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 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1064 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1065 PetscErrorCode ierr; 1066 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1067 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1068 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1069 1070 PetscFunctionBegin; 1071 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1072 mat->getrowactive = PETSC_TRUE; 1073 1074 if (!mat->rowvalues && (idx || v)) { 1075 /* 1076 allocate enough space to hold information from the longest row. 1077 */ 1078 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1079 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1080 PetscInt max = 1,mbs = mat->mbs,tmp; 1081 for (i=0; i<mbs; i++) { 1082 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1083 if (max < tmp) { max = tmp; } 1084 } 1085 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1086 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1087 } 1088 1089 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1090 lrow = row - brstart; /* local row index */ 1091 1092 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1093 if (!v) {pvA = 0; pvB = 0;} 1094 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1095 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1096 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1097 nztot = nzA + nzB; 1098 1099 cmap = mat->garray; 1100 if (v || idx) { 1101 if (nztot) { 1102 /* Sort by increasing column numbers, assuming A and B already sorted */ 1103 PetscInt imark = -1; 1104 if (v) { 1105 *v = v_p = mat->rowvalues; 1106 for (i=0; i<nzB; i++) { 1107 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1108 else break; 1109 } 1110 imark = i; 1111 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1112 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1113 } 1114 if (idx) { 1115 *idx = idx_p = mat->rowindices; 1116 if (imark > -1) { 1117 for (i=0; i<imark; i++) { 1118 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1119 } 1120 } else { 1121 for (i=0; i<nzB; i++) { 1122 if (cmap[cworkB[i]/bs] < cstart) 1123 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1124 else break; 1125 } 1126 imark = i; 1127 } 1128 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1129 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1130 } 1131 } else { 1132 if (idx) *idx = 0; 1133 if (v) *v = 0; 1134 } 1135 } 1136 *nz = nztot; 1137 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1138 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1139 PetscFunctionReturn(0); 1140 } 1141 1142 #undef __FUNCT__ 1143 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1144 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1145 { 1146 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1147 1148 PetscFunctionBegin; 1149 if (!baij->getrowactive) { 1150 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1151 } 1152 baij->getrowactive = PETSC_FALSE; 1153 PetscFunctionReturn(0); 1154 } 1155 1156 #undef __FUNCT__ 1157 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1158 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1159 { 1160 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1161 PetscErrorCode ierr; 1162 1163 PetscFunctionBegin; 1164 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1165 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1166 PetscFunctionReturn(0); 1167 } 1168 1169 #undef __FUNCT__ 1170 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1171 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1172 { 1173 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1174 Mat A = a->A,B = a->B; 1175 PetscErrorCode ierr; 1176 PetscReal isend[5],irecv[5]; 1177 1178 PetscFunctionBegin; 1179 info->block_size = (PetscReal)matin->bs; 1180 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1181 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1182 isend[3] = info->memory; isend[4] = info->mallocs; 1183 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1184 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1185 isend[3] += info->memory; isend[4] += info->mallocs; 1186 if (flag == MAT_LOCAL) { 1187 info->nz_used = isend[0]; 1188 info->nz_allocated = isend[1]; 1189 info->nz_unneeded = isend[2]; 1190 info->memory = isend[3]; 1191 info->mallocs = isend[4]; 1192 } else if (flag == MAT_GLOBAL_MAX) { 1193 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1194 info->nz_used = irecv[0]; 1195 info->nz_allocated = irecv[1]; 1196 info->nz_unneeded = irecv[2]; 1197 info->memory = irecv[3]; 1198 info->mallocs = irecv[4]; 1199 } else if (flag == MAT_GLOBAL_SUM) { 1200 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1201 info->nz_used = irecv[0]; 1202 info->nz_allocated = irecv[1]; 1203 info->nz_unneeded = irecv[2]; 1204 info->memory = irecv[3]; 1205 info->mallocs = irecv[4]; 1206 } else { 1207 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1208 } 1209 info->rows_global = (PetscReal)A->M; 1210 info->columns_global = (PetscReal)A->N; 1211 info->rows_local = (PetscReal)A->m; 1212 info->columns_local = (PetscReal)A->N; 1213 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1214 info->fill_ratio_needed = 0; 1215 info->factor_mallocs = 0; 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #undef __FUNCT__ 1220 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1221 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1222 { 1223 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1224 PetscErrorCode ierr; 1225 1226 PetscFunctionBegin; 1227 switch (op) { 1228 case MAT_NO_NEW_NONZERO_LOCATIONS: 1229 case MAT_YES_NEW_NONZERO_LOCATIONS: 1230 case MAT_COLUMNS_UNSORTED: 1231 case MAT_COLUMNS_SORTED: 1232 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1233 case MAT_KEEP_ZEROED_ROWS: 1234 case MAT_NEW_NONZERO_LOCATION_ERR: 1235 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1236 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1237 break; 1238 case MAT_ROW_ORIENTED: 