1 /*$Id: sbaij.c,v 1.62 2001/08/07 03:03:01 balay Exp $*/ 2 3 /* 4 Defines the basic matrix operations for the SBAIJ (compressed row) 5 matrix storage format. 6 */ 7 #include "src/mat/impls/baij/seq/baij.h" /*I "petscmat.h" I*/ 8 #include "src/inline/spops.h" 9 #include "src/mat/impls/sbaij/seq/sbaij.h" 10 11 #define CHUNKSIZE 10 12 13 /* 14 Checks for missing diagonals 15 */ 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatMissingDiagonal_SeqSBAIJ" 18 int MatMissingDiagonal_SeqSBAIJ(Mat A) 19 { 20 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 21 int *diag,*jj = a->j,i,ierr; 22 23 PetscFunctionBegin; 24 ierr = MatMarkDiagonal_SeqSBAIJ(A);CHKERRQ(ierr); 25 diag = a->diag; 26 for (i=0; i<a->mbs; i++) { 27 if (jj[diag[i]] != i) SETERRQ1(1,"Matrix is missing diagonal number %d",i); 28 } 29 PetscFunctionReturn(0); 30 } 31 32 #undef __FUNCT__ 33 #define __FUNCT__ "MatMarkDiagonal_SeqSBAIJ" 34 int MatMarkDiagonal_SeqSBAIJ(Mat A) 35 { 36 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 37 int i,mbs = a->mbs,ierr; 38 39 PetscFunctionBegin; 40 if (a->diag) PetscFunctionReturn(0); 41 42 ierr = PetscMalloc((mbs+1)*sizeof(int),&a->diag);CHKERRQ(ierr); 43 PetscLogObjectMemory(A,(mbs+1)*sizeof(int)); 44 for (i=0; i<mbs; i++) a->diag[i] = a->i[i]; 45 PetscFunctionReturn(0); 46 } 47 48 #undef __FUNCT__ 49 #define __FUNCT__ "MatGetRowIJ_SeqSBAIJ" 50 static int MatGetRowIJ_SeqSBAIJ(Mat A,int oshift,PetscTruth symmetric,int *nn,int *ia[],int *ja[],PetscTruth *done) 51 { 52 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 53 int n = a->mbs,i; 54 55 PetscFunctionBegin; 56 *nn = n; 57 if (!ia) PetscFunctionReturn(0); 58 59 if (oshift == 1) { 60 /* temporarily add 1 to i and j indices */ 61 int nz = a->i[n]; 62 for (i=0; i<nz; i++) a->j[i]++; 63 for (i=0; i<n+1; i++) a->i[i]++; 64 *ia = a->i; *ja = a->j; 65 } else { 66 *ia = a->i; *ja = a->j; 67 } 68 PetscFunctionReturn(0); 69 } 70 71 #undef __FUNCT__ 72 #define __FUNCT__ "MatRestoreRowIJ_SeqSBAIJ" 73 static int MatRestoreRowIJ_SeqSBAIJ(Mat A,int oshift,PetscTruth symmetric,int *nn,int *ia[],int *ja[],PetscTruth *done) 74 { 75 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 76 int i,n = a->mbs; 77 78 PetscFunctionBegin; 79 if (!ia) PetscFunctionReturn(0); 80 81 if (oshift == 1) { 82 int nz = a->i[n]-1; 83 for (i=0; i<nz; i++) a->j[i]--; 84 for (i=0; i<n+1; i++) a->i[i]--; 85 } 86 PetscFunctionReturn(0); 87 } 88 89 #undef __FUNCT__ 90 #define __FUNCT__ "MatGetBlockSize_SeqSBAIJ" 91 int MatGetBlockSize_SeqSBAIJ(Mat mat,int *bs) 92 { 93 Mat_SeqSBAIJ *sbaij = (Mat_SeqSBAIJ*)mat->data; 94 95 PetscFunctionBegin; 96 *bs = sbaij->bs; 97 PetscFunctionReturn(0); 98 } 99 100 #undef __FUNCT__ 101 #define __FUNCT__ "MatDestroy_SeqSBAIJ" 102 int MatDestroy_SeqSBAIJ(Mat A) 103 { 104 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 105 int ierr; 106 107 PetscFunctionBegin; 108 #if defined(PETSC_USE_LOG) 109 PetscLogObjectState((PetscObject)A,"Rows=%d, NZ=%d",A->m,a->nz); 110 #endif 111 ierr = PetscFree(a->a);CHKERRQ(ierr); 112 if (!a->singlemalloc) { 113 ierr = PetscFree(a->i);CHKERRQ(ierr); 114 ierr = PetscFree(a->j);CHKERRQ(ierr); 115 } 116 if (a->row) { 117 ierr = ISDestroy(a->row);CHKERRQ(ierr); 118 } 119 if (a->diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} 120 if (a->ilen) {ierr = PetscFree(a->ilen);CHKERRQ(ierr);} 121 if (a->imax) {ierr = PetscFree(a->imax);CHKERRQ(ierr);} 122 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} 123 if (a->solve_work) {ierr = PetscFree(a->solve_work);CHKERRQ(ierr);} 124 if (a->solves_work) {ierr = PetscFree(a->solves_work);CHKERRQ(ierr);} 125 if (a->mult_work) {ierr = PetscFree(a->mult_work);CHKERRQ(ierr);} 126 if (a->saved_values) {ierr = PetscFree(a->saved_values);CHKERRQ(ierr);} 127 if (a->xtoy) {ierr = PetscFree(a->xtoy);CHKERRQ(ierr);} 128 129 if (a->inew){ 130 ierr = PetscFree(a->inew);CHKERRQ(ierr); 131 a->inew = 0; 132 } 133 ierr = PetscFree(a);CHKERRQ(ierr); 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNCT__ 138 #define __FUNCT__ "MatSetOption_SeqSBAIJ" 139 int MatSetOption_SeqSBAIJ(Mat A,MatOption op) 140 { 141 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 142 143 PetscFunctionBegin; 144 switch (op) { 145 case MAT_ROW_ORIENTED: 146 a->roworiented = PETSC_TRUE; 147 break; 148 case MAT_COLUMN_ORIENTED: 149 a->roworiented = PETSC_FALSE; 150 break; 151 case MAT_COLUMNS_SORTED: 152 a->sorted = PETSC_TRUE; 153 break; 154 case MAT_COLUMNS_UNSORTED: 155 a->sorted = PETSC_FALSE; 156 break; 157 case MAT_KEEP_ZEROED_ROWS: 158 a->keepzeroedrows = PETSC_TRUE; 159 break; 160 case MAT_NO_NEW_NONZERO_LOCATIONS: 161 a->nonew = 1; 162 break; 163 case MAT_NEW_NONZERO_LOCATION_ERR: 164 a->nonew = -1; 165 break; 166 case MAT_NEW_NONZERO_ALLOCATION_ERR: 167 a->nonew = -2; 168 break; 169 case MAT_YES_NEW_NONZERO_LOCATIONS: 170 a->nonew = 0; 171 break; 172 case MAT_ROWS_SORTED: 173 case MAT_ROWS_UNSORTED: 174 case MAT_YES_NEW_DIAGONALS: 175 case MAT_IGNORE_OFF_PROC_ENTRIES: 176 case MAT_USE_HASH_TABLE: 177 PetscLogInfo(A,"MatSetOption_SeqSBAIJ:Option ignored\n"); 178 break; 179 case MAT_NO_NEW_DIAGONALS: 180 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 181 case MAT_NOT_SYMMETRIC: 182 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 183 case MAT_HERMITIAN: 184 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 185 case MAT_SYMMETRIC: 186 case MAT_STRUCTURALLY_SYMMETRIC: 187 case MAT_NOT_HERMITIAN: 188 case MAT_SYMMETRY_ETERNAL: 189 case MAT_NOT_SYMMETRY_ETERNAL: 190 break; 191 default: 192 SETERRQ(PETSC_ERR_SUP,"unknown option"); 193 } 194 PetscFunctionReturn(0); 195 } 196 197 #undef __FUNCT__ 198 #define __FUNCT__ "MatGetRow_SeqSBAIJ" 199 int MatGetRow_SeqSBAIJ(Mat A,int row,int *ncols,int **cols,PetscScalar **v) 200 { 201 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 202 int itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*cols_i,bs2,ierr; 203 MatScalar *aa,*aa_i; 204 PetscScalar *v_i; 205 206 PetscFunctionBegin; 207 bs = a->bs; 208 ai = a->i; 209 aj = a->j; 210 aa = a->a; 211 bs2 = a->bs2; 212 213 if (row < 0 || row >= A->m) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE, "Row %d out of range", row); 214 215 bn = row/bs; /* Block number */ 216 bp = row % bs; /* Block position */ 217 M = ai[bn+1] - ai[bn]; 218 *ncols = bs*M; 219 220 if (v) { 221 *v = 0; 222 if (*ncols) { 223 ierr = PetscMalloc((*ncols+row)*sizeof(PetscScalar),v);CHKERRQ(ierr); 224 for (i=0; i<M; i++) { /* for each block in the block row */ 225 v_i = *v + i*bs; 226 aa_i = aa + bs2*(ai[bn] + i); 227 for (j=bp,k=0; j<bs2; j+=bs,k++) {v_i[k] = aa_i[j];} 228 } 229 } 230 } 231 232 if (cols) { 233 *cols = 0; 234 if (*ncols) { 235 ierr = PetscMalloc((*ncols+row)*sizeof(int),cols);CHKERRQ(ierr); 236 for (i=0; i<M; i++) { /* for each block in the block row */ 237 cols_i = *cols + i*bs; 238 itmp = bs*aj[ai[bn] + i]; 239 for (j=0; j<bs; j++) {cols_i[j] = itmp++;} 240 } 241 } 242 } 243 244 /*search column A(0:row-1,row) (=A(row,0:row-1)). Could be expensive! */ 245 /* this segment is currently removed, so only entries in the upper triangle are obtained */ 246 #ifdef column_search 247 v_i = *v + M*bs; 248 cols_i = *cols + M*bs; 249 for (i=0; i<bn; i++){ /* for each block row */ 250 M = ai[i+1] - ai[i]; 251 for (j=0; j<M; j++){ 252 itmp = aj[ai[i] + j]; /* block column value */ 253 if (itmp == bn){ 254 aa_i = aa + bs2*(ai[i] + j) + bs*bp; 255 for (k=0; k<bs; k++) { 256 *cols_i++ = i*bs+k; 257 *v_i++ = aa_i[k]; 258 } 259 *ncols += bs; 260 break; 261 } 262 } 263 } 264 #endif 265 266 PetscFunctionReturn(0); 267 } 268 269 #undef __FUNCT__ 270 #define __FUNCT__ "MatRestoreRow_SeqSBAIJ" 271 int MatRestoreRow_SeqSBAIJ(Mat A,int row,int *nz,int **idx,PetscScalar **v) 272 { 273 int ierr; 274 275 PetscFunctionBegin; 276 if (idx) {if (*idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);}} 277 if (v) {if (*v) {ierr = PetscFree(*v);CHKERRQ(ierr);}} 278 PetscFunctionReturn(0); 279 } 280 281 #undef __FUNCT__ 282 #define __FUNCT__ "MatTranspose_SeqSBAIJ" 283 int MatTranspose_SeqSBAIJ(Mat A,Mat *B) 284 { 285 int ierr; 286 PetscFunctionBegin; 287 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 288 PetscFunctionReturn(0); 289 } 290 291 #undef __FUNCT__ 292 #define __FUNCT__ "MatView_SeqSBAIJ_ASCII" 293 static int MatView_SeqSBAIJ_ASCII(Mat A,PetscViewer viewer) 294 { 295 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 296 int