1 /*$Id: mpisbaij.c,v 1.58 2001/08/06 21:15:59 bsmith Exp balay $*/ 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(double),&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,MPI_DOUBLE,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",((double)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__ "MatGetOwnershipRange_MPISBAIJ" 961 int MatGetOwnershipRange_MPISBAIJ(Mat matin,int *m,int *n) 962 { 963 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 964 965 PetscFunctionBegin; 966 if (m) *m = mat->rstart*mat->bs; 967 if (n) *n = mat->rend*mat->bs; 968 PetscFunctionReturn(0); 969 } 970 971 #undef __FUNCT__ 972 #define __FUNCT__ "MatGetRow_MPISBAIJ" 973 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 974 { 975 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 976 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 977 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 978 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 979 int *cmap,*idx_p,cstart = mat->cstart; 980 981 PetscFunctionBegin; 982 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 983 mat->getrowactive = PETSC_TRUE; 984 985 if (!mat->rowvalues && (idx || v)) { 986 /* 987 allocate enough space to hold information from the longest row. 988 */ 989 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 990 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 991 int max = 1,mbs = mat->mbs,tmp; 992 for (i=0; i<mbs; i++) { 993 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 994 if (max < tmp) { max = tmp; } 995 } 996 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 997 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 998 } 999 1000 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1001 lrow = row - brstart; /* local row index */ 1002 1003 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1004 if (!v) {pvA = 0; pvB = 0;} 1005 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1006 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1007 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1008 nztot = nzA + nzB; 1009 1010 cmap = mat->garray; 1011 if (v || idx) { 1012 if (nztot) { 1013 /* Sort by increasing column numbers, assuming A and B already sorted */ 1014 int imark = -1; 1015 if (v) { 1016 *v = v_p = mat->rowvalues; 1017 for (i=0; i<nzB; i++) { 1018 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1019 else break; 1020 } 1021 imark = i; 1022 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1023 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1024 } 1025 if (idx) { 1026 *idx = idx_p = mat->rowindices; 1027 if (imark > -1) { 1028 for (i=0; i<imark; i++) { 1029 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1030 } 1031 } else { 1032 for (i=0; i<nzB; i++) { 1033 if (cmap[cworkB[i]/bs] < cstart) 1034 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1035 else break; 1036 } 1037 imark = i; 1038 } 1039 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1040 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1041 } 1042 } else { 1043 if (idx) *idx = 0; 1044 if (v) *v = 0; 1045 } 1046 } 1047 *nz = nztot; 1048 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1049 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1050 PetscFunctionReturn(0); 1051 } 1052 1053 #undef __FUNCT__ 1054 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1055 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1056 { 1057 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1058 1059 PetscFunctionBegin; 1060 if (baij->getrowactive == PETSC_FALSE) { 1061 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1062 } 1063 baij->getrowactive = PETSC_FALSE; 1064 PetscFunctionReturn(0); 1065 } 1066 1067 #undef __FUNCT__ 1068 #define __FUNCT__ "MatGetBlockSize_MPISBAIJ" 1069 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1070 { 1071 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1072 1073 PetscFunctionBegin; 1074 *bs = baij->bs; 1075 PetscFunctionReturn(0); 1076 } 1077 1078 #undef __FUNCT__ 1079 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1080 int MatZeroEntries_MPISBAIJ(Mat A) 1081 { 1082 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1083 int ierr; 1084 1085 PetscFunctionBegin; 1086 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1087 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1088 PetscFunctionReturn(0); 1089 } 1090 1091 #undef __FUNCT__ 1092 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1093 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1094 { 1095 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1096 Mat A = a->A,B = a->B; 1097 int ierr; 1098 PetscReal isend[5],irecv[5]; 1099 1100 PetscFunctionBegin; 1101 info->block_size = (double)a->bs; 1102 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1103 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1104 isend[3] = info->memory; isend[4] = info->mallocs; 1105 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1106 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1107 isend[3] += info->memory; isend[4] += info->mallocs; 1108 if (flag == MAT_LOCAL) { 1109 info->nz_used = isend[0]; 1110 info->nz_allocated = isend[1]; 1111 info->nz_unneeded = isend[2]; 1112 info->memory = isend[3]; 1113 info->mallocs = isend[4]; 1114 } else if (flag == MAT_GLOBAL_MAX) { 1115 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1116 info->nz_used = irecv[0]; 1117 info->nz_allocated = irecv[1]; 1118 info->nz_unneeded = irecv[2]; 1119 info->memory = irecv[3]; 1120 info->mallocs = irecv[4]; 1121 } else if (flag == MAT_GLOBAL_SUM) { 1122 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1123 info->nz_used = irecv[0]; 1124 info->nz_allocated = irecv[1]; 1125 info->nz_unneeded = irecv[2]; 1126 info->memory = irecv[3]; 1127 info->mallocs = irecv[4]; 1128 } else { 1129 