1239 a->roworiented = PETSC_TRUE; 1240 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1241 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1242 break; 1243 case MAT_ROWS_SORTED: 1244 case MAT_ROWS_UNSORTED: 1245 case MAT_YES_NEW_DIAGONALS: 1246 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1247 break; 1248 case MAT_COLUMN_ORIENTED: 1249 a->roworiented = PETSC_FALSE; 1250 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1251 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1252 break; 1253 case MAT_IGNORE_OFF_PROC_ENTRIES: 1254 a->donotstash = PETSC_TRUE; 1255 break; 1256 case MAT_NO_NEW_DIAGONALS: 1257 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1258 case MAT_USE_HASH_TABLE: 1259 a->ht_flag = PETSC_TRUE; 1260 break; 1261 case MAT_NOT_SYMMETRIC: 1262 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1263 case MAT_HERMITIAN: 1264 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1265 case MAT_SYMMETRIC: 1266 case MAT_STRUCTURALLY_SYMMETRIC: 1267 case MAT_NOT_HERMITIAN: 1268 case MAT_SYMMETRY_ETERNAL: 1269 case MAT_NOT_SYMMETRY_ETERNAL: 1270 break; 1271 default: 1272 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1273 } 1274 PetscFunctionReturn(0); 1275 } 1276 1277 #undef __FUNCT__ 1278 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1279 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1280 { 1281 PetscErrorCode ierr; 1282 PetscFunctionBegin; 1283 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1284 PetscFunctionReturn(0); 1285 } 1286 1287 #undef __FUNCT__ 1288 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1289 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1290 { 1291 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1292 Mat a = baij->A,b = baij->B; 1293 PetscErrorCode ierr; 1294 PetscInt s1,s2,s3; 1295 1296 PetscFunctionBegin; 1297 if (ll != rr) { 1298 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1299 } 1300 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1301 if (rr) { 1302 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1303 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1304 /* Overlap communication with computation. */ 1305 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1306 /*} if (ll) { */ 1307 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1308 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1309 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1310 /* } */ 1311 /* scale the diagonal block */ 1312 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1313 1314 /* if (rr) { */ 1315 /* Do a scatter end and then right scale the off-diagonal block */ 1316 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1317 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1318 } 1319 1320 PetscFunctionReturn(0); 1321 } 1322 1323 #undef __FUNCT__ 1324 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1325 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1326 { 1327 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1328 MPI_Comm comm = A->comm; 1329 static PetscTruth called = PETSC_FALSE; 1330 PetscErrorCode ierr; 1331 1332 PetscFunctionBegin; 1333 if (!a->rank) { 1334 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1335 } 1336 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1337 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1338 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1339 PetscFunctionReturn(0); 1340 } 1341 1342 #undef __FUNCT__ 1343 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1344 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1345 { 1346 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1347 PetscErrorCode ierr; 1348 1349 PetscFunctionBegin; 1350 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1351 PetscFunctionReturn(0); 1352 } 1353 1354 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1355 1356 #undef __FUNCT__ 1357 #define __FUNCT__ "MatEqual_MPISBAIJ" 1358 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1359 { 1360 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1361 Mat a,b,c,d; 1362 PetscTruth flg; 1363 PetscErrorCode ierr; 1364 1365 PetscFunctionBegin; 1366 a = matA->A; b = matA->B; 1367 c = matB->A; d = matB->B; 1368 1369 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1370 if (flg) { 1371 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1372 } 1373 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1374 PetscFunctionReturn(0); 1375 } 1376 1377 #undef __FUNCT__ 1378 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1379 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1380 { 1381 PetscErrorCode ierr; 1382 1383 PetscFunctionBegin; 1384 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1385 PetscFunctionReturn(0); 1386 } 1387 1388 #undef __FUNCT__ 1389 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1390 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1391 { 1392 PetscErrorCode ierr; 1393 PetscInt i; 1394 PetscTruth flg; 1395 1396 PetscFunctionBegin; 1397 for (i=0; i<n; i++) { 1398 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1399 if (!flg) { 1400 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1401 } 1402 } 1403 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1404 PetscFunctionReturn(0); 1405 } 1406 1407 1408 /* -------------------------------------------------------------------*/ 1409 static struct _MatOps MatOps_Values = { 1410 MatSetValues_MPISBAIJ, 1411 MatGetRow_MPISBAIJ, 1412 MatRestoreRow_MPISBAIJ, 1413 MatMult_MPISBAIJ, 1414 /* 4*/ MatMultAdd_MPISBAIJ, 1415 MatMultTranspose_MPISBAIJ, 1416 MatMultTransposeAdd_MPISBAIJ, 1417 0, 1418 0, 1419 0, 1420 /*10*/ 0, 1421 0, 1422 0, 1423 MatRelax_MPISBAIJ, 1424 MatTranspose_MPISBAIJ, 1425 /*15*/ MatGetInfo_MPISBAIJ, 1426 MatEqual_MPISBAIJ, 1427 MatGetDiagonal_MPISBAIJ, 1428 MatDiagonalScale_MPISBAIJ, 1429 MatNorm_MPISBAIJ, 1430 /*20*/ MatAssemblyBegin_MPISBAIJ, 1431 MatAssemblyEnd_MPISBAIJ, 1432 0, 1433 MatSetOption_MPISBAIJ, 1434 MatZeroEntries_MPISBAIJ, 1435 /*25*/ 0, 1436 0, 1437 0, 1438 0, 1439 0, 1440 