1 /*$Id: mpisbaij.c,v 1.48 2001/03/22 20:30:33 bsmith Exp bsmith $*/ 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 *,Scalar *); 13 extern int MatSetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *,InsertMode); 14 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 15 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 16 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 17 extern int MatPrintHelp_SeqSBAIJ(Mat); 18 extern int MatZeroRows_SeqSBAIJ(Mat,IS,Scalar*); 19 extern int MatZeroRows_SeqBAIJ(Mat,IS,Scalar *); 20 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 21 22 /* UGLY, ugly, ugly 23 When MatScalar == Scalar 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 __FUNC__ 45 #define __FUNC__ "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 __FUNC__ 60 #define __FUNC__ "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 __FUNC__ 80 #define __FUNC__ "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(Scalar));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 __FUNC__ 246 #define __FUNC__ "MatSetValues_MPISBAIJ" 247 int MatSetValues_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *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 __FUNC__ 269 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ" 270 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *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 __FUNC__ 291 #define __FUNC__ "MatSetValues_MPISBAIJ_HT" 292 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *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 __FUNC__ 304 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ_HT" 305 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *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 __FUNC__ 321 #define __FUNC__ "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 __FUNC__ 430 #define __FUNC__ "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 __FUNC__ 443 #define __FUNC__ "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 __FUNC__ 452 #define __FUNC__ "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 __FUNC__ 461 #define __FUNC__ "MatGetValues_MPISBAIJ" 462 int MatGetValues_MPISBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *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 __FUNC__ 505 #define __FUNC__ "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 __FUNC__ 550 #define __FUNC__ "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 __FUNC__ 559 #define __FUNC__ "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 __FUNC__ 588 #define __FUNC__ "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 __FUNC__ 696 #define __FUNC__ "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 = MatView(baij->A,viewer);CHKERRQ(ierr); 739 } else { 740 /* assemble the entire matrix onto first processor. */ 741 Mat A; 742 Mat_SeqSBAIJ *Aloc; 743 Mat_SeqBAIJ *Bloc; 744 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 745 MatScalar *a; 746 747 if (!rank) { 748 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 749 } else { 750 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 751 } 752 PetscLogObjectParent(mat,A); 753 754 /* copy over the A part */ 755 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 756 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 757 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 758 759 for (i=0; i<mbs; i++) { 760 rvals[0] = bs*(baij->rstart + i); 761 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 762 for (j=ai[i]; j<ai[i+1]; j++) { 763 col = (baij->cstart+aj[j])*bs; 764 for (k=0; k<bs; k++) { 765 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 766 col++; a += bs; 767 } 768 } 769 } 770 /* copy over the B part */ 771 Bloc = (Mat_SeqBAIJ*)baij->B->data; 772 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 773 for (i=0; i<mbs; i++) { 774 rvals[0] = bs*(baij->rstart + i); 775 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 776 for (j=ai[i]; j<ai[i+1]; j++) { 777 col = baij->garray[aj[j]]*bs; 778 for (k=0; k<bs; k++) { 779 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 780 col++; a += bs; 781 } 782 } 783 } 784 ierr = PetscFree(rvals);CHKERRQ(ierr); 785 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 786 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 787 /* 788 Everyone has to call to draw the matrix since the graphics waits are 789 synchronized across all processors that share the PetscDraw object 790 */ 791 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 792 if (!rank) { 793 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 794 } 795 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 796 ierr = MatDestroy(A);CHKERRQ(ierr); 797 } 798 PetscFunctionReturn(0); 799 } 800 801 #undef __FUNC__ 802 #define __FUNC__ "MatView_MPISBAIJ" 803 int MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 804 { 805 int ierr; 806 PetscTruth isascii,isdraw,issocket,isbinary; 807 808 PetscFunctionBegin; 809 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 810 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 811 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 812 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 813 if (isascii || isdraw || issocket || isbinary) { 814 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 815 } else { 816 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 817 } 818 PetscFunctionReturn(0); 819 } 820 821 #undef __FUNC__ 822 #define __FUNC__ "MatDestroy_MPISBAIJ" 823 int MatDestroy_MPISBAIJ(Mat mat) 824 { 825 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 826 int ierr; 827 828 PetscFunctionBegin; 829 #if defined(PETSC_USE_LOG) 830 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 831 #endif 832 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 833 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 834 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 835 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 836 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 837 #if defined (PETSC_USE_CTABLE) 838 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 839 #else 840 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 841 #endif 842 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 843 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 844 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 845 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 846 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 847 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 848 #if defined(PETSC_USE_MAT_SINGLE) 849 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 850 #endif 851 ierr = PetscFree(baij);CHKERRQ(ierr); 852 PetscFunctionReturn(0); 853 } 854 855 #undef __FUNC__ 856 #define __FUNC__ "MatMult_MPISBAIJ" 857 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 858 { 859 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 860 int ierr,nt; 861 862 PetscFunctionBegin; 863 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 864 if (nt != A->n) { 865 