ierr,i,j,bs = a->bs,k,l,bs2=a->bs2; 297 char *name; 298 PetscViewerFormat format; 299 300 PetscFunctionBegin; 301 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 302 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 303 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 304 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 305 } else if (format == PETSC_VIEWER_ASCII_MATLAB) { 306 SETERRQ(PETSC_ERR_SUP,"Matlab format not supported"); 307 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 308 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 309 for (i=0; i<a->mbs; i++) { 310 for (j=0; j<bs; j++) { 311 ierr = PetscViewerASCIIPrintf(viewer,"row %d:",i*bs+j);CHKERRQ(ierr); 312 for (k=a->i[i]; k<a->i[i+1]; k++) { 313 for (l=0; l<bs; l++) { 314 #if defined(PETSC_USE_COMPLEX) 315 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 316 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g + %g i) ",bs*a->j[k]+l, 317 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 318 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 319 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g - %g i) ",bs*a->j[k]+l, 320 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 321 } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 322 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 323 } 324 #else 325 if (a->a[bs2*k + l*bs + j] != 0.0) { 326 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 327 } 328 #endif 329 } 330 } 331 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 332 } 333 } 334 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 335 } else { 336 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 337 for (i=0; i<a->mbs; i++) { 338 for (j=0; j<bs; j++) { 339 ierr = PetscViewerASCIIPrintf(viewer,"row %d:",i*bs+j);CHKERRQ(ierr); 340 for (k=a->i[i]; k<a->i[i+1]; k++) { 341 for (l=0; l<bs; l++) { 342 #if defined(PETSC_USE_COMPLEX) 343 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) { 344 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g + %g i) ",bs*a->j[k]+l, 345 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 346 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { 347 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g - %g i) ",bs*a->j[k]+l, 348 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 349 } else { 350 ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 351 } 352 #else 353 ierr = PetscViewerASCIIPrintf(viewer," %d %g ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 354 #endif 355 } 356 } 357 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 358 } 359 } 360 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 361 } 362 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 363 PetscFunctionReturn(0); 364 } 365 366 #undef __FUNCT__ 367 #define __FUNCT__ "MatView_SeqSBAIJ_Draw_Zoom" 368 static int MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 369 { 370 Mat A = (Mat) Aa; 371 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 372 int row,ierr,i,j,k,l,mbs=a->mbs,color,bs=a->bs,bs2=a->bs2,rank; 373 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 374 MatScalar *aa; 375 MPI_Comm comm; 376 PetscViewer viewer; 377 378 PetscFunctionBegin; 379 /* 380 This is nasty. If this is called from an originally parallel matrix 381 then all processes call this,but only the first has the matrix so the 382 rest should return immediately. 383 */ 384 ierr = PetscObjectGetComm((PetscObject)draw,&comm);CHKERRQ(ierr); 385 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 386 if (rank) PetscFunctionReturn(0); 387 388 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 389 390 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 391 PetscDrawString(draw, .3*(xl+xr), .3*(yl+yr), PETSC_DRAW_BLACK, "symmetric"); 392 393 /* loop over matrix elements drawing boxes */ 394 color = PETSC_DRAW_BLUE; 395 for (i=0,row=0; i<mbs; i++,row+=bs) { 396 for (j=a->i[i]; j<a->i[i+1]; j++) { 397 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 398 x_l = a->j[j]*bs; x_r = x_l + 1.0; 399 aa = a->a + j*bs2; 400 for (k=0; k<bs; k++) { 401 for (l=0; l<bs; l++) { 402 if (PetscRealPart(*aa++) >= 0.) continue; 403 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 404 } 405 } 406 } 407 } 408 color = PETSC_DRAW_CYAN; 409 for (i=0,row=0; i<mbs; i++,row+=bs) { 410 for (j=a->i[i]; j<a->i[i+1]; j++) { 411 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 412 x_l = a->j[j]*bs; x_r = x_l + 1.0; 413 aa = a->a + j*bs2; 414 for (k=0; k<bs; k++) { 415 for (l=0; l<bs; l++) { 416 if (PetscRealPart(*aa++) != 0.) continue; 417 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 418 } 419 } 420 } 421 } 422 423 color = PETSC_DRAW_RED; 424 for (i=0,row=0; i<mbs; i++,row+=bs) { 425 for (j=a->i[i]; j<a->i[i+1]; j++) { 426 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 427 x_l = a->j[j]*bs; x_r = x_l + 1.0; 428 aa = a->a + j*bs2; 429 for (k=0; k<bs; k++) { 430 for (l=0; l<bs; l++) { 431 if (PetscRealPart(*aa++) <= 0.) continue; 432 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 433 } 434 } 435 } 436 } 437 PetscFunctionReturn(0); 438 } 439 440 #undef __FUNCT__ 441 #define __FUNCT__ "MatView_SeqSBAIJ_Draw" 442 static int MatView_SeqSBAIJ_Draw(Mat A,PetscViewer viewer) 443 { 444 int ierr; 445 PetscReal xl,yl,xr,yr,w,h; 446 PetscDraw draw; 447 PetscTruth isnull; 448 449 PetscFunctionBegin; 450 451 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 452 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 453 454 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 455 xr = A->m; yr = A->m; h = yr/10.0; w = xr/10.0; 456 xr += w; yr += h; xl = -w; yl = -h; 457 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 458 ierr = PetscDrawZoom(draw,MatView_SeqSBAIJ_Draw_Zoom,A);CHKERRQ(ierr); 459 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 460 PetscFunctionReturn(0); 461 } 462 463 #undef __FUNCT__ 464 #define __FUNCT__ "MatView_SeqSBAIJ" 465 int MatView_SeqSBAIJ(Mat A,PetscViewer viewer) 466 { 467 int ierr; 468 PetscTruth isascii,isdraw; 469 470 PetscFunctionBegin; 471 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 472 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 473 if (isascii){ 474 ierr = MatView_SeqSBAIJ_ASCII(A,viewer);CHKERRQ(ierr); 475 } else if (isdraw) { 476 ierr = MatView_SeqSBAIJ_Draw(A,viewer);CHKERRQ(ierr); 477 } else { 478 Mat B; 479 ierr = MatConvert(A,MATSEQAIJ,&B);CHKERRQ(ierr); 480 ierr = MatView(B,viewer);CHKERRQ(ierr); 481 ierr = MatDestroy(B);CHKERRQ(ierr); 482 } 483 PetscFunctionReturn(0); 484 } 485 486 487 #undef __FUNCT__ 488 #define __FUNCT__ "MatGetValues_SeqSBAIJ" 489 int MatGetValues_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],PetscScalar v[]) 490 { 491 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 492 int *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 493 int *ai = a->i,*ailen = a->ilen; 494 int brow,bcol,ridx,cidx,bs=a->bs,bs2=a->bs2; 495 MatScalar *ap,*aa = a->a,zero = 0.0; 496 497 PetscFunctionBegin; 498 for (k=0; k<m; k++) { /* loop over rows */ 499 row = im[k]; brow = row/bs; 500 if (row < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %d",row); 501 if (row >= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,A->m-1); 502 rp = aj + ai[brow] ; ap = aa + bs2*ai[brow] ; 503 nrow = ailen[brow]; 504 for (l=0; l<n; l++) { /* loop over columns */ 505 if (in[l] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %d",in[l]); 506 if (in[l] >= A->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[l],A->n-1); 507 col = in[l] ; 508 bcol = col/bs; 509 cidx = col%bs; 510 ridx = row%bs; 511 high = nrow; 512 low = 0; /* assume unsorted */ 513 while (high-low > 5) { 514 t = (low+high)/2; 515 if (rp[t] > bcol) high = t; 516 else low = t; 517 } 518 for (i=low; i<high; i++) { 519 if (rp[i] > bcol) break; 520 if (rp[i] == bcol) { 521 *v++ = ap[bs2*i+bs*cidx+ridx]; 522 goto finished; 523 } 524 } 525 *v++ = zero; 526 finished:; 527 } 528 } 529 PetscFunctionReturn(0); 530 } 531 532 533 #undef __FUNCT__ 534 #define __FUNCT__ "MatSetValuesBlocked_SeqSBAIJ" 535 int MatSetValuesBlocked_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode is) 536 { 537 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 538 int *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,sorted=a->sorted; 539 int *imax=a->imax,*ai=a->i,*ailen=a->ilen; 540 int *aj=a->j,nonew=a->nonew,bs2=a->bs2,bs=a->bs,stepval,ierr; 541 PetscTruth