1 /*$Id: mpisbaij.c,v 1.61 2001/08/10 03:31:37 bsmith Exp $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "src/vec/vecimpl.h" 5 #include "mpisbaij.h" 6 #include "src/mat/impls/sbaij/seq/sbaij.h" 7 8 extern int MatSetUpMultiply_MPISBAIJ(Mat); 9 extern int MatSetUpMultiply_MPISBAIJ_2comm(Mat); 10 extern int DisAssemble_MPISBAIJ(Mat); 11 extern int MatIncreaseOverlap_MPISBAIJ(Mat,int,IS *,int); 12 extern int MatGetSubMatrices_MPISBAIJ(Mat,int,IS *,IS *,MatReuse,Mat **); 13 extern int MatGetValues_SeqSBAIJ(Mat,int,int *,int,int *,PetscScalar *); 14 extern int MatSetValues_SeqSBAIJ(Mat,int,int *,int,int *,PetscScalar *,InsertMode); 15 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,int*,int,int*,PetscScalar*,InsertMode); 16 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,PetscScalar**); 17 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,PetscScalar**); 18 extern int MatPrintHelp_SeqSBAIJ(Mat); 19 extern int MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 20 extern int MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 21 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 22 extern int MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,int,int,Vec); 23 24 /* UGLY, ugly, ugly 25 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 26 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 27 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 28 converts the entries into single precision and then calls ..._MatScalar() to put them 29 into the single precision data structures. 30 */ 31 #if defined(PETSC_USE_MAT_SINGLE) 32 extern int MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 33 extern int MatSetValues_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 34 extern int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 35 extern int MatSetValues_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 36 extern int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 37 #else 38 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 39 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 40 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 41 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 42 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 43 #endif 44 45 EXTERN_C_BEGIN 46 #undef __FUNCT__ 47 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 48 int MatStoreValues_MPISBAIJ(Mat mat) 49 { 50 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 51 int ierr; 52 53 PetscFunctionBegin; 54 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 55 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 56 PetscFunctionReturn(0); 57 } 58 EXTERN_C_END 59 60 EXTERN_C_BEGIN 61 #undef __FUNCT__ 62 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 63 int MatRetrieveValues_MPISBAIJ(Mat mat) 64 { 65 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 66 int ierr; 67 68 PetscFunctionBegin; 69 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 70 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 71 PetscFunctionReturn(0); 72 } 73 EXTERN_C_END 74 75 /* 76 Local utility routine that creates a mapping from the global column 77 number to the local number in the off-diagonal part of the local 78 storage of the matrix. This is done in a non scable way since the 79 length of colmap equals the global matrix length. 80 */ 81 #undef __FUNCT__ 82 #define __FUNCT__ "CreateColmap_MPISBAIJ_Private" 83 static int CreateColmap_MPISBAIJ_Private(Mat mat) 84 { 85 PetscFunctionBegin; 86 SETERRQ(1,"Function not yet written for SBAIJ format"); 87 /* PetscFunctionReturn(0); */ 88 } 89 90 #define CHUNKSIZE 10 91 92 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 93 { \ 94 \ 95 brow = row/bs; \ 96 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 97 rmax = aimax[brow]; nrow = ailen[brow]; \ 98 bcol = col/bs; \ 99 ridx = row % bs; cidx = col % bs; \ 100 low = 0; high = nrow; \ 101 while (high-low > 3) { \ 102 t = (low+high)/2; \ 103 if (rp[t] > bcol) high = t; \ 104 else low = t; \ 105 } \ 106 for (_i=low; _i<high; _i++) { \ 107 if (rp[_i] > bcol) break; \ 108 if (rp[_i] == bcol) { \ 109 bap = ap + bs2*_i + bs*cidx + ridx; \ 110 if (addv == ADD_VALUES) *bap += value; \ 111 else *bap = value; \ 112 goto a_noinsert; \ 113 } \ 114 } \ 115 if (a->nonew == 1) goto a_noinsert; \ 116 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 117 if (nrow >= rmax) { \ 118 /* there is no extra room in row, therefore enlarge */ \ 119 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 120 MatScalar *new_a; \ 121 \ 122 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 123 \ 124 /* malloc new storage space */ \ 125 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 126 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 127 new_j = (int*)(new_a + bs2*new_nz); \ 128 new_i = new_j + new_nz; \ 129 \ 130 /* copy over old data into new slots */ \ 131 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 132 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 133 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 134 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 135 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 136 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 137 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 138 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 139 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 140 /* free up old matrix storage */ \ 141 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 142 if (!a->singlemalloc) { \ 143 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 144 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 145 } \ 146 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 147 a->singlemalloc = PETSC_TRUE; \ 148 \ 149 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 150 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 151 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 152 a->s_maxnz += bs2*CHUNKSIZE; \ 153 a->reallocs++; \ 154 a->s_nz++; \ 155 } \ 156 N = nrow++ - 1; \ 157 /* shift up all the later entries in this row */ \ 158 for (ii=N; ii>=_i; ii--) { \ 159 rp[ii+1] = rp[ii]; \ 160 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 161 } \ 162 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 163 rp[_i] = bcol; \ 164 ap[bs2*_i + bs*cidx + ridx] = value; \ 165 a_noinsert:; \ 166 ailen[brow] = nrow; \ 167 } 168 #ifndef MatSetValues_SeqBAIJ_B_Private 169 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 170 { \ 171 brow = row/bs; \ 172 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 173 rmax = bimax[brow]; nrow = bilen[brow]; \ 174 bcol = col/bs; \ 175 ridx = row % bs; cidx = col % bs; \ 176 low = 0; high = nrow; \ 177 while (high-low > 3) { \ 178 t = (low+high)/2; \ 179 if (rp[t] > bcol) high = t; \ 180 else low = t; \ 181 } \ 182 for (_i=low; _i<high; _i++) { \ 183 if (rp[_i] > bcol) break; \ 184 if (rp[_i] == bcol) { \ 185 bap = ap + bs2*_i + bs*cidx + ridx; \ 186 if (addv == ADD_VALUES) *bap += value; \ 187 else *bap = value; \ 188 goto b_noinsert; \ 189 } \ 190 } \ 191 if (b->nonew == 1) goto b_noinsert; \ 192 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 193 if (nrow >= rmax) { \ 194 /* there is no extra room in row, therefore enlarge */ \ 195 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 196 MatScalar *new_a; \ 197 \ 198 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 199 \ 200 /* malloc new storage space */ \ 201 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 202 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 203 new_j = (int*)(new_a + bs2*new_nz); \ 204 new_i = new_j + new_nz; \ 205 \ 206 /* copy over old data into new slots */ \ 207 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 208 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 209 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 210 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 211 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 212 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 213 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 214 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 215 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 216 /* free up old matrix storage */ \ 217 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 218 if (!b->singlemalloc) { \ 219 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 220 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 221 } \ 222 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 223 b->singlemalloc = PETSC_TRUE; \ 224 \ 225 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 226 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 227 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 228 b->maxnz += bs2*CHUNKSIZE; \ 229 b->reallocs++; \ 230 b->nz++; \ 231 } \ 232 N = nrow++ - 1; \ 233 /* shift up all the later entries in this row */ \ 234 for (ii=N; ii>=_i; ii--) { \ 235 rp[ii+1] = rp[ii]; \ 236 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 237 } \ 238 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 239 rp[_i] = bcol; \ 240 ap[bs2*_i + bs*cidx + ridx] = value; \ 241 b_noinsert:; \ 242 bilen[brow] = nrow; \ 243 } 244 #endif 245 246 #if defined(PETSC_USE_MAT_SINGLE) 247 #undef __FUNCT__ 248 #define __FUNCT__ "MatSetValues_MPISBAIJ" 249 int MatSetValues_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv) 250 { 251 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 252 int ierr,i,N = m*n; 253 MatScalar *vsingle; 254 255 PetscFunctionBegin; 256 if (N > b->setvalueslen) { 257 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 258 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 259 b->setvalueslen = N; 260 } 261 vsingle = b->setvaluescopy; 262 263 for (i=0; i<N; i++) { 264 vsingle[i] = v[i]; 265 } 266 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 267 PetscFunctionReturn(0); 268 } 269 270 #undef __FUNCT__ 271 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 272 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv) 273 { 274 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 275 int ierr,i,N = m*n*b->bs2; 276 MatScalar *vsingle; 277 278 PetscFunctionBegin; 279 if (N > b->setvalueslen) { 280 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 281 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 282 b->setvalueslen = N; 283 } 284 vsingle = b->setvaluescopy; 285 for (i=0; i<N; i++) { 286 vsingle[i] = v[i]; 287 } 288 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 289 PetscFunctionReturn(0); 290 } 291 292 #undef __FUNCT__ 293 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT" 294 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv) 295 { 296 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 297 int ierr,i,N = m*n; 298 MatScalar *vsingle; 299 300 PetscFunctionBegin; 301 SETERRQ(1,"Function not yet written for SBAIJ format"); 302 /* PetscFunctionReturn(0); */ 303 } 304 305 #undef __FUNCT__ 306 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT" 307 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv) 308 { 309 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 310 int ierr,i,N = m*n*b->bs2; 311 MatScalar *vsingle; 312 313 PetscFunctionBegin; 314 SETERRQ(1,"Function not yet written for SBAIJ format"); 315 /* PetscFunctionReturn(0); */ 316 } 317 #endif 318 319 /* Only add/insert a(i,j) with i<=j (blocks). 