1 2 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 3 #include "mpisbaij.h" 4 #include "src/mat/impls/sbaij/seq/sbaij.h" 5 6 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 8 EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat); 9 EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 10 EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 11 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 13 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 14 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 16 EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 EXTERN PetscErrorCode MatPrintHelp_SeqSBAIJ(Mat); 18 EXTERN PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 19 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 20 EXTERN PetscErrorCode MatGetRowMax_MPISBAIJ(Mat,Vec); 21 EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 /* UGLY, ugly, ugly 24 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 25 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 26 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 27 converts the entries into single precision and then calls ..._MatScalar() to put them 28 into the single precision data structures. 29 */ 30 #if defined(PETSC_USE_MAT_SINGLE) 31 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 32 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 33 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 34 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 35 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 36 #else 37 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 38 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 39 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 40 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 41 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 42 #endif 43 44 EXTERN_C_BEGIN 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 47 PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 48 { 49 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 EXTERN_C_END 58 59 EXTERN_C_BEGIN 60 #undef __FUNCT__ 61 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 62 PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 63 { 64 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 65 PetscErrorCode ierr; 66 67 PetscFunctionBegin; 68 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 69 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 70 PetscFunctionReturn(0); 71 } 72 EXTERN_C_END 73 74 75 #define CHUNKSIZE 10 76 77 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 78 { \ 79 \ 80 brow = row/bs; \ 81 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 82 rmax = aimax[brow]; nrow = ailen[brow]; \ 83 bcol = col/bs; \ 84 ridx = row % bs; cidx = col % bs; \ 85 low = 0; high = nrow; \ 86 while (high-low > 3) { \ 87 t = (low+high)/2; \ 88 if (rp[t] > bcol) high = t; \ 89 else low = t; \ 90 } \ 91 for (_i=low; _i<high; _i++) { \ 92 if (rp[_i] > bcol) break; \ 93 if (rp[_i] == bcol) { \ 94 bap = ap + bs2*_i + bs*cidx + ridx; \ 95 if (addv == ADD_VALUES) *bap += value; \ 96 else *bap = value; \ 97 goto a_noinsert; \ 98 } \ 99 } \ 100 if (a->nonew == 1) goto a_noinsert; \ 101 else if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 102 if (nrow >= rmax) { \ 103 /* there is no extra room in row, therefore enlarge */ \ 104 PetscInt new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 105 MatScalar *new_a; \ 106 \ 107 if (a->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 108 \ 109 /* malloc new storage space */ \ 110 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(PetscInt); \ 111 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 112 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 113 new_i = new_j + new_nz; \ 114 \ 115 /* copy over old data into new slots */ \ 116 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 117 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 118 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 119 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 120 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 121 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 122 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 123 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 124 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 125 /* free up old matrix storage */ \ 126 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 127 if (!a->singlemalloc) { \ 128 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 129 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 130 } \ 131 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 132 a->singlemalloc = PETSC_TRUE; \ 133 \ 134 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 135 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 136 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 137 a->maxnz += bs2*CHUNKSIZE; \ 138 a->reallocs++; \ 139 a->nz++; \ 140 } \ 141 N = nrow++ - 1; \ 142 /* shift up all the later entries in this row */ \ 143 for (ii=N; ii>=_i; ii--) { \ 144 rp[ii+1] = rp[ii]; \ 145 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 146 } \ 147 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 148 rp[_i] = bcol; \ 149 ap[bs2*_i + bs*cidx + ridx] = value; \ 150 a_noinsert:; \ 151 ailen[brow] = nrow; \ 152 } 153 #ifndef MatSetValues_SeqBAIJ_B_Private 154 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 155 { \ 156 brow = row/bs; \ 157 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 158 rmax = bimax[brow]; nrow = bilen[brow]; \ 159 bcol = col/bs; \ 160 ridx = row % bs; cidx = col % bs; \ 161 low = 0; high = nrow; \ 162 while (high-low > 3) { \ 163 t = (low+high)/2; \ 164 if (rp[t] > bcol) high = t; \ 165 else low = t; \ 166 } \ 167 for (_i=low; _i<high; _i++) { \ 168 if (rp[_i] > bcol) break; \ 169 if (rp[_i] == bcol) { \ 170 bap = ap + bs2*_i + bs*cidx + ridx; \ 171 if (addv == ADD_VALUES) *bap += value; \ 172 else *bap = value; \ 173 goto b_noinsert; \ 174 } \ 175 } \ 176 if (b->nonew == 1) goto b_noinsert; \ 177 else if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 178 if (nrow >= rmax) { \ 179 /* there is no extra room in row, therefore enlarge */ \ 180 PetscInt new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 181 MatScalar *new_a; \ 182 \ 183 if (b->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 184 \ 185 /* malloc new storage space */ \ 186 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(PetscInt); \ 187 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 188 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 189 new_i = new_j + new_nz; \ 190 \ 191 /* copy over old data into new slots */ \ 192 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 193 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 194 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 195 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 196 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 197 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 198 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 199 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 200 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 201 /* free up old matrix storage */ \ 202 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 203 if (!b->singlemalloc) { \ 204 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 205 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 206 } \ 207 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 208 b->singlemalloc = PETSC_TRUE; \ 209 \ 210 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 211 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 212 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 213 b->maxnz += bs2*CHUNKSIZE; \ 214 b->reallocs++; \ 215 b->nz++; \ 216 } \ 217 N = nrow++ - 1; \ 218 /* shift up all the later entries in this row */ \ 219 for (ii=N; ii>=_i; ii--) { \ 220 rp[ii+1] = rp[ii]; \ 221 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 222 } \ 223 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 224 rp[_i] = bcol; \ 225 ap[bs2*_i + bs*cidx + ridx] = value; \ 226 b_noinsert:; \ 227 bilen[brow] = nrow; \ 228 } 229 #endif 230 231 #if defined(PETSC_USE_MAT_SINGLE) 232 #undef __FUNCT__ 233 #define __FUNCT__ "MatSetValues_MPISBAIJ" 234 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 235 { 236 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 237 PetscErrorCode ierr; 238 PetscInt i,N = m*n; 239 MatScalar *vsingle; 240 241 PetscFunctionBegin; 242 if (N > b->setvalueslen) { 243 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 244 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 245 b->setvalueslen = N; 246 } 247 vsingle = b->setvaluescopy; 248 249 for (i=0; i<N; i++) { 250 vsingle[i] = v[i]; 251 } 252 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 258 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 259 { 260 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 261 PetscErrorCode ierr; 262 PetscInt i,N = m*n*b->bs2; 263 MatScalar *vsingle; 264 265 PetscFunctionBegin; 266 if (N > b->setvalueslen) { 267 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 268 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 269 b->setvalueslen = N; 270 } 271 vsingle = b->setvaluescopy; 272 for (i=0; i<N; i++) { 273 vsingle[i] = v[i]; 274 } 275 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 276 PetscFunctionReturn(0); 277 } 278 279 #undef __FUNCT__ 280 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT" 281 PetscErrorCode MatSetValues_MPISBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 282 { 283 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 284 PetscErrorCode ierr; 285 PetscInt i,N = m*n; 286 MatScalar *vsingle; 287 288 PetscFunctionBegin; 289 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 290 /* PetscFunctionReturn(0); */ 291 } 292 293 #undef __FUNCT__ 294 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT" 295 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 296 { 297 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 298 PetscErrorCode ierr; 299 PetscInt i,N = m*n*b->bs2; 300 MatScalar *vsingle; 301 302 PetscFunctionBegin; 303 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 304 /* PetscFunctionReturn(0); */ 305 } 306 #endif 307 308 /* Only add/insert a(i,j) with i<=j (blocks). 309 Any a(i,j) with i>j input by user is ingored. 