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,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 + in[j]%bs; 387 #else 388 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 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 } 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->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 849 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 850 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 851 #if defined(PETSC_USE_MAT_SINGLE) 852 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 853 #endif 854 ierr = PetscFree(baij);CHKERRQ(ierr); 855 PetscFunctionReturn(0); 856 } 857 858 #undef __FUNCT__ 859 #define __FUNCT__ "MatMult_MPISBAIJ" 860 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 861 { 862 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 863 int ierr,nt; 864 865 PetscFunctionBegin; 866 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 867 if (nt != A->n) { 868 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 869 } 870 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 871 if (nt != A->m) { 872 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 873 } 874 875 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 876 /* do diagonal part */ 877 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 878 /* do supperdiagonal part */ 879 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 880 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 881 /* do subdiagonal part */ 882 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 883 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 884 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 885 886 PetscFunctionReturn(0); 887 } 888 889 #undef __FUNCT__ 890 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 891 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 892 { 893 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 894 int ierr; 895 896 PetscFunctionBegin; 897 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 898 /* do diagonal part */ 899 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 900 /* do supperdiagonal part */ 901 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 902 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 903 904 /* do subdiagonal part */ 905 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 906 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 907 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 908 909 PetscFunctionReturn(0); 910 } 911 912 #undef __FUNCT__ 913 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 914 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 915 { 916 PetscFunctionBegin; 917 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 918 /* PetscFunctionReturn(0); */ 919 } 920 921 #undef __FUNCT__ 922 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 923 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 924 { 925 PetscFunctionBegin; 926 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 927 /* PetscFunctionReturn(0); */ 928 } 929 930 /* 931 This only works correctly for square matrices where the subblock A->A is the 932 diagonal block 933 */ 934 #undef __FUNCT__ 935 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 936 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 937 { 938 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 939 int ierr; 940 941 PetscFunctionBegin; 942 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 943 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 944 PetscFunctionReturn(0); 945 } 946 947 #undef __FUNCT__ 948 #define __FUNCT__ "MatScale_MPISBAIJ" 949 int MatScale_MPISBAIJ(PetscScalar *aa,Mat A) 950 { 951 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 952 int ierr; 953 954 PetscFunctionBegin; 955 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 956 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 957 PetscFunctionReturn(0); 958 } 959 960 #undef __FUNCT__ 961 #define __FUNCT__ "MatGetRow_MPISBAIJ" 962 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 963 { 964 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 965 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 966 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 967 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 968 int *cmap,*idx_p,cstart = mat->cstart; 969 970 PetscFunctionBegin; 971 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 972 mat->getrowactive = PETSC_TRUE; 973 974 if (!mat->rowvalues && (idx || v)) { 975 /* 976 allocate enough space to hold information from the longest row. 977 */ 978 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 979 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 980 int max = 1,mbs = mat->mbs,tmp; 981 for (i=0; i<mbs; i++) { 982 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 983 if (max < tmp) { max = tmp; } 984 } 985 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 986 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 987 } 988 989 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 990 lrow = row - brstart; /* local row index */ 991 992 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 993 if (!v) {pvA = 0; pvB = 0;} 994 if (!idx) {pcA = 0; if (!v) pcB = 0;} 995 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 