320 Any a(i,j) with i>j input by user is ingored. 321 */ 322 #undef __FUNCT__ 323 #define __FUNCT__ "MatSetValues_MPIBAIJ" 324 int MatSetValues_MPISBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 325 { 326 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 327 MatScalar value; 328 PetscTruth roworiented = baij->roworiented; 329 int ierr,i,j,row,col; 330 int rstart_orig=baij->rstart_bs; 331 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 332 int cend_orig=baij->cend_bs,bs=baij->bs; 333 334 /* Some Variables required in the macro */ 335 Mat A = baij->A; 336 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 337 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 338 MatScalar *aa=a->a; 339 340 Mat B = baij->B; 341 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 342 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 343 MatScalar *ba=b->a; 344 345 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 346 int low,high,t,ridx,cidx,bs2=a->bs2; 347 MatScalar *ap,*bap; 348 349 /* for stash */ 350 int n_loc, *in_loc=0; 351 MatScalar *v_loc=0; 352 353 PetscFunctionBegin; 354 355 if(!baij->donotstash){ 356 ierr = PetscMalloc(n*sizeof(int),&in_loc);CHKERRQ(ierr); 357 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 358 } 359 360 for (i=0; i<m; i++) { 361 if (im[i] < 0) continue; 362 #if defined(PETSC_USE_BOPT_g) 363 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 364 #endif 365 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 366 row = im[i] - rstart_orig; /* local row index */ 367 for (j=0; j<n; j++) { 368 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 369 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 370 col = in[j] - cstart_orig; /* local col index */ 371 brow = row/bs; bcol = col/bs; 372 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 373 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 374 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 375 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 376 } else if (in[j] < 0) continue; 377 #if defined(PETSC_USE_BOPT_g) 378 else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Col too large");} 379 #endif 380 else { /* off-diag entry (B) */ 381 if (mat->was_assembled) { 382 if (!baij->colmap) { 383 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 384 } 385 #if defined (PETSC_USE_CTABLE) 386 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 387 col = col - 1; 388 #else 389 col = baij->colmap[in[j]/bs] - 1; 390 #endif 391 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 392 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 393 col = in[j]; 394 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 395 B = baij->B; 396 b = (Mat_SeqBAIJ*)(B)->data; 397 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 398 ba=b->a; 399 } else col += in[j]%bs; 400 } else col = in[j]; 401 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 402 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 403 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 404 } 405 } 406 } else { /* off processor entry */ 407 if (!baij->donotstash) { 408 n_loc = 0; 409 for (j=0; j<n; j++){ 410 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 411 in_loc[n_loc] = in[j]; 412 if (roworiented) { 413 v_loc[n_loc] = v[i*n+j]; 414 } else { 415 v_loc[n_loc] = v[j*m+i]; 416 } 417 n_loc++; 418 } 419 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 420 } 421 } 422 } 423 424 if(!baij->donotstash){ 425 ierr = PetscFree(in_loc);CHKERRQ(ierr); 426 ierr = PetscFree(v_loc);CHKERRQ(ierr); 427 } 428 PetscFunctionReturn(0); 429 } 430 431 #undef __FUNCT__ 432 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 433 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 434 { 435 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 436 MatScalar *value,*barray=baij->barray; 437 PetscTruth roworiented = baij->roworiented; 438 int ierr,i,j,ii,jj,row,col,rstart=baij->rstart; 439 int rend=baij->rend,cstart=baij->cstart,stepval; 440 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 441 442 PetscFunctionBegin; 443 if(!barray) { 444 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 445 baij->barray = barray; 446 } 447 448 if (roworiented) { 449 stepval = (n-1)*bs; 450 } else { 451 stepval = (m-1)*bs; 452 } 453 for (i=0; i<m; i++) { 454 if (im[i] < 0) continue; 455 #if defined(PETSC_USE_BOPT_g) 456 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %d max %d",im[i],baij->Mbs); 457 #endif 458 if (im[i] >= rstart && im[i] < rend) { 459 row = im[i] - rstart; 460 for (j=0; j<n; j++) { 461 /* If NumCol = 1 then a copy is not required */ 462 if ((roworiented) && (n == 1)) { 463 barray = v + i*bs2; 464 } else if((!roworiented) && (m == 1)) { 465 barray = v + j*bs2; 466 } else { /* Here a copy is required */ 467 if (roworiented) { 468 value = v + i*(stepval+bs)*bs + j*bs; 469 } else { 470 value = v + j*(stepval+bs)*bs + i*bs; 471 } 472 for (ii=0; ii<bs; ii++,value+=stepval) { 473 for (jj=0; jj<bs; jj++) { 474 *barray++ = *value++; 475 } 476 } 477 barray -=bs2; 478 } 479 480 if (in[j] >= cstart && in[j] < cend){ 481 col = in[j] - cstart; 482 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 483 } 484 else if (in[j] < 0) continue; 485 #if defined(PETSC_USE_BOPT_g) 486 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %d max %d",in[j],baij->Nbs);} 487 #endif 488 else { 489 if (mat->was_assembled) { 490 if (!baij->colmap) { 491 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 492 } 493 494 #if defined(PETSC_USE_BOPT_g) 495 #if defined (PETSC_USE_CTABLE) 496 { int data; 497 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 498 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 499 } 500 #else 501 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 502 #endif 503 #endif 504 #if defined (PETSC_USE_CTABLE) 505 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 506 col = (col - 1)/bs; 507 #else 508 col = (baij->colmap[in[j]] - 1)/bs; 509 #endif 510 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 511 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 512 col = in[j]; 513 } 514 } 515 else col = in[j]; 516 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 517 } 518 } 519 } else { 520 if (!baij->donotstash) { 521 if (roworiented) { 522 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 523 } else { 524 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 525 } 526 } 527 } 528 } 529 PetscFunctionReturn(0); 530 } 531 532 #define HASH_KEY 0.6180339887 533 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 534 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 535 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 536 #undef __FUNCT__ 537 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT_MatScalar" 538 int MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 539 { 540 PetscFunctionBegin; 541 SETERRQ(1,"Function not yet written for SBAIJ format"); 542 /* PetscFunctionReturn(0); */ 543 } 544 545 #undef __FUNCT__ 546 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 547 int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 548 { 549 PetscFunctionBegin; 550 SETERRQ(1,"Function not yet written for SBAIJ format"); 551 /* PetscFunctionReturn(0); */ 552 } 553 554 #undef __FUNCT__ 555 #define __FUNCT__ "MatGetValues_MPISBAIJ" 556 int MatGetValues_MPISBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,PetscScalar *v) 557 { 558 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 559 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 560 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 561 562 PetscFunctionBegin; 563 for (i=0; i<m; i++) { 564 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 565 if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 566 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 567 row = idxm[i] - bsrstart; 568 for (j=0; j<n; j++) { 569 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 570 if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 571 if (idxn[j] >= bscstart && idxn[j] < bscend){ 572 col = idxn[j] - bscstart; 573 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 574 } else { 575 if (!baij->colmap) { 576 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 577 } 578 #if defined (PETSC_USE_CTABLE) 579 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 580 data --; 581 #else 582 data = baij->colmap[idxn[j]/bs]-1; 583 #endif 584 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 585 else { 586 col = data + idxn[j]%bs; 587 ierr = MatGetValues_SeqSBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 588 } 589 } 590 } 591 } else { 592 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 593 } 594 } 595 PetscFunctionReturn(0); 596 } 597 598 #undef __FUNCT__ 599 #define __FUNCT__ "MatNorm_MPISBAIJ" 600 int MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 601 { 602 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 603 /* Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ*)baij->A->data; */ 604 /* Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ*)baij->B->data; */ 605 int ierr; 606 PetscReal sum[2],*lnorm2; 607 608 PetscFunctionBegin; 609 if (baij->size == 1) { 610 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 611 } else { 612 if (type == NORM_FROBENIUS) { 613 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 614 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 615 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 616 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 617 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 618 /* 619 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 620 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], lnorm2=%g, %g\n",rank,lnorm2[0],lnorm2[1]); 621 */ 622 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 623 /* 624 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], sum=%g, %g\n",rank,sum[0],sum[1]); 625 PetscSynchronizedFlush(PETSC_COMM_WORLD); */ 626 627 *norm = sqrt(sum[0] + 2*sum[1]); 628 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 629 } else { 630 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 631 } 632 } 633 PetscFunctionReturn(0); 634 } 635 636 /* 637 Creates the hash table, and sets the table 638 This table is created only once. 639 If new entried need to be added to the matrix 640 then the hash table has to be destroyed and 641 recreated. 