1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <../src/mat/impls/sbaij/mpi/mpisbaij.h> 4 #include <../src/mat/impls/sbaij/seq/sbaij.h> 5 #include <petscblaslapack.h> 6 7 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 8 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 extern PetscErrorCode MatDisAssemble_MPISBAIJ(Mat); 10 extern PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 11 extern PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 13 extern PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 14 extern PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 16 extern PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 extern PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 18 extern PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*,Vec,Vec); 19 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*,Vec,Vec); 20 extern PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]); 21 extern PetscErrorCode MatSOR_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 #undef __FUNCT__ 24 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 25 PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 26 { 27 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 28 PetscErrorCode ierr; 29 30 PetscFunctionBegin; 31 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 32 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 33 PetscFunctionReturn(0); 34 } 35 36 #undef __FUNCT__ 37 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 38 PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 39 { 40 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 41 PetscErrorCode ierr; 42 43 PetscFunctionBegin; 44 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 45 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 46 PetscFunctionReturn(0); 47 } 48 49 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 50 { \ 51 \ 52 brow = row/bs; \ 53 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 54 rmax = aimax[brow]; nrow = ailen[brow]; \ 55 bcol = col/bs; \ 56 ridx = row % bs; cidx = col % bs; \ 57 low = 0; high = nrow; \ 58 while (high-low > 3) { \ 59 t = (low+high)/2; \ 60 if (rp[t] > bcol) high = t; \ 61 else low = t; \ 62 } \ 63 for (_i=low; _i<high; _i++) { \ 64 if (rp[_i] > bcol) break; \ 65 if (rp[_i] == bcol) { \ 66 bap = ap + bs2*_i + bs*cidx + ridx; \ 67 if (addv == ADD_VALUES) *bap += value; \ 68 else *bap = value; \ 69 goto a_noinsert; \ 70 } \ 71 } \ 72 if (a->nonew == 1) goto a_noinsert; \ 73 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 74 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 75 N = nrow++ - 1; \ 76 /* shift up all the later entries in this row */ \ 77 for (ii=N; ii>=_i; ii--) { \ 78 rp[ii+1] = rp[ii]; \ 79 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 80 } \ 81 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 82 rp[_i] = bcol; \ 83 ap[bs2*_i + bs*cidx + ridx] = value; \ 84 A->nonzerostate++;\ 85 a_noinsert:; \ 86 ailen[brow] = nrow; \ 87 } 88 89 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 90 { \ 91 brow = row/bs; \ 92 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 93 rmax = bimax[brow]; nrow = bilen[brow]; \ 94 bcol = col/bs; \ 95 ridx = row % bs; cidx = col % bs; \ 96 low = 0; high = nrow; \ 97 while (high-low > 3) { \ 98 t = (low+high)/2; \ 99 if (rp[t] > bcol) high = t; \ 100 else low = t; \ 101 } \ 102 for (_i=low; _i<high; _i++) { \ 103 if (rp[_i] > bcol) break; \ 104 if (rp[_i] == bcol) { \ 105 bap = ap + bs2*_i + bs*cidx + ridx; \ 106 if (addv == ADD_VALUES) *bap += value; \ 107 else *bap = value; \ 108 goto b_noinsert; \ 109 } \ 110 } \ 111 if (b->nonew == 1) goto b_noinsert; \ 112 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 113 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 114 N = nrow++ - 1; \ 115 /* shift up all the later entries in this row */ \ 116 for (ii=N; ii>=_i; ii--) { \ 117 rp[ii+1] = rp[ii]; \ 118 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 119 } \ 120 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 121 rp[_i] = bcol; \ 122 ap[bs2*_i + bs*cidx + ridx] = value; \ 123 B->nonzerostate++;\ 124 b_noinsert:; \ 125 bilen[brow] = nrow; \ 126 } 127 128 /* Only add/insert a(i,j) with i<=j (blocks). 129 Any a(i,j) with i>j input by user is ingored. 130 */ 131 #undef __FUNCT__ 132 #define __FUNCT__ "MatSetValues_MPISBAIJ" 133 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 134 { 135 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 136 MatScalar value; 137 PetscBool roworiented = baij->roworiented; 138 PetscErrorCode ierr; 139 PetscInt i,j,row,col; 140 PetscInt rstart_orig=mat->rmap->rstart; 141 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 142 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 143 144 /* Some Variables required in the macro */ 145 Mat A = baij->A; 146 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 147 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 148 MatScalar *aa =a->a; 149 150 Mat B = baij->B; 151 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 152 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 153 MatScalar *ba =b->a; 154 155 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 156 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 157 MatScalar *ap,*bap; 158 159 /* for stash */ 160 PetscInt n_loc, *in_loc = NULL; 161 MatScalar *v_loc = NULL; 162 163 PetscFunctionBegin; 164 if (v) PetscValidScalarPointer(v,6); 165 if (!baij->donotstash) { 166 if (n > baij->n_loc) { 167 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 168 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 169 ierr = PetscMalloc1(n,&baij->in_loc);CHKERRQ(ierr); 170 ierr = PetscMalloc1(n,&baij->v_loc);CHKERRQ(ierr); 171 172 baij->n_loc = n; 173 } 174 in_loc = baij->in_loc; 175 v_loc = baij->v_loc; 176 } 177 178 for (i=0; i<m; i++) { 179 if (im[i] < 0) continue; 180 #if defined(PETSC_USE_DEBUG) 181 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 182 #endif 183 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 184 row = im[i] - rstart_orig; /* local row index */ 185 for (j=0; j<n; j++) { 186 if (im[i]/bs > in[j]/bs) { 187 if (a->ignore_ltriangular) { 188 continue; /* ignore lower triangular blocks */ 189 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 190 } 191 if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */ 192 col = in[j] - cstart_orig; /* local col index */ 193 brow = row/bs; bcol = col/bs; 194 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 195 if (roworiented) value = v[i*n+j]; 196 else value = v[i+j*m]; 197 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 198 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 199 } else if (in[j] < 0) continue; 200 #if defined(PETSC_USE_DEBUG) 201 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 202 #endif 203 else { /* off-diag entry (B) */ 204 if (mat->was_assembled) { 205 if (!baij->colmap) { 206 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 207 } 208 #if defined(PETSC_USE_CTABLE) 209 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 210 col = col - 1; 211 #else 212 col = baij->colmap[in[j]/bs] - 1; 213 #endif 214 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 215 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 216 col = in[j]; 217 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 218 B = baij->B; 219 b = (Mat_SeqBAIJ*)(B)->data; 220 bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 221 ba = b->a; 222 } else col += in[j]%bs; 223 } else col = in[j]; 224 if (roworiented) value = v[i*n+j]; 225 else value = v[i+j*m]; 226 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 227 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 228 } 229 } 230 } else { /* off processor entry */ 231 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 232 if (!baij->donotstash) { 233 mat->assembled = PETSC_FALSE; 234 n_loc = 0; 235 for (j=0; j<n; j++) { 236 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 237 in_loc[n_loc] = in[j]; 238 if (roworiented) { 239 v_loc[n_loc] = v[i*n+j]; 240 } else { 241 v_loc[n_loc] = v[j*m+i]; 242 } 243 n_loc++; 244 } 245 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);CHKERRQ(ierr); 246 } 247 } 248 } 249 PetscFunctionReturn(0); 250 } 251 252 #undef __FUNCT__ 253 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 254 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 255 { 256 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 257 const MatScalar *value; 258 MatScalar *barray =baij->barray; 259 PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular; 260 PetscErrorCode ierr; 261 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 262 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 263 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 264 265 PetscFunctionBegin; 266 if (!barray) { 267 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 268 baij->barray = barray; 269 } 270 271 if (roworiented) { 272 stepval = (n-1)*bs; 273 } else { 274 stepval = (m-1)*bs; 275 } 276 for (i=0; i<m; i++) { 277 if (im[i] < 0) continue; 278 #if defined(PETSC_USE_DEBUG) 279 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 280 #endif 281 if (im[i] >= rstart && im[i] < rend) { 282 row = im[i] - rstart; 283 for (j=0; j<n; j++) { 284 if (im[i] > in[j]) { 285 if (ignore_ltriangular) continue; /* ignore lower triangular blocks */ 286 else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 287 } 288 /* If NumCol = 1 then a copy is not required */ 289 if ((roworiented) && (n == 1)) { 290 barray = (MatScalar*) v + i*bs2; 291 } else if ((!roworiented) && (m == 1)) { 292 barray = (MatScalar*) v + j*bs2; 293 } else { /* Here a copy is required */ 294 if (roworiented) { 295 value = v + i*(stepval+bs)*bs + j*bs; 296 } else { 297 value = v + j*(stepval+bs)*bs + i*bs; 298 } 299 for (ii=0; ii<bs; ii++,value+=stepval) { 300 for (jj=0; jj<bs; jj++) { 301 *barray++ = *value++; 302 } 303 } 304 barray -=bs2; 305 } 306 307 if (in[j] >= cstart && in[j] < cend) { 308 col = in[j] - cstart; 309 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 310 } else if (in[j] < 0) continue; 311 #if defined(PETSC_USE_DEBUG) 312 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 313 #endif 314 else { 315 if (mat->was_assembled) { 316 if (!baij->colmap) { 317 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 318 } 319 320 #if defined(PETSC_USE_DEBUG) 321 #if defined(PETSC_USE_CTABLE) 322 { PetscInt data; 323 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 324 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 325 } 326 #else 327 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 328 #endif 329 #endif 330 #if defined(PETSC_USE_CTABLE) 331 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 332 col = (col - 1)/bs; 333 #else 334 col = (baij->colmap[in[j]] - 1)/bs; 335 #endif 336 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 337 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 338 col = in[j]; 339 } 340 } else col = in[j]; 341 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 342 } 343 } 344 } else { 345 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 346 if (!baij->donotstash) { 347 if (roworiented) { 348 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 349 } else { 350 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 351 } 352 } 353 } 354 } 355 PetscFunctionReturn(0); 356 } 357 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatGetValues_MPISBAIJ" 360 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 361 { 362 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 365 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 366 367 PetscFunctionBegin; 368 for (i=0; i<m; i++) { 369 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 370 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 371 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 372 row = idxm[i] - bsrstart; 373 for (j=0; j<n; j++) { 374 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 375 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 376 if (idxn[j] >= bscstart && idxn[j] < bscend) { 377 col = idxn[j] - bscstart; 378 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 379 } else { 380 if (!baij->colmap) { 381 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 382 } 383 #if defined(PETSC_USE_CTABLE) 384 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 385 data--; 386 #else 387 data = baij->colmap[idxn[j]/bs]-1; 388 #endif 389 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 390 else { 391 col = data + idxn[j]%bs; 392 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 393 } 394 } 395 } 396 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 397 } 398 PetscFunctionReturn(0); 399 } 400 401 #undef __FUNCT__ 402 #define __FUNCT__ "MatNorm_MPISBAIJ" 403 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 404 { 405 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 406 PetscErrorCode ierr; 407 PetscReal sum[2],*lnorm2; 408 409 PetscFunctionBegin; 410 if (baij->size == 1) { 411 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 412 } else { 413 if (type == NORM_FROBENIUS) { 414 ierr = PetscMalloc1(2,&lnorm2);CHKERRQ(ierr); 415 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 416 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 417 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 418 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 419 ierr = MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 420 *norm = PetscSqrtReal(sum[0] + 2*sum[1]); 421 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 422 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 423 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 424 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 425 PetscReal *rsum,*rsum2,vabs; 426 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 427 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 428 MatScalar *v; 429 430 ierr = PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);CHKERRQ(ierr); 431 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 432 /* Amat */ 433 v = amat->a; jj = amat->j; 434 for (brow=0; brow<mbs; brow++) { 435 grow = bs*(rstart + brow); 436 nz = amat->i[brow+1] - amat->i[brow]; 437 for (bcol=0; bcol<nz; bcol++) { 438 gcol = bs*(rstart + *jj); jj++; 439 for (col=0; col<bs; col++) { 440 for (row=0; row<bs; row++) { 441 vabs = PetscAbsScalar(*v); v++; 442 rsum[gcol+col] += vabs; 443 /* non-diagonal block */ 444 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 445 } 446 } 447 } 448 } 449 /* Bmat */ 450 v = bmat->a; jj = bmat->j; 451 for (brow=0; brow<mbs; brow++) { 452 grow = bs*(rstart + brow); 453 nz = bmat->i[brow+1] - bmat->i[brow]; 454 for (bcol=0; bcol<nz; bcol++) { 455 gcol = bs*garray[*jj]; jj++; 456 for (col=0; col<bs; col++) { 457 for (row=0; row<bs; row++) { 458 vabs = PetscAbsScalar(*v); v++; 459 rsum[gcol+col] += vabs; 460 rsum[grow+row] += vabs; 461 } 462 } 463 } 464 } 465 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 466 *norm = 0.0; 467 for (col=0; col<mat->cmap->N; col++) { 468 if (rsum2[col] > *norm) *norm = rsum2[col]; 469 } 470 ierr = PetscFree2(rsum,rsum2);CHKERRQ(ierr); 471 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet"); 472 } 473 PetscFunctionReturn(0); 474 } 475 476 #undef __FUNCT__ 477 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 478 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 479 { 480 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 481 PetscErrorCode ierr; 482 PetscInt nstash,reallocs; 483 InsertMode addv; 484 485 PetscFunctionBegin; 486 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 487 488 /* make sure all processors are either in INSERTMODE or ADDMODE */ 489 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 490 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 491 mat->insertmode = addv; /* in case this processor had no cache */ 492 493 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 494 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 495 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 496 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 497 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 498 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 499 PetscFunctionReturn(0); 500 } 501 502 #undef __FUNCT__ 503 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 504 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 505 { 506 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 507 Mat_SeqSBAIJ *a =(Mat_SeqSBAIJ*)baij->A->data; 508 PetscErrorCode ierr; 509 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 510 PetscInt *row,*col; 511 PetscBool other_disassembled; 512 PetscMPIInt n; 513 PetscBool r1,r2,r3; 514 MatScalar *val; 515 InsertMode addv = mat->insertmode; 516 517 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 518 PetscFunctionBegin; 519 if (!baij->donotstash && !mat->nooffprocentries) { 520 while (1) { 521 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 522 if (!flg) break; 523 524 for (i=0; i<n;) { 525 /* Now identify the consecutive vals belonging to the same row */ 526 for (j=i,rstart=row[j]; j<n; j++) { 527 if (row[j] != rstart) break; 528 } 529 if (j < n) ncols = j-i; 530 else ncols = n-i; 531 /* Now assemble all these values with a single function call */ 532 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 533 i = j; 534 } 535 } 536 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 537 /* Now process the block-stash. Since the values are stashed column-oriented, 538 set the roworiented flag to column oriented, and after MatSetValues() 539 restore the original flags */ 540 r1 = baij->roworiented; 541 r2 = a->roworiented; 542 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 543 544 baij->roworiented = PETSC_FALSE; 545 a->roworiented = PETSC_FALSE; 546 547 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 548 while (1) { 549 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 550 if (!flg) break; 551 552 for (i=0; i<n;) { 553 /* Now identify the consecutive vals belonging to the same row */ 554 for (j=i,rstart=row[j]; j<n; j++) { 555 if (row[j] != rstart) break; 556 } 557 if (j < n) ncols = j-i; 558 else ncols = n-i; 559 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 560 i = j; 561 } 562 } 563 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 564 565 baij->roworiented = r1; 566 a->roworiented = r2; 567 568 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 569 } 570 571 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 572 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 573 574 /* determine if any processor has disassembled, if so we must 575 also disassemble ourselfs, in order that we may reassemble. */ 576 /* 577 if nonzero structure of submatrix B cannot change then we know that 578 no processor disassembled thus we can skip this stuff 579 */ 580 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 581 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 582 if (mat->was_assembled && !other_disassembled) { 583 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 584 } 585 } 586 587 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 588 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 589 } 590 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 591 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 592 593 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 594 595 baij->rowvalues = 0; 596 { 597 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 598 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 599 } 600 PetscFunctionReturn(0); 601 } 602 603 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 604 #include <petscdraw.h> 605 #undef __FUNCT__ 606 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 607 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 608 { 609 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 610 PetscErrorCode ierr; 611 PetscInt bs = mat->rmap->bs; 612 PetscMPIInt size = baij->size,rank = baij->rank; 613 PetscBool iascii,isdraw; 614 PetscViewer sviewer; 615 PetscViewerFormat format; 616 617 PetscFunctionBegin; 618 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 619 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 620 if (iascii) { 621 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 622 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 623 MatInfo info; 624 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 625 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 626 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 627 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 628 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 629 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 630 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 631 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 632 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 633 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 634 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 635 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_INFO) { 638 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 639 PetscFunctionReturn(0); 640 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 641 PetscFunctionReturn(0); 642 } 643 } 644 645 if (isdraw) { 646 PetscDraw draw; 647 PetscBool isnull; 648 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 649 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 650 } 651 652 if (size == 1) { 653 