996 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 997 nztot = nzA + nzB; 998 999 cmap = mat->garray; 1000 if (v || idx) { 1001 if (nztot) { 1002 /* Sort by increasing column numbers, assuming A and B already sorted */ 1003 int imark = -1; 1004 if (v) { 1005 *v = v_p = mat->rowvalues; 1006 for (i=0; i<nzB; i++) { 1007 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1008 else break; 1009 } 1010 imark = i; 1011 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1012 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1013 } 1014 if (idx) { 1015 *idx = idx_p = mat->rowindices; 1016 if (imark > -1) { 1017 for (i=0; i<imark; i++) { 1018 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1019 } 1020 } else { 1021 for (i=0; i<nzB; i++) { 1022 if (cmap[cworkB[i]/bs] < cstart) 1023 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1024 else break; 1025 } 1026 imark = i; 1027 } 1028 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1029 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1030 } 1031 } else { 1032 if (idx) *idx = 0; 1033 if (v) *v = 0; 1034 } 1035 } 1036 *nz = nztot; 1037 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1038 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1039 PetscFunctionReturn(0); 1040 } 1041 1042 #undef __FUNCT__ 1043 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1044 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1045 { 1046 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1047 1048 PetscFunctionBegin; 1049 if (baij->getrowactive == PETSC_FALSE) { 1050 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1051 } 1052 baij->getrowactive = PETSC_FALSE; 1053 PetscFunctionReturn(0); 1054 } 1055 1056 #undef __FUNCT__ 1057 #define __FUNCT__ "MatGetBlockSize_MPISBAIJ" 1058 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1059 { 1060 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1061 1062 PetscFunctionBegin; 1063 *bs = baij->bs; 1064 PetscFunctionReturn(0); 1065 } 1066 1067 #undef __FUNCT__ 1068 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1069 int MatZeroEntries_MPISBAIJ(Mat A) 1070 { 1071 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1072 int ierr; 1073 1074 PetscFunctionBegin; 1075 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1076 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1077 PetscFunctionReturn(0); 1078 } 1079 1080 #undef __FUNCT__ 1081 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1082 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1083 { 1084 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1085 Mat A = a->A,B = a->B; 1086 int ierr; 1087 PetscReal isend[5],irecv[5]; 1088 1089 PetscFunctionBegin; 1090 info->block_size = (PetscReal)a->bs; 1091 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1092 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1093 isend[3] = info->memory; isend[4] = info->mallocs; 1094 ierr = MatGetInfo(B,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 if (flag == MAT_LOCAL) { 1098 info->nz_used = isend[0]; 1099 info->nz_allocated = isend[1]; 1100 info->nz_unneeded = isend[2]; 1101 info->memory = isend[3]; 1102 info->mallocs = isend[4]; 1103 } else if (flag == MAT_GLOBAL_MAX) { 1104 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1105 info->nz_used = irecv[0]; 1106 info->nz_allocated = irecv[1]; 1107 info->nz_unneeded = irecv[2]; 1108 info->memory = irecv[3]; 1109 info->mallocs = irecv[4]; 1110 } else if (flag == MAT_GLOBAL_SUM) { 1111 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1112 info->nz_used = irecv[0]; 1113 info->nz_allocated = irecv[1]; 1114 info->nz_unneeded = irecv[2]; 1115 info->memory = irecv[3]; 1116 info->mallocs = irecv[4]; 1117 } else { 1118 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1119 } 1120 info->rows_global = (PetscReal)A->M; 1121 info->columns_global = (PetscReal)A->N; 1122 info->rows_local = (PetscReal)A->m; 1123 info->columns_local = (PetscReal)A->N; 1124 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1125 info->fill_ratio_needed = 0; 1126 info->factor_mallocs = 0; 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1132 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1133 { 1134 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1135 int ierr; 1136 1137 PetscFunctionBegin; 1138 switch (op) { 1139 case MAT_NO_NEW_NONZERO_LOCATIONS: 1140 case MAT_YES_NEW_NONZERO_LOCATIONS: 1141 case MAT_COLUMNS_UNSORTED: 1142 case MAT_COLUMNS_SORTED: 1143 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1144 case MAT_KEEP_ZEROED_ROWS: 1145 case MAT_NEW_NONZERO_LOCATION_ERR: 1146 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1147 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1148 break; 1149 case MAT_ROW_ORIENTED: 1150 a->roworiented = PETSC_TRUE; 1151 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1152 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1153 break; 1154 case MAT_ROWS_SORTED: 1155 case MAT_ROWS_UNSORTED: 1156 case MAT_YES_NEW_DIAGONALS: 1157 case MAT_USE_SINGLE_PRECISION_SOLVES: 1158 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1159 break; 1160 case MAT_COLUMN_ORIENTED: 1161 a->roworiented = PETSC_FALSE; 1162 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1163 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1164 