1 /*$Id: mpisbaij.c,v 1.31 2000/10/18 01:31:01 bsmith Exp bsmith $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "src/vec/vecimpl.h" 5 #include "mpisbaij.h" 6 #include "src/mat/impls/sbaij/seq/sbaij.h" 7 8 extern int MatSetUpMultiply_MPISBAIJ(Mat); 9 extern int DisAssemble_MPISBAIJ(Mat); 10 extern int MatIncreaseOverlap_MPISBAIJ(Mat,int,IS *,int); 11 extern int MatGetSubMatrices_MPISBAIJ(Mat,int,IS *,IS *,MatReuse,Mat **); 12 extern int MatGetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *); 13 extern int MatSetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *,InsertMode); 14 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 15 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 16 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 17 extern int MatPrintHelp_SeqSBAIJ(Mat); 18 extern int MatZeroRows_SeqSBAIJ(Mat,IS,Scalar*); 19 extern int MatZeroRows_SeqBAIJ(Mat,IS,Scalar *); 20 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 21 22 /* UGLY, ugly, ugly 23 When MatScalar == Scalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 24 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 25 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 26 converts the entries into single precision and then calls ..._MatScalar() to put them 27 into the single precision data structures. 28 */ 29 #if defined(PETSC_USE_MAT_SINGLE) 30 extern int MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 31 extern int MatSetValues_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 32 extern int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 33 extern int MatSetValues_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 34 extern int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 35 #else 36 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 37 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 38 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 39 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 40 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 41 #endif 42 43 EXTERN_C_BEGIN 44 #undef __FUNC__ 45 #define __FUNC__ /*<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 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1544 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1545 if (B->M != B->N || B->m != B->n){ /* N and n are not used after this */ 1546 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, set M=N and m=n"); 1547 } 1548 1549 B->data = (void*)(b = PetscNew(Mat_MPISBAIJ));CHKPTRQ(b); 1550 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1551 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1552 1553 B->ops->destroy = MatDestroy_MPISBAIJ; 1554 B->ops->view = MatView_MPISBAIJ; 1555 B->mapping = 0; 1556 B->factor = 0; 1557 B->assembled = PETSC_FALSE; 1558 1559 B->insertmode = NOT_SET_VALUES; 1560 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1561 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1562 1563 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1564 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1565 1566 /* the information in the maps duplicates the information computed below, eventually 1567 we should remove the duplicate information that is not contained in the maps */ 1568 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1569 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1570 1571 /* build local table of row and column ownerships */ 1572 b->rowners = (int*)PetscMalloc(3*(b->size+2)*sizeof(int));CHKPTRQ(b->rowners); 1573 b->cowners = b->rowners + b->size + 2; 1574 b->rowners_bs = b->cowners + b->size + 2; 1575 PLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1576 1577 /* build cache for off array entries formed */ 1578 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1579 b->donotstash = PETSC_FALSE; 1580 b->colmap = PETSC_NULL; 1581 b->garray = PETSC_NULL; 1582 b->roworiented = PETSC_TRUE; 1583 1584 #if defined(PEYSC_USE_MAT_SINGLE) 1585 /* stuff for MatSetValues_XXX in single precision */ 1586 b->lensetvalues = 0; 1587 b->setvaluescopy = PETSC_NULL; 1588 #endif 1589 1590 /* stuff used in block assembly */ 1591 b->barray = 0; 1592 1593 /* stuff used for matrix vector multiply */ 1594 b->lvec = 0; 1595 b->Mvctx = 0; 1596 1597 /* stuff for MatGetRow() */ 1598 b->rowindices = 0; 1599 b->rowvalues = 0; 1600 b->getrowactive = PETSC_FALSE; 1601 1602 /* hash table stuff */ 1603 