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1130 } 1131 info->rows_global = (double)A->M; 1132 info->columns_global = (double)A->N; 1133 info->rows_local = (double)A->m; 1134 info->columns_local = (double)A->N; 1135 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1136 info->fill_ratio_needed = 0; 1137 info->factor_mallocs = 0; 1138 PetscFunctionReturn(0); 1139 } 1140 1141 #undef __FUNCT__ 1142 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1143 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1144 { 1145 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1146 int ierr; 1147 1148 PetscFunctionBegin; 1149 switch (op) { 1150 case MAT_NO_NEW_NONZERO_LOCATIONS: 1151 case MAT_YES_NEW_NONZERO_LOCATIONS: 1152 case MAT_COLUMNS_UNSORTED: 1153 case MAT_COLUMNS_SORTED: 1154 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1155 case MAT_KEEP_ZEROED_ROWS: 1156 case MAT_NEW_NONZERO_LOCATION_ERR: 1157 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1158 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1159 break; 1160 case MAT_ROW_ORIENTED: 1161 a->roworiented = PETSC_TRUE; 1162 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1163 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1164 break; 1165 case MAT_ROWS_SORTED: 1166 case MAT_ROWS_UNSORTED: 1167 case MAT_YES_NEW_DIAGONALS: 1168 case MAT_USE_SINGLE_PRECISION_SOLVES: 1169 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1170 break; 1171 case MAT_COLUMN_ORIENTED: 1172 a->roworiented = PETSC_FALSE; 1173 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1174 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1175 break; 1176 case MAT_IGNORE_OFF_PROC_ENTRIES: 1177 a->donotstash = PETSC_TRUE; 1178 break; 1179 case MAT_NO_NEW_DIAGONALS: 1180 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1181 break; 1182 case MAT_USE_HASH_TABLE: 1183 a->ht_flag = PETSC_TRUE; 1184 break; 1185 default: 1186 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1187 break; 1188 } 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatTranspose_MPISBAIJ(" 1194 int MatTranspose_MPISBAIJ(Mat A,Mat *matout) 1195 { 1196 PetscFunctionBegin; 1197 SETERRQ(1,"Matrix is symmetric. MatTranspose() should not be called"); 1198 /* PetscFunctionReturn(0); */ 1199 } 1200 1201 #undef __FUNCT__ 1202 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1203 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1204 { 1205 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1206 Mat a = baij->A,b = baij->B; 1207 int ierr,s1,s2,s3; 1208 1209 PetscFunctionBegin; 1210 if (ll != rr) { 1211 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1212 } 1213 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1214 if (rr) { 1215 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1216 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1217 /* Overlap communication with computation. */ 1218 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1219 /*} if (ll) { */ 1220 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1221 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1222 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1223 /* } */ 1224 /* scale the diagonal block */ 1225 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1226 1227 /* if (rr) { */ 1228 /* Do a scatter end and then right scale the off-diagonal block */ 1229 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1230 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1231 } 1232 1233 PetscFunctionReturn(0); 1234 } 1235 1236 #undef __FUNCT__ 1237 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1238 int MatZeroRows_MPISBAIJ(Mat A,IS is,PetscScalar *diag) 1239 { 1240 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1241 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 1242 int *procs,*nprocs,j,idx,nsends,*work,row; 1243 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1244 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1245 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1246 MPI_Comm comm = A->comm; 1247 MPI_Request *send_waits,*recv_waits; 1248 MPI_Status recv_status,*send_status; 1249 IS istmp; 1250 PetscTruth found; 1251 1252 PetscFunctionBegin; 1253 ierr = ISGetSize(is,&N);CHKERRQ(ierr); 1254 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1255 1256 /* first count number of contributors to each processor */ 1257 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 1258 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 1259 procs = nprocs + size; 1260 ierr = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/ 1261 for (i=0; i<N; i++) { 1262 idx = rows[i]; 1263 found = PETSC_FALSE; 1264 for (j=0; j<size; j++) { 1265 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1266 nprocs[j]++; procs[j] = 1; owner[i] = j; found = PETSC_TRUE; break; 1267 } 1268 } 1269 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1270 } 1271 nsends = 0; for (i=0; i<size; i++) { nsends += procs[i];} 1272 1273 /* inform other processors of number of messages and max length*/ 1274 ierr = PetscMalloc(2*size*sizeof(int),&work);CHKERRQ(ierr); 1275 ierr = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr); 1276 nmax = work[rank]; 1277 nrecvs = work[size+rank]; 1278 ierr = PetscFree(work);CHKERRQ(ierr); 1279 1280 /* post receives: */ 1281 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 1282 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1283 for (i=0; i<nrecvs; i++) { 1284 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1285 } 1286 1287 /* do sends: 1288 1) starts[i] gives the starting index in svalues for stuff going to 1289 the ith processor 1290 */ 1291 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 1292 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1293 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 1294 starts[0] = 0; 1295 