310 */ 311 #undef __FUNCT__ 312 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 313 PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 314 { 315 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 316 MatScalar value; 317 PetscTruth roworiented = baij->roworiented; 318 PetscErrorCode ierr; 319 PetscInt i,j,row,col; 320 PetscInt rstart_orig=baij->rstart_bs; 321 PetscInt rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 322 PetscInt cend_orig=baij->cend_bs,bs=mat->bs; 323 324 /* Some Variables required in the macro */ 325 Mat A = baij->A; 326 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 327 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 328 MatScalar *aa=a->a; 329 330 Mat B = baij->B; 331 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 332 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 333 MatScalar *ba=b->a; 334 335 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 336 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 337 MatScalar *ap,*bap; 338 339 /* for stash */ 340 PetscInt n_loc, *in_loc=0; 341 MatScalar *v_loc=0; 342 343 PetscFunctionBegin; 344 345 if(!baij->donotstash){ 346 ierr = PetscMalloc(n*sizeof(PetscInt),&in_loc);CHKERRQ(ierr); 347 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 348 } 349 350 for (i=0; i<m; i++) { 351 if (im[i] < 0) continue; 352 #if defined(PETSC_USE_BOPT_g) 353 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->M-1); 354 #endif 355 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 356 row = im[i] - rstart_orig; /* local row index */ 357 for (j=0; j<n; j++) { 358 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 359 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 360 col = in[j] - cstart_orig; /* local col index */ 361 brow = row/bs; bcol = col/bs; 362 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 363 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 364 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 365 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 366 } else if (in[j] < 0) continue; 367 #if defined(PETSC_USE_BOPT_g) 368 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->N-1);} 369 #endif 370 else { /* off-diag entry (B) */ 371 if (mat->was_assembled) { 372 if (!baij->colmap) { 373 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 374 } 375 #if defined (PETSC_USE_CTABLE) 376 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 377 col = col - 1; 378 #else 379 col = baij->colmap[in[j]/bs] - 1; 380 #endif 381 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 382 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 383 col = in[j]; 384 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 385 B = baij->B; 386 b = (Mat_SeqBAIJ*)(B)->data; 387 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 388 ba=b->a; 389 } else col += in[j]%bs; 390 } else col = in[j]; 391 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 392 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 393 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 394 } 395 } 396 } else { /* off processor entry */ 397 if (!baij->donotstash) { 398 n_loc = 0; 399 for (j=0; j<n; j++){ 400 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 401 in_loc[n_loc] = in[j]; 402 if (roworiented) { 403 v_loc[n_loc] = v[i*n+j]; 404 } else { 405 v_loc[n_loc] = v[j*m+i]; 406 } 407 n_loc++; 408 } 409 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 410 } 411 } 412 } 413 414 if(!baij->donotstash){ 415 ierr = PetscFree(in_loc);CHKERRQ(ierr); 416 ierr = PetscFree(v_loc);CHKERRQ(ierr); 417 } 418 PetscFunctionReturn(0); 419 } 420 421 #undef __FUNCT__ 422 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 423 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 424 { 425 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 426 const MatScalar *value; 427 MatScalar *barray=baij->barray; 428 PetscTruth roworiented = baij->roworiented; 429 PetscErrorCode ierr; 430 PetscInt i,j,ii,jj,row,col,rstart=baij->rstart; 431 PetscInt rend=baij->rend,cstart=baij->cstart,stepval; 432 PetscInt cend=baij->cend,bs=mat->bs,bs2=baij->bs2; 433 434 PetscFunctionBegin; 435 if(!barray) { 436 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 437 baij->barray = barray; 438 } 439 440 if (roworiented) { 441 stepval = (n-1)*bs; 442 } else { 443 stepval = (m-1)*bs; 444 } 445 for (i=0; i<m; i++) { 446 if (im[i] < 0) continue; 447 #if defined(PETSC_USE_BOPT_g) 448 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 449 #endif 450 if (im[i] >= rstart && im[i] < rend) { 451 row = im[i] - rstart; 452 for (j=0; j<n; j++) { 453 /* If NumCol = 1 then a copy is not required */ 454 if ((roworiented) && (n == 1)) { 455 barray = (MatScalar*) v + i*bs2; 456 } else if((!roworiented) && (m == 1)) { 457 barray = (MatScalar*) v + j*bs2; 458 } else { /* Here a copy is required */ 459 if (roworiented) { 460 value = v + i*(stepval+bs)*bs + j*bs; 461 } else { 462 value = v + j*(stepval+bs)*bs + i*bs; 463 } 464 for (ii=0; ii<bs; ii++,value+=stepval) { 465 for (jj=0; jj<bs; jj++) { 466 *barray++ = *value++; 467 } 468 } 469 barray -=bs2; 470 } 471 472 if (in[j] >= cstart && in[j] < cend){ 473 col = in[j] - cstart; 474 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 475 } 476 else if (in[j] < 0) continue; 477 #if defined(PETSC_USE_BOPT_g) 478 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 479 #endif 480 else { 481 if (mat->was_assembled) { 482 if (!baij->colmap) { 483 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 484 } 485 486 #if defined(PETSC_USE_BOPT_g) 487 #if defined (PETSC_USE_CTABLE) 488 { PetscInt data; 489 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 490 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 491 } 492 #else 493 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 494 #endif 495 #endif 496 #if defined (PETSC_USE_CTABLE) 497 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 498 col = (col - 1)/bs; 499 #else 500 col = (baij->colmap[in[j]] - 1)/bs; 501 #endif 502 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 503 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 504 col = in[j]; 505 } 506 } 507 else col = in[j]; 508 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 509 } 510 } 511 } else { 512 if (!baij->donotstash) { 513 if (roworiented) { 514 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 515 } else { 516 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 517 } 518 } 519 } 520 } 521 PetscFunctionReturn(0); 522 } 523 524 #define HASH_KEY 0.6180339887 525 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 526 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 527 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 528 #undef __FUNCT__ 529 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT_MatScalar" 530 PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 531 { 532 PetscFunctionBegin; 533 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 534 /* PetscFunctionReturn(0); */ 535 } 536 537 #undef __FUNCT__ 538 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 539 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 540 { 541 PetscFunctionBegin; 542 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 543 /* PetscFunctionReturn(0); */ 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatGetValues_MPISBAIJ" 548 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 549 { 550 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 551 PetscErrorCode ierr; 552 PetscInt bs=mat->bs,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 553 PetscInt bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 554 555 PetscFunctionBegin; 556 for (i=0; i<m; i++) { 557 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); 558 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->M-1); 559 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 560 row = idxm[i] - bsrstart; 561 for (j=0; j<n; j++) { 562 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); 563 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->N-1); 564 if (idxn[j] >= bscstart && idxn[j] < bscend){ 565 col = idxn[j] - bscstart; 566 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 567 } else { 568 if (!baij->colmap) { 569 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 570 } 571 #if defined (PETSC_USE_CTABLE) 572 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 573 data --; 574 #else 575 data = baij->colmap[idxn[j]/bs]-1; 576 #endif 577 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 578 else { 579 col = data + idxn[j]%bs; 580 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 581 } 582 } 583 } 584 } else { 585 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 586 } 587 } 588 PetscFunctionReturn(0); 589 } 590 591 #undef __FUNCT__ 592 #define __FUNCT__ "MatNorm_MPISBAIJ" 593 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 594 { 595 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 596 PetscErrorCode ierr; 597 PetscReal sum[2],*lnorm2; 598 599 PetscFunctionBegin; 600 if (baij->size == 1) { 601 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 602 } else { 603 if (type == NORM_FROBENIUS) { 604 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 605 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 606 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 607 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 608 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 609 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 610 *norm = sqrt(sum[0] + 2*sum[1]); 611 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 612 } else { 613 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 614 } 615 } 616 PetscFunctionReturn(0); 617 } 618 619 /* 620 Creates the hash table, and sets the table 621 This table is created only once. 622 If new entried need to be added to the matrix 623 then the hash table has to be destroyed and 624 recreated. 625 */ 626 #undef __FUNCT__ 627 #define __FUNCT__ "MatCreateHashTable_MPISBAIJ_Private" 628 PetscErrorCode MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 629 { 630 PetscFunctionBegin; 631 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 632 /* PetscFunctionReturn(0); */ 633 } 634 635 #undef __FUNCT__ 636 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 637 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 638 { 639 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 640 PetscErrorCode ierr; 641 PetscInt nstash,reallocs; 642 InsertMode addv; 643 644 PetscFunctionBegin; 645 if (baij->donotstash) { 646 PetscFunctionReturn(0); 647 } 648 649 /* make sure all processors are either in INSERTMODE or ADDMODE */ 650 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 651 if (addv == (ADD_VALUES|INSERT_VALUES)) { 652 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 653 } 654 mat->insertmode = addv; /* in case this processor had no cache */ 655 656 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 657 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 658 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 659 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %D entries,uses %D mallocs.