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 866 } 867 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 868 if (nt != A->m) { 869 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 870 } 871 872 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 873 /* do diagonal part */ 874 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 875 /* do supperdiagonal part */ 876 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 877 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 878 /* do subdiagonal part */ 879 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 880 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 881 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 882 883 PetscFunctionReturn(0); 884 } 885 886 #undef __FUNC__ 887 #define __FUNC__ "MatMultAdd_MPISBAIJ" 888 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 889 { 890 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 891 int ierr; 892 893 PetscFunctionBegin; 894 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 895 /* do diagonal part */ 896 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 897 /* do supperdiagonal part */ 898 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 899 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 900 901 /* do subdiagonal part */ 902 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 903 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 904 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 905 906 PetscFunctionReturn(0); 907 } 908 909 #undef __FUNC__ 910 #define __FUNC__ "MatMultTranspose_MPISBAIJ" 911 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 912 { 913 PetscFunctionBegin; 914 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 915 /* PetscFunctionReturn(0); */ 916 } 917 918 #undef __FUNC__ 919 #define __FUNC__ "MatMultTransposeAdd_MPISBAIJ" 920 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 921 { 922 PetscFunctionBegin; 923 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 924 /* PetscFunctionReturn(0); */ 925 } 926 927 /* 928 This only works correctly for square matrices where the subblock A->A is the 929 diagonal block 930 */ 931 #undef __FUNC__ 932 #define __FUNC__ "MatGetDiagonal_MPISBAIJ" 933 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 934 { 935 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 936 int ierr; 937 938 PetscFunctionBegin; 939 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 940 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 941 PetscFunctionReturn(0); 942 } 943 944 #undef __FUNC__ 945 #define __FUNC__ "MatScale_MPISBAIJ" 946 int MatScale_MPISBAIJ(Scalar *aa,Mat A) 947 { 948 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 949 int ierr; 950 951 PetscFunctionBegin; 952 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 953 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 954 PetscFunctionReturn(0); 955 } 956 957 #undef __FUNC__ 958 #define __FUNC__ "MatGetOwnershipRange_MPISBAIJ" 959 int MatGetOwnershipRange_MPISBAIJ(Mat matin,int *m,int *n) 960 { 961 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 962 963 PetscFunctionBegin; 964 if (m) *m = mat->rstart*mat->bs; 965 if (n) *n = mat->rend*mat->bs; 966 PetscFunctionReturn(0); 967 } 968 969 #undef __FUNC__ 970 #define __FUNC__ "MatGetRow_MPISBAIJ" 971 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 972 { 973 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 974 Scalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 975 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 976 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 977 int *cmap,*idx_p,cstart = mat->cstart; 978 979 PetscFunctionBegin; 980 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 981 mat->getrowactive = PETSC_TRUE; 982 983 if (!mat->rowvalues && (idx || v)) { 984 /* 985 allocate enough space to hold information from the longest row. 986 */ 987 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 988 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 989 int max = 1,mbs = mat->mbs,tmp; 990 for (i=0; i<mbs; i++) { 991 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 992 if (max < tmp) { max = tmp; } 993 } 994 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(Scalar)),&mat->rowvalues);CHKERRQ(ierr); 995 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 996 } 997 998 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 999 lrow = row - brstart; /* local row index */ 1000 1001 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1002 if (!v) {pvA = 0; pvB = 0;} 1003 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1004 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1005 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1006 nztot = nzA + nzB; 1007 1008 cmap = mat->garray; 1009 if (v || idx) { 1010 if (nztot) { 1011 /* Sort by increasing column numbers, assuming A and B already sorted */ 1012 int imark = -1; 1013 if (v) { 1014 *v = v_p = mat->rowvalues; 1015 for (i=0; i<nzB; i++) { 1016 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1017 else break; 1018 } 1019 imark = i; 1020 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1021 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1022 } 1023 if (idx) { 1024 *idx = idx_p = mat->rowindices; 1025 if (imark > -1) { 1026 for (i=0; i<imark; i++) { 1027 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1028 } 1029 } else { 1030 for (i=0; i<nzB; i++) { 1031 if (cmap[cworkB[i]/bs] < cstart) 1032 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1033 else break; 1034 } 1035 imark = i; 1036 } 1037 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1038 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1039 } 1040 } else { 1041 if (idx) *idx = 0; 1042 if (v) *v = 0; 1043 } 1044 } 1045 *nz = nztot; 1046 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1047 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1048 PetscFunctionReturn(0); 1049 } 1050 1051 #undef __FUNC__ 1052 #define __FUNC__ "MatRestoreRow_MPISBAIJ" 1053 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1054 { 1055 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1056 1057 PetscFunctionBegin; 1058 if (baij->getrowactive == PETSC_FALSE) { 1059 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1060 } 1061 baij->getrowactive = PETSC_FALSE; 1062 PetscFunctionReturn(0); 1063 } 1064 1065 #undef __FUNC__ 1066 #define __FUNC__ "MatGetBlockSize_MPISBAIJ" 1067 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1068 { 1069 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1070 1071 PetscFunctionBegin; 1072 *bs = baij->bs; 1073 PetscFunctionReturn(0); 1074 } 1075 1076 #undef __FUNC__ 1077 #define __FUNC__ "MatZeroEntries_MPISBAIJ" 1078 int MatZeroEntries_MPISBAIJ(Mat A) 1079 { 1080 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1081 int ierr; 1082 1083 PetscFunctionBegin; 1084 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1085 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1086 PetscFunctionReturn(0); 1087 } 1088 1089 #undef __FUNC__ 