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1296 for (i=0; i<N; i++) { 1297 svalues[starts[owner[i]]++] = rows[i]; 1298 } 1299 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1300 1301 starts[0] = 0; 1302 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1303 count = 0; 1304 for (i=0; i<size; i++) { 1305 if (procs[i]) { 1306 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1307 } 1308 } 1309 ierr = PetscFree(starts);CHKERRQ(ierr); 1310 1311 base = owners[rank]*bs; 1312 1313 /* wait on receives */ 1314 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 1315 source = lens + nrecvs; 1316 count = nrecvs; slen = 0; 1317 while (count) { 1318 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1319 /* unpack receives into our local space */ 1320 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1321 source[imdex] = recv_status.MPI_SOURCE; 1322 lens[imdex] = n; 1323 slen += n; 1324 count--; 1325 } 1326 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1327 1328 /* move the data into the send scatter */ 1329 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 1330 count = 0; 1331 for (i=0; i<nrecvs; i++) { 1332 values = rvalues + i*nmax; 1333 for (j=0; j<lens[i]; j++) { 1334 lrows[count++] = values[j] - base; 1335 } 1336 } 1337 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1338 ierr = PetscFree(lens);CHKERRQ(ierr); 1339 ierr = PetscFree(owner);CHKERRQ(ierr); 1340 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1341 1342 /* actually zap the local rows */ 1343 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1344 PetscLogObjectParent(A,istmp); 1345 1346 /* 1347 Zero the required rows. If the "diagonal block" of the matrix 1348 is square and the user wishes to set the diagonal we use seperate 1349 code so that MatSetValues() is not called for each diagonal allocating 1350 new memory, thus calling lots of mallocs and slowing things down. 1351 1352 Contributed by: Mathew Knepley 1353 */ 1354 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1355 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1356 if (diag && (l->A->M == l->A->N)) { 1357 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1358 } else if (diag) { 1359 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1360 if (((Mat_SeqSBAIJ*)l->A->data)->nonew) { 1361 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1362 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1363 } 1364 for (i=0; i<slen; i++) { 1365 row = lrows[i] + rstart_bs; 1366 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1367 } 1368 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1369 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1370 } else { 1371 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1372 } 1373 1374 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1375 ierr = PetscFree(lrows);CHKERRQ(ierr); 1376 1377 /* wait on sends */ 1378 if (nsends) { 1379 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1380 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1381 ierr = PetscFree(send_status);CHKERRQ(ierr); 1382 } 1383 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1384 ierr = PetscFree(svalues);CHKERRQ(ierr); 1385 1386 PetscFunctionReturn(0); 1387 } 1388 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1391 int MatPrintHelp_MPISBAIJ(Mat A) 1392 { 1393 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1394 MPI_Comm comm = A->comm; 1395 static int called = 0; 1396 int ierr; 1397 1398 PetscFunctionBegin; 1399 if (!a->rank) { 1400 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1401 } 1402 if (called) {PetscFunctionReturn(0);} else called = 1; 1403 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1404 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1405 PetscFunctionReturn(0); 1406 } 1407 1408 #undef __FUNCT__ 1409 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1410 int MatSetUnfactored_MPISBAIJ(Mat A) 1411 { 1412 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1413 int ierr; 1414 1415 PetscFunctionBegin; 1416 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1417 PetscFunctionReturn(0); 1418 } 1419 1420 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1421 1422 #undef __FUNCT__ 1423 #define __FUNCT__ "MatEqual_MPISBAIJ" 1424 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1425 { 1426 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1427 Mat a,b,c,d; 1428 PetscTruth flg; 1429 int ierr; 1430 1431 PetscFunctionBegin; 1432 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg);CHKERRQ(ierr); 1433 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1434 a = matA->A; b = matA->B; 1435 c = matB->A; d = matB->B; 1436 1437 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1438 if (flg == PETSC_TRUE) { 1439 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1440 } 1441 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1442 PetscFunctionReturn(0); 1443 } 1444 1445 #undef __FUNCT__ 1446 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1447 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1448 { 1449 int ierr; 1450 1451 PetscFunctionBegin; 1452 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1453 PetscFunctionReturn(0); 1454 } 1455 /* -------------------------------------------------------------------*/ 1456 static struct _MatOps MatOps_Values = { 1457 MatSetValues_MPISBAIJ, 1458 MatGetRow_MPISBAIJ, 1459 MatRestoreRow_MPISBAIJ, 1460 MatMult_MPISBAIJ, 1461 MatMultAdd_MPISBAIJ, 1462 MatMultTranspose_MPISBAIJ, 1463 MatMultTransposeAdd_MPISBAIJ, 1464 0, 1465 0, 1466 0, 1467 0, 1468 0, 1469 0, 1470 0, 1471 MatTranspose_MPISBAIJ, 1472 MatGetInfo_MPISBAIJ, 1473 MatEqual_MPISBAIJ, 1474 MatGetDiagonal_MPISBAIJ, 1475 MatDiagonalScale_MPISBAIJ, 1476 MatNorm_MPISBAIJ, 1477 MatAssemblyBegin_MPISBAIJ, 1478 MatAssemblyEnd_MPISBAIJ, 1479 0, 1480 MatSetOption_MPISBAIJ, 