isol_loc[i] -= 1; /* change Fortran style to C style */ 970 } 971 ierr = ISCreateGeneral(PETSC_COMM_SELF,mumps->id.lsol_loc,mumps->id.isol_loc,PETSC_COPY_VALUES,&is_petsc);CHKERRQ(ierr); /* to */ 972 ierr = VecScatterCreate(mumps->x_seq,is_iden,x,is_petsc,&mumps->scat_sol);CHKERRQ(ierr); 973 ierr = ISDestroy(&is_iden);CHKERRQ(ierr); 974 ierr = ISDestroy(&is_petsc);CHKERRQ(ierr); 975 976 mumps->ICNTL9_pre = mumps->id.ICNTL(9); /* save current value of id.ICNTL(9) */ 977 } 978 979 ierr = VecScatterBegin(mumps->scat_sol,mumps->x_seq,x,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 980 ierr = VecScatterEnd(mumps->scat_sol,mumps->x_seq,x,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 981 } 982 PetscFunctionReturn(0); 983 } 984 985 #undef __FUNCT__ 986 #define __FUNCT__ "MatSolveTranspose_MUMPS" 987 PetscErrorCode MatSolveTranspose_MUMPS(Mat A,Vec b,Vec x) 988 { 989 Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 990 PetscErrorCode ierr; 991 992 PetscFunctionBegin; 993 mumps->id.ICNTL(9) = 0; 994 ierr = MatSolve_MUMPS(A,b,x);CHKERRQ(ierr); 995 mumps->id.ICNTL(9) = 1; 996 PetscFunctionReturn(0); 997 } 998 999 #undef __FUNCT__ 1000 #define __FUNCT__ "MatMatSolve_MUMPS" 1001 PetscErrorCode MatMatSolve_MUMPS(Mat A,Mat B,Mat X) 1002 { 1003 PetscErrorCode ierr; 1004 PetscBool flg; 1005 Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 1006 PetscInt i,nrhs,M; 1007 PetscScalar *array,*bray; 1008 1009 PetscFunctionBegin; 1010 ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 1011 if (!flg) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 1012 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 1013 if (!flg) SETERRQ(PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 1014 if (B->rmap->n != X->rmap->n) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_WRONG,"Matrix B and X must have same row distribution"); 1015 1016 ierr = MatGetSize(B,&M,&nrhs);CHKERRQ(ierr); 1017 mumps->id.nrhs = nrhs; 1018 mumps->id.lrhs = M; 1019 1020 if (mumps->size == 1) { 1021 /* copy B to X */ 1022 ierr = MatDenseGetArray(B,&bray);CHKERRQ(ierr); 1023 ierr = MatDenseGetArray(X,&array);CHKERRQ(ierr); 1024 ierr = PetscMemcpy(array,bray,M*nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 1025 ierr = MatDenseRestoreArray(B,&bray);CHKERRQ(ierr); 1026 mumps->id.rhs = (MumpsScalar*)array; 1027 /* handle condensation step of Schur complement (if any) */ 1028 ierr = MatMumpsHandleSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); 1029 1030 /* solve phase */ 1031 /*-------------*/ 1032 mumps->id.job = JOB_SOLVE; 1033 PetscMUMPS_c(&mumps->id); 1034 if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in solve phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); 1035 1036 /* handle expansion step of Schur complement (if any) */ 1037 ierr = MatMumpsHandleSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); 1038 ierr = MatDenseRestoreArray(X,&array);CHKERRQ(ierr); 1039 } else { /*--------- parallel case --------*/ 1040 PetscInt lsol_loc,nlsol_loc,*isol_loc,*idx,*iidx,*idxx,*isol_loc_save; 1041 MumpsScalar *sol_loc,*sol_loc_save; 1042 IS is_to,is_from; 1043 PetscInt k,proc,j,m; 1044 const PetscInt *rstart; 1045 Vec v_mpi,b_seq,x_seq; 1046 VecScatter scat_rhs,scat_sol; 1047 1048 /* create x_seq to hold local solution */ 1049 isol_loc_save = mumps->id.isol_loc; /* save it for MatSovle() */ 1050 sol_loc_save = mumps->id.sol_loc; 1051 1052 lsol_loc = mumps->id.INFO(23); 1053 nlsol_loc = nrhs*lsol_loc; /* length of sol_loc */ 1054 ierr = PetscMalloc2(nlsol_loc,&sol_loc,nlsol_loc,&isol_loc);CHKERRQ(ierr); 1055 mumps->id.sol_loc = (MumpsScalar*)sol_loc; 1056 mumps->id.isol_loc = isol_loc; 1057 1058 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nlsol_loc,(PetscScalar*)sol_loc,&x_seq);CHKERRQ(ierr); 1059 1060 /* copy rhs matrix B into vector v_mpi */ 1061 ierr = MatGetLocalSize(B,&m,NULL);CHKERRQ(ierr); 1062 ierr = MatDenseGetArray(B,&bray);CHKERRQ(ierr); 1063 ierr = VecCreateMPIWithArray(PetscObjectComm((PetscObject)B),1,nrhs*m,nrhs*M,(const PetscScalar*)bray,&v_mpi);CHKERRQ(ierr); 1064 ierr = MatDenseRestoreArray(B,&bray);CHKERRQ(ierr); 1065 1066 /* scatter v_mpi to b_seq because MUMPS only supports centralized rhs */ 1067 /* idx: maps from k-th index of v_mpi to (i,j)-th global entry of B; 1068 iidx: inverse of idx, will be used by scattering xx_seq -> X */ 1069 ierr = PetscMalloc2(nrhs*M,&idx,nrhs*M,&iidx);CHKERRQ(ierr); 1070 ierr = MatGetOwnershipRanges(B,&rstart);CHKERRQ(ierr); 1071 k = 0; 1072 for (proc=0; proc<mumps->size; proc++){ 1073 for (j=0; j<nrhs; j++){ 1074 for (i=rstart[proc]; i<rstart[proc+1]; i++){ 1075 iidx[j*M + i] = k; 1076 idx[k++] = j*M + i; 1077 } 1078 } 1079 } 1080 1081 if (!mumps->myid) { 1082 ierr = VecCreateSeq(PETSC_COMM_SELF,nrhs*M,&b_seq);CHKERRQ(ierr); 1083 ierr = ISCreateGeneral(PETSC_COMM_SELF,nrhs*M,idx,PETSC_COPY_VALUES,&is_to);CHKERRQ(ierr); 1084 ierr = ISCreateStride(PETSC_COMM_SELF,nrhs*M,0,1,&is_from);CHKERRQ(ierr); 1085 } else { 1086 ierr = VecCreateSeq(PETSC_COMM_SELF,0,&b_seq);CHKERRQ(ierr); 1087 ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_to);CHKERRQ(ierr); 1088 ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_from);CHKERRQ(ierr); 1089 } 1090 ierr = VecScatterCreate(v_mpi,is_from,b_seq,is_to,&scat_rhs);CHKERRQ(ierr); 1091 ierr = VecScatterBegin(scat_rhs,v_mpi,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1092 ierr = ISDestroy(&is_to);CHKERRQ(ierr); 1093 ierr = ISDestroy(&is_from);CHKERRQ(ierr); 1094 ierr = VecScatterEnd(scat_rhs,v_mpi,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1095 1096 if (!mumps->myid) { /* define rhs on the host */ 1097 ierr = VecGetArray(b_seq,&bray);CHKERRQ(ierr); 1098 mumps->id.rhs = (MumpsScalar*)bray; 1099 ierr = VecRestoreArray(b_seq,&bray);CHKERRQ(ierr); 1100 } 1101 1102 /* solve phase */ 1103 /*-------------*/ 1104 mumps->id.job = JOB_SOLVE; 1105 PetscMUMPS_c(&mumps->id); 1106 if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in solve phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); 1107 1108 /* scatter mumps distributed solution to petsc vector v_mpi, which shares local arrays with solution matrix X */ 1109 ierr = MatDenseGetArray(X,&array);CHKERRQ(ierr); 1110 ierr = VecPlaceArray(v_mpi,array);CHKERRQ(ierr); 1111 1112 /* create scatter scat_sol */ 1113 ierr = PetscMalloc1(nlsol_loc,&idxx);CHKERRQ(ierr); 1114 ierr = ISCreateStride(PETSC_COMM_SELF,nlsol_loc,0,1,&is_from);CHKERRQ(ierr); 1115 for (i=0; i<lsol_loc; i++) { 1116 isol_loc[i] -= 1; /* change Fortran style to C style */ 1117 idxx[i] = iidx[isol_loc[i]]; 1118 for (j=1; j<nrhs; j++){ 1119 idxx[j*lsol_loc+i] = iidx[isol_loc[i]+j*M]; 1120 } 1121 } 1122 ierr = ISCreateGeneral(PETSC_COMM_SELF,nlsol_loc,idxx,PETSC_COPY_VALUES,&is_to);CHKERRQ(ierr); 1123 ierr = VecScatterCreate(x_seq,is_from,v_mpi,is_to,&scat_sol);CHKERRQ(ierr); 1124 ierr = VecScatterBegin(scat_sol,x_seq,v_mpi,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1125 ierr = ISDestroy(&is_from);CHKERRQ(ierr); 1126 ierr = ISDestroy(&is_to);CHKERRQ(ierr); 1127 ierr = VecScatterEnd(scat_sol,x_seq,v_mpi,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1128 ierr = MatDenseRestoreArray(X,&array);CHKERRQ(ierr); 1129 1130 /* free spaces */ 1131 mumps->id.sol_loc = sol_loc_save; 1132 mumps->id.isol_loc = isol_loc_save; 1133 1134 ierr = PetscFree2(sol_loc,isol_loc);CHKERRQ(ierr); 1135 ierr = PetscFree2(idx,iidx);CHKERRQ(ierr); 1136 ierr = PetscFree(idxx);CHKERRQ(ierr); 1137 ierr = VecDestroy(&x_seq);CHKERRQ(ierr); 1138 ierr = VecDestroy(&v_mpi);CHKERRQ(ierr); 1139 ierr = VecDestroy(&b_seq);CHKERRQ(ierr); 1140 ierr = VecScatterDestroy(&scat_rhs);CHKERRQ(ierr); 1141 ierr = VecScatterDestroy(&scat_sol);CHKERRQ(ierr); 1142 } 1143 PetscFunctionReturn(0); 1144 } 1145 1146 #if !defined(PETSC_USE_COMPLEX) 1147 /* 1148 input: 1149 F: numeric factor 1150 output: 1151 nneg: total number of negative pivots 1152 nzero: total number of zero pivots 1153 npos: (global dimension of F) - nneg - nzero 1154 */ 1155 #undef __FUNCT__ 1156 #define __FUNCT__ "MatGetInertia_SBAIJMUMPS" 1157 PetscErrorCode MatGetInertia_SBAIJMUMPS(Mat F,int *nneg,int *nzero,int *npos) 1158 { 1159 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1160 PetscErrorCode ierr; 1161 PetscMPIInt size; 1162 1163 PetscFunctionBegin; 1164 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&size);CHKERRQ(ierr); 1165 /* MUMPS 4.3.1 calls ScaLAPACK when ICNTL(13)=0 (default), which does not offer the possibility to compute the inertia of a dense matrix. Set ICNTL(13)=1 to skip ScaLAPACK */ 1166 if (size > 1 && mumps->id.ICNTL(13) != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"ICNTL(13)=%d. -mat_mumps_icntl_13 must be set as 1 for correct global matrix inertia\n",mumps->id.INFOG(13)); 1167 1168 if (nneg) *nneg = mumps->id.INFOG(12); 1169 if (nzero || npos) { 1170 if (mumps->id.ICNTL(24) != