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