\n",nstash,reallocs); 660 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 661 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs); 662 PetscFunctionReturn(0); 663 } 664 665 #undef __FUNCT__ 666 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 667 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 668 { 669 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 670 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 671 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 672 PetscErrorCode ierr; 673 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 674 PetscInt *row,*col,other_disassembled; 675 PetscMPIInt n; 676 PetscTruth r1,r2,r3; 677 MatScalar *val; 678 InsertMode addv = mat->insertmode; 679 680 PetscFunctionBegin; 681 682 if (!baij->donotstash) { 683 while (1) { 684 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 685 if (!flg) break; 686 687 for (i=0; i<n;) { 688 /* Now identify the consecutive vals belonging to the same row */ 689 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 690 if (j < n) ncols = j-i; 691 else ncols = n-i; 692 /* Now assemble all these values with a single function call */ 693 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 694 i = j; 695 } 696 } 697 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 698 /* Now process the block-stash. Since the values are stashed column-oriented, 699 set the roworiented flag to column oriented, and after MatSetValues() 700 restore the original flags */ 701 r1 = baij->roworiented; 702 r2 = a->roworiented; 703 r3 = b->roworiented; 704 baij->roworiented = PETSC_FALSE; 705 a->roworiented = PETSC_FALSE; 706 b->roworiented = PETSC_FALSE; 707 while (1) { 708 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 709 if (!flg) break; 710 711 for (i=0; i<n;) { 712 /* Now identify the consecutive vals belonging to the same row */ 713 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 714 if (j < n) ncols = j-i; 715 else ncols = n-i; 716 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 717 i = j; 718 } 719 } 720 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 721 baij->roworiented = r1; 722 a->roworiented = r2; 723 b->roworiented = r3; 724 } 725 726 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 727 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 728 729 /* determine if any processor has disassembled, if so we must 730 also disassemble ourselfs, in order that we may reassemble. */ 731 /* 732 if nonzero structure of submatrix B cannot change then we know that 733 no processor disassembled thus we can skip this stuff 734 */ 735 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 736 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 737 if (mat->was_assembled && !other_disassembled) { 738 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 739 } 740 } 741 742 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 743 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 744 } 745 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 746 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 747 748 #if defined(PETSC_USE_BOPT_g) 749 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 750 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 751 baij->ht_total_ct = 0; 752 baij->ht_insert_ct = 0; 753 } 754 #endif 755 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 756 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 757 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 758 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 759 } 760 761 if (baij->rowvalues) { 762 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 763 baij->rowvalues = 0; 764 } 765 766 PetscFunctionReturn(0); 767 } 768 769 #undef __FUNCT__ 770 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 771 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 772 { 773 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 774 PetscErrorCode ierr; 775 PetscInt bs = mat->bs; 776 PetscMPIInt size = baij->size,rank = baij->rank; 777 PetscTruth iascii,isdraw; 778 PetscViewer sviewer; 779 PetscViewerFormat format; 780 781 PetscFunctionBegin; 782 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 783 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 784 if (iascii) { 785 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 786 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 787 MatInfo info; 788 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 789 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 790 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 791 rank,mat->m,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 792 mat->bs,(PetscInt)info.memory);CHKERRQ(ierr); 793 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 794 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 795 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 796 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 797 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 798 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 799 PetscFunctionReturn(0); 800 } else if (format == PETSC_VIEWER_ASCII_INFO) { 801 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 802 PetscFunctionReturn(0); 803 } 804 } 805 806 if (isdraw) { 807 PetscDraw draw; 808 PetscTruth isnull; 809 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 810 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 811 } 812 813 if (size == 1) { 814 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 815 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 816 } else { 817 /* assemble the entire matrix onto first processor. */ 818 Mat A; 819 Mat_SeqSBAIJ *Aloc; 820 Mat_SeqBAIJ *Bloc; 821 PetscInt M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 822 MatScalar *a; 823 824 /* Should this be the same type as mat? */ 825 if (!rank) { 826 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 827 } else { 828 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 829 } 830 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 831 ierr = MatMPISBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 832 PetscLogObjectParent(mat,A); 833 834 /* copy over the A part */ 835 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 836 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 837 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 838 839 for (i=0; i<mbs; i++) { 840 rvals[0] = bs*(baij->rstart + i); 841 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 842 for (j=ai[i]; j<ai[i+1]; j++) { 843 col = (baij->cstart+aj[j])*bs; 844 for (k=0; k<bs; k++) { 845 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 846 col++; a += bs; 847 } 848 } 849 } 850 /* copy over the B part */ 851 Bloc = (Mat_SeqBAIJ*)baij->B->data; 852 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 853 for (i=0; i<mbs; i++) { 854 rvals[0] = bs*(baij->rstart + i); 855 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 856 for (j=ai[i]; j<ai[i+1]; j++) { 857 col = baij->garray[aj[j]]*bs; 858 for (k=0; k<bs; k++) { 859 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 860 col++; a += bs; 861 } 862 } 863 } 864 ierr = PetscFree(rvals);CHKERRQ(ierr); 865 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 866 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 867 /* 868 Everyone has to call to draw the matrix since the graphics waits are 869 synchronized across all processors that share the PetscDraw object 870 */ 871 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 872 if (!rank) { 873 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 874 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 875 } 876 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 877 ierr = MatDestroy(A);CHKERRQ(ierr); 878 } 879 PetscFunctionReturn(0); 880 } 881 882 #undef __FUNCT__ 883 #define __FUNCT__ "MatView_MPISBAIJ" 884 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 885 { 886 PetscErrorCode ierr; 887 PetscTruth iascii,isdraw,issocket,isbinary; 888 889 PetscFunctionBegin; 890 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 891 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 892 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 893 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 894 if (iascii || isdraw || issocket || isbinary) { 895 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 896 } else { 897 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 898 } 899 PetscFunctionReturn(0); 900 } 901 902 #undef __FUNCT__ 903 #define __FUNCT__ "MatDestroy_MPISBAIJ" 904 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 905 { 906 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 907 PetscErrorCode ierr; 908 909 PetscFunctionBegin; 910 #if defined(PETSC_USE_LOG) 911 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 912 #endif 913 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 914 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 915 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 916 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 917 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 918 #if defined (PETSC_USE_CTABLE) 919 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 920 #else 921 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 922 #endif 923 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 924 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 925 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 926 if (baij->slvec0) { 927 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 928 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 929 } 930 if (baij->slvec1) { 931 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 932 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 933 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 934 } 935 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 936 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 937 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 938 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 939 #if defined(PETSC_USE_MAT_SINGLE) 940 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 941 #endif 942 ierr = PetscFree(baij);CHKERRQ(ierr); 943 944 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 945 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 946 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 947 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatMult_MPISBAIJ" 953 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 954 { 955 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 956 PetscErrorCode ierr; 957 PetscInt nt,mbs=a->mbs,bs=A->bs; 958 PetscScalar *x,*from,zero=0.0; 959 960 PetscFunctionBegin; 961 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 962 if (nt != A->n) { 963 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 964 } 965 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 966 if (nt != A->m) { 967 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 968 } 969 970 /* diagonal part */ 971 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 972 