break; 1165 case MAT_IGNORE_OFF_PROC_ENTRIES: 1166 a->donotstash = PETSC_TRUE; 1167 break; 1168 case MAT_NO_NEW_DIAGONALS: 1169 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1170 break; 1171 case MAT_USE_HASH_TABLE: 1172 a->ht_flag = PETSC_TRUE; 1173 break; 1174 default: 1175 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1176 break; 1177 } 1178 PetscFunctionReturn(0); 1179 } 1180 1181 #undef __FUNCT__ 1182 #define __FUNCT__ "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 __FUNCT__ 1191 #define __FUNCT__ "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 __FUNCT__ 1226 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1227 int MatZeroRows_MPISBAIJ(Mat A,IS is,PetscScalar *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 __FUNCT__ 1379 #define __FUNCT__ "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 __FUNCT__ 1398 #define __FUNCT__ "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 __FUNCT__ 1412 #define __FUNCT__ "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 __FUNCT__ 1435 #define __FUNCT__ "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 MatRelax_MPISBAIJ, 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 0, 1479 0, 1480 0, 1481 MatDuplicate_MPISBAIJ, 1482 0, 1483 0, 1484 0, 1485 0, 1486 0, 1487 MatGetSubMatrices_MPISBAIJ, 1488 MatIncreaseOverlap_MPISBAIJ, 1489 MatGetValues_MPISBAIJ, 1490 0, 1491 MatPrintHelp_MPISBAIJ, 1492 MatScale_MPISBAIJ, 1493 0, 1494 0, 1495 0, 1496 MatGetBlockSize_MPISBAIJ, 1497 0, 1498 0, 1499 0, 1500 0, 1501 0, 1502 0, 1503 MatSetUnfactored_MPISBAIJ, 1504 0, 1505 MatSetValuesBlocked_MPISBAIJ, 1506 0, 1507 0, 1508 0, 1509 MatGetPetscMaps_Petsc, 1510 0, 1511 0, 1512 0, 1513 0, 1514 0, 1515 0, 1516 MatGetRowMax_MPISBAIJ}; 1517 1518 1519 EXTERN_C_BEGIN 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1522 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1523 { 1524 PetscFunctionBegin; 1525 *a = ((Mat_MPISBAIJ *)A->data)->A; 1526 *iscopy = PETSC_FALSE; 1527 PetscFunctionReturn(0); 1528 } 1529 EXTERN_C_END 1530 1531 EXTERN_C_BEGIN 1532 #undef __FUNCT__ 1533 #define __FUNCT__ "MatCreate_MPISBAIJ" 1534 int MatCreate_MPISBAIJ(Mat B) 1535 { 1536 Mat_MPISBAIJ *b; 1537 int ierr; 1538 PetscTruth flg; 1539 1540 PetscFunctionBegin; 1541 1542 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1543 B->data = (void*)b; 1544 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1545 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1546 1547 B->ops->destroy = MatDestroy_MPISBAIJ; 1548 B->ops->view = MatView_MPISBAIJ; 1549 B->mapping = 0; 1550 B->factor = 0; 1551 B->assembled = PETSC_FALSE; 1552 1553 B->insertmode = NOT_SET_VALUES; 1554 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1555 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1556 1557 /* build local table of row and column ownerships */ 1558 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1559 b->cowners = b->rowners + b->size + 2; 1560 b->rowners_bs = b->cowners + b->size + 2; 1561 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1562 1563 /* build cache for off array entries formed */ 1564 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1565 b->donotstash = PETSC_FALSE; 1566 b->colmap = PETSC_NULL; 1567 b->garray = PETSC_NULL; 1568 b->roworiented = PETSC_TRUE; 1569 1570 #if defined(PETSC_USE_MAT_SINGLE) 1571 /* stuff for MatSetValues_XXX in single precision */ 1572 b->setvalueslen = 0; 1573 b->setvaluescopy = PETSC_NULL; 1574 #endif 1575 1576 /* stuff used in block assembly */ 1577 b->barray = 0; 1578 1579 /* stuff used for matrix vector multiply */ 1580 b->lvec = 0; 1581 b->Mvctx = 0; 1582 1583 /* stuff for MatGetRow() */ 1584 b->rowindices = 0; 1585 b->rowvalues = 0; 1586 b->getrowactive = PETSC_FALSE; 1587 1588 /* hash table stuff */ 1589 b->ht = 0; 1590 b->hd = 0; 1591 b->ht_size = 0; 1592 b->ht_flag = PETSC_FALSE; 1593 b->ht_fact = 0; 1594 b->ht_total_ct = 0; 1595 b->ht_insert_ct = 0; 1596 1597 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1598 if (flg) { 1599 PetscReal fact = 1.39; 1600 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1601 ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1602 if (fact <= 1.0) fact = 1.39; 1603 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1604 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1605 } 1606 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1607 "MatStoreValues_MPISBAIJ", 1608 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1609 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1610 "MatRetrieveValues_MPISBAIJ", 1611 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1612 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1613 "MatGetDiagonalBlock_MPISBAIJ", 1614 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1615 PetscFunctionReturn(0); 1616 } 1617 EXTERN_C_END 1618 1619 #undef __FUNCT__ 1620 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1621 /*@C 1622 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1623 the user should preallocate the matrix storage by setting the parameters 1624 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1625 performance can be increased by more than a factor of 50. 