1 /*$Id: mpibaij.c,v 1.223 2001/06/21 22:08:18 buschelm Exp buschelm $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "src/vec/vecimpl.h" 5 6 EXTERN int MatSetUpMultiply_MPIBAIJ(Mat); 7 EXTERN int DisAssemble_MPIBAIJ(Mat); 8 EXTERN int MatIncreaseOverlap_MPIBAIJ(Mat,int,IS *,int); 9 EXTERN int MatGetSubMatrices_MPIBAIJ(Mat,int,IS *,IS *,MatReuse,Mat **); 10 EXTERN int MatGetValues_SeqBAIJ(Mat,int,int *,int,int *,Scalar *); 11 EXTERN int MatSetValues_SeqBAIJ(Mat,int,int *,int,int *,Scalar *,InsertMode); 12 EXTERN int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 13 EXTERN int MatGetRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 14 EXTERN int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 15 EXTERN int MatPrintHelp_SeqBAIJ(Mat); 16 EXTERN int MatZeroRows_SeqBAIJ(Mat,IS,Scalar*); 17 18 /* UGLY, ugly, ugly 19 When MatScalar == Scalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 20 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 21 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 22 converts the entries into single precision and then calls ..._MatScalar() to put them 23 into the single precision data structures. 24 */ 25 #if defined(PETSC_USE_MAT_SINGLE) 26 EXTERN int MatSetValuesBlocked_SeqBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 27 EXTERN int MatSetValues_MPIBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 28 EXTERN int MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 29 EXTERN int MatSetValues_MPIBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 30 EXTERN int MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 31 #else 32 #define MatSetValuesBlocked_SeqBAIJ_MatScalar MatSetValuesBlocked_SeqBAIJ 33 #define MatSetValues_MPIBAIJ_MatScalar MatSetValues_MPIBAIJ 34 #define MatSetValuesBlocked_MPIBAIJ_MatScalar MatSetValuesBlocked_MPIBAIJ 35 #define MatSetValues_MPIBAIJ_HT_MatScalar MatSetValues_MPIBAIJ_HT 36 #define MatSetValuesBlocked_MPIBAIJ_HT_MatScalar MatSetValuesBlocked_MPIBAIJ_HT 37 #endif 38 39 #undef __FUNCT__ 40 #define __FUNCT__ "MatGetRowMax_MPIBAIJ" 41 int MatGetRowMax_MPIBAIJ(Mat A,Vec v) 42 { 43 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 44 int ierr,i; 45 Scalar *va,*vb; 46 Vec vtmp; 47 48 PetscFunctionBegin; 49 50 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 51 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 52 53 ierr = VecCreateSeq(PETSC_COMM_SELF,A->m,&vtmp);CHKERRQ(ierr); 54 ierr = MatGetRowMax(a->B,vtmp);CHKERRQ(ierr); 55 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 56 57 for (i=0; i<A->m; i++){ 58 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) va[i] = vb[i]; 59 } 60 61 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 62 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 63 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 64 65 PetscFunctionReturn(0); 66 } 67 68 EXTERN_C_BEGIN 69 #undef __FUNCT__ 70 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 71 int MatStoreValues_MPIBAIJ(Mat mat) 72 { 73 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 74 int ierr; 75 76 PetscFunctionBegin; 77 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 78 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 79 PetscFunctionReturn(0); 80 } 81 EXTERN_C_END 82 83 EXTERN_C_BEGIN 84 #undef __FUNCT__ 85 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 86 int MatRetrieveValues_MPIBAIJ(Mat mat) 87 { 88 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 89 int ierr; 90 91 PetscFunctionBegin; 92 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 93 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 94 PetscFunctionReturn(0); 95 } 96 EXTERN_C_END 97 98 /* 99 Local utility routine that creates a mapping from the global column 100 number to the local number in the off-diagonal part of the local 101 storage of the matrix. This is done in a non scable way since the 102 length of colmap equals the global matrix length. 103 */ 104 #undef __FUNCT__ 105 #define __FUNCT__ "CreateColmap_MPIBAIJ_Private" 106 static int CreateColmap_MPIBAIJ_Private(Mat mat) 107 { 108 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 109 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 110 int nbs = B->nbs,i,bs=B->bs,ierr; 111 112 PetscFunctionBegin; 113 #if defined (PETSC_USE_CTABLE) 114 ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr); 115 for (i=0; i<nbs; i++){ 116 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr); 117 } 118 #else 119 ierr = PetscMalloc((baij->Nbs+1)*sizeof(int),&baij->colmap);CHKERRQ(ierr); 120 PetscLogObjectMemory(mat,baij->Nbs*sizeof(int)); 121 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(int));CHKERRQ(ierr); 122 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 123 #endif 124 PetscFunctionReturn(0); 125 } 126 127 #define CHUNKSIZE 10 128 129 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 130 { \ 131 \ 132 brow = row/bs; \ 133 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 134 rmax = aimax[brow]; nrow = ailen[brow]; \ 135 bcol = col/bs; \ 136 ridx = row % bs; cidx = col % bs; \ 137 low = 0; high = nrow; \ 138 while (high-low > 3) { \ 139 t = (low+high)/2; \ 140 if (rp[t] > bcol) high = t; \ 141 else low = t; \ 142 } \ 143 for (_i=low; _i<high; _i++) { \ 144 if (rp[_i] > bcol) break; \ 145 if (rp[_i] == bcol) { \ 146 bap = ap + bs2*_i + bs*cidx + ridx; \ 147 if (addv == ADD_VALUES) *bap += value; \ 148 else *bap = value; \ 149 goto a_noinsert; \ 150 } \ 151 } \ 152 if (a->nonew == 1) goto a_noinsert; \ 153 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 154 if (nrow >= rmax) { \ 155 /* there is no extra room in row, therefore enlarge */ \ 156 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 157 MatScalar *new_a; \ 158 \ 159 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 160 \ 161 /* malloc new storage space */ \ 162 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 163 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 164 new_j = (int*)(new_a + bs2*new_nz); \ 165 new_i = new_j + new_nz; \ 166 \ 167 /* copy over old data into new slots */ \ 168 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 169 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 170 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 171 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 172 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 173 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 174 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar));CHKERRQ(ierr); \ 175 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 176 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 177 /* free up old matrix storage */ \ 178 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 179 if (!a->singlemalloc) { \ 180 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 181 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 182 } \ 183 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 184 a->singlemalloc = PETSC_TRUE; \ 185 \ 186 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 187 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 188 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 189 a->maxnz += bs2*CHUNKSIZE; \ 190 a->reallocs++; \ 191 a->nz++; \ 192 } \ 193 N = nrow++ - 1; \ 194 /* shift up all the later entries in this row */ \ 195 for (ii=N; ii>=_i; ii--) { \ 196 rp[ii+1] = rp[ii]; \ 197 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 198 } \ 199 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 200 rp[_i] = bcol; \ 201 ap[bs2*_i + bs*cidx + ridx] = value; \ 202 a_noinsert:; \ 203 ailen[brow] = nrow; \ 204 } 205 206 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 207 { \ 208 brow = row/bs; \ 209 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 210 rmax = bimax[brow]; nrow = bilen[brow]; \ 211 bcol = col/bs; \ 212 ridx = row % bs; cidx = col % bs; \ 213 low = 0; high = nrow; \ 214 while (high-low > 3) { \ 215 t = (low+high)/2; \ 216 if (rp[t] > bcol) high = t; \ 217 else low = t; \ 218 } \ 219 for (_i=low; _i<high; _i++) { \ 220 if (rp[_i] > bcol) break; \ 221 if (rp[_i] == bcol) { \ 222 bap = ap + bs2*_i + bs*cidx + ridx; \ 223 if (addv == ADD_VALUES) *bap += value; \ 224 else *bap = value; \ 225 goto b_noinsert; \ 226 } \ 227 } \ 228 if (b->nonew == 1) goto b_noinsert; \ 229 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 230 if (nrow >= rmax) { \ 231 /* there is no extra room in row, therefore enlarge */ \ 232 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 233 MatScalar *new_a; \ 234 \ 235 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 236 \ 237 /* malloc new storage space */ \ 238 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 239 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 240 new_j = (int*)(new_a + bs2*new_nz); \ 241 new_i = new_j + new_nz; \ 242 \ 243 /* copy over old data into new slots */ \ 244 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 245 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 246 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 247 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 248 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 249 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 250 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 251 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 252 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 253 /* free up old matrix storage */ \ 254 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 255 if (!b->singlemalloc) { \ 256 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 257 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 258 } \ 259 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 260 b->singlemalloc = PETSC_TRUE; \ 261 \ 262 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 263 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 264 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 265 b->maxnz += bs2*CHUNKSIZE; \ 266 b->reallocs++; \ 267 b->nz++; \ 268 } \ 269 N = nrow++ - 1; \ 270 /* shift up all the later entries in this row */ \ 271 for (ii=N; ii>=_i; ii--) { \ 272 rp[ii+1] = rp[ii]; \ 273 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 274 } \ 275 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 276 rp[_i] = bcol; \ 277 ap[bs2*_i + bs*cidx + ridx] = value; \ 278 b_noinsert:; \ 279 bilen[brow] = nrow; \ 280 } 281 282 #if defined(PETSC_USE_MAT_SINGLE) 283 #undef __FUNCT__ 284 #define __FUNCT__ "MatSetValues_MPIBAIJ" 285 int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 286 { 287 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 288 int ierr,i,N = m*n; 289 MatScalar *vsingle; 290 291 PetscFunctionBegin; 292 if (N > b->setvalueslen) { 293 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 294 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 295 b->setvalueslen = N; 296 } 297 vsingle = b->setvaluescopy; 298 299 for (i=0; i<N; i++) { 300 vsingle[i] = v[i]; 301 } 302 ierr = MatSetValues_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 303 PetscFunctionReturn(0); 304 } 305 306 #undef __FUNCT__ 307 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 