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1441 0, 1442 0, 1443 0, 1444 0, 1445 /*35*/ MatDuplicate_MPISBAIJ, 1446 0, 1447 0, 1448 0, 1449 0, 1450 /*40*/ 0, 1451 MatGetSubMatrices_MPISBAIJ, 1452 MatIncreaseOverlap_MPISBAIJ, 1453 MatGetValues_MPISBAIJ, 1454 0, 1455 /*45*/ MatPrintHelp_MPISBAIJ, 1456 MatScale_MPISBAIJ, 1457 0, 1458 0, 1459 0, 1460 /*50*/ 0, 1461 0, 1462 0, 1463 0, 1464 0, 1465 /*55*/ 0, 1466 0, 1467 MatSetUnfactored_MPISBAIJ, 1468 0, 1469 MatSetValuesBlocked_MPISBAIJ, 1470 /*60*/ 0, 1471 0, 1472 0, 1473 MatGetPetscMaps_Petsc, 1474 0, 1475 /*65*/ 0, 1476 0, 1477 0, 1478 0, 1479 0, 1480 /*70*/ MatGetRowMax_MPISBAIJ, 1481 0, 1482 0, 1483 0, 1484 0, 1485 /*75*/ 0, 1486 0, 1487 0, 1488 0, 1489 0, 1490 /*80*/ 0, 1491 0, 1492 0, 1493 0, 1494 MatLoad_MPISBAIJ, 1495 /*85*/ 0, 1496 0, 1497 0, 1498 0, 1499 0, 1500 /*90*/ 0, 1501 0, 1502 0, 1503 0, 1504 0, 1505 /*95*/ 0, 1506 0, 1507 0, 1508 0}; 1509 1510 1511 EXTERN_C_BEGIN 1512 #undef __FUNCT__ 1513 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1514 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1515 { 1516 PetscFunctionBegin; 1517 *a = ((Mat_MPISBAIJ *)A->data)->A; 1518 *iscopy = PETSC_FALSE; 1519 PetscFunctionReturn(0); 1520 } 1521 EXTERN_C_END 1522 1523 EXTERN_C_BEGIN 1524 #undef __FUNCT__ 1525 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1526 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1527 { 1528 Mat_MPISBAIJ *b; 1529 PetscErrorCode ierr; 1530 PetscInt i,mbs,Mbs; 1531 1532 PetscFunctionBegin; 1533 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1534 1535 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1536 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1537 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1538 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1539 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1540 if (d_nnz) { 1541 for (i=0; i<B->m/bs; i++) { 1542 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]); 1543 } 1544 } 1545 if (o_nnz) { 1546 for (i=0; i<B->m/bs; i++) { 1547 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]); 1548 } 1549 } 1550 B->preallocated = PETSC_TRUE; 1551 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1552 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1553 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1554 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1555 1556 b = (Mat_MPISBAIJ*)B->data; 1557 mbs = B->m/bs; 1558 Mbs = B->M/bs; 1559 if (mbs*bs != B->m) { 1560 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1561 } 1562 1563 B->bs = bs; 1564 b->bs2 = bs*bs; 1565 b->mbs = mbs; 1566 b->nbs = mbs; 1567 b->Mbs = Mbs; 1568 b->Nbs = Mbs; 1569 1570 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 1571 b->rowners[0] = 0; 1572 for (i=2; i<=b->size; i++) { 1573 b->rowners[i] += b->rowners[i-1]; 1574 } 1575 b->rstart = b->rowners[b->rank]; 1576 b->rend = b->rowners[b->rank+1]; 1577 b->cstart = b->rstart; 1578 b->cend = b->rend; 1579 for (i=0; i<=b->size; i++) { 1580 b->rowners_bs[i] = b->rowners[i]*bs; 1581 } 1582 b->rstart_bs = b-> rstart*bs; 1583 b->rend_bs = b->rend*bs; 1584 1585 b->cstart_bs = b->cstart*bs; 1586 b->cend_bs = b->cend*bs; 1587 1588 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1589 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1590 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1591 PetscLogObjectParent(B,b->A); 1592 1593 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1594 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1595 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1596 PetscLogObjectParent(B,b->B); 1597 1598 /* build cache for off array entries formed */ 1599 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1600 1601 PetscFunctionReturn(0); 1602 } 1603 EXTERN_C_END 1604 1605 /*MC 1606 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1607 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1608 1609 Options Database Keys: 1610 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1611 1612 Level: beginner 1613 1614 .seealso: MatCreateMPISBAIJ 1615 M*/ 1616 1617 EXTERN_C_BEGIN 1618 #undef __FUNCT__ 1619 #define __FUNCT__ "MatCreate_MPISBAIJ" 1620 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1621 { 1622 Mat_MPISBAIJ *b; 1623 PetscErrorCode ierr; 1624 PetscTruth flg; 1625 1626 PetscFunctionBegin; 1627 1628 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1629 B->data = (void*)b; 1630 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1631 1632 B->ops->destroy = MatDestroy_MPISBAIJ; 1633 B->ops->view = MatView_MPISBAIJ; 1634 B->mapping = 0; 1635 B->factor = 0; 1636 B->assembled = PETSC_FALSE; 1637 1638 B->insertmode = NOT_SET_VALUES; 1639 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1640 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1641 1642 /* build local table of row and column ownerships */ 1643 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1644 b->cowners = b->rowners + b->size + 2; 1645 b->rowners_bs = b->cowners + b->size + 2; 1646 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1647 1648 /* build cache for off array entries formed */ 1649 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1650 b->donotstash = PETSC_FALSE; 1651 b->colmap = PETSC_NULL; 1652 b->garray = PETSC_NULL; 1653 b->roworiented = PETSC_TRUE; 1654 1655 #if defined(PETSC_USE_MAT_SINGLE) 1656 /* stuff for MatSetValues_XXX in single precision */ 1657 b->setvalueslen = 0; 1658 b->setvaluescopy = PETSC_NULL; 1659 #endif 1660 1661 /* stuff used in block assembly */ 1662 b->barray = 0; 1663 1664 /* stuff used for matrix vector multiply */ 1665 b->lvec = 0; 1666 b->Mvctx = 0; 1667 b->slvec0 = 0; 1668 b->slvec0b = 0; 1669 b->slvec1 = 0; 1670 b->slvec1a = 0; 1671 b->slvec1b = 0; 1672 b->sMvctx = 0; 1673 1674 /* stuff for MatGetRow() */ 1675 b->rowindices = 0; 1676 b->rowvalues = 0; 1677 b->getrowactive = PETSC_FALSE; 1678 1679 /* hash table stuff */ 1680 b->ht = 0; 1681 b->hd = 0; 1682 b->ht_size = 0; 1683 b->ht_flag = PETSC_FALSE; 