1626 1627 Collective on Mat 1628 1629 Input Parameters: 1630 + A - the matrix 1631 . bs - size of blockk 1632 . d_nz - number of block nonzeros per block row in diagonal portion of local 1633 submatrix (same for all local rows) 1634 . d_nnz - array containing the number of block nonzeros in the various block rows 1635 of the in diagonal portion of the local (possibly different for each block 1636 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1637 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1638 submatrix (same for all local rows). 1639 - o_nnz - array containing the number of nonzeros in the various block rows of the 1640 off-diagonal portion of the local submatrix (possibly different for 1641 each block row) or PETSC_NULL. 1642 1643 1644 Options Database Keys: 1645 . -mat_no_unroll - uses code that does not unroll the loops in the 1646 block calculations (much slower) 1647 . -mat_block_size - size of the blocks to use 1648 1649 Notes: 1650 1651 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1652 than it must be used on all processors that share the object for that argument. 1653 1654 Storage Information: 1655 For a square global matrix we define each processor's diagonal portion 1656 to be its local rows and the corresponding columns (a square submatrix); 1657 each processor's off-diagonal portion encompasses the remainder of the 1658 local matrix (a rectangular submatrix). 1659 1660 The user can specify preallocated storage for the diagonal part of 1661 the local submatrix with either d_nz or d_nnz (not both). Set 1662 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1663 memory allocation. Likewise, specify preallocated storage for the 1664 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1665 1666 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1667 the figure below we depict these three local rows and all columns (0-11). 1668 1669 .vb 1670 0 1 2 3 4 5 6 7 8 9 10 11 1671 ------------------- 1672 row 3 | o o o d d d o o o o o o 1673 row 4 | o o o d d d o o o o o o 1674 row 5 | o o o d d d o o o o o o 1675 ------------------- 1676 .ve 1677 1678 Thus, any entries in the d locations are stored in the d (diagonal) 1679 submatrix, and any entries in the o locations are stored in the 1680 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1681 stored simply in the MATSEQBAIJ format for compressed row storage. 1682 1683 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1684 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1685 In general, for PDE problems in which most nonzeros are near the diagonal, 1686 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1687 or you will get TERRIBLE performance; see the users' manual chapter on 1688 matrices. 1689 1690 Level: intermediate 1691 1692 .keywords: matrix, block, aij, compressed row, sparse, parallel 1693 1694 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1695 @*/ 1696 1697 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1698 { 1699 Mat_MPISBAIJ *b; 1700 int ierr,i,mbs,Mbs; 1701 PetscTruth flg2; 1702 1703 PetscFunctionBegin; 1704 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1705 if (!flg2) PetscFunctionReturn(0); 1706 1707 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1708 1709 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1710 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1711 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1712 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1713 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1714 if (d_nnz) { 1715 for (i=0; i<B->m/bs; i++) { 1716 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]); 1717 } 1718 } 1719 if (o_nnz) { 1720 for (i=0; i<B->m/bs; i++) { 1721 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]); 1722 } 1723 } 1724 B->preallocated = PETSC_TRUE; 1725 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1726 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1727 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1728 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1729 1730 b = (Mat_MPISBAIJ*)B->data; 1731 mbs = B->m/bs; 1732 Mbs = B->M/bs; 1733 if (mbs*bs != B->m) { 1734 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1735 } 1736 1737 b->bs = bs; 1738 b->bs2 = bs*bs; 1739 b->mbs = mbs; 1740 b->nbs = mbs; 1741 b->Mbs = Mbs; 1742 b->Nbs = Mbs; 1743 1744 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1745 b->rowners[0] = 0; 1746 for (i=2; i<=b->size; i++) { 1747 b->rowners[i] += b->rowners[i-1]; 1748 } 1749 b->rstart = b->rowners[b->rank]; 1750 b->rend = b->rowners[b->rank+1]; 1751 b->cstart = b->rstart; 1752 b->cend = b->rend; 1753 for (i=0; i<=b->size; i++) { 1754 b->rowners_bs[i] = b->rowners[i]*bs; 1755 } 1756 b->rstart_bs = b-> rstart*bs; 1757 b->rend_bs = b->rend*bs; 1758 1759 b->cstart_bs = b->cstart*bs; 1760 b->cend_bs = b->cend*bs; 1761 1762 1763 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1764 PetscLogObjectParent(B,b->A); 1765 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1766 PetscLogObjectParent(B,b->B); 1767 1768 /* build cache for off array entries formed */ 1769 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1770 1771 PetscFunctionReturn(0); 1772 } 1773 1774 #undef __FUNCT__ 1775 #define __FUNCT__ "MatCreateMPISBAIJ" 1776 /*@C 1777 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1778 (block compressed row). For good matrix assembly performance 1779 the user should preallocate the matrix storage by setting the parameters 1780 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1781 performance can be increased by more than a factor of 50. 