roworiented=a->roworiented; 542 const MatScalar *value = v; 543 MatScalar *ap,*aa = a->a,*bap; 544 545 PetscFunctionBegin; 546 if (roworiented) { 547 stepval = (n-1)*bs; 548 } else { 549 stepval = (m-1)*bs; 550 } 551 for (k=0; k<m; k++) { /* loop over added rows */ 552 row = im[k]; 553 if (row < 0) continue; 554 #if defined(PETSC_USE_BOPT_g) 555 if (row >= a->mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,a->mbs-1); 556 #endif 557 rp = aj + ai[row]; 558 ap = aa + bs2*ai[row]; 559 rmax = imax[row]; 560 nrow = ailen[row]; 561 low = 0; 562 for (l=0; l<n; l++) { /* loop over added columns */ 563 if (in[l] < 0) continue; 564 col = in[l]; 565 #if defined(PETSC_USE_BOPT_g) 566 if (col >= a->nbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",col,a->nbs-1); 567 #endif 568 if (col < row) continue; /* ignore lower triangular block */ 569 if (roworiented) { 570 value = v + k*(stepval+bs)*bs + l*bs; 571 } else { 572 value = v + l*(stepval+bs)*bs + k*bs; 573 } 574 if (!sorted) low = 0; high = nrow; 575 while (high-low > 7) { 576 t = (low+high)/2; 577 if (rp[t] > col) high = t; 578 else low = t; 579 } 580 for (i=low; i<high; i++) { 581 if (rp[i] > col) break; 582 if (rp[i] == col) { 583 bap = ap + bs2*i; 584 if (roworiented) { 585 if (is == ADD_VALUES) { 586 for (ii=0; ii<bs; ii++,value+=stepval) { 587 for (jj=ii; jj<bs2; jj+=bs) { 588 bap[jj] += *value++; 589 } 590 } 591 } else { 592 for (ii=0; ii<bs; ii++,value+=stepval) { 593 for (jj=ii; jj<bs2; jj+=bs) { 594 bap[jj] = *value++; 595 } 596 } 597 } 598 } else { 599 if (is == ADD_VALUES) { 600 for (ii=0; ii<bs; ii++,value+=stepval) { 601 for (jj=0; jj<bs; jj++) { 602 *bap++ += *value++; 603 } 604 } 605 } else { 606 for (ii=0; ii<bs; ii++,value+=stepval) { 607 for (jj=0; jj<bs; jj++) { 608 *bap++ = *value++; 609 } 610 } 611 } 612 } 613 goto noinsert2; 614 } 615 } 616 if (nonew == 1) goto noinsert2; 617 else if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); 618 if (nrow >= rmax) { 619 /* there is no extra room in row, therefore enlarge */ 620 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; 621 MatScalar *new_a; 622 623 if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); 624 625 /* malloc new storage space */ 626 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); 627 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); 628 new_j = (int*)(new_a + bs2*new_nz); 629 new_i = new_j + new_nz; 630 631 /* copy over old data into new slots */ 632 for (ii=0; ii<row+1; ii++) {new_i[ii] = ai[ii];} 633 for (ii=row+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} 634 ierr = PetscMemcpy(new_j,aj,(ai[row]+nrow)*sizeof(int));CHKERRQ(ierr); 635 len = (new_nz - CHUNKSIZE - ai[row] - nrow); 636 ierr = PetscMemcpy(new_j+ai[row]+nrow+CHUNKSIZE,aj+ai[row]+nrow,len*sizeof(int));CHKERRQ(ierr); 637 ierr = PetscMemcpy(new_a,aa,(ai[row]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); 638 ierr = PetscMemzero(new_a+bs2*(ai[row]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); 639 ierr = PetscMemcpy(new_a+bs2*(ai[row]+nrow+CHUNKSIZE),aa+bs2*(ai[row]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); 640 /* free up old matrix storage */ 641 ierr = PetscFree(a->a);CHKERRQ(ierr); 642 if (!a->singlemalloc) { 643 ierr = PetscFree(a->i);CHKERRQ(ierr); 644 ierr = PetscFree(a->j);CHKERRQ(ierr); 645 } 646 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; 647 a->singlemalloc = PETSC_TRUE; 648 649 rp = aj + ai[row]; ap = aa + bs2*ai[row]; 650 rmax = imax[row] = imax[row] + CHUNKSIZE; 651 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); 652 a->maxnz += bs2*CHUNKSIZE; 653 a->reallocs++; 654 a->nz++; 655 } 656 N = nrow++ - 1; 657 /* shift up all the later entries in this row */ 658 for (ii=N; ii>=i; ii--) { 659 rp[ii+1] = rp[ii]; 660 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 661 } 662 if (N >= i) { 663 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 664 } 665 rp[i] = col; 666 bap = ap + bs2*i; 667 if (roworiented) { 668 for (ii=0; ii<bs; ii++,value+=stepval) { 669 for (jj=ii; jj<bs2; jj+=bs) { 670 bap[jj] = *value++; 671 } 672 } 673 } else { 674 for (ii=0; ii<bs; ii++,value+=stepval) { 675 for (jj=0; jj<bs; jj++) { 676 *bap++ = *value++; 677 } 678 } 679 } 680 noinsert2:; 681 low = i; 682 } 683 ailen[row] = nrow; 684 } 685 PetscFunctionReturn(0); 686 } 687 688 #undef __FUNCT__ 689 #define __FUNCT__ "MatAssemblyEnd_SeqSBAIJ" 690 int MatAssemblyEnd_SeqSBAIJ(Mat A,MatAssemblyType mode) 691 { 692 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 693 int fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 694 int m = A->m,*ip,N,*ailen = a->ilen; 695 int mbs = a->mbs,bs2 = a->bs2,rmax = 0,ierr; 696 MatScalar *aa = a->a,*ap; 697 698 PetscFunctionBegin; 699 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 700 701 if (m) rmax = ailen[0]; 702 for (i=1; i<mbs; i++) { 703 /* move each row back by the amount of empty slots (fshift) before it*/ 704 fshift += imax[i-1] - ailen[i-1]; 705 rmax = PetscMax(rmax,ailen[i]); 706 if (fshift) { 707 ip = aj + ai[i]; ap = aa + bs2*ai[i]; 708 N = ailen[i]; 709 for (j=0; j<N; j++) { 710 ip[j-fshift] = ip[j]; 711 ierr = PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 712 } 713 } 714 ai[i] = ai[i-1] + ailen[i-1]; 715 } 716 if (mbs) { 717 fshift += imax[mbs-1] - ailen[mbs-1]; 718 ai[mbs] = ai[mbs-1] + ailen[mbs-1]; 719 } 720 /* reset ilen and imax for each row */ 721 for (i=0; i<mbs; i++) { 722 ailen[i] = imax[i] = ai[i+1] - ai[i]; 723 } 724 a->nz = ai[mbs]; 725 726 /* diagonals may have moved, reset it */ 727 if (a->diag) { 728 ierr = PetscMemcpy(a->diag,ai,(mbs+1)*sizeof(int));CHKERRQ(ierr); 729 } 730 PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Matrix size: %d X %d, block size %d; storage space: %d unneeded, %d used\n", 731 m,A->m,a->bs,fshift*bs2,a->nz*bs2); 732 PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Number of mallocs during MatSetValues is %d\n", 733 a->reallocs); 734 PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Most nonzeros blocks in any row is %d\n",rmax); 735 a->reallocs = 0; 736 A->info.nz_unneeded = (PetscReal)fshift*bs2; 737 738 PetscFunctionReturn(0); 739 } 740 741 /* 742 This function returns an array of flags which indicate the locations of contiguous 743 blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] 744 then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] 745 Assume: sizes should be long enough to hold all the values. 746 */ 747 #undef __FUNCT__ 748 #define __FUNCT__ "MatZeroRows_SeqSBAIJ_Check_Blocks" 749 int MatZeroRows_SeqSBAIJ_Check_Blocks(int idx[],int n,int bs,int sizes[], int *bs_max) 750 { 751 int i,j,k,row; 752 PetscTruth flg; 753 754 PetscFunctionBegin; 755 for (i=0,j=0; i<n; j++) { 756 row = idx[i]; 757 if (row%bs!=0) { /* Not the begining of a block */ 758 sizes[j] = 1; 759 i++; 760 } else if (i+bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */ 761 sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ 762 i++; 763 } else { /* Begining of the block, so check if the complete block exists */ 764 flg = PETSC_TRUE; 765 for (k=1; k<bs; k++) { 766 if (row+k != idx[i+k]) { /* break in the block */ 767 flg = PETSC_FALSE; 768 break; 769 } 770 } 771 if (flg == PETSC_TRUE) { /* No break in the bs */ 772 sizes[j] = bs; 773 i+= bs; 774 } else { 775 sizes[j] = 1; 776 i++; 777 } 778 } 779 } 780 *bs_max = j; 781 PetscFunctionReturn(0); 782 } 783 784 #undef __FUNCT__ 785 #define __FUNCT__ "MatZeroRows_SeqSBAIJ" 786 int MatZeroRows_SeqSBAIJ(Mat A,IS is,const PetscScalar *diag) 787 { 788 PetscFunctionBegin; 789 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 790 } 791 792 /* Only add/insert a(i,j) with i<=j (blocks). 793 Any a(i,j) with i>j input by user is ingored. 