308 int MatSetValuesBlocked_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 309 { 310 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 311 int ierr,i,N = m*n*b->bs2; 312 MatScalar *vsingle; 313 314 PetscFunctionBegin; 315 if (N > b->setvalueslen) { 316 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 317 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 318 b->setvalueslen = N; 319 } 320 vsingle = b->setvaluescopy; 321 for (i=0; i<N; i++) { 322 vsingle[i] = v[i]; 323 } 324 ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 325 PetscFunctionReturn(0); 326 } 327 328 #undef __FUNCT__ 329 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 330 int MatSetValues_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 331 { 332 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 333 int ierr,i,N = m*n; 334 MatScalar *vsingle; 335 336 PetscFunctionBegin; 337 if (N > b->setvalueslen) { 338 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 339 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 340 b->setvalueslen = N; 341 } 342 vsingle = b->setvaluescopy; 343 for (i=0; i<N; i++) { 344 vsingle[i] = v[i]; 345 } 346 ierr = MatSetValues_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 347 PetscFunctionReturn(0); 348 } 349 350 #undef __FUNCT__ 351 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 352 int MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 353 { 354 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 355 int ierr,i,N = m*n*b->bs2; 356 MatScalar *vsingle; 357 358 PetscFunctionBegin; 359 if (N > b->setvalueslen) { 360 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 361 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 362 b->setvalueslen = N; 363 } 364 vsingle = b->setvaluescopy; 365 for (i=0; i<N; i++) { 366 vsingle[i] = v[i]; 367 } 368 ierr = MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 369 PetscFunctionReturn(0); 370 } 371 #endif 372 373 #undef __FUNCT__ 374 #define __FUNCT__ "MatSetValues_MPIBAIJ" 375 int MatSetValues_MPIBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 376 { 377 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 378 MatScalar value; 379 PetscTruth roworiented = baij->roworiented; 380 int ierr,i,j,row,col; 381 int rstart_orig=baij->rstart_bs; 382 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 383 int cend_orig=baij->cend_bs,bs=baij->bs; 384 385 /* Some Variables required in the macro */ 386 Mat A = baij->A; 387 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 388 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 389 MatScalar *aa=a->a; 390 391 Mat B = baij->B; 392 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 393 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 394 MatScalar *ba=b->a; 395 396 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 397 int low,high,t,ridx,cidx,bs2=a->bs2; 398 MatScalar *ap,*bap; 399 400 PetscFunctionBegin; 401 for (i=0; i<m; i++) { 402 if (im[i] < 0) continue; 403 #if defined(PETSC_USE_BOPT_g) 404 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 405 #endif 406 if (im[i] >= rstart_orig && im[i] < rend_orig) { 407 row = im[i] - rstart_orig; 408 for (j=0; j<n; j++) { 409 if (in[j] >= cstart_orig && in[j] < cend_orig){ 410 col = in[j] - cstart_orig; 411 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 412 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 413 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 414 } else if (in[j] < 0) continue; 415 #if defined(PETSC_USE_BOPT_g) 416 else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");} 417 #endif 418 else { 419 if (mat->was_assembled) { 420 if (!baij->colmap) { 421 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 422 } 423 #if defined (PETSC_USE_CTABLE) 424 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 425 col = col - 1 + in[j]%bs; 426 #else 427 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 428 #endif 429 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 430 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 431 col = in[j]; 432 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 433 B = baij->B; 434 b = (Mat_SeqBAIJ*)(B)->data; 435 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 436 ba=b->a; 437 } 438 } else col = in[j]; 439 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 440 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 441 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 442 } 443 } 444 } else { 445 if (!baij->donotstash) { 446 if (roworiented) { 447 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 448 } else { 449 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 450 } 451 } 452 } 453 } 454 PetscFunctionReturn(0); 455 } 456 457 #undef __FUNCT__ 458 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_MatScalar" 459 int MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 460 { 461 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 462 MatScalar *value,*barray=baij->barray; 463 PetscTruth roworiented = baij->roworiented; 464 int ierr,i,j,ii,jj,row,col,rstart=baij->rstart; 465 int rend=baij->rend,cstart=baij->cstart,stepval; 466 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 467 468 PetscFunctionBegin; 469 if(!barray) { 470 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 471 baij->barray = barray; 472 } 473 474 if (roworiented) { 475 stepval = (n-1)*bs; 476 } else { 477 stepval = (m-1)*bs; 478 } 479 for (i=0; i<m; i++) { 480 if (im[i] < 0) continue; 481 #if defined(PETSC_USE_BOPT_g) 482 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %d max %d",im[i],baij->Mbs); 483 #endif 484 if (im[i] >= rstart && im[i] < rend) { 485 row = im[i] - rstart; 486 for (j=0; j<n; j++) { 487 /* If NumCol = 1 then a copy is not required */ 488 if ((roworiented) && (n == 1)) { 489 barray = v + i*bs2; 490 } else if((!roworiented) && (m == 1)) { 491 barray = v + j*bs2; 492 } else { /* Here a copy is required */ 493 if (roworiented) { 494 value = v + i*(stepval+bs)*bs + j*bs; 495 } else { 496 value = v + j*(stepval+bs)*bs + i*bs; 497 } 498 for (ii=0; ii<bs; ii++,value+=stepval) { 499 for (jj=0; jj<bs; jj++) { 500 *barray++ = *value++; 501 } 502 } 503 barray -=bs2; 504 } 505 506 if (in[j] >= cstart && in[j] < cend){ 507 col = in[j] - cstart; 508 ierr = MatSetValuesBlocked_SeqBAIJ_MatScalar(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 509 } 510 else if (in[j] < 0) continue; 511 #if defined(PETSC_USE_BOPT_g) 512 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %d max %d",in[j],baij->Nbs);} 513 #endif 514 else { 515 if (mat->was_assembled) { 516 if (!baij->colmap) { 517 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 518 } 519 520 #if defined(PETSC_USE_BOPT_g) 521 #if defined (PETSC_USE_CTABLE) 522 { int data; 523 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 524 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 525 } 526 #else 527 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 528 #endif 529 #endif 530 #if defined (PETSC_USE_CTABLE) 531 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 532 col = (col - 1)/bs; 533 #else 534 col = (baij->colmap[in[j]] - 1)/bs; 535 #endif 536 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 537 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 538 col = in[j]; 539 } 540 } 541 else col = in[j]; 542 ierr = MatSetValuesBlocked_SeqBAIJ_MatScalar(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 543 } 544 } 545 } else { 546 if (!baij->donotstash) { 547 if (roworiented) { 548 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 549 } else { 550 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 551 } 552 } 553 } 554 } 555 PetscFunctionReturn(0); 556 } 557 558 #define HASH_KEY 0.6180339887 559 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 560 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 561 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 562 #undef __FUNCT__ 563 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT_MatScalar" 564 int MatSetValues_MPIBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 565 { 566 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 567 PetscTruth roworiented = baij->roworiented; 568 int ierr,i,j,row,col; 569 int rstart_orig=baij->rstart_bs; 570 int rend_orig=baij->rend_bs,Nbs=baij->Nbs; 571 int h1,key,size=baij->ht_size,bs=baij->bs,*HT=baij->ht,idx; 572 PetscReal tmp; 573 MatScalar **HD = baij->hd,value; 574 #if defined(PETSC_USE_BOPT_g) 575 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 576 #endif 577 578 PetscFunctionBegin; 579 580 for (i=0; i<m; i++) { 581 #if defined(PETSC_USE_BOPT_g) 582 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 583 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 584 #endif 585 row = im[i]; 586 if (row >= rstart_orig && row < rend_orig) { 587 for (j=0; j<n; j++) { 588 col = in[j]; 589 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 590 /* Look up into the Hash Table */ 591 key = (row/bs)*Nbs+(col/bs)+1; 592 h1 = HASH(size,key,tmp); 593 594 595 idx = h1; 596 #if defined(PETSC_USE_BOPT_g) 597 insert_ct++; 598 total_ct++; 599 if (HT[idx] != key) { 600 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 601 if (idx == size) { 602 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 603 if (idx == h1) { 604 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"(row,col) has no entry in the hash table"); 605 } 606 } 607 } 608 #else 609 if (HT[idx] != key) { 610 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 611 if (idx == size) { 612 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 613 if (idx == h1) { 614 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"(row,col) has no entry in the hash table"); 615 } 616 } 617 } 618 #endif 619 /* A HASH table entry is found, so insert the values at the correct address */ 620 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 621 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 622 } 623 } else { 624 if (!baij->donotstash) { 625 if (roworiented) { 626 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 627 } else { 628 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 629 } 630 } 631 } 632 } 633 #if defined(PETSC_USE_BOPT_g) 634 baij->ht_total_ct = total_ct; 635 baij->ht_insert_ct = insert_ct; 636 #endif 637 PetscFunctionReturn(0); 638 } 639 640 #undef __FUNCT__ 641 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT_MatScalar" 642 int MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 643 { 644 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 645 PetscTruth roworiented = baij->roworiented; 646 int ierr,i,j,ii,jj,row,col; 647 int rstart=baij->rstart ; 648 int rend=baij->rend,stepval,bs=baij->bs,bs2=baij->bs2; 649 int h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 650 PetscReal tmp; 651 MatScalar **HD = baij->hd,*baij_a; 652 MatScalar *v_t,*value; 653 #if defined(PETSC_USE_BOPT_g) 654 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 655 #endif 656 657 PetscFunctionBegin; 658 659 if (roworiented) { 660 stepval = (n-1)*bs; 661 } else { 662 stepval = (m-1)*bs; 663 } 664 for (i=0; i<m; i++) { 665 #if defined(PETSC_USE_BOPT_g) 666 