1 2 /* 3 Provides an interface to the LUSOL package of .... 4 5 */ 6 #include <../src/mat/impls/aij/seq/aij.h> 7 8 #if defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 9 #define LU1FAC lu1fac_ 10 #define LU6SOL lu6sol_ 11 #define M1PAGE m1page_ 12 #define M5SETX m5setx_ 13 #define M6RDEL m6rdel_ 14 #elif !defined(PETSC_HAVE_FORTRAN_CAPS) 15 #define LU1FAC lu1fac 16 #define LU6SOL lu6sol 17 #define M1PAGE m1page 18 #define M5SETX m5setx 19 #define M6RDEL m6rdel 20 #endif 21 22 /* 23 Dummy symbols that the MINOS files mi25bfac.f and mi15blas.f may require 24 */ 25 PETSC_EXTERN void PETSC_STDCALL M1PAGE() 26 { 27 ; 28 } 29 PETSC_EXTERN void PETSC_STDCALL M5SETX() 30 { 31 ; 32 } 33 34 PETSC_EXTERN void PETSC_STDCALL M6RDEL() 35 { 36 ; 37 } 38 39 PETSC_EXTERN void PETSC_STDCALL LU1FAC(int *m, int *n, int *nnz, int *size, int *luparm, 40 double *parmlu, double *data, int *indc, int *indr, 41 int *rowperm, int *colperm, int *collen, int *rowlen, 42 int *colstart, int *rowstart, int *rploc, int *cploc, 43 int *rpinv, int *cpinv, double *w, int *inform); 44 45 PETSC_EXTERN void PETSC_STDCALL LU6SOL(int *mode, int *m, int *n, double *rhs, double *x, 46 int *size, int *luparm, double *parmlu, double *data, 47 int *indc, int *indr, int *rowperm, int *colperm, 48 int *collen, int *rowlen, int *colstart, int *rowstart, 49 int *inform); 50 51 extern PetscErrorCode MatDuplicate_LUSOL(Mat,MatDuplicateOption,Mat*); 52 53 typedef struct { 54 double *data; 55 int *indc; 56 int *indr; 57 58 int *ip; 59 int *iq; 60 int *lenc; 61 int *lenr; 62 int *locc; 63 int *locr; 64 int *iploc; 65 int *iqloc; 66 int *ipinv; 67 int *iqinv; 68 double *mnsw; 69 double *mnsv; 70 71 double elbowroom; 72 double luroom; /* Extra space allocated when factor fails */ 73 double parmlu[30]; /* Input/output to LUSOL */ 74 75 int n; /* Number of rows/columns in matrix */ 76 int nz; /* Number of nonzeros */ 77 int nnz; /* Number of nonzeros allocated for factors */ 78 int luparm[30]; /* Input/output to LUSOL */ 79 80 PetscBool CleanUpLUSOL; 81 82 } Mat_LUSOL; 83 84 /* LUSOL input/Output Parameters (Description uses C-style indexes 85 * 86 * Input parameters Typical value 87 * 88 * luparm(0) = nout File number for printed messages. 6 89 * luparm(1) = lprint Print level. 0 90 * < 0 suppresses output. 91 * = 0 gives error messages. 92 * = 1 gives debug output from some of the 93 * other routines in LUSOL. 94 * >= 2 gives the pivot row and column and the 95 * no. of rows and columns involved at 96 * each elimination step in lu1fac. 97 * luparm(2) = maxcol lu1fac: maximum number of columns 5 98 * searched allowed in a Markowitz-type 99 * search for the next pivot element. 100 * For some of the factorization, the 101 * number of rows searched is 102 * maxrow = maxcol - 1. 103 * 104 * 105 * Output parameters 106 * 107 * luparm(9) = inform Return code from last call to any LU routine. 108 * luparm(10) = nsing No. of singularities marked in the 109 * output array w(*). 110 * luparm(11) = jsing Column index of last singularity. 111 * luparm(12) = minlen Minimum recommended value for lena. 112 * luparm(13) = maxlen ? 113 * luparm(14) = nupdat No. of updates performed by the lu8 routines. 