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 s1,s2,s3; 1221 1222 PetscFunctionBegin; 1223 if (ll != rr) { 1224 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1225 } 1226 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1227 if (rr) { 1228 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1229 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1230 /* Overlap communication with computation. */ 1231 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1232 /*} if (ll) { */ 1233 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1234 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1235 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1236 /* } */ 1237 /* scale the diagonal block */ 1238 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1239 1240 /* if (rr) { */ 1241 /* Do a scatter end and then right scale the off-diagonal block */ 1242 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1243 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1244 } 1245 1246 PetscFunctionReturn(0); 1247 } 1248 1249 #undef __FUNCT__ 1250 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1251 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1252 { 1253 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1254 MPI_Comm comm = A->comm; 1255 static PetscTruth called = PETSC_FALSE; 1256 PetscErrorCode ierr; 1257 1258 PetscFunctionBegin; 1259 if (!a->rank) { 1260 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1261 } 1262 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1263 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1264 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1270 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1271 { 1272 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1277 PetscFunctionReturn(0); 1278 } 1279 1280 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1281 1282 #undef __FUNCT__ 1283 #define __FUNCT__ "MatEqual_MPISBAIJ" 1284 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1285 { 1286 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1287 Mat a,b,c,d; 1288 PetscTruth flg; 1289 PetscErrorCode ierr; 1290 1291 PetscFunctionBegin; 1292 a = matA->A; b = matA->B; 1293 c = matB->A; d = matB->B; 1294 1295 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1296 if (flg) { 1297 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1298 } 1299 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1300 PetscFunctionReturn(0); 1301 } 1302 1303 #undef __FUNCT__ 1304 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1305 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1306 { 1307 PetscErrorCode ierr; 1308 1309 PetscFunctionBegin; 1310 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1311 PetscFunctionReturn(0); 1312 } 1313 1314 #undef __FUNCT__ 1315 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1316 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1317 { 1318 PetscErrorCode ierr; 1319 PetscInt i; 1320 PetscTruth flg; 1321 1322 PetscFunctionBegin; 1323 for (i=0; i<n; i++) { 1324 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1325 if (!flg) { 1326 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1327 } 1328 } 1329 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1330 PetscFunctionReturn(0); 1331 } 1332 1333 1334 /* -------------------------------------------------------------------*/ 1335 static struct _MatOps MatOps_Values = { 1336 MatSetValues_MPISBAIJ, 1337 MatGetRow_MPISBAIJ, 1338 MatRestoreRow_MPISBAIJ, 1339 MatMult_MPISBAIJ, 1340 /* 4*/ MatMultAdd_MPISBAIJ, 1341 MatMultTranspose_MPISBAIJ, 1342 MatMultTransposeAdd_MPISBAIJ, 1343 0, 1344 0, 1345 0, 1346 /*10*/ 0, 1347 0, 1348 0, 1349 MatRelax_MPISBAIJ, 1350 MatTranspose_MPISBAIJ, 1351 /*15*/ MatGetInfo_MPISBAIJ, 1352 MatEqual_MPISBAIJ, 1353 MatGetDiagonal_MPISBAIJ, 1354 MatDiagonalScale_MPISBAIJ, 1355 MatNorm_MPISBAIJ, 1356 /*20*/ MatAssemblyBegin_MPISBAIJ, 1357 MatAssemblyEnd_MPISBAIJ, 1358 0, 1359 MatSetOption_MPISBAIJ, 1360 MatZeroEntries_MPISBAIJ, 1361 /*25*/ 0, 1362 0, 1363 0, 1364 0, 1365 0, 1366 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1367 0, 1368 0, 1369 0, 1370 0, 1371 /*35*/ MatDuplicate_MPISBAIJ, 1372 0, 1373 0, 1374 0, 1375 0, 1376 /*40*/ 0, 1377 MatGetSubMatrices_MPISBAIJ, 1378 MatIncreaseOverlap_MPISBAIJ, 1379 MatGetValues_MPISBAIJ, 1380 0, 1381 /*45*/ MatPrintHelp_MPISBAIJ, 1382 MatScale_MPISBAIJ, 1383 0, 1384 0, 1385 0, 1386 /*50*/ 0, 1387 0, 1388 0, 1389 0, 1390 0, 1391 /*55*/ 0, 1392 0, 1393 MatSetUnfactored_MPISBAIJ, 1394 0, 1395 MatSetValuesBlocked_MPISBAIJ, 1396 /*60*/ 0, 1397 0, 1398 0, 1399 MatGetPetscMaps_Petsc, 1400 0, 1401 /*65*/ 0, 1402 0, 1403 0, 1404 0, 1405 0, 1406 /*70*/ MatGetRowMax_MPISBAIJ, 1407 0, 1408 0, 1409 0, 1410 0, 1411 /*75*/ 0, 1412 0, 1413 0, 1414 0, 1415 0, 1416 /*80*/ 0, 1417 0, 1418 0, 1419 0, 1420 MatLoad_MPISBAIJ, 1421 /*85*/ 0, 1422 0, 1423 0, 1424 0, 1425 0, 1426 /*90*/ 0, 1427 0, 1428 0, 1429 0, 1430 0, 1431 /*95*/ 0, 1432 0, 1433 0, 1434 0}; 1435 1436 1437 EXTERN_C_BEGIN 1438 #undef __FUNCT__ 1439 