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 654 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 655 } else { 656 /* assemble the entire matrix onto first processor. */ 657 Mat A; 658 Mat_SeqSBAIJ *Aloc; 659 Mat_SeqBAIJ *Bloc; 660 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 661 MatScalar *a; 662 663 /* Should this be the same type as mat? */ 664 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 665 if (!rank) { 666 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 667 } else { 668 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 669 } 670 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 671 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 672 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 674 675 /* copy over the A part */ 676 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 677 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 678 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 679 680 for (i=0; i<mbs; i++) { 681 rvals[0] = bs*(baij->rstartbs + i); 682 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 683 for (j=ai[i]; j<ai[i+1]; j++) { 684 col = (baij->cstartbs+aj[j])*bs; 685 for (k=0; k<bs; k++) { 686 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 687 col++; 688 a += bs; 689 } 690 } 691 } 692 /* copy over the B part */ 693 Bloc = (Mat_SeqBAIJ*)baij->B->data; 694 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 695 for (i=0; i<mbs; i++) { 696 697 rvals[0] = bs*(baij->rstartbs + i); 698 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 699 for (j=ai[i]; j<ai[i+1]; j++) { 700 col = baij->garray[aj[j]]*bs; 701 for (k=0; k<bs; k++) { 702 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 703 col++; 704 a += bs; 705 } 706 } 707 } 708 ierr = PetscFree(rvals);CHKERRQ(ierr); 709 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 710 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 711 /* 712 Everyone has to call to draw the matrix since the graphics waits are 713 synchronized across all processors that share the PetscDraw object 714 */ 715 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 716 if (!rank) { 717 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 718 /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/ 719 ierr = PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ);CHKERRQ(ierr); 720 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 721 } 722 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 723 ierr = MatDestroy(&A);CHKERRQ(ierr); 724 } 725 PetscFunctionReturn(0); 726 } 727 728 #undef __FUNCT__ 729 #define __FUNCT__ "MatView_MPISBAIJ" 730 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 731 { 732 PetscErrorCode ierr; 733 PetscBool iascii,isdraw,issocket,isbinary; 734 735 PetscFunctionBegin; 736 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 737 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 738 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 739 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 740 if (iascii || isdraw || issocket || isbinary) { 741 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 742 } 743 PetscFunctionReturn(0); 744 } 745 746 #undef __FUNCT__ 747 #define __FUNCT__ "MatDestroy_MPISBAIJ" 748 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 749 { 750 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 751 PetscErrorCode ierr; 752 753 PetscFunctionBegin; 754 #if defined(PETSC_USE_LOG) 755 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 756 #endif 757 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 758 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 759 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 760 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 761 #if defined(PETSC_USE_CTABLE) 762 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 763 #else 764 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 765 #endif 766 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 767 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 768 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 770 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 771 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 772 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 773 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 774 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 775 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 776 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 777 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 778 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 779 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 780 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 781 #if defined(PETSC_USE_REAL_MAT_SINGLE) 782 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 783 #endif 784 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 785 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 786 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 787 ierr = PetscFree(mat->data);CHKERRQ(ierr); 788 789 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 791 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 792 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 793 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 794 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);CHKERRQ(ierr); 795 PetscFunctionReturn(0); 796 } 797 798 #undef __FUNCT__ 799 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 800 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 801 { 802 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 803 PetscErrorCode ierr; 804 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 805 PetscScalar *x,*from; 806 807 PetscFunctionBegin; 808 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 809 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 810 811 /* diagonal part */ 812 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 813 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 814 815 /* subdiagonal part */ 816 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 817 818 /* copy x into the vec slvec0 */ 819 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 823 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 824 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 825 826 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 827 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 828 /* supperdiagonal part */ 829 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 830 PetscFunctionReturn(0); 831 } 832 833 #undef __FUNCT__ 834 #define __FUNCT__ "MatMult_MPISBAIJ" 835 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 836 { 837 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 838 PetscErrorCode ierr; 839 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 840 PetscScalar *x,*from; 841 842 PetscFunctionBegin; 843 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 844 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 845 846 /* diagonal part */ 847 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 848 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 849 850 /* subdiagonal part */ 851 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 852 853 /* copy x into the vec slvec0 */ 854 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 855 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 856 857 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 858 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 859 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 860 861 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 862 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 863 /* supperdiagonal part */ 864 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 #undef __FUNCT__ 869 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 870 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 871 { 872 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 873 PetscErrorCode ierr; 874 PetscInt nt; 875 876 PetscFunctionBegin; 877 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 878 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 879 880 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 881 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 882 883 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 884 /* do diagonal part */ 885 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 886 /* do supperdiagonal part */ 887 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 888 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 889 /* do subdiagonal part */ 890 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 891 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 892 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 893 PetscFunctionReturn(0); 894 } 895 896 #undef __FUNCT__ 897 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 898 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 899 { 900 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 901 PetscErrorCode ierr; 902 PetscInt mbs=a->mbs,bs=A->rmap->bs; 903 PetscScalar *x,*from,zero=0.0; 904 905 PetscFunctionBegin; 906 /* 907 PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n"); 908 PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT); 909 */ 910 /* diagonal part */ 911 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 912 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 913 914 /* subdiagonal part */ 915 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 916 917 /* copy x into the vec slvec0 */ 918 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 919 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 920 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 921 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 922 923 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 924 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 925 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 926 927 /* supperdiagonal part */ 928 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 929 PetscFunctionReturn(0); 930 } 931 932 #undef __FUNCT__ 933 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 934 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 935 { 936 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 937 PetscErrorCode ierr; 938 939 PetscFunctionBegin; 940 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 941 /* do diagonal part */ 942 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 943 /* do supperdiagonal part */ 944 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 946 947 /* do subdiagonal part */ 948 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 949 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 950 