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 973 974 /* subdiagonal part */ 975 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 976 977 /* copy x into the vec slvec0 */ 978 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 979 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 980 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 981 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 982 983 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 984 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 985 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 986 987 /* supperdiagonal part */ 988 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 989 990 PetscFunctionReturn(0); 991 } 992 993 #undef __FUNCT__ 994 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 995 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 996 { 997 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 998 PetscErrorCode ierr; 999 PetscInt nt; 1000 1001 PetscFunctionBegin; 1002 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1003 if (nt != A->n) { 1004 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1005 } 1006 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1007 if (nt != A->m) { 1008 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1009 } 1010 1011 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1012 /* do diagonal part */ 1013 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1014 /* do supperdiagonal part */ 1015 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1016 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1017 /* do subdiagonal part */ 1018 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1019 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1020 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1021 1022 PetscFunctionReturn(0); 1023 } 1024 1025 #undef __FUNCT__ 1026 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 1027 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1028 { 1029 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1030 PetscErrorCode ierr; 1031 PetscInt mbs=a->mbs,bs=A->bs; 1032 PetscScalar *x,*from,zero=0.0; 1033 1034 PetscFunctionBegin; 1035 /* 1036 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 1037 PetscSynchronizedFlush(A->comm); 1038 */ 1039 /* diagonal part */ 1040 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 1041 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 1042 1043 /* subdiagonal part */ 1044 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 1045 1046 /* copy x into the vec slvec0 */ 1047 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 1048 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1049 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1050 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1051 1052 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1053 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1054 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1055 1056 /* supperdiagonal part */ 1057 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 1058 1059 PetscFunctionReturn(0); 1060 } 1061 1062 #undef __FUNCT__ 1063 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 1064 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 1065 { 1066 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1067 PetscErrorCode ierr; 1068 1069 PetscFunctionBegin; 1070 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1071 /* do diagonal part */ 1072 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1073 /* do supperdiagonal part */ 1074 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1075 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1076 1077 /* do subdiagonal part */ 1078 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1079 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1080 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1081 1082 PetscFunctionReturn(0); 1083 } 1084 1085 #undef __FUNCT__ 1086 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1087 PetscErrorCode MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1088 { 1089 PetscErrorCode ierr; 1090 1091 PetscFunctionBegin; 1092 ierr = MatMult(A,xx,yy);CHKERRQ(ierr); 1093 PetscFunctionReturn(0); 1094 } 1095 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1098 PetscErrorCode MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1099 { 1100 PetscErrorCode ierr; 1101 1102 PetscFunctionBegin; 1103 ierr = MatMultAdd(A,xx,yy,zz);CHKERRQ(ierr); 1104 PetscFunctionReturn(0); 1105 } 1106 1107 /* 1108 This only works correctly for square matrices where the subblock A->A is the 1109 diagonal block 1110 */ 1111 #undef __FUNCT__ 1112 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1113 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1114 { 1115 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1116 PetscErrorCode ierr; 1117 1118 PetscFunctionBegin; 1119 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1120 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1121 PetscFunctionReturn(0); 1122 } 1123 1124 #undef __FUNCT__ 1125 #define __FUNCT__ "MatScale_MPISBAIJ" 1126 PetscErrorCode MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1127 { 1128 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1129 PetscErrorCode ierr; 1130 1131 PetscFunctionBegin; 1132 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1133 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1134 PetscFunctionReturn(0); 1135 } 1136 1137 #undef __FUNCT__ 1138 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1139 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1140 { 1141 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1142 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1143 PetscErrorCode ierr; 1144 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1145 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1146 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1147 1148 PetscFunctionBegin; 1149 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1150 mat->getrowactive = PETSC_TRUE; 1151 1152 if (!mat->rowvalues && (idx || v)) { 1153 /* 1154 allocate enough space to hold information from the longest row. 1155 */ 1156 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1157 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1158 PetscInt max = 1,mbs = mat->mbs,tmp; 1159 for (i=0; i<mbs; i++) { 1160 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1161 if (max < tmp) { max = tmp; } 1162 } 1163 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1164 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1165 } 1166 1167 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1168 lrow = row - brstart; /* local row index */ 1169 1170 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1171 if (!v) {pvA = 0; pvB = 0;} 1172 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1173 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1174 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1175 nztot = nzA + nzB; 1176 1177 cmap = mat->garray; 1178 if (v || idx) { 1179 if (nztot) { 1180 /* Sort by increasing column numbers, assuming A and B already sorted */ 1181 PetscInt imark = -1; 1182 if (v) { 1183 *v = v_p = mat->rowvalues; 1184 for (i=0; i<nzB; i++) { 1185 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1186 else break; 1187 } 1188 imark = i; 1189 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1190 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1191 } 1192 if (idx) { 1193 *idx = idx_p = mat->rowindices; 1194 if (imark > -1) { 1195 for (i=0; i<imark; i++) { 1196 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1197 } 1198 } else { 1199 for (i=0; i<nzB; i++) { 1200 if (cmap[cworkB[i]/bs] < cstart) 1201 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1202 else break; 1203 } 1204 imark = i; 1205 } 1206 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1207 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1208 } 1209 } else { 1210 if (idx) *idx = 0; 1211 if (v) *v = 0; 1212 } 1213 } 1214 *nz = nztot; 1215 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1216 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1217 PetscFunctionReturn(0); 1218 } 1219 1220 #undef __FUNCT__ 1221 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1222 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1223 { 1224 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1225 1226 PetscFunctionBegin; 1227 if (baij->getrowactive == PETSC_FALSE) { 1228 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1229 } 1230 baij->getrowactive = PETSC_FALSE; 1231 PetscFunctionReturn(0); 1232 } 1233 1234 #undef __FUNCT__ 1235 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1236 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1237 { 1238 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1239 PetscErrorCode ierr; 1240 1241 PetscFunctionBegin; 1242 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1243 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1244 PetscFunctionReturn(0); 1245 } 1246 1247 #undef __FUNCT__ 1248 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1249 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1250 { 1251 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1252 Mat A = a->A,B = a->B; 1253 PetscErrorCode ierr; 1254 PetscReal isend[5],irecv[5]; 1255 1256 PetscFunctionBegin; 1257 info->block_size = (PetscReal)matin->bs; 1258 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1259 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1260 isend[3] = info->memory; isend[4] = info->mallocs; 1261 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1262 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1263 isend[3] += info->memory; isend[4] += info->mallocs; 1264 if (flag == MAT_LOCAL) { 1265 info->nz_used = isend[0]; 1266 info->nz_allocated = isend[1]; 1267 info->nz_unneeded = isend[2]; 1268 info->memory = isend[3]; 1269 info->mallocs = isend[4]; 1270 } else if (flag == MAT_GLOBAL_MAX) { 1271 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1272 info->nz_used = irecv[0]; 1273 info->nz_allocated = irecv[1]; 1274 info->nz_unneeded = irecv[2]; 1275 info->memory = irecv[3]; 1276 info->mallocs = irecv[4]; 1277 } else if (flag == MAT_GLOBAL_SUM) { 1278 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1279 info->nz_used = irecv[0]; 1280 info->nz_allocated = irecv[1]; 1281 info->nz_unneeded = irecv[2]; 1282 info->memory = irecv[3]; 1283 info->mallocs = irecv[4]; 1284 } else { 1285 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1286 } 1287 info->rows_global = (PetscReal)A->M; 1288 info->columns_global = (PetscReal)A->N; 1289 info->rows_local = (PetscReal)A->m; 1290 info->columns_local = (PetscReal)A->N; 1291 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1292 info->fill_ratio_needed = 0; 1293 info->factor_mallocs = 0; 1294 PetscFunctionReturn(0); 