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 667 if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 668 #endif 669 row = im[i]; 670 v_t = v + i*bs2; 671 if (row >= rstart && row < rend) { 672 for (j=0; j<n; j++) { 673 col = in[j]; 674 675 /* Look up into the Hash Table */ 676 key = row*Nbs+col+1; 677 h1 = HASH(size,key,tmp); 678 679 idx = h1; 680 #if defined(PETSC_USE_BOPT_g) 681 total_ct++; 682 insert_ct++; 683 if (HT[idx] != key) { 684 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 685 if (idx == size) { 686 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 687 if (idx == h1) { 688 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"(row,col) has no entry in the hash table"); 689 } 690 } 691 } 692 #else 693 if (HT[idx] != key) { 694 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 695 if (idx == size) { 696 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 697 if (idx == h1) { 698 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"(row,col) has no entry in the hash table"); 699 } 700 } 701 } 702 #endif 703 baij_a = HD[idx]; 704 if (roworiented) { 705 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 706 /* value = v + (i*(stepval+bs)+j)*bs; */ 707 value = v_t; 708 v_t += bs; 709 if (addv == ADD_VALUES) { 710 for (ii=0; ii<bs; ii++,value+=stepval) { 711 for (jj=ii; jj<bs2; jj+=bs) { 712 baij_a[jj] += *value++; 713 } 714 } 715 } else { 716 for (ii=0; ii<bs; ii++,value+=stepval) { 717 for (jj=ii; jj<bs2; jj+=bs) { 718 baij_a[jj] = *value++; 719 } 720 } 721 } 722 } else { 723 value = v + j*(stepval+bs)*bs + i*bs; 724 if (addv == ADD_VALUES) { 725 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 726 for (jj=0; jj<bs; jj++) { 727 baij_a[jj] += *value++; 728 } 729 } 730 } else { 731 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 732 for (jj=0; jj<bs; jj++) { 733 baij_a[jj] = *value++; 734 } 735 } 736 } 737 } 738 } 739 } else { 740 if (!baij->donotstash) { 741 if (roworiented) { 742 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 743 } else { 744 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 745 } 746 } 747 } 748 } 749 #if defined(PETSC_USE_BOPT_g) 750 baij->ht_total_ct = total_ct; 751 baij->ht_insert_ct = insert_ct; 752 #endif 753 PetscFunctionReturn(0); 754 } 755 756 #undef __FUNCT__ 757 #define __FUNCT__ "MatGetValues_MPIBAIJ" 758 int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 759 { 760 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 761 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 762 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 763 764 PetscFunctionBegin; 765 for (i=0; i<m; i++) { 766 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 767 if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 768 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 769 row = idxm[i] - bsrstart; 770 for (j=0; j<n; j++) { 771 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 772 if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 773 if (idxn[j] >= bscstart && idxn[j] < bscend){ 774 col = idxn[j] - bscstart; 775 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 776 } else { 777 if (!baij->colmap) { 778 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 779 } 780 #if defined (PETSC_USE_CTABLE) 781 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 782 data --; 783 #else 784 data = baij->colmap[idxn[j]/bs]-1; 785 #endif 786 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 787 else { 788 col = data + idxn[j]%bs; 789 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 790 } 791 } 792 } 793 } else { 794 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 795 } 796 } 797 PetscFunctionReturn(0); 798 } 799 800 #undef __FUNCT__ 801 #define __FUNCT__ "MatNorm_MPIBAIJ" 802 int MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *norm) 803 { 804 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 805 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 806 int ierr,i,bs2=baij->bs2; 807 PetscReal sum = 0.0; 808 MatScalar *v; 809 810 PetscFunctionBegin; 811 if (baij->size == 1) { 812 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 813 } else { 814 if (type == NORM_FROBENIUS) { 815 v = amat->a; 816 for (i=0; i<amat->nz*bs2; i++) { 817 #if defined(PETSC_USE_COMPLEX) 818 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 819 #else 820 sum += (*v)*(*v); v++; 821 #endif 822 } 823 v = bmat->a; 824 for (i=0; i<bmat->nz*bs2; i++) { 825 #if defined(PETSC_USE_COMPLEX) 826 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 827 #else 828 sum += (*v)*(*v); v++; 829 #endif 830 } 831 ierr = MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 832 *norm = sqrt(*norm); 833 } else { 834 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 835 } 836 } 837 PetscFunctionReturn(0); 838 } 839 840 841 /* 842 Creates the hash table, and sets the table 843 This table is created only once. 844 If new entried need to be added to the matrix 845 then the hash table has to be destroyed and 846 recreated. 847 */ 848 #undef __FUNCT__ 849 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 850 int MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 851 { 852 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 853 Mat A = baij->A,B=baij->B; 854 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 855 int i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 856 int size,bs2=baij->bs2,rstart=baij->rstart,ierr; 857 int cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs; 858 int *HT,key; 859 MatScalar **HD; 860 PetscReal tmp; 861 #if defined(PETSC_USE_BOPT_g) 862 int ct=0,max=0; 863 #endif 864 865 PetscFunctionBegin; 866 baij->ht_size=(int)(factor*nz); 867 size = baij->ht_size; 868 869 if (baij->ht) { 870 PetscFunctionReturn(0); 871 } 872 873 /* Allocate Memory for Hash Table */ 874 ierr = PetscMalloc((size)*(sizeof(int)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr); 875 baij->ht = (int*)(baij->hd + size); 876 HD = baij->hd; 877 HT = baij->ht; 878 879 880 ierr = PetscMemzero(HD,size*(sizeof(int)+sizeof(Scalar*)));CHKERRQ(ierr); 881 882 883 /* Loop Over A */ 884 for (i=0; i<a->mbs; i++) { 885 for (j=ai[i]; j<ai[i+1]; j++) { 886 row = i+rstart; 887 col = aj[j]+cstart; 888 889 key = row*Nbs + col + 1; 890 h1 = HASH(size,key,tmp); 891 for (k=0; k<size; k++){ 892 if (HT[(h1+k)%size] == 0.0) { 893 HT[(h1+k)%size] = key; 894 HD[(h1+k)%size] = a->a + j*bs2; 895 break; 896 #if defined(PETSC_USE_BOPT_g) 897 } else { 898 ct++; 899 #endif 900 } 901 } 902 #if defined(PETSC_USE_BOPT_g) 903 if (k> max) max = k; 904 #endif 905 } 906 } 907 /* Loop Over B */ 908 for (i=0; i<b->mbs; i++) { 909 for (j=bi[i]; j<bi[i+1]; j++) { 910 row = i+rstart; 911 col = garray[bj[j]]; 912 key = row*Nbs + col + 1; 913 h1 = HASH(size,key,tmp); 914 for (k=0; k<size; k++){ 915 if (HT[(h1+k)%size] == 0.0) { 916 HT[(h1+k)%size] = key; 917 HD[(h1+k)%size] = b->a + j*bs2; 918 break; 919 #if defined(PETSC_USE_BOPT_g) 920 } else { 921 ct++; 922 #endif 923 } 924 } 925 #if defined(PETSC_USE_BOPT_g) 926 if (k> max) max = k; 927 #endif 928 } 929 } 930 931 /* Print Summary */ 932 #if defined(PETSC_USE_BOPT_g) 933 for (i=0,j=0; i<size; i++) { 934 if (HT[i]) {j++;} 935 } 936 PetscLogInfo(0,"MatCreateHashTable_MPIBAIJ_Private: Average Search = %5.2f,max search = %d\n",(j== 0)? 0.0:((PetscReal)(ct+j))/j,max); 937 #endif 938 PetscFunctionReturn(0); 939 } 940 941 #undef __FUNCT__ 942 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 943 int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 944 { 945 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 946 int ierr,nstash,reallocs; 947 InsertMode addv; 948 949 PetscFunctionBegin; 950 if (baij->donotstash) { 951 PetscFunctionReturn(0); 952 } 953 954 /* make sure all processors are either in INSERTMODE or ADDMODE */ 955 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 956 if (addv == (ADD_VALUES|INSERT_VALUES)) { 957 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 958 } 959 mat->insertmode = addv; /* in case this processor had no cache */ 960 961 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 962 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 963 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 964 PetscLogInfo(0,"MatAssemblyBegin_MPIBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 965 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 966 PetscLogInfo(0,"MatAssemblyBegin_MPIBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 967 PetscFunctionReturn(0); 968 } 969 970 #undef __FUNCT__ 971 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 972 int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 973 { 974 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 975 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data,*b=(Mat_SeqBAIJ*)baij->B->data; 976 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 977 int *row,*col,other_disassembled; 978 PetscTruth r1,r2,r3; 979 MatScalar *val; 980 InsertMode addv = mat->insertmode; 981 982 PetscFunctionBegin; 983 if (!baij->donotstash) { 984 while (1) { 985 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 986 if (!flg) break; 987 988 for (i=0; i<n;) { 989 /* Now identify the consecutive vals belonging to the same row */ 990 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 991 if (j < n) ncols = j-i; 992 else ncols = n-i; 993 /* Now assemble all these values with a single function call */ 994 ierr = MatSetValues_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 995 i = j; 996 } 997 } 998 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 999 /* Now process the block-stash. Since the values are stashed column-oriented, 1000 set the roworiented flag to column oriented, and after MatSetValues() 1001 restore the original flags */ 1002 r1 = baij->roworiented; 1003 r2 = a->roworiented; 1004 r3 = b->roworiented; 1005 baij->roworiented = PETSC_FALSE; 1006 a->roworiented = PETSC_FALSE; 1007 b->roworiented = PETSC_FALSE; 1008 while (1) { 1009 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 1010 if (!flg) break; 1011 1012 for (i=0; i<n;) { 1013 /* Now identify the consecutive vals belonging to the same row */ 1014 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 1015 if (j < n) ncols = j-i; 1016 else ncols = n-i; 1017 ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 1018 i = j; 1019 } 1020 } 1021 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 1022 baij->roworiented = r1; 1023 a->roworiented = r2; 1024 b->roworiented = r3; 1025 } 1026 1027 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 1028 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 1029 1030 /* determine if any processor has disassembled, if so we must 1031 also disassemble ourselfs, in order that we may reassemble. */ 1032 /* 1033 if nonzero structure of submatrix B cannot change then we know that 1034 no processor disassembled thus we can skip this stuff 1035 */ 1036 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 1037 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 1038 if (mat->was_assembled && !other_disassembled) { 1039 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 1040 } 1041 } 1042 