642 */ 643 #undef __FUNCT__ 644 #define __FUNCT__ "MatCreateHashTable_MPISBAIJ_Private" 645 int MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 646 { 647 PetscFunctionBegin; 648 SETERRQ(1,"Function not yet written for SBAIJ format"); 649 /* PetscFunctionReturn(0); */ 650 } 651 652 #undef __FUNCT__ 653 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 654 int MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 655 { 656 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 657 int ierr,nstash,reallocs; 658 InsertMode addv; 659 660 PetscFunctionBegin; 661 if (baij->donotstash) { 662 PetscFunctionReturn(0); 663 } 664 665 /* make sure all processors are either in INSERTMODE or ADDMODE */ 666 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 667 if (addv == (ADD_VALUES|INSERT_VALUES)) { 668 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 669 } 670 mat->insertmode = addv; /* in case this processor had no cache */ 671 672 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 673 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 674 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 675 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 676 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 677 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 678 PetscFunctionReturn(0); 679 } 680 681 #undef __FUNCT__ 682 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 683 int MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 684 { 685 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 686 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 687 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 688 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 689 int *row,*col,other_disassembled; 690 PetscTruth r1,r2,r3; 691 MatScalar *val; 692 InsertMode addv = mat->insertmode; 693 #if defined(PETSC_HAVE_SPOOLES) 694 PetscTruth flag; 695 #endif 696 697 PetscFunctionBegin; 698 699 if (!baij->donotstash) { 700 while (1) { 701 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 702 /* 703 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d]: in AssemblyEnd, stash, flg=%d\n",rank,flg); 704 PetscSynchronizedFlush(PETSC_COMM_WORLD); 705 */ 706 if (!flg) break; 707 708 for (i=0; i<n;) { 709 /* Now identify the consecutive vals belonging to the same row */ 710 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 711 if (j < n) ncols = j-i; 712 else ncols = n-i; 713 /* Now assemble all these values with a single function call */ 714 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 715 i = j; 716 } 717 } 718 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 719 /* Now process the block-stash. Since the values are stashed column-oriented, 720 set the roworiented flag to column oriented, and after MatSetValues() 721 restore the original flags */ 722 r1 = baij->roworiented; 723 r2 = a->roworiented; 724 r3 = b->roworiented; 725 baij->roworiented = PETSC_FALSE; 726 a->roworiented = PETSC_FALSE; 727 b->roworiented = PETSC_FALSE; 728 while (1) { 729 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 730 if (!flg) break; 731 732 for (i=0; i<n;) { 733 /* Now identify the consecutive vals belonging to the same row */ 734 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 735 if (j < n) ncols = j-i; 736 else ncols = n-i; 737 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 738 i = j; 739 } 740 } 741 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 742 baij->roworiented = r1; 743 a->roworiented = r2; 744 b->roworiented = r3; 745 } 746 747 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 748 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 749 750 /* determine if any processor has disassembled, if so we must 751 also disassemble ourselfs, in order that we may reassemble. */ 752 /* 753 if nonzero structure of submatrix B cannot change then we know that 754 no processor disassembled thus we can skip this stuff 755 */ 756 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 757 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 758 if (mat->was_assembled && !other_disassembled) { 759 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 760 } 761 } 762 763 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 764 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 765 } 766 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 767 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 768 769 #if defined(PETSC_USE_BOPT_g) 770 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 771 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 772 baij->ht_total_ct = 0; 773 baij->ht_insert_ct = 0; 774 } 775 #endif 776 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 777 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 778 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 779 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 780 } 781 782 if (baij->rowvalues) { 783 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 784 baij->rowvalues = 0; 785 } 786 787 #if defined(PETSC_HAVE_SPOOLES) 788 ierr = PetscOptionsHasName(mat->prefix,"-mat_sbaij_spooles",&flag);CHKERRQ(ierr); 789 if (flag) { ierr = MatUseSpooles_MPISBAIJ(mat);CHKERRQ(ierr); } 790 #endif 791 PetscFunctionReturn(0); 792 } 793 794 #undef __FUNCT__ 795 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 796 static int MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 797 { 798 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 799 int ierr,bs = baij->bs,size = baij->size,rank = baij->rank; 800 PetscTruth isascii,isdraw; 801 PetscViewer sviewer; 802 PetscViewerFormat format; 803 804 PetscFunctionBegin; 805 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 806 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 807 if (isascii) { 808 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 809 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 810 MatInfo info; 811 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 812 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 813 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 814 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 815 baij->bs,(int)info.memory);CHKERRQ(ierr); 816 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 817 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 818 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 819 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 820 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 821 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 822 PetscFunctionReturn(0); 823 } else if (format == PETSC_VIEWER_ASCII_INFO) { 824 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 825 PetscFunctionReturn(0); 826 } 827 } 828 829 if (isdraw) { 830 PetscDraw draw; 831 PetscTruth isnull; 832 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 833 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 834 } 835 836 if (size == 1) { 837 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 838 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 839 } else { 840 /* assemble the entire matrix onto first processor. */ 841 Mat A; 842 Mat_SeqSBAIJ *Aloc; 843 Mat_SeqBAIJ *Bloc; 844 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 845 MatScalar *a; 846 847 if (!rank) { 848 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 849 } else { 850 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 851 } 852 PetscLogObjectParent(mat,A); 853 854 /* copy over the A part */ 855 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 856 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 857 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 858 859 for (i=0; i<mbs; i++) { 860 rvals[0] = bs*(baij->rstart + i); 861 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 862 for (j=ai[i]; j<ai[i+1]; j++) { 863 col = (baij->cstart+aj[j])*bs; 864 for (k=0; k<bs; k++) { 865 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 866 col++; a += bs; 867 } 868 } 869 } 870 /* copy over the B part */ 871 Bloc = (Mat_SeqBAIJ*)baij->B->data; 872 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 873 for (i=0; i<mbs; i++) { 874 rvals[0] = bs*(baij->rstart + i); 875 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 876 for (j=ai[i]; j<ai[i+1]; j++) { 877 col = baij->garray[aj[j]]*bs; 878 for (k=0; k<bs; k++) { 879 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 880 col++; a += bs; 881 } 882 } 883 } 884 ierr = PetscFree(rvals);CHKERRQ(ierr); 885 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 886 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 /* 888 Everyone has to call to draw the matrix since the graphics waits are 889 synchronized across all processors that share the PetscDraw object 890 */ 891 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 892 if (!rank) { 893 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 894 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 895 } 896 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 897 ierr = MatDestroy(A);CHKERRQ(ierr); 898 } 899 PetscFunctionReturn(0); 900 } 901 902 #undef __FUNCT__ 903 #define __FUNCT__ "MatView_MPISBAIJ" 904 int MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 905 { 906 int ierr; 907 PetscTruth isascii,isdraw,issocket,isbinary; 908 909 PetscFunctionBegin; 910 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 911 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 912 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 913 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 914 if (isascii || isdraw || issocket || isbinary) { 915 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 916 } else { 917 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 918 } 919 PetscFunctionReturn(0); 920 } 921 922 #undef __FUNCT__ 923 #define __FUNCT__ "MatDestroy_MPISBAIJ" 924 int MatDestroy_MPISBAIJ(Mat mat) 925 { 926 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 927 int ierr; 928 929 