1295 } 1296 1297 #undef __FUNCT__ 1298 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1299 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1300 { 1301 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1302 PetscErrorCode ierr; 1303 1304 PetscFunctionBegin; 1305 switch (op) { 1306 case MAT_NO_NEW_NONZERO_LOCATIONS: 1307 case MAT_YES_NEW_NONZERO_LOCATIONS: 1308 case MAT_COLUMNS_UNSORTED: 1309 case MAT_COLUMNS_SORTED: 1310 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1311 case MAT_KEEP_ZEROED_ROWS: 1312 case MAT_NEW_NONZERO_LOCATION_ERR: 1313 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1314 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1315 break; 1316 case MAT_ROW_ORIENTED: 1317 a->roworiented = PETSC_TRUE; 1318 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1319 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1320 break; 1321 case MAT_ROWS_SORTED: 1322 case MAT_ROWS_UNSORTED: 1323 case MAT_YES_NEW_DIAGONALS: 1324 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1325 break; 1326 case MAT_COLUMN_ORIENTED: 1327 a->roworiented = PETSC_FALSE; 1328 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1329 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1330 break; 1331 case MAT_IGNORE_OFF_PROC_ENTRIES: 1332 a->donotstash = PETSC_TRUE; 1333 break; 1334 case MAT_NO_NEW_DIAGONALS: 1335 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1336 case MAT_USE_HASH_TABLE: 1337 a->ht_flag = PETSC_TRUE; 1338 break; 1339 case MAT_NOT_SYMMETRIC: 1340 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1341 case MAT_HERMITIAN: 1342 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1343 case MAT_SYMMETRIC: 1344 case MAT_STRUCTURALLY_SYMMETRIC: 1345 case MAT_NOT_HERMITIAN: 1346 case MAT_SYMMETRY_ETERNAL: 1347 case MAT_NOT_SYMMETRY_ETERNAL: 1348 break; 1349 default: 1350 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1351 } 1352 PetscFunctionReturn(0); 1353 } 1354 1355 #undef __FUNCT__ 1356 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1357 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1358 { 1359 PetscErrorCode ierr; 1360 PetscFunctionBegin; 1361 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNCT__ 1366 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1367 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1368 { 1369 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1370 Mat a = baij->A,b = baij->B; 1371 PetscErrorCode ierr; 1372 PetscInt s1,s2,s3; 1373 1374 PetscFunctionBegin; 1375 if (ll != rr) { 1376 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1377 } 1378 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1379 if (rr) { 1380 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1381 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1382 /* Overlap communication with computation. */ 1383 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1384 /*} if (ll) { */ 1385 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1386 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1387 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1388 /* } */ 1389 /* scale the diagonal block */ 1390 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1391 1392 /* if (rr) { */ 1393 /* Do a scatter end and then right scale the off-diagonal block */ 1394 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1395 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1396 } 1397 1398 PetscFunctionReturn(0); 1399 } 1400 1401 #undef __FUNCT__ 1402 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1403 PetscErrorCode MatZeroRows_MPISBAIJ(Mat A,IS is,const PetscScalar *diag) 1404 { 1405 PetscFunctionBegin; 1406 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1407 } 1408 1409 #undef __FUNCT__ 1410 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1411 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1412 { 1413 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1414 MPI_Comm comm = A->comm; 1415 static PetscTruth called = PETSC_FALSE; 1416 PetscErrorCode ierr; 1417 1418 PetscFunctionBegin; 1419 if (!a->rank) { 1420 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1421 } 1422 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1423 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1424 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1425 PetscFunctionReturn(0); 1426 } 1427 1428 #undef __FUNCT__ 1429 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1430 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1431 { 1432 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1433 PetscErrorCode ierr; 1434 1435 PetscFunctionBegin; 1436 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1437 PetscFunctionReturn(0); 1438 } 1439 1440 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1441 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatEqual_MPISBAIJ" 1444 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1445 { 1446 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1447 Mat a,b,c,d; 1448 PetscTruth flg; 1449 PetscErrorCode ierr; 1450 1451 PetscFunctionBegin; 1452 a = matA->A; b = matA->B; 1453 c = matB->A; d = matB->B; 1454 1455 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1456 if (flg == PETSC_TRUE) { 1457 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1458 } 1459 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1460 PetscFunctionReturn(0); 1461 } 1462 1463 #undef __FUNCT__ 1464 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1465 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1466 { 1467 PetscErrorCode ierr; 1468 1469 PetscFunctionBegin; 1470 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1471 PetscFunctionReturn(0); 1472 } 1473 1474 #undef __FUNCT__ 1475 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1476 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1477 { 1478 PetscErrorCode ierr; 1479 PetscInt i; 1480 PetscTruth flg; 1481 1482 PetscFunctionBegin; 1483 for (i=0; i<n; i++) { 1484 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1485 if (!flg) { 1486 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1487 } 1488 } 1489 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1490 PetscFunctionReturn(0); 1491 } 1492 1493 1494 /* -------------------------------------------------------------------*/ 1495 static struct _MatOps MatOps_Values = { 1496 MatSetValues_MPISBAIJ, 1497 MatGetRow_MPISBAIJ, 1498 MatRestoreRow_MPISBAIJ, 1499 MatMult_MPISBAIJ, 1500 /* 4*/ MatMultAdd_MPISBAIJ, 1501 MatMultTranspose_MPISBAIJ, 1502 MatMultTransposeAdd_MPISBAIJ, 1503 0, 1504 0, 1505 0, 1506 /*10*/ 0, 1507 0, 1508 0, 1509 MatRelax_MPISBAIJ, 1510 MatTranspose_MPISBAIJ, 1511 /*15*/ MatGetInfo_MPISBAIJ, 1512 MatEqual_MPISBAIJ, 1513 MatGetDiagonal_MPISBAIJ, 1514 MatDiagonalScale_MPISBAIJ, 1515 MatNorm_MPISBAIJ, 1516 /*20*/ MatAssemblyBegin_MPISBAIJ, 1517 MatAssemblyEnd_MPISBAIJ, 1518 0, 1519 MatSetOption_MPISBAIJ, 1520 MatZeroEntries_MPISBAIJ, 1521 /*25*/ MatZeroRows_MPISBAIJ, 1522 0, 1523 0, 1524 0, 1525 0, 1526 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1527 0, 1528 0, 1529 0, 1530 0, 1531 /*35*/ MatDuplicate_MPISBAIJ, 1532 0, 1533 0, 1534 0, 1535 0, 1536 /*40*/ 0, 1537 MatGetSubMatrices_MPISBAIJ, 1538 MatIncreaseOverlap_MPISBAIJ, 1539 MatGetValues_MPISBAIJ, 1540 0, 1541 /*45*/ MatPrintHelp_MPISBAIJ, 1542 MatScale_MPISBAIJ, 1543 0, 1544 0, 1545 0, 1546 /*50*/ 0, 1547 0, 1548 0, 1549 0, 1550 0, 1551 /*55*/ 0, 1552 0, 1553 MatSetUnfactored_MPISBAIJ, 1554 0, 1555 MatSetValuesBlocked_MPISBAIJ, 1556 /*60*/ 0, 1557 0, 1558 0, 1559 MatGetPetscMaps_Petsc, 1560 0, 1561 /*65*/ 0, 1562 0, 1563 0, 1564 0, 1565 0, 1566 /*70*/ MatGetRowMax_MPISBAIJ, 1567 0, 1568 0, 1569 0, 1570 0, 1571 /*75*/ 0, 1572 0, 1573 0, 1574 0, 1575 0, 1576 /*80*/ 0, 1577 0, 1578 0, 1579 0, 1580 MatLoad_MPISBAIJ, 1581 /*85*/ 0, 1582 0, 1583 0, 1584 0, 1585 0, 1586 /*90*/ 0, 1587 0, 1588 0, 1589 0, 1590 0, 1591 /*95*/ 0, 1592 0, 1593 0, 1594 0}; 1595 1596 1597 EXTERN_C_BEGIN 1598 #undef __FUNCT__ 1599 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1600 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1601 { 1602 PetscFunctionBegin; 1603 *a = ((Mat_MPISBAIJ *)A->data)->A; 1604 *iscopy = PETSC_FALSE; 1605 PetscFunctionReturn(0); 1606 } 1607 EXTERN_C_END 1608 1609 EXTERN_C_BEGIN 1610 #undef __FUNCT__ 1611 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1612 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1613 { 1614 Mat_MPISBAIJ *b; 1615 PetscErrorCode ierr; 1616 PetscInt i,mbs,Mbs; 1617 1618 PetscFunctionBegin; 1619 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1620 1621 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1622 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1623 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1624 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1625 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1626 if (d_nnz) { 1627 for (i=0; i<B->m/bs; i++) { 1628 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]); 1629 } 1630 } 1631 if (o_nnz) { 1632 for (i=0; i<B->m/bs; i++) { 1633 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]); 1634 } 1635 } 1636 B->preallocated = PETSC_TRUE; 1637 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1638 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1639 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1640 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1641 1642 b = (Mat_MPISBAIJ*)B->data; 1643 mbs = B->m/bs; 1644 Mbs = B->M/bs; 1645 if (mbs*bs != B->m) { 1646 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1647 } 1648 1649 B->bs = bs; 1650 b->bs2 = bs*bs; 1651 b->mbs = mbs; 1652 b->nbs = mbs; 1653 b->Mbs = Mbs; 1654 b->Nbs = Mbs; 1655 1656 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 1657 b->rowners[0] = 0; 1658 for (i=2; i<=b->size; i++) { 1659 b->rowners[i] += b->rowners[i-1]; 1660 } 1661 b->rstart = b->rowners[b->rank]; 1662 b->rend = b->rowners[b->rank+1]; 1663 b->cstart = b->rstart; 1664 b->cend = b->rend; 1665 for (i=0; i<=b->size; i++) { 1666 b->rowners_bs[i] = b->rowners[i]*bs; 1667 } 1668 b->rstart_bs = b-> rstart*bs; 1669 b->rend_bs = b->rend*bs; 1670 1671 b->cstart_bs = b->cstart*bs; 1672 b->cend_bs = b->cend*bs; 1673 1674 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1675 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1676 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1677 PetscLogObjectParent(B,b->A); 1678 1679 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1680 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1681 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1682 PetscLogObjectParent(B,b->B); 1683 1684 /* build cache for off array entries formed */ 1685 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1686 1687 PetscFunctionReturn(0); 1688 } 1689 EXTERN_C_END 1690 1691 /*MC 1692 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1693 