1 /*$Id: mpibaij.c,v 1.234 2001/09/25 22:56:49 balay Exp $*/ 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 *,PetscScalar *); 11 EXTERN int MatSetValues_SeqBAIJ(Mat,int,int *,int,int *,PetscScalar *,InsertMode); 12 EXTERN int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,PetscScalar*,InsertMode); 13 EXTERN int MatGetRow_SeqBAIJ(Mat,int,int*,int**,PetscScalar**); 14 EXTERN int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,PetscScalar**); 15 EXTERN int MatPrintHelp_SeqBAIJ(Mat); 16 EXTERN int MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*); 17 18 /* UGLY, ugly, ugly 19 When MatScalar == PetscScalar 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 PetscScalar *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(PetscScalar));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,PetscScalar *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,PetscScalar *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,PetscScalar *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,PetscScalar *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; 426 #else 427 col = baij->colmap[in[j]/bs] - 1; 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 } else col += in[j]%bs; 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,PetscScalar *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 *nrm) 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,nrm);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,nrm,1,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 832 *nrm = sqrt(*nrm); 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(PetscScalar*)));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 EXTERN int MatUseDSCPACK_MPIBAIJ(Mat); 971 #undef __FUNCT__ 972 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 973 int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 974 { 975 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 976 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data,*b=(Mat_SeqBAIJ*)baij->B->data; 977 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 978 int *row,*col,other_disassembled; 979 PetscTruth r1,r2,r3; 980 MatScalar *val; 981 InsertMode addv = mat->insertmode; 982 #if defined(PETSC_HAVE_DSCPACK) 983 PetscTruth flag; 984 #endif 985 986 PetscFunctionBegin; 987 if (!baij->donotstash) { 988 while (1) { 989 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 990 if (!flg) break; 991 992 for (i=0; i<n;) { 993 /* Now identify the consecutive vals belonging to the same row */ 994 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 995 if (j < n) ncols = j-i; 996 else ncols = n-i; 997 /* Now assemble all these values with a single function call */ 998 ierr = MatSetValues_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 999 i = j; 1000 } 1001 } 1002 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 1003 /* Now process the block-stash. Since the values are stashed column-oriented, 1004 set the roworiented flag to column oriented, and after MatSetValues() 1005 restore the original flags */ 1006 r1 = baij->roworiented; 1007 r2 = a->roworiented; 1008 r3 = b->roworiented; 1009 baij->roworiented = PETSC_FALSE; 1010 a->roworiented = PETSC_FALSE; 1011 b->roworiented = PETSC_FALSE; 1012 while (1) { 1013 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 1014 if (!flg) break; 1015 1016 for (i=0; i<n;) { 1017 /* Now identify the consecutive vals belonging to the same row */ 1018 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 1019 if (j < n) ncols = j-i; 1020 else ncols = n-i; 1021 ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 1022 i = j; 1023 } 1024 } 1025 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 1026 baij->roworiented = r1; 1027 a->roworiented = r2; 1028 b->roworiented = r3; 1029 } 1030 1031 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 1032 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 1033 1034 /* determine if any processor has disassembled, if so we must 1035 also disassemble ourselfs, in order that we may reassemble. */ 1036 /* 1037 if nonzero structure of submatrix B cannot change then we know that 1038 no processor disassembled thus we can skip this stuff 1039 */ 1040 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 1041 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 1042 if (mat->was_assembled && !other_disassembled) { 1043 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 1044 } 1045 } 1046 1047 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 1048 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 1049 } 1050 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 1051 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 1052 1053 #if defined(PETSC_USE_BOPT_g) 1054 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 1055 PetscLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 1056 baij->ht_total_ct = 0; 1057 baij->ht_insert_ct = 0; 1058 } 1059 #endif 1060 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 1061 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 1062 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 1063 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 1064 } 1065 1066 if (baij->rowvalues) { 1067 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1068 baij->rowvalues = 0; 1069 } 1070 #if defined(PETSC_HAVE_DSCPACK) 1071 ierr = PetscOptionsHasName(mat->prefix,"-mat_baij_dscpack",&flag);CHKERRQ(ierr); 1072 if (flag) { ierr = MatUseDSCPACK_MPIBAIJ(mat);CHKERRQ(ierr); } 1073 #endif 1074 PetscFunctionReturn(0); 1075 } 1076 1077 extern int MatMPIBAIJFactorInfo_DSCPACK(Mat,PetscViewer); 1078 1079 #undef __FUNCT__ 1080 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 1081 static int MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1082 { 1083 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1084 int ierr,bs = baij->bs,size = baij->size,rank = baij->rank; 1085 PetscTruth isascii,isdraw; 1086 PetscViewer sviewer; 1087 PetscViewerFormat format; 1088 1089 PetscFunctionBegin; 1090 /* printf(" MatView_MPIBAIJ_ASCIIorDraworSocket is called ...\n"); */ 1091 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 1092 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1093 if (isascii) { 1094 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1095 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1096 MatInfo info; 1097 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 1098 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1099 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 1100 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 1101 baij->bs,(int)info.memory);CHKERRQ(ierr); 1102 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1103 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 1104 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1105 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 1106 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1107 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 1108 PetscFunctionReturn(0); 1109 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1110 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 1111 PetscFunctionReturn(0); 1112 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1113 #if defined(PETSC_HAVE_DSCPACK) && !defined(PETSC_USE_SINGLE) && !defined(PETSC_USE_COMPLEX) 1114 ierr = MatMPIBAIJFactorInfo_DSCPACK(mat,viewer);CHKERRQ(ierr); 1115 #endif 1116 PetscFunctionReturn(0); 1117 } 1118 } 1119 1120 if (isdraw) { 1121 PetscDraw