794 */ 795 796 #undef __FUNCT__ 797 #define __FUNCT__ "MatSetValues_SeqSBAIJ" 798 int MatSetValues_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode is) 799 { 800 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 801 int *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,sorted=a->sorted; 802 int *imax=a->imax,*ai=a->i,*ailen=a->ilen,roworiented=a->roworiented; 803 int *aj=a->j,nonew=a->nonew,bs=a->bs,brow,bcol; 804 int ridx,cidx,bs2=a->bs2,ierr; 805 MatScalar *ap,value,*aa=a->a,*bap; 806 807 PetscFunctionBegin; 808 809 for (k=0; k<m; k++) { /* loop over added rows */ 810 row = im[k]; /* row number */ 811 brow = row/bs; /* block row number */ 812 if (row < 0) continue; 813 #if defined(PETSC_USE_BOPT_g) 814 if (row >= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,A->m-1); 815 #endif 816 rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/ 817 ap = aa + bs2*ai[brow]; /*ptr to beginning of element value of the row block*/ 818 rmax = imax[brow]; /* maximum space allocated for this row */ 819 nrow = ailen[brow]; /* actual length of this row */ 820 low = 0; 821 822 for (l=0; l<n; l++) { /* loop over added columns */ 823 if (in[l] < 0) continue; 824 #if defined(PETSC_USE_BOPT_g) 825 if (in[l] >= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[l],A->m-1); 826 #endif 827 col = in[l]; 828 bcol = col/bs; /* block col number */ 829 830 if (brow <= bcol){ 831 ridx = row % bs; cidx = col % bs; /*row and col index inside the block */ 832 if ((brow==bcol && ridx<=cidx) || (brow<bcol)){ 833 /* element value a(k,l) */ 834 if (roworiented) { 835 value = v[l + k*n]; 836 } else { 837 value = v[k + l*m]; 838 } 839 840 /* move pointer bap to a(k,l) quickly and add/insert value */ 841 if (!sorted) low = 0; high = nrow; 842 while (high-low > 7) { 843 t = (low+high)/2; 844 if (rp[t] > bcol) high = t; 845 else low = t; 846 } 847 for (i=low; i<high; i++) { 848 /* printf("The loop of i=low.., rp[%d]=%d\n",i,rp[i]); */ 849 if (rp[i] > bcol) break; 850 if (rp[i] == bcol) { 851 bap = ap + bs2*i + bs*cidx + ridx; 852 if (is == ADD_VALUES) *bap += value; 853 else *bap = value; 854 /* for diag block, add/insert its symmetric element a(cidx,ridx) */ 855 if (brow == bcol && ridx < cidx){ 856 bap = ap + bs2*i + bs*ridx + cidx; 857 if (is == ADD_VALUES) *bap += value; 858 else *bap = value; 859 } 860 goto noinsert1; 861 } 862 } 863 864 if (nonew == 1) goto noinsert1; 865 else if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); 866 if (nrow >= rmax) { 867 /* there is no extra room in row, therefore enlarge */ 868 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; 869 MatScalar *new_a; 870 871 if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); 872 873 /* Malloc new storage space */ 874 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); 875 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); 876 new_j = (int*)(new_a + bs2*new_nz); 877 new_i = new_j + new_nz; 878 879 /* copy over old data into new slots */ 880 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} 881 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} 882 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); 883 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); 884 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); 885 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); 886 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); 887 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE),aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); 888 /* free up old matrix storage */ 889 ierr = PetscFree(a->a);CHKERRQ(ierr); 890 if (!a->singlemalloc) { 891 ierr = PetscFree(a->i);CHKERRQ(ierr); 892 ierr = PetscFree(a->j);CHKERRQ(ierr); 893 } 894 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; 895 a->singlemalloc = PETSC_TRUE; 896 897 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; 898 rmax = imax[brow] = imax[brow] + CHUNKSIZE; 899 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); 900 a->maxnz += bs2*CHUNKSIZE; 901 a->reallocs++; 902 a->nz++; 903 } 904 905 N = nrow++ - 1; 906 /* shift up all the later entries in this row */ 907 for (ii=N; ii>=i; ii--) { 908 rp[ii+1] = rp[ii]; 909 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 910 } 911 if (N>=i) { 912 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 913 } 914 rp[i] = bcol; 915 ap[bs2*i + bs*cidx + ridx] = value; 916 noinsert1:; 917 low = i; 918 /* } */ 919 } 920 } /* end of if .. if.. */ 921 } /* end of loop over added columns */ 922 ailen[brow] = nrow; 923 } /* end of loop over added rows */ 924 925 PetscFunctionReturn(0); 926 } 927 928 extern int MatCholeskyFactorSymbolic_SeqSBAIJ(Mat,IS,MatFactorInfo*,Mat*); 929 extern int MatCholeskyFactor_SeqSBAIJ(Mat,IS,MatFactorInfo*); 930 extern int MatIncreaseOverlap_SeqSBAIJ(Mat,int,IS[],int); 931 extern int MatGetSubMatrix_SeqSBAIJ(Mat,IS,IS,int,MatReuse,Mat*); 932 extern int MatGetSubMatrices_SeqSBAIJ(Mat,int,const IS[],const IS[],MatReuse,Mat*[]); 933 extern int MatMultTranspose_SeqSBAIJ(Mat,Vec,Vec); 934 extern int MatMultTransposeAdd_SeqSBAIJ(Mat,Vec,Vec,Vec); 935 extern int MatScale_SeqSBAIJ(const PetscScalar*,Mat); 936 extern int MatNorm_SeqSBAIJ(Mat,NormType,PetscReal *); 937 extern int MatEqual_SeqSBAIJ(Mat,Mat,PetscTruth*); 938 extern int MatGetDiagonal_SeqSBAIJ(Mat,Vec); 939 extern int MatDiagonalScale_SeqSBAIJ(Mat,Vec,Vec); 940 extern int MatGetInfo_SeqSBAIJ(Mat,MatInfoType,MatInfo *); 941 extern int MatZeroEntries_SeqSBAIJ(Mat); 942 extern int MatGetRowMax_SeqSBAIJ(Mat,Vec); 943 944 extern int MatSolve_SeqSBAIJ_N(Mat,Vec,Vec); 945 extern int MatSolve_SeqSBAIJ_1(Mat,Vec,Vec); 946 extern int MatSolve_SeqSBAIJ_2(Mat,Vec,Vec); 947 extern int MatSolve_SeqSBAIJ_3(Mat,Vec,Vec); 948 extern int MatSolve_SeqSBAIJ_4(Mat,Vec,Vec); 949 extern int MatSolve_SeqSBAIJ_5(Mat,Vec,Vec); 950 extern int MatSolve_SeqSBAIJ_6(Mat,Vec,Vec); 951 extern int MatSolve_SeqSBAIJ_7(Mat,Vec,Vec); 952 extern int MatSolveTranspose_SeqSBAIJ_7(Mat,Vec,Vec); 953 extern int MatSolveTranspose_SeqSBAIJ_6(Mat,Vec,Vec); 954 extern int MatSolveTranspose_SeqSBAIJ_5(Mat,Vec,Vec); 955 extern int MatSolveTranspose_SeqSBAIJ_4(Mat,Vec,Vec); 956 extern int MatSolveTranspose_SeqSBAIJ_3(Mat,Vec,Vec); 957 extern int MatSolveTranspose_SeqSBAIJ_2(Mat,Vec,Vec); 958 extern int MatSolveTranspose_SeqSBAIJ_1(Mat,Vec,Vec); 959 960 extern int MatSolves_SeqSBAIJ_1(Mat,Vecs,Vecs); 961 962 extern int MatSolve_SeqSBAIJ_1_NaturalOrdering(Mat,Vec,Vec); 963 extern int MatSolve_SeqSBAIJ_2_NaturalOrdering(Mat,Vec,Vec); 964 extern int MatSolve_SeqSBAIJ_3_NaturalOrdering(Mat,Vec,Vec); 965 extern int MatSolve_SeqSBAIJ_4_NaturalOrdering(Mat,Vec,Vec); 966 extern int MatSolve_SeqSBAIJ_5_NaturalOrdering(Mat,Vec,Vec); 967 extern int MatSolve_SeqSBAIJ_6_NaturalOrdering(Mat,Vec,Vec); 968 extern int MatSolve_SeqSBAIJ_7_NaturalOrdering(Mat,Vec,Vec); 969 extern int MatSolve_SeqSBAIJ_N_NaturalOrdering(Mat,Vec,Vec); 970 971 extern int MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat,Mat*); 972 extern int MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat,Mat*); 973 extern int MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat,Mat*); 974 extern int MatCholeskyFactorNumeric_SeqSBAIJ_3(Mat,Mat*); 975 extern int MatCholeskyFactorNumeric_SeqSBAIJ_4(Mat,Mat*); 976 extern int MatCholeskyFactorNumeric_SeqSBAIJ_5(Mat,Mat*); 977 extern int MatCholeskyFactorNumeric_SeqSBAIJ_6(Mat,Mat*); 978 extern int MatCholeskyFactorNumeric_SeqSBAIJ_7(Mat,Mat*); 979 extern int MatGetInertia_SeqSBAIJ(Mat,int*,int*,int*); 980 981 extern int MatMult_SeqSBAIJ_1(Mat,Vec,Vec); 982 extern int MatMult_SeqSBAIJ_2(Mat,Vec,Vec); 983 extern int MatMult_SeqSBAIJ_3(Mat,Vec,Vec); 984 extern int MatMult_SeqSBAIJ_4(Mat,Vec,Vec); 985 extern int MatMult_SeqSBAIJ_5(Mat,Vec,Vec); 986 extern int MatMult_SeqSBAIJ_6(Mat,Vec,Vec); 987 extern int MatMult_SeqSBAIJ_7(Mat,Vec,Vec); 988 extern int MatMult_SeqSBAIJ_N(Mat,Vec,Vec); 989 990 extern int MatMultAdd_SeqSBAIJ_1(Mat,Vec,Vec,Vec); 991 extern int MatMultAdd_SeqSBAIJ_2(Mat,Vec,Vec,Vec); 992 extern int MatMultAdd_SeqSBAIJ_3(Mat,Vec,Vec,Vec); 993 extern int MatMultAdd_SeqSBAIJ_4(Mat,Vec,Vec,Vec); 994 extern int MatMultAdd_SeqSBAIJ_5(Mat,Vec,Vec,Vec); 995 extern int MatMultAdd_SeqSBAIJ_6(Mat,Vec,Vec,Vec); 996 extern int MatMultAdd_SeqSBAIJ_7(Mat,Vec,Vec,Vec); 997 extern int MatMultAdd_SeqSBAIJ_N(Mat,Vec,Vec,Vec); 998 999 #ifdef HAVE_MatICCFactor 1000 /* modefied from MatILUFactor_SeqSBAIJ, needs further work! */ 1001 #undef __FUNCT__ 1002 #define __FUNCT__ "MatICCFactor_SeqSBAIJ" 1003 int MatICCFactor_SeqSBAIJ(Mat inA,IS row,MatFactorInfo *info) 1004 { 1005 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)inA->data; 1006 Mat outA; 1007 int ierr; 1008 PetscTruth row_identity,col_identity; 1009 1010 PetscFunctionBegin; 1011 /* 1012 if (level != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); 1013 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 1014 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 1015 if (!row_identity || !col_identity) { 1016 SETERRQ(1,"Row and column permutations must be identity for in-place ICC"); 1017 } 1018 */ 1019 1020 outA = inA; 1021 inA->factor = FACTOR_CHOLESKY; 1022 1023 if (!a->diag) { 1024 ierr = MatMarkDiagonal_SeqSBAIJ(inA);CHKERRQ(ierr); 1025 } 1026 /* 1027 Blocksize 2, 3, 4, 5, 6 and 7 have a special faster factorization/solver 1028 for ILU(0) factorization with natural ordering 1029 */ 1030 switch (a->bs) { 1031 case 1: 1032 inA->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1033 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1034 inA->ops->solves = MatSolves_SeqSBAIJ_1; 1035 PetscLoginfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering solvetrans BS=1\n"); 1036 case 2: 1037 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 1038 inA->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 1039 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering; 1040 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=2\n"); 1041 break; 1042 case 3: 1043 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 1044 inA->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 1045 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_3_NaturalOrdering; 1046 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=3\n"); 1047 break; 1048 case 4: 1049 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 1050 inA->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 1051 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_4_NaturalOrdering; 1052 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=4\n"); 1053 break; 1054 case 5: 1055 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 1056 inA->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 1057 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_5_NaturalOrdering; 1058 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=5\n"); 1059 break; 1060 case 6: 1061 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 1062 inA->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 1063 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_6_NaturalOrdering; 1064 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=6\n"); 1065 break; 1066 case 7: 1067 inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 1068 inA->ops->solvetranspose = MatSolve_SeqSBAIJ_7_NaturalOrdering; 1069 inA->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 1070 PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=7\n"); 1071 break; 1072 default: 1073 a->row = row; 1074 a->icol = col; 1075 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 1076 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 1077 1078 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 1079 ierr = ISInvertPermutation(col,PETSC_DECIDE, &(a->icol));CHKERRQ(ierr); 1080 PetscLogObjectParent(inA,a->icol); 1081 1082 if (!a->solve_work) { 1083 ierr = PetscMalloc((A->m+a->bs)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 1084 PetscLogObjectMemory(inA,(A->m+a->bs)*sizeof(PetscScalar)); 1085 } 1086 } 1087 1088 ierr = MatCholeskyFactorNumeric(inA,&outA);CHKERRQ(ierr); 1089 1090 PetscFunctionReturn(0); 1091 } 1092 #endif 1093 1094 #undef __FUNCT__ 1095 #define __FUNCT__ "MatPrintHelp_SeqSBAIJ" 1096 int MatPrintHelp_SeqSBAIJ(Mat A) 1097 { 1098 static PetscTruth called = PETSC_FALSE; 1099 MPI_Comm comm = A->comm; 1100 int ierr; 1101 1102 PetscFunctionBegin; 1103 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1104 ierr = (*PetscHelpPrintf)(comm," Options for MATSEQSBAIJ and MATMPISBAIJ matrix formats (the defaults):\n");CHKERRQ(ierr); 1105 ierr = (*PetscHelpPrintf)(comm," -mat_block_size <block_size>\n");CHKERRQ(ierr); 1106 PetscFunctionReturn(0); 1107 } 1108 1109 EXTERN_C_BEGIN 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatSeqSBAIJSetColumnIndices_SeqSBAIJ" 1112 int MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat,int *indices) 1113 { 1114 Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data; 1115 int i,nz,n; 1116 1117 PetscFunctionBegin; 1118 nz = baij->maxnz; 1119 n = mat->n; 1120 for (i=0; i<nz; i++) { 1121 baij->j[i] = indices[i]; 1122 } 1123 baij->nz = nz; 1124 for (i=0; i<n; i++) { 1125 baij->ilen[i] = baij->imax[i]; 1126 } 1127 1128 PetscFunctionReturn(0); 1129 } 1130 EXTERN_C_END 1131 1132 #undef __FUNCT__ 1133 #define __FUNCT__ "MatSeqSBAIJSetColumnIndices" 1134 /*@ 1135 MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows 1136 in the matrix. 1137 1138 Input Parameters: 1139 + mat - the SeqSBAIJ matrix 1140 - indices - the column indices 1141 1142 Level: advanced 1143 1144 Notes: 1145 This can be called if you have precomputed the nonzero structure of the 1146 matrix and want to provide it to the matrix object to improve the performance 1147 of the MatSetValues() operation. 1148 1149 You MUST have set the correct numbers of nonzeros per row in the call to 1150 MatCreateSeqSBAIJ(). 1151 1152 MUST be called before any calls to MatSetValues() 1153 1154 .seealso: MatCreateSeqSBAIJ 1155 @*/ 1156 int MatSeqSBAIJSetColumnIndices(Mat mat,int *indices) 1157 { 1158 int ierr,(*f)(Mat,int *); 1159 1160 PetscFunctionBegin; 1161 PetscValidHeaderSpecific(mat,MAT_COOKIE); 1162 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqSBAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); 1163 if (f) { 1164 ierr = (*f)(mat,indices);CHKERRQ(ierr); 1165 } else { 1166 SETERRQ(1,"Wrong type of matrix to set column indices"); 1167 } 1168 PetscFunctionReturn(0); 1169 } 1170 1171 #undef __FUNCT__ 1172 #define __FUNCT__ "MatSetUpPreallocation_SeqSBAIJ" 1173 int MatSetUpPreallocation_SeqSBAIJ(Mat A) 1174 { 1175 int ierr; 1176 1177 PetscFunctionBegin; 1178 ierr = MatSeqSBAIJSetPreallocation(A,1,PETSC_DEFAULT,0);CHKERRQ(ierr); 1179 PetscFunctionReturn(0); 1180 } 1181 1182 #undef __FUNCT__ 1183 #define __FUNCT__ "MatGetArray_SeqSBAIJ" 1184 int MatGetArray_SeqSBAIJ(Mat A,PetscScalar *array[]) 1185 { 1186 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 1187 PetscFunctionBegin; 1188 *array = a->a; 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatRestoreArray_SeqSBAIJ" 1194 int MatRestoreArray_SeqSBAIJ(Mat A,PetscScalar *array[]) 1195 { 1196 PetscFunctionBegin; 1197 PetscFunctionReturn(0); 1198 } 1199 1200 #include "petscblaslapack.h" 1201 #undef __FUNCT__ 1202 #define __FUNCT__ "MatAXPY_SeqSBAIJ" 1203 int MatAXPY_SeqSBAIJ(const PetscScalar *a,Mat X,Mat Y,MatStructure str) 1204 { 1205 Mat_SeqSBAIJ *x=(Mat_SeqSBAIJ *)X->data, *y=(Mat_SeqSBAIJ *)Y->data; 1206 int ierr,one=1,i,bs=y->bs,bs2,j; 1207 1208 PetscFunctionBegin; 1209 if (str == SAME_NONZERO_PATTERN) { 1210 BLaxpy_(&x->nz,(PetscScalar*)a,x->a,&one,y->a,&one); 1211 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 1212 if (y->xtoy && y->XtoY != X) { 1213 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1214 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1215 } 1216 if (!y->xtoy) { /* get xtoy */ 1217 ierr = MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); 1218 y->XtoY = X; 1219 } 1220 bs2 = bs*bs; 1221 for (i=0; i<x->nz; i++) { 1222 j = 0; 1223 while (j < bs2){ 1224 y->a[bs2*y->xtoy[i]+j] += (*a)*(x->a[bs2*i+j]); 1225 j++; 1226 } 1227 } 1228 PetscLogInfo(0,"MatAXPY_SeqSBAIJ: ratio of nnz_s(X)/nnz_s(Y): %d/%d = %g\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz)); 1229 } else { 1230 ierr = MatAXPY_Basic(a,X,Y,str);CHKERRQ(ierr); 1231 } 1232 PetscFunctionReturn(0); 1233 } 1234 1235 #undef __FUNCT__ 1236 #define __FUNCT__ "MatIsSymmetric_SeqSBAIJ" 1237 int MatIsSymmetric_SeqSBAIJ(Mat A,PetscTruth *flg) 1238 { 1239 PetscFunctionBegin; 1240 *flg = PETSC_TRUE; 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatIsStructurallySymmetric_SeqSBAIJ" 1246 int MatIsStructurallySymmetric_SeqSBAIJ(Mat A,PetscTruth *flg) 1247 { 1248 PetscFunctionBegin; 1249 *flg = PETSC_TRUE; 1250 PetscFunctionReturn(0); 1251 } 1252 1253 #undef __FUNCT__ 1254 #define __FUNCT__ "MatIsHermitian_SeqSBAIJ" 1255 int MatIsHermitian_SeqSBAIJ(Mat A,PetscTruth *flg) 1256 { 1257 PetscFunctionBegin; 1258 *flg = PETSC_FALSE; 1259 PetscFunctionReturn(0); 1260 } 1261 1262 /* -------------------------------------------------------------------*/ 1263 static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ, 1264 MatGetRow_SeqSBAIJ, 1265 MatRestoreRow_SeqSBAIJ, 1266 MatMult_SeqSBAIJ_N, 1267 /* 4*/ MatMultAdd_SeqSBAIJ_N, 1268 MatMultTranspose_SeqSBAIJ, 1269 MatMultTransposeAdd_SeqSBAIJ, 1270 MatSolve_SeqSBAIJ_N, 1271 0, 1272 0, 1273 /*10*/ 0, 1274 0, 1275 MatCholeskyFactor_SeqSBAIJ, 1276 MatRelax_SeqSBAIJ, 