b->ht = 0; 1604 b->hd = 0; 1605 b->ht_size = 0; 1606 b->ht_flag = PETSC_FALSE; 1607 b->ht_fact = 0; 1608 b->ht_total_ct = 0; 1609 b->ht_insert_ct = 0; 1610 1611 ierr = OptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1612 if (flg) { 1613 double fact = 1.39; 1614 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1615 ierr = OptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1616 if (fact <= 1.0) fact = 1.39; 1617 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1618 PLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1619 } 1620 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1621 "MatStoreValues_MPISBAIJ", 1622 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1623 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1624 "MatRetrieveValues_MPISBAIJ", 1625 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1626 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1627 "MatGetDiagonalBlock_MPISBAIJ", 1628 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1629 PetscFunctionReturn(0); 1630 } 1631 EXTERN_C_END 1632 1633 #undef __FUNC__ 1634 #define __FUNC__ /*<a name=""></a>*/"MatMPISBAIJSetPreallocation" 1635 /*@C 1636 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1637 the user should preallocate the matrix storage by setting the parameters 1638 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1639 performance can be increased by more than a factor of 50. 1640 1641 Collective on Mat 1642 1643 Input Parameters: 1644 + A - the matrix 1645 . bs - size of blockk 1646 . d_nz - number of block nonzeros per block row in diagonal portion of local 1647 submatrix (same for all local rows) 1648 . d_nnz - array containing the number of block nonzeros in the various block rows 1649 of the in diagonal portion of the local (possibly different for each block 1650 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1651 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1652 submatrix (same for all local rows). 1653 - o_nnz - array containing the number of nonzeros in the various block rows of the 1654 off-diagonal portion of the local submatrix (possibly different for 1655 each block row) or PETSC_NULL. 1656 1657 1658 Options Database Keys: 1659 . -mat_no_unroll - uses code that does not unroll the loops in the 1660 block calculations (much slower) 1661 . -mat_block_size - size of the blocks to use 1662 1663 Notes: 1664 1665 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1666 than it must be used on all processors that share the object for that argument. 1667 1668 Storage Information: 1669 For a square global matrix we define each processor's diagonal portion 1670 to be its local rows and the corresponding columns (a square submatrix); 1671 each processor's off-diagonal portion encompasses the remainder of the 1672 local matrix (a rectangular submatrix). 1673 1674 The user can specify preallocated storage for the diagonal part of 1675 the local submatrix with either d_nz or d_nnz (not both). Set 1676 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1677 memory allocation. Likewise, specify preallocated storage for the 1678 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1679 1680 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1681 the figure below we depict these three local rows and all columns (0-11). 1682 1683 .vb 1684 0 1 2 3 4 5 6 7 8 9 10 11 1685 ------------------- 1686 row 3 | o o o d d d o o o o o o 1687 row 4 | o o o d d d o o o o o o 1688 row 5 | o o o d d d o o o o o o 1689 ------------------- 1690 .ve 1691 1692 Thus, any entries in the d locations are stored in the d (diagonal) 1693 submatrix, and any entries in the o locations are stored in the 1694 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1695 stored simply in the MATSEQBAIJ format for compressed row storage. 1696 1697 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1698 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1699 In general, for PDE problems in which most nonzeros are near the diagonal, 1700 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1701 or you will get TERRIBLE performance; see the users' manual chapter on 1702 matrices. 