1 /*$Id: mpisbaij.c,v 1.36 2000/10/30 18:23:34 hzhang Exp hzhang $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "src/vec/vecimpl.h" 5 #include "mpisbaij.h" 6 #include "src/mat/impls/sbaij/seq/sbaij.h" 7 8 extern int MatSetUpMultiply_MPISBAIJ(Mat); 9 extern int DisAssemble_MPISBAIJ(Mat); 10 extern int MatIncreaseOverlap_MPISBAIJ(Mat,int,IS *,int); 11 extern int MatGetSubMatrices_MPISBAIJ(Mat,int,IS *,IS *,MatReuse,Mat **); 12 extern int MatGetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *); 13 extern int MatSetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *,InsertMode); 14 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 15 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 16 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 17 extern int MatPrintHelp_SeqSBAIJ(Mat); 18 extern int MatZeroRows_SeqSBAIJ(Mat,IS,Scalar*); 19 extern int MatZeroRows_SeqBAIJ(Mat,IS,Scalar *); 20 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 21 22 /* UGLY, ugly, ugly 23 When MatScalar == Scalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 24 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 25 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 26 converts the entries into single precision and then calls ..._MatScalar() to put them 27 into the single precision data structures. 28 */ 29 #if defined(PETSC_USE_MAT_SINGLE) 30 extern int MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 31 extern int MatSetValues_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 32 extern int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 33 extern int MatSetValues_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 34 extern int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 35 #else 36 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 37 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 38 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 39 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 40 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 41 #endif 42 43 EXTERN_C_BEGIN 44 #undef __FUNC__ 45 #define __FUNC__ /*<a name="MatStoreValues_MPISBAIJ"></a>*/"MatStoreValues_MPISBAIJ" 46 int MatStoreValues_MPISBAIJ(Mat mat) 47 { 48 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 49 int ierr; 50 51 PetscFunctionBegin; 52 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 53 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 54 PetscFunctionReturn(0); 55 } 56 EXTERN_C_END 57 58 EXTERN_C_BEGIN 59 #undef __FUNC__ 60 #define __FUNC__ /*<a name="MatRetrieveValues_MPISBAIJ"></a>*/"MatRetrieveValues_MPISBAIJ" 61 int MatRetrieveValues_MPISBAIJ(Mat mat) 62 { 63 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 64 int ierr; 65 66 PetscFunctionBegin; 67 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 68 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 69 PetscFunctionReturn(0); 70 } 71 EXTERN_C_END 72 73 /* 74 Local utility routine that creates a mapping from the global column 75 number to the local number in the off-diagonal part of the local 76 storage of the matrix. This is done in a non scable way since the 77 length of colmap equals the global matrix length. 78 */ 79 #undef __FUNC__ 80 #define __FUNC__ /*<a name="CreateColmap_MPISBAIJ_Private"></a>*/"CreateColmap_MPISBAIJ_Private" 81 static int CreateColmap_MPISBAIJ_Private(Mat mat) 82 { 83 PetscFunctionBegin; 84 SETERRQ(1,"Function not yet written for SBAIJ format"); 85 /* PetscFunctionReturn(0); */ 86 } 87 88 #define CHUNKSIZE 10 89 90 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 91 { \ 92 \ 93 brow = row/bs; \ 94 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 95 rmax = aimax[brow]; nrow = ailen[brow]; \ 96 bcol = col/bs; \ 97 ridx = row % bs; cidx = col % bs; \ 98 low = 0; high = nrow; \ 99 while (high-low > 3) { \ 100 t = (low+high)/2; \ 101 if (rp[t] > bcol) high = t; \ 102 else low = t; \ 103 } \ 104 for (_i=low; _i<high; _i++) { \ 105 if (rp[_i] > bcol) break; \ 106 if (rp[_i] == bcol) { \ 107 bap = ap + bs2*_i + bs*cidx + ridx; \ 108 if (addv == ADD_VALUES) *bap += value; \ 109 else *bap = value; \ 110 goto a_noinsert; \ 111 } \ 112 } \ 113 if (a->nonew == 1) goto a_noinsert; \ 114 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 115 if (nrow >= rmax) { \ 116 /* there is no extra room in row, therefore enlarge */ \ 117 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 118 MatScalar *new_a; \ 119 \ 120 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 121 \ 122 /* malloc new storage space */ \ 123 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 124 new_a = (MatScalar*)PetscMalloc(len);CHKPTRQ(new_a); \ 125 new_j = (int*)(new_a + bs2*new_nz); \ 126 new_i = new_j + new_nz; \ 127 \ 128 /* copy over old data into new slots */ \ 129 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 130 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 131 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 132 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 133 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 134 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 135 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar));CHKERRQ(ierr); \ 136 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 137 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 138 /* free up old matrix storage */ \ 139 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 140 if (!a->singlemalloc) { \ 141 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 142 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 143 } \ 144 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 145 a->singlemalloc = PETSC_TRUE; \ 146 \ 147 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 148 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 149 PLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 150 a->s_maxnz += bs2*CHUNKSIZE; \ 151 a->reallocs++; \ 152 a->s_nz++; \ 153 } \ 154 N = nrow++ - 1; \ 155 /* shift up all the later entries in this row */ \ 156 for (ii=N; ii>=_i; ii--) { \ 157 rp[ii+1] = rp[ii]; \ 158 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 159 } \ 160 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 161 rp[_i] = bcol; \ 162 ap[bs2*_i + bs*cidx + ridx] = value; \ 163 a_noinsert:; \ 164 ailen[brow] = nrow; \ 165 } 166 #ifndef MatSetValues_SeqBAIJ_B_Private 167 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 168 { \ 169 brow = row/bs; \ 170 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 171 rmax = bimax[brow]; nrow = bilen[brow]; \ 172 bcol = col/bs; \ 173 ridx = row % bs; cidx = col % bs; \ 174 low = 0; high = nrow; \ 175 while (high-low > 3) { \ 176 t = (low+high)/2; \ 177 if (rp[t] > bcol) high = t; \ 178 else low = t; \ 179 } \ 180 for (_i=low; _i<high; _i++) { \ 181 if (rp[_i] > bcol) break; \ 182 if (rp[_i] == bcol) { \ 183 bap = ap + bs2*_i + bs*cidx + ridx; \ 184 if (addv == ADD_VALUES) *bap += value; \ 185 else *bap = value; \ 186 goto b_noinsert; \ 187 } \ 188 } \ 189 if (b->nonew == 1) goto b_noinsert; \ 190 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 191 if (nrow >= rmax) { \ 192 /* there is no extra room in row, therefore enlarge */ \ 193 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 194 MatScalar *new_a; \ 195 \ 196 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 197 \ 198 /* malloc new storage space */ \ 199 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 200 new_a = (MatScalar*)PetscMalloc(len);CHKPTRQ(new_a); \ 201 new_j = (int*)(new_a + bs2*new_nz); \ 202 new_i = new_j + new_nz; \ 203 \ 204 /* copy over old data into new slots */ \ 205 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 206 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 207 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 208 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 209 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 210 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 211 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 212 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 213 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 214 /* free up old matrix storage */ \ 215 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 216 if (!b->singlemalloc) { \ 217 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 218 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 219 } \ 220 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 221 b->singlemalloc = PETSC_TRUE; \ 222 \ 223 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 224 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 225 PLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 226 b->maxnz += bs2*CHUNKSIZE; \ 227 b->reallocs++; \ 228 b->nz++; \ 229 } \ 230 N = nrow++ - 1; \ 231 /* shift up all the later entries in this row */ \ 232 for (ii=N; ii>=_i; ii--) { \ 233 rp[ii+1] = rp[ii]; \ 234 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 235 } \ 236 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 237 rp[_i] = bcol; \ 238 ap[bs2*_i + bs*cidx + ridx] = value; \ 239 b_noinsert:; \ 240 bilen[brow] = nrow; \ 241 } 242 #endif 243 244 #if defined(PETSC_USE_MAT_SINGLE) 245 #undef __FUNC__ 246 #define __FUNC__ /*<a name="MatSetValues_MPISBAIJ"></a>*/"MatSetValues_MPISBAIJ" 247 int MatSetValues_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 248 { 249 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 250 int ierr,i,N = m*n; 251 MatScalar *vsingle; 252 253 PetscFunctionBegin; 254 if (N > b->setvalueslen) { 255 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 256 b->setvaluescopy = (MatScalar*)PetscMalloc(N*sizeof(MatScalar));CHKPTRQ(b->setvaluescopy); 257 b->setvalueslen = N; 258 } 259 vsingle = b->setvaluescopy; 260 261 for (i=0; i<N; i++) { 262 vsingle[i] = v[i]; 263 } 264 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 265 PetscFunctionReturn(0); 266 } 267 268 #undef __FUNC__ 269 #define __FUNC__ /*<a name="MatSetValuesBlocked_MPISBAIJ"></a>*/"MatSetValuesBlocked_MPISBAIJ" 270 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 271 { 272 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 273 int ierr,i,N = m*n*b->bs2; 274 MatScalar *vsingle; 275 276 PetscFunctionBegin; 277 if (N > b->setvalueslen) { 278 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 279 b->setvaluescopy = (MatScalar*)PetscMalloc(N*sizeof(MatScalar));CHKPTRQ(b->setvaluescopy); 280 b->setvalueslen = N; 281 } 282 vsingle = b->setvaluescopy; 283 for (i=0; i<N; i++) { 284 vsingle[i] = v[i]; 285 } 286 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 287 PetscFunctionReturn(0); 288 } 289 290 #undef __FUNC__ 291 #define __FUNC__ /*<a name="MatSetValues_MPISBAIJ_HT"></a>*/"MatSetValues_MPISBAIJ_HT" 292 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 293 { 294 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 295 int ierr,i,N = m*n; 296 MatScalar *vsingle; 297 298 PetscFunctionBegin; 299 SETERRQ(1,"Function not yet written for SBAIJ format"); 300 /* PetscFunctionReturn(0); */ 301 } 302 303 #undef __FUNC__ 304 #define __FUNC__ /*<a name="MatSetValuesBlocked_MPISBAIJ_HT"></a>*/"MatSetValuesBlocked_MPISBAIJ_HT" 305 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 306 { 307 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 308 int ierr,i,N = m*n*b->bs2; 309 MatScalar *vsingle; 310 311 PetscFunctionBegin; 312 SETERRQ(1,"Function not yet written for SBAIJ format"); 313 /* PetscFunctionReturn(0); */ 314 } 315 #endif 316 317 /* Only add/insert a(i,j) with i<=j (blocks). 318 Any a(i,j) with i>j input by user is ingored. 319 */ 320 #undef __FUNC__ 321 #define __FUNC__ /*<a name="MatSetValues_MPIBAIJ"></a>*/"MatSetValues_MPIBAIJ" 322 int MatSetValues_MPISBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 323 { 324 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 325 MatScalar value; 326 PetscTruth roworiented = baij->roworiented; 327 int ierr,i,j,row,col; 328 int rstart_orig=baij->rstart_bs; 329 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 330 int cend_orig=baij->cend_bs,bs=baij->bs; 331 332 /* Some Variables required in the macro */ 333 Mat A = baij->A; 334 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 335 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 336 MatScalar *aa=a->a; 337 338 Mat B = baij->B; 339 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 340 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 341 MatScalar *ba=b->a; 342 343 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 344 int low,high,t,ridx,cidx,bs2=a->bs2; 345 MatScalar *ap,*bap; 346 347 /* for stash */ 348 int n_loc, *in_loc=0; 349 MatScalar *v_loc=0; 350 351 PetscFunctionBegin; 352 353 if(!baij->donotstash){ 354 in_loc = (int*)PetscMalloc(n*sizeof(int));CHKPTRQ(in_loc); 355 v_loc = (MatScalar*)PetscMalloc(n*sizeof(MatScalar));CHKPTRQ(v_loc); 356 } 357 358 for (i=0; i<m; i++) { 359 if (im[i] < 0) continue; 360 #if defined(PETSC_USE_BOPT_g) 361 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 362 #endif 363 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 364 row = im[i] - rstart_orig; /* local row index */ 365 for (j=0; j<n; j++) { 366 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 367 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 368 col = in[j] - cstart_orig; /* local col index */ 369 brow = row/bs; bcol = col/bs; 370 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 371 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 372 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 373 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 374 } else if (in[j] < 0) continue; 375 #if defined(PETSC_USE_BOPT_g) 376 else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Col too large");} 377 #endif 378 else { /* off-diag entry (B) */ 379 if (mat->was_assembled) { 380 if (!baij->colmap) { 381 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 382 } 383 #if defined (PETSC_USE_CTABLE) 384 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 385 col = col - 1 + in[j]%bs; 386 #else 387 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 388 #endif 389 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 390 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 391 col = in[j]; 392 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 393 B = baij->B; 394 b = (Mat_SeqBAIJ*)(B)->data; 395 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 396 ba=b->a; 397 } 398 } else col = in[j]; 399 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 400 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 401 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 402 } 403 } 404 } else { /* off processor entry */ 405 if (!baij->donotstash) { 406 n_loc = 0; 407 for (j=0; j<n; j++){ 408 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 409 in_loc[n_loc] = in[j]; 410 if (roworiented) { 411 v_loc[n_loc] = v[i*n+j]; 412 } else { 413 v_loc[n_loc] = v[j*m+i]; 414 } 415 n_loc++; 416 } 417 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 418 } 419 } 420 } 421 422 if(!baij->donotstash){ 423 ierr = PetscFree(in_loc);CHKERRQ(ierr); 424 ierr = PetscFree(v_loc);CHKERRQ(ierr); 425 } 426 PetscFunctionReturn(0); 427 } 428 429 #undef __FUNC__ 430 #define __FUNC__ /*<a name="MatSetValuesBlocked_MPISBAIJ"></a>*/"MatSetValuesBlocked_MPISBAIJ" 431 int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 432 { 433 PetscFunctionBegin; 434 SETERRQ(1,"Function not yet written for SBAIJ format"); 435 /* PetscFunctionReturn(0); */ 436 } 437 438 #define HASH_KEY 0.6180339887 439 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 440 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 441 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 442 #undef __FUNC__ 443 #define __FUNC__ /*<a name="MatSetValues_MPISBAIJ_HT_MatScalar"></a>*/"MatSetValues_MPISBAIJ_HT_MatScalar" 444 int MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 445 { 446 PetscFunctionBegin; 447 SETERRQ(1,"Function not yet written for SBAIJ format"); 448 /* PetscFunctionReturn(0); */ 449 } 450 451 #undef __FUNC__ 452 #define __FUNC__ /*<a name=""></a>*/"MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 453 int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 454 { 455 PetscFunctionBegin; 456 SETERRQ(1,"Function not yet written for SBAIJ format"); 457 /* PetscFunctionReturn(0); */ 458 } 459 460 #undef __FUNC__ 461 #define __FUNC__ /*<a name=""></a>*/"MatGetValues_MPISBAIJ" 462 int MatGetValues_MPISBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 463 { 464 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 465 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 466 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 467 468 PetscFunctionBegin; 469 for (i=0; i<m; i++) { 470 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 471 if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 472 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 473 row = idxm[i] - bsrstart; 474 for (j=0; j<n; j++) { 475 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 476 if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 477 if (idxn[j] >= bscstart && idxn[j] < bscend){ 478 col = idxn[j] - bscstart; 479 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 480 } else { 481 if (!baij->colmap) { 482 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 483 } 484 #if defined (PETSC_USE_CTABLE) 485 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 486 data --; 487 #else 488 data = baij->colmap[idxn[j]/bs]-1; 489 #endif 490 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 491 else { 492 col = data + idxn[j]%bs; 493 ierr = MatGetValues_SeqSBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 494 } 495 } 496 } 497 } else { 498 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 499 } 500 } 501 PetscFunctionReturn(0); 502 } 503 504 #undef __FUNC__ 505 #define __FUNC__ /*<a name=""></a>*/"MatNorm_MPISBAIJ" 506 int MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 507 { 508 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 509 /* Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ*)baij->A->data; */ 510 /* Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ*)baij->B->data; */ 511 int ierr; 512 PetscReal sum[2],*lnorm2; 513 514 PetscFunctionBegin; 515 if (baij->size == 1) { 516 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 517 } else { 518 if (type == NORM_FROBENIUS) { 519 lnorm2 = (double*)PetscMalloc(2*sizeof(double));CHKPTRQ(lnorm2); 520 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 521 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 522 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 523 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 524 /* 525 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 526 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], lnorm2=%g, %g\n",rank,lnorm2[0],lnorm2[1]); 527 */ 528 ierr = MPI_Allreduce(lnorm2,&sum,2,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 529 /* 530 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], sum=%g, %g\n",rank,sum[0],sum[1]); 531 PetscSynchronizedFlush(PETSC_COMM_WORLD); */ 532 533 *norm = sqrt(sum[0] + 2*sum[1]); 534 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 535 } else { 536 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 537 } 538 } 539 PetscFunctionReturn(0); 540 } 541 542 /* 543 Creates the hash table, and sets the table 544 This table is created only once. 545 If new entried need to be added to the matrix 546 then the hash table has to be destroyed and 547 recreated. 548 */ 549 #undef __FUNC__ 550 #define __FUNC__ /*<a name=""></a>*/"MatCreateHashTable_MPISBAIJ_Private" 551 int MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 552 { 553 PetscFunctionBegin; 554 SETERRQ(1,"Function not yet written for SBAIJ format"); 555 /* PetscFunctionReturn(0); */ 556 } 557 558 #undef __FUNC__ 559 #define __FUNC__ /*<a name=""></a>*/"MatAssemblyBegin_MPISBAIJ" 560 int MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 561 { 562 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 563 int ierr,nstash,reallocs; 564 InsertMode addv; 565 566 PetscFunctionBegin; 567 if (baij->donotstash) { 568 PetscFunctionReturn(0); 569 } 570 571 /* make sure all processors are either in INSERTMODE or ADDMODE */ 572 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 573 if (addv == (ADD_VALUES|INSERT_VALUES)) { 574 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 575 } 576 mat->insertmode = addv; /* in case this processor had no cache */ 577 578 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 579 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 