draw; 1122 PetscTruth isnull; 1123 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1124 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1125 } 1126 1127 if (size == 1) { 1128 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 1129 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1130 } else { 1131 /* assemble the entire matrix onto first processor. */ 1132 Mat A; 1133 Mat_SeqBAIJ *Aloc; 1134 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1135 MatScalar *a; 1136 1137 if (!rank) { 1138 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1139 } else { 1140 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1141 } 1142 PetscLogObjectParent(mat,A); 1143 1144 /* copy over the A part */ 1145 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1146 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1147 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 1148 1149 for (i=0; i<mbs; i++) { 1150 rvals[0] = bs*(baij->rstart + i); 1151 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1152 for (j=ai[i]; j<ai[i+1]; j++) { 1153 col = (baij->cstart+aj[j])*bs; 1154 for (k=0; k<bs; k++) { 1155 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1156 col++; a += bs; 1157 } 1158 } 1159 } 1160 /* copy over the B part */ 1161 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1162 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1163 for (i=0; i<mbs; i++) { 1164 rvals[0] = bs*(baij->rstart + i); 1165 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1166 for (j=ai[i]; j<ai[i+1]; j++) { 1167 col = baij->garray[aj[j]]*bs; 1168 for (k=0; k<bs; k++) { 1169 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1170 col++; a += bs; 1171 } 1172 } 1173 } 1174 ierr = PetscFree(rvals);CHKERRQ(ierr); 1175 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1176 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1177 /* 1178 Everyone has to call to draw the matrix since the graphics waits are 1179 synchronized across all processors that share the PetscDraw object 1180 */ 1181 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1182 if (!rank) { 1183 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 1184 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1185 } 1186 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1187 ierr = MatDestroy(A);CHKERRQ(ierr); 1188 } 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatView_MPIBAIJ" 1194 int MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1195 { 1196 int ierr; 1197 PetscTruth isascii,isdraw,issocket,isbinary; 1198 1199 PetscFunctionBegin; 1200 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 1201 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1202 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1203 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1204 if (isascii || isdraw || issocket || isbinary) { 1205 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1206 } else { 1207 SETERRQ1(1,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1208 } 1209 PetscFunctionReturn(0); 1210 } 1211 1212 #undef __FUNCT__ 1213 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1214 int MatDestroy_MPIBAIJ(Mat mat) 1215 { 1216 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1217 int ierr; 1218 1219 PetscFunctionBegin; 1220 #if defined(PETSC_USE_LOG) 1221 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 1222 #endif 1223 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1224 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1225 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 1226 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1227 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1228 #if defined (PETSC_USE_CTABLE) 1229 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 1230 #else 1231 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 1232 #endif 1233 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 1234 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1235 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1236 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 1237 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 1238 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 1239 #if defined(PETSC_USE_MAT_SINGLE) 1240 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 1241 #endif 1242 ierr = PetscFree(baij);CHKERRQ(ierr); 1243 PetscFunctionReturn(0); 1244 } 1245 1246 #undef __FUNCT__ 1247 #define __FUNCT__ "MatMult_MPIBAIJ" 1248 int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1249 { 1250 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1251 int ierr,nt; 1252 1253 PetscFunctionBegin; 1254 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1255 if (nt != A->n) { 1256 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1257 } 1258 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1259 if (nt != A->m) { 1260 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1261 } 1262 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1263 ierr = (*a->A->ops->mult)(a->A,xx,yy);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,yy,yy);CHKERRQ(ierr); 1266 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1267 PetscFunctionReturn(0); 1268 } 1269 1270 #undef __FUNCT__ 1271 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1272 int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1273 { 1274 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1275 int ierr; 1276 1277 PetscFunctionBegin; 1278 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1279 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1280 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1281 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1282 PetscFunctionReturn(0); 1283 } 1284 1285 #undef __FUNCT__ 1286 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1287 int MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1288 { 1289 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1290 int ierr; 1291 1292 PetscFunctionBegin; 1293 /* do nondiagonal part */ 1294 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1295 /* send it on its way */ 1296 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1297 /* do local part */ 1298 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1299 /* receive remote parts: note this assumes the values are not actually */ 1300 /* inserted in yy until the next line, which is true for my implementation*/ 1301 /* but is not perhaps always true. */ 1302 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1303 PetscFunctionReturn(0); 1304 } 1305 1306 #undef __FUNCT__ 1307 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1308 int MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1309 { 1310 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1311 int ierr; 1312 1313 PetscFunctionBegin; 1314 /* do nondiagonal part */ 1315 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1316 /* send it on its way */ 1317 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1318 /* do local part */ 1319 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1320 /* receive remote parts: note this assumes the values are not actually */ 1321 /* inserted in yy until the next line, which is true for my implementation*/ 1322 /* but is not perhaps always true. */ 1323 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1324 PetscFunctionReturn(0); 1325 } 1326 1327 /* 1328 This only works correctly for square matrices where the subblock A->A is the 1329 diagonal block 