114 * luparm(15) = nrank No. of nonempty rows of U. 115 * luparm(16) = ndens1 No. of columns remaining when the density of 116 * the matrix being factorized reached dens1. 117 * luparm(17) = ndens2 No. of columns remaining when the density of 118 * the matrix being factorized reached dens2. 119 * luparm(18) = jumin The column index associated with dumin. 120 * luparm(19) = numl0 No. of columns in initial L. 121 * luparm(20) = lenl0 Size of initial L (no. of nonzeros). 122 * luparm(21) = lenu0 Size of initial U. 123 * luparm(22) = lenl Size of current L. 124 * luparm(23) = lenu Size of current U. 125 * luparm(24) = lrow Length of row file. 126 * luparm(25) = ncp No. of compressions of LU data structures. 127 * luparm(26) = mersum lu1fac: sum of Markowitz merit counts. 128 * luparm(27) = nutri lu1fac: triangular rows in U. 129 * luparm(28) = nltri lu1fac: triangular rows in L. 130 * luparm(29) = 131 * 132 * 133 * Input parameters Typical value 134 * 135 * parmlu(0) = elmax1 Max multiplier allowed in L 10.0 136 * during factor. 137 * parmlu(1) = elmax2 Max multiplier allowed in L 10.0 138 * during updates. 139 * parmlu(2) = small Absolute tolerance for eps**0.8 140 * treating reals as zero. IBM double: 3.0d-13 141 * parmlu(3) = utol1 Absolute tol for flagging eps**0.66667 142 * small diagonals of U. IBM double: 3.7d-11 143 * parmlu(4) = utol2 Relative tol for flagging eps**0.66667 144 * small diagonals of U. IBM double: 3.7d-11 145 * parmlu(5) = uspace Factor limiting waste space in U. 3.0 146 * In lu1fac, the row or column lists 147 * are compressed if their length 148 * exceeds uspace times the length of 149 * either file after the last compression. 150 * parmlu(6) = dens1 The density at which the Markowitz 0.3 151 * strategy should search maxcol columns 152 * and no rows. 153 * parmlu(7) = dens2 the density at which the Markowitz 0.6 154 * strategy should search only 1 column 155 * or (preferably) use a dense LU for 156 * all the remaining rows and columns. 157 * 158 * 159 * Output parameters 160 * 161 * parmlu(9) = amax Maximum element in A. 162 * parmlu(10) = elmax Maximum multiplier in current L. 163 * parmlu(11) = umax Maximum element in current U. 164 * parmlu(12) = dumax Maximum diagonal in U. 165 * parmlu(13) = dumin Minimum diagonal in U. 166 * parmlu(14) = 167 * parmlu(15) = 168 * parmlu(16) = 169 * parmlu(17) = 170 * parmlu(18) = 171 * parmlu(19) = resid lu6sol: residual after solve with U or U'. 172 * ... 173 * parmlu(29) = 174 */ 175 176 #define Factorization_Tolerance 1e-1 177 #define Factorization_Pivot_Tolerance pow(2.2204460492503131E-16, 2.0 / 3.0) 178 #define Factorization_Small_Tolerance 1e-15 /* pow(DBL_EPSILON, 0.8) */ 179 180 #undef __FUNCT__ 181 #define __FUNCT__ "MatDestroy_LUSOL" 182 PetscErrorCode MatDestroy_LUSOL(Mat A) 183 { 184 PetscErrorCode ierr; 185 Mat_LUSOL *lusol=(Mat_LUSOL*)A->spptr; 186 187 PetscFunctionBegin; 188 if (lusol && lusol->CleanUpLUSOL) { 189 ierr = PetscFree(lusol->ip);CHKERRQ(ierr); 190 ierr = PetscFree(lusol->iq);CHKERRQ(ierr); 191 ierr = PetscFree(lusol->lenc);CHKERRQ(ierr); 192 ierr = PetscFree(lusol->lenr);CHKERRQ(ierr); 193 ierr = PetscFree(lusol->locc);CHKERRQ(ierr); 194 ierr = PetscFree(lusol->locr);CHKERRQ(ierr); 195 ierr = PetscFree(lusol->iploc);CHKERRQ(ierr); 