1277 MatTranspose_SeqSBAIJ, 1278 /*15*/ MatGetInfo_SeqSBAIJ, 1279 MatEqual_SeqSBAIJ, 1280 MatGetDiagonal_SeqSBAIJ, 1281 MatDiagonalScale_SeqSBAIJ, 1282 MatNorm_SeqSBAIJ, 1283 /*20*/ 0, 1284 MatAssemblyEnd_SeqSBAIJ, 1285 0, 1286 MatSetOption_SeqSBAIJ, 1287 MatZeroEntries_SeqSBAIJ, 1288 /*25*/ MatZeroRows_SeqSBAIJ, 1289 0, 1290 0, 1291 MatCholeskyFactorSymbolic_SeqSBAIJ, 1292 MatCholeskyFactorNumeric_SeqSBAIJ_N, 1293 /*30*/ MatSetUpPreallocation_SeqSBAIJ, 1294 0, 1295 MatICCFactorSymbolic_SeqSBAIJ, 1296 MatGetArray_SeqSBAIJ, 1297 MatRestoreArray_SeqSBAIJ, 1298 /*35*/ MatDuplicate_SeqSBAIJ, 1299 0, 1300 0, 1301 0, 1302 0, 1303 /*40*/ MatAXPY_SeqSBAIJ, 1304 MatGetSubMatrices_SeqSBAIJ, 1305 MatIncreaseOverlap_SeqSBAIJ, 1306 MatGetValues_SeqSBAIJ, 1307 0, 1308 /*45*/ MatPrintHelp_SeqSBAIJ, 1309 MatScale_SeqSBAIJ, 1310 0, 1311 0, 1312 0, 1313 /*50*/ MatGetBlockSize_SeqSBAIJ, 1314 MatGetRowIJ_SeqSBAIJ, 1315 MatRestoreRowIJ_SeqSBAIJ, 1316 0, 1317 0, 1318 /*55*/ 0, 1319 0, 1320 0, 1321 0, 1322 MatSetValuesBlocked_SeqSBAIJ, 1323 /*60*/ MatGetSubMatrix_SeqSBAIJ, 1324 0, 1325 0, 1326 MatGetPetscMaps_Petsc, 1327 0, 1328 /*65*/ 0, 1329 0, 1330 0, 1331 0, 1332 0, 1333 /*70*/ MatGetRowMax_SeqSBAIJ, 1334 0, 1335 0, 1336 0, 1337 0, 1338 /*75*/ 0, 1339 0, 1340 0, 1341 0, 1342 0, 1343 /*80*/ 0, 1344 0, 1345 0, 1346 #if !defined(PETSC_USE_COMPLEX) 1347 MatGetInertia_SeqSBAIJ, 1348 #else 1349 0, 1350 #endif 1351 /*85*/ MatLoad_SeqSBAIJ, 1352 MatIsSymmetric_SeqSBAIJ, 1353 MatIsStructurallySymmetric_SeqSBAIJ, 1354 MatIsHermitian_SeqSBAIJ 1355 }; 1356 1357 EXTERN_C_BEGIN 1358 #undef __FUNCT__ 1359 #define __FUNCT__ "MatStoreValues_SeqSBAIJ" 1360 int MatStoreValues_SeqSBAIJ(Mat mat) 1361 { 1362 Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data; 1363 int nz = aij->i[mat->m]*aij->bs*aij->bs2; 1364 int ierr; 1365 1366 PetscFunctionBegin; 1367 if (aij->nonew != 1) { 1368 SETERRQ(1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 1369 } 1370 1371 /* allocate space for values if not already there */ 1372 if (!aij->saved_values) { 1373 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 1374 } 1375 1376 /* copy values over */ 1377 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 1378 PetscFunctionReturn(0); 1379 } 1380 EXTERN_C_END 1381 1382 EXTERN_C_BEGIN 1383 #undef __FUNCT__ 1384 #define __FUNCT__ "MatRetrieveValues_SeqSBAIJ" 1385 int MatRetrieveValues_SeqSBAIJ(Mat mat) 1386 { 1387 Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data; 1388 int nz = aij->i[mat->m]*aij->bs*aij->bs2,ierr; 1389 1390 PetscFunctionBegin; 1391 if (aij->nonew != 1) { 1392 SETERRQ(1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 1393 } 1394 if (!aij->saved_values) { 1395 SETERRQ(1,"Must call MatStoreValues(A);first"); 1396 } 1397 1398 /* copy values over */ 1399 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 1400 PetscFunctionReturn(0); 1401 } 1402 EXTERN_C_END 1403 1404 EXTERN_C_BEGIN 1405 #undef __FUNCT__ 1406 #define __FUNCT__ "MatSeqSBAIJSetPreallocation_SeqSBAIJ" 1407 int MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B,int bs,int nz,int *nnz) 1408 { 1409 Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ*)B->data; 1410 int i,len,ierr,mbs,bs2; 1411 PetscTruth flg; 1412 1413 PetscFunctionBegin; 1414 B->preallocated = PETSC_TRUE; 1415 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1416 mbs = B->m/bs; 1417 bs2 = bs*bs; 1418 1419 if (mbs*bs != B->m) { 1420 SETERRQ(PETSC_ERR_ARG_SIZ,"Number rows, cols must be divisible by blocksize"); 1421 } 1422 1423 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3; 1424 if (nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 1425 if (nnz) { 1426 for (i=0; i<mbs; i++) { 1427 if (nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %d value %d",i,nnz[i]); 1428 if (nnz[i] > mbs) SETERRQ3(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %d value %d rowlength %d",i,nnz[i],mbs); 1429 } 1430 } 1431 1432 ierr = PetscOptionsHasName(B->prefix,"-mat_no_unroll",&flg);CHKERRQ(ierr); 1433 if (!flg) { 1434 switch (bs) { 1435 case 1: 1436 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1; 1437 B->ops->solve = MatSolve_SeqSBAIJ_1; 1438 B->ops->solves = MatSolves_SeqSBAIJ_1; 1439 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_1; 1440 B->ops->mult = MatMult_SeqSBAIJ_1; 1441 B->ops->multadd = MatMultAdd_SeqSBAIJ_1; 1442 break; 1443 case 2: 1444 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2; 1445 B->ops->solve = MatSolve_SeqSBAIJ_2; 1446 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_2; 1447 B->ops->mult = MatMult_SeqSBAIJ_2; 1448 B->ops->multadd = MatMultAdd_SeqSBAIJ_2; 1449 break; 1450 case 3: 1451 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3; 1452 B->ops->solve = MatSolve_SeqSBAIJ_3; 1453 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_3; 1454 B->ops->mult = MatMult_SeqSBAIJ_3; 1455 B->ops->multadd = MatMultAdd_SeqSBAIJ_3; 1456 break; 1457 case 4: 1458 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4; 1459 B->ops->solve = MatSolve_SeqSBAIJ_4; 1460 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_4; 1461 B->ops->mult = MatMult_SeqSBAIJ_4; 1462 B->ops->multadd = MatMultAdd_SeqSBAIJ_4; 1463 break; 1464 case 5: 1465 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5; 1466 B->ops->solve = MatSolve_SeqSBAIJ_5; 1467 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_5; 1468 B->ops->mult = MatMult_SeqSBAIJ_5; 1469 B->ops->multadd = MatMultAdd_SeqSBAIJ_5; 1470 break; 1471 case 6: 1472 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6; 1473 B->ops->solve = MatSolve_SeqSBAIJ_6; 1474 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_6; 1475 B->ops->mult = MatMult_SeqSBAIJ_6; 1476 B->ops->multadd = MatMultAdd_SeqSBAIJ_6; 1477 break; 1478 case 7: 1479 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7; 1480 B->ops->solve = MatSolve_SeqSBAIJ_7; 1481 B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_7; 1482 B->ops->mult = MatMult_SeqSBAIJ_7; 1483 B->ops->multadd = MatMultAdd_SeqSBAIJ_7; 1484 break; 1485 } 1486 } 1487 1488 b->mbs = mbs; 1489 b->nbs = mbs; 1490 ierr = PetscMalloc((mbs+1)*sizeof(int),&b->imax);CHKERRQ(ierr); 1491 if (!nnz) { 1492 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 1493 else if (nz <= 0) nz = 1; 1494 for (i=0; i<mbs; i++) { 1495 b->imax[i] = nz; 1496 } 1497 nz = nz*mbs; /* total nz */ 1498 } else { 1499 nz = 0; 1500 for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 1501 } 1502 /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */ 1503 1504 /* allocate the matrix space */ 1505 len = nz*sizeof(int) + nz*bs2*sizeof(MatScalar) + (B->m+1)*sizeof(int); 1506 ierr = PetscMalloc(len,&b->a);CHKERRQ(ierr); 1507 ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); 1508 b->j = (int*)(b->a + nz*bs2); 1509 ierr = PetscMemzero(b->j,nz*sizeof(int));CHKERRQ(ierr); 1510 b->i = b->j + nz; 1511 b->singlemalloc = PETSC_TRUE; 1512 1513 /* pointer to beginning of each row */ 1514 b->i[0] = 0; 1515 for (i=1; i<mbs+1; i++) { 1516 b->i[i] = b->i[i-1] + b->imax[i-1]; 1517 } 1518 1519 /* b->ilen will count nonzeros in each block row so far. */ 1520 ierr = PetscMalloc((mbs+1)*sizeof(int),&b->ilen);CHKERRQ(ierr); 1521 PetscLogObjectMemory(B,len+2*(mbs+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqSBAIJ)); 1522 for (i=0; i<mbs; i++) { b->ilen[i] = 0;} 1523 1524 b->bs = bs; 1525 b->bs2 = bs2; 1526 b->nz = 0; 1527 b->maxnz = nz*bs2; 1528 1529 b->inew = 0; 1530 b->jnew = 0; 1531 b->anew = 0; 1532 b->a2anew = 0; 1533 b->permute = PETSC_FALSE; 1534 PetscFunctionReturn(0); 1535 } 1536 EXTERN_C_END 1537 1538 EXTERN_C_BEGIN 1539 EXTERN int MatConvert_SeqSBAIJ_SeqAIJ(Mat,const MatType,Mat*); 1540 EXTERN int MatConvert_SeqSBAIJ_SeqBAIJ(Mat,const MatType,Mat*); 1541 EXTERN_C_END 1542 1543 /*MC 1544 MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices, 1545 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1546 1547 Options Database Keys: 1548 . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to MatSetFromOptions() 1549 1550 Level: beginner 1551 1552 .seealso: MatCreateSeqSBAIJ 1553 M*/ 1554 1555 EXTERN_C_BEGIN 1556 #undef __FUNCT__ 1557 #define __FUNCT__ "MatCreate_SeqSBAIJ" 1558 int MatCreate_SeqSBAIJ(Mat B) 1559 { 1560 Mat_SeqSBAIJ *b; 1561 int ierr,size; 1562 1563 PetscFunctionBegin; 1564 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 1565 if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 1566 B->m = B->M = PetscMax(B->m,B->M); 1567 B->n = B->N = PetscMax(B->n,B->N); 1568 1569 ierr = PetscNew(Mat_SeqSBAIJ,&b);CHKERRQ(ierr); 1570 B->data = (void*)b; 1571 ierr = PetscMemzero(b,sizeof(Mat_SeqSBAIJ));CHKERRQ(ierr); 1572 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1573 B->ops->destroy = MatDestroy_SeqSBAIJ; 1574 B->ops->view = MatView_SeqSBAIJ; 1575 B->factor = 0; 1576 B->lupivotthreshold = 1.0; 1577 B->mapping = 0; 1578 b->row = 0; 1579 b->icol = 0; 1580 b->reallocs = 0; 1581 b->saved_values = 0; 1582 1583 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1584 ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 1585 1586 b->sorted = PETSC_FALSE; 1587 b->roworiented = PETSC_TRUE; 1588 b->nonew = 0; 1589 b->diag = 0; 1590 b->solve_work = 0; 1591 b->mult_work = 0; 1592 B->spptr = 0; 1593 b->keepzeroedrows = PETSC_FALSE; 1594 b->xtoy = 0; 1595 b->XtoY = 0; 1596 1597 b->inew = 0; 1598 b->jnew = 0; 1599 b->anew = 0; 1600 b->a2anew = 0; 1601 b->permute = PETSC_FALSE; 1602 1603 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1604 "MatStoreValues_SeqSBAIJ", 1605 MatStoreValues_SeqSBAIJ);CHKERRQ(ierr); 1606 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1607 "MatRetrieveValues_SeqSBAIJ", 1608 (void*)MatRetrieveValues_SeqSBAIJ);CHKERRQ(ierr); 1609 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetColumnIndices_C", 1610 "MatSeqSBAIJSetColumnIndices_SeqSBAIJ", 1611 MatSeqSBAIJSetColumnIndices_SeqSBAIJ);CHKERRQ(ierr); 1612 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqaij_C", 1613 "MatConvert_SeqSBAIJ_SeqAIJ", 1614 MatConvert_SeqSBAIJ_SeqAIJ);CHKERRQ(ierr); 1615 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqbaij_C", 1616 "MatConvert_SeqSBAIJ_SeqBAIJ", 1617 MatConvert_SeqSBAIJ_SeqBAIJ);CHKERRQ(ierr); 1618 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetPreallocation_C", 1619 "MatSeqSBAIJSetPreallocation_SeqSBAIJ", 1620 MatSeqSBAIJSetPreallocation_SeqSBAIJ);CHKERRQ(ierr); 1621 PetscFunctionReturn(0); 1622 } 1623 EXTERN_C_END 1624 1625 #undef __FUNCT__ 1626 #define __FUNCT__ "MatSeqSBAIJSetPreallocation" 1627 /*@C 1628 MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block 1629 compressed row) format. For good matrix assembly performance the 1630 user should preallocate the matrix storage by setting the parameter nz 1631 (or the array nnz). By setting these parameters accurately, performance 1632 during matrix assembly can be increased by more than a factor of 50. 1633 1634 Collective on Mat 1635 1636 Input Parameters: 1637 + A - the symmetric matrix 1638 . bs - size of block 1639 . nz - number of block nonzeros per block row (same for all rows) 1640 - nnz - array containing the number of block nonzeros in the upper triangular plus 1641 diagonal portion of each block (possibly different for each block row) or PETSC_NULL 1642 1643 Options Database Keys: 1644 . -mat_no_unroll - uses code that does not unroll the loops in the 1645 block calculations (much slower) 1646 . -mat_block_size - size of the blocks to use 1647 1648 Level: intermediate 1649 1650 Notes: 1651 Specify the preallocated storage with either nz or nnz (not both). 1652 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 1653 allocation. For additional details, see the users manual chapter on 1654 matrices. 1655 1656 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ() 1657 @*/ 1658 int MatSeqSBAIJSetPreallocation(Mat B,int bs,int nz,const int nnz[]) { 1659 int ierr,(*f)(Mat,int,int,const int[]); 1660 1661 PetscFunctionBegin; 1662 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqSBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1663 if (f) { 1664 ierr = (*f)(B,bs,nz,nnz);CHKERRQ(ierr); 1665 } 1666 PetscFunctionReturn(0); 1667 } 1668 1669 #undef __FUNCT__ 1670 #define __FUNCT__ "MatCreateSeqSBAIJ" 1671 /*@C 1672 MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in block AIJ (block 1673 compressed row) format. For good matrix assembly performance the 1674 user should preallocate the matrix storage by setting the parameter nz 1675 (or the array nnz). By setting these parameters accurately, performance 1676 during matrix assembly can be increased by more than a factor of 50. 1677 1678 Collective on MPI_Comm 1679 1680 Input Parameters: 1681 + comm - MPI communicator, set to PETSC_COMM_SELF 1682 . bs - size of block 1683 . m - number of rows, or number of columns 1684 . nz - number of block nonzeros per block row (same for all rows) 1685 - nnz - array containing the number of block nonzeros in the upper triangular plus 1686 diagonal portion of each block (possibly different for each block row) or PETSC_NULL 1687 1688 Output Parameter: 1689 . A - the symmetric matrix 1690 1691 Options Database Keys: 1692 . -mat_no_unroll - uses code that does not unroll the loops in the 1693 block calculations (much slower) 1694 . -mat_block_size - size of the blocks to use 1695 1696 Level: intermediate 1697 1698 Notes: 1699 1700 Specify the preallocated storage with either nz or nnz (not both). 1701 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 1702 allocation. For additional details, see the users manual chapter on 1703 matrices. 1704 1705 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ() 1706 @*/ 1707 int MatCreateSeqSBAIJ(MPI_Comm comm,int bs,int m,int n,int nz,const int nnz[],Mat *A) 1708 { 1709 int ierr; 1710 1711 PetscFunctionBegin; 1712 ierr = MatCreate(comm,m,n,m,n,A);CHKERRQ(ierr); 1713 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1714 ierr = MatSeqSBAIJSetPreallocation(*A,bs,nz,nnz);CHKERRQ(ierr); 1715 PetscFunctionReturn(0); 1716 } 1717 1718 #undef __FUNCT__ 1719 #define __FUNCT__ "MatDuplicate_SeqSBAIJ" 1720 int MatDuplicate_SeqSBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 1721 { 1722 Mat C; 1723 Mat_SeqSBAIJ *c,*a = (Mat_SeqSBAIJ*)A->data; 1724 int i,len,mbs = a->mbs,nz = a->nz,bs2 =a->bs2,ierr; 1725 1726 PetscFunctionBegin; 1727 if (a->i[mbs] != nz) SETERRQ(PETSC_ERR_PLIB,"Corrupt matrix"); 1728 1729 *B = 0; 1730 ierr = MatCreate(A->comm,A->m,A->n,A->m,A->n,&C);CHKERRQ(ierr); 1731 ierr = MatSetType(C,MATSEQSBAIJ);CHKERRQ(ierr); 1732 c = (Mat_SeqSBAIJ*)C->data; 1733 1734 ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1735 C->preallocated = PETSC_TRUE; 1736 C->factor = A->factor; 1737 c->row = 0; 1738 c->icol = 0; 1739 c->saved_values = 0; 1740 c->keepzeroedrows = a->keepzeroedrows; 1741 C->assembled = PETSC_TRUE; 1742 1743 c->bs = a->bs; 1744 c->bs2 = a->bs2; 1745 c->mbs = a->mbs; 1746 c->nbs = a->nbs; 1747 1748 ierr = PetscMalloc((mbs+1)*sizeof(int),&c->imax);CHKERRQ(ierr); 1749 ierr = PetscMalloc((mbs+1)*sizeof(int),&c->ilen);CHKERRQ(ierr); 1750 for (i=0; i<mbs; i++) { 1751 c->imax[i] = a->imax[i]; 1752 c->ilen[i] = a->ilen[i]; 1753 } 1754 1755 /* allocate the matrix space */ 1756 c->singlemalloc = PETSC_TRUE; 1757 len = (mbs+1)*sizeof(int) + nz*(bs2*sizeof(MatScalar) + sizeof(int)); 1758 ierr = PetscMalloc(len,&c->a);CHKERRQ(ierr); 1759 c->j = (int*)(c->a + nz*bs2); 1760 c->i = c->j + nz; 1761 ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(int));CHKERRQ(ierr); 1762 if (mbs > 0) { 1763 ierr = PetscMemcpy(c->j,a->j,nz*sizeof(int));CHKERRQ(ierr); 1764 if (cpvalues == MAT_COPY_VALUES) { 1765 ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 1766 } else { 1767 ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 1768 } 1769 } 1770 1771 PetscLogObjectMemory(C,len+2*(mbs+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqSBAIJ)); 1772 c->sorted = a->sorted; 1773 c->roworiented = a->roworiented; 1774 c->nonew = a->nonew; 1775 1776 if (a->diag) { 1777 ierr = PetscMalloc((mbs+1)*sizeof(int),&c->diag);CHKERRQ(ierr); 1778 PetscLogObjectMemory(C,(mbs+1)*sizeof(int)); 1779 for (i=0; i<mbs; i++) { 1780 c->diag[i] = a->diag[i]; 1781 } 1782 } else c->diag = 0; 1783 c->nz = a->nz; 1784 c->maxnz = a->maxnz; 1785 c->solve_work = 0; 1786 C->spptr = 0; /* Dangerous -I'm throwing away a->spptr */ 1787 c->mult_work = 0; 1788 *B = C; 1789 ierr = PetscFListDuplicate(A->qlist,&C->qlist);CHKERRQ(ierr); 1790 PetscFunctionReturn(0); 1791 } 1792 1793 #undef __FUNCT__ 1794 #define __FUNCT__ "MatLoad_SeqSBAIJ" 1795 int MatLoad_SeqSBAIJ(PetscViewer viewer,const MatType type,Mat *A) 1796 { 1797 Mat_SeqSBAIJ *a; 1798 Mat B; 1799 int i,nz,ierr,fd,header[4],size,*rowlengths=0,M,N,bs=1; 1800 int *mask,mbs,*jj,j,rowcount,nzcount,k,*s_browlengths,maskcount; 1801 int