1703 1704 Level: intermediate 1705 1706 .keywords: matrix, block, aij, compressed row, sparse, parallel 1707 1708 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1709 @*/ 1710 1711 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1712 { 1713 Mat_MPISBAIJ *b; 1714 int ierr,i,mbs,Mbs=PETSC_DECIDE; 1715 PetscTruth flg2; 1716 1717 PetscFunctionBegin; 1718 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1719 if (!flg2) PetscFunctionReturn(0); 1720 1721 ierr = OptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1722 1723 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1724 if (d_nz < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than -2: value %d",d_nz); 1725 if (o_nz < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than -2: value %d",o_nz); 1726 if (d_nnz) { 1727 for (i=0; i<B->m/bs; i++) { 1728 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]); 1729 } 1730 } 1731 if (o_nnz) { 1732 for (i=0; i<B->m/bs; i++) { 1733 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]); 1734 } 1735 } 1736 1737 b = (Mat_MPISBAIJ*)B->data; 1738 mbs = B->m/bs; 1739 Mbs = B->M/bs; 1740 if (mbs*bs != B->m) { 1741 SETERRQ(PETSC_ERR_ARG_SIZ,"No of local rows/cols must be divisible by blocksize"); 1742 } 1743 1744 b->bs = bs; 1745 b->bs2 = bs*bs; 1746 b->mbs = mbs; 1747 b->nbs = mbs; 1748 b->Mbs = Mbs; 1749 b->Nbs = Mbs; 1750 1751 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1752 b->rowners[0] = 0; 1753 for (i=2; i<=b->size; i++) { 1754 b->rowners[i] += b->rowners[i-1]; 1755 } 1756 b->rstart = b->rowners[b->rank]; 1757 b->rend = b->rowners[b->rank+1]; 1758 b->cstart = b->rstart; 1759 b->cend = b->rend; 1760 for (i=0; i<=b->size; i++) { 1761 b->rowners_bs[i] = b->rowners[i]*bs; 1762 } 1763 b->rstart_bs = b-> rstart*bs; 1764 b->rend_bs = b->rend*bs; 1765 1766 b->cstart_bs = b->cstart*bs; 1767 b->cend_bs = b->cend*bs; 1768 1769 1770 if (d_nz == PETSC_DEFAULT) d_nz = 5; 1771 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1772 PLogObjectParent(B,b->A); 1773 if (o_nz == PETSC_DEFAULT) o_nz = 0; 1774 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1775 PLogObjectParent(B,b->B); 1776 1777 /* build cache for off array entries formed */ 1778 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1779 1780 PetscFunctionReturn(0); 1781 } 1782 1783 #undef __FUNC__ 1784 #define __FUNC__ /*<a name=""></a>*/"MatCreateMPISBAIJ" 1785 /*@C 1786 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1787 (block compressed row). For good matrix assembly performance 1788 the user should preallocate the matrix storage by setting the parameters 1789 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1790 performance can be increased by more than a factor of 50. 1791 1792 Collective on MPI_Comm 1793 1794 Input Parameters: 1795 + comm - MPI communicator 1796 . bs - size of blockk 1797 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1798 This value should be the same as the local size used in creating the 1799 y vector for the matrix-vector product y = Ax. 1800 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1801 This value should be the same as the local size used in creating the 1802 x vector for the matrix-vector product y = Ax. 1803 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1804 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1805 . d_nz - number of block nonzeros per block row in diagonal portion of local 1806 submatrix (same for all local rows) 1807 . d_nnz - array containing the number of block nonzeros in the various block rows 1808 of the in diagonal portion of the local (possibly different for each block 1809 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1810 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1811 submatrix (same for all local rows). 1812 - o_nnz - array containing the number of nonzeros in the various block rows of the 1813 off-diagonal portion of the local submatrix (possibly different for 1814 each block row) or PETSC_NULL. 1815 1816 Output Parameter: 1817 . A - the matrix 1818 1819 Options Database Keys: 1820 . -mat_no_unroll - uses code that does not unroll the loops in the 1821 block calculations (much slower) 1822 . -mat_block_size - size of the blocks to use 1823 . -mat_mpi - use the parallel matrix data structures even on one processor 1824 (defaults to using SeqBAIJ format on one processor) 1825 1826 Notes: 1827 The user MUST specify either the local or global matrix dimensions 1828 (possibly both). 1829 1830 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1831 than it must be used on all processors that share the object for that argument. 