1330 */ 1331 #undef __FUNCT__ 1332 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1333 int MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1334 { 1335 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1336 int ierr; 1337 1338 PetscFunctionBegin; 1339 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1340 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1341 PetscFunctionReturn(0); 1342 } 1343 1344 #undef __FUNCT__ 1345 #define __FUNCT__ "MatScale_MPIBAIJ" 1346 int MatScale_MPIBAIJ(PetscScalar *aa,Mat A) 1347 { 1348 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1349 int ierr; 1350 1351 PetscFunctionBegin; 1352 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1353 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1354 PetscFunctionReturn(0); 1355 } 1356 1357 #undef __FUNCT__ 1358 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1359 int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 1360 { 1361 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1362 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1363 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 1364 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1365 int *cmap,*idx_p,cstart = mat->cstart; 1366 1367 PetscFunctionBegin; 1368 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1369 mat->getrowactive = PETSC_TRUE; 1370 1371 if (!mat->rowvalues && (idx || v)) { 1372 /* 1373 allocate enough space to hold information from the longest row. 1374 */ 1375 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1376 int max = 1,mbs = mat->mbs,tmp; 1377 for (i=0; i<mbs; i++) { 1378 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1379 if (max < tmp) { max = tmp; } 1380 } 1381 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1382 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 1383 } 1384 1385 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1386 lrow = row - brstart; 1387 1388 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1389 if (!v) {pvA = 0; pvB = 0;} 1390 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1391 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1392 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1393 nztot = nzA + nzB; 1394 1395 cmap = mat->garray; 1396 if (v || idx) { 1397 if (nztot) { 1398 /* Sort by increasing column numbers, assuming A and B already sorted */ 1399 int imark = -1; 1400 if (v) { 1401 *v = v_p = mat->rowvalues; 1402 for (i=0; i<nzB; i++) { 1403 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1404 else break; 1405 } 1406 imark = i; 1407 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1408 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1409 } 1410 if (idx) { 1411 *idx = idx_p = mat->rowindices; 1412 if (imark > -1) { 1413 for (i=0; i<imark; i++) { 1414 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1415 } 1416 } else { 1417 for (i=0; i<nzB; i++) { 1418 if (cmap[cworkB[i]/bs] < cstart) 1419 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1420 else break; 1421 } 1422 imark = i; 1423 } 1424 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1425 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1426 } 1427 } else { 1428 if (idx) *idx = 0; 1429 if (v) *v = 0; 1430 } 1431 } 1432 *nz = nztot; 1433 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1434 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1435 PetscFunctionReturn(0); 1436 } 1437 1438 #undef __FUNCT__ 1439 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1440 int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1441 { 1442 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1443 1444 PetscFunctionBegin; 1445 if (baij->getrowactive == PETSC_FALSE) { 1446 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1447 } 1448 baij->getrowactive = PETSC_FALSE; 1449 PetscFunctionReturn(0); 1450 } 1451 1452 #undef __FUNCT__ 1453 #define __FUNCT__ "MatGetBlockSize_MPIBAIJ" 1454 int MatGetBlockSize_MPIBAIJ(Mat mat,int *bs) 1455 { 1456 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1457 1458 PetscFunctionBegin; 1459 *bs = baij->bs; 1460 PetscFunctionReturn(0); 1461 } 1462 1463 #undef __FUNCT__ 1464 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1465 int MatZeroEntries_MPIBAIJ(Mat A) 1466 { 1467 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1468 int ierr; 1469 1470 PetscFunctionBegin; 1471 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1472 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1473 PetscFunctionReturn(0); 1474 } 1475 1476 #undef __FUNCT__ 1477 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1478 int MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1479 { 1480 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1481 Mat A = a->A,B = a->B; 1482 int ierr; 1483 PetscReal isend[5],irecv[5]; 1484 1485 PetscFunctionBegin; 1486 info->block_size = (PetscReal)a->bs; 1487 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1488 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1489 isend[3] = info->memory; isend[4] = info->mallocs; 1490 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1491 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1492 isend[3] += info->memory; isend[4] += info->mallocs; 1493 if (flag == MAT_LOCAL) { 1494 info->nz_used = isend[0]; 1495 info->nz_allocated = isend[1]; 1496 info->nz_unneeded = isend[2]; 1497 info->memory = isend[3]; 1498 info->mallocs = isend[4]; 1499 } else if (flag == MAT_GLOBAL_MAX) { 1500 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1501 info->nz_used = irecv[0]; 1502 info->nz_allocated = irecv[1]; 1503 info->nz_unneeded = irecv[2]; 1504 info->memory = irecv[3]; 1505 info->mallocs = irecv[4]; 1506 } else if (flag == MAT_GLOBAL_SUM) { 1507 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1508 info->nz_used = irecv[0]; 1509 info->nz_allocated = irecv[1]; 1510 info->nz_unneeded = irecv[2]; 1511 info->memory = irecv[3]; 1512 info->mallocs = irecv[4]; 1513 } else { 1514 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1515 } 1516 info->rows_global = (PetscReal)A->M; 1517 info->columns_global = (PetscReal)A->N; 1518 info->rows_local = (PetscReal)A->m; 1519 info->columns_local = (PetscReal)A->N; 1520 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1521 info->fill_ratio_needed = 0; 1522 info->factor_mallocs = 0; 1523 PetscFunctionReturn(0); 1524 } 1525 1526 #undef __FUNCT__ 1527 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1528 int MatSetOption_MPIBAIJ(Mat A,MatOption op) 1529 { 1530 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1531 int ierr; 1532 1533 PetscFunctionBegin; 1534 switch (op) { 1535 case MAT_NO_NEW_NONZERO_LOCATIONS: 1536 case MAT_YES_NEW_NONZERO_LOCATIONS: 1537 case MAT_COLUMNS_UNSORTED: 1538 case MAT_COLUMNS_SORTED: 1539 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1540 case MAT_KEEP_ZEROED_ROWS: 1541 case MAT_NEW_NONZERO_LOCATION_ERR: 1542 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1543 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1544 break; 1545 case MAT_ROW_ORIENTED: 1546 a->roworiented = PETSC_TRUE; 1547 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1548 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1549 break; 1550 case MAT_ROWS_SORTED: 1551 case MAT_ROWS_UNSORTED: 1552 case MAT_YES_NEW_DIAGONALS: 1553 case MAT_USE_SINGLE_PRECISION_SOLVES: 1554 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1555 break; 1556 case MAT_COLUMN_ORIENTED: 1557 a->roworiented = PETSC_FALSE; 