1481 MatZeroEntries_MPISBAIJ, 1482 MatZeroRows_MPISBAIJ, 1483 0, 1484 0, 1485 0, 1486 0, 1487 MatSetUpPreallocation_MPISBAIJ, 1488 0, 1489 MatGetOwnershipRange_MPISBAIJ, 1490 0, 1491 0, 1492 0, 1493 0, 1494 MatDuplicate_MPISBAIJ, 1495 0, 1496 0, 1497 0, 1498 0, 1499 0, 1500 MatGetSubMatrices_MPISBAIJ, 1501 MatIncreaseOverlap_MPISBAIJ, 1502 MatGetValues_MPISBAIJ, 1503 0, 1504 MatPrintHelp_MPISBAIJ, 1505 MatScale_MPISBAIJ, 1506 0, 1507 0, 1508 0, 1509 MatGetBlockSize_MPISBAIJ, 1510 0, 1511 0, 1512 0, 1513 0, 1514 0, 1515 0, 1516 MatSetUnfactored_MPISBAIJ, 1517 0, 1518 MatSetValuesBlocked_MPISBAIJ, 1519 0, 1520 0, 1521 0, 1522 MatGetPetscMaps_Petsc, 1523 0, 1524 0, 1525 0, 1526 0, 1527 0, 1528 0, 1529 MatGetRowMax_MPISBAIJ}; 1530 1531 1532 EXTERN_C_BEGIN 1533 #undef __FUNCT__ 1534 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1535 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1536 { 1537 PetscFunctionBegin; 1538 *a = ((Mat_MPISBAIJ *)A->data)->A; 1539 *iscopy = PETSC_FALSE; 1540 PetscFunctionReturn(0); 1541 } 1542 EXTERN_C_END 1543 1544 EXTERN_C_BEGIN 1545 #undef __FUNCT__ 1546 #define __FUNCT__ "MatCreate_MPISBAIJ" 1547 int MatCreate_MPISBAIJ(Mat B) 1548 { 1549 Mat_MPISBAIJ *b; 1550 int ierr; 1551 PetscTruth flg; 1552 1553 PetscFunctionBegin; 1554 1555 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1556 B->data = (void*)b; 1557 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1558 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1559 1560 B->ops->destroy = MatDestroy_MPISBAIJ; 1561 B->ops->view = MatView_MPISBAIJ; 1562 B->mapping = 0; 1563 B->factor = 0; 1564 B->assembled = PETSC_FALSE; 1565 1566 B->insertmode = NOT_SET_VALUES; 1567 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1568 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1569 1570 /* build local table of row and column ownerships */ 1571 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1572 b->cowners = b->rowners + b->size + 2; 1573 b->rowners_bs = b->cowners + b->size + 2; 1574 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1575 1576 /* build cache for off array entries formed */ 1577 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1578 b->donotstash = PETSC_FALSE; 1579 b->colmap = PETSC_NULL; 1580 b->garray = PETSC_NULL; 1581 b->roworiented = PETSC_TRUE; 1582 1583 #if defined(PETSC_USE_MAT_SINGLE) 1584 /* stuff for MatSetValues_XXX in single precision */ 1585 b->setvalueslen = 0; 1586 b->setvaluescopy = PETSC_NULL; 1587 #endif 1588 1589 /* stuff used in block assembly */ 1590 b->barray = 0; 1591 1592 /* stuff used for matrix vector multiply */ 1593 b->lvec = 0; 1594 b->Mvctx = 0; 1595 1596 /* stuff for MatGetRow() */ 1597 b->rowindices = 0; 1598 b->rowvalues = 0; 1599 b->getrowactive = PETSC_FALSE; 1600 1601 /* hash table stuff */ 1602 b->ht = 0; 1603 b->hd = 0; 1604 b->ht_size = 0; 1605 b->ht_flag = PETSC_FALSE; 1606 b->ht_fact = 0; 1607 b->ht_total_ct = 0; 1608 b->ht_insert_ct = 0; 1609 1610 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1611 if (flg) { 1612 double fact = 1.39; 1613 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1614 ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1615 if (fact <= 1.0) fact = 1.39; 1616 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1617 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1618 } 1619 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1620 "MatStoreValues_MPISBAIJ", 1621 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1622 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1623 "MatRetrieveValues_MPISBAIJ", 1624 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1625 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1626 "MatGetDiagonalBlock_MPISBAIJ", 1627 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1628 PetscFunctionReturn(0); 1629 } 1630 EXTERN_C_END 1631 1632 #undef __FUNCT__ 1633 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1634 /*@C 1635 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1636 the user should preallocate the matrix storage by setting the parameters 1637 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1638 performance can be increased by more than a factor of 50. 1639 1640 Collective on Mat 1641 1642 Input Parameters: 1643 + A - the matrix 1644 . bs - size of blockk 1645 . d_nz - number of block nonzeros per block row in diagonal portion of local 1646 submatrix (same for all local rows) 1647 . d_nnz - array containing the number of block nonzeros in the various block rows 1648 of the in diagonal portion of the local (possibly different for each block 1649 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1650 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1651 submatrix (same for all local rows). 1652 - o_nnz - array containing the number of nonzeros in the various block rows of the 1653 off-diagonal portion of the local submatrix (possibly different for 1654 each block row) or PETSC_NULL. 1655 1656 1657 Options Database Keys: 1658 . -mat_no_unroll - uses code that does not unroll the loops in the 1659 block calculations (much slower) 1660 . -mat_block_size - size of the blocks to use 1661 1662 Notes: 1663 1664 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1665 than it must be used on all processors that share the object for that argument. 1666 1667 Storage Information: 1668 For a square global matrix we define each processor's diagonal portion 1669 to be its local rows and the corresponding columns (a square submatrix); 1670 each processor's off-diagonal portion encompasses the remainder of the 1671 local matrix (a rectangular submatrix). 