1090 #define __FUNC__ "MatGetInfo_MPISBAIJ" 1091 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1092 { 1093 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1094 Mat A = a->A,B = a->B; 1095 int ierr; 1096 PetscReal isend[5],irecv[5]; 1097 1098 PetscFunctionBegin; 1099 info->block_size = (double)a->bs; 1100 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1101 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1102 isend[3] = info->memory; isend[4] = info->mallocs; 1103 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1104 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1105 isend[3] += info->memory; isend[4] += info->mallocs; 1106 if (flag == MAT_LOCAL) { 1107 info->nz_used = isend[0]; 1108 info->nz_allocated = isend[1]; 1109 info->nz_unneeded = isend[2]; 1110 info->memory = isend[3]; 1111 info->mallocs = isend[4]; 1112 } else if (flag == MAT_GLOBAL_MAX) { 1113 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1114 info->nz_used = irecv[0]; 1115 info->nz_allocated = irecv[1]; 1116 info->nz_unneeded = irecv[2]; 1117 info->memory = irecv[3]; 1118 info->mallocs = irecv[4]; 1119 } else if (flag == MAT_GLOBAL_SUM) { 1120 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1121 info->nz_used = irecv[0]; 1122 info->nz_allocated = irecv[1]; 1123 info->nz_unneeded = irecv[2]; 1124 info->memory = irecv[3]; 1125 info->mallocs = irecv[4]; 1126 } else { 1127 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1128 } 1129 info->rows_global = (double)A->M; 1130 info->columns_global = (double)A->N; 1131 info->rows_local = (double)A->m; 1132 info->columns_local = (double)A->N; 1133 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1134 info->fill_ratio_needed = 0; 1135 info->factor_mallocs = 0; 1136 PetscFunctionReturn(0); 1137 } 1138 1139 #undef __FUNC__ 1140 #define __FUNC__ "MatSetOption_MPISBAIJ" 1141 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1142 { 1143 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1144 int ierr; 1145 1146 PetscFunctionBegin; 1147 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1148 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1149 op == MAT_COLUMNS_UNSORTED || 1150 op == MAT_COLUMNS_SORTED || 1151 op == MAT_NEW_NONZERO_ALLOCATION_ERR || 1152 op == MAT_KEEP_ZEROED_ROWS || 1153 op == MAT_NEW_NONZERO_LOCATION_ERR) { 1154 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1155 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1156 } else if (op == MAT_ROW_ORIENTED) { 1157 a->roworiented = PETSC_TRUE; 1158 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1159 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1160 } else if (op == MAT_ROWS_SORTED || 1161 op == MAT_ROWS_UNSORTED || 1162 op == MAT_YES_NEW_DIAGONALS || 1163 op == MAT_USE_HASH_TABLE) { 1164 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1165 } else if (op == MAT_COLUMN_ORIENTED) { 1166 a->roworiented = PETSC_FALSE; 1167 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1168 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1169 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1170 a->donotstash = PETSC_TRUE; 1171 } else if (op == MAT_NO_NEW_DIAGONALS) { 1172 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1173 } else if (op == MAT_USE_HASH_TABLE) { 1174 a->ht_flag = PETSC_TRUE; 1175 } else { 1176 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1177 } 1178 PetscFunctionReturn(0); 1179 } 1180 1181 #undef __FUNC__ 1182 #define __FUNC__ "MatTranspose_MPISBAIJ(" 1183 int MatTranspose_MPISBAIJ(Mat A,Mat *matout) 1184 { 1185 PetscFunctionBegin; 1186 SETERRQ(1,"Matrix is symmetric. MatTranspose() should not be called"); 1187 /* PetscFunctionReturn(0); */ 1188 } 1189 1190 #undef __FUNC__ 1191 #define __FUNC__ "MatDiagonalScale_MPISBAIJ" 1192 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1193 { 1194 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1195 Mat a = baij->A,b = baij->B; 1196 int ierr,s1,s2,s3; 1197 1198 PetscFunctionBegin; 1199 if (ll != rr) { 1200 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1201 } 1202 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1203 if (rr) { 1204 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1205 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1206 /* Overlap communication with computation. */ 1207 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1208 /*} if (ll) { */ 1209 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1210 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1211 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1212 /* } */ 1213 /* scale the diagonal block */ 1214 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1215 1216 /* if (rr) { */ 1217 /* Do a scatter end and then right scale the off-diagonal block */ 1218 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1219 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1220 } 1221 1222 PetscFunctionReturn(0); 1223 } 1224 1225 #undef __FUNC__ 1226 #define __FUNC__ "MatZeroRows_MPISBAIJ" 1227 int MatZeroRows_MPISBAIJ(Mat A,IS is,Scalar *diag) 1228 { 1229 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1230 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 1231 int *procs,*nprocs,j,idx,nsends,*work,row; 1232 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1233 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1234 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1235 MPI_Comm comm = A->comm; 1236 MPI_Request *send_waits,*recv_waits; 1237 MPI_Status recv_status,*send_status; 1238 IS istmp; 1239 PetscTruth found; 1240 1241 PetscFunctionBegin; 1242 ierr = ISGetSize(is,&N);CHKERRQ(ierr); 1243 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1244 1245 /* first count number of contributors to each processor */ 1246 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 1247 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 1248 procs = nprocs + size; 1249 ierr = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/ 1250 for (i=0; i<N; i++) { 1251 idx = rows[i]; 1252 found = PETSC_FALSE; 1253 for (j=0; j<size; j++) { 1254 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1255 nprocs[j]++; procs[j] = 1; owner[i] = j; found = PETSC_TRUE; break; 1256 } 1257 } 1258 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1259 } 1260 nsends = 0; for (i=0; i<size; i++) { nsends += procs[i];} 1261 1262 /* inform other processors of number of messages and max length*/ 1263 ierr = PetscMalloc(2*size*sizeof(int),&work);CHKERRQ(ierr); 1264 ierr = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr); 1265 nmax = work[rank]; 1266 nrecvs = work[size+rank]; 1267 ierr = PetscFree(work);CHKERRQ(ierr); 1268 1269 /* post receives: */ 1270 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 1271 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1272 for (i=0; i<nrecvs; i++) { 1273 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1274 } 1275 1276 /* do sends: 1277 1) starts[i] gives the starting index in svalues for stuff going to 1278 the ith processor 