PetscFunctionBegin; 930 #if defined(PETSC_USE_LOG) 931 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 932 #endif 933 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 934 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 935 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 936 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 937 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 938 #if defined (PETSC_USE_CTABLE) 939 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 940 #else 941 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 942 #endif 943 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 944 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 945 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 946 if (baij->slvec0) { 947 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 948 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 949 } 950 if (baij->slvec1) { 951 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 952 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 953 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 954 } 955 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 956 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 957 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 958 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 959 #if defined(PETSC_USE_MAT_SINGLE) 960 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 961 #endif 962 ierr = PetscFree(baij);CHKERRQ(ierr); 963 PetscFunctionReturn(0); 964 } 965 966 #undef __FUNCT__ 967 #define __FUNCT__ "MatMult_MPISBAIJ" 968 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 969 { 970 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 971 int ierr,nt,mbs=a->mbs,bs=a->bs; 972 PetscScalar *x,*from,zero=0.0; 973 974 PetscFunctionBegin; 975 /* 976 PetscSynchronizedPrintf(PETSC_COMM_WORLD," _1comm is called ...\n"); 977 PetscSynchronizedFlush(PETSC_COMM_WORLD); 978 */ 979 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 980 if (nt != A->n) { 981 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 982 } 983 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 984 if (nt != A->m) { 985 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 986 } 987 988 /* diagonal part */ 989 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 990 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 991 992 /* subdiagonal part */ 993 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 994 995 /* copy x into the vec slvec0 */ 996 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 997 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 998 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 999 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1000 1001 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1002 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1003 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1004 1005 /* supperdiagonal part */ 1006 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 1007 1008 PetscFunctionReturn(0); 1009 } 1010 1011 #undef __FUNCT__ 1012 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 1013 int MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 1014 { 1015 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1016 int ierr,nt; 1017 1018 PetscFunctionBegin; 1019 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1020 if (nt != A->n) { 1021 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1022 } 1023 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1024 if (nt != A->m) { 1025 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1026 } 1027 1028 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1029 /* do diagonal part */ 1030 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1031 /* do supperdiagonal part */ 1032 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1033 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1034 /* do subdiagonal part */ 1035 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1036 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1037 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1038 1039 PetscFunctionReturn(0); 1040 } 1041 1042 #undef __FUNCT__ 1043 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 1044 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1045 { 1046 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1047 int ierr,mbs=a->mbs,bs=a->bs; 1048 PetscScalar *x,*from,zero=0.0; 1049 1050 PetscFunctionBegin; 1051 /* 1052 PetscSynchronizedPrintf(PETSC_COMM_WORLD," MatMultAdd is called ...\n"); 1053 PetscSynchronizedFlush(PETSC_COMM_WORLD); 1054 */ 1055 /* diagonal part */ 1056 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 1057 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 1058 1059 /* subdiagonal part */ 1060 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 1061 1062 /* copy x into the vec slvec0 */ 1063 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 1064 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1065 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1066 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1067 1068 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1069 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1070 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1071 1072 /* supperdiagonal part */ 1073 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 1074 1075 PetscFunctionReturn(0); 1076 } 1077 1078 #undef __FUNCT__ 1079 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 1080 int MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 1081 { 1082 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1083 int ierr; 1084 1085 PetscFunctionBegin; 1086 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1087 /* do diagonal part */ 1088 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1089 /* do supperdiagonal part */ 1090 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1091 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1092 1093 /* do subdiagonal part */ 1094 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1095 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1096 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1097 1098 PetscFunctionReturn(0); 1099 } 1100 1101 #undef __FUNCT__ 1102 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1103 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1104 { 1105 PetscFunctionBegin; 1106 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 1107 /* PetscFunctionReturn(0); */ 1108 } 1109 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1112 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1113 { 1114 PetscFunctionBegin; 1115 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 1116 /* PetscFunctionReturn(0); */ 1117 } 1118 1119 /* 1120 This only works correctly for square matrices where the subblock A->A is the 1121 diagonal block 1122 */ 1123 #undef __FUNCT__ 1124 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1125 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1126 { 1127 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1128 int ierr; 1129 1130 PetscFunctionBegin; 1131 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1132 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatScale_MPISBAIJ" 1138 int MatScale_MPISBAIJ(PetscScalar *aa,Mat A) 1139 { 1140 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1141 int ierr; 1142 1143 PetscFunctionBegin; 1144 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1145 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1146 PetscFunctionReturn(0); 1147 } 1148 1149 #undef __FUNCT__ 1150 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1151 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 1152 { 1153 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1154 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1155 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 1156 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1157 int *cmap,*idx_p,cstart = mat->cstart; 1158 1159 PetscFunctionBegin; 1160 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1161 mat->getrowactive = PETSC_TRUE; 1162 1163 if (!mat->rowvalues && (idx || v)) { 1164 /* 1165 allocate enough space to hold information from the longest row. 1166 */ 1167 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1168 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1169 int max = 1,mbs = mat->mbs,tmp; 1170 for (i=0; i<mbs; i++) { 1171 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1172 if (max < tmp) { max = tmp; } 1173 } 1174 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1175 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 1176 } 1177 1178 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1179 lrow = row - brstart; /* local row index */ 1180 1181 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1182 if (!v) {pvA = 0; pvB = 0;} 1183 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1184 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1185 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1186 nztot = nzA + nzB; 1187 1188 cmap = mat->garray; 1189 if (v || idx) { 1190 if (nztot) { 1191 /* Sort by increasing column numbers, assuming A and B already sorted */ 1192 int imark = -1; 1193 if (v) { 1194 *v = v_p = mat->rowvalues; 1195 for (i=0; i<nzB; i++) { 1196 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1197 else break; 1198 } 1199 imark = i; 1200 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1201 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1202 } 1203 if (idx) { 1204 *idx = idx_p = mat->rowindices; 1205 if (imark > -1) { 1206 for (i=0; i<imark; i++) { 1207 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1208 } 1209 } else { 1210 for (i=0; i<nzB; i++) { 1211 if (cmap[cworkB[i]/bs] < cstart) 1212 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1213 else break; 1214 } 1215 imark = i; 1216 } 1217 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1218 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1219 } 1220 } else { 1221 if (idx) *idx = 0; 1222 if (v) *v = 0; 1223 } 1224 } 1225 *nz = nztot; 1226 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1227 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1228 PetscFunctionReturn(0); 1229 } 1230 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1233 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1234 { 1235 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1236 1237 PetscFunctionBegin; 1238 if (baij->getrowactive == PETSC_FALSE) { 1239 