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 951 PetscFunctionReturn(0); 952 } 953 954 /* 955 This only works correctly for square matrices where the subblock A->A is the 956 diagonal block 957 */ 958 #undef __FUNCT__ 959 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 960 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 961 { 962 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 963 PetscErrorCode ierr; 964 965 PetscFunctionBegin; 966 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 967 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 968 PetscFunctionReturn(0); 969 } 970 971 #undef __FUNCT__ 972 #define __FUNCT__ "MatScale_MPISBAIJ" 973 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 974 { 975 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 976 PetscErrorCode ierr; 977 978 PetscFunctionBegin; 979 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 980 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 981 PetscFunctionReturn(0); 982 } 983 984 #undef __FUNCT__ 985 #define __FUNCT__ "MatGetRow_MPISBAIJ" 986 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 987 { 988 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 989 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 990 PetscErrorCode ierr; 991 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 992 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 993 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 994 995 PetscFunctionBegin; 996 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 997 mat->getrowactive = PETSC_TRUE; 998 999 if (!mat->rowvalues && (idx || v)) { 1000 /* 1001 allocate enough space to hold information from the longest row. 1002 */ 1003 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1004 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1005 PetscInt max = 1,mbs = mat->mbs,tmp; 1006 for (i=0; i<mbs; i++) { 1007 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1008 if (max < tmp) max = tmp; 1009 } 1010 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1011 } 1012 1013 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1014 lrow = row - brstart; /* local row index */ 1015 1016 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1017 if (!v) {pvA = 0; pvB = 0;} 1018 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1019 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1020 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1021 nztot = nzA + nzB; 1022 1023 cmap = mat->garray; 1024 if (v || idx) { 1025 if (nztot) { 1026 /* Sort by increasing column numbers, assuming A and B already sorted */ 1027 PetscInt imark = -1; 1028 if (v) { 1029 *v = v_p = mat->rowvalues; 1030 for (i=0; i<nzB; i++) { 1031 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1032 else break; 1033 } 1034 imark = i; 1035 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1036 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1037 } 1038 if (idx) { 1039 *idx = idx_p = mat->rowindices; 1040 if (imark > -1) { 1041 for (i=0; i<imark; i++) { 1042 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1043 } 1044 } else { 1045 for (i=0; i<nzB; i++) { 1046 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1047 else break; 1048 } 1049 imark = i; 1050 } 1051 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1052 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1053 } 1054 } else { 1055 if (idx) *idx = 0; 1056 if (v) *v = 0; 1057 } 1058 } 1059 *nz = nztot; 1060 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1061 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1062 PetscFunctionReturn(0); 1063 } 1064 1065 #undef __FUNCT__ 1066 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1067 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1068 { 1069 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1070 1071 PetscFunctionBegin; 1072 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1073 baij->getrowactive = PETSC_FALSE; 1074 PetscFunctionReturn(0); 1075 } 1076 1077 #undef __FUNCT__ 1078 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1079 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1080 { 1081 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1082 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1083 1084 PetscFunctionBegin; 1085 aA->getrow_utriangular = PETSC_TRUE; 1086 PetscFunctionReturn(0); 1087 } 1088 #undef __FUNCT__ 1089 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1090 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1091 { 1092 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1093 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1094 1095 PetscFunctionBegin; 1096 aA->getrow_utriangular = PETSC_FALSE; 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1102 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1103 { 1104 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 1107 PetscFunctionBegin; 1108 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1109 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1110 PetscFunctionReturn(0); 1111 } 1112 1113 #undef __FUNCT__ 1114 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1115 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1116 { 1117 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1118 PetscErrorCode ierr; 1119 1120 PetscFunctionBegin; 1121 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1122 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1123 PetscFunctionReturn(0); 1124 } 1125 1126 #undef __FUNCT__ 1127 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1128 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1129 { 1130 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1131 PetscErrorCode ierr; 1132 1133 PetscFunctionBegin; 1134 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1135 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1136 PetscFunctionReturn(0); 1137 } 1138 1139 #undef __FUNCT__ 1140 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1141 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1142 { 1143 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1144 Mat A = a->A,B = a->B; 1145 PetscErrorCode ierr; 1146 PetscReal isend[5],irecv[5]; 1147 1148 PetscFunctionBegin; 1149 info->block_size = (PetscReal)matin->rmap->bs; 1150 1151 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1152 1153 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1154 isend[3] = info->memory; isend[4] = info->mallocs; 1155 1156 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1157 1158 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1159 isend[3] += info->memory; isend[4] += info->mallocs; 1160 if (flag == MAT_LOCAL) { 1161 info->nz_used = isend[0]; 1162 info->nz_allocated = isend[1]; 1163 info->nz_unneeded = isend[2]; 1164 info->memory = isend[3]; 1165 info->mallocs = isend[4]; 1166 } else if (flag == MAT_GLOBAL_MAX) { 1167 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1168 1169 info->nz_used = irecv[0]; 1170 info->nz_allocated = irecv[1]; 1171 info->nz_unneeded = irecv[2]; 1172 info->memory = irecv[3]; 1173 info->mallocs = irecv[4]; 1174 } else if (flag == MAT_GLOBAL_SUM) { 1175 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1176 1177 info->nz_used = irecv[0]; 1178 info->nz_allocated = irecv[1]; 1179 info->nz_unneeded = irecv[2]; 1180 info->memory = irecv[3]; 1181 info->mallocs = irecv[4]; 1182 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1183 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1184 info->fill_ratio_needed = 0; 1185 info->factor_mallocs = 0; 1186 PetscFunctionReturn(0); 1187 } 1188 1189 #undef __FUNCT__ 1190 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1191 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1192 { 1193 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1194 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1195 PetscErrorCode ierr; 1196 1197 PetscFunctionBegin; 1198 switch (op) { 1199 case MAT_NEW_NONZERO_LOCATIONS: 1200 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1201 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1202 case MAT_KEEP_NONZERO_PATTERN: 1203 case MAT_NEW_NONZERO_LOCATION_ERR: 1204 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1205 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1206 break; 1207 case MAT_ROW_ORIENTED: 1208 a->roworiented = flg; 1209 1210 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1211 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1212 break; 1213 case MAT_NEW_DIAGONALS: 1214 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1215 break; 1216 case MAT_IGNORE_OFF_PROC_ENTRIES: 1217 a->donotstash = flg; 1218 break; 1219 case MAT_USE_HASH_TABLE: 1220 a->ht_flag = flg; 1221 break; 1222 case MAT_HERMITIAN: 1223 if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first"); 1224 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1225 1226 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1227 break; 1228 case MAT_SPD: 1229 A->spd_set = PETSC_TRUE; 1230 A->spd = flg; 1231 if (flg) { 1232 A->symmetric = PETSC_TRUE; 1233 A->structurally_symmetric = PETSC_TRUE; 1234 A->symmetric_set = PETSC_TRUE; 1235 A->structurally_symmetric_set = PETSC_TRUE; 1236 } 1237 break; 1238 case MAT_SYMMETRIC: 1239 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1240 break; 1241 case MAT_STRUCTURALLY_SYMMETRIC: 1242 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1243 break; 1244 case MAT_SYMMETRY_ETERNAL: 1245 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1246 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1247 break; 1248 case MAT_IGNORE_LOWER_TRIANGULAR: 1249 aA->ignore_ltriangular = flg; 1250 break; 1251 case MAT_ERROR_LOWER_TRIANGULAR: 1252 aA->ignore_ltriangular = flg; 1253 break; 1254 case MAT_GETROW_UPPERTRIANGULAR: 1255 aA->getrow_utriangular = flg; 1256 break; 1257 default: 1258 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1259 } 1260 PetscFunctionReturn(0); 1261 } 1262 1263 #undef __FUNCT__ 1264 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1265 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1266 { 1267 PetscErrorCode ierr; 1268 1269 PetscFunctionBegin; 1270 if (MAT_INITIAL_MATRIX || *B != A) { 1271 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1272 } 1273 PetscFunctionReturn(0); 1274 } 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1278 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1279 { 1280 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1281 Mat a = baij->A, b=baij->B; 1282 PetscErrorCode ierr; 1283 PetscInt nv,m,n; 1284 PetscBool flg; 1285 1286 PetscFunctionBegin; 1287 if (ll != rr) { 1288 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1289 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1290 } 1291 if (!ll) PetscFunctionReturn(0); 1292 1293 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1294 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1295 1296 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1297 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1298 1299 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1300 1301 /* left diagonalscale the off-diagonal part */ 1302 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1303 1304 /* scale the diagonal part */ 1305 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1306 1307 /* right diagonalscale the off-diagonal part */ 1308 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1309 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1310 PetscFunctionReturn(0); 1311 } 1312 1313 #undef __FUNCT__ 1314 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1315 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1316 { 1317 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1318 PetscErrorCode ierr; 1319 1320 PetscFunctionBegin; 1321 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1322 PetscFunctionReturn(0); 1323 } 1324 1325 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*); 1326 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatEqual_MPISBAIJ" 1329 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1330 { 1331 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1332 Mat a,b,c,d; 1333 PetscBool flg; 1334 PetscErrorCode ierr; 1335 1336 PetscFunctionBegin; 1337 a = matA->A; b = matA->B; 1338 c = matB->A; d = matB->B; 1339 1340 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1341 if (flg) { 1342 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1343 } 1344 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1345 PetscFunctionReturn(0); 1346 } 1347 1348 #undef __FUNCT__ 1349 #define __FUNCT__ "MatCopy_MPISBAIJ" 1350 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1351 { 1352 PetscErrorCode ierr; 1353 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1354 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data; 1355 1356 PetscFunctionBegin; 1357 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1358 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1359 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1360 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1361 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1362 } else { 1363 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1364 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1365 } 1366 PetscFunctionReturn(0); 1367 } 1368 1369 #undef __FUNCT__ 1370 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1371 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1372 { 1373 PetscErrorCode ierr; 1374 1375 PetscFunctionBegin; 1376 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1377 PetscFunctionReturn(0); 1378 } 1379 1380 #undef __FUNCT__ 1381 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1382 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1383 { 1384 PetscErrorCode ierr; 1385 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data; 1386 PetscBLASInt bnz,one=1; 1387 Mat_SeqSBAIJ *xa,*ya; 1388 Mat_SeqBAIJ *xb,*yb; 1389 1390 PetscFunctionBegin; 1391 if (str == SAME_NONZERO_PATTERN) { 1392 PetscScalar alpha = a; 1393 xa = (Mat_SeqSBAIJ*)xx->A->data; 1394 ya = (Mat_SeqSBAIJ*)yy->A->data; 1395 ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr); 1396 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one)); 1397 xb = (Mat_SeqBAIJ*)xx->B->data; 1398 yb = (Mat_SeqBAIJ*)yy->B->data; 1399 ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr); 1400 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one)); 1401 } else { 1402 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1403 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1404 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1405 } 1406 PetscFunctionReturn(0); 1407 } 1408 1409 #undef __FUNCT__ 1410 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1411 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1412 { 1413 PetscErrorCode ierr; 1414 PetscInt i; 1415 PetscBool flg; 1416 1417 PetscFunctionBegin; 1418 for (i=0; i<n; i++) { 1419 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1420 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1421 } 1422 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1423 PetscFunctionReturn(0); 1424 } 1425 1426 1427 /* -------------------------------------------------------------------*/ 1428 static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ, 1429 MatGetRow_MPISBAIJ, 1430 MatRestoreRow_MPISBAIJ, 1431 MatMult_MPISBAIJ, 1432 /* 4*/ MatMultAdd_MPISBAIJ, 1433 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1434 MatMultAdd_MPISBAIJ, 1435 0, 1436 0, 1437 0, 1438 /* 10*/ 0, 1439 0, 1440 0, 1441 MatSOR_MPISBAIJ, 1442 MatTranspose_MPISBAIJ, 1443 /* 15*/ MatGetInfo_MPISBAIJ, 1444 MatEqual_MPISBAIJ, 1445 MatGetDiagonal_MPISBAIJ, 1446 MatDiagonalScale_MPISBAIJ, 1447 MatNorm_MPISBAIJ, 1448 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1449 MatAssemblyEnd_MPISBAIJ, 1450 MatSetOption_MPISBAIJ, 1451 MatZeroEntries_MPISBAIJ, 1452 /* 24*/ 0, 1453 0, 1454 0, 1455 0, 1456 0, 1457 /* 29*/ MatSetUp_MPISBAIJ, 1458 0, 1459 0, 1460 0, 1461 0, 1462 /* 34*/ MatDuplicate_MPISBAIJ, 1463 0, 1464 0, 1465 0, 1466 0, 1467 /* 39*/ MatAXPY_MPISBAIJ, 1468 MatGetSubMatrices_MPISBAIJ, 1469 MatIncreaseOverlap_MPISBAIJ, 1470 MatGetValues_MPISBAIJ, 1471 MatCopy_MPISBAIJ, 1472 /* 44*/ 0, 1473 MatScale_MPISBAIJ, 1474 0, 1475 0, 1476 0, 1477 /* 49*/ 0, 1478 0, 1479 0, 1480 0, 1481 0, 1482 /* 54*/ 0, 1483 0, 1484 MatSetUnfactored_MPISBAIJ, 1485 0, 1486 MatSetValuesBlocked_MPISBAIJ, 1487 /* 59*/ 0, 1488 0, 1489 0, 1490 0, 1491 0, 1492 /* 64*/ 0, 1493 0, 1494 0, 1495 0, 1496 0, 1497 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1498 0, 1499 0, 1500 0, 1501 0, 1502 /* 74*/ 0, 1503 0, 1504 0, 1505 0, 1506 0, 1507 /* 79*/ 0, 1508 0, 1509 0, 1510 0, 1511 MatLoad_MPISBAIJ, 1512 /* 84*/ 0, 1513 0, 1514 0, 1515 0, 1516 0, 1517 /* 89*/ 0, 1518 0, 1519 0, 1520 0, 1521 0, 1522 /* 94*/ 0, 1523 0, 1524 0, 1525 0, 1526 0, 1527 /* 99*/ 0, 1528 0, 1529 0, 1530 0, 1531 0, 1532 /*104*/ 0, 1533 MatRealPart_MPISBAIJ, 1534 MatImaginaryPart_MPISBAIJ, 1535 MatGetRowUpperTriangular_MPISBAIJ, 1536 MatRestoreRowUpperTriangular_MPISBAIJ, 1537 /*109*/ 0, 1538 0, 1539 0, 1540 0, 1541 0, 1542 /*114*/ 0, 1543 0, 1544 0, 1545 0, 1546 0, 1547 /*119*/ 0, 1548 0, 1549 0, 1550 0, 1551 0, 1552 /*124*/ 0, 1553 0, 1554 0, 1555 0, 1556 0, 1557 /*129*/ 0, 1558 0, 1559 0, 1560 0, 1561 0, 1562 /*134*/ 0, 1563 0, 1564 0, 1565 0, 1566 0, 1567 /*139*/ 0, 1568 0, 1569 0 1570 }; 1571 1572 1573 #undef __FUNCT__ 1574 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1575 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1576 { 1577 PetscFunctionBegin; 1578 *a = ((Mat_MPISBAIJ*)A->data)->A; 1579 PetscFunctionReturn(0); 1580 } 1581 1582 #undef __FUNCT__ 1583 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1584 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 1585 { 1586 Mat_MPISBAIJ *b; 1587 PetscErrorCode ierr; 1588 PetscInt i,mbs,Mbs; 1589 1590 PetscFunctionBegin; 1591 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 1592 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1593 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1594 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1595 1596 b = (Mat_MPISBAIJ*)B->data; 1597 mbs = B->rmap->n/bs; 1598 Mbs = B->rmap->N/bs; 1599 if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs); 1600 1601 B->rmap->bs = bs; 1602 b->bs2 = bs*bs; 1603 b->mbs = mbs; 1604 b->nbs = mbs; 1605 b->Mbs = Mbs; 1606 b->Nbs = Mbs; 1607 1608 for (i=0; i<=b->size; i++) { 1609 b->rangebs[i] = B->rmap->range[i]/bs; 1610 } 1611 b->rstartbs = B->rmap->rstart/bs; 1612 b->rendbs = B->rmap->rend/bs; 1613 1614 b->cstartbs = B->cmap->rstart/bs; 1615 b->cendbs = B->cmap->rend/bs; 1616 1617 if (!B->preallocated) { 1618 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1619 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1620 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1621 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 1622 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1623 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1624 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1625 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 1626 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 1627 } 1628 1629 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1630 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1631 1632 B->preallocated = PETSC_TRUE; 1633 PetscFunctionReturn(0); 1634 } 1635 1636 #undef __FUNCT__ 1637 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1638 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1639 { 1640 PetscInt m,rstart,cstart,cend; 1641 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1642 const PetscInt *JJ =0; 1643 PetscScalar *values=0; 1644 PetscErrorCode ierr; 1645 1646 PetscFunctionBegin; 1647 if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1648 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1649 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1650 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1651 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1652 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1653 m = B->rmap->n/bs; 1654 rstart = B->rmap->rstart/bs; 1655 cstart = B->cmap->rstart/bs; 1656 cend = B->cmap->rend/bs; 1657 1658 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1659 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 1660 for (i=0; i<m; i++) { 1661 nz = ii[i+1] - ii[i]; 1662 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1663 nz_max = PetscMax(nz_max,nz); 1664 JJ = jj + ii[i]; 1665 for (j=0; j<nz; j++) { 1666 if (*JJ >= cstart) break; 1667 JJ++; 1668 } 1669 d = 0; 1670 for (; j<nz; j++) { 1671 if (*JJ++ >= cend) break; 1672 d++; 1673 } 1674 d_nnz[i] = d; 1675 o_nnz[i] = nz - d; 1676 } 1677 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1678 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1679 1680 values = (PetscScalar*)V; 1681 if (!values) { 1682 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 1683 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1684 } 1685 for (i=0; i<m; i++) { 1686 PetscInt row = i + rstart; 1687 PetscInt ncols = ii[i+1] - ii[i]; 1688 const PetscInt *icols = jj + ii[i]; 1689 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1690 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1691 } 1692 1693 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1694 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1695 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1696 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1697 PetscFunctionReturn(0); 1698 } 1699 1700 #if defined(PETSC_HAVE_MUMPS) 1701 PETSC_EXTERN PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*); 1702 #endif 1703 #if defined(PETSC_HAVE_PASTIX) 1704 PETSC_EXTERN PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1705 #endif 1706 1707 /*MC 1708 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1709 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1710 the matrix is stored. 