kmax,jcount,block,idx,point,nzcountb,extra_rows; 1802 int *masked,nmask,tmp,bs2,ishift; 1803 PetscScalar *aa; 1804 MPI_Comm comm = ((PetscObject)viewer)->comm; 1805 1806 PetscFunctionBegin; 1807 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1808 bs2 = bs*bs; 1809 1810 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1811 if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"view must have one processor"); 1812 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1813 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 1814 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); 1815 M = header[1]; N = header[2]; nz = header[3]; 1816 1817 if (header[3] < 0) { 1818 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqSBAIJ"); 1819 } 1820 1821 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 1822 1823 /* 1824 This code adds extra rows to make sure the number of rows is 1825 divisible by the blocksize 1826 */ 1827 mbs = M/bs; 1828 extra_rows = bs - M + bs*(mbs); 1829 if (extra_rows == bs) extra_rows = 0; 1830 else mbs++; 1831 if (extra_rows) { 1832 PetscLogInfo(0,"MatLoad_SeqSBAIJ:Padding loaded matrix to match blocksize\n"); 1833 } 1834 1835 /* read in row lengths */ 1836 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 1837 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1838 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 1839 1840 /* read in column indices */ 1841 ierr = PetscMalloc((nz+extra_rows)*sizeof(int),&jj);CHKERRQ(ierr); 1842 ierr = PetscBinaryRead(fd,jj,nz,PETSC_INT);CHKERRQ(ierr); 1843 for (i=0; i<extra_rows; i++) jj[nz+i] = M+i; 1844 1845 /* loop over row lengths determining block row lengths */ 1846 ierr = PetscMalloc(mbs*sizeof(int),&s_browlengths);CHKERRQ(ierr); 1847 ierr = PetscMemzero(s_browlengths,mbs*sizeof(int));CHKERRQ(ierr); 1848 ierr = PetscMalloc(2*mbs*sizeof(int),&mask);CHKERRQ(ierr); 1849 ierr = PetscMemzero(mask,mbs*sizeof(int));CHKERRQ(ierr); 1850 masked = mask + mbs; 1851 rowcount = 0; nzcount = 0; 1852 for (i=0; i<mbs; i++) { 1853 nmask = 0; 1854 for (j=0; j<bs; j++) { 1855 kmax = rowlengths[rowcount]; 1856 for (k=0; k<kmax; k++) { 1857 tmp = jj[nzcount++]/bs; /* block col. index */ 1858 if (!mask[tmp] && tmp >= i) {masked[nmask++] = tmp; mask[tmp] = 1;} 1859 } 1860 rowcount++; 1861 } 1862 s_browlengths[i] += nmask; 1863 1864 /* zero out the mask elements we set */ 1865 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 1866 } 1867 1868 /* create our matrix */ 1869 ierr = MatCreate(comm,M+extra_rows,N+extra_rows,M+extra_rows,N+extra_rows,&B);CHKERRQ(ierr); 1870 ierr = MatSetType(B,type);CHKERRQ(ierr); 1871 ierr = MatSeqSBAIJSetPreallocation(B,bs,0,s_browlengths);CHKERRQ(ierr); 1872 a = (Mat_SeqSBAIJ*)B->data; 1873 1874 /* set matrix "i" values */ 1875 a->i[0] = 0; 1876 for (i=1; i<= mbs; i++) { 1877 a->i[i] = a->i[i-1] + s_browlengths[i-1]; 1878 a->ilen[i-1] = s_browlengths[i-1]; 1879 } 1880 a->nz = a->i[mbs]; 1881 1882 /* read in nonzero values */ 1883 ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);CHKERRQ(ierr); 1884 ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); 1885 for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0; 1886 1887 /* set "a" and "j" values into matrix */ 1888 nzcount = 0; jcount = 0; 1889 for (i=0; i<mbs; i++) { 1890 nzcountb = nzcount; 1891 nmask = 0; 1892 for (j=0; j<bs; j++) { 1893 kmax = rowlengths[i*bs+j]; 1894 for (k=0; k<kmax; k++) { 1895 tmp = jj[nzcount++]/bs; /* block col. index */ 1896 if (!mask[tmp] && tmp >= i) { masked[nmask++] = tmp; mask[tmp] = 1;} 1897 } 1898 } 1899 /* sort the masked values */ 1900 ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); 1901 1902 /* set "j" values into matrix */ 1903 maskcount = 1; 1904 for (j=0; j<nmask; j++) { 1905 a->j[jcount++] = masked[j]; 1906 mask[masked[j]] = maskcount++; 1907 } 1908 1909 /* set "a" values into matrix */ 1910 ishift = bs2*a->i[i]; 1911 for (j=0; j<bs; j++) { 1912 kmax = rowlengths[i*bs+j]; 1913 for (k=0; k<kmax; k++) { 1914 tmp = jj[nzcountb]/bs ; /* block col. index */ 1915 if (tmp >= i){ 1916 block = mask[tmp] - 1; 1917 point = jj[nzcountb] - bs*tmp; 1918 idx = ishift + bs2*block + j + bs*point; 1919 a->a[idx] = aa[nzcountb]; 1920 } 1921 nzcountb++; 1922 } 1923 } 1924 /* zero out the mask elements we set */ 1925 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 1926 } 1927 if (jcount != a->nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); 1928 1929 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1930 ierr = PetscFree(s_browlengths);CHKERRQ(ierr); 1931 ierr = PetscFree(aa);CHKERRQ(ierr); 1932 ierr = PetscFree(jj);CHKERRQ(ierr); 1933 ierr = PetscFree(mask);CHKERRQ(ierr); 1934 1935 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1936 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1937 ierr = MatView_Private(B);CHKERRQ(ierr); 1938 *A = B; 1939 PetscFunctionReturn(0); 1940 } 1941 1942 #undef __FUNCT__ 1943 #define __FUNCT__ "MatRelax_SeqSBAIJ" 1944 int MatRelax_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 1945 { 1946 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 1947 MatScalar *aa=a->a,*v,*v1; 1948 PetscScalar *x,*b,*t,sum,d; 1949 int m=a->mbs,bs=a->bs,*ai=a->i,*aj=a->j,ierr; 1950 int nz,nz1,*vj,*vj1,i; 1951 1952 PetscFunctionBegin; 1953 its = its*lits; 1954 if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 1955 1956 if (bs > 1) 1957 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 1958 1959 ierr = VecGetArrayFast(xx,&x);CHKERRQ(ierr); 1960 if (xx != bb) { 1961 ierr = VecGetArrayFast(bb,&b);CHKERRQ(ierr); 1962 } else { 1963 b = x; 1964 } 1965 1966 ierr = PetscMalloc(m*sizeof(PetscScalar),&t);CHKERRQ(ierr); 1967 1968 if (flag & SOR_ZERO_INITIAL_GUESS) { 1969 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1970 for (i=0; i<m; i++) 1971 t[i] = b[i]; 1972 1973 for (i=0; i<m; i++){ 1974 d = *(aa + ai[i]); /* diag[i] */ 1975 v = aa + ai[i] + 1; 1976 vj = aj + ai[i] + 1; 1977 nz = ai[i+1] - ai[i] - 1; 1978 x[i] = omega*t[i]/d; 1979 while (nz--) t[*vj++] -= x[i]*(*v++); /* update rhs */ 1980 PetscLogFlops(2*nz-1); 1981 } 1982 } 1983 1984 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1985 for (i=0; i<m; i++) 1986 t[i] = b[i]; 1987 1988 for (i=0; i<m-1; i++){ /* update rhs */ 1989 v = aa + ai[i] + 1; 1990 vj = aj + ai[i] + 1; 1991 nz = ai[i+1] - ai[i] - 1; 1992 while (nz--) t[*vj++] -= x[i]*(*v++); 1993 PetscLogFlops(2*nz-1); 1994 } 1995 for (i=m-1; i>=0; i--){ 1996 d = *(aa + ai[i]); 1997 v = aa + ai[i] + 1; 1998 vj = aj + ai[i] + 1; 1999 nz = ai[i+1] - ai[i] - 1; 2000 sum = t[i]; 2001 while (nz--) sum -= x[*vj++]*(*v++); 2002 PetscLogFlops(2*nz-1); 2003 x[i] = (1-omega)*x[i] + omega*sum/d; 2004 } 2005 } 2006 its--; 2007 } 2008 2009 while (its--) { 2010 /* 2011 forward sweep: 2012 for i=0,...,m-1: 2013 sum[i] = (b[i] - U(i,:)x )/d[i]; 2014 x[i] = (1-omega)x[i] + omega*sum[i]; 2015 b = b - x[i]*U^T(i,:); 2016 2017 */ 2018 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 2019 for (i=0; i<m; i++) 2020 t[i] = b[i]; 2021 2022 for (i=0; i<m; i++){ 2023 d = *(aa + ai[i]); /* diag[i] */ 2024 v = aa + ai[i] + 1; v1=v; 2025 vj = aj + ai[i] + 1; vj1=vj; 2026 nz = ai[i+1] - ai[i] - 1; nz1=nz; 2027 sum = t[i]; 2028 while (nz1--) sum -= (*v1++)*x[*vj1++]; 2029 x[i] = (1-omega)*x[i] + omega*sum/d; 2030 while (nz--) t[*vj++] -= x[i]*(*v++); 2031 PetscLogFlops(4*nz-2); 2032 } 2033 } 2034 2035 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 2036 /* 2037 backward sweep: 2038 b = b - x[i]*U^T(i,:), i=0,...,n-2 2039 for i=m-1,...,0: 2040 sum[i] = (b[i] - U(i,:)x )/d[i]; 2041 x[i] = (1-omega)x[i] + omega*sum[i]; 2042 */ 2043 for (i=0; i<m; i++) 2044 t[i] = b[i]; 2045 2046 for (i=0; i<m-1; i++){ /* update rhs */ 2047 v = aa + ai[i] + 1; 2048 vj = aj + ai[i] + 1; 2049 nz = ai[i+1] - ai[i] - 1; 2050 while (nz--) t[*vj++] -= x[i]*(*v++); 2051 PetscLogFlops(2*nz-1); 2052 } 2053 for (i=m-1; i>=0; i--){ 2054 d = *(aa + ai[i]); 2055 v = aa + ai[i] + 1; 2056 vj = aj + ai[i] + 1; 2057 nz = ai[i+1] - ai[i] - 1; 2058 sum = t[i]; 2059 while (nz--) sum -= x[*vj++]*(*v++); 2060 PetscLogFlops(2*nz-1); 2061 x[i] = (1-omega)*x[i] + omega*sum/d; 2062 } 2063 } 2064 } 2065 2066 ierr = PetscFree(t); CHKERRQ(ierr); 2067 ierr = VecRestoreArrayFast(xx,&x);CHKERRQ(ierr); 2068 if (bb != xx) { 2069 ierr = VecRestoreArrayFast(bb,&b);CHKERRQ(ierr); 2070 } 2071 2072 PetscFunctionReturn(0); 2073 } 2074 2075 2076 2077 2078 2079 2080