1672 1673 The user can specify preallocated storage for the diagonal part of 1674 the local submatrix with either d_nz or d_nnz (not both). Set 1675 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1676 memory allocation. Likewise, specify preallocated storage for the 1677 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1678 1679 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1680 the figure below we depict these three local rows and all columns (0-11). 1681 1682 .vb 1683 0 1 2 3 4 5 6 7 8 9 10 11 1684 ------------------- 1685 row 3 | o o o d d d o o o o o o 1686 row 4 | o o o d d d o o o o o o 1687 row 5 | o o o d d d o o o o o o 1688 ------------------- 1689 .ve 1690 1691 Thus, any entries in the d locations are stored in the d (diagonal) 1692 submatrix, and any entries in the o locations are stored in the 1693 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1694 stored simply in the MATSEQBAIJ format for compressed row storage. 1695 1696 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1697 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1698 In general, for PDE problems in which most nonzeros are near the diagonal, 1699 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1700 or you will get TERRIBLE performance; see the users' manual chapter on 1701 matrices. 1702 1703 Level: intermediate 1704 1705 .keywords: matrix, block, aij, compressed row, sparse, parallel 1706 1707 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1708 @*/ 1709 1710 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1711 { 1712 Mat_MPISBAIJ *b; 1713 int ierr,i,mbs,Mbs; 1714 PetscTruth flg2; 1715 1716 PetscFunctionBegin; 1717 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1718 if (!flg2) PetscFunctionReturn(0); 1719 1720 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1721 1722 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1723 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1724 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1725 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1726 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1727 if (d_nnz) { 1728 for (i=0; i<B->m/bs; i++) { 1729 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]); 1730 } 1731 } 1732 if (o_nnz) { 1733 for (i=0; i<B->m/bs; i++) { 1734 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]); 1735 } 1736 } 1737 B->preallocated = PETSC_TRUE; 1738 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1739 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1740 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1741 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1742 1743 b = (Mat_MPISBAIJ*)B->data; 1744 mbs = B->m/bs; 1745 Mbs = B->M/bs; 1746 if (mbs*bs != B->m) { 1747 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1748 } 1749 1750 b->bs = bs; 1751 b->bs2 = bs*bs; 1752 b->mbs = mbs; 1753 b->nbs = mbs; 1754 b->Mbs = Mbs; 1755 b->Nbs = Mbs; 1756 1757 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1758 b->rowners[0] = 0; 1759 for (i=2; i<=b->size; i++) { 1760 b->rowners[i] += b->rowners[i-1]; 1761 } 1762 b->rstart = b->rowners[b->rank]; 1763 b->rend = b->rowners[b->rank+1]; 1764 b->cstart = b->rstart; 1765 b->cend = b->rend; 1766 for (i=0; i<=b->size; i++) { 1767 b->rowners_bs[i] = b->rowners[i]*bs; 1768 } 1769 b->rstart_bs = b-> rstart*bs; 1770 b->rend_bs = b->rend*bs; 1771 1772 b->cstart_bs = b->cstart*bs; 1773 b->cend_bs = b->cend*bs; 1774 1775 1776 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1777 PetscLogObjectParent(B,b->A); 1778 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1779 PetscLogObjectParent(B,b->B); 1780 1781 /* build cache for off array entries formed */ 1782 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1783 1784 PetscFunctionReturn(0); 1785 } 1786 1787 #undef __FUNCT__ 1788 #define __FUNCT__ "MatCreateMPISBAIJ" 1789 /*@C 1790 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1791 (block compressed row). For good matrix assembly performance 1792 the user should preallocate the matrix storage by setting the parameters 1793 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1794 performance can be increased by more than a factor of 50. 1795 1796 Collective on MPI_Comm 1797 1798 Input Parameters: 1799 + comm - MPI communicator 1800 . bs - size of blockk 1801 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1802 This value should be the same as the local size used in creating the 1803 y vector for the matrix-vector product y = Ax. 1804 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1805 This value should be the same as the local size used in creating the 1806 x vector for the matrix-vector product y = Ax. 1807 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1808 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1809 . d_nz - number of block nonzeros per block row in diagonal portion of local 1810 submatrix (same for all local rows) 1811 . d_nnz - array containing the number of block nonzeros in the various block rows 1812 of the in diagonal portion of the local (possibly different for each block 1813 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1814 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1815 submatrix (same for all local rows). 1816 - o_nnz - array containing the number of nonzeros in the various block rows of the 1817 off-diagonal portion of the local submatrix (possibly different for 1818 each block row) or PETSC_NULL. 1819 1820 Output Parameter: 1821 . A - the matrix 1822 1823 Options Database Keys: 1824 . -mat_no_unroll - uses code that does not unroll the loops in the 1825 block calculations (much slower) 1826 . -mat_block_size - size of the blocks to use 1827 . -mat_mpi - use the parallel matrix data structures even on one processor 1828 (defaults to using SeqBAIJ format on one processor) 1829 1830 Notes: 1831 The user MUST specify either the local or global matrix dimensions 1832 (possibly both). 1833 1834 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1835 than it must be used on all processors that share the object for that argument. 