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 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 680 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 681 682 if (baij->rowvalues) { 683 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 684 baij->rowvalues = 0; 685 } 686 687 PetscFunctionReturn(0); 688 } 689 690 #undef __FUNCT__ 691 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 692 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 693 { 694 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 695 PetscErrorCode ierr; 696 PetscInt bs = mat->bs; 697 PetscMPIInt size = baij->size,rank = baij->rank; 698 PetscTruth iascii,isdraw; 699 PetscViewer sviewer; 700 PetscViewerFormat format; 701 702 PetscFunctionBegin; 703 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 704 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 705 if (iascii) { 706 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 707 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 708 MatInfo info; 709 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 710 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 711 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 712 rank,mat->m,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 713 mat->bs,(PetscInt)info.memory);CHKERRQ(ierr); 714 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 715 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 716 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 717 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 718 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 719 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 720 PetscFunctionReturn(0); 721 } else if (format == PETSC_VIEWER_ASCII_INFO) { 722 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 723 PetscFunctionReturn(0); 724 } 725 } 726 727 if (isdraw) { 728 PetscDraw draw; 729 PetscTruth isnull; 730 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 731 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 732 } 733 734 if (size == 1) { 735 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 736 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 737 } else { 738 /* assemble the entire matrix onto first processor. */ 739 Mat A; 740 Mat_SeqSBAIJ *Aloc; 741 Mat_SeqBAIJ *Bloc; 742 PetscInt M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 743 MatScalar *a; 744 745 /* Should this be the same type as mat? */ 746 if (!rank) { 747 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 748 } else { 749 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 750 } 751 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 752 ierr = MatMPISBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 753 PetscLogObjectParent(mat,A); 754 755 /* copy over the A part */ 756 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 757 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 758 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 759 760 for (i=0; i<mbs; i++) { 761 rvals[0] = bs*(baij->rstart + i); 762 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 763 for (j=ai[i]; j<ai[i+1]; j++) { 764 col = (baij->cstart+aj[j])*bs; 765 for (k=0; k<bs; k++) { 766 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 767 col++; a += bs; 768 } 769 } 770 } 771 /* copy over the B part */ 772 Bloc = (Mat_SeqBAIJ*)baij->B->data; 773 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 774 for (i=0; i<mbs; i++) { 775 rvals[0] = bs*(baij->rstart + i); 776 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 777 for (j=ai[i]; j<ai[i+1]; j++) { 778 col = baij->garray[aj[j]]*bs; 779 for (k=0; k<bs; k++) { 780 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 781 col++; a += bs; 782 } 783 } 784 } 785 ierr = PetscFree(rvals);CHKERRQ(ierr); 786 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 787 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 788 /* 789 Everyone has to call to draw the matrix since the graphics waits are 790 synchronized across all processors that share the PetscDraw object 791 */ 792 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 793 if (!rank) { 794 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 795 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 796 } 797 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 798 ierr = MatDestroy(A);CHKERRQ(ierr); 799 } 800 PetscFunctionReturn(0); 801 } 802 803 #undef __FUNCT__ 804 #define __FUNCT__ "MatView_MPISBAIJ" 805 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 806 { 807 PetscErrorCode ierr; 808 PetscTruth iascii,isdraw,issocket,isbinary; 809 810 PetscFunctionBegin; 811 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 812 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 813 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 814 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 815 if (iascii || isdraw || issocket || isbinary) { 816 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 817 } else { 818 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 819 } 820 PetscFunctionReturn(0); 821 } 822 823 #undef __FUNCT__ 824 #define __FUNCT__ "MatDestroy_MPISBAIJ" 825 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 826 { 827 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 828 PetscErrorCode ierr; 829 830 PetscFunctionBegin; 831 #if defined(PETSC_USE_LOG) 832 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 833 #endif 834 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 835 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 836 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 837 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 838 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 839 #if defined (PETSC_USE_CTABLE) 840 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 841 #else 842 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 843 #endif 844 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 845 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 846 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 847 if (baij->slvec0) { 848 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 849 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 850 } 851 if (baij->slvec1) { 852 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 853 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 854 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 855 } 856 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 857 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 858 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 859 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 860 #if defined(PETSC_USE_MAT_SINGLE) 861 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 862 #endif 863 ierr = PetscFree(baij);CHKERRQ(ierr); 864 865 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 866 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 867 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 868 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 869 PetscFunctionReturn(0); 870 } 871 872 #undef __FUNCT__ 873 #define __FUNCT__ "MatMult_MPISBAIJ" 874 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 875 { 876 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 877 PetscErrorCode ierr; 878 PetscInt nt,mbs=a->mbs,bs=A->bs; 879 PetscScalar *x,*from,zero=0.0; 880 881 PetscFunctionBegin; 882 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 883 if (nt != A->n) { 884 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 885 } 886 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 887 if (nt != A->m) { 888 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 889 } 890 891 /* diagonal part */ 892 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 893 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 894 895 /* subdiagonal part */ 896 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 897 898 /* copy x into the vec slvec0 */ 899 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 900 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 901 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 902 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 903 904 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 905 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 906 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 907 908 /* supperdiagonal part */ 909 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 910 911 PetscFunctionReturn(0); 912 } 913 914 #undef __FUNCT__ 915 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 916 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 917 { 918 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 919 PetscErrorCode ierr; 920 PetscInt nt; 921 922 PetscFunctionBegin; 923 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 924 if (nt != A->n) { 925 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 926 } 927 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 928 if (nt != A->m) { 929 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 930 } 931 932 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 933 /* do diagonal part */ 934 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 935 /* do supperdiagonal part */ 936 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 937 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 938 /* do subdiagonal part */ 939 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 940 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 941 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 942 943 PetscFunctionReturn(0); 944 } 945 946 #undef __FUNCT__ 947 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 948 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 949 { 950 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 951 PetscErrorCode ierr; 952 PetscInt mbs=a->mbs,bs=A->bs; 953 PetscScalar *x,*from,zero=0.0; 954 955 PetscFunctionBegin; 956 /* 957 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 958 PetscSynchronizedFlush(A->comm); 959 */ 960 /* diagonal part */ 961 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 962 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 963 964 /* subdiagonal part */ 965 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 966 967 /* copy x into the vec slvec0 */ 968 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 969 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 970 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 971 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 972 973 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 974 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 975 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 976 977 /* supperdiagonal part */ 978 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 979 980 PetscFunctionReturn(0); 981 } 982 983 #undef __FUNCT__ 984 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 985 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 986 { 987 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 988 PetscErrorCode ierr; 989 990 PetscFunctionBegin; 991 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 992 /* do diagonal part */ 993 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 994 /* do supperdiagonal part */ 995 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 996 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 997 998 /* do subdiagonal part */ 999 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1000 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1001 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1002 1003 PetscFunctionReturn(0); 1004 } 1005 1006 #undef __FUNCT__ 1007 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1008 PetscErrorCode MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1009 { 1010 PetscErrorCode ierr; 1011 1012 PetscFunctionBegin; 1013 ierr = MatMult(A,xx,yy);CHKERRQ(ierr); 1014 PetscFunctionReturn(0); 1015 } 1016 1017 #undef __FUNCT__ 1018 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1019 PetscErrorCode MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1020 { 1021 PetscErrorCode ierr; 1022 1023 PetscFunctionBegin; 1024 ierr = MatMultAdd(A,xx,yy,zz);CHKERRQ(ierr); 1025 PetscFunctionReturn(0); 1026 } 1027 1028 /* 1029 This only works correctly for square matrices where the subblock A->A is the 1030 diagonal block 1031 */ 1032 #undef __FUNCT__ 1033 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1034 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1035 { 1036 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1037 PetscErrorCode ierr; 1038 1039 PetscFunctionBegin; 1040 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1041 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1042 PetscFunctionReturn(0); 1043 } 1044 1045 #undef __FUNCT__ 1046 #define __FUNCT__ "MatScale_MPISBAIJ" 1047 PetscErrorCode MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1048 { 1049 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1050 PetscErrorCode ierr; 1051 1052 PetscFunctionBegin; 1053 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1054 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 #undef __FUNCT__ 1059 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1060 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1061 { 1062 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1063 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1064 PetscErrorCode ierr; 1065 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1066 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1067 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1068 1069 PetscFunctionBegin; 1070 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1071 mat->getrowactive = PETSC_TRUE; 1072 1073 if (!mat->rowvalues && (idx || v)) { 1074 /* 1075 allocate enough space to hold information from the longest row. 1076 */ 1077 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1078 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1079 PetscInt max = 1,mbs = mat->mbs,tmp; 1080 for (i=0; i<mbs; i++) { 1081 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1082 if (max < tmp) { max = tmp; } 1083 } 1084 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1085 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1086 } 1087 1088 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1089 lrow = row - brstart; /* local row index */ 1090 1091 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1092 if (!v) {pvA = 0; pvB = 0;} 1093 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1094 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1095 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1096 nztot = nzA + nzB; 1097 1098 cmap = mat->garray; 1099 if (v || idx) { 1100 if (nztot) { 1101 /* Sort by increasing column numbers, assuming A and B already sorted */ 1102 PetscInt imark = -1; 1103 if (v) { 1104 *v = v_p = mat->rowvalues; 1105 for (i=0; i<nzB; i++) { 1106 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1107 else break; 1108 } 1109 imark = i; 1110 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1111 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1112 } 1113 if (idx) { 1114 *idx = idx_p = mat->rowindices; 1115 if (imark > -1) { 1116 for (i=0; i<imark; i++) { 1117 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1118 } 1119 } else { 1120 for (i=0; i<nzB; i++) { 1121 if (cmap[cworkB[i]/bs] < cstart) 1122 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1123 else break; 1124 } 1125 imark = i; 1126 } 1127 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1128 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1129 } 1130 } else { 1131 if (idx) *idx = 0; 1132 if (v) *v = 0; 1133 } 1134 } 1135 *nz = nztot; 1136 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1137 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1138 PetscFunctionReturn(0); 1139 } 1140 1141 #undef __FUNCT__ 1142 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1143 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1144 { 1145 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1146 1147 PetscFunctionBegin; 1148 if (baij->getrowactive == PETSC_FALSE) { 1149 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1150 } 1151 baij->getrowactive = PETSC_FALSE; 1152 PetscFunctionReturn(0); 1153 } 1154 1155 #undef __FUNCT__ 1156 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1157 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1158 { 1159 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1160 PetscErrorCode ierr; 1161 1162 PetscFunctionBegin; 1163 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1164 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1165 PetscFunctionReturn(0); 1166 } 1167 1168 #undef __FUNCT__ 1169 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1170 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1171 { 1172 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1173 Mat A = a->A,B = a->B; 1174 PetscErrorCode ierr; 1175 PetscReal isend[5],irecv[5]; 1176 1177 PetscFunctionBegin; 1178 info->block_size = (PetscReal)matin->bs; 1179 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1180 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1181 isend[3] = info->memory; isend[4] = info->mallocs; 1182 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1183 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1184 isend[3] += info->memory; isend[4] += info->mallocs; 1185 if (flag == MAT_LOCAL) { 1186 info->nz_used = isend[0]; 1187 info->nz_allocated = isend[1]; 1188 info->nz_unneeded = isend[2]; 1189 info->memory = isend[3]; 1190 info->mallocs = isend[4]; 1191 } else if (flag == MAT_GLOBAL_MAX) { 1192 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1193 info->nz_used = irecv[0]; 1194 info->nz_allocated = irecv[1]; 1195 info->nz_unneeded = irecv[2]; 1196 info->memory = irecv[3]; 1197 info->mallocs = irecv[4]; 1198 } else if (flag == MAT_GLOBAL_SUM) { 1199 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1200 info->nz_used = irecv[0]; 1201 info->nz_allocated = irecv[1]; 1202 info->nz_unneeded = irecv[2]; 1203 info->memory = irecv[3]; 1204 info->mallocs = irecv[4]; 1205 } else { 1206 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1207 } 1208 info->rows_global = (PetscReal)A->M; 1209 info->columns_global = (PetscReal)A->N; 1210 info->rows_local = (PetscReal)A->m; 1211 info->columns_local = (PetscReal)A->N; 1212 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1213 info->fill_ratio_needed = 0; 1214 info->factor_mallocs = 0; 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1220 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1221 { 1222 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 switch (op) { 1227 case MAT_NO_NEW_NONZERO_LOCATIONS: 1228 case MAT_YES_NEW_NONZERO_LOCATIONS: 1229 case MAT_COLUMNS_UNSORTED: 1230 case MAT_COLUMNS_SORTED: 1231 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1232 case MAT_KEEP_ZEROED_ROWS: 1233 case MAT_NEW_NONZERO_LOCATION_ERR: 1234 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1235 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1236 break; 1237 case MAT_ROW_ORIENTED: 1238 a->roworiented = PETSC_TRUE; 1239 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1240 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1241 break; 1242 case MAT_ROWS_SORTED: 1243 case MAT_ROWS_UNSORTED: 1244 case MAT_YES_NEW_DIAGONALS: 1245 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1246 break; 1247 case MAT_COLUMN_ORIENTED: 1248 a->roworiented = PETSC_FALSE; 1249 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1250 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1251 break; 1252 case MAT_IGNORE_OFF_PROC_ENTRIES: 1253 a->donotstash = PETSC_TRUE; 1254 break; 1255 case MAT_NO_NEW_DIAGONALS: 1256 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1257 case MAT_USE_HASH_TABLE: 1258 a->ht_flag = PETSC_TRUE; 1259 break; 1260 case MAT_NOT_SYMMETRIC: 1261 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1262 case MAT_HERMITIAN: 1263 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1264 case MAT_SYMMETRIC: 1265 case MAT_STRUCTURALLY_SYMMETRIC: 1266 case MAT_NOT_HERMITIAN: 1267 case MAT_SYMMETRY_ETERNAL: 1268 case MAT_NOT_SYMMETRY_ETERNAL: 1269 break; 1270 default: 1271 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1272 } 1273 PetscFunctionReturn(0); 1274 } 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1278 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1279 { 1280 PetscErrorCode ierr; 1281 PetscFunctionBegin; 1282 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1283 PetscFunctionReturn(0); 1284 } 1285 1286 #undef __FUNCT__ 1287 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1288 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1289 { 1290 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1291 Mat a = baij->A,b = baij->B; 1292 PetscErrorCode ierr; 1293 PetscInt s1,s2,s3; 1294 1295 PetscFunctionBegin; 1296 if (ll != rr) { 1297 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1298 } 1299 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1300 if (rr) { 1301 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1302 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1303 /* Overlap communication with computation. */ 1304 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1305 /*} if (ll) { */ 1306 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1307 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1308 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1309 /* } */ 1310 /* scale the diagonal block */ 1311 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1312 1313 /* if (rr) { */ 1314 /* Do a scatter end and then right scale the off-diagonal block */ 1315 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1316 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1317 } 1318 1319 PetscFunctionReturn(0); 1320 } 1321 1322 #undef __FUNCT__ 1323 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1324 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1325 { 1326 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1327 MPI_Comm comm = A->comm; 1328 static PetscTruth called = PETSC_FALSE; 1329 PetscErrorCode ierr; 1330 1331 PetscFunctionBegin; 1332 if (!a->rank) { 1333 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1334 } 1335 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1336 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1337 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1338 PetscFunctionReturn(0); 1339 } 1340 1341 #undef __FUNCT__ 1342 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1343 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1344 { 1345 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1346 PetscErrorCode ierr; 1347 1348 PetscFunctionBegin; 1349 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1350 PetscFunctionReturn(0); 1351 } 1352 1353 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1354 1355 #undef __FUNCT__ 