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1440 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1441 { 1442 PetscFunctionBegin; 1443 *a = ((Mat_MPISBAIJ *)A->data)->A; 1444 *iscopy = PETSC_FALSE; 1445 PetscFunctionReturn(0); 1446 } 1447 EXTERN_C_END 1448 1449 EXTERN_C_BEGIN 1450 #undef __FUNCT__ 1451 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1452 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1453 { 1454 Mat_MPISBAIJ *b; 1455 PetscErrorCode ierr; 1456 PetscInt i,mbs,Mbs; 1457 1458 PetscFunctionBegin; 1459 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1460 1461 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1462 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1463 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1464 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1465 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1466 if (d_nnz) { 1467 for (i=0; i<B->m/bs; i++) { 1468 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]); 1469 } 1470 } 1471 if (o_nnz) { 1472 for (i=0; i<B->m/bs; i++) { 1473 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]); 1474 } 1475 } 1476 B->preallocated = PETSC_TRUE; 1477 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1478 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1479 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1480 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1481 1482 b = (Mat_MPISBAIJ*)B->data; 1483 mbs = B->m/bs; 1484 Mbs = B->M/bs; 1485 if (mbs*bs != B->m) { 1486 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1487 } 1488 1489 B->bs = bs; 1490 b->bs2 = bs*bs; 1491 b->mbs = mbs; 1492 b->nbs = mbs; 1493 b->Mbs = Mbs; 1494 b->Nbs = Mbs; 1495 1496 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 1497 b->rowners[0] = 0; 1498 for (i=2; i<=b->size; i++) { 1499 b->rowners[i] += b->rowners[i-1]; 1500 } 1501 b->rstart = b->rowners[b->rank]; 1502 b->rend = b->rowners[b->rank+1]; 1503 b->cstart = b->rstart; 1504 b->cend = b->rend; 1505 for (i=0; i<=b->size; i++) { 1506 b->rowners_bs[i] = b->rowners[i]*bs; 1507 } 1508 b->rstart_bs = b-> rstart*bs; 1509 b->rend_bs = b->rend*bs; 1510 1511 b->cstart_bs = b->cstart*bs; 1512 b->cend_bs = b->cend*bs; 1513 1514 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1515 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1516 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1517 PetscLogObjectParent(B,b->A); 1518 1519 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1520 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1521 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1522 PetscLogObjectParent(B,b->B); 1523 1524 /* build cache for off array entries formed */ 1525 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1526 1527 PetscFunctionReturn(0); 1528 } 1529 EXTERN_C_END 1530 1531 /*MC 1532 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1533 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1534 1535 Options Database Keys: 1536 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1537 1538 Level: beginner 1539 1540 .seealso: MatCreateMPISBAIJ 1541 M*/ 1542 1543 EXTERN_C_BEGIN 1544 #undef __FUNCT__ 1545 #define __FUNCT__ "MatCreate_MPISBAIJ" 1546 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1547 { 1548 Mat_MPISBAIJ *b; 1549 PetscErrorCode ierr; 1550 PetscTruth flg; 1551 1552 PetscFunctionBegin; 1553 1554 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1555 B->data = (void*)b; 1556 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1557 1558 B->ops->destroy = MatDestroy_MPISBAIJ; 1559 B->ops->view = MatView_MPISBAIJ; 1560 B->mapping = 0; 1561 B->factor = 0; 1562 B->assembled = PETSC_FALSE; 1563 1564 B->insertmode = NOT_SET_VALUES; 1565 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1566 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1567 1568 /* build local table of row and column ownerships */ 1569 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1570 b->cowners = b->rowners + b->size + 2; 1571 b->rowners_bs = b->cowners + b->size + 2; 1572 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1573 1574 /* build cache for off array entries formed */ 1575 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1576 b->donotstash = PETSC_FALSE; 1577 b->colmap = PETSC_NULL; 1578 b->garray = PETSC_NULL; 1579 b->roworiented = PETSC_TRUE; 1580 1581 #if defined(PETSC_USE_MAT_SINGLE) 1582 /* stuff for MatSetValues_XXX in single precision */ 1583 b->setvalueslen = 0; 1584 b->setvaluescopy = PETSC_NULL; 1585 #endif 1586 1587 /* stuff used in block assembly */ 1588 b->barray = 0; 1589 1590 /* stuff used for matrix vector multiply */ 1591 b->lvec = 0; 1592 b->Mvctx = 0; 1593 b->slvec0 = 0; 1594 b->slvec0b = 0; 1595 b->slvec1 = 0; 1596 b->slvec1a = 0; 1597 b->slvec1b = 0; 1598 b->sMvctx = 0; 1599 1600 /* stuff for MatGetRow() */ 1601 b->rowindices = 0; 1602 b->rowvalues = 0; 1603 b->getrowactive = PETSC_FALSE; 1604 1605 /* hash table stuff */ 1606 b->ht = 0; 1607 b->hd = 0; 1608 b->ht_size = 0; 1609 b->ht_flag = PETSC_FALSE; 1610 b->ht_fact = 0; 1611 b->ht_total_ct = 0; 1612 b->ht_insert_ct = 0; 1613 1614 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1615 if (flg) { 1616 PetscReal fact = 1.39; 1617 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1618 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1619 if (fact <= 1.0) fact = 1.39; 1620 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1621 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1622 } 1623 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1624 "MatStoreValues_MPISBAIJ", 1625 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1626 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1627 "MatRetrieveValues_MPISBAIJ", 1628 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1629 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1630 "MatGetDiagonalBlock_MPISBAIJ", 1631 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1632 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1633 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1634 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1635 B->symmetric = PETSC_TRUE; 1636 B->structurally_symmetric = PETSC_TRUE; 1637 B->symmetric_set = PETSC_TRUE; 1638 B->structurally_symmetric_set = PETSC_TRUE; 1639 PetscFunctionReturn(0); 1640 } 1641 EXTERN_C_END 1642 1643 /*MC 1644 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1645 1646 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1647 and MATMPISBAIJ otherwise. 1648 1649 Options Database Keys: 1650 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1651 1652 Level: beginner 1653 1654 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1655 M*/ 1656 1657 EXTERN_C_BEGIN 1658 #undef __FUNCT__ 1659 #define __FUNCT__ "MatCreate_SBAIJ" 1660 PetscErrorCode MatCreate_SBAIJ(Mat A) 1661 { 1662 PetscErrorCode ierr; 1663 PetscMPIInt size; 1664 1665 PetscFunctionBegin; 1666 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1667 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1668 if (size == 1) { 1669 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1670 } else { 1671 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1672 } 1673 PetscFunctionReturn(0); 1674 } 1675 EXTERN_C_END 1676 1677 #undef __FUNCT__ 1678 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1679 /*@C 1680 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1681 the user should preallocate the matrix storage by setting the parameters 1682 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1683 performance can be increased by more than a factor of 50. 1684 1685 Collective on Mat 1686 1687 Input Parameters: 1688 + A - the matrix 1689 . bs - size of blockk 1690 . d_nz - number of block nonzeros per block row in diagonal portion of local 1691 submatrix (same for all local rows) 1692 . d_nnz - array containing the number of block nonzeros in the various block rows 1693 in the upper triangular and diagonal part of the in diagonal portion of the local 1694 (possibly different for each block row) or PETSC_NULL. You must leave room 1695 for the diagonal entry even if it is zero. 1696 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1697 submatrix (same for all local rows). 1698 - o_nnz - array containing the number of nonzeros in the various block rows of the 1699 off-diagonal portion of the local submatrix (possibly different for 1700 each block row) or PETSC_NULL. 1701 1702 1703 Options Database Keys: 1704 . -mat_no_unroll - uses code that does not unroll the loops in the 1705 block calculations (much slower) 1706 . -mat_block_size - size of the blocks to use 1707 1708 Notes: 1709 1710 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1711 than it must be used on all processors that share the object for that argument. 1712 1713 If the *_nnz parameter is given then the *_nz parameter is ignored 1714 1715 Storage Information: 1716 For a square global matrix we define each processor's diagonal portion 1717 to be its local rows and the corresponding columns (a square submatrix); 1718 each processor's off-diagonal portion encompasses the remainder of the 1719 local matrix (a rectangular submatrix). 1720 1721 The user can specify preallocated storage for the diagonal part of 1722 the local submatrix with either d_nz or d_nnz (not both). Set 1723 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1724 memory allocation. Likewise, specify preallocated storage for the 1725 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1726 1727 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1728 the figure below we depict these three local rows and all columns (0-11). 