1836 1837 Storage Information: 1838 For a square global matrix we define each processor's diagonal portion 1839 to be its local rows and the corresponding columns (a square submatrix); 1840 each processor's off-diagonal portion encompasses the remainder of the 1841 local matrix (a rectangular submatrix). 1842 1843 The user can specify preallocated storage for the diagonal part of 1844 the local submatrix with either d_nz or d_nnz (not both). Set 1845 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1846 memory allocation. Likewise, specify preallocated storage for the 1847 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1848 1849 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1850 the figure below we depict these three local rows and all columns (0-11). 1851 1852 .vb 1853 0 1 2 3 4 5 6 7 8 9 10 11 1854 ------------------- 1855 row 3 | o o o d d d o o o o o o 1856 row 4 | o o o d d d o o o o o o 1857 row 5 | o o o d d d o o o o o o 1858 ------------------- 1859 .ve 1860 1861 Thus, any entries in the d locations are stored in the d (diagonal) 1862 submatrix, and any entries in the o locations are stored in the 1863 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1864 stored simply in the MATSEQBAIJ format for compressed row storage. 1865 1866 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1867 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1868 In general, for PDE problems in which most nonzeros are near the diagonal, 1869 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1870 or you will get TERRIBLE performance; see the users' manual chapter on 1871 matrices. 1872 1873 Level: intermediate 1874 1875 .keywords: matrix, block, aij, compressed row, sparse, parallel 1876 1877 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1878 @*/ 1879 1880 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) 1881 { 1882 int ierr,size; 1883 1884 PetscFunctionBegin; 1885 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1886 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1887 if (size > 1) { 1888 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1889 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1890 } else { 1891 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1892 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1893 } 1894 PetscFunctionReturn(0); 1895 } 1896 1897 1898 #undef __FUNCT__ 1899 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1900 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1901 { 1902 Mat mat; 1903 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1904 int ierr,len=0; 1905 1906 PetscFunctionBegin; 1907 *newmat = 0; 1908 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1909 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1910 mat->preallocated = PETSC_TRUE; 1911 a = (Mat_MPISBAIJ*)mat->data; 1912 a->bs = oldmat->bs; 1913 a->bs2 = oldmat->bs2; 1914 a->mbs = oldmat->mbs; 1915 a->nbs = oldmat->nbs; 1916 a->Mbs = oldmat->Mbs; 1917 a->Nbs = oldmat->Nbs; 1918 1919 a->rstart = oldmat->rstart; 1920 a->rend = oldmat->rend; 1921 a->cstart = oldmat->cstart; 1922 a->cend = oldmat->cend; 1923 a->size = oldmat->size; 1924 a->rank = oldmat->rank; 1925 a->donotstash = oldmat->donotstash; 1926 a->roworiented = oldmat->roworiented; 1927 a->rowindices = 0; 1928 a->rowvalues = 0; 1929 a->getrowactive = PETSC_FALSE; 1930 a->barray = 0; 1931 a->rstart_bs = oldmat->rstart_bs; 1932 a->rend_bs = oldmat->rend_bs; 1933 a->cstart_bs = oldmat->cstart_bs; 1934 a->cend_bs = oldmat->cend_bs; 1935 1936 /* hash table stuff */ 1937 a->ht = 0; 1938 a->hd = 0; 1939 a->ht_size = 0; 1940 a->ht_flag = oldmat->ht_flag; 1941 a->ht_fact = oldmat->ht_fact; 1942 a->ht_total_ct = 0; 1943 a->ht_insert_ct = 0; 1944 1945 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 1946 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1947 a->cowners = a->rowners + a->size + 2; 1948 a->rowners_bs = a->cowners + a->size + 2; 1949 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1950 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1951 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1952 if (oldmat->colmap) { 1953 #if defined (PETSC_USE_CTABLE) 1954 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1955 #else 1956 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1957 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1958 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1959 #endif 1960 } else a->colmap = 0; 1961 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1962 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 1963 PetscLogObjectMemory(mat,len*sizeof(int)); 1964 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 1965 } else a->garray = 0; 1966 1967 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1968 PetscLogObjectParent(mat,a->lvec); 1969 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1970 1971 PetscLogObjectParent(mat,a->Mvctx); 1972 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1973 PetscLogObjectParent(mat,a->A); 1974 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1975 PetscLogObjectParent(mat,a->B); 1976 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1977 *newmat = mat; 1978 PetscFunctionReturn(0); 1979 } 1980 1981 #include "petscsys.h" 1982 1983 EXTERN_C_BEGIN 1984 #undef __FUNCT__ 1985 #define __FUNCT__ "MatLoad_MPISBAIJ" 1986 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1987 { 1988 Mat A; 1989 int i,nz,ierr,j,rstart,rend,fd; 1990 PetscScalar *vals,*buf; 1991 MPI_Comm comm = ((PetscObject)viewer)->comm; 1992 MPI_Status status; 1993 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 1994 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 1995 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 1996 