1558 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1559 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1560 break; 1561 case MAT_IGNORE_OFF_PROC_ENTRIES: 1562 a->donotstash = PETSC_TRUE; 1563 break; 1564 case MAT_NO_NEW_DIAGONALS: 1565 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1566 case MAT_USE_HASH_TABLE: 1567 a->ht_flag = PETSC_TRUE; 1568 break; 1569 default: 1570 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1571 } 1572 PetscFunctionReturn(0); 1573 } 1574 1575 #undef __FUNCT__ 1576 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1577 int MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1578 { 1579 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1580 Mat_SeqBAIJ *Aloc; 1581 Mat B; 1582 int ierr,M=A->M,N=A->N,*ai,*aj,i,*rvals,j,k,col; 1583 int bs=baij->bs,mbs=baij->mbs; 1584 MatScalar *a; 1585 1586 PetscFunctionBegin; 1587 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1588 ierr = MatCreateMPIBAIJ(A->comm,baij->bs,A->n,A->m,N,M,0,PETSC_NULL,0,PETSC_NULL,&B);CHKERRQ(ierr); 1589 1590 /* copy over the A part */ 1591 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1592 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1593 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 1594 1595 for (i=0; i<mbs; i++) { 1596 rvals[0] = bs*(baij->rstart + i); 1597 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1598 for (j=ai[i]; j<ai[i+1]; j++) { 1599 col = (baij->cstart+aj[j])*bs; 1600 for (k=0; k<bs; k++) { 1601 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1602 col++; a += bs; 1603 } 1604 } 1605 } 1606 /* copy over the B part */ 1607 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1608 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1609 for (i=0; i<mbs; i++) { 1610 rvals[0] = bs*(baij->rstart + i); 1611 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1612 for (j=ai[i]; j<ai[i+1]; j++) { 1613 col = baij->garray[aj[j]]*bs; 1614 for (k=0; k<bs; k++) { 1615 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1616 col++; a += bs; 1617 } 1618 } 1619 } 1620 ierr = PetscFree(rvals);CHKERRQ(ierr); 1621 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1622 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1623 1624 if (matout) { 1625 *matout = B; 1626 } else { 1627 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1628 } 1629 PetscFunctionReturn(0); 1630 } 1631 1632 #undef __FUNCT__ 1633 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1634 int MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1635 { 1636 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1637 Mat a = baij->A,b = baij->B; 1638 int ierr,s1,s2,s3; 1639 1640 PetscFunctionBegin; 1641 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1642 if (rr) { 1643 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1644 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1645 /* Overlap communication with computation. */ 1646 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1647 } 1648 if (ll) { 1649 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1650 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1651 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1652 } 1653 /* scale the diagonal block */ 1654 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1655 1656 if (rr) { 1657 /* Do a scatter end and then right scale the off-diagonal block */ 1658 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1659 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1660 } 1661 1662 PetscFunctionReturn(0); 1663 } 1664 1665 #undef __FUNCT__ 1666 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1667 int MatZeroRows_MPIBAIJ(Mat A,IS is,PetscScalar *diag) 1668 { 1669 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1670 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 1671 int *nprocs,j,idx,nsends,row; 1672 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1673 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1674 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1675 MPI_Comm comm = A->comm; 1676 MPI_Request *send_waits,*recv_waits; 1677 MPI_Status recv_status,*send_status; 1678 IS istmp; 1679 PetscTruth found; 1680 1681 PetscFunctionBegin; 1682 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 1683 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1684 1685 /* first count number of contributors to each processor */ 1686 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 1687 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 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[2*j]++; nprocs[2*j+1] = 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 += nprocs[2*i+1];} 1700 1701 /* inform other processors of number of messages and max length*/ 1702 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1703 1704 /* post receives: */ 1705 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 1706 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1707 for (i=0; i<nrecvs; i++) { 1708 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1709 } 1710 1711 /* do sends: 1712 1) starts[i] gives the starting index in svalues for stuff going to 1713 the ith processor 1714 */ 1715 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 1716 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1717 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 1718 starts[0] = 0; 1719 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1720 for (i=0; i<N; i++) { 1721 svalues[starts[owner[i]]++] = rows[i]; 1722 } 1723 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1724 1725 starts[0] = 0; 1726 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1727 count = 0; 1728 for (i=0; i<size; i++) { 1729 if (nprocs[2*i+1]) { 1730 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1731 } 1732 } 1733 ierr = PetscFree(starts);CHKERRQ(ierr); 1734 1735 base = owners[rank]*bs; 1736 1737 /* wait on receives */ 1738 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 1739 source = lens + nrecvs; 1740 count = nrecvs; slen = 0; 1741 while (count) { 1742 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1743 /* unpack receives into our local space */ 1744 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1745 source[imdex] = recv_status.MPI_SOURCE; 1746 lens[imdex] = n; 1747 slen += n; 1748 count--; 1749 } 1750 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1751 1752 /* move the data into the send scatter */ 1753 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 1754 count = 0; 1755 for (i=0; i<nrecvs; i++) { 1756 values = rvalues + i*nmax; 1757 for (j=0; j<lens[i]; j++) { 1758 lrows[count++] = values[j] - base; 1759 } 1760 } 1761 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1762 ierr = PetscFree(lens);CHKERRQ(ierr); 1763 ierr = PetscFree(owner);CHKERRQ(ierr); 1764 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1765 1766 /* actually zap the local rows */ 1767 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1768 PetscLogObjectParent(A,istmp); 1769 1770 /* 1771 Zero the required rows. If the "diagonal block" of the matrix 1772 is square and the user wishes to set the diagonal we use seperate 1773 code so that MatSetValues() is not called for each diagonal allocating 1774 new memory, thus calling lots of mallocs and slowing things down. 1775 1776 Contributed by: Mathew Knepley 1777 */ 1778 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1779 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1780 if (diag && (l->A->M == l->A->N)) { 1781 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1782 } else if (diag) { 1783 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1784 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1785 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1786 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1787 } 1788 for (i=0; i<slen; i++) { 1789 row = lrows[i] + rstart_bs; 1790 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1791 } 1792 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1793 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1794 } else { 1795 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1796 } 1797 1798 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1799 ierr = PetscFree(lrows);CHKERRQ(ierr); 1800 1801 /* wait on sends */ 1802 if (nsends) { 1803 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1804 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1805 ierr = PetscFree(send_status);CHKERRQ(ierr); 1806 } 1807 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1808 ierr = PetscFree(svalues);CHKERRQ(ierr); 1809 1810 PetscFunctionReturn(0); 1811 } 1812 1813 #undef __FUNCT__ 1814 #define __FUNCT__ "MatPrintHelp_MPIBAIJ" 1815 int MatPrintHelp_MPIBAIJ(Mat A) 1816 { 1817 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1818 MPI_Comm comm = A->comm; 1819 static int called = 0; 1820 int ierr; 1821 1822 PetscFunctionBegin; 1823 if (!a->rank) { 1824 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1825 } 1826 if (called) {PetscFunctionReturn(0);} else called = 1; 1827 ierr = (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1828 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1829 PetscFunctionReturn(0); 1830 } 1831 1832 #undef __FUNCT__ 1833 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1834 int MatSetUnfactored_MPIBAIJ(Mat A) 1835 { 1836 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1837 int ierr; 1838 1839 PetscFunctionBegin; 1840 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1841 PetscFunctionReturn(0); 1842 } 1843 1844 static int MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1845 1846 #undef __FUNCT__ 1847 #define __FUNCT__ "MatEqual_MPIBAIJ" 1848 int MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1849 { 1850 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1851 Mat a,b,c,d; 1852 PetscTruth flg; 1853 int ierr; 1854 1855 PetscFunctionBegin; 1856 ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg);CHKERRQ(ierr); 1857 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1858 a = matA->A; b = matA->B; 1859 c = matB->A; d = matB->B; 1860 1861 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1862 if (flg == PETSC_TRUE) { 1863 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1864 } 1865 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1866 PetscFunctionReturn(0); 1867 } 1868 1869 1870 #undef __FUNCT__ 1871 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1872 int MatSetUpPreallocation_MPIBAIJ(Mat A) 1873 { 1874 int ierr; 1875 1876 PetscFunctionBegin; 1877 ierr = MatMPIBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1878 PetscFunctionReturn(0); 1879 } 1880 1881 /* -------------------------------------------------------------------*/ 1882 static struct _MatOps MatOps_Values = { 1883 MatSetValues_MPIBAIJ, 1884 MatGetRow_MPIBAIJ, 1885 MatRestoreRow_MPIBAIJ, 1886 MatMult_MPIBAIJ, 1887 MatMultAdd_MPIBAIJ, 1888 MatMultTranspose_MPIBAIJ, 1889 MatMultTransposeAdd_MPIBAIJ, 1890 0, 1891 0, 1892 0, 1893 0, 1894 0, 1895 0, 1896 0, 1897 MatTranspose_MPIBAIJ, 1898 MatGetInfo_MPIBAIJ, 1899 MatEqual_MPIBAIJ, 1900 MatGetDiagonal_MPIBAIJ, 1901 MatDiagonalScale_MPIBAIJ, 1902 MatNorm_MPIBAIJ, 1903 MatAssemblyBegin_MPIBAIJ, 1904 MatAssemblyEnd_MPIBAIJ, 1905 0, 1906 MatSetOption_MPIBAIJ, 1907 MatZeroEntries_MPIBAIJ, 1908 MatZeroRows_MPIBAIJ, 1909 0, 1910 0, 1911 0, 1912 0, 1913 MatSetUpPreallocation_MPIBAIJ, 1914 0, 1915 0, 1916 0, 1917 0, 1918 MatDuplicate_MPIBAIJ, 1919 0, 1920 0, 1921 0, 1922 0, 1923 0, 1924 MatGetSubMatrices_MPIBAIJ, 1925 MatIncreaseOverlap_MPIBAIJ, 1926 MatGetValues_MPIBAIJ, 1927 0, 1928 MatPrintHelp_MPIBAIJ, 1929 MatScale_MPIBAIJ, 1930 0, 1931 0, 1932 0, 1933 MatGetBlockSize_MPIBAIJ, 1934 0, 1935 0, 1936 0, 1937 0, 1938 0, 1939 0, 1940 MatSetUnfactored_MPIBAIJ, 1941 0, 1942 MatSetValuesBlocked_MPIBAIJ, 1943 0, 1944 MatDestroy_MPIBAIJ, 1945 MatView_MPIBAIJ, 1946 MatGetPetscMaps_Petsc, 1947 0, 1948 0, 1949 0, 1950 0, 1951 0, 1952 0, 1953 MatGetRowMax_MPIBAIJ}; 1954 1955 1956 EXTERN_C_BEGIN 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 1959 int MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1960 { 1961 PetscFunctionBegin; 1962 *a = ((Mat_MPIBAIJ *)A->data)->A; 1963 *iscopy = PETSC_FALSE; 1964 PetscFunctionReturn(0); 1965 } 1966 EXTERN_C_END 1967 1968 EXTERN_C_BEGIN 1969 #undef __FUNCT__ 1970 #define __FUNCT__ "MatCreate_MPIBAIJ" 1971 int MatCreate_MPIBAIJ(Mat B) 1972 { 1973 Mat_MPIBAIJ *b; 1974 int ierr; 1975 PetscTruth flg; 1976 1977 PetscFunctionBegin; 1978 1979 ierr = PetscNew(Mat_MPIBAIJ,&b);CHKERRQ(ierr); 1980 B->data = (void*)b; 1981 1982 ierr = PetscMemzero(b,sizeof(Mat_MPIBAIJ));CHKERRQ(ierr); 1983 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1984 B->mapping = 0; 1985 B->factor = 0; 1986 B->assembled = PETSC_FALSE; 1987 1988 B->insertmode = NOT_SET_VALUES; 1989 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1990 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1991 1992 /* build local table of row and column ownerships */ 1993 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1994 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 1995 b->cowners = b->rowners + b->size + 2; 1996 b->rowners_bs = b->cowners + b->size + 2; 1997 1998 /* build cache for off array entries formed */ 1999 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 2000 b->donotstash = PETSC_FALSE; 2001 b->colmap = PETSC_NULL; 2002 b->garray = PETSC_NULL; 2003 b->roworiented = PETSC_TRUE; 2004 2005 #if defined(PETSC_USE_MAT_SINGLE) 2006 /* stuff for MatSetValues_XXX in single precision */ 2007 b->setvalueslen = 0; 2008 b->setvaluescopy = PETSC_NULL; 2009 #endif 2010 2011 /* stuff used in block assembly */ 2012 b->barray = 0; 2013 2014 /* stuff used for matrix vector multiply */ 2015 b->lvec = 0; 2016 b->Mvctx = 0; 2017 2018 /* stuff for MatGetRow() */ 2019 b->rowindices = 0; 2020 b->rowvalues = 0; 2021 b->getrowactive = PETSC_FALSE; 2022 2023 /* hash table stuff */ 2024 b->ht = 0; 2025 b->hd = 0; 2026 b->ht_size = 0; 2027 b->ht_flag = PETSC_FALSE; 2028 b->ht_fact = 0; 2029 b->ht_total_ct = 0; 2030 b->ht_insert_ct = 0; 2031 2032 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 2033 if (flg) { 2034 PetscReal fact = 1.39; 2035 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 2036 ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 2037 if (fact <= 1.0) fact = 1.39; 2038 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2039 PetscLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact); 2040 } 2041 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2042 "MatStoreValues_MPIBAIJ", 2043 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2044 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2045 "MatRetrieveValues_MPIBAIJ", 2046 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2047 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2048 "MatGetDiagonalBlock_MPIBAIJ", 2049 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2050 PetscFunctionReturn(0); 2051 } 2052 EXTERN_C_END 2053 2054 #undef __FUNCT__ 2055 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2056 /*@C 2057 MatMPIBAIJSetPreallocation - Creates a sparse parallel matrix in block AIJ format 2058 (block compressed row). For good matrix assembly performance 2059 the user should preallocate the matrix storage by setting the parameters 2060 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2061 performance can be increased by more than a factor of 50. 