580 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 581 PLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 582 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 583 PLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 584 PetscFunctionReturn(0); 585 } 586 587 #undef __FUNC__ 588 #define __FUNC__ /*<a name=""></a>*/"MatAssemblyEnd_MPISBAIJ" 589 int MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 590 { 591 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 592 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 593 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 594 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 595 int *row,*col,other_disassembled; 596 PetscTruth r1,r2,r3; 597 MatScalar *val; 598 InsertMode addv = mat->insertmode; 599 int rank; 600 601 PetscFunctionBegin; 602 /* remove 2 line below later */ 603 ierr = MPI_Comm_rank(PETSC_COMM_WORLD, &rank);CHKERRQ(ierr); 604 605 if (!baij->donotstash) { 606 while (1) { 607 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 608 /* 609 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d]: in AssemblyEnd, stash, flg=%d\n",rank,flg); 610 PetscSynchronizedFlush(PETSC_COMM_WORLD); 611 */ 612 if (!flg) break; 613 614 for (i=0; i<n;) { 615 /* Now identify the consecutive vals belonging to the same row */ 616 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 617 if (j < n) ncols = j-i; 618 else ncols = n-i; 619 /* Now assemble all these values with a single function call */ 620 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 621 i = j; 622 } 623 } 624 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 625 /* Now process the block-stash. Since the values are stashed column-oriented, 626 set the roworiented flag to column oriented, and after MatSetValues() 627 restore the original flags */ 628 r1 = baij->roworiented; 629 r2 = a->roworiented; 630 r3 = b->roworiented; 631 baij->roworiented = PETSC_FALSE; 632 a->roworiented = PETSC_FALSE; 633 b->roworiented = PETSC_FALSE; 634 while (1) { 635 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 636 if (!flg) break; 637 638 for (i=0; i<n;) { 639 /* Now identify the consecutive vals belonging to the same row */ 640 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 641 if (j < n) ncols = j-i; 642 else ncols = n-i; 643 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 644 i = j; 645 } 646 } 647 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 648 baij->roworiented = r1; 649 a->roworiented = r2; 650 b->roworiented = r3; 651 } 652 653 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 654 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 655 656 /* determine if any processor has disassembled, if so we must 657 also disassemble ourselfs, in order that we may reassemble. */ 658 /* 659 if nonzero structure of submatrix B cannot change then we know that 660 no processor disassembled thus we can skip this stuff 661 */ 662 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 663 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 664 if (mat->was_assembled && !other_disassembled) { 665 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 666 } 667 } 668 669 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 670 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); 671 } 672 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 673 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 674 675 #if defined(PETSC_USE_BOPT_g) 676 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 677 PLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((double)baij->ht_total_ct)/baij->ht_insert_ct); 678 baij->ht_total_ct = 0; 679 baij->ht_insert_ct = 0; 680 } 681 #endif 682 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 683 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 684 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 685 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 686 } 687 688 if (baij->rowvalues) { 689 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 690 baij->rowvalues = 0; 691 } 692 PetscFunctionReturn(0); 693 } 694 695 #undef __FUNC__ 696 #define __FUNC__ /*<a name=""></a>*/"MatView_MPISBAIJ_ASCIIorDraworSocket" 697 static int MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,Viewer viewer) 698 { 699 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 700 int ierr,format,bs = baij->bs,size = baij->size,rank = baij->rank; 701 PetscTruth isascii,isdraw; 702 Viewer sviewer; 703 704 PetscFunctionBegin; 705 ierr = PetscTypeCompare((PetscObject)viewer,ASCII_VIEWER,&isascii);CHKERRQ(ierr); 706 ierr = PetscTypeCompare((PetscObject)viewer,DRAW_VIEWER,&isdraw);CHKERRQ(ierr); 707 if (isascii) { 708 ierr = ViewerGetFormat(viewer,&format);CHKERRQ(ierr); 709 if (format == VIEWER_FORMAT_ASCII_INFO_LONG) { 710 MatInfo info; 711 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 712 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 713 ierr = ViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 714 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 715 baij->bs,(int)info.memory);CHKERRQ(ierr); 716 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 717 ierr = ViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 718 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 719 ierr = ViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 720 ierr = ViewerFlush(viewer);CHKERRQ(ierr); 721 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 722 PetscFunctionReturn(0); 723 } else if (format == VIEWER_FORMAT_ASCII_INFO) { 724 ierr = ViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 725 PetscFunctionReturn(0); 726 } 727 } 728 729 if (isdraw) { 730 Draw draw; 731 PetscTruth isnull; 732 ierr = ViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 733 ierr = DrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 734 } 735 736 if (size == 1) { 737 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 738 } else { 739 /* assemble the entire matrix onto first processor. */ 740 Mat A; 741 Mat_SeqSBAIJ *Aloc; 742 Mat_SeqBAIJ *Bloc; 743 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 744 MatScalar *a; 745 746 if (!rank) { 747 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 748 } else { 749 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 750 } 751 PLogObjectParent(mat,A); 752 753 /* copy over the A part */ 754 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 755 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 756 rvals = (int*)PetscMalloc(bs*sizeof(int));CHKPTRQ(rvals); 757 758 for (i=0; i<mbs; i++) { 759 rvals[0] = bs*(baij->rstart + i); 760 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 761 for (j=ai[i]; j<ai[i+1]; j++) { 762 col = (baij->cstart+aj[j])*bs; 763 for (k=0; k<bs; k++) { 764 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 765 col++; a += bs; 766 } 767 } 768 } 769 /* copy over the