1043 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 1044 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 1045 } 1046 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 1047 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 1048 1049 #if defined(PETSC_USE_BOPT_g) 1050 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 1051 PetscLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((double)baij->ht_total_ct)/baij->ht_insert_ct); 1052 baij->ht_total_ct = 0; 1053 baij->ht_insert_ct = 0; 1054 } 1055 #endif 1056 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 1057 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 1058 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 1059 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 1060 } 1061 1062 if (baij->rowvalues) { 1063 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1064 baij->rowvalues = 0; 1065 } 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 1071 static int MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1072 { 1073 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1074 int ierr,bs = baij->bs,size = baij->size,rank = baij->rank; 1075 PetscTruth isascii,isdraw; 1076 PetscViewer sviewer; 1077 PetscViewerFormat format; 1078 1079 PetscFunctionBegin; 1080 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 1081 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1082 if (isascii) { 1083 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1084 if (format == PETSC_VIEWER_ASCII_INFO_LONG) { 1085 MatInfo info; 1086 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 1087 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1088 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 1089 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 1090 baij->bs,(int)info.memory);CHKERRQ(ierr); 1091 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1092 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 1093 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1094 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 1095 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1096 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1099 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 1100 PetscFunctionReturn(0); 1101 } 1102 } 1103 1104 if (isdraw) { 1105 PetscDraw draw; 1106 PetscTruth isnull; 1107 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1108 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1109 } 1110 1111 if (size == 1) { 1112 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 1113 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1114 } else { 1115 /* assemble the entire matrix onto first processor. */ 1116 Mat A; 1117 Mat_SeqBAIJ *Aloc; 1118 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1119 MatScalar *a; 1120 1121 if (!rank) { 1122 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1123 } else { 1124 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1125 } 1126 PetscLogObjectParent(mat,A); 1127 1128 /* copy over the A part */ 1129 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1130 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1131 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 1132 1133 for (i=0; i<mbs; i++) { 1134 rvals[0] = bs*(baij->rstart + i); 1135 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1136 for (j=ai[i]; j<ai[i+1]; j++) { 1137 col = (baij->cstart+aj[j])*bs; 1138 for (k=0; k<bs; k++) { 1139 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1140 col++; a += bs; 1141 } 1142 } 1143 } 1144 /* copy over the B part */ 1145 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1146 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1147 for (i=0; i<mbs; i++) { 1148 rvals[0] = bs*(baij->rstart + i); 1149 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1150 for (j=ai[i]; j<ai[i+1]; j++) { 1151 col = baij->garray[aj[j]]*bs; 1152 for (k=0; k<bs; k++) { 1153 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1154 col++; a += bs; 1155 } 1156 } 1157 } 1158 ierr = PetscFree(rvals);CHKERRQ(ierr); 1159 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1160 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1161 /* 1162 Everyone has to call to draw the matrix since the graphics waits are 1163 synchronized across all processors that share the PetscDraw object 1164 */ 1165 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1166 if (!rank) { 1167 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 1168 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1169 } 1170 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1171 ierr = MatDestroy(A);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatView_MPIBAIJ" 1178 int MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1179 { 1180 int ierr; 1181 PetscTruth isascii,isdraw,issocket,isbinary; 1182 1183 PetscFunctionBegin; 1184 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 1185 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1186 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1187 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1188 if (isascii || isdraw || issocket || isbinary) { 1189 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1190 } else { 1191 SETERRQ1(1,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1192 } 1193 PetscFunctionReturn(0); 1194 } 1195 1196 #undef __FUNCT__ 1197 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1198 int MatDestroy_MPIBAIJ(Mat mat) 1199 { 1200 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1201 int ierr; 1202 1203 PetscFunctionBegin; 1204 #if defined(PETSC_USE_LOG) 1205 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 1206 #endif 1207 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1208 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1209 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 1210 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1211 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1212 #if defined (PETSC_USE_CTABLE) 1213 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 1214 #else 1215 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 1216 #endif 1217 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 1218 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1219 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1220 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 1221 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 1222 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 1223 #if defined(PETSC_USE_MAT_SINGLE) 1224 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 1225 #endif 1226 ierr = PetscFree(baij);CHKERRQ(ierr); 1227 PetscFunctionReturn(0); 1228 } 1229 1230 #undef __FUNCT__ 1231 #define __FUNCT__ "MatMult_MPIBAIJ" 1232 int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1233 { 1234 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1235 int ierr,nt; 1236 1237 PetscFunctionBegin; 1238 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1239 if (nt != A->n) { 1240 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1241 } 1242 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1243 if (nt != A->m) { 1244 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1245 } 1246 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1247 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1248 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1249 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1250 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1251 PetscFunctionReturn(0); 1252 } 1253 1254 #undef __FUNCT__ 1255 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1256 int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1257 { 1258 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1259 int ierr; 1260 1261 PetscFunctionBegin; 1262 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1263 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1264 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1265 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1266 PetscFunctionReturn(0); 1267 } 1268 1269 #undef __FUNCT__ 1270 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1271 int MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1272 { 1273 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1274 int ierr; 1275 1276 PetscFunctionBegin; 1277 /* do nondiagonal part */ 1278 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1279 /* send it on its way */ 1280 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1281 /* do local part */ 1282 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1283 /* receive remote parts: note this assumes the values are not actually */ 1284 /* inserted in yy until the next line, which is true for my implementation*/ 1285 /* but is not perhaps always true. */ 1286 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1287 PetscFunctionReturn(0); 1288 } 1289 1290 #undef __FUNCT__ 1291 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1292 int MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1293 { 1294 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1295 int ierr; 1296 1297 PetscFunctionBegin; 1298 /* do nondiagonal part */ 1299 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1300 /* send it on its way */ 1301 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1302 /* do local part */ 1303 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1304 /* receive remote parts: note this assumes the values are not actually */ 1305 /* inserted in yy until the next line, which is true for my implementation*/ 1306 /* but is not perhaps always true. */ 1307 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1308 PetscFunctionReturn(0); 1309 } 1310 1311 /* 1312 This only works correctly for square matrices where the subblock A->A is the 1313 diagonal block 1314 */ 1315 #undef __FUNCT__ 1316 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1317 int MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1318 { 1319 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1320 int ierr; 1321 1322 PetscFunctionBegin; 1323 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1324 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1325 PetscFunctionReturn(0); 1326 } 1327 1328 #undef __FUNCT__ 1329 #define __FUNCT__ "MatScale_MPIBAIJ" 1330 int MatScale_MPIBAIJ(Scalar *aa,Mat A) 1331 { 1332 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1333 int ierr; 1334 1335 PetscFunctionBegin; 1336 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1337 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1338 PetscFunctionReturn(0); 1339 } 1340 1341 #undef __FUNCT__ 1342 #define __FUNCT__ "MatGetOwnershipRange_MPIBAIJ" 1343 int MatGetOwnershipRange_MPIBAIJ(Mat matin,int *m,int *n) 1344 { 1345 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1346 1347 PetscFunctionBegin; 1348 if (m) *m = mat->rstart_bs; 1349 if (n) *n = mat->rend_bs; 1350 PetscFunctionReturn(0); 1351 } 1352 1353 #undef __FUNCT__ 1354 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1355 int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1356 { 1357 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1358 Scalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1359 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 1360 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1361 int *cmap,*idx_p,cstart = mat->cstart; 1362 1363 PetscFunctionBegin; 1364 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1365 mat->getrowactive = PETSC_TRUE; 1366 1367 if (!mat->rowvalues && (idx || v)) { 1368 /* 1369 allocate enough space to hold information from the longest row. 1370 */ 1371 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1372 int max = 1,mbs = mat->mbs,tmp; 1373 for (i=0; i<mbs; i++) { 1374 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1375 if (max < tmp) { max = tmp; } 1376 } 1377 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(Scalar)),&mat->rowvalues);CHKERRQ(ierr); 1378 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 1379 } 1380 1381 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1382 lrow = row - brstart; 1383 1384 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1385 if (!v) {pvA = 0; pvB = 0;} 1386 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1387 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1388 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1389 nztot = nzA + nzB; 1390 1391 cmap = mat->garray; 1392 if (v || idx) { 1393 if (nztot) { 1394 /* Sort by increasing column numbers, assuming A and B already sorted */ 1395 int imark = -1; 1396 if (v) { 1397 *v = v_p = mat->rowvalues; 1398 for (i=0; i<nzB; i++) { 1399 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1400 else break; 1401 } 1402 imark = i; 1403 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1404 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1405 } 1406 if (idx) { 1407 *idx = idx_p = mat->rowindices; 1408 if (imark > -1) { 1409 for (i=0; i<imark; i++) { 1410 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1411 } 1412 } else { 1413 for (i=0; i<nzB; i++) { 1414 if (cmap[cworkB[i]/bs] < cstart) 1415 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1416 else break; 1417 } 1418 imark = i; 1419 } 1420 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1421 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1422 } 1423 } else { 1424 if (idx) *idx = 0; 1425 if (v) *v = 0; 1426 } 1427 } 1428 *nz = nztot; 1429 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1430 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1431 PetscFunctionReturn(0); 1432 } 1433 1434 #undef __FUNCT__ 1435 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1436 int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1437 { 1438 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1439 1440 PetscFunctionBegin; 1441 if (baij->getrowactive == PETSC_FALSE) { 1442 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1443 } 1444 baij->getrowactive = PETSC_FALSE; 1445 PetscFunctionReturn(0); 1446 } 1447 1448 #undef __FUNCT__ 1449 #define __FUNCT__ "MatGetBlockSize_MPIBAIJ" 1450 int MatGetBlockSize_MPIBAIJ(Mat mat,int *bs) 1451 { 1452 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1453 1454 PetscFunctionBegin; 1455 *bs = baij->bs; 1456 PetscFunctionReturn(0); 1457 } 1458 1459 #undef __FUNCT__ 1460 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1461 int MatZeroEntries_MPIBAIJ(Mat A) 1462 { 1463 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1464 int ierr; 1465 1466 PetscFunctionBegin; 1467 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1468 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1469 PetscFunctionReturn(0); 1470 } 1471 1472 #undef __FUNCT__ 1473 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1474 int MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1475 { 1476 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1477 Mat A = a->A,B = a->B; 1478 int ierr; 1479 PetscReal isend[5],irecv[5]; 1480 1481 PetscFunctionBegin; 1482 info->block_size = (double)a->bs; 1483 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1484 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1485 isend[3] = info->memory; isend[4] = info->mallocs; 1486 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1487 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1488 isend[3] += info->memory; isend[4] += info->mallocs; 1489 if (flag == MAT_LOCAL) { 1490 info->nz_used = isend[0]; 1491 info->nz_allocated = isend[1]; 1492 info->nz_unneeded = isend[2]; 1493 info->memory = isend[3]; 1494 info->mallocs = isend[4]; 1495 } else if (flag == MAT_GLOBAL_MAX) { 1496 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1497 info->nz_used = irecv[0]; 1498 info->nz_allocated = irecv[1]; 1499 info->nz_unneeded = irecv[2]; 1500 info->memory = irecv[3]; 1501 info->mallocs = irecv[4]; 1502 } else if (flag == MAT_GLOBAL_SUM) { 1503 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1504 info->nz_used = irecv[0]; 1505 info->nz_allocated = irecv[1]; 1506 info->nz_unneeded = irecv[2]; 1507 info->memory = irecv[3]; 1508 info->mallocs = irecv[4]; 1509 } else { 1510 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1511 } 1512 info->rows_global = (double)A->M; 1513 info->columns_global = (double)A->N; 1514 info->rows_local = (double)A->m; 1515 info->columns_local = (double)A->N; 1516 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1517 info->fill_ratio_needed = 0; 1518 info->factor_mallocs = 0; 1519 PetscFunctionReturn(0); 1520 } 1521 1522 #undef __FUNCT__ 1523 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1524 int MatSetOption_MPIBAIJ(Mat A,MatOption op) 1525 { 1526 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1527 int ierr; 1528 1529 PetscFunctionBegin; 1530 switch (op) { 1531 case MAT_NO_NEW_NONZERO_LOCATIONS: 1532 case MAT_YES_NEW_NONZERO_LOCATIONS: 1533 case MAT_COLUMNS_UNSORTED: 1534 case MAT_COLUMNS_SORTED: 1535 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1536 case MAT_KEEP_ZEROED_ROWS: 1537 case MAT_NEW_NONZERO_LOCATION_ERR: 1538 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1539 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1540 break; 1541 case MAT_ROW_ORIENTED: 1542 a->roworiented = PETSC_TRUE; 1543 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1544 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1545 break; 1546 case MAT_ROWS_SORTED: 1547 case MAT_ROWS_UNSORTED: 1548 case MAT_YES_NEW_DIAGONALS: 1549 case MAT_USE_HASH_TABLE: 1550 case MAT_USE_SINGLE_PRECISION_SOLVES: 1551 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1552 break; 1553 case MAT_COLUMN_ORIENTED: 1554 a->roworiented = PETSC_FALSE; 1555 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1556 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1557 break; 1558 case MAT_IGNORE_OFF_PROC_ENTRIES: 1559 a->donotstash = PETSC_TRUE; 1560 break; 1561 case MAT_NO_NEW_DIAGONALS: 1562 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1563 break; 1564 case MAT_USE_HASH_TABLE: 1565 a->ht_flag = PETSC_TRUE; 1566 break; 1567 default: 1568 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1569 break; 1570 } 1571 PetscFunctionReturn(0); 1572 } 1573 1574 #undef __FUNCT__ 1575 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1576 int MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1577 { 1578 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1579 Mat_SeqBAIJ *Aloc; 1580 Mat B; 1581 int ierr,M=A->M,N=A->N,*ai,*aj,i,*rvals,j,k,col; 1582 int bs=baij->bs,mbs=baij->mbs; 1583 MatScalar *a; 1584 1585 PetscFunctionBegin; 1586 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1587 ierr = MatCreateMPIBAIJ(A->comm,baij->bs,A->n,A->m,N,M,0,PETSC_NULL,0,PETSC_NULL,&B);CHKERRQ(ierr); 1588 1589 /* copy over the A part */ 1590 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1591 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1592 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 1593 1594 for (i=0; i<mbs; i++) { 1595 rvals[0] = bs*(baij->rstart + i); 1596 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1597 for (j=ai[i]; j<ai[i+1]; j++) { 1598 col = (baij->cstart+aj[j])*bs; 1599 for (k=0; k<bs; k++) { 1600 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1601 col++; a += bs; 1602 } 1603 } 1604 } 1605 /* copy over the B part */ 1606 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1607 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1608 for (i=0; i<mbs; i++) { 1609 rvals[0] = bs*(baij->rstart + i); 1610 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1611 for (j=ai[i]; j<ai[i+1]; j++) { 1612 col = baij->garray[aj[j]]*bs; 1613 for (k=0; k<bs; k++) { 1614 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1615 col++; a += bs; 1616 } 1617 } 1618 } 1619 ierr = PetscFree(rvals);CHKERRQ(ierr); 1620 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1621 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1622 1623 if (matout) { 1624 *matout = B; 1625 } else { 1626 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1627 } 1628 PetscFunctionReturn(0); 1629 } 1630 1631 #undef __FUNCT__ 1632 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1633 int MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1634 { 1635 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1636 Mat a = baij->A,b = baij->B; 1637 int ierr,s1,s2,s3; 1638 1639 PetscFunctionBegin; 1640 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1641 if (rr) { 1642 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1643 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1644 /* Overlap communication with computation. */ 1645 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1646 } 1647 if (ll) { 1648 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1649 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1650 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1651 } 1652 /* scale the diagonal block */ 1653 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1654 1655 if (rr) { 1656 /* Do a scatter end and then right scale the off-diagonal block */ 1657 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1658 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1659 } 1660 1661 PetscFunctionReturn(0); 1662 } 1663 1664 #undef __FUNCT__ 1665 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1666 int MatZeroRows_MPIBAIJ(Mat A,IS is,Scalar *diag) 1667 { 1668 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1669 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 1670 int *procs,*nprocs,j,idx,nsends,*work,row; 1671 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1672 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1673 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1674 MPI_Comm comm = A->comm; 1675 MPI_Request *send_waits,*recv_waits; 1676 MPI_Status recv_status,*send_status; 1677 IS istmp; 1678 PetscTruth found; 1679 1680 PetscFunctionBegin; 1681 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 1682 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1683 1684 /* first count number of contributors to each processor */ 1685 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 1686 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 1687 procs = nprocs + size; 1688 ierr = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/ 1689 for (i=0; i<N; i++) { 1690 idx = rows[i]; 1691 found = PETSC_FALSE; 1692 for (j=0; j<size; j++) { 1693 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1694 nprocs[j]++; procs[j] = 1; owner[i] = j; found = PETSC_TRUE; break; 1695 } 1696 } 1697 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1698 } 1699 nsends = 0; for (i=0; i<size; i++) { nsends += procs[i];} 1700 1701 /* inform other processors of number of messages and max length*/ 1702 ierr = PetscMalloc(2*size*sizeof(int),&work);CHKERRQ(ierr); 1703 ierr = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr); 1704 nmax = work[rank]; 1705 nrecvs = work[size+rank]; 1706 ierr = PetscFree(work);CHKERRQ(ierr); 1707 1708 /* post receives: */ 1709 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 1710 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1711 for (i=0; i<nrecvs; i++) { 1712 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1713 } 1714 1715 /* do sends: 1716 1) starts[i] gives the starting index in svalues for stuff going to 1717 the ith processor 1718 */ 1719 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 1720 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1721 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 1722 starts[0] = 0; 1723 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1724 for (i=0; i<N; i++) { 1725 svalues[starts[owner[i]]++] = rows[i]; 1726 } 1727 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1728 1729 starts[0] = 0; 1730 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1731 count = 0; 1732 for (i=0; i<size; i++) { 1733 if (procs[i]) { 1734 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1735 } 1736 } 1737 ierr = PetscFree(starts);CHKERRQ(ierr); 1738 1739 base = owners[rank]*bs; 1740 1741 /* wait on receives */ 1742 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 1743 source = lens + nrecvs; 1744 count = nrecvs; slen = 0; 1745 while (count) { 1746 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1747 /* unpack receives into our local space */ 1748 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1749 source[imdex] = recv_status.MPI_SOURCE; 1750 lens[imdex] = n; 1751 slen += n; 1752 count--; 1753 } 1754 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1755 1756 /* move the data into the send scatter */ 1757 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 1758 count = 0; 1759 for (i=0; i<nrecvs; i++) { 1760 values = rvalues + i*nmax; 1761 for (j=0; j<lens[i]; j++) { 1762 lrows[count++] = values[j] - base; 1763 } 1764 } 1765 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1766 ierr = PetscFree(lens);CHKERRQ(ierr); 1767 ierr = PetscFree(owner);CHKERRQ(ierr); 1768 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1769 1770 /* actually zap the local rows */ 1771 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1772 PetscLogObjectParent(A,istmp); 1773 1774 /* 1775 Zero the required rows. If the "diagonal block" of the matrix 1776 is square and the user wishes to set the diagonal we use seperate 1777 code so that MatSetValues() is not called for each diagonal allocating 1778 new memory, thus calling lots of mallocs and slowing things down. 1779 1780 Contributed by: Mathew Knepley 1781 */ 1782 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1783 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1784 if (diag && (l->A->M == l->A->N)) { 1785 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1786 } else if (diag) { 1787 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1788 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1789 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1790 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1791 } 1792 for (i=0; i<slen; i++) { 1793 row = lrows[i] + rstart_bs; 1794 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1795 } 1796 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1797 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1798 } else { 1799 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1800 } 1801 1802 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1803 ierr = PetscFree(lrows);CHKERRQ(ierr); 1804 1805 /* wait on sends */ 1806 if (nsends) { 1807 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1808 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1809 ierr = PetscFree(send_status);CHKERRQ(ierr); 1810 } 1811 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1812 ierr = PetscFree(svalues);CHKERRQ(ierr); 1813 1814 PetscFunctionReturn(0); 1815 } 1816 1817 #undef __FUNCT__ 1818 #define __FUNCT__ "MatPrintHelp_MPIBAIJ" 1819 int MatPrintHelp_MPIBAIJ(Mat A) 1820 { 1821 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1822 MPI_Comm comm = A->comm; 1823 static int called = 0; 1824 int ierr; 1825 1826 PetscFunctionBegin; 1827 if (!a->rank) { 1828 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1829 } 1830 if (called) {PetscFunctionReturn(0);} else called = 1; 1831 ierr = (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1832 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1833 PetscFunctionReturn(0); 1834 } 1835 1836 #undef __FUNCT__ 1837 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1838 int MatSetUnfactored_MPIBAIJ(Mat A) 1839 { 1840 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1841 int ierr; 1842 1843 PetscFunctionBegin; 1844 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1845 PetscFunctionReturn(0); 1846 } 1847 1848 static int MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1849 1850 #undef __FUNCT__ 1851 #define __FUNCT__ "MatEqual_MPIBAIJ" 1852 int MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1853 { 1854 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1855 Mat a,b,c,d; 1856 PetscTruth flg; 1857 int ierr; 1858 1859 PetscFunctionBegin; 1860 ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg);CHKERRQ(ierr); 1861 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1862 a = matA->A; b = matA->B; 1863 c = matB->A; d = matB->B; 1864 1865 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1866 if (flg == PETSC_TRUE) { 1867 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1868 } 1869 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1870 PetscFunctionReturn(0); 1871 } 1872 1873 1874 #undef __FUNCT__ 1875 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1876 int MatSetUpPreallocation_MPIBAIJ(Mat A) 1877 { 1878 int ierr; 1879 1880 PetscFunctionBegin; 1881 ierr = MatMPIBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1882 PetscFunctionReturn(0); 1883 } 1884 1885 /* -------------------------------------------------------------------*/ 1886 static struct _MatOps MatOps_Values = { 1887 MatSetValues_MPIBAIJ, 1888 MatGetRow_MPIBAIJ, 1889 MatRestoreRow_MPIBAIJ, 1890 MatMult_MPIBAIJ, 1891 MatMultAdd_MPIBAIJ, 1892 MatMultTranspose_MPIBAIJ, 1893 MatMultTransposeAdd_MPIBAIJ, 1894 0, 1895 0, 1896 0, 1897 0, 1898 0, 1899 0, 1900 0, 1901 MatTranspose_MPIBAIJ, 1902 MatGetInfo_MPIBAIJ, 1903 MatEqual_MPIBAIJ, 1904 MatGetDiagonal_MPIBAIJ, 1905 MatDiagonalScale_MPIBAIJ, 1906 MatNorm_MPIBAIJ, 1907 MatAssemblyBegin_MPIBAIJ, 1908 MatAssemblyEnd_MPIBAIJ, 1909 0, 1910 MatSetOption_MPIBAIJ, 1911 MatZeroEntries_MPIBAIJ, 1912 MatZeroRows_MPIBAIJ, 1913 0, 1914 0, 1915 0, 1916 0, 1917 MatSetUpPreallocation_MPIBAIJ, 1918 0, 1919 MatGetOwnershipRange_MPIBAIJ, 1920 0, 1921 0, 1922 0, 1923 0, 1924 MatDuplicate_MPIBAIJ, 1925 0, 1926 0, 1927 0, 1928 0, 1929 0, 1930 MatGetSubMatrices_MPIBAIJ, 1931 MatIncreaseOverlap_MPIBAIJ, 1932 MatGetValues_MPIBAIJ, 1933 0, 1934 MatPrintHelp_MPIBAIJ, 1935 MatScale_MPIBAIJ, 1936 0, 1937 0, 1938 0, 1939 MatGetBlockSize_MPIBAIJ, 1940 0, 1941 0, 1942 0, 1943 0, 1944 0, 1945 0, 1946 MatSetUnfactored_MPIBAIJ, 1947 0, 1948 MatSetValuesBlocked_MPIBAIJ, 1949 0, 1950 MatDestroy_MPIBAIJ, 1951 MatView_MPIBAIJ, 1952 MatGetMaps_Petsc, 1953 0, 1954 0, 1955 0, 1956 0, 1957 0, 1958 0, 1959 MatGetRowMax_MPIBAIJ}; 1960 1961 1962 EXTERN_C_BEGIN 1963 #undef __FUNCT__ 1964 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 1965 int MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1966 { 1967 PetscFunctionBegin; 1968 *a = ((Mat_MPIBAIJ *)A->data)->A; 1969 *iscopy = PETSC_FALSE; 1970 PetscFunctionReturn(0); 1971 } 1972 EXTERN_C_END 1973 1974 EXTERN_C_BEGIN 1975 #undef __FUNCT__ 1976 #define __FUNCT__ "MatCreate_MPIBAIJ" 1977 int MatCreate_MPIBAIJ(Mat B) 1978 { 1979 Mat_MPIBAIJ *b; 1980 int ierr; 1981 PetscTruth flg; 1982 1983 PetscFunctionBegin; 1984 1985 ierr = PetscNew(Mat_MPIBAIJ,&b);CHKERRQ(ierr); 1986 B->data = (void*)b; 1987 1988 ierr = PetscMemzero(b,sizeof(Mat_MPIBAIJ));CHKERRQ(ierr); 1989 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1990 B->mapping = 0; 1991 B->factor = 0; 1992 B->assembled = PETSC_FALSE; 1993 1994 B->insertmode = NOT_SET_VALUES; 1995 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1996 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1997 1998 /* build local table of row and column ownerships */ 1999 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 2000 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 2001 b->cowners = b->rowners + b->size + 2; 2002 b->rowners_bs = b->cowners + b->size + 2; 2003 2004 /* build cache for off array entries formed */ 2005 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 2006 b->donotstash = PETSC_FALSE; 2007 b->colmap = PETSC_NULL; 2008 b->garray = PETSC_NULL; 2009 b->roworiented = PETSC_TRUE; 2010 2011 #if defined(PETSC_USE_MAT_SINGLE) 2012 /* stuff for MatSetValues_XXX in single precision */ 2013 b->setvalueslen = 0; 2014 b->setvaluescopy = PETSC_NULL; 2015 #endif 2016 2017 /* stuff used in block assembly */ 2018 b->barray = 0; 2019 2020 /* stuff used for matrix vector multiply */ 2021 b->lvec = 0; 2022 b->Mvctx = 0; 2023 2024 /* stuff for MatGetRow() */ 2025 b->rowindices = 0; 2026 b->rowvalues = 0; 2027 b->getrowactive = PETSC_FALSE; 2028 2029 /* hash table stuff */ 2030 b->ht = 0; 2031 b->hd = 0; 2032 b->ht_size = 0; 2033 b->ht_flag = PETSC_FALSE; 2034 b->ht_fact = 0; 2035 b->ht_total_ct = 0; 2036 b->ht_insert_ct = 0; 2037 2038 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 2039 if (flg) { 2040 double fact = 1.39; 2041 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 2042 ierr = PetscOptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 2043 if (fact <= 1.0) fact = 1.39; 2044 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2045 PetscLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact); 2046 } 2047 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2048 "MatStoreValues_MPIBAIJ", 2049 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2050 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2051 "MatRetrieveValues_MPIBAIJ", 2052 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2053 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2054 "MatGetDiagonalBlock_MPIBAIJ", 2055 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2056 PetscFunctionReturn(0); 2057 } 2058 EXTERN_C_END 2059 2060 #undef __FUNCT__ 2061 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2062 /*@C 2063 MatMPIBAIJSetPreallocation - Creates a sparse parallel matrix in block AIJ format 2064 (block compressed row). For good matrix assembly performance 2065 the user should preallocate the matrix storage by setting the parameters 2066 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2067 performance can be increased by more than a factor of 50. 