2062 2063 Collective on Mat 2064 2065 Input Parameters: 2066 + A - the matrix 2067 . bs - size of blockk 2068 . d_nz - number of block nonzeros per block row in diagonal portion of local 2069 submatrix (same for all local rows) 2070 . d_nnz - array containing the number of block nonzeros in the various block rows 2071 of the in diagonal portion of the local (possibly different for each block 2072 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2073 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2074 submatrix (same for all local rows). 2075 - o_nnz - array containing the number of nonzeros in the various block rows of the 2076 off-diagonal portion of the local submatrix (possibly different for 2077 each block row) or PETSC_NULL. 2078 2079 Output Parameter: 2080 2081 2082 Options Database Keys: 2083 . -mat_no_unroll - uses code that does not unroll the loops in the 2084 block calculations (much slower) 2085 . -mat_block_size - size of the blocks to use 2086 2087 Notes: 2088 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2089 than it must be used on all processors that share the object for that argument. 2090 2091 Storage Information: 2092 For a square global matrix we define each processor's diagonal portion 2093 to be its local rows and the corresponding columns (a square submatrix); 2094 each processor's off-diagonal portion encompasses the remainder of the 2095 local matrix (a rectangular submatrix). 2096 2097 The user can specify preallocated storage for the diagonal part of 2098 the local submatrix with either d_nz or d_nnz (not both). Set 2099 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2100 memory allocation. Likewise, specify preallocated storage for the 2101 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2102 2103 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2104 the figure below we depict these three local rows and all columns (0-11). 2105 2106 .vb 2107 0 1 2 3 4 5 6 7 8 9 10 11 2108 ------------------- 2109 row 3 | o o o d d d o o o o o o 2110 row 4 | o o o d d d o o o o o o 2111 row 5 | o o o d d d o o o o o o 2112 ------------------- 2113 .ve 2114 2115 Thus, any entries in the d locations are stored in the d (diagonal) 2116 submatrix, and any entries in the o locations are stored in the 2117 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2118 stored simply in the MATSEQBAIJ format for compressed row storage. 2119 2120 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2121 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2122 In general, for PDE problems in which most nonzeros are near the diagonal, 2123 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2124 or you will get TERRIBLE performance; see the users' manual chapter on 2125 matrices. 2126 2127 Level: intermediate 2128 2129 .keywords: matrix, block, aij, compressed row, sparse, parallel 2130 2131 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2132 @*/ 2133 int MatMPIBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2134 { 2135 Mat_MPIBAIJ *b; 2136 int ierr,i; 2137 PetscTruth flg2; 2138 2139 PetscFunctionBegin; 2140 ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg2);CHKERRQ(ierr); 2141 if (!flg2) PetscFunctionReturn(0); 2142 2143 B->preallocated = PETSC_TRUE; 2144 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2145 2146 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2147 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2148 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2149 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2150 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2151 if (d_nnz) { 2152 for (i=0; i<B->m/bs; i++) { 2153 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]); 2154 } 2155 } 2156 if (o_nnz) { 2157 for (i=0; i<B->m/bs; i++) { 2158 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]); 2159 } 2160 } 2161 2162 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 2163 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 2164 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 2165 ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 2166 2167 b = (Mat_MPIBAIJ*)B->data; 2168 b->bs = bs; 2169 b->bs2 = bs*bs; 2170 b->mbs = B->m/bs; 2171 b->nbs = B->n/bs; 2172 b->Mbs = B->M/bs; 2173 b->Nbs = B->N/bs; 2174 2175 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 2176 b->rowners[0] = 0; 2177 for (i=2; i<=b->size; i++) { 2178 b->rowners[i] += b->rowners[i-1]; 2179 } 2180 b->rstart = b->rowners[b->rank]; 2181 b->rend = b->rowners[b->rank+1]; 2182 2183 ierr = MPI_Allgather(&b->nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 2184 b->cowners[0] = 0; 2185 for (i=2; i<=b->size; i++) { 2186 b->cowners[i] += b->cowners[i-1]; 2187 } 2188 b->cstart = b->cowners[b->rank]; 2189 b->cend = b->cowners[b->rank+1]; 2190 2191 for (i=0; i<=b->size; i++) { 2192 b->rowners_bs[i] = b->rowners[i]*bs; 2193 } 2194 b->rstart_bs = b->rstart*bs; 2195 b->rend_bs = b->rend*bs; 2196 b->cstart_bs = b->cstart*bs; 2197 b->cend_bs = b->cend*bs; 2198 2199 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2200 PetscLogObjectParent(B,b->A); 2201 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2202 PetscLogObjectParent(B,b->B); 2203 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 2204 2205 PetscFunctionReturn(0); 2206 } 2207 2208 #undef __FUNCT__ 2209 #define __FUNCT__ "MatCreateMPIBAIJ" 2210 /*@C 2211 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2212 (block compressed row). For good matrix assembly performance 2213 the user should preallocate the matrix storage by setting the parameters 2214 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2215 performance can be increased by more than a factor of 50. 2216 2217 Collective on MPI_Comm 2218 2219 Input Parameters: 2220 + comm - MPI communicator 2221 . bs - size of blockk 2222 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2223 This value should be the same as the local size used in creating the 2224 y vector for the matrix-vector product y = Ax. 2225 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2226 This value should be the same as the local size used in creating the 2227 x vector for the matrix-vector product y = Ax. 2228 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2229 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2230 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2231 submatrix (same for all local rows) 2232 . d_nnz - array containing the number of nonzero blocks in the various block rows 2233 of the in diagonal portion of the local (possibly different for each block 2234 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2235 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2236 submatrix (same for all local rows). 