1782 1783 Collective on MPI_Comm 1784 1785 Input Parameters: 1786 + comm - MPI communicator 1787 . bs - size of blockk 1788 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1789 This value should be the same as the local size used in creating the 1790 y vector for the matrix-vector product y = Ax. 1791 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1792 This value should be the same as the local size used in creating the 1793 x vector for the matrix-vector product y = Ax. 1794 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1795 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1796 . d_nz - number of block nonzeros per block row in diagonal portion of local 1797 submatrix (same for all local rows) 1798 . d_nnz - array containing the number of block nonzeros in the various block rows 1799 of the in diagonal portion of the local (possibly different for each block 1800 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1801 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1802 submatrix (same for all local rows). 1803 - o_nnz - array containing the number of nonzeros in the various block rows of the 1804 off-diagonal portion of the local submatrix (possibly different for 1805 each block row) or PETSC_NULL. 1806 1807 Output Parameter: 1808 . A - the matrix 1809 1810 Options Database Keys: 1811 . -mat_no_unroll - uses code that does not unroll the loops in the 1812 block calculations (much slower) 1813 . -mat_block_size - size of the blocks to use 1814 . -mat_mpi - use the parallel matrix data structures even on one processor 1815 (defaults to using SeqBAIJ format on one processor) 1816 1817 Notes: 1818 The user MUST specify either the local or global matrix dimensions 1819 (possibly both). 1820 1821 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1822 than it must be used on all processors that share the object for that argument. 1823 1824 Storage Information: 1825 For a square global matrix we define each processor's diagonal portion 1826 to be its local rows and the corresponding columns (a square submatrix); 1827 each processor's off-diagonal portion encompasses the remainder of the 1828 local matrix (a rectangular submatrix). 1829 1830 The user can specify preallocated storage for the diagonal part of 1831 the local submatrix with either d_nz or d_nnz (not both). Set 1832 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1833 memory allocation. Likewise, specify preallocated storage for the 1834 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1835 1836 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1837 the figure below we depict these three local rows and all columns (0-11). 1838 1839 .vb 1840 0 1 2 3 4 5 6 7 8 9 10 11 1841 ------------------- 1842 row 3 | o o o d d d o o o o o o 1843 row 4 | o o o d d d o o o o o o 1844 row 5 | o o o d d d o o o o o o 1845 ------------------- 1846 .ve 1847 1848 Thus, any entries in the d locations are stored in the d (diagonal) 1849 submatrix, and any entries in the o locations are stored in the 1850 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1851 stored simply in the MATSEQBAIJ format for compressed row storage. 1852 1853 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1854 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1855 In general, for PDE problems in which most nonzeros are near the diagonal, 1856 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1857 or you will get TERRIBLE performance; see the users' manual chapter on 1858 matrices. 1859 1860 Level: intermediate 1861 1862 .keywords: matrix, block, aij, compressed row, sparse, parallel 1863 1864 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1865 @*/ 1866 1867 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) 1868 { 1869 int ierr,size; 1870 1871 PetscFunctionBegin; 1872 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1873 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1874 if (size > 1) { 1875 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1876 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1877 } else { 1878 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1879 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1880 } 1881 PetscFunctionReturn(0); 1882 } 1883 1884 1885 #undef __FUNCT__ 1886 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1887 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1888 { 1889 Mat mat; 1890 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1891 int ierr,len=0; 1892 1893 PetscFunctionBegin; 1894 *newmat = 0; 1895 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1896 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1897 mat->preallocated = PETSC_TRUE; 1898 a = (Mat_MPISBAIJ*)mat->data; 1899 a->bs = oldmat->bs; 1900 a->bs2 = oldmat->bs2; 1901 a->mbs = oldmat->mbs; 1902 a->nbs = oldmat->nbs; 1903 a->Mbs = oldmat->Mbs; 1904 a->Nbs = oldmat->Nbs; 1905 1906 a->rstart = oldmat->rstart; 1907 a->rend = oldmat->rend; 1908 a->cstart = oldmat->cstart; 1909 a->cend = oldmat->cend; 1910 a->size = oldmat->size; 1911 a->rank = oldmat->rank; 1912 a->donotstash = oldmat->donotstash; 1913 a->roworiented = oldmat->roworiented; 1914 a->rowindices = 0; 1915 a->rowvalues = 0; 1916 a->getrowactive = PETSC_FALSE; 1917 a->barray = 0; 1918 a->rstart_bs = oldmat->rstart_bs; 1919 a->rend_bs = oldmat->rend_bs; 1920 a->cstart_bs = oldmat->cstart_bs; 1921 a->cend_bs = oldmat->cend_bs; 1922 1923 /* hash table stuff */ 1924 a->ht = 0; 1925 a->hd = 0; 1926 a->ht_size = 0; 1927 a->ht_flag = oldmat->ht_flag; 1928 a->ht_fact = oldmat->ht_fact; 1929 a->ht_total_ct = 0; 1930 a->ht_insert_ct = 0; 1931 1932 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 1933 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1934 a->cowners = a->rowners + a->size + 2; 1935 a->rowners_bs = a->cowners + a->size + 2; 1936 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1937 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1938 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1939 if (oldmat->colmap) { 1940 #if defined (PETSC_USE_CTABLE) 1941 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1942 #else 1943 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1944 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1945 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1946 #endif 1947 } else a->colmap = 0; 1948 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1949 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 1950 PetscLogObjectMemory(mat,len*sizeof(int)); 1951 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 1952 } else a->garray = 0; 1953 1954 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1955 PetscLogObjectParent(mat,a->lvec); 1956 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1957 1958 PetscLogObjectParent(mat,a->Mvctx); 1959 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1960 PetscLogObjectParent(mat,a->A); 1961 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1962 PetscLogObjectParent(mat,a->B); 1963 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1964 *newmat = mat; 1965 PetscFunctionReturn(0); 1966 } 1967 1968 #include "petscsys.h" 1969 1970 EXTERN_C_BEGIN 1971 #undef __FUNCT__ 1972 #define __FUNCT__ "MatLoad_MPISBAIJ" 1973 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1974 { 1975 Mat A; 1976 int i,nz,ierr,j,rstart,rend,fd; 1977 PetscScalar *vals,*buf; 1978 MPI_Comm comm = ((PetscObject)viewer)->comm; 1979 MPI_Status status; 1980 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 1981 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 1982 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 1983 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 1984 int dcount,kmax,k,nzcount,tmp; 1985 1986 PetscFunctionBegin; 1987 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1988 1989 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1990 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1991 if (!rank) { 1992 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1993 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1994 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1995 if (header[3] < 0) { 1996 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 1997 } 1998 } 1999 2000 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2001 M = header[1]; N = header[2]; 2002 2003 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2004 2005 /* 2006 This code adds extra rows to make sure the number of rows is 2007 divisible by the blocksize 2008 */ 2009 Mbs = M/bs; 2010 extra_rows = bs - M + bs*(Mbs); 2011 if (extra_rows == bs) extra_rows = 0; 2012 else Mbs++; 2013 if (extra_rows &&!rank) { 2014 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2015 } 2016 2017 /* determine ownership of all rows */ 2018 mbs = Mbs/size + ((Mbs % size) > rank); 2019 m = mbs*bs; 2020 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2021 browners = rowners + size + 1; 2022 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2023 rowners[0] = 0; 2024 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2025 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2026 rstart = rowners[rank]; 2027 rend = rowners[rank+1]; 2028 2029 /* distribute row lengths to all processors */ 2030 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2031 if (!rank) { 2032 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2033 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2034 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2035 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2036 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2037 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2038 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2039 } else { 2040 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2041 } 2042 2043 if (!rank) { /* procs[0] */ 2044 /* calculate the number of nonzeros on each processor */ 2045 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2046 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2047 for (i=0; i<size; i++) { 2048 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2049 procsnz[i] += rowlengths[j]; 2050 } 2051 } 2052 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2053 2054 /* determine max buffer needed and allocate it */ 2055 maxnz = 0; 2056 for (i=0; i<size; i++) { 