1832 1833 Storage Information: 1834 For a square global matrix we define each processor's diagonal portion 1835 to be its local rows and the corresponding columns (a square submatrix); 1836 each processor's off-diagonal portion encompasses the remainder of the 1837 local matrix (a rectangular submatrix). 1838 1839 The user can specify preallocated storage for the diagonal part of 1840 the local submatrix with either d_nz or d_nnz (not both). Set 1841 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1842 memory allocation. Likewise, specify preallocated storage for the 1843 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1844 1845 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1846 the figure below we depict these three local rows and all columns (0-11). 1847 1848 .vb 1849 0 1 2 3 4 5 6 7 8 9 10 11 1850 ------------------- 1851 row 3 | o o o d d d o o o o o o 1852 row 4 | o o o d d d o o o o o o 1853 row 5 | o o o d d d o o o o o o 1854 ------------------- 1855 .ve 1856 1857 Thus, any entries in the d locations are stored in the d (diagonal) 1858 submatrix, and any entries in the o locations are stored in the 1859 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1860 stored simply in the MATSEQBAIJ format for compressed row storage. 1861 1862 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1863 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1864 In general, for PDE problems in which most nonzeros are near the diagonal, 1865 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1866 or you will get TERRIBLE performance; see the users' manual chapter on 1867 matrices. 1868 1869 Level: intermediate 1870 1871 .keywords: matrix, block, aij, compressed row, sparse, parallel 1872 1873 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1874 @*/ 1875 1876 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) 1877 { 1878 int ierr,size; 1879 1880 PetscFunctionBegin; 1881 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1882 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1883 if (size > 1) { 1884 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1885 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1886 } else { 1887 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1888 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1889 } 1890 PetscFunctionReturn(0); 1891 } 1892 1893 1894 #undef __FUNC__ 1895 #define __FUNC__ /*<a name=""></a>*/"MatDuplicate_MPISBAIJ" 1896 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1897 { 1898 Mat mat; 1899 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1900 int ierr,len=0; 1901 1902 PetscFunctionBegin; 1903 *newmat = 0; 1904 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1905 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1906 mat->preallocated = PETSC_TRUE; 1907 a = (Mat_MPISBAIJ*)mat->data; 1908 a->bs = oldmat->bs; 1909 a->bs2 = oldmat->bs2; 1910 a->mbs = oldmat->mbs; 1911 a->nbs = oldmat->nbs; 1912 a->Mbs = oldmat->Mbs; 1913 a->Nbs = oldmat->Nbs; 1914 1915 a->rstart = oldmat->rstart; 1916 a->rend = oldmat->rend; 1917 a->cstart = oldmat->cstart; 1918 a->cend = oldmat->cend; 1919 a->size = oldmat->size; 1920 a->rank = oldmat->rank; 1921 a->donotstash = oldmat->donotstash; 1922 a->roworiented = oldmat->roworiented; 1923 a->rowindices = 0; 1924 a->rowvalues = 0; 1925 a->getrowactive = PETSC_FALSE; 1926 a->barray = 0; 1927 a->rstart_bs = oldmat->rstart_bs; 1928 a->rend_bs = oldmat->rend_bs; 1929 a->cstart_bs = oldmat->cstart_bs; 1930 a->cend_bs = oldmat->cend_bs; 1931 1932 /* hash table stuff */ 1933 a->ht = 0; 1934 a->hd = 0; 1935 a->ht_size = 0; 1936 a->ht_flag = oldmat->ht_flag; 1937 a->ht_fact = oldmat->ht_fact; 1938 a->ht_total_ct = 0; 1939 a->ht_insert_ct = 0; 1940 1941 a->rowners = (int*)PetscMalloc(3*(a->size+2)*sizeof(int));CHKPTRQ(a->rowners); 1942 PLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1943 a->cowners = a->rowners + a->size + 2; 1944 a->rowners_bs = a->cowners + a->size + 2; 1945 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1946 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1947 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1948 if (oldmat->colmap) { 1949 #if defined (PETSC_USE_CTABLE) 1950 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1951 #else 1952 a->colmap = (int*)PetscMalloc((a->Nbs)*sizeof(int));CHKPTRQ(a->colmap); 1953 PLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1954 