2237 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2238 off-diagonal portion of the local submatrix (possibly different for 2239 each block row) or PETSC_NULL. 2240 2241 Output Parameter: 2242 . A - the matrix 2243 2244 Options Database Keys: 2245 . -mat_no_unroll - uses code that does not unroll the loops in the 2246 block calculations (much slower) 2247 . -mat_block_size - size of the blocks to use 2248 2249 Notes: 2250 A nonzero block is any block that as 1 or more nonzeros in it 2251 2252 The user MUST specify either the local or global matrix dimensions 2253 (possibly both). 2254 2255 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2256 than it must be used on all processors that share the object for that argument. 2257 2258 Storage Information: 2259 For a square global matrix we define each processor's diagonal portion 2260 to be its local rows and the corresponding columns (a square submatrix); 2261 each processor's off-diagonal portion encompasses the remainder of the 2262 local matrix (a rectangular submatrix). 2263 2264 The user can specify preallocated storage for the diagonal part of 2265 the local submatrix with either d_nz or d_nnz (not both). Set 2266 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2267 memory allocation. Likewise, specify preallocated storage for the 2268 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2269 2270 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2271 the figure below we depict these three local rows and all columns (0-11). 2272 2273 .vb 2274 0 1 2 3 4 5 6 7 8 9 10 11 2275 ------------------- 2276 row 3 | o o o d d d o o o o o o 2277 row 4 | o o o d d d o o o o o o 2278 row 5 | o o o d d d o o o o o o 2279 ------------------- 2280 .ve 2281 2282 Thus, any entries in the d locations are stored in the d (diagonal) 2283 submatrix, and any entries in the o locations are stored in the 2284 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2285 stored simply in the MATSEQBAIJ format for compressed row storage. 2286 2287 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2288 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2289 In general, for PDE problems in which most nonzeros are near the diagonal, 2290 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2291 or you will get TERRIBLE performance; see the users' manual chapter on 2292 matrices. 2293 2294 Level: intermediate 2295 2296 .keywords: matrix, block, aij, compressed row, sparse, parallel 2297 2298 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2299 @*/ 2300 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) 2301 { 2302 int ierr,size; 2303 2304 PetscFunctionBegin; 2305 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2306 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2307 if (size > 1) { 2308 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2309 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2310 } else { 2311 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2312 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2313 } 2314 PetscFunctionReturn(0); 2315 } 2316 2317 #undef __FUNCT__ 2318 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2319 static int MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2320 { 2321 Mat mat; 2322 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2323 int ierr,len=0; 2324 2325 PetscFunctionBegin; 2326 *newmat = 0; 2327 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2328 ierr = MatSetType(mat,MATMPIBAIJ);CHKERRQ(ierr); 2329 mat->preallocated = PETSC_TRUE; 2330 mat->assembled = PETSC_TRUE; 2331 a = (Mat_MPIBAIJ*)mat->data; 2332 a->bs = oldmat->bs; 2333 a->bs2 = oldmat->bs2; 2334 a->mbs = oldmat->mbs; 2335 a->nbs = oldmat->nbs; 2336 a->Mbs = oldmat->Mbs; 2337 a->Nbs = oldmat->Nbs; 2338 2339 a->rstart = oldmat->rstart; 2340 a->rend = oldmat->rend; 2341 a->cstart = oldmat->cstart; 2342 a->cend = oldmat->cend; 2343 a->size = oldmat->size; 2344 a->rank = oldmat->rank; 2345 a->donotstash = oldmat->donotstash; 2346 a->roworiented = oldmat->roworiented; 2347 a->rowindices = 0; 2348 a->rowvalues = 0; 2349 a->getrowactive = PETSC_FALSE; 2350 a->barray = 0; 2351 a->rstart_bs = oldmat->rstart_bs; 2352 a->rend_bs = oldmat->rend_bs; 2353 a->cstart_bs = oldmat->cstart_bs; 2354 a->cend_bs = oldmat->cend_bs; 2355 2356 /* hash table stuff */ 2357 a->ht = 0; 2358 a->hd = 0; 2359 a->ht_size = 0; 2360 a->ht_flag = oldmat->ht_flag; 2361 a->ht_fact = oldmat->ht_fact; 2362 a->ht_total_ct = 0; 2363 a->ht_insert_ct = 0; 2364 2365 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 2366 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2367 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 2368 if (oldmat->colmap) { 2369 #if defined (PETSC_USE_CTABLE) 2370 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2371 #else 2372 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 2373 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2374 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 2375 #endif 2376 } else a->colmap = 0; 2377 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2378 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2379 PetscLogObjectMemory(mat,len*sizeof(int)); 2380 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2381 } else a->garray = 0; 2382 2383 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2384 PetscLogObjectParent(mat,a->lvec); 2385 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2386 2387 PetscLogObjectParent(mat,a->Mvctx); 2388 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2389 PetscLogObjectParent(mat,a->A); 2390 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2391 PetscLogObjectParent(mat,a->B); 2392 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 2393 *newmat = mat; 2394 PetscFunctionReturn(0); 2395 } 2396 2397 #include "petscsys.h" 2398 2399 EXTERN_C_BEGIN 2400 #undef __FUNCT__ 2401 #define __FUNCT__ "MatLoad_MPIBAIJ" 2402 int MatLoad_MPIBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 2403 { 2404 Mat A; 2405 int i,nz,ierr,j,rstart,rend,fd; 2406 PetscScalar *vals,*buf; 2407 MPI_Comm comm = ((PetscObject)viewer)->comm; 2408 MPI_Status status; 2409 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2410 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2411 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2412 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2413 int dcount,kmax,k,nzcount,tmp; 2414 2415 PetscFunctionBegin; 2416 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2417 2418 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2419 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2420 if (!rank) { 2421 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2422 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2423 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2424 if (header[3] < 0) { 2425 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPIBAIJ"); 2426 } 2427 } 2428 2429 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2430 M = header[1]; N = header[2]; 2431 2432 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2433 2434 /* 2435 This code adds extra rows to make sure the number of rows is 2436 divisible by the blocksize 2437 */ 2438 Mbs = M/bs; 2439 extra_rows = bs - M + bs*(Mbs); 2440 if (extra_rows == bs) extra_rows = 0; 2441 else Mbs++; 2442 if (extra_rows &&!rank) { 2443 PetscLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"); 2444 } 2445 2446 /* determine ownership of all rows */ 2447 mbs = Mbs/size + ((Mbs % size) > rank); 2448 m = mbs*bs; 2449 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2450 browners = rowners + size + 1; 2451 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2452 rowners[0] = 