B part */ 770 Bloc = (Mat_SeqBAIJ*)baij->B->data; 771 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 772 for (i=0; i<mbs; i++) { 773 rvals[0] = bs*(baij->rstart + i); 774 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 775 for (j=ai[i]; j<ai[i+1]; j++) { 776 col = baij->garray[aj[j]]*bs; 777 for (k=0; k<bs; k++) { 778 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 779 col++; a += bs; 780 } 781 } 782 } 783 ierr = PetscFree(rvals);CHKERRQ(ierr); 784 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 785 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 786 /* 787 Everyone has to call to draw the matrix since the graphics waits are 788 synchronized across all processors that share the Draw object 789 */ 790 ierr = ViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 791 if (!rank) { 792 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 793 } 794 ierr = ViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 795 ierr = MatDestroy(A);CHKERRQ(ierr); 796 } 797 PetscFunctionReturn(0); 798 } 799 800 #undef __FUNC__ 801 #define __FUNC__ /*<a name=""></a>*/"MatView_MPISBAIJ" 802 int MatView_MPISBAIJ(Mat mat,Viewer viewer) 803 { 804 int ierr; 805 PetscTruth isascii,isdraw,issocket,isbinary; 806 807 PetscFunctionBegin; 808 ierr = PetscTypeCompare((PetscObject)viewer,ASCII_VIEWER,&isascii);CHKERRQ(ierr); 809 ierr = PetscTypeCompare((PetscObject)viewer,DRAW_VIEWER,&isdraw);CHKERRQ(ierr); 810 ierr = PetscTypeCompare((PetscObject)viewer,SOCKET_VIEWER,&issocket);CHKERRQ(ierr); 811 ierr = PetscTypeCompare((PetscObject)viewer,BINARY_VIEWER,&isbinary);CHKERRQ(ierr); 812 if (isascii || isdraw || issocket || isbinary) { 813 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 814 } else { 815 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 816 } 817 PetscFunctionReturn(0); 818 } 819 820 #undef __FUNC__ 821 #define __FUNC__ /*<a name=""></a>*/"MatDestroy_MPISBAIJ" 822 int MatDestroy_MPISBAIJ(Mat mat) 823 { 824 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 825 int ierr; 826 827 PetscFunctionBegin; 828 #if defined(PETSC_USE_LOG) 829 PLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 830 #endif 831 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 832 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 833 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 834 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 835 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 836 #if defined (PETSC_USE_CTABLE) 837 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 838 #else 839 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 840 #endif 841 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 842 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 843 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 844 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 845 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 846 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 847 #if defined(PETSC_USE_MAT_SINGLE) 848 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 849 #endif 850 ierr = PetscFree(baij);CHKERRQ(ierr); 851 PetscFunctionReturn(0); 852 } 853 854 #undef __FUNC__ 855 #define __FUNC__ /*<a name=""></a>*/"MatMult_MPISBAIJ" 856 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 857 { 858 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 859 int ierr,nt; 860 861 PetscFunctionBegin; 862 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 863 if (nt != A->n) { 864 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 865 } 866 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 867 if (nt != A->m) { 868 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 869 } 870 871 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 872 /* do diagonal part */ 873 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 874 /* do supperdiagonal part */ 875 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 876 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 877 /* do subdiagonal part */ 878 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 879 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 880 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 881 882 PetscFunctionReturn(0); 883 } 884 885 #undef __FUNC__ 886 #define __FUNC__ /*<a name=""></a>*/"MatMultAdd_MPISBAIJ" 887 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 888 { 889 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 890 int ierr; 891 892 PetscFunctionBegin; 893 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 894 /* do diagonal part */ 895 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 896 /* do supperdiagonal part */ 897 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 898 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 899 900 /* do subdiagonal part */ 901 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 902 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 903 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 904 905 PetscFunctionReturn(0); 906 } 907 908 #undef __FUNC__ 909 #define __FUNC__ /*<a name=""></a>*/"MatMultTranspose_MPISBAIJ" 910 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 911 { 912 PetscFunctionBegin; 913 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 914 /* PetscFunctionReturn(0); */ 915 } 916 917 #undef __FUNC__ 918 #define __FUNC__ /*<a name=""></a>*/"MatMultTransposeAdd_MPISBAIJ" 919 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 920 { 921 PetscFunctionBegin; 922 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 923 /* PetscFunctionReturn(0); */ 924 } 925 926 /* 927 This only works correctly for square matrices where the subblock A->A is the 928 diagonal block 929 */ 930 #undef __FUNC__ 931 #define __FUNC__ /*<a name=""></a>*/"MatGetDiagonal_MPISBAIJ" 932 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 933 { 934 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 935 int ierr; 936 937 PetscFunctionBegin; 938 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 939 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 940 PetscFunctionReturn(0); 941 } 942 943 #undef __FUNC__ 944 #define __FUNC__ /*<a name=""></a>*/"MatScale_MPISBAIJ" 945 int MatScale_MPISBAIJ(Scalar *aa,Mat A) 946 { 947 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 948 int ierr; 949 950 PetscFunctionBegin; 951 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 952 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 953 PetscFunctionReturn(0); 954 } 955 956 #undef __FUNC__ 957 #define __FUNC__ /*<a name=""></a>*/"MatGetOwnershipRange_MPISBAIJ" 958 int MatGetOwnershipRange_MPISBAIJ(Mat matin,int *m,int *n) 959 { 960 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 961 962 PetscFunctionBegin; 963 if (m) *m = mat->rstart*mat->bs; 964 if (n) *n = mat->rend*mat->bs; 965 PetscFunctionReturn(0); 966 } 967 968 #undef __FUNC__ 