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