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"-mat_mumps_icntl_24 must be set as 1 for null pivot row detection"); 1171 if (nzero) *nzero = mumps->id.INFOG(28); 1172 if (npos) *npos = F->rmap->N - (mumps->id.INFOG(12) + mumps->id.INFOG(28)); 1173 } 1174 PetscFunctionReturn(0); 1175 } 1176 #endif 1177 1178 #undef __FUNCT__ 1179 #define __FUNCT__ "MatFactorNumeric_MUMPS" 1180 PetscErrorCode MatFactorNumeric_MUMPS(Mat F,Mat A,const MatFactorInfo *info) 1181 { 1182 Mat_MUMPS *mumps =(Mat_MUMPS*)(F)->data; 1183 PetscErrorCode ierr; 1184 PetscBool isMPIAIJ; 1185 1186 PetscFunctionBegin; 1187 if (mumps->id.INFOG(1) < 0) { 1188 if (mumps->id.INFOG(1) == -6) { 1189 ierr = PetscInfo2(A,"MatFactorNumeric is called with singular matrix structure, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1190 } 1191 ierr = PetscInfo2(A,"MatFactorNumeric is called after analysis phase fails, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1192 PetscFunctionReturn(0); 1193 } 1194 1195 ierr = (*mumps->ConvertToTriples)(A, 1, MAT_REUSE_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); 1196 1197 /* numerical factorization phase */ 1198 /*-------------------------------*/ 1199 mumps->id.job = JOB_FACTNUMERIC; 1200 if (!mumps->id.ICNTL(18)) { /* A is centralized */ 1201 if (!mumps->myid) { 1202 mumps->id.a = (MumpsScalar*)mumps->val; 1203 } 1204 } else { 1205 mumps->id.a_loc = (MumpsScalar*)mumps->val; 1206 } 1207 PetscMUMPS_c(&mumps->id); 1208 if (mumps->id.INFOG(1) < 0) { 1209 if (A->erroriffailure) { 1210 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2)); 1211 } else { 1212 if (mumps->id.INFOG(1) == -10) { /* numerically singular matrix */ 1213 ierr = PetscInfo2(F,"matrix is numerically singular, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1214 F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1215 } else if (mumps->id.INFOG(1) == -13) { 1216 ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, cannot allocate required memory %d megabytes\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1217 F->factorerrortype = MAT_FACTOR_OUTMEMORY; 1218 } else if (mumps->id.INFOG(1) == -8 || mumps->id.INFOG(1) == -9 || (-16 < mumps->id.INFOG(1) && mumps->id.INFOG(1) < -10) ) { 1219 ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d, problem with workarray \n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1220 F->factorerrortype = MAT_FACTOR_OUTMEMORY; 1221 } else { 1222 ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1223 F->factorerrortype = MAT_FACTOR_OTHER; 1224 } 1225 } 1226 } 1227 if (!mumps->myid && mumps->id.ICNTL(16) > 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB," mumps->id.ICNTL(16):=%d\n",mumps->id.INFOG(16)); 1228 1229 (F)->assembled = PETSC_TRUE; 1230 mumps->matstruc = SAME_NONZERO_PATTERN; 1231 mumps->schur_factored = PETSC_FALSE; 1232 mumps->schur_inverted = PETSC_FALSE; 1233 1234 /* just to be sure that ICNTL(19) value returned by a call from MatMumpsGetIcntl is always consistent */ 1235 if (!mumps->sym && mumps->id.ICNTL(19) && mumps->id.ICNTL(19) != 1) mumps->id.ICNTL(19) = 3; 1236 1237 if (mumps->size > 1) { 1238 PetscInt lsol_loc; 1239 PetscScalar *sol_loc; 1240 1241 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);CHKERRQ(ierr); 1242 1243 /* distributed solution; Create x_seq=sol_loc for repeated use */ 1244 if (mumps->x_seq) { 1245 ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); 1246 ierr = PetscFree2(mumps->id.sol_loc,mumps->id.isol_loc);CHKERRQ(ierr); 1247 ierr = VecDestroy(&mumps->x_seq);CHKERRQ(ierr); 1248 } 1249 lsol_loc = mumps->id.INFO(23); /* length of sol_loc */ 1250 ierr = PetscMalloc2(lsol_loc,&sol_loc,lsol_loc,&mumps->id.isol_loc);CHKERRQ(ierr); 1251 mumps->id.lsol_loc = lsol_loc; 1252 mumps->id.sol_loc = (MumpsScalar*)sol_loc; 1253 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,lsol_loc,sol_loc,&mumps->x_seq);CHKERRQ(ierr); 1254 } 1255 PetscFunctionReturn(0); 1256 } 1257 1258 /* Sets MUMPS options from the options database */ 1259 #undef __FUNCT__ 1260 #define __FUNCT__ "PetscSetMUMPSFromOptions" 1261 PetscErrorCode PetscSetMUMPSFromOptions(Mat F, Mat A) 1262 { 1263 Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 1264 PetscErrorCode ierr; 1265 PetscInt icntl,info[40],i,ninfo=40; 1266 PetscBool flg; 1267 1268 PetscFunctionBegin; 1269 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MUMPS Options","Mat");CHKERRQ(ierr); 1270 ierr = PetscOptionsInt("-mat_mumps_icntl_1","ICNTL(1): output stream for error messages","None",mumps->id.ICNTL(1),&icntl,&flg);CHKERRQ(ierr); 1271 if (flg) mumps->id.ICNTL(1) = icntl; 1272 ierr = PetscOptionsInt("-mat_mumps_icntl_2","ICNTL(2): output stream for diagnostic printing, statistics, and warning","None",mumps->id.ICNTL(2),&icntl,&flg);CHKERRQ(ierr); 1273 if (flg) mumps->id.ICNTL(2) = icntl; 1274 ierr = PetscOptionsInt("-mat_mumps_icntl_3","ICNTL(3): output stream for global information, collected on the host","None",mumps->id.ICNTL(3),&icntl,&flg);CHKERRQ(ierr); 1275 if (flg) mumps->id.ICNTL(3) = icntl; 1276 1277 ierr = PetscOptionsInt("-mat_mumps_icntl_4","ICNTL(4): level of printing (0 to 4)","None",mumps->id.ICNTL(4),&icntl,&flg);CHKERRQ(ierr); 1278 if (flg) mumps->id.ICNTL(4) = icntl; 1279 if (mumps->id.ICNTL(4) || PetscLogPrintInfo) mumps->id.ICNTL(3) = 6; /* resume MUMPS default id.ICNTL(3) = 6 */ 1280 1281 ierr = PetscOptionsInt("-mat_mumps_icntl_6","ICNTL(6): permutes to a zero-free diagonal and/or scale the matrix (0 to 7)","None",mumps->id.ICNTL(6),&icntl,&flg);CHKERRQ(ierr); 1282 if (flg) mumps->id.ICNTL(6) = icntl; 1283 1284 ierr = PetscOptionsInt("-mat_mumps_icntl_7","ICNTL(7): computes a symmetric permutation in sequential analysis (0 to 7). 3=Scotch, 4=PORD, 5=Metis","None",mumps->id.ICNTL(7),&icntl,&flg);CHKERRQ(ierr); 1285 if (flg) { 1286 if (icntl== 1 && mumps->size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"pivot order be set by the user in PERM_IN -- not supported by the PETSc/MUMPS interface\n"); 1287 else mumps->id.ICNTL(7) = icntl; 1288 } 1289 1290 ierr = PetscOptionsInt("-mat_mumps_icntl_8","ICNTL(8): scaling strategy (-2 to 8 or 77)","None",mumps->id.ICNTL(8),&mumps->id.ICNTL(8),NULL);CHKERRQ(ierr); 1291 /* ierr = PetscOptionsInt("-mat_mumps_icntl_9","ICNTL(9): computes the solution using A or A^T","None",mumps->id.ICNTL(9),&mumps->id.ICNTL(9),NULL);CHKERRQ(ierr); handled by MatSolveTranspose_MUMPS() */ 1292 ierr = PetscOptionsInt("-mat_mumps_icntl_10","ICNTL(10): max num of refinements","None",mumps->id.ICNTL(10),&mumps->id.ICNTL(10),NULL);CHKERRQ(ierr); 1293 ierr = PetscOptionsInt("-mat_mumps_icntl_11","ICNTL(11): statistics related to an error analysis (via -ksp_view)","None",mumps->id.ICNTL(11),&mumps->id.ICNTL(11),NULL);CHKERRQ(ierr); 1294 ierr = PetscOptionsInt("-mat_mumps_icntl_12","ICNTL(12): an ordering strategy for symmetric matrices (0 to 3)","None",mumps->id.ICNTL(12),&mumps->id.ICNTL(12),NULL);CHKERRQ(ierr); 1295 ierr = PetscOptionsInt("-mat_mumps_icntl_13","ICNTL(13): parallelism of the root node (enable ScaLAPACK) and its splitting","None",mumps->id.ICNTL(13),&mumps->id.ICNTL(13),NULL);CHKERRQ(ierr); 1296 ierr = PetscOptionsInt("-mat_mumps_icntl_14","ICNTL(14): percentage increase in the estimated working space","None",mumps->id.ICNTL(14),&mumps->id.ICNTL(14),NULL);CHKERRQ(ierr); 1297 ierr = PetscOptionsInt("-mat_mumps_icntl_19","ICNTL(19): computes the Schur complement","None",mumps->id.ICNTL(19),&mumps->id.ICNTL(19),NULL);CHKERRQ(ierr); 1298 if (mumps->id.ICNTL(19) <= 0 || mumps->id.ICNTL(19) > 3) { /* reset any schur data (if any) */ 1299 ierr = MatMumpsResetSchur_Private(mumps);CHKERRQ(ierr); 1300 } 1301 /* ierr = PetscOptionsInt("-mat_mumps_icntl_20","ICNTL(20): the format (dense or sparse) of the right-hand sides","None",mumps->id.ICNTL(20),&mumps->id.ICNTL(20),NULL);CHKERRQ(ierr); -- sparse rhs is not supported in PETSc API */ 1302 /* ierr = PetscOptionsInt("-mat_mumps_icntl_21","ICNTL(21): the distribution (centralized or distributed) of the solution vectors","None",mumps->id.ICNTL(21),&mumps->id.ICNTL(21),NULL);CHKERRQ(ierr); we only use distributed solution vector */ 1303 1304 ierr = PetscOptionsInt("-mat_mumps_icntl_22","ICNTL(22): in-core/out-of-core factorization and solve (0 or 1)","None",mumps->id.ICNTL(22),&mumps->id.ICNTL(22),NULL);CHKERRQ(ierr); 1305 ierr = PetscOptionsInt("-mat_mumps_icntl_23","ICNTL(23): max size of the working memory (MB) that can allocate per processor","None",mumps->id.ICNTL(23),&mumps->id.ICNTL(23),NULL);CHKERRQ(ierr); 1306 ierr = PetscOptionsInt("-mat_mumps_icntl_24","ICNTL(24): detection of null pivot rows (0 or 1)","None",mumps->id.ICNTL(24),&mumps->id.ICNTL(24),NULL);CHKERRQ(ierr); 1307 if (mumps->id.ICNTL(24)) { 1308 mumps->id.ICNTL(13) = 1; /* turn-off ScaLAPACK to help with the correct detection of null pivots */ 1309 } 1310 1311 ierr = PetscOptionsInt("-mat_mumps_icntl_25","ICNTL(25): compute a solution of a deficient matrix and a null space basis","None",mumps->id.ICNTL(25),&mumps->id.ICNTL(25),NULL);CHKERRQ(ierr); 1312 ierr = PetscOptionsInt("-mat_mumps_icntl_26","ICNTL(26): drives the solution phase if a Schur complement matrix","None",mumps->id.ICNTL(26),&mumps->id.ICNTL(26),NULL);CHKERRQ(ierr); 1313 ierr = PetscOptionsInt("-mat_mumps_icntl_27","ICNTL(27): the blocking size for multiple right-hand sides","None",mumps->id.ICNTL(27),&mumps->id.ICNTL(27),NULL);CHKERRQ(ierr); 1314 ierr = PetscOptionsInt("-mat_mumps_icntl_28","ICNTL(28): use 1 for sequential analysis and ictnl(7) ordering, or 2 for parallel analysis and ictnl(29) ordering","None",mumps->id.ICNTL(28),&mumps->id.ICNTL(28),NULL);CHKERRQ(ierr); 1315 ierr = PetscOptionsInt("-mat_mumps_icntl_29","ICNTL(29): parallel ordering 1 = ptscotch, 2 = parmetis","None",mumps->id.ICNTL(29),&mumps->id.ICNTL(29),NULL);CHKERRQ(ierr); 1316 ierr = PetscOptionsInt("-mat_mumps_icntl_30","ICNTL(30): compute user-specified set of entries in inv(A)","None",mumps->id.ICNTL(30),&mumps->id.ICNTL(30),NULL);CHKERRQ(ierr); 1317 ierr = PetscOptionsInt("-mat_mumps_icntl_31","ICNTL(31): indicates which factors may be discarded during factorization","None",mumps->id.ICNTL(31),&mumps->id.ICNTL(31),NULL);CHKERRQ(ierr); 1318 /* ierr = PetscOptionsInt("-mat_mumps_icntl_32","ICNTL(32): performs the forward elemination of the right-hand sides during factorization","None",mumps->id.ICNTL(32),&mumps->id.ICNTL(32),NULL);CHKERRQ(ierr); -- not supported by PETSc API */ 1319 ierr = PetscOptionsInt("-mat_mumps_icntl_33","ICNTL(33): compute determinant","None",mumps->id.ICNTL(33),&mumps->id.ICNTL(33),NULL);CHKERRQ(ierr); 1320 1321 ierr = PetscOptionsReal("-mat_mumps_cntl_1","CNTL(1): relative pivoting threshold","None",mumps->id.CNTL(1),&mumps->id.CNTL(1),NULL);CHKERRQ(ierr); 1322 ierr = PetscOptionsReal("-mat_mumps_cntl_2","CNTL(2): stopping criterion