0; 2453 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2454 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2455 rstart = rowners[rank]; 2456 rend = rowners[rank+1]; 2457 2458 /* distribute row lengths to all processors */ 2459 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2460 if (!rank) { 2461 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2462 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2463 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2464 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2465 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2466 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2467 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2468 } else { 2469 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2470 } 2471 2472 if (!rank) { 2473 /* calculate the number of nonzeros on each processor */ 2474 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2475 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2476 for (i=0; i<size; i++) { 2477 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2478 procsnz[i] += rowlengths[j]; 2479 } 2480 } 2481 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2482 2483 /* determine max buffer needed and allocate it */ 2484 maxnz = 0; 2485 for (i=0; i<size; i++) { 2486 maxnz = PetscMax(maxnz,procsnz[i]); 2487 } 2488 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2489 2490 /* read in my part of the matrix column indices */ 2491 nz = procsnz[0]; 2492 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2493 mycols = ibuf; 2494 if (size == 1) nz -= extra_rows; 2495 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2496 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2497 2498 /* read in every ones (except the last) and ship off */ 2499 for (i=1; i<size-1; i++) { 2500 nz = procsnz[i]; 2501 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2502 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2503 } 2504 /* read in the stuff for the last proc */ 2505 if (size != 1) { 2506 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2507 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2508 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2509 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2510 } 2511 ierr = PetscFree(cols);CHKERRQ(ierr); 2512 } else { 2513 /* determine buffer space needed for message */ 2514 nz = 0; 2515 for (i=0; i<m; i++) { 2516 nz += locrowlens[i]; 2517 } 2518 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2519 mycols = ibuf; 2520 /* receive message of column indices*/ 2521 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2522 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2523 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2524 } 2525 2526 /* loop over local rows, determining number of off diagonal entries */ 2527 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2528 odlens = dlens + (rend-rstart); 2529 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2530 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2531 masked1 = mask + Mbs; 2532 masked2 = masked1 + Mbs; 2533 rowcount = 0; nzcount = 0; 2534 for (i=0; i<mbs; i++) { 2535 dcount = 0; 2536 odcount = 0; 2537 for (j=0; j<bs; j++) { 2538 kmax = locrowlens[rowcount]; 2539 for (k=0; k<kmax; k++) { 2540 tmp = mycols[nzcount++]/bs; 2541 if (!mask[tmp]) { 2542 mask[tmp] = 1; 2543 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2544 else masked1[dcount++] = tmp; 2545 } 2546 } 2547 rowcount++; 2548 } 2549 2550 dlens[i] = dcount; 2551 odlens[i] = odcount; 2552 2553 /* zero out the mask elements we set */ 2554 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2555 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2556 } 2557 2558 /* create our matrix */ 2559 ierr = MatCreateMPIBAIJ(comm,bs,m,m,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat);CHKERRQ(ierr); 2560 A = *newmat; 2561 MatSetOption(A,MAT_COLUMNS_SORTED); 2562 2563 if (!rank) { 2564 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2565 /* read in my part of the matrix numerical values */ 2566 nz = procsnz[0]; 2567 vals = buf; 2568 mycols = ibuf; 2569 if (size == 1) nz -= extra_rows; 2570 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2571 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2572 2573 /* insert into matrix */ 2574 jj = rstart*bs; 2575 for (i=0; i<m; i++) { 2576 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2577 mycols += locrowlens[i]; 2578 vals += locrowlens[i]; 2579 jj++; 2580 } 2581 /* read in other processors (except the last one) and ship out */ 2582 for (i=1; i<size-1; i++) { 2583 nz = procsnz[i]; 2584 vals = buf; 2585 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2586 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2587 } 2588 /* the last proc */ 2589 if (size != 1){ 2590 nz = procsnz[i] - extra_rows; 2591 vals = buf; 2592 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2593 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2594 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2595 } 2596 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2597 } else { 2598 /* receive numeric values */ 2599 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2600 2601 /* receive message of values*/ 2602 vals = buf; 2603 mycols = ibuf; 2604 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2605 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2606 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2607 2608 /* insert into matrix */ 2609 jj = rstart*bs; 2610 for (i=0; i<m; i++) { 2611 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2612 mycols += locrowlens[i]; 2613 vals += locrowlens[i]; 2614 jj++; 2615 } 2616 } 2617 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2618 ierr = PetscFree(buf);CHKERRQ(ierr); 2619 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2620 ierr = PetscFree(rowners);CHKERRQ(ierr); 2621 ierr = PetscFree(dlens);CHKERRQ(ierr); 2622 ierr = PetscFree(mask);CHKERRQ(ierr); 2623 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2624 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2625 PetscFunctionReturn(0); 2626 } 2627 EXTERN_C_END 2628 2629 #undef __FUNCT__ 2630 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2631 /*@ 2632 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2633 2634 Input Parameters: 2635 . mat - the matrix 2636 . fact - factor 2637 2638 Collective on Mat 2639 2640 Level: advanced 2641 2642 Notes: 2643 This can also be set by the command line option: -mat_use_hash_table fact 2644 2645 .keywords: matrix, hashtable, factor, HT 2646 2647 .seealso: MatSetOption() 2648 @*/ 2649 int MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2650 { 2651 Mat_MPIBAIJ *baij; 2652 int ierr; 2653 PetscTruth flg; 2654 2655 PetscFunctionBegin; 2656 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2657 ierr = PetscTypeCompare((PetscObject)mat,MATMPIBAIJ,&flg);CHKERRQ(ierr); 2658 if (!flg) { 2659 SETERRQ(PETSC_ERR_ARG_WRONG,"Incorrect matrix type. Use MPIBAIJ only."); 2660 } 2661 baij = (Mat_MPIBAIJ*)mat->data; 2662 baij->ht_fact = fact; 2663 PetscFunctionReturn(0); 2664 } 2665 2666 #undef __FUNCT__ 2667 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2668 int MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2669 { 2670 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2671 PetscFunctionBegin; 2672 *Ad = a->A; 2673 *Ao = a->B; 2674 *colmap = a->garray; 2675 PetscFunctionReturn(0); 2676 } 2677