196 ierr = PetscFree(lusol->iqloc);CHKERRQ(ierr); 197 ierr = PetscFree(lusol->ipinv);CHKERRQ(ierr); 198 ierr = PetscFree(lusol->iqinv);CHKERRQ(ierr); 199 ierr = PetscFree(lusol->mnsw);CHKERRQ(ierr); 200 ierr = PetscFree(lusol->mnsv);CHKERRQ(ierr); 201 ierr = PetscFree3(lusol->data,lusol->indc,lusol->indr);CHKERRQ(ierr); 202 } 203 ierr = PetscFree(A->spptr);CHKERRQ(ierr); 204 ierr = MatDestroy_SeqAIJ(A);CHKERRQ(ierr); 205 PetscFunctionReturn(0); 206 } 207 208 #undef __FUNCT__ 209 #define __FUNCT__ "MatSolve_LUSOL" 210 PetscErrorCode MatSolve_LUSOL(Mat A,Vec b,Vec x) 211 { 212 Mat_LUSOL *lusol=(Mat_LUSOL*)A->spptr; 213 double *bb,*xx; 214 int mode=5; 215 PetscErrorCode ierr; 216 int i,m,n,nnz,status; 217 218 PetscFunctionBegin; 219 ierr = VecGetArray(x, &xx);CHKERRQ(ierr); 220 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 221 222 m = n = lusol->n; 223 nnz = lusol->nnz; 224 225 for (i = 0; i < m; i++) lusol->mnsv[i] = bb[i]; 226 227 LU6SOL(&mode, &m, &n, lusol->mnsv, xx, &nnz, 228 lusol->luparm, lusol->parmlu, lusol->data, 229 lusol->indc, lusol->indr, lusol->ip, lusol->iq, 230 lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, &status); 231 232 if (status) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"solve failed, error code %d",status); 233 234 ierr = VecRestoreArray(x, &xx);CHKERRQ(ierr); 235 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 236 PetscFunctionReturn(0); 237 } 238 239 #undef __FUNCT__ 240 #define __FUNCT__ "MatLUFactorNumeric_LUSOL" 241 PetscErrorCode MatLUFactorNumeric_LUSOL(Mat F,Mat A,const MatFactorInfo *info) 242 { 243 Mat_SeqAIJ *a; 244 Mat_LUSOL *lusol = (Mat_LUSOL*)F->spptr; 245 PetscErrorCode ierr; 246 int m, n, nz, nnz, status; 247 int i, rs, re; 248 int factorizations; 249 250 PetscFunctionBegin; 251 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr);CHKERRQ(ierr); 252 a = (Mat_SeqAIJ*)A->data; 253 254 if (m != lusol->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"factorization struct inconsistent"); 255 256 factorizations = 0; 257 do { 258 /*******************************************************************/ 259 /* Check the workspace allocation. */ 260 /*******************************************************************/ 261 262 nz = a->nz; 263 nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom*nz)); 264 nnz = PetscMax(nnz, 5*n); 265 266 if (nnz < lusol->luparm[12]) { 267 nnz = (int)(lusol->luroom * lusol->luparm[12]); 268 } else if ((factorizations > 0) && (lusol->luroom < 6)) { 269 lusol->luroom += 0.1; 270 } 271 272 nnz = PetscMax(nnz, (int)(lusol->luroom*(lusol->luparm[22] + lusol->luparm[23]))); 273 274 if (nnz > lusol->nnz) { 275 ierr = PetscFree3(lusol->data,lusol->indc,lusol->indr);CHKERRQ(ierr); 276 ierr = PetscMalloc3(nnz,&lusol->data,nnz,&lusol->indc,nnz,&lusol->indr);CHKERRQ(ierr); 277 lusol->nnz = nnz; 278 } 279 280 /*******************************************************************/ 281 /* Fill in the data for the problem. (1-based Fortran style) */ 282 /*******************************************************************/ 283 284 nz = 0; 285 for (i = 0; i < n; i++) { 286 rs = a->i[i]; 287 re = a->i[i+1]; 288 289 while (rs < re) { 290 if (a->a[rs] != 0.0) { 291 lusol->indc[nz] = i + 1; 292 