969 #define __FUNC__ /*<a name=""></a>*/"MatGetRow_MPISBAIJ" 970 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 971 { 972 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 973 Scalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 974 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 975 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 976 int *cmap,*idx_p,cstart = mat->cstart; 977 978 PetscFunctionBegin; 979 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 980 mat->getrowactive = PETSC_TRUE; 981 982 if (!mat->rowvalues && (idx || v)) { 983 /* 984 allocate enough space to hold information from the longest row. 985 */ 986 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 987 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 988 int max = 1,mbs = mat->mbs,tmp; 989 for (i=0; i<mbs; i++) { 990 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 991 if (max < tmp) { max = tmp; } 992 } 993 mat->rowvalues = (Scalar*)PetscMalloc(max*bs2*(sizeof(int)+sizeof(Scalar)));CHKPTRQ(mat->rowvalues); 994 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 995 } 996 997 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 998 lrow = row - brstart; /* local row index */ 999 1000 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1001 if (!v) {pvA = 0; pvB = 0;} 1002 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1003 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1004 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1005 nztot = nzA + nzB; 1006 1007 cmap = mat->garray; 1008 if (v || idx) { 1009 if (nztot) { 1010 /* Sort by increasing column numbers, assuming A and B already sorted */ 1011 int imark = -1; 1012 if (v) { 1013 *v = v_p = mat->rowvalues; 1014 for (i=0; i<nzB; i++) { 1015 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1016 else break; 1017 } 1018 imark = i; 1019 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1020 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1021 } 1022 if (idx) { 1023 *idx = idx_p = mat->rowindices; 1024 if (imark > -1) { 1025 for (i=0; i<imark; i++) { 1026 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1027 } 1028 } else { 1029 for (i=0; i<nzB; i++) { 1030 if (cmap[cworkB[i]/bs] < cstart) 1031 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1032 else break; 1033 } 1034 imark = i; 1035 } 1036 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1037 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1038 } 1039 } else { 1040 if (idx) *idx = 0; 1041 if (v) *v = 0; 1042 } 1043 } 1044 *nz = nztot; 1045 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1046 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1047 PetscFunctionReturn(0); 1048 } 1049 1050 #undef __FUNC__ 1051 #define __FUNC__ /*<a name=""></a>*/"MatRestoreRow_MPISBAIJ" 1052 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1053 { 1054 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1055 1056 PetscFunctionBegin; 1057 if (baij->getrowactive == PETSC_FALSE) { 1058 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1059 } 1060 baij->getrowactive = PETSC_FALSE; 1061 PetscFunctionReturn(0); 1062 } 1063 1064 #undef __FUNC__ 1065 #define __FUNC__ /*<a name=""></a>*/"MatGetBlockSize_MPISBAIJ" 1066 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1067 { 1068 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1069 1070 PetscFunctionBegin; 1071 *bs = baij->bs; 1072 PetscFunctionReturn(0); 1073 } 1074 1075 #undef __FUNC__ 1076 #define __FUNC__ /*<a name=""></a>*/"MatZeroEntries_MPISBAIJ" 1077 int MatZeroEntries_MPISBAIJ(Mat A) 1078 { 1079 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1080 int ierr; 1081 1082 PetscFunctionBegin; 1083 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1084 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1085 PetscFunctionReturn(0); 1086 } 1087 1088 #undef __FUNC__ 1089 #define __FUNC__ /*<a name=""></a>*/"MatGetInfo_MPISBAIJ" 1090 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1091 { 1092 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1093 Mat A = a->A,B = a->B; 1094 int ierr; 1095 PetscReal isend[5],irecv[5]; 1096 1097 PetscFunctionBegin; 1098 info->block_size = (double)a->bs; 1099 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1100 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1101 isend[3] = info->memory; isend[4] = info->mallocs; 1102 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1103 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1104 isend[3] += info->memory; isend[4] += info->mallocs; 1105 if (flag == MAT_LOCAL) { 1106 info->nz_used = isend[0]; 1107 info->nz_allocated = isend[1]; 1108 info->nz_unneeded = isend[2]; 1109 info->memory = isend[3]; 1110 info->mallocs = isend[4]; 1111 } else if (flag == MAT_GLOBAL_MAX) { 1112 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1113 info->nz_used = irecv[0]; 1114 info->nz_allocated = irecv[1]; 1115 info->nz_unneeded = irecv[2]; 1116 info->memory = irecv[3]; 1117 info->mallocs = irecv[4]; 1118 } else if (flag == MAT_GLOBAL_SUM) { 1119 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1120 info->nz_used = irecv[0]; 1121 info->nz_allocated = irecv[1]; 1122 info->nz_unneeded = irecv[2]; 1123 info->memory = irecv[3]; 1124 info->mallocs = irecv[4]; 1125 } else { 1126 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1127 } 1128 info->rows_global = (double)A->M; 1129 info->columns_global = (double)A->N; 1130 info->rows_local = (double)A->m; 1131 info->columns_local = (double)A->N; 1132 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1133 info->fill_ratio_needed = 0; 1134 info->factor_mallocs = 0; 1135 PetscFunctionReturn(0); 1136 } 1137 1138 #undef __FUNC__ 1139 #define __FUNC__ /*<a name=""></a>*/"MatSetOption_MPISBAIJ" 1140 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1141 { 1142 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1143 int ierr; 1144 1145 PetscFunctionBegin; 1146 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1147 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1148 op == MAT_COLUMNS_UNSORTED || 1149 op == MAT_COLUMNS_SORTED || 1150 op == MAT_NEW_NONZERO_ALLOCATION_ERR || 1151 op == MAT_KEEP_ZEROED_ROWS || 1152 op == MAT_NEW_NONZERO_LOCATION_ERR) { 1153 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1154 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1155 } else if (op == MAT_ROW_ORIENTED) { 1156 a->roworiented = PETSC_TRUE; 1157 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1158 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1159 } else if (op == MAT_ROWS_SORTED || 1160 op == MAT_ROWS_UNSORTED || 1161 op == MAT_SYMMETRIC || 1162 op == MAT_STRUCTURALLY_SYMMETRIC || 1163 op == MAT_YES_NEW_DIAGONALS || 1164 op == MAT_USE_HASH_TABLE) { 1165 PLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1166 } else if (op == MAT_COLUMN_ORIENTED) { 1167 a->roworiented = PETSC_FALSE; 