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