1711 1712 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1713 can call MatSetOption(Mat, MAT_HERMITIAN); 1714 1715 Options Database Keys: 1716 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1717 1718 Level: beginner 1719 1720 .seealso: MatCreateMPISBAIJ 1721 M*/ 1722 1723 PETSC_EXTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1724 1725 #undef __FUNCT__ 1726 #define __FUNCT__ "MatCreate_MPISBAIJ" 1727 PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1728 { 1729 Mat_MPISBAIJ *b; 1730 PetscErrorCode ierr; 1731 PetscBool flg; 1732 1733 PetscFunctionBegin; 1734 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 1735 B->data = (void*)b; 1736 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1737 1738 B->ops->destroy = MatDestroy_MPISBAIJ; 1739 B->ops->view = MatView_MPISBAIJ; 1740 B->assembled = PETSC_FALSE; 1741 B->insertmode = NOT_SET_VALUES; 1742 1743 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 1744 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 1745 1746 /* build local table of row and column ownerships */ 1747 ierr = PetscMalloc1((b->size+2),&b->rangebs);CHKERRQ(ierr); 1748 1749 /* build cache for off array entries formed */ 1750 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 1751 1752 b->donotstash = PETSC_FALSE; 1753 b->colmap = NULL; 1754 b->garray = NULL; 1755 b->roworiented = PETSC_TRUE; 1756 1757 /* stuff used in block assembly */ 1758 b->barray = 0; 1759 1760 /* stuff used for matrix vector multiply */ 1761 b->lvec = 0; 1762 b->Mvctx = 0; 1763 b->slvec0 = 0; 1764 b->slvec0b = 0; 1765 b->slvec1 = 0; 1766 b->slvec1a = 0; 1767 b->slvec1b = 0; 1768 b->sMvctx = 0; 1769 1770 /* stuff for MatGetRow() */ 1771 b->rowindices = 0; 1772 b->rowvalues = 0; 1773 b->getrowactive = PETSC_FALSE; 1774 1775 /* hash table stuff */ 1776 b->ht = 0; 1777 b->hd = 0; 1778 b->ht_size = 0; 1779 b->ht_flag = PETSC_FALSE; 1780 b->ht_fact = 0; 1781 b->ht_total_ct = 0; 1782 b->ht_insert_ct = 0; 1783 1784 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1785 b->ijonly = PETSC_FALSE; 1786 1787 b->in_loc = 0; 1788 b->v_loc = 0; 1789 b->n_loc = 0; 1790 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1791 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 1792 if (flg) { 1793 PetscReal fact = 1.39; 1794 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1795 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 1796 if (fact <= 1.0) fact = 1.39; 1797 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1798 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1799 } 1800 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1801 1802 #if defined(PETSC_HAVE_PASTIX) 1803 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1804 #endif 1805 #if defined(PETSC_HAVE_MUMPS) 1806 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 1807 #endif 1808 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1809 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1810 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1811 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1812 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1813 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1814 1815 B->symmetric = PETSC_TRUE; 1816 B->structurally_symmetric = PETSC_TRUE; 1817 B->symmetric_set = PETSC_TRUE; 1818 B->structurally_symmetric_set = PETSC_TRUE; 1819 1820 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1821 PetscFunctionReturn(0); 1822 } 1823 1824 /*MC 1825 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1826 1827 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1828 and MATMPISBAIJ otherwise. 1829 1830 Options Database Keys: 1831 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1832 1833 Level: beginner 1834 1835 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1836 M*/ 1837 1838 #undef __FUNCT__ 1839 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1840 /*@C 1841 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1842 the user should preallocate the matrix storage by setting the parameters 1843 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1844 performance can be increased by more than a factor of 50. 1845 1846 Collective on Mat 1847 1848 Input Parameters: 1849 + A - the matrix 1850 . bs - size of blockk 1851 . d_nz - number of block nonzeros per block row in diagonal portion of local 1852 submatrix (same for all local rows) 1853 . d_nnz - array containing the number of block nonzeros in the various block rows 1854 in the upper triangular and diagonal part of the in diagonal portion of the local 1855 (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room 1856 for the diagonal entry and set a value even if it is zero. 1857 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1858 submatrix (same for all local rows). 1859 - o_nnz - array containing the number of nonzeros in the various block rows of the 1860 off-diagonal portion of the local submatrix that is right of the diagonal 1861 (possibly different for each block row) or NULL. 1862 1863 1864 Options Database Keys: 1865 . -mat_no_unroll - uses code that does not unroll the loops in the 1866 block calculations (much slower) 1867 . -mat_block_size - size of the blocks to use 1868 1869 Notes: 1870 1871 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1872 than it must be used on all processors that share the object for that argument. 1873 1874 If the *_nnz parameter is given then the *_nz parameter is ignored 1875 1876 Storage Information: 1877 For a square global matrix we define each processor's diagonal portion 1878 to be its local rows and the corresponding columns (a square submatrix); 1879 each processor's off-diagonal portion encompasses the remainder of the 1880 local matrix (a rectangular submatrix). 1881 1882 The user can specify preallocated storage for the diagonal part of 1883 the local submatrix with either d_nz or d_nnz (not both). Set 1884 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 1885 memory allocation. Likewise, specify preallocated storage for the 1886 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1887 1888 You can call MatGetInfo() to get information on how effective the preallocation was; 1889 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1890 You can also run with the option -info and look for messages with the string 1891 malloc in them to see if additional memory allocation was needed. 1892 1893 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1894 the figure below we depict these three local rows and all columns (0-11). 1895 1896 .vb 1897 0 1 2 3 4 5 6 7 8 9 10 11 1898 -------------------------- 1899 row 3 |. . . d d d o o o o o o 1900 row 4 |. . . d d d o o o o o o 1901 row 5 |. . . d d d o o o o o o 1902 -------------------------- 1903 .ve 1904 1905 Thus, any entries in the d locations are stored in the d (diagonal) 1906 submatrix, and any entries in the o locations are stored in the 1907 o (off-diagonal) submatrix. Note that the d matrix is stored in 1908 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1909 1910 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1911 plus the diagonal part of the d matrix, 1912 and o_nz should indicate the number of block nonzeros per row in the o matrix 1913 1914 In general, for PDE problems in which most nonzeros are near the diagonal, 1915 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1916 or you will get TERRIBLE performance; see the users' manual chapter on 1917 matrices. 1918 1919 Level: intermediate 1920 1921 .keywords: matrix, block, aij, compressed row, sparse, parallel 1922 1923 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership() 1924 @*/ 1925 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1926 { 1927 PetscErrorCode ierr; 1928 1929 PetscFunctionBegin; 1930 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 1931 PetscValidType(B,1); 1932 PetscValidLogicalCollectiveInt(B,bs,2); 1933 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 1934 PetscFunctionReturn(0); 1935 } 1936 1937 #undef __FUNCT__ 1938 #define __FUNCT__ "MatCreateSBAIJ" 1939 /*@C 1940 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1941 (block compressed row). For good matrix assembly performance 1942 the user should preallocate the matrix storage by setting the parameters 1943 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1944 performance can be increased by more than a factor of 50. 1945 1946 Collective on MPI_Comm 1947 1948 Input Parameters: 1949 + comm - MPI communicator 1950 . bs - size of blockk 1951 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1952 This value should be the same as the local size used in creating the 1953 y vector for the matrix-vector product y = Ax. 1954 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1955 This value should be the same as the local size used in creating the 1956 x vector for the matrix-vector product y = Ax. 1957 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1958 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1959 . d_nz - number of block nonzeros per block row in diagonal portion of local 1960 submatrix (same for all local rows) 1961 . d_nnz - array containing the number of block nonzeros in the various block rows 1962 in the upper triangular portion of the in diagonal portion of the local 1963 (possibly different for each block block row) or NULL. 1964 If you plan to factor the matrix you must leave room for the diagonal entry and 1965 set its value even if it is zero. 1966 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1967 submatrix (same for all local rows). 1968 - o_nnz - array containing the number of nonzeros in the various block rows of the 1969 off-diagonal portion of the local submatrix (possibly different for 1970 each block row) or NULL. 1971 1972 Output Parameter: 1973 . A - the matrix 1974 1975 Options Database Keys: 1976 . -mat_no_unroll - uses code that does not unroll the loops in the 1977 block calculations (much slower) 1978 . -mat_block_size - size of the blocks to use 1979 . -mat_mpi - use the parallel matrix data structures even on one processor 1980 (defaults to using SeqBAIJ format on one processor) 1981 1982 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1983 MatXXXXSetPreallocation() paradgm instead of this routine directly. 