1279 */ 1280 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 1281 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1282 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 1283 starts[0] = 0; 1284 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1285 for (i=0; i<N; i++) { 1286 svalues[starts[owner[i]]++] = rows[i]; 1287 } 1288 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1289 1290 starts[0] = 0; 1291 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1292 count = 0; 1293 for (i=0; i<size; i++) { 1294 if (procs[i]) { 1295 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1296 } 1297 } 1298 ierr = PetscFree(starts);CHKERRQ(ierr); 1299 1300 base = owners[rank]*bs; 1301 1302 /* wait on receives */ 1303 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 1304 source = lens + nrecvs; 1305 count = nrecvs; slen = 0; 1306 while (count) { 1307 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1308 /* unpack receives into our local space */ 1309 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1310 source[imdex] = recv_status.MPI_SOURCE; 1311 lens[imdex] = n; 1312 slen += n; 1313 count--; 1314 } 1315 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1316 1317 /* move the data into the send scatter */ 1318 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 1319 count = 0; 1320 for (i=0; i<nrecvs; i++) { 1321 values = rvalues + i*nmax; 1322 for (j=0; j<lens[i]; j++) { 1323 lrows[count++] = values[j] - base; 1324 } 1325 } 1326 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1327 ierr = PetscFree(lens);CHKERRQ(ierr); 1328 ierr = PetscFree(owner);CHKERRQ(ierr); 1329 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1330 1331 /* actually zap the local rows */ 1332 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1333 PetscLogObjectParent(A,istmp); 1334 1335 /* 1336 Zero the required rows. If the "diagonal block" of the matrix 1337 is square and the user wishes to set the diagonal we use seperate 1338 code so that MatSetValues() is not called for each diagonal allocating 1339 new memory, thus calling lots of mallocs and slowing things down. 1340 1341 Contributed by: Mathew Knepley 1342 */ 1343 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1344 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1345 if (diag && (l->A->M == l->A->N)) { 1346 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1347 } else if (diag) { 1348 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1349 if (((Mat_SeqSBAIJ*)l->A->data)->nonew) { 1350 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1351 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1352 } 1353 for (i=0; i<slen; i++) { 1354 row = lrows[i] + rstart_bs; 1355 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1356 } 1357 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1358 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1359 } else { 1360 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1361 } 1362 1363 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1364 ierr = PetscFree(lrows);CHKERRQ(ierr); 1365 1366 /* wait on sends */ 1367 if (nsends) { 1368 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1369 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1370 ierr = PetscFree(send_status);CHKERRQ(ierr); 1371 } 1372 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1373 ierr = PetscFree(svalues);CHKERRQ(ierr); 1374 1375 PetscFunctionReturn(0); 1376 } 1377 1378 #undef __FUNC__ 1379 #define __FUNC__ "MatPrintHelp_MPISBAIJ" 1380 int MatPrintHelp_MPISBAIJ(Mat A) 1381 { 1382 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1383 MPI_Comm comm = A->comm; 1384 static int called = 0; 1385 int ierr; 1386 1387 PetscFunctionBegin; 1388 if (!a->rank) { 1389 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1390 } 1391 if (called) {PetscFunctionReturn(0);} else called = 1; 1392 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1393 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1394 PetscFunctionReturn(0); 1395 } 1396 1397 #undef __FUNC__ 1398 #define __FUNC__ "MatSetUnfactored_MPISBAIJ" 1399 int MatSetUnfactored_MPISBAIJ(Mat A) 1400 { 1401 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1402 int ierr; 1403 1404 PetscFunctionBegin; 1405 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1406 PetscFunctionReturn(0); 1407 } 1408 1409 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1410 1411 #undef __FUNC__ 1412 #define __FUNC__ "MatEqual_MPISBAIJ" 1413 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1414 { 1415 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1416 Mat a,b,c,d; 1417 PetscTruth flg; 1418 int ierr; 1419 1420 PetscFunctionBegin; 1421 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg);CHKERRQ(ierr); 1422 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1423 a = matA->A; b = matA->B; 1424 c = matB->A; d = matB->B; 1425 1426 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1427 if (flg == PETSC_TRUE) { 1428 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1429 } 1430 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1431 PetscFunctionReturn(0); 1432 } 1433 1434 #undef __FUNC__ 1435 #define __FUNC__ "MatSetUpPreallocation_MPISBAIJ" 1436 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1437 { 1438 int ierr; 1439 1440 PetscFunctionBegin; 1441 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1442 PetscFunctionReturn(0); 1443 } 1444 /* -------------------------------------------------------------------*/ 1445 static struct _MatOps MatOps_Values = { 1446 MatSetValues_MPISBAIJ, 1447 MatGetRow_MPISBAIJ, 1448 MatRestoreRow_MPISBAIJ, 1449 MatMult_MPISBAIJ, 1450 MatMultAdd_MPISBAIJ, 1451 MatMultTranspose_MPISBAIJ, 1452 MatMultTransposeAdd_MPISBAIJ, 1453 0, 1454 0, 1455 0, 1456 0, 1457 0, 1458 0, 1459 0, 1460 MatTranspose_MPISBAIJ, 1461 MatGetInfo_MPISBAIJ, 1462 MatEqual_MPISBAIJ, 1463 MatGetDiagonal_MPISBAIJ, 1464 MatDiagonalScale_MPISBAIJ, 1465 MatNorm_MPISBAIJ, 1466 MatAssemblyBegin_MPISBAIJ, 1467 MatAssemblyEnd_MPISBAIJ, 1468 0, 1469 MatSetOption_MPISBAIJ, 1470 MatZeroEntries_MPISBAIJ, 1471 MatZeroRows_MPISBAIJ, 1472 0, 1473 0, 1474 0, 1475 0, 1476 MatSetUpPreallocation_MPISBAIJ, 1477 0, 1478 MatGetOwnershipRange_MPISBAIJ, 1479 0, 1480 0, 1481 0, 1482 0, 1483 MatDuplicate_MPISBAIJ, 1484 0, 1485 0, 1486 0, 1487 0, 1488 0, 1489 MatGetSubMatrices_MPISBAIJ, 1490 MatIncreaseOverlap_MPISBAIJ, 1491 MatGetValues_MPISBAIJ, 1492 0, 1493 MatPrintHelp_MPISBAIJ, 1494 MatScale_MPISBAIJ, 1495 0, 1496 0, 1497 0, 1498 MatGetBlockSize_MPISBAIJ, 1499 0, 1500 0, 1501 0, 1502 0, 1503 0, 1504 0, 1505 MatSetUnfactored_MPISBAIJ, 1506 0, 1507 MatSetValuesBlocked_MPISBAIJ, 1508 0, 1509 0, 1510 0, 1511 MatGetMaps_Petsc, 1512 0, 1513 0, 1514 0, 1515 0, 1516 0, 1517 0, 1518 MatGetRowMax_MPISBAIJ}; 1519 1520 1521 EXTERN_C_BEGIN 1522 #undef __FUNC__ 1523 #define __FUNC__ "MatGetDiagonalBlock_MPISBAIJ" 1524 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1525 { 1526 PetscFunctionBegin; 1527 *a = ((Mat_MPISBAIJ *)A->data)->A; 1528 *iscopy = PETSC_FALSE; 1529 PetscFunctionReturn(0); 1530 } 1531 EXTERN_C_END 1532 1533 EXTERN_C_BEGIN 1534 #undef __FUNC__ 1535 #define __FUNC__ "MatCreate_MPISBAIJ" 1536 int MatCreate_MPISBAIJ(Mat B) 1537 { 1538 Mat_MPISBAIJ *b; 1539 int ierr; 1540 PetscTruth flg; 1541 1542 PetscFunctionBegin; 1543 1544 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1545 B->data = (void*)b; 1546 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1547 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1548 1549 B->ops->destroy = MatDestroy_MPISBAIJ; 1550 B->ops->view = MatView_MPISBAIJ; 1551 B->mapping = 0; 1552 B->factor = 0; 1553 B->assembled = PETSC_FALSE; 1554 1555 B->insertmode = NOT_SET_VALUES; 1556 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1557 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1558 1559 /* build local table of row and column ownerships */ 1560 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1561 b->cowners = b->rowners + b->size + 2; 1562 b->rowners_bs = b->cowners + b->size + 2; 1563 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1564 1565 /* build cache for off array entries formed */ 1566 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1567 b->donotstash = PETSC_FALSE; 1568 b->colmap = PETSC_NULL; 1569 b->garray = PETSC_NULL; 1570 b->roworiented = PETSC_TRUE; 1571 1572 #if defined(PETSC_USE_MAT_SINGLE) 1573 /* stuff for MatSetValues_XXX in single precision */ 1574 b->lensetvalues = 0; 1575 b->setvaluescopy = PETSC_NULL; 1576 #endif 1577 1578 /* stuff used in block assembly */ 1579 b->barray = 0; 1580 1581 /* stuff used for matrix vector multiply */ 1582 b->lvec = 0; 1583 b->Mvctx = 0; 1584 1585 /* stuff for MatGetRow() */ 1586 b->rowindices = 0; 1587 b->rowvalues = 0; 1588 b->getrowactive = PETSC_FALSE; 1589 1590 /* hash table stuff */ 1591 b->ht = 0; 1592 b->hd = 0; 1593 b->ht_size = 0; 1594 b->ht_flag = PETSC_FALSE; 1595 b->ht_fact = 0; 1596 b->ht_total_ct = 0; 1597 b->ht_insert_ct = 0; 1598 1599 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1600 if (flg) { 1601 double fact = 1.39; 1602 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1603 ierr = PetscOptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1604 if (fact <= 1.0) fact = 1.39; 1605 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1606 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1607 } 1608 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1609 "MatStoreValues_MPISBAIJ", 1610 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1611 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1612 "MatRetrieveValues_MPISBAIJ", 1613 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1614 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1615 "MatGetDiagonalBlock_MPISBAIJ", 1616 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1617 PetscFunctionReturn(0); 1618 } 1619 EXTERN_C_END 1620 1621 #undef __FUNC__ 1622 #define __FUNC__ "MatMPISBAIJSetPreallocation" 1623 /*@C 1624 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1625 the user should preallocate the matrix storage by setting the parameters 1626 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1627 performance can be increased by more than a factor of 50. 1628 1629 Collective on Mat 1630 1631 Input Parameters: 1632 + A - the matrix 1633 . bs - size of blockk 1634 . d_nz - number of block nonzeros per block row in diagonal portion of local 1635 submatrix (same for all local rows) 1636 . d_nnz - array containing the number of block nonzeros in the various block rows 1637 of the in diagonal portion of the local (possibly different for each block 1638 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1639 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1640 submatrix (same for all local rows). 1641 - o_nnz - array containing the number of nonzeros in the various block rows of the 1642 off-diagonal portion of the local submatrix (possibly different for 1643 each block row) or PETSC_NULL. 1644 1645 1646 Options Database Keys: 1647 . -mat_no_unroll - uses code that does not unroll the loops in the 1648 block calculations (much slower) 1649 . -mat_block_size - size of the blocks to use 1650 1651 Notes: 1652 1653 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1654 than it must be used on all processors that share the object for that argument. 1655 1656 Storage Information: 1657 For a square global matrix we define each processor's diagonal portion 1658 to be its local rows and the corresponding columns (a square submatrix); 1659 each processor's off-diagonal portion encompasses the remainder of the 1660 local matrix (a rectangular submatrix). 1661 1662 The user can specify preallocated storage for the diagonal part of 1663 the local submatrix with either d_nz or d_nnz (not both). Set 1664 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1665 memory allocation. Likewise, specify preallocated storage for the 1666 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1667 1668 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1669 the figure below we depict these three local rows and all columns (0-11). 1670 1671 .vb 1672 0 1 2 3 4 5 6 7 8 9 10 11 1673 ------------------- 1674 row 3 | o o o d d d o o o o o o 1675 row 4 | o o o d d d o o o o o o 1676 row 5 | o o o d d d o o o o o o 1677 ------------------- 1678 .ve 1679 1680 Thus, any entries in the d locations are stored in the d (diagonal) 1681 submatrix, and any entries in the o locations are stored in the 1682 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1683 stored simply in the MATSEQBAIJ format for compressed row storage. 1684 1685 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1686 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1687 In general, for PDE problems in which most nonzeros are near the diagonal, 1688 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1689 or you will get TERRIBLE performance; see the users' manual chapter on 1690 matrices. 1691 1692 Level: intermediate 1693 1694 .keywords: matrix, block, aij, compressed row, sparse, parallel 1695 1696 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1697 @*/ 1698 1699 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1700 { 1701 Mat_MPISBAIJ *b; 1702 int ierr,i,mbs,Mbs; 1703 PetscTruth flg2; 1704 1705 PetscFunctionBegin; 1706 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1707 if (!flg2) PetscFunctionReturn(0); 1708 1709 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1710 1711 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1712 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1713 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1714 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1715 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1716 if (d_nnz) { 1717 for (i=0; i<B->m/bs; i++) { 1718 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]); 1719 } 1720 } 1721 if (o_nnz) { 1722 for (i=0; i<B->m/bs; i++) { 1723 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]); 1724 } 1725 } 1726 