2057 maxnz = PetscMax(maxnz,procsnz[i]); 2058 } 2059 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2060 2061 /* read in my part of the matrix column indices */ 2062 nz = procsnz[0]; 2063 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2064 mycols = ibuf; 2065 if (size == 1) nz -= extra_rows; 2066 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2067 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2068 2069 /* read in every ones (except the last) and ship off */ 2070 for (i=1; i<size-1; i++) { 2071 nz = procsnz[i]; 2072 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2073 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2074 } 2075 /* read in the stuff for the last proc */ 2076 if (size != 1) { 2077 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2078 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2079 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2080 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2081 } 2082 ierr = PetscFree(cols);CHKERRQ(ierr); 2083 } else { /* procs[i], i>0 */ 2084 /* determine buffer space needed for message */ 2085 nz = 0; 2086 for (i=0; i<m; i++) { 2087 nz += locrowlens[i]; 2088 } 2089 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2090 mycols = ibuf; 2091 /* receive message of column indices*/ 2092 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2093 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2094 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2095 } 2096 2097 /* loop over local rows, determining number of off diagonal entries */ 2098 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2099 odlens = dlens + (rend-rstart); 2100 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2101 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2102 masked1 = mask + Mbs; 2103 masked2 = masked1 + Mbs; 2104 rowcount = 0; nzcount = 0; 2105 for (i=0; i<mbs; i++) { 2106 dcount = 0; 2107 odcount = 0; 2108 for (j=0; j<bs; j++) { 2109 kmax = locrowlens[rowcount]; 2110 for (k=0; k<kmax; k++) { 2111 tmp = mycols[nzcount++]/bs; /* block col. index */ 2112 if (!mask[tmp]) { 2113 mask[tmp] = 1; 2114 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2115 else masked1[dcount++] = tmp; /* entry in diag portion */ 2116 } 2117 } 2118 rowcount++; 2119 } 2120 2121 dlens[i] = dcount; /* d_nzz[i] */ 2122 odlens[i] = odcount; /* o_nzz[i] */ 2123 2124 /* zero out the mask elements we set */ 2125 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2126 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2127 } 2128 2129 /* create our matrix */ 2130 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2131 CHKERRQ(ierr); 2132 A = *newmat; 2133 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2134 2135 if (!rank) { 2136 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2137 /* read in my part of the matrix numerical values */ 2138 nz = procsnz[0]; 2139 vals = buf; 2140 mycols = ibuf; 2141 if (size == 1) nz -= extra_rows; 2142 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2143 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2144 2145 /* insert into matrix */ 2146 jj = rstart*bs; 2147 for (i=0; i<m; i++) { 2148 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2149 mycols += locrowlens[i]; 2150 vals += locrowlens[i]; 2151 jj++; 2152 } 2153 2154 /* read in other processors (except the last one) and ship out */ 2155 for (i=1; i<size-1; i++) { 2156 nz = procsnz[i]; 2157 vals = buf; 2158 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2159 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2160 } 2161 /* the last proc */ 2162 if (size != 1){ 2163 nz = procsnz[i] - extra_rows; 2164 vals = buf; 2165 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2166 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2167 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2168 } 2169 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2170 2171 } else { 2172 /* receive numeric values */ 2173 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2174 2175 /* receive message of values*/ 2176 vals = buf; 2177 mycols = ibuf; 2178 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2179 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2180 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2181 2182 /* insert into matrix */ 2183 jj = rstart*bs; 2184 for (i=0; i<m; i++) { 2185 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2186 mycols += locrowlens[i]; 2187 vals += locrowlens[i]; 2188 jj++; 2189 } 2190 } 2191 2192 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2193 ierr = PetscFree(buf);CHKERRQ(ierr); 2194 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2195 ierr = PetscFree(rowners);CHKERRQ(ierr); 2196 ierr = PetscFree(dlens);CHKERRQ(ierr); 2197 ierr = PetscFree(mask);CHKERRQ(ierr); 2198 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2199 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2200 PetscFunctionReturn(0); 2201 } 2202 EXTERN_C_END 2203 2204 #undef __FUNCT__ 2205 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2206 /*@ 2207 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2208 2209 Input Parameters: 2210 . mat - the matrix 2211 . fact - factor 2212 2213 Collective on Mat 2214 2215 Level: advanced 2216 2217 Notes: 2218 This can also be set by