1984 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1985 1986 Notes: 1987 The number of rows and columns must be divisible by blocksize. 1988 This matrix type does not support complex Hermitian operation. 1989 1990 The user MUST specify either the local or global matrix dimensions 1991 (possibly both). 1992 1993 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1994 than it must be used on all processors that share the object for that argument. 1995 1996 If the *_nnz parameter is given then the *_nz parameter is ignored 1997 1998 Storage Information: 1999 For a square global matrix we define each processor's diagonal portion 2000 to be its local rows and the corresponding columns (a square submatrix); 2001 each processor's off-diagonal portion encompasses the remainder of the 2002 local matrix (a rectangular submatrix). 2003 2004 The user can specify preallocated storage for the diagonal part of 2005 the local submatrix with either d_nz or d_nnz (not both). Set 2006 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 2007 memory allocation. Likewise, specify preallocated storage for the 2008 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2009 2010 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2011 the figure below we depict these three local rows and all columns (0-11). 2012 2013 .vb 2014 0 1 2 3 4 5 6 7 8 9 10 11 2015 -------------------------- 2016 row 3 |. . . d d d o o o o o o 2017 row 4 |. . . d d d o o o o o o 2018 row 5 |. . . d d d o o o o o o 2019 -------------------------- 2020 .ve 2021 2022 Thus, any entries in the d locations are stored in the d (diagonal) 2023 submatrix, and any entries in the o locations are stored in the 2024 o (off-diagonal) submatrix. Note that the d matrix is stored in 2025 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2026 2027 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2028 plus the diagonal part of the d matrix, 2029 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2030 In general, for PDE problems in which most nonzeros are near the diagonal, 2031 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2032 or you will get TERRIBLE performance; see the users' manual chapter on 2033 matrices. 2034 2035 Level: intermediate 2036 2037 .keywords: matrix, block, aij, compressed row, sparse, parallel 2038 2039 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2040 @*/ 2041 2042 PetscErrorCode MatCreateSBAIJ(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) 2043 { 2044 PetscErrorCode ierr; 2045 PetscMPIInt size; 2046 2047 PetscFunctionBegin; 2048 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2049 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2050 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2051 if (size > 1) { 2052 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2053 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2054 } else { 2055 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2056 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2057 } 2058 PetscFunctionReturn(0); 2059 } 2060 2061 2062 #undef __FUNCT__ 2063 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2064 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2065 { 2066 Mat mat; 2067 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2068 PetscErrorCode ierr; 2069 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2070 PetscScalar *array; 2071 2072 PetscFunctionBegin; 2073 *newmat = 0; 2074 2075 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2076 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2077 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2078 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2079 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2080 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2081 2082 mat->factortype = matin->factortype; 2083 mat->preallocated = PETSC_TRUE; 2084 mat->assembled = PETSC_TRUE; 2085 mat->insertmode = NOT_SET_VALUES; 2086 2087 a = (Mat_MPISBAIJ*)mat->data; 2088 a->bs2 = oldmat->bs2; 2089 a->mbs = oldmat->mbs; 2090 a->nbs = oldmat->nbs; 2091 a->Mbs = oldmat->Mbs; 2092 a->Nbs = oldmat->Nbs; 2093 2094 2095 a->size = oldmat->size; 2096 a->rank = oldmat->rank; 2097 a->donotstash = oldmat->donotstash; 2098 a->roworiented = oldmat->roworiented; 2099 a->rowindices = 0; 2100 a->rowvalues = 0; 2101 a->getrowactive = PETSC_FALSE; 2102 a->barray = 0; 2103 a->rstartbs = oldmat->rstartbs; 2104 a->rendbs = oldmat->rendbs; 2105 a->cstartbs = oldmat->cstartbs; 2106 a->cendbs = oldmat->cendbs; 2107 2108 /* hash table stuff */ 2109 a->ht = 0; 2110 a->hd = 0; 2111 a->ht_size = 0; 2112 a->ht_flag = oldmat->ht_flag; 2113 a->ht_fact = oldmat->ht_fact; 2114 a->ht_total_ct = 0; 2115 a->ht_insert_ct = 0; 2116 2117 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2118 if (oldmat->colmap) { 2119 #if defined(PETSC_USE_CTABLE) 2120 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2121 #else 2122 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 2123 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2124 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2125 #endif 2126 } else a->colmap = 0; 2127 2128 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2129 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 2130 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2131 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2132 } else a->garray = 0; 2133 2134 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2135 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2136 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2137 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2138 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2139 2140 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2141 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2142 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2143 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2144 2145 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2146 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2147 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2148 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2149 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2150 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2151 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2152 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2153 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2154 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2155 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);CHKERRQ(ierr); 2156 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);CHKERRQ(ierr); 2157 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);CHKERRQ(ierr); 2158 2159 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2160 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2161 a->sMvctx = oldmat->sMvctx; 2162 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);CHKERRQ(ierr); 2163 2164 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2165 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2166 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2167 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2168 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2169 *newmat = mat; 2170 PetscFunctionReturn(0); 2171 } 2172 2173 #undef __FUNCT__ 2174 #define __FUNCT__ "MatLoad_MPISBAIJ" 2175 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2176 { 2177 PetscErrorCode ierr; 2178 PetscInt i,nz,j,rstart,rend; 2179 PetscScalar *vals,*buf; 2180 MPI_Comm comm; 2181 MPI_Status status; 2182 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2183 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2184 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2185 PetscInt bs =1,Mbs,mbs,extra_rows; 2186 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2187 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2188 int fd; 2189 2190 PetscFunctionBegin; 2191 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2192 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2193 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2194 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2195 2196 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2198 if (!rank) { 2199 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2200 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2201 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2202 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2203 } 2204 2205 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2206 2207 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2208 M = header[1]; 2209 N = header[2]; 2210 2211 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2212 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2213 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2214 2215 /* If global sizes are set, check if they are consistent with that given in the file */ 2216 if (sizesset) { 2217 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2218 } 2219 if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 2220 if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 2221 2222 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2223 2224 /* 2225 This code adds extra rows to make sure the number of rows is 2226 divisible by the blocksize 2227 */ 2228 Mbs = M/bs; 2229 extra_rows = bs - M + bs*(Mbs); 2230 if (extra_rows == bs) extra_rows = 0; 2231 else Mbs++; 2232 if (extra_rows &&!rank) { 2233 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2234 } 2235 2236 /* determine ownership of all rows */ 2237 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2238 mbs = Mbs/size + ((Mbs % size) > rank); 2239 m = mbs*bs; 2240 } else { /* User Set */ 2241 m = newmat->rmap->n; 2242 mbs = m/bs; 2243 } 2244 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 2245 ierr = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr); 2246 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2247 rowners[0] = 0; 2248 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2249 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2250 rstart = rowners[rank]; 2251 rend = rowners[rank+1]; 2252 2253 /* distribute row lengths to all processors */ 2254 ierr = PetscMalloc1((rend-rstart)*bs,&locrowlens);CHKERRQ(ierr); 2255 if (!rank) { 2256 ierr = PetscMalloc1((M+extra_rows),&rowlengths);CHKERRQ(ierr); 2257 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2258 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2259 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 2260 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2261 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2262 