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