1356 #define __FUNCT__ "MatEqual_MPISBAIJ" 1357 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1358 { 1359 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1360 Mat a,b,c,d; 1361 PetscTruth flg; 1362 PetscErrorCode ierr; 1363 1364 PetscFunctionBegin; 1365 a = matA->A; b = matA->B; 1366 c = matB->A; d = matB->B; 1367 1368 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1369 if (flg == PETSC_TRUE) { 1370 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1371 } 1372 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1373 PetscFunctionReturn(0); 1374 } 1375 1376 #undef __FUNCT__ 1377 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1378 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1379 { 1380 PetscErrorCode ierr; 1381 1382 PetscFunctionBegin; 1383 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1384 PetscFunctionReturn(0); 1385 } 1386 1387 #undef __FUNCT__ 1388 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1389 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1390 { 1391 PetscErrorCode ierr; 1392 PetscInt i; 1393 PetscTruth flg; 1394 1395 PetscFunctionBegin; 1396 for (i=0; i<n; i++) { 1397 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1398 if (!flg) { 1399 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1400 } 1401 } 1402 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1403 PetscFunctionReturn(0); 1404 } 1405 1406 1407 /* -------------------------------------------------------------------*/ 1408 static struct _MatOps MatOps_Values = { 1409 MatSetValues_MPISBAIJ, 1410 MatGetRow_MPISBAIJ, 1411 MatRestoreRow_MPISBAIJ, 1412 MatMult_MPISBAIJ, 1413 /* 4*/ MatMultAdd_MPISBAIJ, 1414 MatMultTranspose_MPISBAIJ, 1415 MatMultTransposeAdd_MPISBAIJ, 1416 0, 1417 0, 1418 0, 1419 /*10*/ 0, 1420 0, 1421 0, 1422 MatRelax_MPISBAIJ, 1423 MatTranspose_MPISBAIJ, 1424 /*15*/ MatGetInfo_MPISBAIJ, 1425 MatEqual_MPISBAIJ, 1426 MatGetDiagonal_MPISBAIJ, 1427 MatDiagonalScale_MPISBAIJ, 1428 MatNorm_MPISBAIJ, 1429 /*20*/ MatAssemblyBegin_MPISBAIJ, 1430 MatAssemblyEnd_MPISBAIJ, 1431 0, 1432 MatSetOption_MPISBAIJ, 1433 MatZeroEntries_MPISBAIJ, 1434 /*25*/ 0, 1435 0, 1436 0, 1437 0, 1438 0, 1439 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1440 0, 1441 0, 1442 0, 1443 0, 1444 /*35*/ MatDuplicate_MPISBAIJ, 1445 0, 1446 0, 1447 0, 1448 0, 1449 /*40*/ 0, 1450 MatGetSubMatrices_MPISBAIJ, 1451 MatIncreaseOverlap_MPISBAIJ, 1452 MatGetValues_MPISBAIJ, 1453 0, 1454 /*45*/ MatPrintHelp_MPISBAIJ, 1455 MatScale_MPISBAIJ, 1456 0, 1457 0, 1458 0, 1459 /*50*/ 0, 1460 0, 1461 0, 1462 0, 1463 0, 1464 /*55*/ 0, 1465 0, 1466 MatSetUnfactored_MPISBAIJ, 1467 0, 1468 MatSetValuesBlocked_MPISBAIJ, 1469 /*60*/ 0, 1470 0, 1471 0, 1472 MatGetPetscMaps_Petsc, 1473 0, 1474 /*65*/ 0, 1475 0, 1476 0, 1477 0, 1478 0, 1479 /*70*/ MatGetRowMax_MPISBAIJ, 1480 0, 1481 0, 1482 0, 1483 0, 1484 /*75*/ 0, 1485 0, 1486 0, 1487 0, 1488 0, 1489 /*80*/ 0, 1490 0, 1491 0, 1492 0, 1493 MatLoad_MPISBAIJ, 1494 /*85*/ 0, 1495 0, 1496 0, 1497 0, 1498 0, 1499 /*90*/ 0, 1500 0, 1501 0, 1502 0, 1503 0, 1504 /*95*/ 0, 1505 0, 1506 0, 1507 0}; 1508 1509 1510 EXTERN_C_BEGIN 1511 #undef __FUNCT__ 1512 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1513 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1514 { 1515 PetscFunctionBegin; 1516 *a = ((Mat_MPISBAIJ *)A->data)->A; 1517 *iscopy = PETSC_FALSE; 1518 PetscFunctionReturn(0); 1519 } 1520 EXTERN_C_END 1521 1522 EXTERN_C_BEGIN 1523 #undef __FUNCT__ 1524 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1525 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1526 { 1527 Mat_MPISBAIJ *b; 1528 PetscErrorCode ierr; 1529 PetscInt i,mbs,Mbs; 1530 1531 PetscFunctionBegin; 1532 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1533 1534 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1535 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1536 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1537 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1538 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1539 if (d_nnz) { 1540 for (i=0; i<B->m/bs; i++) { 1541 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]); 1542 } 1543 } 1544 if (o_nnz) { 1545 for (i=0; i<B->m/bs; i++) { 1546 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]); 1547 } 1548 } 1549 B->preallocated = PETSC_TRUE; 1550 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1551 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1552 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1553 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1554 1555 b = (Mat_MPISBAIJ*)B->data; 1556 mbs = B->m/bs; 1557 Mbs = B->M/bs; 1558 if (mbs*bs != B->m) { 1559 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1560 } 1561 1562 B->bs = bs; 1563 b->bs2 = bs*bs; 1564 b->mbs = mbs; 1565 b->nbs = mbs; 1566 b->Mbs = Mbs; 1567 b->Nbs = Mbs; 1568 1569 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 1570 b->rowners[0] = 0; 1571 for (i=2; i<=b->size; i++) { 1572 b->rowners[i] += b->rowners[i-1]; 1573 } 1574 b->rstart = b->rowners[b->rank]; 1575 b->rend = b->rowners[b->rank+1]; 1576 b->cstart = b->rstart; 1577 b->cend = b->rend; 1578 for (i=0; i<=b->size; i++) { 1579 b->rowners_bs[i] = b->rowners[i]*bs; 1580 } 1581 b->rstart_bs = b-> rstart*bs; 1582 b->rend_bs = b->rend*bs; 1583 1584 b->cstart_bs = b->cstart*bs; 1585 b->cend_bs = b->cend*bs; 1586 1587 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1588 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1589 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1590 PetscLogObjectParent(B,b->A); 1591 1592 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1593 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1594 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1595 PetscLogObjectParent(B,b->B); 1596 1597 /* build cache for off array entries formed */ 1598 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1599 1600 PetscFunctionReturn(0); 1601 } 1602 EXTERN_C_END 1603 1604 /*MC 1605 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1606 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1607 1608 Options Database Keys: 1609 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1610 1611 Level: beginner 1612 1613 .seealso: MatCreateMPISBAIJ 1614 M*/ 1615 1616 EXTERN_C_BEGIN 1617 #undef __FUNCT__ 1618 #define __FUNCT__ "MatCreate_MPISBAIJ" 1619 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1620 { 1621 Mat_MPISBAIJ *b; 1622 PetscErrorCode ierr; 1623 PetscTruth flg; 1624 1625 PetscFunctionBegin; 1626 1627 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1628 B->data = (void*)b; 1629 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1630 1631 B->ops->destroy = MatDestroy_MPISBAIJ; 1632 B->ops->view = MatView_MPISBAIJ; 1633 B->mapping = 0; 1634 B->factor = 0; 1635 B->assembled = PETSC_FALSE; 1636 1637 B->insertmode = NOT_SET_VALUES; 1638 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1639 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1640 1641 /* build local table of row and column ownerships */ 1642 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1643 b->cowners = b->rowners + b->size + 2; 1644 b->rowners_bs = b->cowners + b->size + 2; 1645 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1646 1647 /* build cache for off array entries formed */ 1648 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1649 b->donotstash = PETSC_FALSE; 1650 b->colmap = PETSC_NULL; 1651 b->garray = PETSC_NULL; 1652 b->roworiented = PETSC_TRUE; 1653 1654 #if defined(PETSC_USE_MAT_SINGLE) 1655 /* stuff for MatSetValues_XXX in single precision */ 1656 b->setvalueslen = 0; 1657 b->setvaluescopy = PETSC_NULL; 1658 #endif 1659 1660 /* stuff used in block assembly */ 1661 b->barray = 0; 1662 1663 /* stuff used for matrix vector multiply */ 1664 b->lvec = 0; 1665 b->Mvctx = 0; 1666 b->slvec0 = 0; 1667 b->slvec0b = 0; 1668 b->slvec1 = 0; 1669 b->slvec1a = 0; 1670 b->slvec1b = 0; 1671 b->sMvctx = 0; 1672 1673 /* stuff for MatGetRow() */ 1674 b->rowindices = 0; 1675 b->rowvalues = 0; 1676 b->getrowactive = PETSC_FALSE; 1677 1678 /* hash table stuff */ 1679 b->ht = 0; 1680 b->hd = 0; 1681 b->ht_size = 0; 1682 b->ht_flag = PETSC_FALSE; 1683 b->ht_fact = 0; 1684 b->ht_total_ct = 0; 1685 b->ht_insert_ct = 0; 1686 1687 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1688 if (flg) { 1689 PetscReal fact = 1.39; 1690 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1691 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1692 if (fact <= 1.0) fact = 1.39; 1693 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1694 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1695 } 1696 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1697 "MatStoreValues_MPISBAIJ", 1698 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1699 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1700 "MatRetrieveValues_MPISBAIJ", 1701 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1702 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1703 "MatGetDiagonalBlock_MPISBAIJ", 1704 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1705 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1706 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1707 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1708 B->symmetric = PETSC_TRUE; 1709 B->structurally_symmetric = PETSC_TRUE; 1710 B->symmetric_set = PETSC_TRUE; 1711 B->structurally_symmetric_set = PETSC_TRUE; 1712 PetscFunctionReturn(0); 1713 } 1714 EXTERN_C_END 1715 1716 /*MC 1717 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1718 1719 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1720 and MATMPISBAIJ otherwise. 1721 1722 Options Database Keys: 1723 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1724 1725 Level: beginner 1726 1727 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1728 M*/ 1729 1730 EXTERN_C_BEGIN 1731 #undef __FUNCT__ 1732 #define __FUNCT__ "MatCreate_SBAIJ" 1733 PetscErrorCode MatCreate_SBAIJ(Mat A) 1734 { 1735 PetscErrorCode ierr; 1736 PetscMPIInt size; 1737 1738 PetscFunctionBegin; 1739 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1740 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1741 if (size == 1) { 1742 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1743 } else { 1744 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1745 } 1746 PetscFunctionReturn(0); 1747 } 1748 EXTERN_C_END 1749 1750 #undef __FUNCT__ 1751 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1752 /*@C 1753 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1754 the user should preallocate the matrix storage by setting the parameters 1755 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1756 performance can be increased by more than a factor of 50. 1757 1758 Collective on Mat 1759 1760 Input Parameters: 1761 + A - the matrix 1762 . bs - size of blockk 1763 . d_nz - number of block nonzeros per block row in diagonal portion of local 1764 submatrix (same for all local rows) 1765 . d_nnz - array containing the number of block nonzeros in the various block rows 1766 in the upper triangular and diagonal part of the in diagonal portion of the local 1767 (possibly different for each block row) or PETSC_NULL. You must leave room 1768 for the diagonal entry even if it is zero. 1769 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1770 submatrix (same for all local rows). 1771 - o_nnz - array containing the number of nonzeros in the various block rows of the 1772 off-diagonal portion of the local submatrix (possibly different for 1773 each block row) or PETSC_NULL. 1774 1775 1776 Options Database Keys: 1777 . -mat_no_unroll - uses code that does not unroll the loops in the 1778 block calculations (much slower) 1779 . -mat_block_size - size of the blocks to use 1780 1781 Notes: 1782 1783 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1784 than it must be used on all processors that share the object for that argument. 1785 1786 If the *_nnz parameter is given then the *_nz parameter is ignored 1787 1788 Storage Information: 1789 For a square global matrix we define each processor's diagonal portion 1790 to be its local rows and the corresponding columns (a square submatrix); 1791 each processor's off-diagonal portion encompasses the remainder of the 1792 local matrix (a rectangular submatrix). 1793 1794 The user can specify preallocated storage for the diagonal part of 1795 the local submatrix with either d_nz or d_nnz (not both). Set 1796 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1797 memory allocation. Likewise, specify preallocated storage for the 1798 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1799 1800 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1801 the figure below we depict these three local rows and all columns (0-11). 1802 1803 .vb 1804 0 1 2 3 4 5 6 7 8 9 10 11 1805 ------------------- 1806 row 3 | o o o d d d o o o o o o 1807 row 4 | o o o d d d o o o o o o 1808 row 5 | o o o d d d o o o o o o 1809 ------------------- 1810 .ve 1811 1812 Thus, any entries in the d locations are stored in the d (diagonal) 1813 submatrix, and any entries in the o locations are stored in the 1814 o (off-diagonal) submatrix. Note that the d matrix is stored in 1815 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1816 1817 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1818 plus the diagonal part of the d matrix, 1819 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1820 In general, for PDE problems in which most nonzeros are near the diagonal, 1821 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1822 or you will get TERRIBLE performance; see the users' manual chapter on 1823 matrices. 1824 1825 Level: intermediate 1826 1827 .keywords: matrix, block, aij, compressed row, sparse, parallel 1828 1829 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1830 @*/ 1831 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1832 { 1833 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1834 1835 PetscFunctionBegin; 1836 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1837 if (f) { 1838 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1839 } 1840 PetscFunctionReturn(0); 1841 } 1842 1843 #undef __FUNCT__ 1844 #define __FUNCT__ "MatCreateMPISBAIJ" 1845 /*@C 1846 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1847 (block compressed row). For good matrix assembly performance 1848 the user should preallocate the matrix storage by setting the parameters 1849 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1850 performance can be increased by more than a factor of 50. 1851 1852 Collective on MPI_Comm 1853 1854 Input Parameters: 1855 + comm - MPI communicator 1856 . bs - size of blockk 1857 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1858 This value should be the same as the local size used in creating the 1859 y vector for the matrix-vector product y = Ax. 1860 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1861 This value should be the same as the local size used in creating the 1862 x vector for the matrix-vector product y = Ax. 1863 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1864 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1865 . d_nz - number of block nonzeros per block row in diagonal portion of local 1866 submatrix (same for all local rows) 1867 . d_nnz - array containing the number of block nonzeros in the various block rows 1868 in the upper triangular portion of the in diagonal portion of the local 1869 (possibly different for each block block row) or PETSC_NULL. 1870 You must leave room for the diagonal entry even if it is zero. 1871 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1872 submatrix (same for all local rows). 