of refinement","None",mumps->id.CNTL(2),&mumps->id.CNTL(2),NULL);CHKERRQ(ierr); 1323 ierr = PetscOptionsReal("-mat_mumps_cntl_3","CNTL(3): absolute pivoting threshold","None",mumps->id.CNTL(3),&mumps->id.CNTL(3),NULL);CHKERRQ(ierr); 1324 ierr = PetscOptionsReal("-mat_mumps_cntl_4","CNTL(4): value for static pivoting","None",mumps->id.CNTL(4),&mumps->id.CNTL(4),NULL);CHKERRQ(ierr); 1325 ierr = PetscOptionsReal("-mat_mumps_cntl_5","CNTL(5): fixation for null pivots","None",mumps->id.CNTL(5),&mumps->id.CNTL(5),NULL);CHKERRQ(ierr); 1326 1327 ierr = PetscOptionsString("-mat_mumps_ooc_tmpdir", "out of core directory", "None", mumps->id.ooc_tmpdir, mumps->id.ooc_tmpdir, 256, NULL);CHKERRQ(ierr); 1328 1329 ierr = PetscOptionsIntArray("-mat_mumps_view_info","request INFO local to each processor","",info,&ninfo,NULL);CHKERRQ(ierr); 1330 if (ninfo) { 1331 if (ninfo > 40) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_USER,"number of INFO %d must <= 40\n",ninfo); 1332 ierr = PetscMalloc1(ninfo,&mumps->info);CHKERRQ(ierr); 1333 mumps->ninfo = ninfo; 1334 for (i=0; i<ninfo; i++) { 1335 if (info[i] < 0 || info[i]>40) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_USER,"index of INFO %d must between 1 and 40\n",ninfo); 1336 else mumps->info[i] = info[i]; 1337 } 1338 } 1339 1340 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1341 PetscFunctionReturn(0); 1342 } 1343 1344 #undef __FUNCT__ 1345 #define __FUNCT__ "PetscInitializeMUMPS" 1346 PetscErrorCode PetscInitializeMUMPS(Mat A,Mat_MUMPS *mumps) 1347 { 1348 PetscErrorCode ierr; 1349 1350 PetscFunctionBegin; 1351 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A), &mumps->myid);CHKERRQ(ierr); 1352 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&mumps->size);CHKERRQ(ierr); 1353 ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(mumps->comm_mumps));CHKERRQ(ierr); 1354 1355 mumps->id.comm_fortran = MPI_Comm_c2f(mumps->comm_mumps); 1356 1357 mumps->id.job = JOB_INIT; 1358 mumps->id.par = 1; /* host participates factorizaton and solve */ 1359 mumps->id.sym = mumps->sym; 1360 PetscMUMPS_c(&mumps->id); 1361 1362 mumps->scat_rhs = NULL; 1363 mumps->scat_sol = NULL; 1364 1365 /* set PETSc-MUMPS default options - override MUMPS default */ 1366 mumps->id.ICNTL(3) = 0; 1367 mumps->id.ICNTL(4) = 0; 1368 if (mumps->size == 1) { 1369 mumps->id.ICNTL(18) = 0; /* centralized assembled matrix input */ 1370 } else { 1371 mumps->id.ICNTL(18) = 3; /* distributed assembled matrix input */ 1372 mumps->id.ICNTL(20) = 0; /* rhs is in dense format */ 1373 mumps->id.ICNTL(21) = 1; /* distributed solution */ 1374 } 1375 1376 /* schur */ 1377 mumps->id.size_schur = 0; 1378 mumps->id.listvar_schur = NULL; 1379 mumps->id.schur = NULL; 1380 mumps->sizeredrhs = 0; 1381 mumps->schur_pivots = NULL; 1382 mumps->schur_work = NULL; 1383 mumps->schur_sol = NULL; 1384 mumps->schur_sizesol = 0; 1385 mumps->schur_factored = PETSC_FALSE; 1386 mumps->schur_inverted = PETSC_FALSE; 1387 PetscFunctionReturn(0); 1388 } 1389 1390 #undef __FUNCT__ 1391 #define __FUNCT__ "MatFactorSymbolic_MUMPS_ReportIfError" 1392 PetscErrorCode MatFactorSymbolic_MUMPS_ReportIfError(Mat F,Mat A,const MatFactorInfo *info,Mat_MUMPS *mumps) 1393 { 1394 PetscErrorCode ierr; 1395 1396 PetscFunctionBegin; 1397 if (mumps->id.INFOG(1) < 0) { 1398 if (A->erroriffailure) { 1399 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in analysis phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); 1400 } else { 1401 if (mumps->id.INFOG(1) == -6) { 1402 ierr = PetscInfo2(F,"matrix is singular in structure, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1403 F->factorerrortype = MAT_FACTOR_STRUCT_ZEROPIVOT; 1404 } else if (mumps->id.INFOG(1) == -5 || mumps->id.INFOG(1) == -7) { 1405 ierr = PetscInfo2(F,"problem of workspace, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1406 F->factorerrortype = MAT_FACTOR_OUTMEMORY; 1407 } else { 1408 ierr = PetscInfo2(F,"Error reported by MUMPS in analysis phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); 1409 F->factorerrortype = MAT_FACTOR_OTHER; 1410 } 1411 } 1412 } 1413 PetscFunctionReturn(0); 1414 } 1415 1416 /* Note Petsc r(=c) permutation is used when mumps->id.ICNTL(7)==1 with centralized assembled matrix input; otherwise r and c are ignored */ 1417 #undef __FUNCT__ 1418 #define __FUNCT__ "MatLUFactorSymbolic_AIJMUMPS" 1419 PetscErrorCode MatLUFactorSymbolic_AIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 1420 { 1421 Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 1422 PetscErrorCode ierr; 1423 Vec b; 1424 IS is_iden; 1425 const PetscInt M = A->rmap->N; 1426 1427 PetscFunctionBegin; 1428 mumps->matstruc = DIFFERENT_NONZERO_PATTERN; 1429 1430 /* Set MUMPS options from the options database */ 1431 ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); 1432 1433 ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); 1434 1435 /* analysis phase */ 1436 /*----------------*/ 1437 mumps->id.job = JOB_FACTSYMBOLIC; 1438 mumps->id.n = M; 1439 switch (mumps->id.ICNTL(18)) { 1440 case 0: /* centralized assembled matrix input */ 1441 if (!mumps->myid) { 1442 mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; 1443 if (mumps->id.ICNTL(6)>1) { 1444 mumps->id.a = (MumpsScalar*)mumps->val; 1445 } 1446 if (mumps->id.ICNTL(7) == 1) { /* use user-provide matrix ordering - assuming r = c ordering */ 1447 /* 1448 PetscBool flag; 1449 ierr = ISEqual(r,c,&flag);CHKERRQ(ierr); 1450 if (!flag) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"row_perm != col_perm"); 1451 ierr = ISView(r,PETSC_VIEWER_STDOUT_SELF); 1452 */ 1453 if (!mumps->myid) { 1454 const PetscInt *idx; 1455 PetscInt i,*perm_in; 1456 1457 ierr = PetscMalloc1(M,&perm_in);CHKERRQ(ierr); 1458 ierr = ISGetIndices(r,&idx);CHKERRQ(ierr); 1459 1460 mumps->id.perm_in = perm_in; 1461 for (i=0; i<M; i++) perm_in[i] = idx[i]+1; /* perm_in[]: start from 1, not 0! */ 1462 ierr = ISRestoreIndices(r,&idx);CHKERRQ(ierr); 1463 } 1464 } 1465 } 1466 break; 1467 case 3: /* distributed assembled matrix input (size>1) */ 1468 mumps->id.nz_loc = mumps->nz; 1469 mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; 1470 if (mumps->id.ICNTL(6)>1) { 1471 mumps->id.a_loc = (MumpsScalar*)mumps->val; 1472 } 1473 /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ 1474 if (!mumps->myid) { 1475 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->N,&mumps->b_seq);CHKERRQ(ierr); 1476 ierr = ISCreateStride(PETSC_COMM_SELF,A->rmap->N,0,1,&is_iden);CHKERRQ(ierr); 1477 } else { 1478 ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); 1479 ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); 1480 } 1481 ierr = MatCreateVecs(A,NULL,&b);CHKERRQ(ierr); 1482 ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); 1483 ierr = ISDestroy(&is_iden);CHKERRQ(ierr); 1484 ierr = VecDestroy(&b);CHKERRQ(ierr); 1485 break; 1486 } 1487 PetscMUMPS_c(&mumps->id); 1488 ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); 1489 1490 F->ops->lufactornumeric = MatFactorNumeric_MUMPS; 1491 F->ops->solve = MatSolve_MUMPS; 1492 F->ops->solvetranspose = MatSolveTranspose_MUMPS; 1493 F->ops->matsolve = MatMatSolve_MUMPS; 1494 PetscFunctionReturn(0); 1495 } 1496 1497 /* Note the Petsc r and c permutations are ignored */ 1498 #undef __FUNCT__ 1499 #define __FUNCT__ "MatLUFactorSymbolic_BAIJMUMPS" 1500 PetscErrorCode MatLUFactorSymbolic_BAIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 1501 { 1502 Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 1503 PetscErrorCode ierr; 1504 Vec b; 1505 IS is_iden; 1506 const PetscInt M = A->rmap->N; 1507 1508 PetscFunctionBegin; 1509 mumps->matstruc = DIFFERENT_NONZERO_PATTERN; 1510 1511 /* Set MUMPS options from the options database */ 1512 ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); 1513 1514 ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); 1515 1516 /* analysis phase */ 1517 /*----------------*/ 1518 mumps->id.job = JOB_FACTSYMBOLIC; 1519 mumps->id.n = M; 1520 switch (mumps->id.ICNTL(18)) { 1521 case 0: /* centralized assembled matrix input */ 1522 if (!mumps->myid) { 1523 mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; 1524 if (mumps->id.ICNTL(6)>1) { 1525 mumps->id.a = (MumpsScalar*)mumps->val; 1526 } 1527 } 1528 break; 1529 case 3: /* distributed assembled matrix input (size>1) */ 1530 mumps->id.nz_loc = mumps->nz; 1531 mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; 1532 if (mumps->id.ICNTL(6)>1) { 1533 mumps->id.a_loc = (MumpsScalar*)mumps->val; 1534 } 1535 /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ 1536 if (!mumps->myid) { 1537 ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&mumps->b_seq);CHKERRQ(ierr); 1538 ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr); 1539 } else { 1540 ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); 1541 ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); 1542 } 1543 ierr = MatCreateVecs(A,NULL,&b);CHKERRQ(ierr); 1544 ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); 1545 ierr = ISDestroy(&is_iden);CHKERRQ(ierr); 1546 ierr = VecDestroy(&b);CHKERRQ(ierr); 1547 break; 1548 } 1549 PetscMUMPS_c(&mumps->id); 1550 ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); 1551 1552 F->ops->lufactornumeric = MatFactorNumeric_MUMPS; 1553 F->ops->solve = MatSolve_MUMPS; 1554 F->ops->solvetranspose = MatSolveTranspose_MUMPS; 1555 PetscFunctionReturn(0); 1556 } 1557 1558 /* Note the Petsc r permutation and factor info are ignored */ 1559 #undef __FUNCT__ 1560 #define __FUNCT__ "MatCholeskyFactorSymbolic_MUMPS" 1561 PetscErrorCode MatCholeskyFactorSymbolic_MUMPS(Mat F,Mat A,IS r,const MatFactorInfo *info) 1562 { 1563 Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 1564 PetscErrorCode ierr; 1565 Vec b; 1566 IS is_iden; 1567 const PetscInt M = A->rmap->N; 1568 1569 PetscFunctionBegin; 1570 mumps->matstruc = DIFFERENT_NONZERO_PATTERN; 1571 1572 /* Set MUMPS options from the options database */ 1573 ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); 1574 1575 ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); 1576 1577 /* analysis phase */ 1578 /*----------------*/ 1579 mumps->id.job = JOB_FACTSYMBOLIC; 1580 mumps->id.n = M; 1581 switch (mumps->id.ICNTL(18)) { 1582 case 0: /* centralized assembled matrix input */ 1583 if (!mumps->myid) { 1584 mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; 1585 if (mumps->id.ICNTL(6)>1) { 1586 mumps->id.a = (MumpsScalar*)mumps->val; 1587 } 1588 } 1589 break; 1590 case 3: /* distributed assembled matrix input (size>1) */ 1591 mumps->id.nz_loc = mumps->nz; 1592 mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; 1593 if (mumps->id.ICNTL(6)>1) { 1594 mumps->id.a_loc = (MumpsScalar*)mumps->val; 1595 } 1596 /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ 1597 if (!mumps->myid) { 1598 ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&mumps->b_seq);CHKERRQ(ierr); 1599 ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr); 1600 } else { 1601 ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); 1602 ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); 1603 } 1604 ierr = MatCreateVecs(A,NULL,&b);CHKERRQ(ierr); 1605 ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); 1606 ierr = ISDestroy(&is_iden);CHKERRQ(ierr); 1607 ierr = VecDestroy(&b);CHKERRQ(ierr); 1608 break; 1609 } 1610 PetscMUMPS_c(&mumps->id); 1611 ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); 1612 1613 F->ops->choleskyfactornumeric = MatFactorNumeric_MUMPS; 1614 F->ops->solve = MatSolve_MUMPS; 1615 F->ops->solvetranspose = MatSolve_MUMPS; 1616 F->ops->matsolve = MatMatSolve_MUMPS; 1617 #if defined(PETSC_USE_COMPLEX) 1618 F->ops->getinertia = NULL; 1619 #else 1620 F->ops->getinertia = MatGetInertia_SBAIJMUMPS; 1621 #endif 1622 PetscFunctionReturn(0); 1623 } 1624 1625 #undef __FUNCT__ 1626 #define __FUNCT__ "MatView_MUMPS" 1627 PetscErrorCode MatView_MUMPS(Mat A,PetscViewer viewer) 1628 { 1629 PetscErrorCode ierr; 1630 PetscBool iascii; 1631 PetscViewerFormat format; 1632 Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 1633 1634 PetscFunctionBegin; 1635 /* check if matrix is mumps type */ 1636 if (A->ops->solve != MatSolve_MUMPS) PetscFunctionReturn(0); 1637 1638 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1639 if (iascii) { 1640 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1641 if (format == PETSC_VIEWER_ASCII_INFO) { 1642 ierr = PetscViewerASCIIPrintf(viewer,"MUMPS run parameters:\n");CHKERRQ(ierr); 1643 ierr = PetscViewerASCIIPrintf(viewer," SYM (matrix type): %d \n",mumps->id.sym);CHKERRQ(ierr); 1644 ierr = PetscViewerASCIIPrintf(viewer," PAR (host participation): %d \n",mumps->id.par);CHKERRQ(ierr); 1645 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(1) (output for error): %d \n",mumps->id.ICNTL(1));CHKERRQ(ierr); 1646 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(2) (output of diagnostic msg): %d \n",mumps->id.ICNTL(2));CHKERRQ(ierr); 1647 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(3) (output for global info): %d \n",mumps->id.ICNTL(3));CHKERRQ(ierr); 1648 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(4) (level of printing): %d \n",mumps->id.ICNTL(4));CHKERRQ(ierr); 1649 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(5) (input mat struct): %d \n",mumps->id.ICNTL(5));CHKERRQ(ierr); 1650 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(6) (matrix prescaling): %d \n",mumps->id.ICNTL(6));CHKERRQ(ierr); 1651 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(7) (sequentia matrix ordering):%d \n",mumps->id.ICNTL(7));CHKERRQ(ierr); 1652 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(8) (scalling strategy): %d \n",mumps->id.ICNTL(8));CHKERRQ(ierr); 1653 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(10) (max num of refinements): %d \n",mumps->id.ICNTL(10));CHKERRQ(ierr); 1654 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(11) (error analysis): %d \n",mumps->id.ICNTL(11));CHKERRQ(ierr); 1655 if (mumps->id.ICNTL(11)>0) { 1656 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(4) (inf norm of input mat): %g\n",mumps->id.RINFOG(4));CHKERRQ(ierr); 1657 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(5) (inf norm of solution): %g\n",mumps->id.RINFOG(5));CHKERRQ(ierr); 1658 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(6) (inf norm of residual): %g\n",mumps->id.RINFOG(6));CHKERRQ(ierr); 1659 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(7),RINFOG(8) (backward error est): %g, %g\n",mumps->id.RINFOG(7),mumps->id.RINFOG(8));CHKERRQ(ierr); 1660 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(9) (error estimate): %g \n",mumps->id.RINFOG(9));CHKERRQ(ierr); 1661 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(10),RINFOG(11)(condition numbers): %g, %g\n",mumps->id.RINFOG(10),mumps->id.RINFOG(11));CHKERRQ(ierr); 1662 } 1663 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(12) (efficiency control): %d \n",mumps->id.ICNTL(12));CHKERRQ(ierr); 1664 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(13) (efficiency control): %d \n",mumps->id.ICNTL(13));CHKERRQ(ierr); 1665 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(14) (percentage of estimated workspace increase): %d \n",mumps->id.ICNTL(14));CHKERRQ(ierr); 1666 /* ICNTL(15-17) not used */ 1667 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(18) (input mat struct): %d \n",mumps->id.ICNTL(18));CHKERRQ(ierr); 1668 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(19) (Shur complement info): %d \n",mumps->id.ICNTL(19));CHKERRQ(ierr); 1669 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(20) (rhs sparse pattern): %d \n",mumps->id.ICNTL(20));CHKERRQ(ierr); 1670 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(21) (solution struct): %d \n",mumps->id.ICNTL(21));CHKERRQ(ierr); 1671 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(22) (in-core/out-of-core facility): %d \n",mumps->id.ICNTL(22));CHKERRQ(ierr); 1672 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(23) (max size of memory can be allocated locally):%d \n",mumps->id.ICNTL(23));CHKERRQ(ierr); 1673 1674 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(24) (detection of null pivot rows): %d \n",mumps->id.ICNTL(24));CHKERRQ(ierr); 1675 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(25) (computation of a null space basis): %d \n",mumps->id.ICNTL(25));CHKERRQ(ierr); 1676 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(26) (Schur options for rhs or solution): %d \n",mumps->id.ICNTL(26));CHKERRQ(ierr); 1677 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(27) (experimental parameter): %d \n",mumps->id.ICNTL(27));CHKERRQ(ierr); 1678 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(28) (use parallel or sequential ordering): %d \n",mumps->id.ICNTL(28));CHKERRQ(ierr); 1679 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(29) (parallel ordering): %d \n",mumps->id.ICNTL(29));CHKERRQ(ierr); 1680 1681 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(30) (user-specified set of entries in inv(A)): %d \n",mumps->id.ICNTL(30));CHKERRQ(ierr); 1682 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(31) (factors is discarded in the solve phase): %d \n",mumps->id.ICNTL(31));CHKERRQ(ierr); 1683 ierr = PetscViewerASCIIPrintf(viewer," ICNTL(33) (compute determinant): %d \n",mumps->id.ICNTL(33));CHKERRQ(ierr); 1684 1685 ierr = PetscViewerASCIIPrintf(viewer," CNTL(1) (relative pivoting threshold): %g \n",mumps->id.CNTL(1));CHKERRQ(ierr); 1686 ierr = PetscViewerASCIIPrintf(viewer," CNTL(2) (stopping criterion of refinement): %g \n",mumps->id.CNTL(2));CHKERRQ(ierr); 1687 ierr = PetscViewerASCIIPrintf(viewer," CNTL(3) (absolute pivoting threshold): %g \n",mumps->id.CNTL(3));CHKERRQ(ierr); 1688 ierr = PetscViewerASCIIPrintf(viewer," CNTL(4) (value of static pivoting): %g \n",mumps->id.CNTL(4));CHKERRQ(ierr); 1689 ierr = PetscViewerASCIIPrintf(viewer," CNTL(5) (fixation for null pivots): %g \n",mumps->id.CNTL(5));CHKERRQ(ierr); 1690 1691 /* infomation local to each processor */ 1692 ierr = PetscViewerASCIIPrintf(viewer, " RINFO(1) (local estimated flops for the elimination after analysis): \n");CHKERRQ(ierr); 1693 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1694 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(1));CHKERRQ(ierr); 1695 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1696 ierr = PetscViewerASCIIPrintf(viewer, " RINFO(2) (local estimated flops for the assembly after factorization): \n");CHKERRQ(ierr); 1697 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(2));CHKERRQ(ierr); 1698 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1699 ierr = PetscViewerASCIIPrintf(viewer, " RINFO(3) (local estimated flops for the elimination after factorization): \n");CHKERRQ(ierr); 1700 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(3));CHKERRQ(ierr); 1701 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1702 1703 ierr = PetscViewerASCIIPrintf(viewer, " INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): \n");CHKERRQ(ierr); 1704 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(15));CHKERRQ(ierr); 1705 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1706 1707 ierr = PetscViewerASCIIPrintf(viewer, " INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): \n");CHKERRQ(ierr); 1708 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(16));CHKERRQ(ierr); 1709 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1710 1711 ierr = PetscViewerASCIIPrintf(viewer, " INFO(23) (num of pivots eliminated on this processor after factorization): \n");CHKERRQ(ierr); 1712 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(23));CHKERRQ(ierr); 1713 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1714 1715 if (mumps->ninfo && mumps->ninfo <= 40){ 1716 PetscInt i; 1717 for (i=0; i<mumps->ninfo; i++){ 1718 ierr = PetscViewerASCIIPrintf(viewer, " INFO(%d): \n",mumps->info[i]);CHKERRQ(ierr); 1719 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(mumps->info[i]));CHKERRQ(ierr); 1720 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1721 } 1722 } 1723 1724 1725 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1726 1727 if (!mumps->myid) { /* information from the host */ 1728 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(1) (global estimated flops for the elimination after analysis): %g \n",mumps->id.RINFOG(1));CHKERRQ(ierr); 1729 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(2) (global estimated flops for the assembly after factorization): %g \n",mumps->id.RINFOG(2));CHKERRQ(ierr); 1730 ierr = PetscViewerASCIIPrintf(viewer," RINFOG(3) (global estimated flops for the elimination after factorization): %g \n",mumps->id.RINFOG(3));CHKERRQ(ierr); 1731 ierr = PetscViewerASCIIPrintf(viewer," (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (%g,%g)*(2^%d)\n",mumps->id.RINFOG(12),mumps->id.RINFOG(13),mumps->id.INFOG(34));CHKERRQ(ierr); 1732 1733 ierr = PetscViewerASCIIPrintf(viewer," INFOG(3) (estimated real workspace for factors on all processors after analysis): %d \n",mumps->id.INFOG(3));CHKERRQ(ierr); 1734 ierr = PetscViewerASCIIPrintf(viewer," INFOG(4) (estimated integer workspace for factors on all processors after analysis): %d \n",mumps->id.INFOG(4));CHKERRQ(ierr); 1735 ierr = PetscViewerASCIIPrintf(viewer," INFOG(5) (estimated maximum front size in the complete tree): %d \n",mumps->id.INFOG(5));CHKERRQ(ierr); 1736 ierr = PetscViewerASCIIPrintf(viewer," INFOG(6) (number of nodes in the complete tree): %d \n",mumps->id.INFOG(6));CHKERRQ(ierr); 1737 ierr = PetscViewerASCIIPrintf(viewer," INFOG(7) (ordering option effectively use after analysis): %d \n",mumps->id.INFOG(7));CHKERRQ(ierr); 1738 ierr = PetscViewerASCIIPrintf(viewer," INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): %d \n",mumps->id.INFOG(8));CHKERRQ(ierr); 1739 ierr = PetscViewerASCIIPrintf(viewer," INFOG(9) (total real/complex workspace to store the matrix factors after factorization): %d \n",mumps->id.INFOG(9));CHKERRQ(ierr); 1740 ierr = PetscViewerASCIIPrintf(viewer," INFOG(10) (total integer space store the matrix factors after factorization): %d \n",mumps->id.INFOG(10));CHKERRQ(ierr); 1741 ierr = PetscViewerASCIIPrintf(viewer," INFOG(11) (order of largest frontal matrix after factorization): %d \n",mumps->id.INFOG(11));CHKERRQ(ierr); 1742 ierr = PetscViewerASCIIPrintf(viewer," INFOG(12) (number of off-diagonal pivots): %d \n",mumps->id.INFOG(12));CHKERRQ(ierr); 1743 ierr = PetscViewerASCIIPrintf(viewer," INFOG(13) (number of delayed pivots after factorization): %d \n",mumps->id.INFOG(13));CHKERRQ(ierr); 1744 ierr = PetscViewerASCIIPrintf(viewer," INFOG(14) (number of memory compress after factorization): %d \n",mumps->id.INFOG(14));CHKERRQ(ierr); 1745 ierr = PetscViewerASCIIPrintf(viewer," INFOG(15) (number of steps of iterative refinement after solution): %d \n",mumps->id.INFOG(15));CHKERRQ(ierr); 1746 ierr = PetscViewerASCIIPrintf(viewer," INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): %d \n",mumps->id.INFOG(16));CHKERRQ(ierr); 1747 ierr = PetscViewerASCIIPrintf(viewer," INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): %d \n",mumps->id.INFOG(17));CHKERRQ(ierr); 1748 ierr = PetscViewerASCIIPrintf(viewer," INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): %d \n",mumps->id.INFOG(18));CHKERRQ(ierr); 1749 ierr = PetscViewerASCIIPrintf(viewer," INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): %d \n",mumps->id.INFOG(19));CHKERRQ(ierr); 1750 ierr = PetscViewerASCIIPrintf(viewer," INFOG(20) (estimated number of entries in the factors): %d \n",mumps->id.INFOG(20));CHKERRQ(ierr); 1751 ierr = PetscViewerASCIIPrintf(viewer," INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): %d \n",mumps->id.INFOG(21));CHKERRQ(ierr); 1752 ierr = PetscViewerASCIIPrintf(viewer," INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): %d \n",mumps->id.INFOG(22));CHKERRQ(ierr); 1753 ierr = PetscViewerASCIIPrintf(viewer," INFOG(23) (after analysis: value of ICNTL(6) effectively used): %d \n",mumps->id.INFOG(23));CHKERRQ(ierr); 1754 ierr = PetscViewerASCIIPrintf(viewer," INFOG(24) (after analysis: value of ICNTL(12) effectively used): %d \n",mumps->id.INFOG(24));CHKERRQ(ierr); 1755 ierr = PetscViewerASCIIPrintf(viewer," INFOG(25) (after factorization: number of pivots modified by static pivoting): %d \n",mumps->id.INFOG(25));CHKERRQ(ierr); 1756 ierr = PetscViewerASCIIPrintf(viewer," INFOG(28) (after factorization: number of null pivots encountered): %d\n",mumps->id.INFOG(28));CHKERRQ(ierr); 1757 ierr = PetscViewerASCIIPrintf(viewer," INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): %d\n",mumps->id.INFOG(29));CHKERRQ(ierr); 1758 ierr = PetscViewerASCIIPrintf(viewer," INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): %d, %d\n",mumps->id.INFOG(30),mumps->id.INFOG(31));CHKERRQ(ierr); 1759 ierr = PetscViewerASCIIPrintf(viewer," INFOG(32) (after analysis: type of analysis done): %d\n",mumps->id.INFOG(32));CHKERRQ(ierr); 1760 ierr = PetscViewerASCIIPrintf(viewer," INFOG(33) (value used for ICNTL(8)): %d\n",mumps->id.INFOG(33));CHKERRQ(ierr); 1761 ierr = PetscViewerASCIIPrintf(viewer," INFOG(34) (exponent of the determinant if determinant is requested): %d\n",mumps->id.INFOG(34));CHKERRQ(ierr); 1762 } 1763 } 1764 } 1765 PetscFunctionReturn(0); 1766 } 1767 1768 #undef __FUNCT__ 1769 #define __FUNCT__ "MatGetInfo_MUMPS" 1770 PetscErrorCode MatGetInfo_MUMPS(Mat A,MatInfoType flag,MatInfo *info) 1771 { 1772 Mat_MUMPS *mumps =(Mat_MUMPS*)A->data; 1773 1774 PetscFunctionBegin; 1775 info->block_size = 1.0; 1776 info->nz_allocated = mumps->id.INFOG(20); 1777 info->nz_used = mumps->id.INFOG(20); 1778 info->nz_unneeded = 0.0; 1779 info->assemblies = 0.0; 1780 info->mallocs = 0.0; 1781 info->memory = 0.0; 1782 info->fill_ratio_given = 0; 1783 info->fill_ratio_needed = 0; 1784 info->factor_mallocs = 0; 1785 PetscFunctionReturn(0); 1786 } 1787 1788 /* -------------------------------------------------------------------------------------------*/ 1789 #undef __FUNCT__ 1790 #define __FUNCT__ "MatFactorSetSchurIS_MUMPS" 1791 PetscErrorCode MatFactorSetSchurIS_MUMPS(Mat F, IS is) 1792 { 1793 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1794 const PetscInt *idxs; 1795 PetscInt size,i; 1796 PetscErrorCode ierr; 1797 1798 PetscFunctionBegin; 1799 if (mumps->size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MUMPS parallel Schur complements not yet supported from PETSc\n"); 1800 ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); 1801 if (mumps->id.size_schur != size) { 1802 ierr = PetscFree2(mumps->id.listvar_schur,mumps->id.schur);CHKERRQ(ierr); 1803 mumps->id.size_schur = size; 1804 mumps->id.schur_lld = size; 1805 ierr = PetscMalloc2(size,&mumps->id.listvar_schur,size*size,&mumps->id.schur);CHKERRQ(ierr); 1806 } 1807 ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); 1808 ierr = PetscMemcpy(mumps->id.listvar_schur,idxs,size*sizeof(PetscInt));CHKERRQ(ierr); 1809 /* MUMPS expects Fortran style indices */ 1810 for (i=0;i<size;i++) mumps->id.listvar_schur[i]++; 1811 ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); 1812 if (size) { /* turn on Schur switch if we the set of indices is not empty */ 1813 if (F->factortype == MAT_FACTOR_LU) { 1814 mumps->id.ICNTL(19) = 3; /* MUMPS returns full matrix */ 1815 } else { 1816 mumps->id.ICNTL(19) = 2; /* MUMPS returns lower triangular part */ 1817 } 1818 /* set a special value of ICNTL (not handled my MUMPS) to be used in the solve phase by PETSc */ 1819 mumps->id.ICNTL(26) = -1; 1820 } 1821 PetscFunctionReturn(0); 1822 } 1823 1824 /* -------------------------------------------------------------------------------------------*/ 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatFactorCreateSchurComplement_MUMPS" 1827 PetscErrorCode MatFactorCreateSchurComplement_MUMPS(Mat F,Mat* S) 1828 { 1829 Mat St; 1830 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1831 PetscScalar *array; 1832 #if defined(PETSC_USE_COMPLEX) 1833 PetscScalar im = PetscSqrtScalar((PetscScalar)-1.0); 1834 #endif 1835 PetscErrorCode ierr; 1836 1837 PetscFunctionBegin; 1838 if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 1839 else if (!mumps->id.size_schur) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 1840 1841 ierr = MatCreate(PetscObjectComm((PetscObject)F),&St);CHKERRQ(ierr); 1842 ierr = MatSetSizes(St,PETSC_DECIDE,PETSC_DECIDE,mumps->id.size_schur,mumps->id.size_schur);CHKERRQ(ierr); 1843 ierr = MatSetType(St,MATDENSE);CHKERRQ(ierr); 1844 ierr = MatSetUp(St);CHKERRQ(ierr); 1845 ierr = MatDenseGetArray(St,&array);CHKERRQ(ierr); 1846 if (!mumps->sym) { /* MUMPS always return a full matrix */ 1847 if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ 1848 PetscInt i,j,N=mumps->id.size_schur; 1849 for (i=0;i<N;i++) { 1850 for (j=0;j<N;j++) { 1851 #if !defined(PETSC_USE_COMPLEX) 1852 PetscScalar val = mumps->id.schur[i*N+j]; 1853 #else 1854 PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; 1855 #endif 1856 array[j*N+i] = val; 1857 } 1858 } 1859 } else { /* stored by columns */ 1860 ierr = PetscMemcpy(array,mumps->id.schur,mumps->id.size_schur*mumps->id.size_schur*sizeof(PetscScalar));CHKERRQ(ierr); 1861 } 1862 } else { /* either full or lower-triangular (not packed) */ 1863 if (mumps->id.ICNTL(19) == 2) { /* lower triangular stored by columns */ 1864 PetscInt i,j,N=mumps->id.size_schur; 1865 for (i=0;i<N;i++) { 1866 for (j=i;j<N;j++) { 1867 #if !defined(PETSC_USE_COMPLEX) 1868 PetscScalar val = mumps->id.schur[i*N+j]; 1869 #else 1870 PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; 