B->preallocated = PETSC_TRUE; 1727 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1728 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1729 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1730 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1731 1732 b = (Mat_MPISBAIJ*)B->data; 1733 mbs = B->m/bs; 1734 Mbs = B->M/bs; 1735 if (mbs*bs != B->m) { 1736 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1737 } 1738 1739 b->bs = bs; 1740 b->bs2 = bs*bs; 1741 b->mbs = mbs; 1742 b->nbs = mbs; 1743 b->Mbs = Mbs; 1744 b->Nbs = Mbs; 1745 1746 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1747 b->rowners[0] = 0; 1748 for (i=2; i<=b->size; i++) { 1749 b->rowners[i] += b->rowners[i-1]; 1750 } 1751 b->rstart = b->rowners[b->rank]; 1752 b->rend = b->rowners[b->rank+1]; 1753 b->cstart = b->rstart; 1754 b->cend = b->rend; 1755 for (i=0; i<=b->size; i++) { 1756 b->rowners_bs[i] = b->rowners[i]*bs; 1757 } 1758 b->rstart_bs = b-> rstart*bs; 1759 b->rend_bs = b->rend*bs; 1760 1761 b->cstart_bs = b->cstart*bs; 1762 b->cend_bs = b->cend*bs; 1763 1764 1765 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1766 PetscLogObjectParent(B,b->A); 1767 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1768 PetscLogObjectParent(B,b->B); 1769 1770 /* build cache for off array entries formed */ 1771 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1772 1773 PetscFunctionReturn(0); 1774 } 1775 1776 #undef __FUNC__ 1777 #define __FUNC__ "MatCreateMPISBAIJ" 1778 /*@C 1779 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1780 (block compressed row). For good matrix assembly performance 1781 the user should preallocate the matrix storage by setting the parameters 1782 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1783 performance can be increased by more than a factor of 50. 1784 1785 Collective on MPI_Comm 1786 1787 Input Parameters: 1788 + comm - MPI communicator 1789 . bs - size of blockk 1790 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1791 This value should be the same as the local size used in creating the 1792 y vector for the matrix-vector product y = Ax. 1793 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1794 This value should be the same as the local size used in creating the 1795 x vector for the matrix-vector product y = Ax. 1796 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1797 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1798 . d_nz - number of block nonzeros per block row in diagonal portion of local 1799 submatrix (same for all local rows) 1800 . d_nnz - array containing the number of block nonzeros in the various block rows 1801 of the in diagonal portion of the local (possibly different for each block 1802 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1803 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1804 submatrix (same for all local rows). 1805 - o_nnz - array containing the number of nonzeros in the various block rows of the 1806 off-diagonal portion of the local submatrix (possibly different for 1807 each block row) or PETSC_NULL. 1808 1809 Output Parameter: 1810 . A - the matrix 1811 1812 Options Database Keys: 1813 . -mat_no_unroll - uses code that does not unroll the loops in the 1814 block calculations (much slower) 1815 . -mat_block_size - size of the blocks to use 1816 . -mat_mpi - use the parallel matrix data structures even on one processor 1817 (defaults to using SeqBAIJ format on one processor) 1818 1819 Notes: 1820 The user MUST specify either the local or global matrix dimensions 1821 (possibly both). 1822 1823 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1824 than it must be used on all processors that share the object for that argument. 1825 1826 Storage Information: 1827 For a square global matrix we define each processor's diagonal portion 1828 to be its local rows and the corresponding columns (a square submatrix); 1829 each processor's off-diagonal portion encompasses the remainder of the 1830 local matrix (a rectangular submatrix). 1831 1832 The user can specify preallocated storage for the diagonal part of 1833 the local submatrix with either d_nz or d_nnz (not both). Set 1834 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1835 memory allocation. Likewise, specify preallocated storage for the 1836 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1837 1838 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1839 the figure below we depict these three local rows and all columns (0-11). 1840 1841 .vb 1842 0 1 2 3 4 5 6 7 8 9 10 11 1843 ------------------- 1844 row 3 | o o o d d d o o o o o o 1845 row 4 | o o o d d d o o o o o o 1846 row 5 | o o o d d d o o o o o o 1847 ------------------- 1848 .ve 1849 1850 Thus, any entries in the d locations are stored in the d (diagonal) 1851 submatrix, and any entries in the o locations are stored in the 1852 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1853 stored simply in the MATSEQBAIJ format for compressed row storage. 1854 1855 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1856 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1857 In general, for PDE problems in which most nonzeros are near the diagonal, 1858 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1859 or you will get TERRIBLE performance; see the users' manual chapter on 1860 matrices. 1861 1862 Level: intermediate 1863 1864 .keywords: matrix, block, aij, compressed row, sparse, parallel 1865 1866 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1867 @*/ 1868 1869 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) 1870 { 1871 int ierr,size; 1872 1873 PetscFunctionBegin; 1874 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1875 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1876 if (size > 1) { 1877 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1878 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1879 } else { 1880 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1881 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1882 } 1883 PetscFunctionReturn(0); 1884 } 1885 1886 1887 #undef __FUNC__ 1888 #define __FUNC__ "MatDuplicate_MPISBAIJ" 1889 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1890 { 1891 Mat mat; 1892 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1893 int ierr,len=0; 1894 1895 PetscFunctionBegin; 1896 *newmat = 0; 1897 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1898 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1899 mat->preallocated = PETSC_TRUE; 1900 a = (Mat_MPISBAIJ*)mat->data; 1901 a->bs = oldmat->bs; 1902 a->bs2 = oldmat->bs2; 1903 a->mbs = oldmat->mbs; 1904 a->nbs = oldmat->nbs; 1905 a->Mbs = oldmat->Mbs; 1906 a->Nbs = oldmat->Nbs; 1907 1908 a->rstart = oldmat->rstart; 1909 a->rend = oldmat->rend; 1910 a->cstart = oldmat->cstart; 1911 a->cend = oldmat->cend; 1912 a->size = oldmat->size; 1913 a->rank = oldmat->rank; 1914 a->donotstash = oldmat->donotstash; 1915 a->roworiented = oldmat->roworiented; 1916 a->rowindices = 0; 1917 a->rowvalues = 0; 1918 