1873 - o_nnz - array containing the number of nonzeros in the various block rows of the 1874 off-diagonal portion of the local submatrix (possibly different for 1875 each block row) or PETSC_NULL. 1876 1877 Output Parameter: 1878 . A - the matrix 1879 1880 Options Database Keys: 1881 . -mat_no_unroll - uses code that does not unroll the loops in the 1882 block calculations (much slower) 1883 . -mat_block_size - size of the blocks to use 1884 . -mat_mpi - use the parallel matrix data structures even on one processor 1885 (defaults to using SeqBAIJ format on one processor) 1886 1887 Notes: 1888 The user MUST specify either the local or global matrix dimensions 1889 (possibly both). 1890 1891 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1892 than it must be used on all processors that share the object for that argument. 1893 1894 If the *_nnz parameter is given then the *_nz parameter is ignored 1895 1896 Storage Information: 1897 For a square global matrix we define each processor's diagonal portion 1898 to be its local rows and the corresponding columns (a square submatrix); 1899 each processor's off-diagonal portion encompasses the remainder of the 1900 local matrix (a rectangular submatrix). 1901 1902 The user can specify preallocated storage for the diagonal part of 1903 the local submatrix with either d_nz or d_nnz (not both). Set 1904 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1905 memory allocation. Likewise, specify preallocated storage for the 1906 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1907 1908 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1909 the figure below we depict these three local rows and all columns (0-11). 1910 1911 .vb 1912 0 1 2 3 4 5 6 7 8 9 10 11 1913 ------------------- 1914 row 3 | o o o d d d o o o o o o 1915 row 4 | o o o d d d o o o o o o 1916 row 5 | o o o d d d o o o o o o 1917 ------------------- 1918 .ve 1919 1920 Thus, any entries in the d locations are stored in the d (diagonal) 1921 submatrix, and any entries in the o locations are stored in the 1922 o (off-diagonal) submatrix. Note that the d matrix is stored in 1923 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1924 1925 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1926 plus the diagonal part of the d matrix, 1927 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1928 In general, for PDE problems in which most nonzeros are near the diagonal, 1929 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1930 or you will get TERRIBLE performance; see the users' manual chapter on 1931 matrices. 1932 1933 Level: intermediate 1934 1935 .keywords: matrix, block, aij, compressed row, sparse, parallel 1936 1937 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1938 @*/ 1939 1940 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) 1941 { 1942 PetscErrorCode ierr; 1943 PetscMPIInt size; 1944 1945 PetscFunctionBegin; 1946 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1947 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1948 if (size > 1) { 1949 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1950 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1951 } else { 1952 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1953 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1954 } 1955 PetscFunctionReturn(0); 1956 } 1957 1958 1959 #undef __FUNCT__ 1960 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1961 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1962 { 1963 Mat mat; 1964 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1965 PetscErrorCode ierr; 1966 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 1967 PetscScalar *array; 1968 1969 PetscFunctionBegin; 1970 *newmat = 0; 1971 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1972 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 1973 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1974 1975 mat->factor = matin->factor; 1976 mat->preallocated = PETSC_TRUE; 1977 mat->assembled = PETSC_TRUE; 1978 mat->insertmode = NOT_SET_VALUES; 1979 1980 a = (Mat_MPISBAIJ*)mat->data; 1981 mat->bs = matin->bs; 1982 a->bs2 = oldmat->bs2; 1983 a->mbs = oldmat->mbs; 1984 a->nbs = oldmat->nbs; 1985 a->Mbs = oldmat->Mbs; 1986 a->Nbs = oldmat->Nbs; 1987 1988 a->rstart = oldmat->rstart; 1989 a->rend = oldmat->rend; 1990 a->cstart = oldmat->cstart; 1991 a->cend = oldmat->cend; 1992 a->size = oldmat->size; 1993 a->rank = oldmat->rank; 1994 a->donotstash = oldmat->donotstash; 1995 a->roworiented = oldmat->roworiented; 1996 a->rowindices = 0; 1997 a->rowvalues = 0; 1998 a->getrowactive = PETSC_FALSE; 1999 a->barray = 0; 2000 a->rstart_bs = oldmat->rstart_bs; 2001 a->rend_bs = oldmat->rend_bs; 2002 a->cstart_bs = oldmat->cstart_bs; 2003 a->cend_bs = oldmat->cend_bs; 2004 2005 /* hash table stuff */ 2006 a->ht = 0; 2007 a->hd = 0; 2008 a->ht_size = 0; 2009 a->ht_flag = oldmat->ht_flag; 2010 a->ht_fact = oldmat->ht_fact; 2011 a->ht_total_ct = 0; 2012 a->ht_insert_ct = 0; 2013 2014 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2015 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2016 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2017 if (oldmat->colmap) { 2018 #if defined (PETSC_USE_CTABLE) 2019 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2020 #else 2021 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2022 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 2023 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2024 #endif 2025 } else a->colmap = 0; 2026 2027 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2028 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2029 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 2030 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2031 } else a->garray = 0; 2032 2033 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2034 PetscLogObjectParent(mat,a->lvec); 2035 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2036 PetscLogObjectParent(mat,a->Mvctx); 2037 2038 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2039 PetscLogObjectParent(mat,a->slvec0); 2040 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2041 PetscLogObjectParent(mat,a->slvec1); 2042 2043 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2044 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2045 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2046 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2047 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2048 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2049 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2050 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2051 PetscLogObjectParent(mat,a->slvec0); 2052 PetscLogObjectParent(mat,a->slvec1); 2053 PetscLogObjectParent(mat,a->slvec0b); 2054 PetscLogObjectParent(mat,a->slvec1a); 2055 PetscLogObjectParent(mat,a->slvec1b); 2056 2057 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2058 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2059 a->sMvctx = oldmat->sMvctx; 2060 PetscLogObjectParent(mat,a->sMvctx); 2061 2062 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2063 PetscLogObjectParent(mat,a->A); 2064 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2065 PetscLogObjectParent(mat,a->B); 2066 