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1240 } 1241 baij->getrowactive = PETSC_FALSE; 1242 PetscFunctionReturn(0); 1243 } 1244 1245 #undef __FUNCT__ 1246 #define __FUNCT__ "MatGetBlockSize_MPISBAIJ" 1247 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1248 { 1249 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1250 1251 PetscFunctionBegin; 1252 *bs = baij->bs; 1253 PetscFunctionReturn(0); 1254 } 1255 1256 #undef __FUNCT__ 1257 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1258 int MatZeroEntries_MPISBAIJ(Mat A) 1259 { 1260 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1261 int ierr; 1262 1263 PetscFunctionBegin; 1264 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1265 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1266 PetscFunctionReturn(0); 1267 } 1268 1269 #undef __FUNCT__ 1270 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1271 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1272 { 1273 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1274 Mat A = a->A,B = a->B; 1275 int ierr; 1276 PetscReal isend[5],irecv[5]; 1277 1278 PetscFunctionBegin; 1279 info->block_size = (PetscReal)a->bs; 1280 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1281 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1282 isend[3] = info->memory; isend[4] = info->mallocs; 1283 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1284 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1285 isend[3] += info->memory; isend[4] += info->mallocs; 1286 if (flag == MAT_LOCAL) { 1287 info->nz_used = isend[0]; 1288 info->nz_allocated = isend[1]; 1289 info->nz_unneeded = isend[2]; 1290 info->memory = isend[3]; 1291 info->mallocs = isend[4]; 1292 } else if (flag == MAT_GLOBAL_MAX) { 1293 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1294 info->nz_used = irecv[0]; 1295 info->nz_allocated = irecv[1]; 1296 info->nz_unneeded = irecv[2]; 1297 info->memory = irecv[3]; 1298 info->mallocs = irecv[4]; 1299 } else if (flag == MAT_GLOBAL_SUM) { 1300 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1301 info->nz_used = irecv[0]; 1302 info->nz_allocated = irecv[1]; 1303 info->nz_unneeded = irecv[2]; 1304 info->memory = irecv[3]; 1305 info->mallocs = irecv[4]; 1306 } else { 1307 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1308 } 1309 info->rows_global = (PetscReal)A->M; 1310 info->columns_global = (PetscReal)A->N; 1311 info->rows_local = (PetscReal)A->m; 1312 info->columns_local = (PetscReal)A->N; 1313 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1314 info->fill_ratio_needed = 0; 1315 info->factor_mallocs = 0; 1316 PetscFunctionReturn(0); 1317 } 1318 1319 #undef __FUNCT__ 1320 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1321 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1322 { 1323 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1324 int ierr; 1325 1326 PetscFunctionBegin; 1327 switch (op) { 1328 case MAT_NO_NEW_NONZERO_LOCATIONS: 1329 case MAT_YES_NEW_NONZERO_LOCATIONS: 1330 case MAT_COLUMNS_UNSORTED: 1331 case MAT_COLUMNS_SORTED: 1332 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1333 case MAT_KEEP_ZEROED_ROWS: 1334 case MAT_NEW_NONZERO_LOCATION_ERR: 1335 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1336 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1337 break; 1338 case MAT_ROW_ORIENTED: 1339 a->roworiented = PETSC_TRUE; 1340 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1341 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1342 break; 1343 case MAT_ROWS_SORTED: 1344 case MAT_ROWS_UNSORTED: 1345 case MAT_YES_NEW_DIAGONALS: 1346 case MAT_USE_SINGLE_PRECISION_SOLVES: 1347 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1348 break; 1349 case MAT_COLUMN_ORIENTED: 1350 a->roworiented = PETSC_FALSE; 1351 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1352 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1353 break; 1354 case MAT_IGNORE_OFF_PROC_ENTRIES: 1355 a->donotstash = PETSC_TRUE; 1356 break; 1357 case MAT_NO_NEW_DIAGONALS: 1358 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1359 case MAT_USE_HASH_TABLE: 1360 a->ht_flag = PETSC_TRUE; 1361 break; 1362 default: 1363 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1364 } 1365 PetscFunctionReturn(0); 1366 } 1367 1368 #undef __FUNCT__ 1369 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1370 int MatTranspose_MPISBAIJ(Mat A,Mat *B) 1371 { 1372 int ierr; 1373 PetscFunctionBegin; 1374 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1375 PetscFunctionReturn(0); 1376 } 1377 1378 #undef __FUNCT__ 1379 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1380 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1381 { 1382 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1383 Mat a = baij->A,b = baij->B; 1384 int ierr,s1,s2,s3; 1385 1386 PetscFunctionBegin; 1387 if (ll != rr) { 1388 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1389 } 1390 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1391 if (rr) { 1392 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1393 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1394 /* Overlap communication with computation. */ 1395 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1396 /*} if (ll) { */ 1397 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1398 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1399 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1400 /* } */ 1401 /* scale the diagonal block */ 1402 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1403 1404 /* if (rr) { */ 1405 /* Do a scatter end and then right scale the off-diagonal block */ 1406 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1407 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1408 } 1409 1410 PetscFunctionReturn(0); 1411 } 1412 1413 #undef __FUNCT__ 1414 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1415 int MatZeroRows_MPISBAIJ(Mat A,IS is,PetscScalar *diag) 1416 { 1417 PetscFunctionBegin; 1418 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1419 } 1420 1421 #undef __FUNCT__ 1422 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1423 int MatPrintHelp_MPISBAIJ(Mat A) 1424 { 1425 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1426 MPI_Comm comm = A->comm; 1427 static int called = 0; 1428 int ierr; 1429 1430 PetscFunctionBegin; 1431 if (!a->rank) { 1432 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1433 } 1434 if (called) {PetscFunctionReturn(0);} else called = 1; 1435 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1436 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1437 PetscFunctionReturn(0); 1438 } 1439 1440 #undef __FUNCT__ 1441 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1442 int MatSetUnfactored_MPISBAIJ(Mat A) 1443 { 1444 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1445 int ierr; 1446 1447 PetscFunctionBegin; 1448 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1449 PetscFunctionReturn(0); 1450 } 1451 1452 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1453 1454 #undef __FUNCT__ 1455 #define __FUNCT__ "MatEqual_MPISBAIJ" 1456 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1457 { 1458 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1459 Mat a,b,c,d; 1460 PetscTruth flg; 1461 int ierr; 1462 1463 PetscFunctionBegin; 1464 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg);CHKERRQ(ierr); 1465 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1466 a = matA->A; b = matA->B; 1467 c = matB->A; d = matB->B; 1468 1469 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1470 if (flg == PETSC_TRUE) { 1471 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1472 } 1473 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1474 PetscFunctionReturn(0); 1475 } 1476 1477 #undef __FUNCT__ 1478 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1479 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1480 { 1481 int ierr; 1482 1483 PetscFunctionBegin; 1484 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1485 PetscFunctionReturn(0); 1486 } 1487 /* -------------------------------------------------------------------*/ 1488 static struct _MatOps MatOps_Values = { 1489 MatSetValues_MPISBAIJ, 1490 MatGetRow_MPISBAIJ, 1491 MatRestoreRow_MPISBAIJ, 1492 MatMult_MPISBAIJ, 1493 MatMultAdd_MPISBAIJ, 1494 MatMultTranspose_MPISBAIJ, 1495 MatMultTransposeAdd_MPISBAIJ, 1496 0, 1497 0, 1498 0, 1499 0, 1500 0, 1501 0, 1502 MatRelax_MPISBAIJ, 1503 MatTranspose_MPISBAIJ, 1504 MatGetInfo_MPISBAIJ, 1505 MatEqual_MPISBAIJ, 1506 MatGetDiagonal_MPISBAIJ, 1507 MatDiagonalScale_MPISBAIJ, 1508 MatNorm_MPISBAIJ, 1509 MatAssemblyBegin_MPISBAIJ, 1510 MatAssemblyEnd_MPISBAIJ, 1511 0, 1512 MatSetOption_MPISBAIJ, 1513 MatZeroEntries_MPISBAIJ, 1514 MatZeroRows_MPISBAIJ, 1515 0, 1516 0, 1517 0, 1518 0, 1519 MatSetUpPreallocation_MPISBAIJ, 1520 0, 1521 0, 1522 0, 1523 0, 1524 MatDuplicate_MPISBAIJ, 1525 0, 1526 0, 1527 0, 1528 0, 1529 0, 1530 MatGetSubMatrices_MPISBAIJ, 1531 MatIncreaseOverlap_MPISBAIJ, 1532 MatGetValues_MPISBAIJ, 1533 0, 1534 MatPrintHelp_MPISBAIJ, 1535 MatScale_MPISBAIJ, 1536 0, 1537 0, 1538 0, 1539 MatGetBlockSize_MPISBAIJ, 1540 0, 1541 0, 1542 0, 1543 0, 1544 0, 1545 0, 1546 MatSetUnfactored_MPISBAIJ, 1547 0, 1548 MatSetValuesBlocked_MPISBAIJ, 1549 0, 1550 0, 1551 0, 1552 MatGetPetscMaps_Petsc, 1553 0, 1554 0, 1555 0, 1556 0, 1557 0, 1558 0, 1559 MatGetRowMax_MPISBAIJ}; 1560 1561 1562 EXTERN_C_BEGIN 1563 #undef __FUNCT__ 1564 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1565 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1566 { 1567 PetscFunctionBegin; 1568 *a = ((Mat_MPISBAIJ *)A->data)->A; 1569 *iscopy = PETSC_FALSE; 1570 PetscFunctionReturn(0); 1571 } 1572 EXTERN_C_END 1573 1574 EXTERN_C_BEGIN 1575 #undef __FUNCT__ 1576 #define __FUNCT__ "MatCreate_MPISBAIJ" 1577 int MatCreate_MPISBAIJ(Mat B) 1578 { 1579 Mat_MPISBAIJ *b; 1580 int ierr; 1581 PetscTruth flg; 1582 1583 PetscFunctionBegin; 1584 1585 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1586 B->data = (void*)b; 1587 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1588 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1589 1590 B->ops->destroy = MatDestroy_MPISBAIJ; 1591 B->ops->view = MatView_MPISBAIJ; 1592 B->mapping = 0; 1593 B->factor = 0; 1594 B->assembled = PETSC_FALSE; 1595 1596 B->insertmode = NOT_SET_VALUES; 1597 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1598 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1599 1600 /* build local table of row and column ownerships */ 1601 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1602 b->cowners = b->rowners + b->size + 2; 1603 b->rowners_bs = b->cowners + b->size + 2; 1604 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1605 1606 /* build cache for off array entries formed */ 1607 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1608 b->donotstash = PETSC_FALSE; 1609 b->colmap = PETSC_NULL; 1610 b->garray = PETSC_NULL; 1611 b->roworiented = PETSC_TRUE; 1612 1613 #if defined(PETSC_USE_MAT_SINGLE) 1614 /* stuff for MatSetValues_XXX in single precision */ 1615 b->setvalueslen = 0; 1616 b->setvaluescopy = PETSC_NULL; 1617 #endif 1618 1619 /* stuff used in block assembly */ 1620 b->barray = 0; 1621 1622 /* stuff used for matrix vector multiply */ 1623 b->lvec = 0; 1624 b->Mvctx = 0; 1625 b->slvec0 = 0; 1626 b->slvec0b = 0; 1627 b->slvec1 = 0; 1628 b->slvec1a = 0; 1629 b->slvec1b = 0; 1630 b->sMvctx = 0; 1631 1632 /* stuff for MatGetRow() */ 1633 b->rowindices = 0; 1634 b->rowvalues = 0; 1635 b->getrowactive = PETSC_FALSE; 1636 1637 /* hash table stuff */ 1638 b->ht = 0; 1639 b->hd = 0; 1640 b->ht_size = 0; 1641 b->ht_flag = PETSC_FALSE; 1642 b->ht_fact = 0; 1643 b->ht_total_ct = 0; 1644 b->ht_insert_ct = 0; 1645 1646 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1647 if (flg) { 1648 PetscReal fact = 1.39; 1649 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1650 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1651 if (fact <= 1.0) fact = 1.39; 1652 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1653 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1654 } 1655 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1656 "MatStoreValues_MPISBAIJ", 1657 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1658 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1659 "MatRetrieveValues_MPISBAIJ", 1660 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1661 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1662 "MatGetDiagonalBlock_MPISBAIJ", 1663 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1664 PetscFunctionReturn(0); 1665 } 1666 EXTERN_C_END 1667 1668 #undef __FUNCT__ 1669 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1670 /*@C 1671 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1672 the user should preallocate the matrix storage by setting the parameters 1673 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1674 performance can be increased by more than a factor of 50. 1675 1676 Collective on Mat 1677 1678 Input Parameters: 1679 + A - the matrix 1680 . bs - size of blockk 1681 . d_nz - number of block nonzeros per block row in diagonal portion of local 1682 submatrix (same for all local rows) 1683 . d_nnz - array containing the number of block nonzeros in the various block rows 1684 in the upper triangular and diagonal part of the in diagonal portion of the local 1685 (possibly different for each block row) or PETSC_NULL. You must leave room 1686 for the diagonal entry even if it is zero. 1687 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1688 submatrix (same for all local rows). 1689 - o_nnz - array containing the number of nonzeros in the various block rows of the 1690 off-diagonal portion of the local submatrix (possibly different for 1691 each block row) or PETSC_NULL. 1692 1693 1694 Options Database Keys: 1695 . -mat_no_unroll - uses code that does not unroll the loops in the 1696 block calculations (much slower) 1697 . -mat_block_size - size of the blocks to use 1698 1699 Notes: 1700 1701 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1702 than it must be used on all processors that share the object for that argument. 1703 1704 Storage Information: 1705 For a square global matrix we define each processor's diagonal portion 1706 to be its local rows and the corresponding columns (a square submatrix); 1707 each processor's off-diagonal portion encompasses the remainder of the 1708 local matrix (a rectangular submatrix). 1709 1710 The user can specify preallocated storage for the diagonal part of 1711 the local submatrix with either d_nz or d_nnz (not both). Set 1712 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1713 memory allocation. Likewise, specify preallocated storage for the 1714 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1715 1716 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1717 the figure below we depict these three local rows and all columns (0-11). 1718 1719 .vb 1720 0 1 2 3 4 5 6 7 8 9 10 11 1721 ------------------- 1722 row 3 | o o o d d d o o o o o o 1723 row 4 | o o o d d d o o o o o o 1724 row 5 | o o o d d d o o o o o o 1725 ------------------- 1726 .ve 1727 1728 Thus, any entries in the d locations are stored in the d (diagonal) 1729 submatrix, and any entries in the o locations are stored in the 1730 o (off-diagonal) submatrix. Note that the d matrix is stored in 1731 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1732 1733 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1734 plus the diagonal part of the d matrix, 1735 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1736 In general, for PDE problems in which most nonzeros are near the diagonal, 1737 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1738 or you will get TERRIBLE performance; see the users' manual chapter on 1739 matrices. 1740 1741 Level: intermediate 1742 1743 .keywords: matrix, block, aij, compressed row, sparse, parallel 1744 1745 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1746 @*/ 1747 1748 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1749 { 1750 Mat_MPISBAIJ *b; 1751 int ierr,i,mbs,Mbs; 1752 PetscTruth flg2; 1753 1754 PetscFunctionBegin; 1755 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1756 if (!flg2) PetscFunctionReturn(0); 1757 1758 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1759 1760 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1761 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1762 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1763 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1764 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1765 if (d_nnz) { 1766 for (i=0; i<B->m/bs; i++) { 1767 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %d value %d",i,d_nnz[i]); 1768 } 1769 } 1770 if (o_nnz) { 1771 for (i=0; i<B->m/bs; i++) { 1772 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %d value %d",i,o_nnz[i]); 1773 } 1774 } 1775 B->preallocated = PETSC_TRUE; 1776 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1777 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1778 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1779 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1780 1781 b = (Mat_MPISBAIJ*)B->data; 1782 mbs = B->m/bs; 1783 Mbs = B->M/bs; 1784 if (mbs*bs != B->m) { 1785 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1786 } 1787 1788 b->bs = bs; 1789 b->bs2 = bs*bs; 1790 b->mbs = mbs; 1791 b->nbs = mbs; 1792 b->Mbs = Mbs; 1793 b->Nbs = Mbs; 1794 1795 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1796 b->rowners[0] = 0; 1797 for (i=2; i<=b->size; i++) { 1798 b->rowners[i] += b->rowners[i-1]; 1799 } 1800 b->rstart = b->rowners[b->rank]; 1801 b->rend = b->rowners[b->rank+1]; 1802 b->cstart = b->rstart; 1803 b->cend = b->rend; 1804 for (i=0; i<=b->size; i++) { 1805 b->rowners_bs[i] = b->rowners[i]*bs; 1806 } 1807 b->rstart_bs = b-> rstart*bs; 1808 b->rend_bs = b->rend*bs; 1809 1810 b->cstart_bs = b->cstart*bs; 1811 b->cend_bs = b->cend*bs; 1812 1813 1814 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1815 PetscLogObjectParent(B,b->A); 1816 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1817 PetscLogObjectParent(B,b->B); 1818 1819 /* build cache for off array entries formed */ 1820 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1821 1822 PetscFunctionReturn(0); 1823 } 1824 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatCreateMPISBAIJ" 1827 /*@C 1828 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1829 (block compressed row). For good matrix assembly performance 1830 the user should preallocate the matrix storage by setting the parameters 1831 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1832 performance can be increased by more than a factor of 50. 1833 1834 Collective on MPI_Comm 1835 1836 Input Parameters: 1837 + comm - MPI communicator 1838 . bs - size of blockk 1839 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1840 This value should be the same as the local size used in creating the 1841 y vector for the matrix-vector product y = Ax. 1842 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1843 This value should be the same as the local size used in creating the 1844 x vector for the matrix-vector product y = Ax. 1845 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1846 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1847 . d_nz - number of block nonzeros per block row in diagonal portion of local 1848 submatrix (same for all local rows) 1849 . d_nnz - array containing the number of block nonzeros in the various block rows 1850 in the upper triangular portion of the in diagonal portion of the local 1851 (possibly different for each block block row) or PETSC_NULL. 1852 You must leave room for the diagonal entry even if it is zero. 1853 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1854 submatrix (same for all local rows). 1855 - o_nnz - array containing the number of nonzeros in the various block rows of the 1856 off-diagonal portion of the local submatrix (possibly different for 1857 each block row) or PETSC_NULL. 1858 1859 Output Parameter: 1860 . A - the matrix 1861 1862 Options Database Keys: 1863 . -mat_no_unroll - uses code that does not unroll the loops in the 1864 block calculations (much slower) 1865 . -mat_block_size - size of the blocks to use 1866 . -mat_mpi - use the parallel matrix data structures even on one processor 1867 (defaults to using SeqBAIJ format on one processor) 1868 1869 Notes: 1870 The user MUST specify either the local or global matrix dimensions 1871 (possibly both). 1872 1873 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1874 than it must be used on all processors that share the object for that argument. 1875 1876 Storage Information: 1877 For a square global matrix we define each processor's diagonal portion 1878 to be its local rows and the corresponding columns (a square submatrix); 1879 each processor's off-diagonal portion encompasses the remainder of the 1880 local matrix (a rectangular submatrix). 