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1955 #endif 1956 } else a->colmap = 0; 1957 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1958 a->garray = (int*)PetscMalloc(len*sizeof(int));CHKPTRQ(a->garray); 1959 PLogObjectMemory(mat,len*sizeof(int)); 1960 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 1961 } else a->garray = 0; 1962 1963 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1964 PLogObjectParent(mat,a->lvec); 1965 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1966 1967 PLogObjectParent(mat,a->Mvctx); 1968 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1969 PLogObjectParent(mat,a->A); 1970 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1971 PLogObjectParent(mat,a->B); 1972 ierr = FListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1973 *newmat = mat; 1974 PetscFunctionReturn(0); 1975 } 1976 1977 #include "petscsys.h" 1978 1979 EXTERN_C_BEGIN 1980 #undef __FUNC__ 1981 #define __FUNC__ /*<a name=""></a>*/"MatLoad_MPISBAIJ" 1982 int MatLoad_MPISBAIJ(Viewer viewer,MatType type,Mat *newmat) 1983 { 1984 Mat A; 1985 int i,nz,ierr,j,rstart,rend,fd; 1986 Scalar *vals,*buf; 1987 MPI_Comm comm = ((PetscObject)viewer)->comm; 1988 MPI_Status status; 1989 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 1990 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 1991 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 1992 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 1993 int dcount,kmax,k,nzcount,tmp; 1994 1995 PetscFunctionBegin; 1996 ierr = OptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1997 1998 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1999 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2000 if (!rank) { 2001 ierr = ViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2002 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2003 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2004 if (header[3] < 0) { 2005 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2006 } 2007 } 2008 2009 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2010 M = header[1]; N = header[2]; 2011 2012 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2013 2014 /* 2015 This code adds extra rows to make sure the number of rows is 2016 divisible by the blocksize 2017 */ 2018 Mbs = M/bs; 2019 extra_rows = bs - M + bs*(Mbs); 2020 if (extra_rows == bs) extra_rows = 0; 2021 else Mbs++; 2022 if (extra_rows &&!rank) { 2023 PLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2024 } 2025 2026 /* determine ownership of all rows */ 2027 mbs = Mbs/size + ((Mbs % size) > rank); 2028 m = mbs*bs; 2029 rowners = (int*)PetscMalloc(2*(size+2)*sizeof(int));CHKPTRQ(rowners); 2030 browners = rowners + size + 1; 2031 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2032 rowners[0] = 0; 2033 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2034 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2035 rstart = rowners[rank]; 2036 rend = rowners[rank+1]; 2037 2038 /* distribute row lengths to all processors */ 2039 locrowlens = (int*)PetscMalloc((rend-rstart)*bs*sizeof(int));CHKPTRQ(locrowlens); 2040 if (!rank) { 2041 rowlengths = (int*)PetscMalloc((M+extra_rows)*sizeof(int));CHKPTRQ(rowlengths); 2042 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2043 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2044 sndcounts = (int*)PetscMalloc(size*sizeof(int));CHKPTRQ(sndcounts); 2045 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2046 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2047 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2048 } else { 2049 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2050 } 2051 2052 if (!rank) { /* procs[0] */ 2053 /* calculate the number of nonzeros on each processor */ 2054 procsnz = (int*)PetscMalloc(size*sizeof(int));CHKPTRQ(procsnz); 2055 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2056 for (i=0; i<size; i++) { 2057 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2058 procsnz[i] += rowlengths[j]; 2059 } 2060 } 2061 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2062 2063 /* determine max buffer needed and allocate it */ 2064 maxnz = 0; 2065 for (i=0; i<size; i++) { 2066 maxnz = PetscMax(maxnz,procsnz[i]); 2067 } 2068 cols = (int*)PetscMalloc(maxnz*sizeof(int));CHKPTRQ(cols); 2069 2070 /* read in my part of the matrix column indices */ 2071 