1684 b->ht_fact = 0; 1685 b->ht_total_ct = 0; 1686 b->ht_insert_ct = 0; 1687 1688 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1689 if (flg) { 1690 PetscReal fact = 1.39; 1691 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1692 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1693 if (fact <= 1.0) fact = 1.39; 1694 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1695 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1696 } 1697 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1698 "MatStoreValues_MPISBAIJ", 1699 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1700 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1701 "MatRetrieveValues_MPISBAIJ", 1702 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1703 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1704 "MatGetDiagonalBlock_MPISBAIJ", 1705 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1706 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1707 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1708 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1709 B->symmetric = PETSC_TRUE; 1710 B->structurally_symmetric = PETSC_TRUE; 1711 B->symmetric_set = PETSC_TRUE; 1712 B->structurally_symmetric_set = PETSC_TRUE; 1713 PetscFunctionReturn(0); 1714 } 1715 EXTERN_C_END 1716 1717 /*MC 1718 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1719 1720 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1721 and MATMPISBAIJ otherwise. 1722 1723 Options Database Keys: 1724 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1725 1726 Level: beginner 1727 1728 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1729 M*/ 1730 1731 EXTERN_C_BEGIN 1732 #undef __FUNCT__ 1733 #define __FUNCT__ "MatCreate_SBAIJ" 1734 PetscErrorCode MatCreate_SBAIJ(Mat A) 1735 { 1736 PetscErrorCode ierr; 1737 PetscMPIInt size; 1738 1739 PetscFunctionBegin; 1740 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1741 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1742 if (size == 1) { 1743 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1744 } else { 1745 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1746 } 1747 PetscFunctionReturn(0); 1748 } 1749 EXTERN_C_END 1750 1751 #undef __FUNCT__ 1752 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1753 /*@C 1754 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1755 the user should preallocate the matrix storage by setting the parameters 1756 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1757 performance can be increased by more than a factor of 50. 1758 1759 Collective on Mat 1760 1761 Input Parameters: 1762 + A - the matrix 1763 . bs - size of blockk 1764 . d_nz - number of block nonzeros per block row in diagonal portion of local 1765 submatrix (same for all local rows) 1766 . d_nnz - array containing the number of block nonzeros in the various block rows 1767 in the upper triangular and diagonal part of the in diagonal portion of the local 1768 (possibly different for each block row) or PETSC_NULL. You must leave room 1769 for the diagonal entry even if it is zero. 1770 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1771 submatrix (same for all local rows). 1772 - o_nnz - array containing the number of nonzeros in the various block rows of the 1773 off-diagonal portion of the local submatrix (possibly different for 1774 each block row) or PETSC_NULL. 1775 1776 1777 Options Database Keys: 1778 . -mat_no_unroll - uses code that does not unroll the loops in the 1779 block calculations (much slower) 1780 . -mat_block_size - size of the blocks to use 1781 1782 Notes: 1783 1784 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1785 than it must be used on all processors that share the object for that argument. 1786 1787 If the *_nnz parameter is given then the *_nz parameter is ignored 1788 1789 Storage Information: 1790 For a square global matrix we define each processor's diagonal portion 1791 to be its local rows and the corresponding columns (a square submatrix); 1792 each processor's off-diagonal portion encompasses the remainder of the 1793 local matrix (a rectangular submatrix). 1794 1795 The user can specify preallocated storage for the diagonal part of 1796 the local submatrix with either d_nz or d_nnz (not both). Set 1797 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1798 memory allocation. Likewise, specify preallocated storage for the 1799 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1800 1801 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1802 the figure below we depict these three local rows and all columns (0-11). 1803 1804 .vb 1805 0 1 2 3 4 5 6 7 8 9 10 11 1806 ------------------- 1807 row 3 | o o o d d d o o o o o o 1808 row 4 | o o o d d d o o o o o o 1809 row 5 | o o o d d d o o o o o o 1810 ------------------- 1811 .ve 1812 1813 Thus, any entries in the d locations are stored in the d (diagonal) 1814 submatrix, and any entries in the o locations are stored in the 1815 o (off-diagonal) submatrix. Note that the d matrix is stored in 1816 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1817 1818 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1819 plus the diagonal part of the d matrix, 1820 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1821 In general, for PDE problems in which most nonzeros are near the diagonal, 1822 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1823 or you will get TERRIBLE performance; see the users' manual chapter on 1824 matrices. 1825 1826 Level: intermediate 1827 1828 .keywords: matrix, block, aij, compressed row, sparse, parallel 1829 1830 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1831 @*/ 1832 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1833 { 1834 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1835 1836 PetscFunctionBegin; 1837 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1838 if (f) { 1839 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1840 } 1841 PetscFunctionReturn(0); 1842 } 1843 1844 #undef __FUNCT__ 1845 #define __FUNCT__ "MatCreateMPISBAIJ" 1846 /*@C 1847 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1848 (block compressed row). For good matrix assembly performance 1849 the user should preallocate the matrix storage by setting the parameters 1850 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1851 performance can be increased by more than a factor of 50. 