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2067 *newmat = mat; 2068 PetscFunctionReturn(0); 2069 } 2070 2071 #include "petscsys.h" 2072 2073 #undef __FUNCT__ 2074 #define __FUNCT__ "MatLoad_MPISBAIJ" 2075 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2076 { 2077 Mat A; 2078 PetscErrorCode ierr; 2079 PetscInt i,nz,j,rstart,rend; 2080 PetscScalar *vals,*buf; 2081 MPI_Comm comm = ((PetscObject)viewer)->comm; 2082 MPI_Status status; 2083 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners; 2084 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2085 PetscInt *locrowlens,*procsnz = 0,jj,*mycols,*ibuf; 2086 PetscInt bs=1,Mbs,mbs,extra_rows; 2087 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2088 PetscInt dcount,kmax,k,nzcount,tmp; 2089 int fd; 2090 2091 PetscFunctionBegin; 2092 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2093 2094 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2095 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2096 if (!rank) { 2097 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2098 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2099 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2100 if (header[3] < 0) { 2101 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2102 } 2103 } 2104 2105 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2106 M = header[1]; N = header[2]; 2107 2108 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2109 2110 /* 2111 This code adds extra rows to make sure the number of rows is 2112 divisible by the blocksize 2113 */ 2114 Mbs = M/bs; 2115 extra_rows = bs - M + bs*(Mbs); 2116 if (extra_rows == bs) extra_rows = 0; 2117 else Mbs++; 2118 if (extra_rows &&!rank) { 2119 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2120 } 2121 2122 /* determine ownership of all rows */ 2123 mbs = Mbs/size + ((Mbs % size) > rank); 2124 m = mbs*bs; 2125 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2126 browners = rowners + size + 1; 2127 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2128 rowners[0] = 0; 2129 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2130 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2131 rstart = rowners[rank]; 2132 rend = rowners[rank+1]; 2133 2134 /* distribute row lengths to all processors */ 2135 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2136 if (!rank) { 2137 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2138 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2139 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2140 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2141 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2142 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2143 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2144 } else { 2145 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2146 } 2147 2148 if (!rank) { /* procs[0] */ 2149 /* calculate the number of nonzeros on each processor */ 2150 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2151 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2152 for (i=0; i<size; i++) { 2153 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2154 procsnz[i] += rowlengths[j]; 2155 } 2156 } 2157 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2158 2159 /* determine max buffer needed and allocate it */ 2160 maxnz = 0; 2161 for (i=0; i<size; i++) { 2162 maxnz = PetscMax(maxnz,procsnz[i]); 2163 } 2164 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2165 2166 /* read in my part of the matrix column indices */ 2167 nz = procsnz[0]; 2168 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2169 mycols = ibuf; 2170 if (size == 1) nz -= extra_rows; 2171 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2172 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2173 2174 /* read in every ones (except the last) and ship off */ 2175 for (i=1; i<size-1; i++) { 2176 nz = procsnz[i]; 2177 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2178 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2179 } 2180 /* read in the stuff for the last proc */ 2181 if (size != 1) { 2182 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2183 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2184 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2185 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2186 } 2187 ierr = PetscFree(cols);CHKERRQ(ierr); 2188 } else { /* procs[i], i>0 */ 2189 /* determine buffer space needed for message */ 2190 nz = 0; 2191 for (i=0; i<m; i++) { 2192 nz += locrowlens[i]; 2193 } 2194 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2195 mycols = ibuf; 2196 /* receive message of column indices*/ 2197 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2198 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2199 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2200 } 2201 2202 /* loop over local rows, determining number of off diagonal entries */ 2203 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2204 odlens = dlens + (rend-rstart); 2205 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2206 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2207 masked1 = mask + Mbs; 2208 masked2 = masked1 + Mbs; 2209 rowcount = 0; nzcount = 0; 2210 for (i=0; i<mbs; i++) { 2211 dcount = 0; 2212 odcount = 0; 2213 for (j=0; j<bs; j++) { 2214 kmax = locrowlens[rowcount]; 2215 for (k=0; k<kmax; k++) { 2216 tmp = mycols[nzcount++]/bs; /* block col. index */ 2217 if (!mask[tmp]) { 2218 mask[tmp] = 1; 2219 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2220 else masked1[dcount++] = tmp; /* entry in diag portion */ 2221 } 2222 } 2223 rowcount++; 2224 } 2225 2226 dlens[i] = dcount; /* d_nzz[i] */ 2227 odlens[i] = odcount; /* o_nzz[i] */ 2228 2229 /* zero out the mask elements we set */ 2230 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2231 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2232 } 2233 2234 /* create our matrix */ 2235 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2236 ierr = MatSetType(A,type);CHKERRQ(ierr); 2237 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2238 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2239 2240 if (!rank) { 2241 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2242 /* read in my part of the matrix numerical values */ 2243 nz = procsnz[0]; 2244 vals = buf; 2245 mycols = ibuf; 2246 if (size == 1) nz -= extra_rows; 2247 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2248 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2249 2250 /* insert into matrix */ 2251 jj = rstart*bs; 2252 for (i=0; i<m; i++) { 2253 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2254 mycols += locrowlens[i]; 2255 vals += locrowlens[i]; 2256 jj++; 2257 } 2258 2259 /* read in other processors (except the last one) and ship out */ 2260 for (i=1; i<size-1; i++) { 2261 nz = procsnz[i]; 2262 vals = buf; 2263 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2264 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2265 } 2266 /* the last proc */ 2267 if (size != 1){ 2268 nz = procsnz[i] - extra_rows; 2269 vals = buf; 2270 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2271 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2272 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2273 } 2274 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2275 2276 } else { 2277 /* receive numeric values */ 2278 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2279 2280 /* receive message of values*/ 2281 vals = buf; 2282 mycols = ibuf; 2283 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2284 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2285 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2286 