1871 #endif 1872 array[i*N+j] = val; 1873 array[j*N+i] = val; 1874 } 1875 } 1876 } else if (mumps->id.ICNTL(19) == 3) { /* full matrix */ 1877 ierr = PetscMemcpy(array,mumps->id.schur,mumps->id.size_schur*mumps->id.size_schur*sizeof(PetscScalar));CHKERRQ(ierr); 1878 } else { /* ICNTL(19) == 1 lower triangular stored by rows */ 1879 PetscInt i,j,N=mumps->id.size_schur; 1880 for (i=0;i<N;i++) { 1881 for (j=0;j<i+1;j++) { 1882 #if !defined(PETSC_USE_COMPLEX) 1883 PetscScalar val = mumps->id.schur[i*N+j]; 1884 #else 1885 PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; 1886 #endif 1887 array[i*N+j] = val; 1888 array[j*N+i] = val; 1889 } 1890 } 1891 } 1892 } 1893 ierr = MatDenseRestoreArray(St,&array);CHKERRQ(ierr); 1894 *S = St; 1895 PetscFunctionReturn(0); 1896 } 1897 1898 /* -------------------------------------------------------------------------------------------*/ 1899 #undef __FUNCT__ 1900 #define __FUNCT__ "MatFactorGetSchurComplement_MUMPS" 1901 PetscErrorCode MatFactorGetSchurComplement_MUMPS(Mat F,Mat* S) 1902 { 1903 Mat St; 1904 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1905 PetscErrorCode ierr; 1906 1907 PetscFunctionBegin; 1908 if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 1909 else if (!mumps->id.size_schur) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 1910 1911 /* It should be the responsibility of the user to handle different ICNTL(19) cases and factorization stages if they want to work with the raw data */ 1912 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)F),mumps->id.size_schur,mumps->id.size_schur,(PetscScalar*)mumps->id.schur,&St);CHKERRQ(ierr); 1913 *S = St; 1914 PetscFunctionReturn(0); 1915 } 1916 1917 /* -------------------------------------------------------------------------------------------*/ 1918 #undef __FUNCT__ 1919 #define __FUNCT__ "MatFactorInvertSchurComplement_MUMPS" 1920 PetscErrorCode MatFactorInvertSchurComplement_MUMPS(Mat F) 1921 { 1922 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1923 PetscErrorCode ierr; 1924 1925 PetscFunctionBegin; 1926 if (!mumps->id.ICNTL(19)) { /* do nothing */ 1927 PetscFunctionReturn(0); 1928 } 1929 if (!mumps->id.size_schur) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 1930 ierr = MatMumpsInvertSchur_Private(mumps);CHKERRQ(ierr); 1931 PetscFunctionReturn(0); 1932 } 1933 1934 /* -------------------------------------------------------------------------------------------*/ 1935 #undef __FUNCT__ 1936 #define __FUNCT__ "MatFactorSolveSchurComplement_MUMPS" 1937 PetscErrorCode MatFactorSolveSchurComplement_MUMPS(Mat F, Vec rhs, Vec sol) 1938 { 1939 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1940 MumpsScalar *orhs; 1941 PetscScalar *osol,*nrhs,*nsol; 1942 PetscInt orhs_size,osol_size,olrhs_size; 1943 PetscErrorCode ierr; 1944 1945 PetscFunctionBegin; 1946 if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 1947 if (!mumps->id.size_schur) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 1948 1949 /* swap pointers */ 1950 orhs = mumps->id.redrhs; 1951 olrhs_size = mumps->id.lredrhs; 1952 orhs_size = mumps->sizeredrhs; 1953 osol = mumps->schur_sol; 1954 osol_size = mumps->schur_sizesol; 1955 ierr = VecGetArray(rhs,&nrhs);CHKERRQ(ierr); 1956 ierr = VecGetArray(sol,&nsol);CHKERRQ(ierr); 1957 mumps->id.redrhs = (MumpsScalar*)nrhs; 1958 ierr = VecGetLocalSize(rhs,&mumps->sizeredrhs);CHKERRQ(ierr); 1959 mumps->id.lredrhs = mumps->sizeredrhs; 1960 mumps->schur_sol = nsol; 1961 ierr = VecGetLocalSize(sol,&mumps->schur_sizesol);CHKERRQ(ierr); 1962 1963 /* solve Schur complement */ 1964 mumps->id.nrhs = 1; 1965 ierr = MatMumpsSolveSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); 1966 /* restore pointers */ 1967 ierr = VecRestoreArray(rhs,&nrhs);CHKERRQ(ierr); 1968 ierr = VecRestoreArray(sol,&nsol);CHKERRQ(ierr); 1969 mumps->id.redrhs = orhs; 1970 mumps->id.lredrhs = olrhs_size; 1971 mumps->sizeredrhs = orhs_size; 1972 mumps->schur_sol = osol; 1973 mumps->schur_sizesol = osol_size; 1974 PetscFunctionReturn(0); 1975 } 1976 1977 /* -------------------------------------------------------------------------------------------*/ 1978 #undef __FUNCT__ 1979 #define __FUNCT__ "MatFactorSolveSchurComplementTranspose_MUMPS" 1980 PetscErrorCode MatFactorSolveSchurComplementTranspose_MUMPS(Mat F, Vec rhs, Vec sol) 1981 { 1982 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 1983 MumpsScalar *orhs; 1984 PetscScalar *osol,*nrhs,*nsol; 1985 PetscInt orhs_size,osol_size; 1986 PetscErrorCode ierr; 1987 1988 PetscFunctionBegin; 1989 if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); 1990 else if (!mumps->id.size_schur) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur indices not set! You should call MatFactorSetSchurIS before"); 1991 1992 /* swap pointers */ 1993 orhs = mumps->id.redrhs; 1994 orhs_size = mumps->sizeredrhs; 1995 osol = mumps->schur_sol; 1996 osol_size = mumps->schur_sizesol; 1997 ierr = VecGetArray(rhs,&nrhs);CHKERRQ(ierr); 1998 ierr = VecGetArray(sol,&nsol);CHKERRQ(ierr); 1999 mumps->id.redrhs = (MumpsScalar*)nrhs; 2000 ierr = VecGetLocalSize(rhs,&mumps->sizeredrhs);CHKERRQ(ierr); 2001 mumps->schur_sol = nsol; 2002 ierr = VecGetLocalSize(sol,&mumps->schur_sizesol);CHKERRQ(ierr); 2003 2004 /* solve Schur complement */ 2005 mumps->id.nrhs = 1; 2006 mumps->id.ICNTL(9) = 0; 2007 ierr = MatMumpsSolveSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); 2008 mumps->id.ICNTL(9) = 1; 2009 /* restore pointers */ 2010 ierr = VecRestoreArray(rhs,&nrhs);CHKERRQ(ierr); 2011 ierr = VecRestoreArray(sol,&nsol);CHKERRQ(ierr); 2012 mumps->id.redrhs = orhs; 2013 mumps->sizeredrhs = orhs_size; 2014 mumps->schur_sol = osol; 2015 mumps->schur_sizesol = osol_size; 2016 PetscFunctionReturn(0); 2017 } 2018 2019 /* -------------------------------------------------------------------------------------------*/ 2020 #undef __FUNCT__ 2021 #define __FUNCT__ "MatMumpsSetIcntl_MUMPS" 2022 PetscErrorCode MatMumpsSetIcntl_MUMPS(Mat F,PetscInt icntl,PetscInt ival) 2023 { 2024 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2025 2026 PetscFunctionBegin; 2027 mumps->id.ICNTL(icntl) = ival; 2028 PetscFunctionReturn(0); 2029 } 2030 2031 #undef __FUNCT__ 2032 #define __FUNCT__ "MatMumpsGetIcntl_MUMPS" 2033 PetscErrorCode MatMumpsGetIcntl_MUMPS(Mat F,PetscInt icntl,PetscInt *ival) 2034 { 2035 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2036 2037 PetscFunctionBegin; 2038 *ival = mumps->id.ICNTL(icntl); 2039 PetscFunctionReturn(0); 2040 } 2041 2042 #undef __FUNCT__ 2043 #define __FUNCT__ "MatMumpsSetIcntl" 2044 /*@ 2045 MatMumpsSetIcntl - Set MUMPS parameter ICNTL() 2046 2047 Logically Collective on Mat 2048 2049 Input Parameters: 2050 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2051 . icntl - index of MUMPS parameter array ICNTL() 2052 - ival - value of MUMPS ICNTL(icntl) 2053 2054 Options Database: 2055 . -mat_mumps_icntl_<icntl> <ival> 2056 2057 Level: beginner 2058 2059 References: 2060 . MUMPS Users' Guide 2061 2062 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2063 @*/ 2064 PetscErrorCode MatMumpsSetIcntl(Mat F,PetscInt icntl,PetscInt ival) 2065 { 2066 PetscErrorCode ierr; 2067 2068 PetscFunctionBegin; 2069 PetscValidType(F,1); 2070 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2071 PetscValidLogicalCollectiveInt(F,icntl,2); 2072 PetscValidLogicalCollectiveInt(F,ival,3); 2073 ierr = PetscTryMethod(F,"MatMumpsSetIcntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); 2074 PetscFunctionReturn(0); 2075 } 2076 2077 #undef __FUNCT__ 2078 #define __FUNCT__ "MatMumpsGetIcntl" 2079 /*@ 2080 MatMumpsGetIcntl - Get MUMPS parameter ICNTL() 2081 2082 Logically Collective on Mat 2083 2084 Input Parameters: 2085 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2086 - icntl - index of MUMPS parameter array ICNTL() 2087 2088 Output Parameter: 2089 . ival - value of MUMPS ICNTL(icntl) 2090 2091 Level: beginner 2092 2093 References: 2094 . MUMPS Users' Guide 2095 2096 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2097 @*/ 2098 PetscErrorCode MatMumpsGetIcntl(Mat F,PetscInt icntl,PetscInt *ival) 2099 { 2100 PetscErrorCode ierr; 2101 2102 PetscFunctionBegin; 2103 PetscValidType(F,1); 2104 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2105 PetscValidLogicalCollectiveInt(F,icntl,2); 2106 PetscValidIntPointer(ival,3); 2107 ierr = PetscUseMethod(F,"MatMumpsGetIcntl_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); 2108 PetscFunctionReturn(0); 2109 } 2110 2111 /* -------------------------------------------------------------------------------------------*/ 2112 #undef __FUNCT__ 2113 #define __FUNCT__ "MatMumpsSetCntl_MUMPS" 2114 PetscErrorCode MatMumpsSetCntl_MUMPS(Mat F,PetscInt icntl,PetscReal val) 2115 { 2116 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2117 2118 PetscFunctionBegin; 2119 mumps->id.CNTL(icntl) = val; 2120 PetscFunctionReturn(0); 2121 } 2122 2123 #undef __FUNCT__ 2124 #define __FUNCT__ "MatMumpsGetCntl_MUMPS" 2125 PetscErrorCode MatMumpsGetCntl_MUMPS(Mat F,PetscInt icntl,PetscReal *val) 2126 { 2127 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2128 2129 PetscFunctionBegin; 2130 *val = mumps->id.CNTL(icntl); 2131 PetscFunctionReturn(0); 2132 } 2133 2134 #undef __FUNCT__ 2135 #define __FUNCT__ "MatMumpsSetCntl" 2136 /*@ 2137 MatMumpsSetCntl - Set MUMPS parameter CNTL() 2138 2139 Logically Collective on Mat 2140 2141 Input Parameters: 2142 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2143 . icntl - index of MUMPS parameter array CNTL() 2144 - val - value of MUMPS CNTL(icntl) 2145 2146 Options Database: 2147 . -mat_mumps_cntl_<icntl> <val> 2148 2149 Level: beginner 2150 2151 References: 2152 . MUMPS Users' Guide 2153 2154 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2155 @*/ 2156 PetscErrorCode MatMumpsSetCntl(Mat F,PetscInt