1852 1853 Collective on MPI_Comm 1854 1855 Input Parameters: 1856 + comm - MPI communicator 1857 . bs - size of blockk 1858 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1859 This value should be the same as the local size used in creating the 1860 y vector for the matrix-vector product y = Ax. 1861 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1862 This value should be the same as the local size used in creating the 1863 x vector for the matrix-vector product y = Ax. 1864 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1865 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1866 . d_nz - number of block nonzeros per block row in diagonal portion of local 1867 submatrix (same for all local rows) 1868 . d_nnz - array containing the number of block nonzeros in the various block rows 1869 in the upper triangular portion of the in diagonal portion of the local 1870 (possibly different for each block block row) or PETSC_NULL. 1871 You must leave room for the diagonal entry even if it is zero. 1872 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1873 submatrix (same for all local rows). 1874 - o_nnz - array containing the number of nonzeros in the various block rows of the 1875 off-diagonal portion of the local submatrix (possibly different for 1876 each block row) or PETSC_NULL. 1877 1878 Output Parameter: 1879 . A - the matrix 1880 1881 Options Database Keys: 1882 . -mat_no_unroll - uses code that does not unroll the loops in the 1883 block calculations (much slower) 1884 . -mat_block_size - size of the blocks to use 1885 . -mat_mpi - use the parallel matrix data structures even on one processor 1886 (defaults to using SeqBAIJ format on one processor) 1887 1888 Notes: 1889 The user MUST specify either the local or global matrix dimensions 1890 (possibly both). 1891 1892 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1893 than it must be used on all processors that share the object for that argument. 1894 1895 If the *_nnz parameter is given then the *_nz parameter is ignored 1896 1897 Storage Information: 1898 For a square global matrix we define each processor's diagonal portion 1899 to be its local rows and the corresponding columns (a square submatrix); 1900 each processor's off-diagonal portion encompasses the remainder of the 1901 local matrix (a rectangular submatrix). 1902 1903 The user can specify preallocated storage for the diagonal part of 1904 the local submatrix with either d_nz or d_nnz (not both). Set 1905 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1906 memory allocation. Likewise, specify preallocated storage for the 1907 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1908 1909 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1910 the figure below we depict these three local rows and all columns (0-11). 1911 1912 .vb 1913 0 1 2 3 4 5 6 7 8 9 10 11 1914 ------------------- 1915 row 3 | o o o d d d o o o o o o 1916 row 4 | o o o d d d o o o o o o 1917 row 5 | o o o d d d o o o o o o 1918 ------------------- 1919 .ve 1920 1921 Thus, any entries in the d locations are stored in the d (diagonal) 1922 submatrix, and any entries in the o locations are stored in the 1923 o (off-diagonal) submatrix. Note that the d matrix is stored in 1924 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1925 1926 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1927 plus the diagonal part of the d matrix, 1928 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1929 In general, for PDE problems in which most nonzeros are near the diagonal, 1930 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1931 or you will get TERRIBLE performance; see the users' manual chapter on 1932 matrices. 1933 1934 Level: intermediate 1935 1936 .keywords: matrix, block, aij, compressed row, sparse, parallel 1937 1938 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1939 @*/ 1940 1941 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) 1942 { 1943 PetscErrorCode ierr; 1944 PetscMPIInt size; 1945 1946 PetscFunctionBegin; 1947 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1948 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1949 if (size > 1) { 1950 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1951 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1952 } else { 1953 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1954 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1955 } 1956 PetscFunctionReturn(0); 1957 } 1958 1959 1960 #undef __FUNCT__ 1961 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1962 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1963 { 1964 Mat mat; 1965 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1966 PetscErrorCode ierr; 1967 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 1968 PetscScalar *array; 1969 1970 PetscFunctionBegin; 1971 *newmat = 0; 1972 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1973 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 1974 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1975 1976 mat->factor = matin->factor; 1977 mat->preallocated = PETSC_TRUE; 1978 mat->assembled = PETSC_TRUE; 1979 mat->insertmode = NOT_SET_VALUES; 1980 1981 a = (Mat_MPISBAIJ*)mat->data; 1982 mat->bs = matin->bs; 1983 a->bs2 = oldmat->bs2; 1984 a->mbs = oldmat->mbs; 1985 a->nbs = oldmat->nbs; 1986 a->Mbs = oldmat->Mbs; 1987 a->Nbs = oldmat->Nbs; 1988 1989 a->rstart = oldmat->rstart; 1990 a->rend = oldmat->rend; 1991 a->cstart = oldmat->cstart; 1992 a->cend = oldmat->cend; 1993 a->size = oldmat->size; 1994 a->rank = oldmat->rank; 1995 a->donotstash = oldmat->donotstash; 1996 a->roworiented = oldmat->roworiented; 1997 a->rowindices = 0; 1998 a->rowvalues = 0; 1999 a->getrowactive = PETSC_FALSE; 2000 a->barray = 0; 2001 a->rstart_bs = oldmat->rstart_bs; 2002 a->rend_bs = oldmat->rend_bs; 2003 a->cstart_bs = oldmat->cstart_bs; 2004 a->cend_bs = oldmat->cend_bs; 2005 2006 /* hash table stuff */ 2007 a->ht = 0; 2008 a->hd = 0; 2009 a->ht_size = 0; 2010 a->ht_flag = oldmat->ht_flag; 2011 a->ht_fact = oldmat->ht_fact; 2012 a->ht_total_ct = 0; 2013 a->ht_insert_ct = 0; 2014 2015 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2016 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2017 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2018 if (oldmat->colmap) { 2019 #if defined (PETSC_USE_CTABLE) 2020 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2021 #else 2022 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2023 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 2024 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2025 #endif 2026 } else a->colmap = 0; 2027 2028 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2029 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2030 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 2031 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2032 } else a->garray = 0; 2033 2034 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2035 PetscLogObjectParent(mat,a->lvec); 2036 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2037 PetscLogObjectParent(mat,a->Mvctx); 2038 2039 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2040 PetscLogObjectParent(mat,a->slvec0); 2041 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2042 PetscLogObjectParent(mat,a->slvec1); 2043 2044 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2045 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2046 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2047 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2048 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2049 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2050 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2051 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2052 PetscLogObjectParent(mat,a->slvec0); 2053 PetscLogObjectParent(mat,a->slvec1); 2054 PetscLogObjectParent(mat,a->slvec0b); 2055 PetscLogObjectParent(mat,a->slvec1a); 2056 PetscLogObjectParent(mat,a->slvec1b); 2057 2058 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2059 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2060 a->sMvctx = oldmat->sMvctx; 2061 PetscLogObjectParent(mat,a->sMvctx); 2062 2063 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2064 PetscLogObjectParent(mat,a->A); 2065 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2066 PetscLogObjectParent(mat,a->B); 2067 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2068 *newmat = mat; 2069 PetscFunctionReturn(0); 2070 } 2071 2072 #include "petscsys.h" 2073 2074 #undef __FUNCT__ 2075 #define __FUNCT__ "MatLoad_MPISBAIJ" 2076 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2077 { 2078 Mat A; 2079 PetscErrorCode ierr; 2080 PetscInt i,nz,j,rstart,rend; 2081 PetscScalar *vals,*buf; 2082 MPI_Comm comm = ((PetscObject)viewer)->comm; 2083 MPI_Status status; 2084 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners; 2085 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2086 PetscInt *locrowlens,*procsnz = 0,jj,*mycols,*ibuf; 2087 PetscInt bs=1,Mbs,mbs,extra_rows; 2088 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2089 PetscInt dcount,kmax,k,nzcount,tmp; 2090 int fd; 2091 2092 PetscFunctionBegin; 2093 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2094 2095 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2096 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2097 if (!rank) { 2098 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2099 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2100 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2101 if (header[3] < 0) { 2102 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2103 } 2104 } 2105 2106 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2107 M = header[1]; N = header[2]; 2108 2109 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2110 2111 /* 2112 This code adds extra rows to make sure the number of rows is 2113 divisible by the blocksize 2114 */ 2115 Mbs = M/bs; 2116 extra_rows = bs - M + bs*(Mbs); 2117 if (extra_rows == bs) extra_rows = 0; 2118 else Mbs++; 2119 if (extra_rows &&!rank) { 2120 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2121 } 2122 2123 /* determine ownership of all rows */ 2124 mbs = Mbs/size + ((Mbs % size) > rank); 2125 m = mbs*bs; 2126 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2127 browners = rowners + size + 1; 2128 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2129 rowners[0] = 0; 2130 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2131 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2132 rstart = rowners[rank]; 2133 rend = rowners[rank+1]; 2134 2135 /* distribute row lengths to all processors */ 2136 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2137 if (!rank) { 2138 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2139 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2140 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2141 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2142 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2143 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2144 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2145 } else { 2146 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2147 } 2148 2149 if (!rank) { /* procs[0] */ 2150 /* calculate the number of nonzeros on each processor */ 2151 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2152 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2153 for (i=0; i<size; i++) { 2154 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2155 procsnz[i] += rowlengths[j]; 2156 } 2157 } 2158 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2159 2160 /* determine max buffer needed and