1168 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1169 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1170 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1171 a->donotstash = PETSC_TRUE; 1172 } else if (op == MAT_NO_NEW_DIAGONALS) { 1173 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1174 } else if (op == MAT_USE_HASH_TABLE) { 1175 a->ht_flag = PETSC_TRUE; 1176 } else { 1177 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1178 } 1179 PetscFunctionReturn(0); 1180 } 1181 1182 #undef __FUNC__ 1183 #define __FUNC__ /*<a name=""></a>*/"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 __FUNC__ 1192 #define __FUNC__ /*<a name=""></a>*/"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 __FUNC__ 1227 #define __FUNC__ /*<a name=""></a>*/"MatZeroRows_MPISBAIJ" 1228 int MatZeroRows_MPISBAIJ(Mat A,IS is,Scalar *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,found,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 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 nprocs = (int*)PetscMalloc(2*size*sizeof(int));CHKPTRQ(nprocs); 1247 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 1248 procs = nprocs + size; 1249 owner = (int*)PetscMalloc((N+1)*sizeof(int));CHKPTRQ(owner); /* see note*/ 1250 for (i=0; i<N; i++) { 1251 idx = rows[i]; 1252 found = 0; 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 = 1; 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 work = (int*)PetscMalloc(2*size*sizeof(int));CHKPTRQ(work); 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 rvalues = (int*)PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int));CHKPTRQ(rvalues); 1271 recv_waits = (MPI_Request*)PetscMalloc((nrecvs+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits); 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 svalues = (int*)PetscMalloc((N+1)*sizeof(int));CHKPTRQ(svalues); 1281 send_waits = (MPI_Request*)PetscMalloc((nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits); 1282 starts = (int*)PetscMalloc((size+1)*sizeof(int));CHKPTRQ(starts); 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 lens = (int*)PetscMalloc(2*(nrecvs+1)*sizeof(int));CHKPTRQ(lens); 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 lrows = (int*)PetscMalloc((slen+1)*sizeof(int));CHKPTRQ(lrows); 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 PLogObjectParent(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 send_status = (MPI_Status*)PetscMalloc(nsends*sizeof(MPI_Status));CHKPTRQ(send_status); 1369 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1370 ierr = PetscFree(send_status);CHKERRQ(ierr); 1371 } 1372 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1373 ierr = PetscFree(svalues);CHKERRQ(ierr); 1374 1375 PetscFunctionReturn(0); 1376 } 1377 1378 #undef __FUNC__ 1379 #define __FUNC__ /*<a name=""></a>*/"MatPrintHelp_MPISBAIJ" 1380 int MatPrintHelp_MPISBAIJ(Mat A) 1381 { 1382 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1383 MPI_Comm comm = A->comm; 1384 static int called = 0; 1385 int ierr; 1386 1387 PetscFunctionBegin; 1388 if (!a->rank) { 1389 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1390 } 1391 if (called) {PetscFunctionReturn(0);} else called = 1; 1392 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1393 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1394 PetscFunctionReturn(0); 1395 } 1396 1397 #undef __FUNC__ 1398 #define __FUNC__ /*<a name=""></a>*/"MatSetUnfactored_MPISBAIJ" 1399 int MatSetUnfactored_MPISBAIJ(Mat A) 1400 { 1401 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1402 int ierr; 1403 1404 PetscFunctionBegin; 1405 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1406 PetscFunctionReturn(0); 1407 } 1408 1409 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1410 1411 #undef __FUNC__ 1412 #define __FUNC__ /*<a name=""></a>*/"MatEqual_MPISBAIJ" 1413 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1414 { 1415 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1416 Mat a,b,c,d; 1417 PetscTruth flg; 1418 int ierr; 1419 1420 PetscFunctionBegin; 1421 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg);CHKERRQ(ierr); 1422 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1423 a = matA->A; b = matA->B; 1424 c = matB->A; d = matB->B; 1425 1426 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1427 if (flg == PETSC_TRUE) { 1428 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1429 } 1430 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1431 PetscFunctionReturn(0); 1432 } 1433 1434 #undef __FUNC__ 1435 #define __FUNC__ /*<a name="MatSetUpPreallocation_MPISBAIJ"></a>*/"MatSetUpPreallocation_MPISBAIJ" 1436 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1437 { 1438 int ierr; 1439 1440 PetscFunctionBegin; 1441 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1442 PetscFunctionReturn(0); 1443 } 1444 /* -------------------------------------------------------------------*/ 1445 static struct _MatOps MatOps_Values = { 1446 MatSetValues_MPISBAIJ, 1447 MatGetRow_MPISBAIJ, 1448 MatRestoreRow_MPISBAIJ, 1449 MatMult_MPISBAIJ, 1450 MatMultAdd_MPISBAIJ, 1451 MatMultTranspose_MPISBAIJ, 1452 MatMultTransposeAdd_MPISBAIJ, 1453 0, 1454 0, 1455 0, 1456 0, 1457 0, 1458 0, 1459 0, 1460 MatTranspose_MPISBAIJ, 1461 MatGetInfo_MPISBAIJ, 1462 MatEqual_MPISBAIJ, 1463 MatGetDiagonal_MPISBAIJ, 1464 MatDiagonalScale_MPISBAIJ, 1465 MatNorm_MPISBAIJ, 1466 MatAssemblyBegin_MPISBAIJ, 1467 MatAssemblyEnd_MPISBAIJ, 1468 0, 1469 MatSetOption_MPISBAIJ, 1470 MatZeroEntries_MPISBAIJ, 1471 MatZeroRows_MPISBAIJ, 1472 0, 1473 0, 1474 0, 1475 0, 1476 MatSetUpPreallocation_MPISBAIJ, 1477 0, 1478 MatGetOwnershipRange_MPISBAIJ, 1479 0, 1480 0, 1481 0, 1482 0, 1483 MatDuplicate_MPISBAIJ, 1484 0, 1485 0, 1486 0, 1487 0, 1488 0, 1489 MatGetSubMatrices_MPISBAIJ, 1490 MatIncreaseOverlap_MPISBAIJ, 1491 MatGetValues_MPISBAIJ, 1492 0, 1493 MatPrintHelp_MPISBAIJ, 1494 MatScale_MPISBAIJ, 1495 0, 1496 0, 1497 0, 1498 MatGetBlockSize_MPISBAIJ, 1499 0, 1500 0, 1501 0, 1502 0, 1503 0, 1504 0, 1505 MatSetUnfactored_MPISBAIJ, 1506 0, 1507 MatSetValuesBlocked_MPISBAIJ, 1508 0, 1509 0, 1510 0, 1511 MatGetMaps_Petsc, 1512 0, 1513 0, 1514 0, 1515 0, 1516 0, 1517 0, 1518 MatGetRowMax_MPISBAIJ}; 1519 1520 1521 EXTERN_C_BEGIN 1522 #undef __FUNC__ 1523 #define __FUNC__ /*<a name=""></a>*/"MatGetDiagonalBlock_MPISBAIJ" 1524 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1525 { 1526 PetscFunctionBegin; 1527 *a = ((Mat_MPISBAIJ *)A->data)->A; 1528 *iscopy = PETSC_FALSE; 1529 PetscFunctionReturn(0); 1530 } 1531 EXTERN_C_END 1532 1533 EXTERN_C_BEGIN 1534 #undef __FUNC__ 1535 #define __FUNC__ /*<a name=""></a>*/"MatCreate_MPISBAIJ" 1536 int MatCreate_MPISBAIJ(Mat B) 1537 { 1538 Mat_MPISBAIJ *b; 1539 int ierr; 1540 PetscTruth flg; 1541 1542 PetscFunctionBegin; 1543 1544 B->data = (void*)(b = PetscNew(Mat_MPISBAIJ));CHKPTRQ(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 