icntl,PetscReal val) 2157 { 2158 PetscErrorCode ierr; 2159 2160 PetscFunctionBegin; 2161 PetscValidType(F,1); 2162 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2163 PetscValidLogicalCollectiveInt(F,icntl,2); 2164 PetscValidLogicalCollectiveReal(F,val,3); 2165 ierr = PetscTryMethod(F,"MatMumpsSetCntl_C",(Mat,PetscInt,PetscReal),(F,icntl,val));CHKERRQ(ierr); 2166 PetscFunctionReturn(0); 2167 } 2168 2169 #undef __FUNCT__ 2170 #define __FUNCT__ "MatMumpsGetCntl" 2171 /*@ 2172 MatMumpsGetCntl - Get MUMPS parameter CNTL() 2173 2174 Logically Collective on Mat 2175 2176 Input Parameters: 2177 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2178 - icntl - index of MUMPS parameter array CNTL() 2179 2180 Output Parameter: 2181 . val - value of MUMPS CNTL(icntl) 2182 2183 Level: beginner 2184 2185 References: 2186 . MUMPS Users' Guide 2187 2188 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2189 @*/ 2190 PetscErrorCode MatMumpsGetCntl(Mat F,PetscInt icntl,PetscReal *val) 2191 { 2192 PetscErrorCode ierr; 2193 2194 PetscFunctionBegin; 2195 PetscValidType(F,1); 2196 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2197 PetscValidLogicalCollectiveInt(F,icntl,2); 2198 PetscValidRealPointer(val,3); 2199 ierr = PetscUseMethod(F,"MatMumpsGetCntl_C",(Mat,PetscInt,PetscReal*),(F,icntl,val));CHKERRQ(ierr); 2200 PetscFunctionReturn(0); 2201 } 2202 2203 #undef __FUNCT__ 2204 #define __FUNCT__ "MatMumpsGetInfo_MUMPS" 2205 PetscErrorCode MatMumpsGetInfo_MUMPS(Mat F,PetscInt icntl,PetscInt *info) 2206 { 2207 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2208 2209 PetscFunctionBegin; 2210 *info = mumps->id.INFO(icntl); 2211 PetscFunctionReturn(0); 2212 } 2213 2214 #undef __FUNCT__ 2215 #define __FUNCT__ "MatMumpsGetInfog_MUMPS" 2216 PetscErrorCode MatMumpsGetInfog_MUMPS(Mat F,PetscInt icntl,PetscInt *infog) 2217 { 2218 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2219 2220 PetscFunctionBegin; 2221 *infog = mumps->id.INFOG(icntl); 2222 PetscFunctionReturn(0); 2223 } 2224 2225 #undef __FUNCT__ 2226 #define __FUNCT__ "MatMumpsGetRinfo_MUMPS" 2227 PetscErrorCode MatMumpsGetRinfo_MUMPS(Mat F,PetscInt icntl,PetscReal *rinfo) 2228 { 2229 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2230 2231 PetscFunctionBegin; 2232 *rinfo = mumps->id.RINFO(icntl); 2233 PetscFunctionReturn(0); 2234 } 2235 2236 #undef __FUNCT__ 2237 #define __FUNCT__ "MatMumpsGetRinfog_MUMPS" 2238 PetscErrorCode MatMumpsGetRinfog_MUMPS(Mat F,PetscInt icntl,PetscReal *rinfog) 2239 { 2240 Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 2241 2242 PetscFunctionBegin; 2243 *rinfog = mumps->id.RINFOG(icntl); 2244 PetscFunctionReturn(0); 2245 } 2246 2247 #undef __FUNCT__ 2248 #define __FUNCT__ "MatMumpsGetInfo" 2249 /*@ 2250 MatMumpsGetInfo - Get MUMPS parameter INFO() 2251 2252 Logically Collective on Mat 2253 2254 Input Parameters: 2255 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2256 - icntl - index of MUMPS parameter array INFO() 2257 2258 Output Parameter: 2259 . ival - value of MUMPS INFO(icntl) 2260 2261 Level: beginner 2262 2263 References: 2264 . MUMPS Users' Guide 2265 2266 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2267 @*/ 2268 PetscErrorCode MatMumpsGetInfo(Mat F,PetscInt icntl,PetscInt *ival) 2269 { 2270 PetscErrorCode ierr; 2271 2272 PetscFunctionBegin; 2273 PetscValidType(F,1); 2274 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2275 PetscValidIntPointer(ival,3); 2276 ierr = PetscUseMethod(F,"MatMumpsGetInfo_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); 2277 PetscFunctionReturn(0); 2278 } 2279 2280 #undef __FUNCT__ 2281 #define __FUNCT__ "MatMumpsGetInfog" 2282 /*@ 2283 MatMumpsGetInfog - Get MUMPS parameter INFOG() 2284 2285 Logically Collective on Mat 2286 2287 Input Parameters: 2288 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2289 - icntl - index of MUMPS parameter array INFOG() 2290 2291 Output Parameter: 2292 . ival - value of MUMPS INFOG(icntl) 2293 2294 Level: beginner 2295 2296 References: 2297 . MUMPS Users' Guide 2298 2299 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2300 @*/ 2301 PetscErrorCode MatMumpsGetInfog(Mat F,PetscInt icntl,PetscInt *ival) 2302 { 2303 PetscErrorCode ierr; 2304 2305 PetscFunctionBegin; 2306 PetscValidType(F,1); 2307 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2308 PetscValidIntPointer(ival,3); 2309 ierr = PetscUseMethod(F,"MatMumpsGetInfog_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); 2310 PetscFunctionReturn(0); 2311 } 2312 2313 #undef __FUNCT__ 2314 #define __FUNCT__ "MatMumpsGetRinfo" 2315 /*@ 2316 MatMumpsGetRinfo - Get MUMPS parameter RINFO() 2317 2318 Logically Collective on Mat 2319 2320 Input Parameters: 2321 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2322 - icntl - index of MUMPS parameter array RINFO() 2323 2324 Output Parameter: 2325 . val - value of MUMPS RINFO(icntl) 2326 2327 Level: beginner 2328 2329 References: 2330 . MUMPS Users' Guide 2331 2332 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2333 @*/ 2334 PetscErrorCode MatMumpsGetRinfo(Mat F,PetscInt icntl,PetscReal *val) 2335 { 2336 PetscErrorCode ierr; 2337 2338 PetscFunctionBegin; 2339 PetscValidType(F,1); 2340 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2341 PetscValidRealPointer(val,3); 2342 ierr = PetscUseMethod(F,"MatMumpsGetRinfo_C",(Mat,PetscInt,PetscReal*),(F,icntl,val));CHKERRQ(ierr); 2343 PetscFunctionReturn(0); 2344 } 2345 2346 #undef __FUNCT__ 2347 #define __FUNCT__ "MatMumpsGetRinfog" 2348 /*@ 2349 MatMumpsGetRinfog - Get MUMPS parameter RINFOG() 2350 2351 Logically Collective on Mat 2352 2353 Input Parameters: 2354 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface 2355 - icntl - index of MUMPS parameter array RINFOG() 2356 2357 Output Parameter: 2358 . val - value of MUMPS RINFOG(icntl) 2359 2360 Level: beginner 2361 2362 References: 2363 . MUMPS Users' Guide 2364 2365 .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() 2366 @*/ 2367 PetscErrorCode MatMumpsGetRinfog(Mat F,PetscInt icntl,PetscReal *val) 2368 { 2369 PetscErrorCode ierr; 2370 2371 PetscFunctionBegin; 2372 PetscValidType(F,1); 2373 if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); 2374 PetscValidRealPointer(val,3); 2375 ierr = PetscUseMethod(F,"MatMumpsGetRinfog_C",(Mat,PetscInt,PetscReal*),(F,icntl,val));CHKERRQ(ierr); 2376 PetscFunctionReturn(0); 2377 } 2378 2379 /*MC 2380 MATSOLVERMUMPS - A matrix type providing direct solvers (LU and Cholesky) for 2381 distributed and sequential matrices via the external package MUMPS. 2382 2383 Works with MATAIJ and MATSBAIJ matrices 2384 2385 Use ./configure --download-mumps --download-scalapack --download-parmetis --download-metis --download-ptscotch to have PETSc installed with MUMPS 2386 2387 Use -pc_type cholesky or lu -pc_factor_mat_solver_package mumps to us this direct solver 2388 2389 Options Database Keys: 2390 + -mat_mumps_icntl_1 - ICNTL(1): output stream for error messages 2391 . -mat_mumps_icntl_2 - ICNTL(2): output stream for diagnostic printing, statistics, and warning 2392 . -mat_mumps_icntl_3 - ICNTL(3): output stream for global information, collected on the host 2393 . -mat_mumps_icntl_4 - ICNTL(4): level of printing (0 to 4) 2394 . -mat_mumps_icntl_6 - ICNTL(6): permutes to a zero-free diagonal and/or scale the matrix (0 to 7) 2395 . -mat_mumps_icntl_7 - ICNTL(7): computes a symmetric permutation in sequential analysis (0 to 7). 3=Scotch, 4=PORD, 5=Metis 2396 . -mat_mumps_icntl_8 - ICNTL(8): scaling strategy (-2 to 8 or 77) 2397 . -mat_mumps_icntl_10 - ICNTL(10): max num of refinements 2398 . -mat_mumps_icntl_11 - ICNTL(11): statistics related to an error analysis (via -ksp_view) 2399 . -mat_mumps_icntl_12 - ICNTL(12): an ordering strategy for symmetric matrices (0 to 3) 2400 . -mat_mumps_icntl_13 - ICNTL(13): parallelism of the root node (enable ScaLAPACK) and its splitting 2401 . -mat_mumps_icntl_14 - ICNTL(14): percentage increase in the estimated working space 2402 . -mat_mumps_icntl_19 - ICNTL(19): computes the Schur complement 2403 . -mat_mumps_icntl_22 - ICNTL(22): in-core/out-of-core factorization and solve (0 or 1) 2404 . -mat_mumps_icntl_23 - ICNTL(23): max size of the working memory (MB) that can allocate per processor 2405 . -mat_mumps_icntl_24 - ICNTL(24): detection of null pivot rows (0 or 1) 2406 . -mat_mumps_icntl_25 - ICNTL(25): compute a solution of a deficient matrix and a null space basis 2407 . -mat_mumps_icntl_26 - ICNTL(26): drives the solution phase if a Schur complement matrix 2408 . -mat_mumps_icntl_28 - ICNTL(28): use 1 for sequential analysis and ictnl(7) ordering, or 2 for parallel analysis and ictnl(29) ordering 2409 . -mat_mumps_icntl_29 - ICNTL(29): parallel ordering 1 = ptscotch, 2 = parmetis 2410 . -mat_mumps_icntl_30 - ICNTL(30): compute user-specified set of entries in inv(A) 2411 . -mat_mumps_icntl_31 - ICNTL(31): indicates which factors may be discarded during factorization 2412 . -mat_mumps_icntl_33 - ICNTL(33): compute determinant 2413 . -mat_mumps_cntl_1 - CNTL(1): relative pivoting threshold 2414 . -mat_mumps_cntl_2 - CNTL(2): stopping criterion of refinement 2415 . -mat_mumps_cntl_3 - CNTL(3): absolute pivoting threshold 2416 . -mat_mumps_cntl_4 - CNTL(4): value for static pivoting 2417 - -mat_mumps_cntl_5 - CNTL(5): fixation for null pivots 2418 2419 Level: beginner 2420 2421 Notes: When a MUMPS factorization fails inside a KSP solve, for example with a KSP_DIVERGED_PCSETUP_FAILED, one can find the MUMPS information about the failure by calling 2422 $ KSPGetPC(ksp,&pc); 2423 $ PCFactorGetMatrix(pc,&mat); 2424 $ MatMumpsGetInfo(mat,....); 2425 $ MatMumpsGetInfog(mat,....); etc. 2426 Or you can run with -ksp_error_if_not_converged and the program will be stopped and the information printed in the error message. 2427 2428 .