a->getrowactive = PETSC_FALSE; 1919 a->barray = 0; 1920 a->rstart_bs = oldmat->rstart_bs; 1921 a->rend_bs = oldmat->rend_bs; 1922 a->cstart_bs = oldmat->cstart_bs; 1923 a->cend_bs = oldmat->cend_bs; 1924 1925 /* hash table stuff */ 1926 a->ht = 0; 1927 a->hd = 0; 1928 a->ht_size = 0; 1929 a->ht_flag = oldmat->ht_flag; 1930 a->ht_fact = oldmat->ht_fact; 1931 a->ht_total_ct = 0; 1932 a->ht_insert_ct = 0; 1933 1934 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 1935 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1936 a->cowners = a->rowners + a->size + 2; 1937 a->rowners_bs = a->cowners + a->size + 2; 1938 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1939 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1940 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1941 if (oldmat->colmap) { 1942 #if defined (PETSC_USE_CTABLE) 1943 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1944 #else 1945 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1946 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1947 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1948 #endif 1949 } else a->colmap = 0; 1950 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1951 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 1952 PetscLogObjectMemory(mat,len*sizeof(int)); 1953 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 1954 } else a->garray = 0; 1955 1956 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1957 PetscLogObjectParent(mat,a->lvec); 1958 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1959 1960 PetscLogObjectParent(mat,a->Mvctx); 1961 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1962 PetscLogObjectParent(mat,a->A); 1963 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1964 PetscLogObjectParent(mat,a->B); 1965 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1966 *newmat = mat; 1967 PetscFunctionReturn(0); 1968 } 1969 1970 #include "petscsys.h" 1971 1972 EXTERN_C_BEGIN 1973 #undef __FUNC__ 1974 #define __FUNC__ "MatLoad_MPISBAIJ" 1975 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1976 { 1977 Mat A; 1978 int i,nz,ierr,j,rstart,rend,fd; 1979 Scalar *vals,*buf; 1980 MPI_Comm comm = ((PetscObject)viewer)->comm; 1981 MPI_Status status; 1982 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 1983 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 1984 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 1985 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 1986 int dcount,kmax,k,nzcount,tmp; 1987 1988 PetscFunctionBegin; 1989 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1990 1991 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1992 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1993 if (!rank) { 1994 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1995 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1996 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1997 if (header[3] < 0) { 1998 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 1999 } 2000 } 2001 2002 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2003 M = header[1]; N = header[2]; 2004 2005 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2006 2007 /* 2008 This code adds extra rows to make sure the number of rows is 2009 divisible by the blocksize 2010 */ 2011 Mbs = M/bs; 2012 extra_rows = bs - M + bs*(Mbs); 2013 if (extra_rows == bs) extra_rows = 0; 2014 else Mbs++; 2015 if (extra_rows &&!rank) { 2016 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2017 } 2018 2019 /* determine ownership of all rows */ 2020 mbs = Mbs/size + ((Mbs % size) > rank); 2021 m = mbs*bs; 2022 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2023 browners = rowners + size + 1; 2024 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2025 rowners[0] = 0; 2026 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2027 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2028 rstart = rowners[rank]; 2029 rend = rowners[rank+1]; 2030 2031 /* distribute row lengths to all processors */ 2032 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2033 if (!rank) { 2034 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2035 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2036 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2037 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2038 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2039 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2040 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2041 } else { 2042 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2043 } 2044 2045 if (!rank) { /* procs[0] */ 2046 /* calculate the number of nonzeros on each processor */ 2047 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2048 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2049 for (i=0; i<size; i++) { 2050 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2051 procsnz[i] += rowlengths[j]; 2052 } 2053 } 2054 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2055 2056 /* determine max buffer needed and allocate it */ 2057 maxnz = 0; 2058 for (i=0; i<size; i++) { 2059 maxnz = PetscMax(maxnz,procsnz[i]); 2060 } 2061 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2062 2063 /* read in my part of the matrix column indices */ 2064 nz = procsnz[0]; 2065 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2066 mycols = ibuf; 2067 if (size == 1) nz -= extra_rows; 2068 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2069 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2070 2071 /* read in every ones (except the last) and ship off */ 2072 for (i=1; i<size-1; i++) { 2073 nz = procsnz[i]; 2074 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2075 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2076 } 2077 /* read in the stuff for the last proc */ 2078 if (size != 1) { 2079 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2080 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2081 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2082 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2083 } 2084 ierr = PetscFree(cols);CHKERRQ(ierr); 2085 } else { /* procs[i], i>0 */ 2086 /* determine buffer space needed for message */ 2087 nz = 0; 2088 for (i=0; i<m; i++) { 2089 nz += locrowlens[i]; 2090 } 2091 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2092 mycols = ibuf; 2093 /* receive message of column indices*/ 2094 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2095 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2096 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2097 } 2098 2099 /* loop over local rows, determining number of off diagonal entries */ 2100 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2101 odlens = dlens + (rend-rstart); 2102 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2103 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2104 masked1 = mask + Mbs; 2105 masked2 = masked1 + Mbs; 2106 rowcount = 0; nzcount = 0; 2107 for (i=0; i<mbs; i++) { 2108 dcount = 0; 2109 odcount = 0; 