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1694 1695 Options Database Keys: 1696 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1697 1698 Level: beginner 1699 1700 .seealso: MatCreateMPISBAIJ 1701 M*/ 1702 1703 EXTERN_C_BEGIN 1704 #undef __FUNCT__ 1705 #define __FUNCT__ "MatCreate_MPISBAIJ" 1706 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1707 { 1708 Mat_MPISBAIJ *b; 1709 PetscErrorCode ierr; 1710 PetscTruth flg; 1711 1712 PetscFunctionBegin; 1713 1714 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1715 B->data = (void*)b; 1716 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1717 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1718 1719 B->ops->destroy = MatDestroy_MPISBAIJ; 1720 B->ops->view = MatView_MPISBAIJ; 1721 B->mapping = 0; 1722 B->factor = 0; 1723 B->assembled = PETSC_FALSE; 1724 1725 B->insertmode = NOT_SET_VALUES; 1726 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1727 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1728 1729 /* build local table of row and column ownerships */ 1730 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1731 b->cowners = b->rowners + b->size + 2; 1732 b->rowners_bs = b->cowners + b->size + 2; 1733 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1734 1735 /* build cache for off array entries formed */ 1736 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1737 b->donotstash = PETSC_FALSE; 1738 b->colmap = PETSC_NULL; 1739 b->garray = PETSC_NULL; 1740 b->roworiented = PETSC_TRUE; 1741 1742 #if defined(PETSC_USE_MAT_SINGLE) 1743 /* stuff for MatSetValues_XXX in single precision */ 1744 b->setvalueslen = 0; 1745 b->setvaluescopy = PETSC_NULL; 1746 #endif 1747 1748 /* stuff used in block assembly */ 1749 b->barray = 0; 1750 1751 /* stuff used for matrix vector multiply */ 1752 b->lvec = 0; 1753 b->Mvctx = 0; 1754 b->slvec0 = 0; 1755 b->slvec0b = 0; 1756 b->slvec1 = 0; 1757 b->slvec1a = 0; 1758 b->slvec1b = 0; 1759 b->sMvctx = 0; 1760 1761 /* stuff for MatGetRow() */ 1762 b->rowindices = 0; 1763 b->rowvalues = 0; 1764 b->getrowactive = PETSC_FALSE; 1765 1766 /* hash table stuff */ 1767 b->ht = 0; 1768 b->hd = 0; 1769 b->ht_size = 0; 1770 b->ht_flag = PETSC_FALSE; 1771 b->ht_fact = 0; 1772 b->ht_total_ct = 0; 1773 b->ht_insert_ct = 0; 1774 1775 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1776 if (flg) { 1777 PetscReal fact = 1.39; 1778 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1779 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1780 if (fact <= 1.0) fact = 1.39; 1781 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1782 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1783 } 1784 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1785 "MatStoreValues_MPISBAIJ", 1786 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1787 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1788 "MatRetrieveValues_MPISBAIJ", 1789 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1790 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1791 "MatGetDiagonalBlock_MPISBAIJ", 1792 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1793 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1794 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1795 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1796 B->symmetric = PETSC_TRUE; 1797 B->structurally_symmetric = PETSC_TRUE; 1798 B->symmetric_set = PETSC_TRUE; 1799 B->structurally_symmetric_set = PETSC_TRUE; 1800 PetscFunctionReturn(0); 1801 } 1802 EXTERN_C_END 1803 1804 /*MC 1805 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1806 1807 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1808 and MATMPISBAIJ otherwise. 1809 1810 Options Database Keys: 1811 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1812 1813 Level: beginner 1814 1815 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1816 M*/ 1817 1818 EXTERN_C_BEGIN 1819 #undef __FUNCT__ 1820 #define __FUNCT__ "MatCreate_SBAIJ" 1821 PetscErrorCode MatCreate_SBAIJ(Mat A) 1822 { 1823 PetscErrorCode ierr; 1824 PetscMPIInt size; 1825 1826 PetscFunctionBegin; 1827 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1828 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1829 if (size == 1) { 1830 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1831 } else { 1832 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1833 } 1834 PetscFunctionReturn(0); 1835 } 1836 EXTERN_C_END 1837 1838 #undef __FUNCT__ 1839 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1840 /*@C 1841 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1842 the user should preallocate the matrix storage by setting the parameters 1843 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1844 performance can be increased by more than a factor of 50. 1845 1846 Collective on Mat 1847 1848 Input Parameters: 1849 + A - the matrix 1850 . bs - size of blockk 1851 . d_nz - number of block nonzeros per block row in diagonal portion of local 1852 submatrix (same for all local rows) 1853 . d_nnz - array containing the number of block nonzeros in the various block rows 1854 in the upper triangular and diagonal part of the in diagonal portion of the local 1855 (possibly different for each block row) or PETSC_NULL. You must leave room 1856 for the diagonal entry even if it is zero. 1857 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1858 submatrix (same for all local rows). 1859 - o_nnz - array containing the number of nonzeros in the various block rows of the 1860 off-diagonal portion of the local submatrix (possibly different for 1861 each block row) or PETSC_NULL. 1862 1863 1864 Options Database Keys: 1865 . -mat_no_unroll - uses code that does not unroll the loops in the 1866 block calculations (much slower) 1867 . -mat_block_size - size of the blocks to use 1868 1869 Notes: 1870 1871 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1872 than it must be used on all processors that share the object for that argument. 1873 1874 If the *_nnz parameter is given then the *_nz parameter is ignored 1875 1876 Storage Information: 1877 For a square global matrix we define each processor's diagonal portion 1878 to be its local rows and the corresponding columns (a square submatrix); 1879 each processor's off-diagonal portion encompasses the remainder of the 1880 local matrix (a rectangular submatrix). 1881 1882 The user can specify preallocated storage for the diagonal part of 1883 the local submatrix with either d_nz or d_nnz (not both). Set 1884 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1885 memory allocation. Likewise, specify preallocated storage for the 1886 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1887 1888 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1889 the figure below we depict these three local rows and all columns (0-11). 1890 1891 .vb 1892 0 1 2 3 4 5 6 7 8 9 10 11 1893 ------------------- 1894 row 3 | o o o d d d o o o o o o 1895 row 4 | o o o d d d o o o o o o 1896 row 5 | o o o d d d o o o o o o 1897 ------------------- 1898 .ve 1899 1900 Thus, any entries in the d locations are stored in the d (diagonal) 1901 submatrix, and any entries in the o locations are stored in the 1902 o (off-diagonal) submatrix. Note that the d matrix is stored in 1903 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1904 1905 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1906 plus the diagonal part of the d matrix, 1907 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1908 In general, for PDE problems in which most nonzeros are near the diagonal, 1909 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1910 or you will get TERRIBLE performance; see the users' manual chapter on 1911 matrices. 1912 1913 Level: intermediate 1914 1915 .keywords: matrix, block, aij, compressed row, sparse, parallel 1916 1917 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1918 @*/ 1919 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1920 { 1921 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1922 1923 PetscFunctionBegin; 1924 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1925 if (f) { 1926 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1927 } 1928 PetscFunctionReturn(0); 1929 } 1930 1931 #undef __FUNCT__ 1932 #define __FUNCT__ "MatCreateMPISBAIJ" 1933 /*@C 1934 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1935 (block compressed row). For good matrix assembly performance 1936 the user should preallocate the matrix storage by setting the parameters 1937 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1938 performance can be increased by more than a factor of 50. 1939 1940 Collective on MPI_Comm 1941 1942 Input Parameters: 1943 + comm - MPI communicator 1944 . bs - size of blockk 1945 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1946 This value should be the same as the local size used in creating the 1947 y vector for the matrix-vector product y = Ax. 1948 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1949 This value should be the same as the local size used in creating the 1950 x vector for the matrix-vector product y = Ax. 1951 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1952 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1953 . d_nz - number of block nonzeros per block row in diagonal portion of local 1954 submatrix (same for all local rows) 1955 . d_nnz - array containing the number of block nonzeros in the various block rows 1956 in the upper triangular portion of the in diagonal portion of the local 1957 (possibly different for each block block row) or PETSC_NULL. 1958 You must leave room for the diagonal entry even if it is zero. 1959 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1960 submatrix (same for all local rows). 1961 - o_nnz - array containing the number of nonzeros in the various block rows of the 1962 off-diagonal portion of the local submatrix (possibly different for 1963 each block row) or PETSC_NULL. 1964 1965 Output Parameter: 1966 . A - the matrix 1967 1968 Options Database Keys: 1969 . -mat_no_unroll - uses code that does not unroll the loops in the 1970 block calculations (much slower) 1971 . -mat_block_size - size of the blocks to use 1972 . -mat_mpi - use the parallel matrix data structures even on one processor 1973 (defaults to using SeqBAIJ format on one processor) 1974 1975 Notes: 1976 The user MUST specify either the local or global matrix dimensions 1977 (possibly both). 1978 1979 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1980 than it must be used on all processors that share the object for that argument. 1981 1982 If the *_nnz parameter is given then the *_nz parameter is ignored 1983 1984 Storage Information: 1985 For a square global matrix we define each processor's diagonal portion 1986 to be its local rows and the corresponding columns (a square submatrix); 1987 each processor's off-diagonal portion encompasses the remainder of the 1988 local matrix (a rectangular submatrix). 