1881 1882 The user can specify preallocated storage for the diagonal part of 1883 the local submatrix with either d_nz or d_nnz (not both). Set 1884 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1885 memory allocation. Likewise, specify preallocated storage for the 1886 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1887 1888 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1889 the figure below we depict these three local rows and all columns (0-11). 1890 1891 .vb 1892 0 1 2 3 4 5 6 7 8 9 10 11 1893 ------------------- 1894 row 3 | o o o d d d o o o o o o 1895 row 4 | o o o d d d o o o o o o 1896 row 5 | o o o d d d o o o o o o 1897 ------------------- 1898 .ve 1899 1900 Thus, any entries in the d locations are stored in the d (diagonal) 1901 submatrix, and any entries in the o locations are stored in the 1902 o (off-diagonal) submatrix. Note that the d matrix is stored in 1903 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1904 1905 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1906 plus the diagonal part of the d matrix, 1907 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1908 In general, for PDE problems in which most nonzeros are near the diagonal, 1909 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1910 or you will get TERRIBLE performance; see the users' manual chapter on 1911 matrices. 1912 1913 Level: intermediate 1914 1915 .keywords: matrix, block, aij, compressed row, sparse, parallel 1916 1917 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1918 @*/ 1919 1920 int MatCreateMPISBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N,int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 1921 { 1922 int ierr,size; 1923 1924 PetscFunctionBegin; 1925 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1926 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1927 if (size > 1) { 1928 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1929 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1930 } else { 1931 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1932 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1933 } 1934 PetscFunctionReturn(0); 1935 } 1936 1937 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1940 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1941 { 1942 Mat mat; 1943 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1944 int ierr,len=0; 1945 1946 PetscFunctionBegin; 1947 *newmat = 0; 1948 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1949 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1950 mat->preallocated = PETSC_TRUE; 1951 a = (Mat_MPISBAIJ*)mat->data; 1952 a->bs = oldmat->bs; 1953 a->bs2 = oldmat->bs2; 1954 a->mbs = oldmat->mbs; 1955 a->nbs = oldmat->nbs; 1956 a->Mbs = oldmat->Mbs; 1957 a->Nbs = oldmat->Nbs; 1958 1959 a->rstart = oldmat->rstart; 1960 a->rend = oldmat->rend; 1961 a->cstart = oldmat->cstart; 1962 a->cend = oldmat->cend; 1963 a->size = oldmat->size; 1964 a->rank = oldmat->rank; 1965 a->donotstash = oldmat->donotstash; 1966 a->roworiented = oldmat->roworiented; 1967 a->rowindices = 0; 1968 a->rowvalues = 0; 1969 a->getrowactive = PETSC_FALSE; 1970 a->barray = 0; 1971 a->rstart_bs = oldmat->rstart_bs; 1972 a->rend_bs = oldmat->rend_bs; 1973 a->cstart_bs = oldmat->cstart_bs; 1974 a->cend_bs = oldmat->cend_bs; 1975 1976 /* hash table stuff */ 1977 a->ht = 0; 1978 a->hd = 0; 1979 a->ht_size = 0; 1980 a->ht_flag = oldmat->ht_flag; 1981 a->ht_fact = oldmat->ht_fact; 1982 a->ht_total_ct = 0; 1983 a->ht_insert_ct = 0; 1984 1985 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 1986 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1987 a->cowners = a->rowners + a->size + 2; 1988 a->rowners_bs = a->cowners + a->size + 2; 1989 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1990 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1991 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1992 if (oldmat->colmap) { 1993 #if defined (PETSC_USE_CTABLE) 1994 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1995 #else 1996 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1997 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1998 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1999 #endif 2000 } else a->colmap = 0; 2001 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2002 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2003 PetscLogObjectMemory(mat,len*sizeof(int)); 2004 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2005 } else a->garray = 0; 2006 2007 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2008 PetscLogObjectParent(mat,a->lvec); 2009 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2010 2011 PetscLogObjectParent(mat,a->Mvctx); 2012 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2013 PetscLogObjectParent(mat,a->A); 2014 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2015 PetscLogObjectParent(mat,a->B); 2016 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2017 *newmat = mat; 2018 PetscFunctionReturn(0); 2019 } 2020 2021 #include "petscsys.h" 2022 2023 EXTERN_C_BEGIN 2024 #undef __FUNCT__ 2025 #define __FUNCT__ "MatLoad_MPISBAIJ" 2026 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 2027 { 2028 Mat A; 2029 int i,nz,ierr,j,rstart,rend,fd; 2030 PetscScalar *vals,*buf; 2031 MPI_Comm comm = ((PetscObject)viewer)->comm; 2032 MPI_Status status; 2033 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2034 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2035 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2036 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2037 int dcount,kmax,k,nzcount,tmp; 2038 2039 PetscFunctionBegin; 2040 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2041 2042 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2043 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2044 if (!rank) { 2045 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2046 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2047 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2048 if (header[3] < 0) { 2049 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2050 } 2051 } 2052 2053 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2054 M = header[1]; N = header[2]; 2055 2056 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2057 2058 /* 2059 This code adds extra rows to make sure the number of rows is 2060 divisible by the blocksize 2061 */ 2062 Mbs = M/bs; 2063 extra_rows = bs - M + bs*(Mbs); 2064 if (extra_rows == bs) extra_rows = 0; 2065 else Mbs++; 2066 if (extra_rows &&!rank) { 2067 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2068 } 2069 2070 /* determine ownership of all rows */ 2071 mbs = Mbs/size + ((Mbs % size) > rank); 2072 m = mbs*bs; 2073 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2074 browners = rowners + size + 1; 2075 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2076 rowners[0] = 0; 2077 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2078 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2079 rstart = rowners[rank]; 2080 rend = rowners[rank+1]; 2081 2082 /* distribute row lengths to all processors */ 2083 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2084 if (!rank) { 2085 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2086 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2087 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2088 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2089 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2090 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2091 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2092 } else { 2093 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2094 } 2095 2096 if (!rank) { /* procs[0] */ 2097 /* calculate the number of nonzeros on each processor */ 2098 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2099 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2100 for (i=0; i<size; i++) { 2101 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2102 procsnz[i] += rowlengths[j]; 2103 } 2104 } 2105 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2106 2107 /* determine max buffer needed and allocate it */ 2108 maxnz = 0; 2109 for (i=0; i<size; i++) { 2110 maxnz = PetscMax(maxnz,procsnz[i]); 2111 } 2112 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2113 2114 /* read in my part of the matrix column indices */ 2115 nz = procsnz[0]; 2116 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2117 mycols = ibuf; 2118 if (size == 1) nz -= extra_rows; 2119 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2120 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2121 2122 /* read in every ones (except the last) and ship off */ 2123 for (i=1; i<size-1; i++) { 2124 nz = procsnz[i]; 2125 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2126 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2127 } 2128 /* read in the stuff for the last proc */ 2129 if (size != 1) { 2130 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2131 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2132 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2133 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2134 } 2135 ierr = PetscFree(cols);CHKERRQ(ierr); 2136 } else { /* procs[i], i>0 */ 2137 /* determine buffer space needed for message */ 2138 nz = 0; 2139 for (i=0; i<m; i++) { 2140 nz += locrowlens[i]; 2141 } 2142 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2143 mycols = ibuf; 2144 /* receive message of column indices*/ 2145 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2146 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2147 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2148 } 2149 2150 /* loop over local rows, determining number of off diagonal entries */ 2151 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2152 odlens = dlens + (rend-rstart); 2153 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2154 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2155 masked1 = mask + Mbs; 2156 masked2 = masked1 + Mbs; 2157 rowcount = 0; nzcount = 0; 2158 for (i=0; i<mbs; i++) { 2159 dcount = 0; 2160 odcount = 0; 2161 for (j=0; j<bs; j++) { 2162 kmax = locrowlens[rowcount]; 2163 for (k=0; k<kmax; k++) { 2164 tmp = mycols[nzcount++]/bs; /* block col. index */ 2165 if (!mask[tmp]) { 2166 mask[tmp] = 1; 2167 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2168 else masked1[dcount++] = tmp; /* entry in diag portion */ 2169 } 2170 } 2171 rowcount++; 2172 } 2173 2174 dlens[i] = dcount; /* d_nzz[i] */ 2175 odlens[i] = odcount; /* o_nzz[i] */ 2176 2177 /* zero out the mask elements we set */ 2178 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2179 