nz = procsnz[0]; 2072 ibuf = (int*)PetscMalloc(nz*sizeof(int));CHKPTRQ(ibuf); 2073 mycols = ibuf; 2074 if (size == 1) nz -= extra_rows; 2075 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2076 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2077 2078 /* read in every ones (except the last) and ship off */ 2079 for (i=1; i<size-1; i++) { 2080 nz = procsnz[i]; 2081 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2082 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2083 } 2084 /* read in the stuff for the last proc */ 2085 if (size != 1) { 2086 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2087 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2088 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2089 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2090 } 2091 ierr = PetscFree(cols);CHKERRQ(ierr); 2092 } else { /* procs[i], i>0 */ 2093 /* determine buffer space needed for message */ 2094 nz = 0; 2095 for (i=0; i<m; i++) { 2096 nz += locrowlens[i]; 2097 } 2098 ibuf = (int*)PetscMalloc(nz*sizeof(int));CHKPTRQ(ibuf); 2099 mycols = ibuf; 2100 /* receive message of column indices*/ 2101 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2102 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2103 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2104 } 2105 2106 /* loop over local rows, determining number of off diagonal entries */ 2107 dlens = (int*)PetscMalloc(2*(rend-rstart+1)*sizeof(int));CHKPTRQ(dlens); 2108 odlens = dlens + (rend-rstart); 2109 mask = (int*)PetscMalloc(3*Mbs*sizeof(int));CHKPTRQ(mask); 2110 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2111 masked1 = mask + Mbs; 2112 masked2 = masked1 + Mbs; 2113 rowcount = 0; nzcount = 0; 2114 for (i=0; i<mbs; i++) { 2115 dcount = 0; 2116 odcount = 0; 2117 for (j=0; j<bs; j++) { 2118 kmax = locrowlens[rowcount]; 2119 for (k=0; k<kmax; k++) { 2120 tmp = mycols[nzcount++]/bs; /* block col. index */ 2121 if (!mask[tmp]) { 2122 mask[tmp] = 1; 2123 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2124 else masked1[dcount++] = tmp; /* entry in diag portion */ 2125 } 2126 } 2127 rowcount++; 2128 } 2129 2130 dlens[i] = dcount; /* d_nzz[i] */ 2131 odlens[i] = odcount; /* o_nzz[i] */ 2132 2133 /* zero out the mask elements we set */ 2134 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2135 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2136 } 2137 2138 /* create our matrix */ 2139 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2140 CHKERRQ(ierr); 2141 A = *newmat; 2142 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2143 2144 if (!rank) { 2145 buf = (Scalar*)PetscMalloc(maxnz*sizeof(Scalar));CHKPTRQ(buf); 2146 /* read in my part of the matrix numerical values */ 2147 nz = procsnz[0]; 2148 vals = buf; 2149 mycols = ibuf; 2150 if (size == 1) nz -= extra_rows; 2151 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2152 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2153 2154 /* insert into matrix */ 2155 jj = rstart*bs; 2156 for (i=0; i<m; i++) { 2157 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2158 mycols += locrowlens[i]; 2159 vals += locrowlens[i]; 2160 jj++; 2161 } 2162 2163 /* read in other processors (except the last one) and ship out */ 2164 for (i=1; i<size-1; i++) { 2165 nz = procsnz[i]; 2166 vals = buf; 2167 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2168 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2169 } 2170 /* the last proc */ 2171 if (size != 1){ 2172 nz = procsnz[i] - extra_rows; 2173 vals = buf; 2174 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2175 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2176 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2177 } 2178 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2179 2180 } else { 2181 /* receive numeric values */ 2182 buf = (Scalar*)PetscMalloc(nz*sizeof(Scalar));CHKPTRQ(buf); 2183 2184 /* receive message of values*/ 2185 vals = buf; 2186 mycols = ibuf; 2187 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2188 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2189 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2190 2191 /* insert into matrix */ 2192 jj = rstart*bs; 2193 for (i=0; i<m; i++) { 2194 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2195 mycols += locrowlens[i]; 2196 vals += locrowlens[i]; 2197 jj++; 2198 } 2199 } 2200 2201 