the command line option: -mat_use_hash_table fact 2219 2220 .keywords: matrix, hashtable, factor, HT 2221 2222 .seealso: MatSetOption() 2223 @*/ 2224 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2225 { 2226 PetscFunctionBegin; 2227 SETERRQ(1,"Function not yet written for SBAIJ format"); 2228 /* PetscFunctionReturn(0); */ 2229 } 2230 2231 #undef __FUNCT__ 2232 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2233 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2234 { 2235 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2236 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2237 PetscReal atmp; 2238 PetscReal *work,*svalues,*rvalues; 2239 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2240 int rank,size,*rowners_bs,dest,count,source; 2241 PetscScalar *va; 2242 MatScalar *ba; 2243 MPI_Status stat; 2244 2245 PetscFunctionBegin; 2246 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2247 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2248 2249 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr); 2250 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2251 2252 bs = a->bs; 2253 mbs = a->mbs; 2254 Mbs = a->Mbs; 2255 ba = b->a; 2256 bi = b->i; 2257 bj = b->j; 2258 /* 2259 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2260 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2261 */ 2262 2263 /* find ownerships */ 2264 rowners_bs = a->rowners_bs; 2265 /* 2266 if (!rank){ 2267 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2268 } 2269 */ 2270 2271 /* each proc creates an array to be distributed */ 2272 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2273 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2274 2275 /* row_max for B */ 2276 if (rank != size-1){ 2277 for (i=0; i<mbs; i++) { 2278 ncols = bi[1] - bi[0]; bi++; 2279 brow = bs*i; 2280 for (j=0; j<ncols; j++){ 2281 bcol = bs*(*bj); 2282 for (kcol=0; kcol<bs; kcol++){ 2283 col = bcol + kcol; /* local col index */ 2284 col += rowners_bs[rank+1]; /* global col index */ 2285 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2286 for (krow=0; krow<bs; krow++){ 2287 atmp = PetscAbsScalar(*ba); ba++; 2288 row = brow + krow; /* local row index */ 2289 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2290 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2291 if (work[col] < atmp) work[col] = atmp; 2292 } 2293 } 2294 bj++; 2295 } 2296 } 2297 /* 2298 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2299 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2300 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2301 */ 2302 2303 /* send values to its owners */ 2304 for (dest=rank+1; dest<size; dest++){ 2305 svalues = work + rowners_bs[dest]; 2306 count = rowners_bs[dest+1]-rowners_bs[dest]; 2307 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2308 /* 2309 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]); 2310 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2311 */ 2312 } 2313 } 2314 2315 /* receive values */ 2316 if (rank){ 2317 rvalues = work; 2318 count = rowners_bs[rank+1]-rowners_bs[rank]; 2319 for (source=0; source<rank; source++){ 2320 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2321 /* process values */ 2322 for (i=0; i<count; i++){ 2323 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2324 } 2325 /* 2326 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]); 2327 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2328 */ 2329 } 2330 } 2331 2332 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2333 ierr = PetscFree(work);CHKERRQ(ierr); 2334 PetscFunctionReturn(0); 2335 } 2336 2337 #undef __FUNCT__ 2338 #define __FUNCT__ "MatRelax_MPISBAIJ" 2339 int MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,Vec xx) 2340 { 2341 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2342 int ierr; 2343 PetscScalar mone=-1.0; 2344 Vec lvec1,bb1; 2345 MatSORType lflg=SOR_LOCAL_SYMMETRIC_SWEEP; 2346 2347 PetscFunctionBegin; 2348 2349 if (mat->bs > 1) 2350 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2351 2352 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2353 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,1,xx);CHKERRQ(ierr); 2354 its--; 2355 } 2356 2357 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2358 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2359 while (its--){ 2360 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2361 2362 /* lower diagonal part: bb1 = bb - B^T*xx */ 2363 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2364 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2365 2366 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2367 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2368 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2369 2370 /* upper diagonal part: bb1 = bb1 - B*x */ 2371 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2372 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2373 2374 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2375 2376 /* diagonal part */ 2377 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,lflg,fshift,1,xx);CHKERRQ(ierr); 2378 2379 } 2380 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2381 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2382 PetscFunctionReturn(0); 2383 } 2384 2385