allocate it */ 2161 maxnz = 0; 2162 for (i=0; i<size; i++) { 2163 maxnz = PetscMax(maxnz,procsnz[i]); 2164 } 2165 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2166 2167 /* read in my part of the matrix column indices */ 2168 nz = procsnz[0]; 2169 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2170 mycols = ibuf; 2171 if (size == 1) nz -= extra_rows; 2172 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2173 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2174 2175 /* read in every ones (except the last) and ship off */ 2176 for (i=1; i<size-1; i++) { 2177 nz = procsnz[i]; 2178 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2179 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2180 } 2181 /* read in the stuff for the last proc */ 2182 if (size != 1) { 2183 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2184 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2185 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2186 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2187 } 2188 ierr = PetscFree(cols);CHKERRQ(ierr); 2189 } else { /* procs[i], i>0 */ 2190 /* determine buffer space needed for message */ 2191 nz = 0; 2192 for (i=0; i<m; i++) { 2193 nz += locrowlens[i]; 2194 } 2195 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2196 mycols = ibuf; 2197 /* receive message of column indices*/ 2198 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2199 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2200 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2201 } 2202 2203 /* loop over local rows, determining number of off diagonal entries */ 2204 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2205 odlens = dlens + (rend-rstart); 2206 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2207 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2208 masked1 = mask + Mbs; 2209 masked2 = masked1 + Mbs; 2210 rowcount = 0; nzcount = 0; 2211 for (i=0; i<mbs; i++) { 2212 dcount = 0; 2213 odcount = 0; 2214 for (j=0; j<bs; j++) { 2215 kmax = locrowlens[rowcount]; 2216 for (k=0; k<kmax; k++) { 2217 tmp = mycols[nzcount++]/bs; /* block col. index */ 2218 if (!mask[tmp]) { 2219 mask[tmp] = 1; 2220 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2221 else masked1[dcount++] = tmp; /* entry in diag portion */ 2222 } 2223 } 2224 rowcount++; 2225 } 2226 2227 dlens[i] = dcount; /* d_nzz[i] */ 2228 odlens[i] = odcount; /* o_nzz[i] */ 2229 2230 /* zero out the mask elements we set */ 2231 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2232 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2233 } 2234 2235 /* create our matrix */ 2236 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2237 ierr = MatSetType(A,type);CHKERRQ(ierr); 2238 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2239 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2240 2241 if (!rank) { 2242 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2243 /* read in my part of the matrix numerical values */ 2244 nz = procsnz[0]; 2245 vals = buf; 2246 mycols = ibuf; 2247 if (size == 1) nz -= extra_rows; 2248 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2249 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2250 2251 /* insert into matrix */ 2252 jj = rstart*bs; 2253 for (i=0; i<m; i++) { 2254 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2255 mycols += locrowlens[i]; 2256 vals += locrowlens[i]; 2257 jj++; 2258 } 2259 2260 /* read in other processors (except the last one) and ship out */ 2261 for (i=1; i<size-1; i++) { 2262 nz = procsnz[i]; 2263 vals = buf; 2264 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2265 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2266 } 2267 /* the last proc */ 2268 if (size != 1){ 2269 nz = procsnz[i] - extra_rows; 2270 vals = buf; 2271 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2272 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2273 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2274 } 2275 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2276 2277 } else { 2278 /* receive numeric values */ 2279 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2280 2281 /* receive message of values*/ 2282 vals = buf; 2283 mycols = ibuf; 2284 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2285 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2286 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2287 2288 /* insert into matrix */ 2289 jj = rstart*bs; 2290 for (i=0; i<m; i++) { 2291 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2292 mycols += locrowlens[i]; 2293 vals += locrowlens[i]; 2294 jj++; 2295 } 2296 } 2297 2298 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2299 ierr = PetscFree(buf);CHKERRQ(ierr); 2300 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2301 ierr = PetscFree(rowners);CHKERRQ(ierr); 2302 ierr = PetscFree(dlens);CHKERRQ(ierr); 2303 ierr = PetscFree(mask);CHKERRQ(ierr); 2304 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2305 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2306 *newmat = A; 2307 PetscFunctionReturn(0); 2308 } 2309 2310 #undef __FUNCT__ 2311 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2312 /*XXXXX@ 2313 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2314 2315 Input Parameters: 2316 . mat - the matrix 2317 . fact - factor 2318 2319 Collective on Mat 2320 2321 Level: advanced 2322 2323 Notes: 2324 This can also be set by the command line option: -mat_use_hash_table fact 2325 2326 .keywords: matrix, hashtable, factor, HT 2327 2328 .seealso: MatSetOption() 2329 @XXXXX*/ 2330 2331 2332 #undef __FUNCT__ 2333 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2334 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2335 { 2336 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2337 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2338 PetscReal atmp; 2339 PetscReal *work,*svalues,*rvalues; 2340 PetscErrorCode ierr; 2341 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2342 PetscMPIInt rank,size; 2343 PetscInt *rowners_bs,dest,count,source; 2344 PetscScalar *va; 2345 MatScalar *ba; 2346 MPI_Status stat; 2347 2348 PetscFunctionBegin; 2349 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2350 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2351 2352 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2353 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2354 2355 bs = A->bs; 2356 mbs = a->mbs; 2357 Mbs = a->Mbs; 2358 ba = b->a; 2359 bi = b->i; 2360 bj = b->j; 2361 2362 /* find ownerships */ 2363 rowners_bs = a->rowners_bs; 2364 2365 /* each proc creates an array to be distributed */ 2366 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2367 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2368 2369 /* row_max for B */ 2370 if (rank != size-1){ 2371 for (i=0; i<mbs; i++) { 2372 ncols = bi[1] - bi[0]; bi++; 2373 brow = bs*i; 2374 for (j=0; j<ncols; j++){ 2375 bcol = bs*(*bj); 2376 for (kcol=0; kcol<bs; kcol++){ 2377 col = bcol + kcol; /* local col index */ 2378 col += rowners_bs[rank+1]; /* global col index */ 2379 for (krow=0; krow<bs; krow++){ 2380 atmp = PetscAbsScalar(*ba); ba++; 2381 row = brow + krow; /* local row index */ 2382 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2383 if (work[col] < atmp) work[col] = atmp; 2384 } 2385 } 2386 bj++; 2387 } 2388 } 2389 2390 /* send values to its owners */ 2391 for (dest=rank+1; dest<size; dest++){ 2392 svalues = work + rowners_bs[dest]; 2393 count = rowners_bs[dest+1]-rowners_bs[dest]; 2394 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2395 } 2396 } 2397 2398 /* receive values */ 2399 if (rank){ 2400 rvalues = work; 2401 count = rowners_bs[rank+1]-rowners_bs[rank]; 2402 for (source=0; source<rank; source++){ 2403 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2404 /* process values */ 2405 for (i=0; i<count; i++){ 2406 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2407 } 2408 } 2409 } 2410 2411 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2412 ierr = PetscFree(work);CHKERRQ(ierr); 2413 PetscFunctionReturn(0); 2414 } 2415 2416 #undef __FUNCT__ 2417 #define __FUNCT__ "MatRelax_MPISBAIJ" 2418 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2419 { 2420 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2421 PetscErrorCode ierr; 2422 PetscInt mbs=mat->mbs,bs=matin->bs; 2423 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2424 Vec bb1; 2425 2426 PetscFunctionBegin; 2427 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2428 if (bs > 1) 2429 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2430 2431 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2432 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2433 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2434 its--; 2435 } 2436 2437 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2438 while (its--){ 2439 2440 /* lower triangular part: slvec0b = - B^T*xx */ 2441 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2442 2443 /* copy xx into slvec0a */ 2444 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2445 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2446 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2447 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2448 2449 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2450 2451 /* copy bb into slvec1a */ 2452 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2453 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2454 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2455 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2456 2457 /* set slvec1b = 0 */ 2458 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2459 2460 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2461 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2462 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2463 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2464 2465 /* upper triangular part: bb1 = bb1 - B*x */ 2466 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2467 2468 /* local diagonal sweep */ 2469 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2470 } 2471 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2472 } else { 2473 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2474 } 2475 PetscFunctionReturn(0); 2476 } 2477 2478 #undef __FUNCT__ 2479 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2480 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2481 { 2482 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2483 PetscErrorCode ierr; 2484 PetscScalar mone=-1.0; 2485 Vec lvec1,bb1; 2486 2487 PetscFunctionBegin; 2488 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2489 if (matin->bs > 1) 2490 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2491 2492 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2493 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2494 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2495 its--; 2496 } 2497 2498 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2499 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2500 while (its--){ 2501 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2502 2503 /* lower diagonal part: bb1 = bb - B^T*xx */ 2504 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2505 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2506 2507 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2508 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2509 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2510 2511 /* upper diagonal part: bb1 = bb1 - B*x */ 2512 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2513 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2514 2515 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2516 2517 /* diagonal sweep */ 2518 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2519 } 2520 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2521 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2522 } else { 2523 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2524 } 2525 PetscFunctionReturn(0); 2526 } 2527 2528