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2202 ierr = PetscFree(buf);CHKERRQ(ierr); 2203 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2204 ierr = PetscFree(rowners);CHKERRQ(ierr); 2205 ierr = PetscFree(dlens);CHKERRQ(ierr); 2206 ierr = PetscFree(mask);CHKERRQ(ierr); 2207 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2208 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 EXTERN_C_END 2212 2213 #undef __FUNC__ 2214 #define __FUNC__ /*<a name=""></a>*/"MatMPISBAIJSetHashTableFactor" 2215 /*@ 2216 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2217 2218 Input Parameters: 2219 . mat - the matrix 2220 . fact - factor 2221 2222 Collective on Mat 2223 2224 Level: advanced 2225 2226 Notes: 2227 This can also be set by the command line option: -mat_use_hash_table fact 2228 2229 .keywords: matrix, hashtable, factor, HT 2230 2231 .seealso: MatSetOption() 2232 @*/ 2233 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2234 { 2235 PetscFunctionBegin; 2236 SETERRQ(1,"Function not yet written for SBAIJ format"); 2237 /* PetscFunctionReturn(0); */ 2238 } 2239 2240 #undef __FUNC__ 2241 #define __FUNC__ /*<a name=""></a>*/"MatGetRowMax_MPISBAIJ" 2242 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2243 { 2244 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2245 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2246 PetscReal atmp; 2247 double *work,*svalues,*rvalues; 2248 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2249 int rank,size,*rowners_bs,dest,count,source; 2250 Scalar *ba,*va; 2251 MPI_Status stat; 2252 2253 PetscFunctionBegin; 2254 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2255 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2256 2257 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRA(ierr); 2258 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRA(ierr); 2259 2260 bs = a->bs; 2261 mbs = a->mbs; 2262 Mbs = a->Mbs; 2263 ba = b->a; 2264 bi = b->i; 2265 bj = b->j; 2266 /* 2267 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2268 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2269 */ 2270 2271 /* find ownerships */ 2272 rowners_bs = a->rowners_bs; 2273 /* 2274 for (i=0; i<size+1; i++) { 2275 PetscPrintf(PETSC_COMM_SELF,"rowners_bs: %d\n",i,rowners_bs[i]); 2276 } 2277 */ 2278 2279 /* each proc creates an array to be distributed */ 2280 work = (PetscReal*)PetscMalloc(bs*Mbs*sizeof(PetscReal));CHKPTRQ(work); 2281 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2282 2283 /* row_max for B */ 2284 for (i=0; i<mbs; i++) { 2285 ncols = bi[1] - bi[0]; bi++; 2286 brow = bs*i; 2287 for (j=0; j<ncols; j++){ 2288 bcol = bs*(*bj); 2289 for (kcol=0; kcol<bs; kcol++){ 2290 col = bcol + kcol; /* local col index */ 2291 col += rowners_bs[rank] + bs; /* global col index */ 2292 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2293 for (krow=0; krow<bs; krow++){ 2294 atmp = PetscAbsScalar(*ba); ba++; 2295 row = brow + krow; /* local row index */ 2296 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2297 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2298 if (work[col] < atmp) work[col] = atmp; 2299 } 2300 } 2301 bj++; 2302 } 2303 } 2304 2305 /* send values to its owners */ 2306 if (rank != size-1){ 2307 for (dest=rank+1; dest<size; dest++){ 2308 svalues = work + rowners_bs[dest]; 2309 count = rowners_bs[dest+1]-rowners_bs[dest]; 2310 ierr = MPI_Send(svalues,count,MPI_DOUBLE,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2311 /* 2312 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] sends %d values to [%d]\n",rank,count,dest); 2313 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2314 */ 2315 } 2316 } 2317 2318 /* receive values */ 2319 if (rank){ 2320 rvalues = work; 2321 count = rowners_bs[rank+1]-rowners_bs[rank]; 2322 for (source=0; source<rank; source++){ 2323 ierr = MPI_Recv(rvalues,count,MPI_DOUBLE_PRECISION,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2324 /* process values */ 2325 for (i=0; i<count; i++){ 2326 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2327 } 2328 /* 2329 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] received from [%d] \n",rank,stat.MPI_SOURCE); 2330 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2331 */ 2332 } 2333 } 2334 2335 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2336 ierr = PetscFree(work);CHKERRA(ierr); 2337 PetscFunctionReturn(0); 2338 } 2339