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 1997 int dcount,kmax,k,nzcount,tmp; 1998 1999 PetscFunctionBegin; 2000 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2001 2002 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2003 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2004 if (!rank) { 2005 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2006 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2007 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2008 if (header[3] < 0) { 2009 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2010 } 2011 } 2012 2013 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2014 M = header[1]; N = header[2]; 2015 2016 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2017 2018 /* 2019 This code adds extra rows to make sure the number of rows is 2020 divisible by the blocksize 2021 */ 2022 Mbs = M/bs; 2023 extra_rows = bs - M + bs*(Mbs); 2024 if (extra_rows == bs) extra_rows = 0; 2025 else Mbs++; 2026 if (extra_rows &&!rank) { 2027 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2028 } 2029 2030 /* determine ownership of all rows */ 2031 mbs = Mbs/size + ((Mbs % size) > rank); 2032 m = mbs*bs; 2033 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2034 browners = rowners + size + 1; 2035 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2036 rowners[0] = 0; 2037 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2038 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2039 rstart = rowners[rank]; 2040 rend = rowners[rank+1]; 2041 2042 /* distribute row lengths to all processors */ 2043 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2044 if (!rank) { 2045 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2046 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2047 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2048 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2049 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2050 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2051 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2052 } else { 2053 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2054 } 2055 2056 if (!rank) { /* procs[0] */ 2057 /* calculate the number of nonzeros on each processor */ 2058 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2059 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2060 for (i=0; i<size; i++) { 2061 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2062 procsnz[i] += rowlengths[j]; 2063 } 2064 } 2065 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2066 2067 /* determine max buffer needed and allocate it */ 2068 maxnz = 0; 2069 for (i=0; i<size; i++) { 2070 maxnz = PetscMax(maxnz,procsnz[i]); 2071 } 2072 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2073 2074 /* read in my part of the matrix column indices */ 2075 nz = procsnz[0]; 2076 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2077 mycols = ibuf; 2078 if (size == 1) nz -= extra_rows; 2079 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2080 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2081 2082 /* read in every ones (except the last) and ship off */ 2083 for (i=1; i<size-1; i++) { 2084 nz = procsnz[i]; 2085 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2086 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2087 } 2088 /* read in the stuff for the last proc */ 2089 if (size != 1) { 2090 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2091 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2092 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2093 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2094 } 2095 ierr = PetscFree(cols);CHKERRQ(ierr); 2096 } else { /* procs[i], i>0 */ 2097 /* determine buffer space needed for message */ 2098 nz = 0; 2099 for (i=0; i<m; i++) { 2100 nz += locrowlens[i]; 2101 } 2102 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2103 mycols = ibuf; 2104 /* receive message of column indices*/ 2105 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2106 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2107 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2108 } 2109 2110 /* loop over local rows, determining number of off diagonal entries */ 2111 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2112 odlens = dlens + (rend-rstart); 2113 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2114 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2115 masked1 = mask + Mbs; 2116 masked2 = masked1 + Mbs; 2117 rowcount = 0; nzcount = 0; 2118 for (i=0; i<mbs; i++) { 2119 dcount = 0; 2120 odcount = 0; 2121 for (j=0; j<bs; j++) { 2122 kmax = locrowlens[rowcount]; 2123 for (k=0; k<kmax; k++) { 2124 tmp = mycols[nzcount++]/bs; /* block col. index */ 2125 if (!mask[tmp]) { 2126 mask[tmp] = 1; 2127 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2128 else masked1[dcount++] = tmp; /* entry in diag portion */ 2129 } 2130 } 2131 rowcount++; 2132 } 2133 2134 dlens[i] = dcount; /* d_nzz[i] */ 2135 odlens[i] = odcount; /* o_nzz[i] */ 2136 2137 /* zero out the mask elements we set */ 2138 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2139 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2140 } 2141 2142 /* create our matrix */ 2143 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2144 CHKERRQ(ierr); 2145 A = *newmat; 2146 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2147 2148 if (!rank) { 2149 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2150 /* read in my part of the matrix numerical values */ 2151 nz = procsnz[0]; 2152 vals = buf; 2153 mycols = ibuf; 2154 if (size == 1) nz -= extra_rows; 2155 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2156 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2157 2158 /* insert into matrix */ 2159 jj = rstart*bs; 2160 for (i=0; i<m; i++) { 