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