2110 for (j=0; j<bs; j++) { 2111 kmax = locrowlens[rowcount]; 2112 for (k=0; k<kmax; k++) { 2113 tmp = mycols[nzcount++]/bs; /* block col. index */ 2114 if (!mask[tmp]) { 2115 mask[tmp] = 1; 2116 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2117 else masked1[dcount++] = tmp; /* entry in diag portion */ 2118 } 2119 } 2120 rowcount++; 2121 } 2122 2123 dlens[i] = dcount; /* d_nzz[i] */ 2124 odlens[i] = odcount; /* o_nzz[i] */ 2125 2126 /* zero out the mask elements we set */ 2127 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2128 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2129 } 2130 2131 /* create our matrix */ 2132 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2133 CHKERRQ(ierr); 2134 A = *newmat; 2135 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2136 2137 if (!rank) { 2138 ierr = PetscMalloc(maxnz*sizeof(Scalar),&buf);CHKERRQ(ierr); 2139 /* read in my part of the matrix numerical values */ 2140 nz = procsnz[0]; 2141 vals = buf; 2142 mycols = ibuf; 2143 if (size == 1) nz -= extra_rows; 2144 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2145 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2146 2147 /* insert into matrix */ 2148 jj = rstart*bs; 2149 for (i=0; i<m; i++) { 2150 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2151 mycols += locrowlens[i]; 2152 vals += locrowlens[i]; 2153 jj++; 2154 } 2155 2156 /* read in other processors (except the last one) and ship out */ 2157 for (i=1; i<size-1; i++) { 2158 nz = procsnz[i]; 2159 vals = buf; 2160 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2161 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2162 } 2163 /* the last proc */ 2164 if (size != 1){ 2165 nz = procsnz[i] - extra_rows; 2166 vals = buf; 2167 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2168 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2169 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2170 } 2171 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2172 2173 } else { 2174 /* receive numeric values */ 2175 ierr = PetscMalloc(nz*sizeof(Scalar),&buf);CHKERRQ(ierr); 2176 2177 /* receive message of values*/ 2178 vals = buf; 2179 mycols = ibuf; 2180 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2181 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2182 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2183 2184 /* insert into matrix */ 2185 jj = rstart*bs; 2186 for (i=0; i<m; i++) { 2187 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2188 mycols += locrowlens[i]; 2189 vals += locrowlens[i]; 2190 jj++; 2191 } 2192 } 2193 2194 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2195 ierr = PetscFree(buf);CHKERRQ(ierr); 2196 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2197 ierr = PetscFree(rowners);CHKERRQ(ierr); 2198 ierr = PetscFree(dlens);CHKERRQ(ierr); 2199 ierr = PetscFree(mask);CHKERRQ(ierr); 2200 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2201 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2202 PetscFunctionReturn(0); 2203 } 2204 EXTERN_C_END 2205 2206 #undef __FUNC__ 2207 #define __FUNC__ "MatMPISBAIJSetHashTableFactor" 2208 /*@ 2209 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2210 2211 Input Parameters: 2212 . mat - the matrix 2213 . fact - factor 2214 2215 Collective on Mat 2216 2217 Level: advanced 2218 2219 Notes: 2220 This can also be set by the command line option: -mat_use_hash_table fact 2221 2222 .keywords: matrix, hashtable, factor, HT 2223 2224 .seealso: MatSetOption() 2225 @*/ 2226 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2227 { 2228 PetscFunctionBegin; 2229 SETERRQ(1,"Function not yet written for SBAIJ format"); 2230 /* PetscFunctionReturn(0); */ 2231 } 2232 2233 #undef __FUNC__ 2234 #define __FUNC__ "MatGetRowMax_MPISBAIJ" 2235 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2236 { 2237 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2238 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2239 PetscReal atmp; 2240 double *work,*svalues,*rvalues; 2241 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2242 int rank,size,*rowners_bs,dest,count,source; 2243 Scalar *ba,*va; 2244 MPI_Status stat; 2245 2246 PetscFunctionBegin; 2247 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2248 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2249 2250 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr); 2251 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2252 2253 bs = a->bs; 2254 mbs = a->mbs; 2255 Mbs = a->Mbs; 2256 ba = b->a; 2257 bi = b->i; 2258 bj = b->j; 2259 /* 2260 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2261 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2262 */ 2263 2264 /* find ownerships */ 2265 rowners_bs = a->rowners_bs; 2266 /* 2267 if (!rank){ 2268 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2269 } 2270 */ 2271 2272 /* each proc creates an array to be distributed */ 2273 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2274 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2275 2276 /* row_max for B */ 2277 if (rank != size-1){ 2278 for (i=0; i<mbs; i++) { 2279 ncols = bi[1] - bi[0]; bi++; 2280 brow = bs*i; 2281 for (j=0; j<ncols; j++){ 2282 bcol = bs*(*bj); 2283 for (kcol=0; kcol<bs; kcol++){ 2284 col = bcol + kcol; /* local col index */ 2285 col += rowners_bs[rank+1]; /* global col index */ 2286 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2287 for (krow=0; krow<bs; krow++){ 2288 atmp = PetscAbsScalar(*ba); ba++; 2289 row = brow + krow; /* local row index */ 2290 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2291 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2292 if (work[col] < atmp) work[col] = atmp; 2293 } 2294 } 2295 bj++; 2296 } 2297 } 2298 /* 2299 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2300 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2301 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2302 */ 2303 2304 /* send values to its owners */ 2305 for (dest=rank+1; dest<size; dest++){ 2306 svalues = work + rowners_bs[dest]; 2307 count = rowners_bs[dest+1]-rowners_bs[dest]; 2308 ierr = MPI_Send(svalues,count,MPI_DOUBLE,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2309 /* 2310 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]); 2311 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2312 */ 2313 } 2314 } 2315 2316 /* receive values */ 2317 if (rank){ 2318 rvalues = work; 2319 count = rowners_bs[rank+1]-rowners_bs[rank]; 2320 for (source=0; source<rank; source++){ 2321 ierr = MPI_Recv(rvalues,count,MPI_DOUBLE,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2322 /* process values */ 2323 for (i=0; i<count; i++){ 2324 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2325 } 2326 /* 2327 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]); 2328 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2329 */ 2330 } 2331 } 2332 2333 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2334 ierr = PetscFree(work);CHKERRQ(ierr); 2335 PetscFunctionReturn(0); 2336 } 2337