1729 1730 .vb 1731 0 1 2 3 4 5 6 7 8 9 10 11 1732 ------------------- 1733 row 3 | o o o d d d o o o o o o 1734 row 4 | o o o d d d o o o o o o 1735 row 5 | o o o d d d o o o o o o 1736 ------------------- 1737 .ve 1738 1739 Thus, any entries in the d locations are stored in the d (diagonal) 1740 submatrix, and any entries in the o locations are stored in the 1741 o (off-diagonal) submatrix. Note that the d matrix is stored in 1742 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1743 1744 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1745 plus the diagonal part of the d matrix, 1746 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1747 In general, for PDE problems in which most nonzeros are near the diagonal, 1748 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1749 or you will get TERRIBLE performance; see the users' manual chapter on 1750 matrices. 1751 1752 Level: intermediate 1753 1754 .keywords: matrix, block, aij, compressed row, sparse, parallel 1755 1756 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1757 @*/ 1758 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1759 { 1760 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1761 1762 PetscFunctionBegin; 1763 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1764 if (f) { 1765 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1766 } 1767 PetscFunctionReturn(0); 1768 } 1769 1770 #undef __FUNCT__ 1771 #define __FUNCT__ "MatCreateMPISBAIJ" 1772 /*@C 1773 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1774 (block compressed row). For good matrix assembly performance 1775 the user should preallocate the matrix storage by setting the parameters 1776 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1777 performance can be increased by more than a factor of 50. 1778 1779 Collective on MPI_Comm 1780 1781 Input Parameters: 1782 + comm - MPI communicator 1783 . bs - size of blockk 1784 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1785 This value should be the same as the local size used in creating the 1786 y vector for the matrix-vector product y = Ax. 1787 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1788 This value should be the same as the local size used in creating the 1789 x vector for the matrix-vector product y = Ax. 1790 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1791 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1792 . d_nz - number of block nonzeros per block row in diagonal portion of local 1793 submatrix (same for all local rows) 1794 . d_nnz - array containing the number of block nonzeros in the various block rows 1795 in the upper triangular portion of the in diagonal portion of the local 1796 (possibly different for each block block row) or PETSC_NULL. 1797 You must leave room for the diagonal entry even if it is zero. 1798 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1799 submatrix (same for all local rows). 1800 - o_nnz - array containing the number of nonzeros in the various block rows of the 1801 off-diagonal portion of the local submatrix (possibly different for 1802 each block row) or PETSC_NULL. 1803 1804 Output Parameter: 1805 . A - the matrix 1806 1807 Options Database Keys: 1808 . -mat_no_unroll - uses code that does not unroll the loops in the 1809 block calculations (much slower) 1810 . -mat_block_size - size of the blocks to use 1811 . -mat_mpi - use the parallel matrix data structures even on one processor 1812 (defaults to using SeqBAIJ format on one processor) 1813 1814 Notes: 1815 The user MUST specify either the local or global matrix dimensions 1816 (possibly both). 1817 1818 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1819 than it must be used on all processors that share the object for that argument. 1820 1821 If the *_nnz parameter is given then the *_nz parameter is ignored 1822 1823 Storage Information: 1824 For a square global matrix we define each processor's diagonal portion 1825 to be its local rows and the corresponding columns (a square submatrix); 1826 each processor's off-diagonal portion encompasses the remainder of the 1827 local matrix (a rectangular submatrix). 1828 1829 The user can specify preallocated storage for the diagonal part of 1830 the local submatrix with either d_nz or d_nnz (not both). Set 1831 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1832 memory allocation. Likewise, specify preallocated storage for the 1833 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1834 1835 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1836 the figure below we depict these three local rows and all columns (0-11). 1837 1838 .vb 1839 0 1 2 3 4 5 6 7 8 9 10 11 1840 ------------------- 1841 row 3 | o o o d d d o o o o o o 1842 row 4 | o o o d d d o o o o o o 1843 row 5 | o o o d d d o o o o o o 1844 ------------------- 1845 .ve 1846 1847 Thus, any entries in the d locations are stored in the d (diagonal) 1848 submatrix, and any entries in the o locations are stored in the 1849 o (off-diagonal) submatrix. Note that the d matrix is stored in 1850 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1851 1852 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1853 plus the diagonal part of the d matrix, 1854 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1855 In general, for PDE problems in which most nonzeros are near the diagonal, 1856 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1857 or you will get TERRIBLE performance; see the users' manual chapter on 1858 matrices. 