2068 2069 Collective on Mat 2070 2071 Input Parameters: 2072 + A - the matrix 2073 . bs - size of blockk 2074 . d_nz - number of block nonzeros per block row in diagonal portion of local 2075 submatrix (same for all local rows) 2076 . d_nnz - array containing the number of block nonzeros in the various block rows 2077 of the in diagonal portion of the local (possibly different for each block 2078 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2079 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2080 submatrix (same for all local rows). 2081 - o_nnz - array containing the number of nonzeros in the various block rows of the 2082 off-diagonal portion of the local submatrix (possibly different for 2083 each block row) or PETSC_NULL. 2084 2085 Output Parameter: 2086 2087 2088 Options Database Keys: 2089 . -mat_no_unroll - uses code that does not unroll the loops in the 2090 block calculations (much slower) 2091 . -mat_block_size - size of the blocks to use 2092 2093 Notes: 2094 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2095 than it must be used on all processors that share the object for that argument. 2096 2097 Storage Information: 2098 For a square global matrix we define each processor's diagonal portion 2099 to be its local rows and the corresponding columns (a square submatrix); 2100 each processor's off-diagonal portion encompasses the remainder of the 2101 local matrix (a rectangular submatrix). 2102 2103 The user can specify preallocated storage for the diagonal part of 2104 the local submatrix with either d_nz or d_nnz (not both). Set 2105 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2106 memory allocation. Likewise, specify preallocated storage for the 2107 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2108 2109 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2110 the figure below we depict these three local rows and all columns (0-11). 2111 2112 .vb 2113 0 1 2 3 4 5 6 7 8 9 10 11 2114 ------------------- 2115 row 3 | o o o d d d o o o o o o 2116 row 4 | o o o d d d o o o o o o 2117 row 5 | o o o d d d o o o o o o 2118 ------------------- 2119 .ve 2120 2121 Thus, any entries in the d locations are stored in the d (diagonal) 2122 submatrix, and any entries in the o locations are stored in the 2123 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2124 stored simply in the MATSEQBAIJ format for compressed row storage. 2125 2126 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2127 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2128 In general, for PDE problems in which most nonzeros are near the diagonal, 2129 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2130 or you will get TERRIBLE performance; see the users' manual chapter on 2131 matrices. 2132 2133 Level: intermediate 2134 2135 .keywords: matrix, block, aij, compressed row, sparse, parallel 2136 2137 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2138 @*/ 2139 int MatMPIBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2140 { 2141 Mat_MPIBAIJ *b; 2142 int ierr,i; 2143 PetscTruth flg2; 2144 2145 PetscFunctionBegin; 2146 ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg2);CHKERRQ(ierr); 2147 if (!flg2) PetscFunctionReturn(0); 2148 2149 B->preallocated = PETSC_TRUE; 2150 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2151 2152 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2153 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2154 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2155 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2156 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2157 if (d_nnz) { 2158 for (i=0; i<B->m/bs; i++) { 2159 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]); 2160 } 2161 } 2162 if (o_nnz) { 2163 for (i=0; i<B->m/bs; i++) { 2164 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]); 2165 } 2166 } 2167 2168 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 2169 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 2170 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 2171 ierr = MapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 2172 2173 b = (Mat_MPIBAIJ*)B->data; 2174 b->bs = bs; 2175 b->bs2 = bs*bs; 2176 b->mbs = B->m/bs; 2177 b->nbs = B->n/bs; 2178 b->Mbs = B->M/bs; 2179 b->Nbs = B->N/bs; 2180 2181 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 2182 b->rowners[0] = 0; 2183 for (i=2; i<=b->size; i++) { 2184 b->rowners[i] += b->rowners[i-1]; 2185 } 2186 b->rstart = b->rowners[b->rank]; 2187 b->rend = b->rowners[b->rank+1]; 2188 2189 ierr = MPI_Allgather(&b->nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 2190 b->cowners[0] = 0; 2191 for (i=2; i<=b->size; i++) { 2192 b->cowners[i] += b->cowners[i-1]; 2193 } 2194 b->cstart = b->cowners[b->rank]; 2195 b->cend = b->cowners[b->rank+1]; 2196 2197 for (i=0; i<=b->size; i++) { 2198 b->rowners_bs[i] = b->rowners[i]*bs; 2199 } 2200 b->rstart_bs = b->rstart*bs; 2201 b->rend_bs = b->rend*bs; 2202 b->cstart_bs = b->cstart*bs; 2203 b->cend_bs = b->cend*bs; 2204 2205 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2206 PetscLogObjectParent(B,b->A); 2207 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2208 PetscLogObjectParent(B,b->B); 2209 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 2210 2211 PetscFunctionReturn(0); 2212 } 2213 2214 #undef __FUNCT__ 2215 #define __FUNCT__ "MatCreateMPIBAIJ" 2216 /*@C 2217 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2218 (block compressed row). For good matrix assembly performance 2219 the user should preallocate the matrix storage by setting the parameters 2220 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2221 performance can be increased by more than a factor of 50. 2222 2223 Collective on MPI_Comm 2224 2225 Input Parameters: 2226 + comm - MPI communicator 2227 . bs - size of blockk 2228 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2229 This value should be the same as the local size used in creating the 2230 y vector for the matrix-vector product y = Ax. 2231 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2232 This value should be the same as the local size used in creating the 2233 x vector for the matrix-vector product y = Ax. 2234 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2235 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2236 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2237 submatrix (same for all local rows) 2238 . d_nnz - array containing the number of nonzero blocks in the various block rows 2239 of the in diagonal portion of the local (possibly different for each block 2240 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2241 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2242 submatrix (same for all local rows). 2243 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2244 off-diagonal portion of the local submatrix (possibly different for 2245 each block row) or PETSC_NULL. 2246 2247 Output Parameter: 2248 . A - the matrix 2249 2250 Options Database Keys: 2251 . -mat_no_unroll - uses code that does not unroll the loops in the 2252 block calculations (much slower) 2253 . -mat_block_size - size of the blocks to use 2254 2255 Notes: 2256 A nonzero block is any block that as 1 or more nonzeros in it 2257 2258 The user MUST specify either the local or global matrix dimensions 2259 (possibly both). 2260 2261 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2262 than it must be used on all processors that share the object for that argument. 2263 2264 Storage Information: 2265 For a square global matrix we define each processor's diagonal portion 2266 to be its local rows and the corresponding columns (a square submatrix); 2267 each processor's off-diagonal portion encompasses the remainder of the 2268 local matrix (a rectangular submatrix). 2269 2270 The user can specify preallocated storage for the diagonal part of 2271 the local submatrix with either d_nz or d_nnz (not both). Set 2272 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2273 memory allocation. Likewise, specify preallocated storage for the 2274 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2275 2276 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2277 the figure below we depict these three local rows and all columns (0-11). 2278 2279 .vb 2280 0 1 2 3 4 5 6 7 8 9 10 11 2281 ------------------- 2282 row 3 | o o o d d d o o o o o o 2283 row 4 | o o o d d d o o o o o o 2284 row 5 | o o o d d d o o o o o o 2285 ------------------- 2286 .ve 2287 2288 Thus, any entries in the d locations are stored in the d (diagonal) 2289 submatrix, and any entries in the o locations are stored in the 2290 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2291 stored simply in the MATSEQBAIJ format for compressed row storage. 2292 2293 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2294 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2295 In general, for PDE problems in which most nonzeros are near the diagonal, 2296 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2297 or you will get TERRIBLE performance; see the users' manual chapter on 2298 matrices. 2299 2300 Level: intermediate 2301 2302 .keywords: matrix, block, aij, compressed row, sparse, parallel 2303 2304 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2305 @*/ 2306 int MatCreateMPIBAIJ(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) 2307 { 2308 int ierr,size; 2309 2310 PetscFunctionBegin; 2311 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2312 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2313 if (size > 1) { 2314 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2315 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2316 } else { 2317 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2318 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2319 } 2320 PetscFunctionReturn(0); 2321 } 2322 2323 #undef __FUNCT__ 2324 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2325 static int MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2326 { 2327 Mat mat; 2328 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2329 int ierr,len=0; 2330 2331 PetscFunctionBegin; 2332 *newmat = 0; 2333 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2334 ierr = MatSetType(mat,MATMPIBAIJ);CHKERRQ(ierr); 2335 mat->preallocated = PETSC_TRUE; 2336 mat->assembled = PETSC_TRUE; 2337 a = (Mat_MPIBAIJ*)mat->data; 2338 a->bs = oldmat->bs; 2339 a->bs2 = oldmat->bs2; 2340 a->mbs = oldmat->mbs; 2341 a->nbs = oldmat->nbs; 2342 a->Mbs = oldmat->Mbs; 2343 a->Nbs = oldmat->Nbs; 2344 2345 a->rstart = oldmat->rstart; 2346 a->rend = oldmat->rend; 2347 a->cstart = oldmat->cstart; 2348 a->cend = oldmat->cend; 2349 a->size = oldmat->size; 2350 a->rank = oldmat->rank; 2351 a->donotstash = oldmat->donotstash; 2352 a->roworiented = oldmat->roworiented; 2353 a->rowindices = 0; 2354 a->rowvalues = 0; 2355 a->getrowactive = PETSC_FALSE; 2356 a->barray = 0; 2357 a->rstart_bs = oldmat->rstart_bs; 2358 a->rend_bs = oldmat->rend_bs; 2359 a->cstart_bs = oldmat->cstart_bs; 2360 a->cend_bs = oldmat->cend_bs; 2361 2362 /* hash table stuff */ 2363 a->ht = 0; 2364 a->hd = 0; 2365 a->ht_size = 0; 2366 a->ht_flag = oldmat->ht_flag; 2367 a->ht_fact = oldmat->ht_fact; 2368 a->ht_total_ct = 0; 2369 a->ht_insert_ct = 0; 2370 2371 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 2372 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2373 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 2374 if (oldmat->colmap) { 2375 #if defined (PETSC_USE_CTABLE) 2376 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2377 #else 2378 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 2379 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2380 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 2381 #endif 2382 } else a->colmap = 0; 2383 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2384 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2385 PetscLogObjectMemory(mat,len*sizeof(int)); 2386 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2387 } else a->garray = 0; 2388 2389 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2390 PetscLogObjectParent(mat,a->lvec); 2391 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2392 2393 PetscLogObjectParent(mat,a->Mvctx); 2394 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2395 PetscLogObjectParent(mat,a->A); 2396 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2397 PetscLogObjectParent(mat,a->B); 2398 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 2399 *newmat = mat; 2400 PetscFunctionReturn(0); 2401 } 2402 2403 #include "petscsys.h" 2404 2405 EXTERN_C_BEGIN 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatLoad_MPIBAIJ" 2408 int MatLoad_MPIBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 2409 { 2410 Mat A; 2411 int i,nz,ierr,j,rstart,rend,fd; 2412 Scalar *vals,*buf; 2413 MPI_Comm comm = ((PetscObject)viewer)->comm; 2414 MPI_Status status; 2415 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2416 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2417 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2418 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2419 int dcount,kmax,k,nzcount,tmp; 2420 2421 PetscFunctionBegin; 2422 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2423 2424 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2425 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2426 if (!rank) { 2427 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2428 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2429 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2430 if (header[3] < 0) { 2431 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPIBAIJ"); 2432 } 2433 } 2434 2435 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2436 M = header[1]; N = header[2]; 2437 2438 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2439 2440 /* 2441 This code adds extra rows to make sure the number of rows is 2442 divisible by the blocksize 2443 */ 2444 Mbs = M/bs; 2445 extra_rows = bs - M + bs*(Mbs); 2446 if (extra_rows == bs) extra_rows = 0; 2447 else Mbs++; 2448 if (extra_rows &&!rank) { 2449 PetscLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"); 2450 } 2451 2452 /* determine ownership of all rows */ 2453 mbs = Mbs/size + ((Mbs % size) > rank); 2454 m = mbs*bs; 2455 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2456 browners = rowners + size + 1; 2457 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2458 rowners[0] = 0; 2459 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2460 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2461 rstart = rowners[rank]; 2462 rend = rowners[rank+1]; 2463 2464 /* distribute row lengths to all processors */ 2465 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2466 if (!rank) { 2467 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2468 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2469 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2470 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2471 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2472 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2473 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2474 } else { 2475 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2476 } 2477 2478 if (!rank) { 2479 /* calculate the number of nonzeros on each processor */ 2480 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2481 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2482 for (i=0; i<size; i++) { 2483 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2484 procsnz[i] += rowlengths[j]; 2485 } 2486 } 2487 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2488 2489 /* determine max buffer needed and allocate it */ 2490 maxnz = 0; 2491 for (i=0; i<size; i++) { 2492 maxnz = PetscMax(maxnz,procsnz[i]); 2493 } 2494 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2495 2496 /* read in my part of the matrix column indices */ 2497 nz = procsnz[0]; 2498 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2499 mycols = ibuf; 2500 if (size == 1) nz -= extra_rows; 2501 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2502 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2503 2504 /* read in every ones (except the last) and ship off */ 2505 for (i=1; i<size-1; i++) { 2506 nz = procsnz[i]; 2507 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2508 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2509 } 2510 /* read in the stuff for the last proc */ 2511 if (size != 1) { 2512 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2513 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2514 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2515 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2516 } 2517 ierr = PetscFree(cols);CHKERRQ(ierr); 2518 } else { 2519 /* determine buffer space needed for message */ 2520 nz = 0; 2521 for (i=0; i<m; i++) { 2522 nz += locrowlens[i]; 2523 } 2524 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2525 mycols = ibuf; 2526 /* receive message of column indices*/ 2527 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2528 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2529 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2530 } 2531 2532 /* loop over local rows, determining number of off diagonal entries */ 2533 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2534 odlens = dlens + (rend-rstart); 2535 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2536 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2537 masked1 = mask + Mbs; 2538 masked2 = masked1 + Mbs; 2539 rowcount = 0; nzcount = 0; 2540 for (i=0; i<mbs; i++) { 2541 dcount = 0; 2542 odcount = 0; 2543 for (j=0; j<bs; j++) { 2544 kmax = locrowlens[rowcount]; 2545 for (k=0; k<kmax; k++) { 2546 tmp = mycols[nzcount++]/bs; 2547 if (!mask[tmp]) { 2548 mask[tmp] = 1; 2549 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2550 else masked1[dcount++] = tmp; 2551 } 2552 } 2553 rowcount++; 2554 } 2555 2556 dlens[i] = dcount; 2557 odlens[i] = odcount; 2558 2559 /* zero out the mask elements we set */ 2560 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2561 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2562 } 2563 2564 /* create our matrix */ 2565 ierr = MatCreateMPIBAIJ(comm,bs,m,m,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat);CHKERRQ(ierr); 2566 A = *newmat; 2567 MatSetOption(A,MAT_COLUMNS_SORTED); 2568 2569 if (!rank) { 2570 ierr = PetscMalloc(maxnz*sizeof(Scalar),&buf);CHKERRQ(ierr); 2571 /* read in my part of the matrix numerical values */ 2572 nz = procsnz[0]; 2573 vals = buf; 2574 mycols = ibuf; 2575 if (size == 1) nz -= extra_rows; 2576 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2577 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2578 2579 /* insert into matrix */ 2580 jj = rstart*bs; 2581 for (i=0; i<m; i++) { 2582 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2583 mycols += locrowlens[i]; 2584 vals += locrowlens[i]; 2585 jj++; 2586 } 2587 /* read in other processors (except the last one) and ship out */ 2588 for (i=1; i<size-1; i++) { 2589 nz = procsnz[i]; 2590 vals = buf; 2591 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2592 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2593 } 2594 /* the last proc */ 2595 if (size != 1){ 2596 nz = procsnz[i] - extra_rows; 2597 vals = buf; 2598 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2599 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2600 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2601 } 2602 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2603 } else { 2604 /* receive numeric values */ 2605 ierr = PetscMalloc(nz*sizeof(Scalar),&buf);CHKERRQ(ierr); 2606 2607 /* receive message of values*/ 2608 vals = buf; 2609 mycols = ibuf; 2610 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2611 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2612 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2613 2614 /* insert into matrix */ 2615 jj = rstart*bs; 2616 for (i=0; i<m; i++) { 2617 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2618 mycols += locrowlens[i]; 2619 vals += locrowlens[i]; 2620 jj++; 2621 } 2622 } 2623 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2624 ierr = PetscFree(buf);CHKERRQ(ierr); 2625 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2626 ierr = PetscFree(rowners);CHKERRQ(ierr); 2627 ierr = PetscFree(dlens);CHKERRQ(ierr); 2628 ierr = PetscFree(mask);CHKERRQ(ierr); 2629 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2630 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2631 PetscFunctionReturn(0); 2632 } 2633 EXTERN_C_END 2634 2635 #undef __FUNCT__ 2636 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2637 /*@ 2638 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2639 2640 Input Parameters: 2641 . mat - the matrix 2642 . fact - factor 2643 2644 Collective on Mat 2645 2646 Level: advanced 2647 2648 Notes: 2649 This can also be set by the command line option: -mat_use_hash_table fact 2650 2651 .keywords: matrix, hashtable, factor, HT 2652 2653 .seealso: MatSetOption() 2654 @*/ 2655 int MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2656 { 2657 Mat_MPIBAIJ *baij; 2658 int ierr; 2659 PetscTruth flg; 2660 2661 PetscFunctionBegin; 2662 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2663 ierr = PetscTypeCompare((PetscObject)mat,MATMPIBAIJ,&flg);CHKERRQ(ierr); 2664 if (!flg) { 2665 SETERRQ(PETSC_ERR_ARG_WRONG,"Incorrect matrix type. Use MPIBAIJ only."); 2666 } 2667 baij = (Mat_MPIBAIJ*)mat->data; 2668 baij->ht_fact = fact; 2669 PetscFunctionReturn(0); 2670 } 2671 2672 #undef __FUNCT__ 2673 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2674 int MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2675 { 2676 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2677 PetscFunctionBegin; 2678 *Ad = a->A; 2679 *Ao = a->B; 2680 *colmap = a->garray; 2681 PetscFunctionReturn(0); 2682 } 2683