1989 1990 The user can specify preallocated storage for the diagonal part of 1991 the local submatrix with either d_nz or d_nnz (not both). Set 1992 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1993 memory allocation. Likewise, specify preallocated storage for the 1994 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1995 1996 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1997 the figure below we depict these three local rows and all columns (0-11). 1998 1999 .vb 2000 0 1 2 3 4 5 6 7 8 9 10 11 2001 ------------------- 2002 row 3 | o o o d d d o o o o o o 2003 row 4 | o o o d d d o o o o o o 2004 row 5 | o o o d d d o o o o o o 2005 ------------------- 2006 .ve 2007 2008 Thus, any entries in the d locations are stored in the d (diagonal) 2009 submatrix, and any entries in the o locations are stored in the 2010 o (off-diagonal) submatrix. Note that the d matrix is stored in 2011 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2012 2013 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2014 plus the diagonal part of the d matrix, 2015 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2016 In general, for PDE problems in which most nonzeros are near the diagonal, 2017 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2018 or you will get TERRIBLE performance; see the users' manual chapter on 2019 matrices. 2020 2021 Level: intermediate 2022 2023 .keywords: matrix, block, aij, compressed row, sparse, parallel 2024 2025 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2026 @*/ 2027 2028 PetscErrorCode MatCreateMPISBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 2029 { 2030 PetscErrorCode ierr; 2031 PetscMPIInt size; 2032 2033 PetscFunctionBegin; 2034 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2035 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2036 if (size > 1) { 2037 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2038 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2039 } else { 2040 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2041 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2042 } 2043 PetscFunctionReturn(0); 2044 } 2045 2046 2047 #undef __FUNCT__ 2048 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2049 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2050 { 2051 Mat mat; 2052 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2053 PetscErrorCode ierr; 2054 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 2055 PetscScalar *array; 2056 2057 PetscFunctionBegin; 2058 *newmat = 0; 2059 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2060 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2061 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2062 2063 mat->factor = matin->factor; 2064 mat->preallocated = PETSC_TRUE; 2065 mat->assembled = PETSC_TRUE; 2066 mat->insertmode = NOT_SET_VALUES; 2067 2068 a = (Mat_MPISBAIJ*)mat->data; 2069 mat->bs = matin->bs; 2070 a->bs2 = oldmat->bs2; 2071 a->mbs = oldmat->mbs; 2072 a->nbs = oldmat->nbs; 2073 a->Mbs = oldmat->Mbs; 2074 a->Nbs = oldmat->Nbs; 2075 2076 a->rstart = oldmat->rstart; 2077 a->rend = oldmat->rend; 2078 a->cstart = oldmat->cstart; 2079 a->cend = oldmat->cend; 2080 a->size = oldmat->size; 2081 a->rank = oldmat->rank; 2082 a->donotstash = oldmat->donotstash; 2083 a->roworiented = oldmat->roworiented; 2084 a->rowindices = 0; 2085 a->rowvalues = 0; 2086 a->getrowactive = PETSC_FALSE; 2087 a->barray = 0; 2088 a->rstart_bs = oldmat->rstart_bs; 2089 a->rend_bs = oldmat->rend_bs; 2090 a->cstart_bs = oldmat->cstart_bs; 2091 a->cend_bs = oldmat->cend_bs; 2092 2093 /* hash table stuff */ 2094 a->ht = 0; 2095 a->hd = 0; 2096 a->ht_size = 0; 2097 a->ht_flag = oldmat->ht_flag; 2098 a->ht_fact = oldmat->ht_fact; 2099 a->ht_total_ct = 0; 2100 a->ht_insert_ct = 0; 2101 2102 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2103 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2104 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2105 if (oldmat->colmap) { 2106 #if defined (PETSC_USE_CTABLE) 2107 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2108 #else 2109 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2110 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 2111 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2112 #endif 2113 } else a->colmap = 0; 2114 2115 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2116 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2117 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 2118 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2119 } else a->garray = 0; 2120 2121 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2122 PetscLogObjectParent(mat,a->lvec); 2123 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2124 PetscLogObjectParent(mat,a->Mvctx); 2125 2126 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2127 PetscLogObjectParent(mat,a->slvec0); 2128 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2129 PetscLogObjectParent(mat,a->slvec1); 2130 2131 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2132 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2133 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2134 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2135 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2136 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2137 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2138 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2139 PetscLogObjectParent(mat,a->slvec0); 2140 PetscLogObjectParent(mat,a->slvec1); 2141 PetscLogObjectParent(mat,a->slvec0b); 2142 PetscLogObjectParent(mat,a->slvec1a); 2143 PetscLogObjectParent(mat,a->slvec1b); 2144 2145 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2146 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2147 a->sMvctx = oldmat->sMvctx; 2148 PetscLogObjectParent(mat,a->sMvctx); 2149 2150 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2151 PetscLogObjectParent(mat,a->A); 2152 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2153 PetscLogObjectParent(mat,a->B); 2154 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2155 *newmat = mat; 2156 PetscFunctionReturn(0); 2157 } 2158 2159 #include "petscsys.h" 2160 2161 #undef __FUNCT__ 2162 #define __FUNCT__ "MatLoad_MPISBAIJ" 2163 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2164 { 2165 Mat A; 2166 PetscErrorCode ierr; 2167 PetscInt i,nz,j,rstart,rend; 2168 PetscScalar *vals,*buf; 2169 MPI_Comm comm = ((PetscObject)viewer)->comm; 2170 MPI_Status status; 2171 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners; 2172 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2173 PetscInt *locrowlens,*procsnz = 0,jj,*mycols,*ibuf; 2174 PetscInt bs=1,Mbs,mbs,extra_rows; 2175 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2176 PetscInt dcount,kmax,k,nzcount,tmp; 2177 int fd; 2178 2179 PetscFunctionBegin; 2180 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2181 2182 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2183 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2184 if (!rank) { 2185 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2186 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2187 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2188 if (header[3] < 0) { 2189 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2190 } 2191 } 2192 2193 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2194 M = header[1]; N = header[2]; 2195 2196 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2197 2198 /* 2199 This code adds extra rows to make sure the number of rows is 2200 divisible by the blocksize 2201 */ 2202 Mbs = M/bs; 2203 extra_rows = bs - M + bs*(Mbs); 2204 if (extra_rows == bs) extra_rows = 0; 2205 else Mbs++; 2206 if (extra_rows &&!rank) { 2207 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2208 } 2209 2210 /* determine ownership of all rows */ 2211 mbs = Mbs/size + ((Mbs % size) > rank); 2212 m = mbs*bs; 2213 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2214 browners = rowners + size + 1; 2215 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2216 rowners[0] = 0; 2217 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2218 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2219 rstart = rowners[rank]; 2220 rend = rowners[rank+1]; 2221 2222 /* distribute row lengths to all processors */ 2223 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2224 if (!rank) { 2225 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2226 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2227 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2228 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2229 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2230 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2231 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2232 } else { 2233 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2234 } 2235 2236 if (!rank) { /* procs[0] */ 2237 /* calculate the number of nonzeros on each processor */ 2238 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2239 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2240 for (i=0; i<size; i++) { 2241 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2242 procsnz[i] += rowlengths[j]; 2243 } 2244 } 2245 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2246 2247 /* determine max buffer needed and allocate it */ 2248 maxnz = 0; 2249 for (i=0; i<size; i++) { 2250 maxnz = PetscMax(maxnz,procsnz[i]); 2251 } 2252 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2253 2254 /* read in my part of the matrix column indices */ 2255 nz = procsnz[0]; 2256 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2257 mycols = ibuf; 2258 if (size == 1) nz -= extra_rows; 2259 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2260 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2261 2262 /* read in every ones (except the last) and ship off */ 2263 for (i=1; i<size-1; i++) { 2264 nz = procsnz[i]; 2265 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2266 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2267 } 2268 /* read in the stuff for the last proc */ 2269 if (size != 1) { 2270 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2271 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2272 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2273 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2274 } 2275 ierr = PetscFree(cols);CHKERRQ(ierr); 2276 } else { /* procs[i], i>0 */ 2277 /* determine buffer space needed for message */ 2278 nz = 0; 2279 for (i=0; i<m; i++) { 2280 nz += locrowlens[i]; 2281 } 2282 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2283 mycols = ibuf; 2284 /* receive message of column indices*/ 2285 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2286 