1859 1860 Level: intermediate 1861 1862 .keywords: matrix, block, aij, compressed row, sparse, parallel 1863 1864 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1865 @*/ 1866 1867 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) 1868 { 1869 PetscErrorCode ierr; 1870 PetscMPIInt size; 1871 1872 PetscFunctionBegin; 1873 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1874 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1875 if (size > 1) { 1876 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1877 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1878 } else { 1879 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1880 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1881 } 1882 PetscFunctionReturn(0); 1883 } 1884 1885 1886 #undef __FUNCT__ 1887 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1888 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1889 { 1890 Mat mat; 1891 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1892 PetscErrorCode ierr; 1893 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 1894 PetscScalar *array; 1895 1896 PetscFunctionBegin; 1897 *newmat = 0; 1898 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1899 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 1900 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1901 1902 mat->factor = matin->factor; 1903 mat->preallocated = PETSC_TRUE; 1904 mat->assembled = PETSC_TRUE; 1905 mat->insertmode = NOT_SET_VALUES; 1906 1907 a = (Mat_MPISBAIJ*)mat->data; 1908 mat->bs = matin->bs; 1909 a->bs2 = oldmat->bs2; 1910 a->mbs = oldmat->mbs; 1911 a->nbs = oldmat->nbs; 1912 a->Mbs = oldmat->Mbs; 1913 a->Nbs = oldmat->Nbs; 1914 1915 a->rstart = oldmat->rstart; 1916 a->rend = oldmat->rend; 1917 a->cstart = oldmat->cstart; 1918 a->cend = oldmat->cend; 1919 a->size = oldmat->size; 1920 a->rank = oldmat->rank; 1921 a->donotstash = oldmat->donotstash; 1922 a->roworiented = oldmat->roworiented; 1923 a->rowindices = 0; 1924 a->rowvalues = 0; 1925 a->getrowactive = PETSC_FALSE; 1926 a->barray = 0; 1927 a->rstart_bs = oldmat->rstart_bs; 1928 a->rend_bs = oldmat->rend_bs; 1929 a->cstart_bs = oldmat->cstart_bs; 1930 a->cend_bs = oldmat->cend_bs; 1931 1932 /* hash table stuff */ 1933 a->ht = 0; 1934 a->hd = 0; 1935 a->ht_size = 0; 1936 a->ht_flag = oldmat->ht_flag; 1937 a->ht_fact = oldmat->ht_fact; 1938 a->ht_total_ct = 0; 1939 a->ht_insert_ct = 0; 1940 1941 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 1942 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1943 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 1944 if (oldmat->colmap) { 1945 #if defined (PETSC_USE_CTABLE) 1946 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1947 #else 1948 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 1949 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 1950 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 1951 #endif 1952 } else a->colmap = 0; 1953 1954 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1955 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 1956 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 1957 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 1958 } else a->garray = 0; 1959 1960 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1961 PetscLogObjectParent(mat,a->lvec); 1962 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1963 PetscLogObjectParent(mat,a->Mvctx); 1964 1965 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 1966 PetscLogObjectParent(mat,a->slvec0); 1967 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 1968 PetscLogObjectParent(mat,a->slvec1); 1969 1970 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 1971 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 1972 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 1973 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 1974 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 1975 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 1976 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 1977 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 1978 PetscLogObjectParent(mat,a->slvec0); 1979 PetscLogObjectParent(mat,a->slvec1); 1980 PetscLogObjectParent(mat,a->slvec0b); 1981 PetscLogObjectParent(mat,a->slvec1a); 1982 PetscLogObjectParent(mat,a->slvec1b); 1983 1984 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 1985 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 1986 a->sMvctx = oldmat->sMvctx; 1987 PetscLogObjectParent(mat,a->sMvctx); 1988 1989 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1990 PetscLogObjectParent(mat,a->A); 1991 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1992 PetscLogObjectParent(mat,a->B); 1993 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1994 *newmat = mat; 1995 PetscFunctionReturn(0); 1996 } 1997 1998 #include "petscsys.h" 1999 2000 #undef __FUNCT__ 2001 #define __FUNCT__ "MatLoad_MPISBAIJ" 2002 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2003 { 2004 Mat A; 2005 PetscErrorCode ierr; 2006 PetscInt i,nz,j,rstart,rend; 2007 PetscScalar *vals,*buf; 2008 MPI_Comm comm = ((PetscObject)viewer)->comm; 2009 MPI_Status status; 2010 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners; 2011 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2012 PetscInt *locrowlens,*procsnz = 0,jj,*mycols,*ibuf; 2013 PetscInt bs=1,Mbs,mbs,extra_rows; 2014 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2015 PetscInt dcount,kmax,k,nzcount,tmp; 2016 int fd; 2017 2018 PetscFunctionBegin; 2019 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2020 2021 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2022 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2023 if (!rank) { 2024 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2025 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2026 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2027 if (header[3] < 0) { 2028 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2029 } 2030 } 2031 2032 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2033 M = header[1]; N = header[2]; 2034 2035 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2036 2037 /* 2038 This code adds extra rows to make sure the number of rows is 2039 divisible by the blocksize 2040 */ 2041 Mbs = M/bs; 2042 extra_rows = bs - M + bs*(Mbs); 2043 if (extra_rows == bs) extra_rows = 0; 2044 else Mbs++; 2045 if (extra_rows &&!rank) { 2046 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2047 } 2048 2049 /* determine ownership of all rows */ 2050 mbs = Mbs/size + ((Mbs % size) > rank); 2051 m = mbs*bs; 2052 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2053 browners = rowners + size + 1; 2054 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2055 rowners[0] = 0; 2056 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2057 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2058 rstart = rowners[rank]; 2059 rend = rowners[rank+1]; 2060 2061 /* distribute row lengths to all processors */ 2062 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2063 if (!rank) { 2064 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2065 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2066 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2067 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2068 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2069 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2070 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2071 } else { 2072 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2073 } 2074 2075 if (!rank) { /* procs[0] */ 2076 /* calculate the number of nonzeros on each processor */ 2077 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2078 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2079 for (i=0; i<size; i++) { 2080 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2081 procsnz[i] += rowlengths[j]; 2082 } 2083 } 2084 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2085 2086 /* determine max buffer needed and allocate it */ 2087 maxnz = 0; 2088 for (i=0; i<size; i++) { 2089 maxnz = PetscMax(maxnz,procsnz[i]); 2090 } 2091 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2092 2093 /* read in my part of the matrix column indices */ 2094 nz = procsnz[0]; 2095 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2096 mycols = ibuf; 2097 if (size == 1) nz -= extra_rows; 2098 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2099 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2100 2101 /* read in every ones (except the last) and ship off */ 2102 for (i=1; i<size-1; i++) { 2103 nz = procsnz[i]; 2104 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2105 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2106 } 2107 /* read in the stuff for the last proc */ 2108 if (size != 1) { 2109 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2110 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2111 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2112 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2113 } 2114 ierr = PetscFree(cols);CHKERRQ(ierr); 2115 } else { /* procs[i], i>0 */ 2116 /* determine buffer space needed for message */ 2117 nz = 0; 2118 for (i=0; i<m; i++) { 2119 nz += locrowlens[i]; 2120 } 2121 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2122 mycols = ibuf; 2123 /* receive message of column indices*/ 2124 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2125 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2126 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2127 } 2128 2129 /* loop over local rows, determining number of off diagonal entries */ 2130 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2131 odlens = dlens + (rend-rstart); 2132 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2133 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2134 masked1 = mask + Mbs; 2135 masked2 = masked1 + Mbs; 2136 rowcount = 0; nzcount = 0; 2137 for (i=0; i<mbs; i++) { 2138 dcount = 0; 2139 odcount = 0; 2140 for (j=0; j<bs; j++) { 2141 kmax = locrowlens[rowcount]; 2142 for (k=0; k<kmax; k++) { 2143 tmp = mycols[nzcount++]/bs; /* block col. index */ 2144 if (!mask[tmp]) { 2145 mask[tmp] = 1; 2146 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2147 else masked1[dcount++] = tmp; /* entry in diag portion */ 2148 } 2149 } 2150 rowcount++; 2151 } 2152 2153 dlens[i] = dcount; /* d_nzz[i] */ 2154 odlens[i] = odcount; /* o_nzz[i] */ 2155 2156 /* zero out the mask elements we set */ 2157 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2158 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2159 } 2160 2161 /* create our matrix */ 2162 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2163 ierr = MatSetType(A,type);CHKERRQ(ierr); 2164 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2165 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2166 2167 if (!rank) { 2168 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2169 /* read in my part of the matrix numerical values */ 2170 nz = procsnz[0]; 2171 vals = buf; 2172 mycols = ibuf; 2173 if (size == 1) nz -= extra_rows; 2174 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2175 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2176 2177 /* insert into matrix */ 2178 jj = rstart*bs; 2179 for (i=0; i<m; i++) { 2180 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2181 mycols += locrowlens[i]; 2182 vals += locrowlens[i]; 2183 jj++; 2184 } 2185 2186 /* read in other processors (except the last one) and ship out */ 2187 for (i=1; i<size-1; i++) { 2188 nz = procsnz[i]; 2189 vals = buf; 2190 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2191 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2192 } 2193 /* the last proc */ 2194 if (size != 1){ 2195 nz = procsnz[i] - extra_rows; 2196 vals = buf; 2197 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2198 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2199 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2200 } 2201 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2202 2203 } else { 2204 /* receive numeric values */ 2205 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2206 2207 /* receive message of values*/ 2208 vals = buf; 2209 mycols = ibuf; 2210 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2211 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2212 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2213 2214 /* insert into matrix */ 2215 jj = rstart*bs; 2216 for (i=0; i<m; i++) { 2217 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2218 mycols += locrowlens[i]; 2219 vals += locrowlens[i]; 2220 jj++; 2221 } 2222 } 2223 2224 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2225 ierr = PetscFree(buf);CHKERRQ(ierr); 2226 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2227 ierr = PetscFree(rowners);CHKERRQ(ierr); 2228 ierr = PetscFree(dlens);CHKERRQ(ierr); 2229 ierr = PetscFree(mask);CHKERRQ(ierr); 2230 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2231 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2232 *newmat = A; 2233 PetscFunctionReturn(0); 2234 } 2235 2236 #undef __FUNCT__ 2237 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2238 /*XXXXX@ 2239 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2240 2241 Input Parameters: 2242 . mat - the matrix 2243 . fact - factor 2244 2245 Collective on Mat 2246 2247 Level: advanced 2248 2249 Notes: 2250 This can also be set by the command line option: -mat_use_hash_table fact 2251 2252 .keywords: matrix, hashtable, factor, HT 2253 2254 .seealso: MatSetOption() 2255 @XXXXX*/ 2256 2257 2258 #undef __FUNCT__ 2259 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2260 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2261 { 2262 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2263 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2264 PetscReal atmp; 2265 PetscReal *work,*svalues,*rvalues; 2266 PetscErrorCode ierr; 2267 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2268 PetscMPIInt rank,size; 2269 PetscInt *rowners_bs,dest,count,source; 2270 PetscScalar *va; 2271 MatScalar *ba; 2272 MPI_Status stat; 2273 2274 PetscFunctionBegin; 2275 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2276 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2277 2278 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2279 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2280 2281 bs = A->bs; 2282 mbs = a->mbs; 2283 Mbs = a->Mbs; 2284 ba = b->a; 2285 bi = b->i; 2286 bj = b->j; 2287 2288 /* find ownerships */ 2289 rowners_bs = a->rowners_bs; 2290 2291 /* each proc creates an array to be distributed */ 2292 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2293 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2294 2295 /* row_max for B */ 2296 if (rank != size-1){ 2297 for (i=0; i<mbs; i++) { 2298 ncols = bi[1] - bi[0]; bi++; 2299 brow = bs*i; 2300 for (j=0; j<ncols; j++){ 2301 bcol = bs*(*bj); 2302 for (kcol=0; kcol<bs; kcol++){ 2303 col = bcol + kcol; /* local col index */ 2304 col += rowners_bs[rank+1]; /* global col index */ 2305 for (krow=0; krow<bs; krow++){ 2306 atmp = PetscAbsScalar(*ba); ba++; 2307 row = brow + krow; /* local row index */ 2308 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2309 if (work[col] < atmp) work[col] = atmp; 2310 } 2311 } 2312 bj++; 2313 } 2314 } 2315 2316 /* send values to its owners */ 2317 for (dest=rank+1; dest<size; dest++){ 2318 svalues = work + rowners_bs[dest]; 2319 count = rowners_bs[dest+1]-rowners_bs[dest]; 2320 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2321 } 2322 } 2323 2324 /* receive values */ 2325 if (rank){ 2326 rvalues = work; 2327 count = rowners_bs[rank+1]-rowners_bs[rank]; 2328 for (source=0; source<rank; source++){ 2329 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2330 /* process values */ 2331 for (i=0; i<count; i++){ 2332 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2333 } 2334 } 2335 } 2336 2337 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2338 ierr = PetscFree(work);CHKERRQ(ierr); 2339 PetscFunctionReturn(0); 2340 } 2341 2342 #undef __FUNCT__ 2343 #define __FUNCT__ "MatRelax_MPISBAIJ" 2344 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2345 { 2346 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2347 PetscErrorCode ierr; 2348 PetscInt mbs=mat->mbs,bs=matin->bs; 2349 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2350 Vec bb1; 2351 2352 PetscFunctionBegin; 2353 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2354 if (bs > 1) 2355 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2356 2357 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2358 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2359 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2360 its--; 2361 } 2362 2363 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2364 while (its--){ 2365 2366 /* lower triangular part: slvec0b = - B^T*xx */ 2367 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2368 2369 /* copy xx into slvec0a */ 2370 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2371 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2372 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2373 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2374 2375 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2376 2377 /* copy bb into slvec1a */ 2378 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2379 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2380 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2381 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2382 2383 /* set slvec1b = 0 */ 2384 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2385 2386 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2387 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2388 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2389 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2390 2391 /* upper triangular part: bb1 = bb1 - B*x */ 2392 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2393 2394 /* local diagonal sweep */ 2395 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2396 } 2397 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2398 } else { 2399 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2400 } 2401 PetscFunctionReturn(0); 2402 } 2403 2404 #undef __FUNCT__ 2405 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2406 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2407 { 2408 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2409 PetscErrorCode ierr; 2410 PetscScalar mone=-1.0; 2411 Vec lvec1,bb1; 2412 2413 PetscFunctionBegin; 2414 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2415 if (matin->bs > 1) 2416 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2417 2418 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2419 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2420 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2421 its--; 2422 } 2423 2424 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2425 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2426 while (its--){ 2427 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2428 2429 /* lower diagonal part: bb1 = bb - B^T*xx */ 2430 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2431 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2432 2433 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2434 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2435 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2436 2437 /* upper diagonal part: bb1 = bb1 - B*x */ 2438 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2439 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2440 2441 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2442 2443 /* diagonal sweep */ 2444 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2445 } 2446 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2447 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2448 } else { 2449 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2450 } 2451 PetscFunctionReturn(0); 2452 } 2453 2454