b->rowners = (int*)PetscMalloc(3*(b->size+2)*sizeof(int));CHKPTRQ(b->rowners); 1560 b->cowners = b->rowners + b->size + 2; 1561 b->rowners_bs = b->cowners + b->size + 2; 1562 PLogObjectMemory(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(PEYSC_USE_MAT_SINGLE) 1572 /* stuff for MatSetValues_XXX in single precision */ 1573 b->lensetvalues = 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 = OptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1599 if (flg) { 1600 double fact = 1.39; 1601 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1602 ierr = OptionsGetDouble(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 PLogInfo(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 __FUNC__ 1621 #define __FUNC__ /*<a name=""></a>*/"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=PETSC_DECIDE; 1702 PetscTruth flg2; 1703 1704 PetscFunctionBegin; 1705 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1706 if (!flg2) PetscFunctionReturn(0); 1707 1708 ierr = OptionsGetInt(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 < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than -2: value %d",d_nz); 1712 if (o_nz < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than -2: value %d",o_nz); 1713 if (d_nnz) { 1714 for (i=0; i<B->m/bs; i++) { 1715 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %d value %d",i,d_nnz[i]); 1716 } 1717 } 1718 if (o_nnz) { 1719 for (i=0; i<B->m/bs; i++) { 1720 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %d value %d",i,o_nnz[i]); 1721 } 1722 } 1723 B->preallocated = PETSC_TRUE; 1724 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1725 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1726 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1727 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1728 1729 b = (Mat_MPISBAIJ*)B->data; 1730 mbs = B->m/bs; 1731 Mbs = B->M/bs; 1732 if (mbs*bs != B->m) { 1733 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1734 } 1735 1736 b->bs = bs; 1737 b->bs2 = bs*bs; 1738 b->mbs = mbs; 1739 b->nbs = mbs; 1740 b->Mbs = Mbs; 1741 b->Nbs = Mbs; 1742 1743 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1744 b->rowners[0] = 0; 1745 for (i=2; i<=b->size; i++) { 1746 b->rowners[i] += b->rowners[i-1]; 1747 } 1748 b->rstart = b->rowners[b->rank]; 1749 b->rend = b->rowners[b->rank+1]; 1750 b->cstart = b->rstart; 1751 b->cend = b->rend; 1752 for (i=0; i<=b->size; i++) { 1753 b->rowners_bs[i] = b->rowners[i]*bs; 1754 } 1755 b->rstart_bs = b-> rstart*bs; 1756 b->rend_bs = b->rend*bs; 1757 1758 b->cstart_bs = b->cstart*bs; 1759 b->cend_bs = b->cend*bs; 1760 1761 1762 if (d_nz == PETSC_DEFAULT) d_nz = 5; 1763 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1764 PLogObjectParent(B,b->A); 1765 if (o_nz == PETSC_DEFAULT) o_nz = 0; 1766 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1767 PLogObjectParent(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 __FUNC__ 1776 #define __FUNC__ /*<a name=""></a>*/"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 __FUNC__ 1887 #define __FUNC__ /*<a name=""></a>*/"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 a->rowners = (int*)PetscMalloc(3*(a->size+2)*sizeof(int));CHKPTRQ(a->rowners); 1934 PLogObjectMemory(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 a->colmap = (int*)PetscMalloc((a->Nbs)*sizeof(int));CHKPTRQ(a->colmap); 1945 PLogObjectMemory(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 a->garray = (int*)PetscMalloc(len*sizeof(int));CHKPTRQ(a->garray); 1951 PLogObjectMemory(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 PLogObjectParent(mat,a->lvec); 1957 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1958 1959 PLogObjectParent(mat,a->Mvctx); 1960 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1961 PLogObjectParent(mat,a->A); 1962 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1963 PLogObjectParent(mat,a->B); 1964 ierr = FListDuplicate(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 __FUNC__ 1973 #define __FUNC__ /*<a name=""></a>*/"MatLoad_MPISBAIJ" 1974 int MatLoad_MPISBAIJ(Viewer viewer,MatType type,Mat *newmat) 1975 { 1976 Mat A; 1977 int i,nz,ierr,j,rstart,rend,fd; 1978 Scalar *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 = OptionsGetInt(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 = ViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1994 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1995 if (header[0] != MAT_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 PLogInfo(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 rowners = (int*)PetscMalloc(2*(size+2)*sizeof(int));CHKPTRQ(rowners); 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 locrowlens = (int*)PetscMalloc((rend-rstart)*bs*sizeof(int));CHKPTRQ(locrowlens); 2032 if (!rank) { 2033 rowlengths = (int*)PetscMalloc((M+extra_rows)*sizeof(int));CHKPTRQ(rowlengths); 2034 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2035 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2036 sndcounts = (int*)PetscMalloc(size*sizeof(int));CHKPTRQ(sndcounts); 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 procsnz = (int*)PetscMalloc(size*sizeof(int));CHKPTRQ(procsnz); 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 cols = (int*)PetscMalloc(maxnz*sizeof(int));CHKPTRQ(cols); 2061 2062 /* read in my part of the matrix column indices */ 2063 nz = procsnz[0]; 2064 ibuf = (int*)PetscMalloc(nz*sizeof(int));CHKPTRQ(ibuf); 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 ibuf = (int*)PetscMalloc(nz*sizeof(int));CHKPTRQ(ibuf); 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 dlens = (int*)PetscMalloc(2*(rend-rstart+1)*sizeof(int));CHKPTRQ(dlens); 2100 odlens = dlens + (rend-rstart); 2101 mask = (int*)PetscMalloc(3*Mbs*sizeof(int));CHKPTRQ(mask); 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 buf = (Scalar*)PetscMalloc(maxnz*sizeof(Scalar));CHKPTRQ(buf); 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 buf = (Scalar*)PetscMalloc(nz*sizeof(Scalar));CHKPTRQ(buf); 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 __FUNC__ 2206 #define __FUNC__ /*<a name=""></a>*/"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 __FUNC__ 2233 #define __FUNC__ /*<a name=""></a>*/"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 double *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 Scalar *ba,*va; 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);CHKERRA(ierr); 2250 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRA(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 work = (PetscReal*)PetscMalloc(bs*Mbs*sizeof(PetscReal));CHKPTRQ(work); 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,MPI_DOUBLE,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,MPI_DOUBLE,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);CHKERRA(ierr); 2334 PetscFunctionReturn(0); 2335 } 2336