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2287 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2288 } 2289 2290 /* loop over local rows, determining number of off diagonal entries */ 2291 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2292 odlens = dlens + (rend-rstart); 2293 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2294 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2295 masked1 = mask + Mbs; 2296 masked2 = masked1 + Mbs; 2297 rowcount = 0; nzcount = 0; 2298 for (i=0; i<mbs; i++) { 2299 dcount = 0; 2300 odcount = 0; 2301 for (j=0; j<bs; j++) { 2302 kmax = locrowlens[rowcount]; 2303 for (k=0; k<kmax; k++) { 2304 tmp = mycols[nzcount++]/bs; /* block col. index */ 2305 if (!mask[tmp]) { 2306 mask[tmp] = 1; 2307 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2308 else masked1[dcount++] = tmp; /* entry in diag portion */ 2309 } 2310 } 2311 rowcount++; 2312 } 2313 2314 dlens[i] = dcount; /* d_nzz[i] */ 2315 odlens[i] = odcount; /* o_nzz[i] */ 2316 2317 /* zero out the mask elements we set */ 2318 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2319 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2320 } 2321 2322 /* create our matrix */ 2323 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2324 ierr = MatSetType(A,type);CHKERRQ(ierr); 2325 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2326 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2327 2328 if (!rank) { 2329 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2330 /* read in my part of the matrix numerical values */ 2331 nz = procsnz[0]; 2332 vals = buf; 2333 mycols = ibuf; 2334 if (size == 1) nz -= extra_rows; 2335 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2336 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2337 2338 /* insert into matrix */ 2339 jj = rstart*bs; 2340 for (i=0; i<m; i++) { 2341 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2342 mycols += locrowlens[i]; 2343 vals += locrowlens[i]; 2344 jj++; 2345 } 2346 2347 /* read in other processors (except the last one) and ship out */ 2348 for (i=1; i<size-1; i++) { 2349 nz = procsnz[i]; 2350 vals = buf; 2351 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2352 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2353 } 2354 /* the last proc */ 2355 if (size != 1){ 2356 nz = procsnz[i] - extra_rows; 2357 vals = buf; 2358 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2359 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2360 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2361 } 2362 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2363 2364 } else { 2365 /* receive numeric values */ 2366 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2367 2368 /* receive message of values*/ 2369 vals = buf; 2370 mycols = ibuf; 2371 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2372 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2373 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2374 2375 /* insert into matrix */ 2376 jj = rstart*bs; 2377 for (i=0; i<m; i++) { 2378 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2379 mycols += locrowlens[i]; 2380 vals += locrowlens[i]; 2381 jj++; 2382 } 2383 } 2384 2385 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2386 ierr = PetscFree(buf);CHKERRQ(ierr); 2387 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2388 ierr = PetscFree(rowners);CHKERRQ(ierr); 2389 ierr = PetscFree(dlens);CHKERRQ(ierr); 2390 ierr = PetscFree(mask);CHKERRQ(ierr); 2391 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2392 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2393 *newmat = A; 2394 PetscFunctionReturn(0); 2395 } 2396 2397 #undef __FUNCT__ 2398 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2399 /*@ 2400 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2401 2402 Input Parameters: 2403 . mat - the matrix 2404 . fact - factor 2405 2406 Collective on Mat 2407 2408 Level: advanced 2409 2410 Notes: 2411 This can also be set by the command line option: -mat_use_hash_table fact 2412 2413 .keywords: matrix, hashtable, factor, HT 2414 2415 .seealso: MatSetOption() 2416 @*/ 2417 PetscErrorCode MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2418 { 2419 PetscFunctionBegin; 2420 SETERRQ(PETSC_ERR_SUP,"Function not yet written for SBAIJ format"); 2421 /* PetscFunctionReturn(0); */ 2422 } 2423 2424 #undef __FUNCT__ 2425 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2426 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2427 { 2428 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2429 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2430 PetscReal atmp; 2431 PetscReal *work,*svalues,*rvalues; 2432 PetscErrorCode ierr; 2433 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2434 PetscMPIInt rank,size; 2435 PetscInt *rowners_bs,dest,count,source; 2436 PetscScalar *va; 2437 MatScalar *ba; 2438 MPI_Status stat; 2439 2440 PetscFunctionBegin; 2441 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2442 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2443 2444 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2445 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2446 2447 bs = A->bs; 2448 mbs = a->mbs; 2449 Mbs = a->Mbs; 2450 ba = b->a; 2451 bi = b->i; 2452 bj = b->j; 2453 2454 /* find ownerships */ 2455 rowners_bs = a->rowners_bs; 2456 2457 /* each proc creates an array to be distributed */ 2458 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2459 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2460 2461 /* row_max for B */ 2462 if (rank != size-1){ 2463 for (i=0; i<mbs; i++) { 2464 ncols = bi[1] - bi[0]; bi++; 2465 brow = bs*i; 2466 for (j=0; j<ncols; j++){ 2467 bcol = bs*(*bj); 2468 for (kcol=0; kcol<bs; kcol++){ 2469 col = bcol + kcol; /* local col index */ 2470 col += rowners_bs[rank+1]; /* global col index */ 2471 for (krow=0; krow<bs; krow++){ 2472 atmp = PetscAbsScalar(*ba); ba++; 2473 row = brow + krow; /* local row index */ 2474 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2475 if (work[col] < atmp) work[col] = atmp; 2476 } 2477 } 2478 bj++; 2479 } 2480 } 2481 2482 /* send values to its owners */ 2483 for (dest=rank+1; dest<size; dest++){ 2484 svalues = work + rowners_bs[dest]; 2485 count = rowners_bs[dest+1]-rowners_bs[dest]; 2486 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2487 } 2488 } 2489 2490 /* receive values */ 2491 if (rank){ 2492 rvalues = work; 2493 count = rowners_bs[rank+1]-rowners_bs[rank]; 2494 for (source=0; source<rank; source++){ 2495 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2496 /* process values */ 2497 for (i=0; i<count; i++){ 2498 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2499 } 2500 } 2501 } 2502 2503 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2504 ierr = PetscFree(work);CHKERRQ(ierr); 2505 PetscFunctionReturn(0); 2506 } 2507 2508 #undef __FUNCT__ 2509 #define __FUNCT__ "MatRelax_MPISBAIJ" 2510 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2511 { 2512 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2513 PetscErrorCode ierr; 2514 PetscInt mbs=mat->mbs,bs=matin->bs; 2515 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2516 Vec bb1; 2517 2518 PetscFunctionBegin; 2519 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2520 if (bs > 1) 2521 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2522 2523 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2524 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2525 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2526 its--; 2527 } 2528 2529 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2530 while (its--){ 2531 2532 /* lower triangular part: slvec0b = - B^T*xx */ 2533 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2534 2535 /* copy xx into slvec0a */ 2536 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2537 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2538 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2539 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2540 2541 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2542 2543 /* copy bb into slvec1a */ 2544 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2545 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2546 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2547 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2548 2549 /* set slvec1b = 0 */ 2550 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2551 2552 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2553 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2554 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2555 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2556 2557 /* upper triangular part: bb1 = bb1 - B*x */ 2558 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2559 2560 /* local diagonal sweep */ 2561 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2562 } 2563 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2564 } else { 2565 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2566 } 2567 PetscFunctionReturn(0); 2568 } 2569 2570 #undef __FUNCT__ 2571 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2572 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2573 { 2574 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2575 PetscErrorCode ierr; 2576 PetscScalar mone=-1.0; 2577 Vec lvec1,bb1; 2578 2579 PetscFunctionBegin; 2580 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2581 if (matin->bs > 1) 2582 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2583 2584 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2585 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2586 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2587 its--; 2588 } 2589 2590 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2591 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2592 while (its--){ 2593 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2594 2595 /* lower diagonal part: bb1 = bb - B^T*xx */ 2596 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2597 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2598 2599 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2600 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2601 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2602 2603 /* upper diagonal part: bb1 = bb1 - B*x */ 2604 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2605 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2606 2607 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2608 2609 /* diagonal sweep */ 2610 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2611 } 2612 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2613 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2614 } else { 2615 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2616 } 2617 PetscFunctionReturn(0); 2618 } 2619 2620