2287 /* insert into matrix */ 2288 jj = rstart*bs; 2289 for (i=0; i<m; i++) { 2290 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2291 mycols += locrowlens[i]; 2292 vals += locrowlens[i]; 2293 jj++; 2294 } 2295 } 2296 2297 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2298 ierr = PetscFree(buf);CHKERRQ(ierr); 2299 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2300 ierr = PetscFree(rowners);CHKERRQ(ierr); 2301 ierr = PetscFree(dlens);CHKERRQ(ierr); 2302 ierr = PetscFree(mask);CHKERRQ(ierr); 2303 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2304 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2305 *newmat = A; 2306 PetscFunctionReturn(0); 2307 } 2308 2309 #undef __FUNCT__ 2310 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2311 /*XXXXX@ 2312 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2313 2314 Input Parameters: 2315 . mat - the matrix 2316 . fact - factor 2317 2318 Collective on Mat 2319 2320 Level: advanced 2321 2322 Notes: 2323 This can also be set by the command line option: -mat_use_hash_table fact 2324 2325 .keywords: matrix, hashtable, factor, HT 2326 2327 .seealso: MatSetOption() 2328 @XXXXX*/ 2329 2330 2331 #undef __FUNCT__ 2332 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2333 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2334 { 2335 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2336 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2337 PetscReal atmp; 2338 PetscReal *work,*svalues,*rvalues; 2339 PetscErrorCode ierr; 2340 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2341 PetscMPIInt rank,size; 2342 PetscInt *rowners_bs,dest,count,source; 2343 PetscScalar *va; 2344 MatScalar *ba; 2345 MPI_Status stat; 2346 2347 PetscFunctionBegin; 2348 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2349 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2350 2351 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2352 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2353 2354 bs = A->bs; 2355 mbs = a->mbs; 2356 Mbs = a->Mbs; 2357 ba = b->a; 2358 bi = b->i; 2359 bj = b->j; 2360 2361 /* find ownerships */ 2362 rowners_bs = a->rowners_bs; 2363 2364 /* each proc creates an array to be distributed */ 2365 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2366 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2367 2368 /* row_max for B */ 2369 if (rank != size-1){ 2370 for (i=0; i<mbs; i++) { 2371 ncols = bi[1] - bi[0]; bi++; 2372 brow = bs*i; 2373 for (j=0; j<ncols; j++){ 2374 bcol = bs*(*bj); 2375 for (kcol=0; kcol<bs; kcol++){ 2376 col = bcol + kcol; /* local col index */ 2377 col += rowners_bs[rank+1]; /* global col index */ 2378 for (krow=0; krow<bs; krow++){ 2379 atmp = PetscAbsScalar(*ba); ba++; 2380 row = brow + krow; /* local row index */ 2381 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2382 if (work[col] < atmp) work[col] = atmp; 2383 } 2384 } 2385 bj++; 2386 } 2387 } 2388 2389 /* send values to its owners */ 2390 for (dest=rank+1; dest<size; dest++){ 2391 svalues = work + rowners_bs[dest]; 2392 count = rowners_bs[dest+1]-rowners_bs[dest]; 2393 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2394 } 2395 } 2396 2397 /* receive values */ 2398 if (rank){ 2399 rvalues = work; 2400 count = rowners_bs[rank+1]-rowners_bs[rank]; 2401 for (source=0; source<rank; source++){ 2402 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2403 /* process values */ 2404 for (i=0; i<count; i++){ 2405 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2406 } 2407 } 2408 } 2409 2410 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2411 ierr = PetscFree(work);CHKERRQ(ierr); 2412 PetscFunctionReturn(0); 2413 } 2414 2415 #undef __FUNCT__ 2416 #define __FUNCT__ "MatRelax_MPISBAIJ" 2417 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2418 { 2419 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2420 PetscErrorCode ierr; 2421 PetscInt mbs=mat->mbs,bs=matin->bs; 2422 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2423 Vec bb1; 2424 2425 PetscFunctionBegin; 2426 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2427 if (bs > 1) 2428 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2429 2430 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2431 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2432 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2433 its--; 2434 } 2435 2436 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2437 while (its--){ 2438 2439 /* lower triangular part: slvec0b = - B^T*xx */ 2440 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2441 2442 /* copy xx into slvec0a */ 2443 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2444 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2445 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2446 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2447 2448 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2449 2450 /* copy bb into slvec1a */ 2451 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2452 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2453 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2454 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2455 2456 /* set slvec1b = 0 */ 2457 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2458 2459 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2460 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2461 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2462 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2463 2464 /* upper triangular part: bb1 = bb1 - B*x */ 2465 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2466 2467 /* local diagonal sweep */ 2468 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2469 } 2470 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2471 } else { 2472 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2473 } 2474 PetscFunctionReturn(0); 2475 } 2476 2477 #undef __FUNCT__ 2478 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2479 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2480 { 2481 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2482 PetscErrorCode ierr; 2483 PetscScalar mone=-1.0; 2484 Vec lvec1,bb1; 2485 2486 PetscFunctionBegin; 2487 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2488 if (matin->bs > 1) 2489 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2490 2491 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2492 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2493 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2494 its--; 2495 } 2496 2497 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2498 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2499 while (its--){ 2500 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2501 2502 /* lower diagonal part: bb1 = bb - B^T*xx */ 2503 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2504 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2505 2506 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2507 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2508 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2509 2510 /* upper diagonal part: bb1 = bb1 - B*x */ 2511 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2512 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2513 2514 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2515 2516 /* diagonal sweep */ 2517 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2518 } 2519 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2520 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2521 } else { 2522 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2523 } 2524 PetscFunctionReturn(0); 2525 } 2526 2527