lusol->indr[nz] = a->j[rs] + 1; 293 lusol->data[nz] = a->a[rs]; 294 nz++; 295 } 296 rs++; 297 } 298 } 299 300 /*******************************************************************/ 301 /* Do the factorization. */ 302 /*******************************************************************/ 303 304 LU1FAC(&m, &n, &nz, &nnz, 305 lusol->luparm, lusol->parmlu, lusol->data, 306 lusol->indc, lusol->indr, lusol->ip, lusol->iq, 307 lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, 308 lusol->iploc, lusol->iqloc, lusol->ipinv, 309 lusol->iqinv, lusol->mnsw, &status); 310 311 switch (status) { 312 case 0: /* factored */ 313 break; 314 315 case 7: /* insufficient memory */ 316 break; 317 318 case 1: 319 case -1: /* singular */ 320 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Singular matrix"); 321 322 case 3: 323 case 4: /* error conditions */ 324 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"matrix error"); 325 326 default: /* unknown condition */ 327 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"matrix unknown return code"); 328 } 329 330 factorizations++; 331 } while (status == 7); 332 F->ops->solve = MatSolve_LUSOL; 333 F->assembled = PETSC_TRUE; 334 F->preallocated = PETSC_TRUE; 335 PetscFunctionReturn(0); 336 } 337 338 #undef __FUNCT__ 339 #define __FUNCT__ "MatLUFactorSymbolic_LUSOL" 340 PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat F,Mat A, IS r, IS c,const MatFactorInfo *info) 341 { 342 /************************************************************************/ 343 /* Input */ 344 /* A - matrix to factor */ 345 /* r - row permutation (ignored) */ 346 /* c - column permutation (ignored) */ 347 /* */ 348 /* Output */ 349 /* F - matrix storing the factorization; */ 350 /************************************************************************/ 351 Mat_LUSOL *lusol; 352 PetscErrorCode ierr; 353 int i, m, n, nz, nnz; 354 355 PetscFunctionBegin; 356 /************************************************************************/ 357 /* Check the arguments. */ 358 /************************************************************************/ 359 360 ierr = MatGetSize(A, &m, &n);CHKERRQ(ierr); 361 nz = ((Mat_SeqAIJ*)A->data)->nz; 362 363 /************************************************************************/ 364 /* Create the factorization. */ 365 /************************************************************************/ 366 367 F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL; 368 lusol = (Mat_LUSOL*)(F->spptr); 369 370 /************************************************************************/ 371 /* Initialize parameters */ 372 /************************************************************************/ 373 374 for (i = 0; i < 30; i++) { 375 lusol->luparm[i] = 0; 376 lusol->parmlu[i] = 0; 377 } 378 379 lusol->luparm[1] = -1; 380 lusol->luparm[2] = 5; 381 lusol->luparm[7] = 1; 382 383 lusol->parmlu[0] = 1 / Factorization_Tolerance; 384 lusol->parmlu[1] = 1 / Factorization_Tolerance; 385 lusol->parmlu[2] = Factorization_Small_Tolerance; 386 lusol->parmlu[3] = Factorization_Pivot_Tolerance; 387 lusol->parmlu[4] = Factorization_Pivot_Tolerance; 388 lusol->parmlu[5] = 3.0; 389 lusol->parmlu[6] = 0.3; 390 lusol->parmlu[7] = 0.6; 391 392 /************************************************************************/ 393 /* Allocate the workspace needed by LUSOL. */ 394 /************************************************************************/ 395 396 lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill); 397 nnz = PetscMax((int)(lusol->elbowroom*nz), 5*n); 398 399 lusol->n = n; 400 lusol->nz = nz; 401 lusol->nnz = nnz; 402 lusol->luroom = 1.75; 403 404 ierr = PetscMalloc(sizeof(int)*n,&lusol->ip); 405 ierr = PetscMalloc(sizeof(int)*n,&lusol->iq); 406 ierr = PetscMalloc(sizeof(int)*n,&lusol->lenc); 407 ierr = PetscMalloc(sizeof(int)*n,&lusol->lenr); 408 ierr = PetscMalloc(sizeof(int)*n,&lusol->locc); 409 ierr = PetscMalloc(sizeof(int)*n,&lusol->locr); 410 ierr = PetscMalloc(sizeof(int)*n,&lusol->iploc); 411 ierr = PetscMalloc(sizeof(int)*n,&lusol->iqloc); 412 ierr = PetscMalloc(sizeof(int)*n,&lusol->ipinv); 413 ierr = PetscMalloc(sizeof(int)*n,&lusol->iqinv); 414 ierr = PetscMalloc(sizeof(double)*n,&lusol->mnsw); 415 ierr = PetscMalloc(sizeof(double)*n,&lusol->mnsv); 416 417 ierr = PetscMalloc3(nnz,&lusol->data,nnz,&lusol->indc,nnz,&lusol->indr);CHKERRQ(ierr); 418 419 lusol->CleanUpLUSOL = PETSC_TRUE; 420 F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL; 421 PetscFunctionReturn(0); 422 } 423 424 #undef __FUNCT__ 425 #define __FUNCT__ "MatFactorGetSolverPackage_seqaij_lusol" 426 PetscErrorCode MatFactorGetSolverPackage_seqaij_lusol(Mat A,const MatSolverPackage *type) 427 { 428 PetscFunctionBegin; 429 *type = MATSOLVERLUSOL; 430 PetscFunctionReturn(0); 431 } 432 433 #undef __FUNCT__ 434 #define __FUNCT__ "MatGetFactor_seqaij_lusol" 435 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat A,MatFactorType ftype,Mat *F) 436 { 437 Mat B; 438 Mat_LUSOL *lusol; 439 PetscErrorCode ierr; 440 int m, n; 441 442 PetscFunctionBegin; 443 ierr = MatGetSize(A, &m, &n);CHKERRQ(ierr); 444 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 445 ierr = MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,m,n);CHKERRQ(ierr); 446 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 447 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 448 449 ierr = PetscNewLog(B,&lusol);CHKERRQ(ierr); 450 B->spptr = lusol; 451 452 B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL; 453 B->ops->destroy = MatDestroy_LUSOL; 454 455 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_seqaij_lusol);CHKERRQ(ierr); 456 457 B->factortype = MAT_FACTOR_LU; 458 PetscFunctionReturn(0); 459 } 460 461 #undef __FUNCT__ 462 #define __FUNCT__ "MatSolverPackageRegister_Lusol" 463 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_Lusol(void) 464 { 465 PetscErrorCode ierr; 466 467 PetscFunctionBegin; 468 ierr = MatSolverPackageRegister(MATSOLVERLUSOL,MATSEQAIJ, MAT_FACTOR_LU,MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 469 PetscFunctionReturn(0); 470 } 471 472 /*MC 473 MATSOLVERLUSOL - "lusol" - Provides direct solvers (LU) for sequential matrices 474 via the external package LUSOL. 475 476 If LUSOL is installed (see the manual for 477 instructions on how to declare the existence of external packages), 478 479 Works with MATSEQAIJ matrices 480 481 Level: beginner 482 483 .seealso: PCLU, PCFactorSetMatSolverPackage(), MatSolverPackage 484 485 M*/ 486