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2180 } 2181 2182 /* create our matrix */ 2183 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2184 CHKERRQ(ierr); 2185 A = *newmat; 2186 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2187 2188 if (!rank) { 2189 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2190 /* read in my part of the matrix numerical values */ 2191 nz = procsnz[0]; 2192 vals = buf; 2193 mycols = ibuf; 2194 if (size == 1) nz -= extra_rows; 2195 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2196 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2197 2198 /* insert into matrix */ 2199 jj = rstart*bs; 2200 for (i=0; i<m; i++) { 2201 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2202 mycols += locrowlens[i]; 2203 vals += locrowlens[i]; 2204 jj++; 2205 } 2206 2207 /* read in other processors (except the last one) and ship out */ 2208 for (i=1; i<size-1; i++) { 2209 nz = procsnz[i]; 2210 vals = buf; 2211 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2212 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2213 } 2214 /* the last proc */ 2215 if (size != 1){ 2216 nz = procsnz[i] - extra_rows; 2217 vals = buf; 2218 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2219 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2220 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2221 } 2222 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2223 2224 } else { 2225 /* receive numeric values */ 2226 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2227 2228 /* receive message of values*/ 2229 vals = buf; 2230 mycols = ibuf; 2231 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2232 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2233 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2234 2235 /* insert into matrix */ 2236 jj = rstart*bs; 2237 for (i=0; i<m; i++) { 2238 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2239 mycols += locrowlens[i]; 2240 vals += locrowlens[i]; 2241 jj++; 2242 } 2243 } 2244 2245 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2246 ierr = PetscFree(buf);CHKERRQ(ierr); 2247 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2248 ierr = PetscFree(rowners);CHKERRQ(ierr); 2249 ierr = PetscFree(dlens);CHKERRQ(ierr); 2250 ierr = PetscFree(mask);CHKERRQ(ierr); 2251 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2252 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2253 PetscFunctionReturn(0); 2254 } 2255 EXTERN_C_END 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2259 /*@ 2260 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2261 2262 Input Parameters: 2263 . mat - the matrix 2264 . fact - factor 2265 2266 Collective on Mat 2267 2268 Level: advanced 2269 2270 Notes: 2271 This can also be set by the command line option: -mat_use_hash_table fact 2272 2273 .keywords: matrix, hashtable, factor, HT 2274 2275 .seealso: MatSetOption() 2276 @*/ 2277 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2278 { 2279 PetscFunctionBegin; 2280 SETERRQ(1,"Function not yet written for SBAIJ format"); 2281 /* PetscFunctionReturn(0); */ 2282 } 2283 2284 #undef __FUNCT__ 2285 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2286 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2287 { 2288 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2289 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2290 PetscReal atmp; 2291 PetscReal *work,*svalues,*rvalues; 2292 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2293 int rank,size,*rowners_bs,dest,count,source; 2294 PetscScalar *va; 2295 MatScalar *ba; 2296 MPI_Status stat; 2297 2298 PetscFunctionBegin; 2299 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2300 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2301 2302 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr); 2303 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2304 2305 bs = a->bs; 2306 mbs = a->mbs; 2307 Mbs = a->Mbs; 2308 ba = b->a; 2309 bi = b->i; 2310 bj = b->j; 2311 /* 2312 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2313 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2314 */ 2315 2316 /* find ownerships */ 2317 rowners_bs = a->rowners_bs; 2318 /* 2319 if (!rank){ 2320 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2321 } 2322 */ 2323 2324 /* each proc creates an array to be distributed */ 2325 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2326 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2327 2328 /* row_max for B */ 2329 if (rank != size-1){ 2330 for (i=0; i<mbs; i++) { 2331 ncols = bi[1] - bi[0]; bi++; 2332 brow = bs*i; 2333 for (j=0; j<ncols; j++){ 2334 bcol = bs*(*bj); 2335 for (kcol=0; kcol<bs; kcol++){ 2336 col = bcol + kcol; /* local col index */ 2337 col += rowners_bs[rank+1]; /* global col index */ 2338 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2339 for (krow=0; krow<bs; krow++){ 2340 atmp = PetscAbsScalar(*ba); ba++; 2341 row = brow + krow; /* local row index */ 2342 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2343 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2344 if (work[col] < atmp) work[col] = atmp; 2345 } 2346 } 2347 bj++; 2348 } 2349 } 2350 /* 2351 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2352 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2353 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2354 */ 2355 2356 /* send values to its owners */ 2357 for (dest=rank+1; dest<size; dest++){ 2358 svalues = work + rowners_bs[dest]; 2359 count = rowners_bs[dest+1]-rowners_bs[dest]; 2360 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2361 /* 2362 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] sends %d values to [%d]: %g, %g, %g, %g\n",rank,count,dest,svalues[0],svalues[1],svalues[2],svalues[3]); 2363 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2364 */ 2365 } 2366 } 2367 2368 /* receive values */ 2369 if (rank){ 2370 rvalues = work; 2371 count = rowners_bs[rank+1]-rowners_bs[rank]; 2372 for (source=0; source<rank; source++){ 2373 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2374 /* process values */ 2375 for (i=0; i<count; i++){ 2376 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2377 } 2378 /* 2379 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] received %d values from [%d]: %g, %g, %g, %g \n",rank,count,stat.MPI_SOURCE,rvalues[0],rvalues[1],rvalues[2],rvalues[3]); 2380 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2381 */ 2382 } 2383 } 2384 2385 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2386 ierr = PetscFree(work);CHKERRQ(ierr); 2387 PetscFunctionReturn(0); 2388 } 2389 2390 #undef __FUNCT__ 2391 #define __FUNCT__ "MatRelax_MPISBAIJ" 2392 int MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2393 { 2394 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2395 int ierr,mbs=mat->mbs,bs=mat->bs; 2396 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2397 Vec bb1; 2398 2399 PetscFunctionBegin; 2400 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2401 if (bs > 1) 2402 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2403 2404 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2405 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2406 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2407 its--; 2408 } 2409 2410 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2411 while (its--){ 2412 2413 /* lower triangular part: slvec0b = - B^T*xx */ 2414 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2415 2416 /* copy xx into slvec0a */ 2417 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2418 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2419 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2420 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2421 2422 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2423 2424 /* copy bb into slvec1a */ 2425 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2426 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2427 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2428 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2429 2430 /* set slvec1b = 0 */ 2431 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2432 2433 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2434 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2435 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2436 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2437 2438 /* upper triangular part: bb1 = bb1 - B*x */ 2439 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2440 2441 /* local diagonal sweep */ 2442 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2443 } 2444 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2445 } else { 2446 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2447 } 2448 PetscFunctionReturn(0); 2449 } 2450 2451 #undef __FUNCT__ 2452 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2453 int MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2454 { 2455 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2456 int ierr; 2457 PetscScalar mone=-1.0; 2458 Vec lvec1,bb1; 2459 2460 PetscFunctionBegin; 2461 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2462 if (mat->bs > 1) 2463 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2464 2465 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2466 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2467 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2468 its--; 2469 } 2470 2471 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2472 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2473 while (its--){ 2474 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2475 2476 /* lower diagonal part: bb1 = bb - B^T*xx */ 2477 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2478 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2479 2480 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2481 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2482 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2483 2484 /* upper diagonal part: bb1 = bb1 - B*x */ 2485 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2486 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2487 2488 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2489 2490 /* diagonal sweep */ 2491 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2492 } 2493 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2494 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2495 } else { 2496 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2497 } 2498 PetscFunctionReturn(0); 2499 } 2500 2501