2161 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2162 mycols += locrowlens[i]; 2163 vals += locrowlens[i]; 2164 jj++; 2165 } 2166 2167 /* read in other processors (except the last one) and ship out */ 2168 for (i=1; i<size-1; i++) { 2169 nz = procsnz[i]; 2170 vals = buf; 2171 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2172 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2173 } 2174 /* the last proc */ 2175 if (size != 1){ 2176 nz = procsnz[i] - extra_rows; 2177 vals = buf; 2178 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2179 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2180 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2181 } 2182 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2183 2184 } else { 2185 /* receive numeric values */ 2186 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2187 2188 /* receive message of values*/ 2189 vals = buf; 2190 mycols = ibuf; 2191 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2192 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2193 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2194 2195 /* insert into matrix */ 2196 jj = rstart*bs; 2197 for (i=0; i<m; i++) { 2198 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2199 mycols += locrowlens[i]; 2200 vals += locrowlens[i]; 2201 jj++; 2202 } 2203 } 2204 2205 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2206 ierr = PetscFree(buf);CHKERRQ(ierr); 2207 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2208 ierr = PetscFree(rowners);CHKERRQ(ierr); 2209 ierr = PetscFree(dlens);CHKERRQ(ierr); 2210 ierr = PetscFree(mask);CHKERRQ(ierr); 2211 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2212 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2213 PetscFunctionReturn(0); 2214 } 2215 EXTERN_C_END 2216 2217 #undef __FUNCT__ 2218 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2219 /*@ 2220 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2221 2222 Input Parameters: 2223 . mat - the matrix 2224 . fact - factor 2225 2226 Collective on Mat 2227 2228 Level: advanced 2229 2230 Notes: 2231 This can also be set by the command line option: -mat_use_hash_table fact 2232 2233 .keywords: matrix, hashtable, factor, HT 2234 2235 .seealso: MatSetOption() 2236 @*/ 2237 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2238 { 2239 PetscFunctionBegin; 2240 SETERRQ(1,"Function not yet written for SBAIJ format"); 2241 /* PetscFunctionReturn(0); */ 2242 } 2243 2244 #undef __FUNCT__ 2245 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2246 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2247 { 2248 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2249 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2250 PetscReal atmp; 2251 PetscReal *work,*svalues,*rvalues; 2252 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2253 int rank,size,*rowners_bs,dest,count,source; 2254 PetscScalar *va; 2255 MatScalar *ba; 2256 MPI_Status stat; 2257 2258 PetscFunctionBegin; 2259 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2260 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2261 2262 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr); 2263 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2264 2265 bs = a->bs; 2266 mbs = a->mbs; 2267 Mbs = a->Mbs; 2268 ba = b->a; 2269 bi = b->i; 2270 bj = b->j; 2271 /* 2272 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2273 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2274 */ 2275 2276 /* find ownerships */ 2277 rowners_bs = a->rowners_bs; 2278 /* 2279 if (!rank){ 2280 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2281 } 2282 */ 2283 2284 /* each proc creates an array to be distributed */ 2285 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2286 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2287 2288 /* row_max for B */ 2289 if (rank != size-1){ 2290 for (i=0; i<mbs; i++) { 2291 ncols = bi[1] - bi[0]; bi++; 2292 brow = bs*i; 2293 for (j=0; j<ncols; j++){ 2294 bcol = bs*(*bj); 2295 for (kcol=0; kcol<bs; kcol++){ 2296 col = bcol + kcol; /* local col index */ 2297 col += rowners_bs[rank+1]; /* global col index */ 2298 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2299 for (krow=0; krow<bs; krow++){ 2300 atmp = PetscAbsScalar(*ba); ba++; 2301 row = brow + krow; /* local row index */ 2302 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2303 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2304 if (work[col] < atmp) work[col] = atmp; 2305 } 2306 } 2307 bj++; 2308 } 2309 } 2310 /* 2311 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2312 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2313 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2314 */ 2315 2316 /* send values to its owners */ 2317 for (dest=rank+1; dest<size; dest++){ 2318 svalues = work + rowners_bs[dest]; 2319 count = rowners_bs[dest+1]-rowners_bs[dest]; 2320 ierr = MPI_Send(svalues,count,MPI_DOUBLE,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2321 /* 2322 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]); 2323 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2324 */ 2325 } 2326 } 2327 2328 /* receive values */ 2329 if (rank){ 2330 rvalues = work; 2331 count = rowners_bs[rank+1]-rowners_bs[rank]; 2332 for (source=0; source<rank; source++){ 2333 ierr = MPI_Recv(rvalues,count,MPI_DOUBLE,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2334 /* process values */ 2335 for (i=0; i<count; i++){ 2336 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2337 } 2338 /* 2339 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]); 2340 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2341 */ 2342 } 2343 } 2344 2345 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2346 ierr = PetscFree(work);CHKERRQ(ierr); 2347 PetscFunctionReturn(0); 2348 } 2349