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage, MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog(), KSPGetPC(), PCGetFactor(), PCFactorGetMatrix() 2429 2430 M*/ 2431 2432 #undef __FUNCT__ 2433 #define __FUNCT__ "MatFactorGetSolverPackage_mumps" 2434 static PetscErrorCode MatFactorGetSolverPackage_mumps(Mat A,const MatSolverPackage *type) 2435 { 2436 PetscFunctionBegin; 2437 *type = MATSOLVERMUMPS; 2438 PetscFunctionReturn(0); 2439 } 2440 2441 /* MatGetFactor for Seq and MPI AIJ matrices */ 2442 #undef __FUNCT__ 2443 #define __FUNCT__ "MatGetFactor_aij_mumps" 2444 static PetscErrorCode MatGetFactor_aij_mumps(Mat A,MatFactorType ftype,Mat *F) 2445 { 2446 Mat B; 2447 PetscErrorCode ierr; 2448 Mat_MUMPS *mumps; 2449 PetscBool isSeqAIJ; 2450 2451 PetscFunctionBegin; 2452 /* Create the factorization matrix */ 2453 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); 2454 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2455 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2456 ierr = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); 2457 ierr = MatSetUp(B);CHKERRQ(ierr); 2458 2459 ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); 2460 2461 B->ops->view = MatView_MUMPS; 2462 B->ops->getinfo = MatGetInfo_MUMPS; 2463 2464 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); 2465 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); 2466 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); 2467 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); 2468 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); 2469 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); 2470 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); 2471 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); 2472 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); 2473 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); 2474 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); 2475 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); 2476 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); 2477 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); 2478 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_MUMPS);CHKERRQ(ierr); 2479 2480 if (ftype == MAT_FACTOR_LU) { 2481 B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMUMPS; 2482 B->factortype = MAT_FACTOR_LU; 2483 if (isSeqAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqaij_seqaij; 2484 else mumps->ConvertToTriples = MatConvertToTriples_mpiaij_mpiaij; 2485 mumps->sym = 0; 2486 } else { 2487 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MUMPS; 2488 B->factortype = MAT_FACTOR_CHOLESKY; 2489 if (isSeqAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqaij_seqsbaij; 2490 else mumps->ConvertToTriples = MatConvertToTriples_mpiaij_mpisbaij; 2491 #if defined(PETSC_USE_COMPLEX) 2492 mumps->sym = 2; 2493 #else 2494 if (A->spd_set && A->spd) mumps->sym = 1; 2495 else mumps->sym = 2; 2496 #endif 2497 } 2498 2499 /* set solvertype */ 2500 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 2501 ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); 2502 2503 mumps->isAIJ = PETSC_TRUE; 2504 B->ops->destroy = MatDestroy_MUMPS; 2505 B->data = (void*)mumps; 2506 2507 ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); 2508 2509 *F = B; 2510 PetscFunctionReturn(0); 2511 } 2512 2513 /* MatGetFactor for Seq and MPI SBAIJ matrices */ 2514 #undef __FUNCT__ 2515 #define __FUNCT__ "MatGetFactor_sbaij_mumps" 2516 static PetscErrorCode MatGetFactor_sbaij_mumps(Mat A,MatFactorType ftype,Mat *F) 2517 { 2518 Mat B; 2519 PetscErrorCode ierr; 2520 Mat_MUMPS *mumps; 2521 PetscBool isSeqSBAIJ; 2522 2523 PetscFunctionBegin; 2524 if (ftype != MAT_FACTOR_CHOLESKY) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with MUMPS LU, use AIJ matrix"); 2525 if (A->rmap->bs > 1) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with block size > 1 with MUMPS Cholesky, use AIJ matrix instead"); 2526 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); 2527 /* Create the factorization matrix */ 2528 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2529 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2530 ierr = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); 2531 ierr = MatSetUp(B);CHKERRQ(ierr); 2532 2533 ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); 2534 if (isSeqSBAIJ) { 2535 mumps->ConvertToTriples = MatConvertToTriples_seqsbaij_seqsbaij; 2536 } else { 2537 mumps->ConvertToTriples = MatConvertToTriples_mpisbaij_mpisbaij; 2538 } 2539 2540 B->ops->getinfo = MatGetInfo_External; 2541 B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MUMPS; 2542 B->ops->view = MatView_MUMPS; 2543 2544 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); 2545 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); 2546 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); 2547 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); 2548 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); 2549 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); 2550 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); 2551 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); 2552 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); 2553 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); 2554 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); 2555 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); 2556 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); 2557 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); 2558 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_MUMPS);CHKERRQ(ierr); 2559 2560 B->factortype = MAT_FACTOR_CHOLESKY; 2561 #if defined(PETSC_USE_COMPLEX) 2562 mumps->sym = 2; 2563 #else 2564 if (A->spd_set && A->spd) mumps->sym = 1; 2565 else mumps->sym = 2; 2566 #endif 2567 2568 /* set solvertype */ 2569 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 2570 ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); 2571 2572 mumps->isAIJ = PETSC_FALSE; 2573 B->ops->destroy = MatDestroy_MUMPS; 2574 B->data = (void*)mumps; 2575 2576 ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); 2577 2578 *F = B; 2579 PetscFunctionReturn(0); 2580 } 2581 2582 #undef __FUNCT__ 2583 #define __FUNCT__ "MatGetFactor_baij_mumps" 2584 static PetscErrorCode MatGetFactor_baij_mumps(Mat A,MatFactorType ftype,Mat *F) 2585 { 2586 Mat B; 2587 PetscErrorCode ierr; 2588 Mat_MUMPS *mumps; 2589 PetscBool isSeqBAIJ; 2590 2591 PetscFunctionBegin; 2592 /* Create the factorization matrix */ 2593 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); 2594 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2595 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2596 ierr = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); 2597 ierr = MatSetUp(B);CHKERRQ(ierr); 2598 2599 ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); 2600 if (ftype == MAT_FACTOR_LU) { 2601 B->ops->lufactorsymbolic = MatLUFactorSymbolic_BAIJMUMPS; 2602 B->factortype = MAT_FACTOR_LU; 2603 if (isSeqBAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqbaij_seqaij; 2604 else mumps->ConvertToTriples = MatConvertToTriples_mpibaij_mpiaij; 2605 mumps->sym = 0; 2606 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc BAIJ matrices with MUMPS Cholesky, use SBAIJ or AIJ matrix instead\n"); 2607 2608 B->ops->getinfo = MatGetInfo_External; 2609 B->ops->view = MatView_MUMPS; 2610 2611 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); 2612 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); 2613 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); 2614 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); 2615 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); 2616 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); 2617 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); 2618 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); 2619 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); 2620 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); 2621 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); 2622 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); 2623 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); 2624 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); 2625 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_MUMPS);CHKERRQ(ierr); 2626 2627 /* set solvertype */ 2628 ierr = PetscFree(B->solvertype);CHKERRQ(ierr); 2629 ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); 2630 2631 mumps->isAIJ = PETSC_TRUE; 2632 B->ops->destroy = MatDestroy_MUMPS; 2633 B->data = (void*)mumps; 2634 2635 ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); 2636 2637 *F = B; 2638 PetscFunctionReturn(0); 2639 } 2640 2641 #undef __FUNCT__ 2642 #define __FUNCT__ "MatSolverPackageRegister_MUMPS" 2643 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MUMPS(void) 2644 { 2645 PetscErrorCode ierr; 2646 2647 PetscFunctionBegin; 2648 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mumps);CHKERRQ(ierr); 2649 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mumps);CHKERRQ(ierr); 2650 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIBAIJ,MAT_FACTOR_LU,MatGetFactor_baij_mumps);CHKERRQ(ierr); 2651 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_baij_mumps);CHKERRQ(ierr); 2652 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPISBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 2653 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mumps);CHKERRQ(ierr); 2654 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mumps);CHKERRQ(ierr); 2655 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_baij_mumps);CHKERRQ(ierr); 2656 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_baij_mumps);CHKERRQ(ierr); 2657 ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 2658 PetscFunctionReturn(0); 2659 } 2660 2661