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2263 } else { 2264 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2265 } 2266 2267 if (!rank) { /* procs[0] */ 2268 /* calculate the number of nonzeros on each processor */ 2269 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 2270 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2271 for (i=0; i<size; i++) { 2272 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2273 procsnz[i] += rowlengths[j]; 2274 } 2275 } 2276 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2277 2278 /* determine max buffer needed and allocate it */ 2279 maxnz = 0; 2280 for (i=0; i<size; i++) { 2281 maxnz = PetscMax(maxnz,procsnz[i]); 2282 } 2283 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2284 2285 /* read in my part of the matrix column indices */ 2286 nz = procsnz[0]; 2287 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2288 mycols = ibuf; 2289 if (size == 1) nz -= extra_rows; 2290 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2291 if (size == 1) { 2292 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 2293 } 2294 2295 /* read in every ones (except the last) and ship off */ 2296 for (i=1; i<size-1; i++) { 2297 nz = procsnz[i]; 2298 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2299 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2300 } 2301 /* read in the stuff for the last proc */ 2302 if (size != 1) { 2303 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2304 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2305 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2306 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2307 } 2308 ierr = PetscFree(cols);CHKERRQ(ierr); 2309 } else { /* procs[i], i>0 */ 2310 /* determine buffer space needed for message */ 2311 nz = 0; 2312 for (i=0; i<m; i++) nz += locrowlens[i]; 2313 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2314 mycols = ibuf; 2315 /* receive message of column indices*/ 2316 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2317 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2318 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2319 } 2320 2321 /* loop over local rows, determining number of off diagonal entries */ 2322 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 2323 ierr = PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 2324 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2325 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2326 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2327 rowcount = 0; 2328 nzcount = 0; 2329 for (i=0; i<mbs; i++) { 2330 dcount = 0; 2331 odcount = 0; 2332 for (j=0; j<bs; j++) { 2333 kmax = locrowlens[rowcount]; 2334 for (k=0; k<kmax; k++) { 2335 tmp = mycols[nzcount++]/bs; /* block col. index */ 2336 if (!mask[tmp]) { 2337 mask[tmp] = 1; 2338 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2339 else masked1[dcount++] = tmp; /* entry in diag portion */ 2340 } 2341 } 2342 rowcount++; 2343 } 2344 2345 dlens[i] = dcount; /* d_nzz[i] */ 2346 odlens[i] = odcount; /* o_nzz[i] */ 2347 2348 /* zero out the mask elements we set */ 2349 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2350 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2351 } 2352 if (!sizesset) { 2353 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2354 } 2355 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2356 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2357 2358 if (!rank) { 2359 ierr = PetscMalloc1(maxnz,&buf);CHKERRQ(ierr); 2360 /* read in my part of the matrix numerical values */ 2361 nz = procsnz[0]; 2362 vals = buf; 2363 mycols = ibuf; 2364 if (size == 1) nz -= extra_rows; 2365 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2366 if (size == 1) { 2367 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 2368 } 2369 2370 /* insert into matrix */ 2371 jj = rstart*bs; 2372 for (i=0; i<m; i++) { 2373 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2374 mycols += locrowlens[i]; 2375 vals += locrowlens[i]; 2376 jj++; 2377 } 2378 2379 /* read in other processors (except the last one) and ship out */ 2380 for (i=1; i<size-1; i++) { 2381 nz = procsnz[i]; 2382 vals = buf; 2383 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2384 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2385 } 2386 /* the last proc */ 2387 if (size != 1) { 2388 nz = procsnz[i] - extra_rows; 2389 vals = buf; 2390 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2391 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2392 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2393 } 2394 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2395 2396 } else { 2397 /* receive numeric values */ 2398 ierr = PetscMalloc1(nz,&buf);CHKERRQ(ierr); 2399 2400 /* receive message of values*/ 2401 vals = buf; 2402 mycols = ibuf; 2403 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2404 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2405 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2406 2407 /* insert into matrix */ 2408 jj = rstart*bs; 2409 for (i=0; i<m; i++) { 2410 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2411 mycols += locrowlens[i]; 2412 vals += locrowlens[i]; 2413 jj++; 2414 } 2415 } 2416 2417 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2418 ierr = PetscFree(buf);CHKERRQ(ierr); 2419 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2420 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2421 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2422 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2423 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2424 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2425 PetscFunctionReturn(0); 2426 } 2427 2428 #undef __FUNCT__ 2429 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2430 /*XXXXX@ 2431 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2432 2433 Input Parameters: 2434 . mat - the matrix 2435 . fact - factor 2436 2437 Not Collective on Mat, each process can have a different hash factor 2438 2439 Level: advanced 2440 2441 Notes: 2442 This can also be set by the command line option: -mat_use_hash_table fact 2443 2444 .keywords: matrix, hashtable, factor, HT 2445 2446 .seealso: MatSetOption() 2447 @XXXXX*/ 2448 2449 2450 #undef __FUNCT__ 2451 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2452 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2453 { 2454 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2455 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2456 PetscReal atmp; 2457 PetscReal *work,*svalues,*rvalues; 2458 PetscErrorCode ierr; 2459 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2460 PetscMPIInt rank,size; 2461 PetscInt *rowners_bs,dest,count,source; 2462 PetscScalar *va; 2463 MatScalar *ba; 2464 MPI_Status stat; 2465 2466 PetscFunctionBegin; 2467 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2468 ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr); 2469 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2470 2471 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2472 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2473 2474 bs = A->rmap->bs; 2475 mbs = a->mbs; 2476 Mbs = a->Mbs; 2477 ba = b->a; 2478 bi = b->i; 2479 bj = b->j; 2480 2481 /* find ownerships */ 2482 rowners_bs = A->rmap->range; 2483 2484 /* each proc creates an array to be distributed */ 2485 ierr = PetscMalloc1(bs*Mbs,&work);CHKERRQ(ierr); 2486 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2487 2488 /* row_max for B */ 2489 if (rank != size-1) { 2490 for (i=0; i<mbs; i++) { 2491 ncols = bi[1] - bi[0]; bi++; 2492 brow = bs*i; 2493 for (j=0; j<ncols; j++) { 2494 bcol = bs*(*bj); 2495 for (kcol=0; kcol<bs; kcol++) { 2496 col = bcol + kcol; /* local col index */ 2497 col += rowners_bs[rank+1]; /* global col index */ 2498 for (krow=0; krow<bs; krow++) { 2499 atmp = PetscAbsScalar(*ba); ba++; 2500 row = brow + krow; /* local row index */ 2501 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2502 if (work[col] < atmp) work[col] = atmp; 2503 } 2504 } 2505 bj++; 2506 } 2507 } 2508 2509 /* send values to its owners */ 2510 for (dest=rank+1; dest<size; dest++) { 2511 svalues = work + rowners_bs[dest]; 2512 count = rowners_bs[dest+1]-rowners_bs[dest]; 2513 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2514 } 2515 } 2516 2517 /* receive values */ 2518 if (rank) { 2519 rvalues = work; 2520 count = rowners_bs[rank+1]-rowners_bs[rank]; 2521 for (source=0; source<rank; source++) { 2522 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr); 2523 /* process values */ 2524 for (i=0; i<count; i++) { 2525 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2526 } 2527 } 2528 } 2529 2530 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2531 ierr = PetscFree(work);CHKERRQ(ierr); 2532 PetscFunctionReturn(0); 2533 } 2534 2535 #undef __FUNCT__ 2536 #define __FUNCT__ "MatSOR_MPISBAIJ" 2537 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2538 { 2539 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2540 PetscErrorCode ierr; 2541 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2542 PetscScalar *x,*ptr,*from; 2543 Vec bb1; 2544 const PetscScalar *b; 2545 2546 PetscFunctionBegin; 2547 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2548 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2549 2550 if (flag == SOR_APPLY_UPPER) { 2551 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2552 PetscFunctionReturn(0); 2553 } 2554 2555 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2556 if (flag & SOR_ZERO_INITIAL_GUESS) { 2557 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2558 its--; 2559 } 2560 2561 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2562 while (its--) { 2563 2564 /* lower triangular part: slvec0b = - B^T*xx */ 2565 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2566 2567 /* copy xx into slvec0a */ 2568 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2569 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2570 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2571 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2572 2573 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2574 2575 /* copy bb into slvec1a */ 2576 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2577 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2578 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2579 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2580 2581 /* set slvec1b = 0 */ 2582 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2583 2584 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2585 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2586 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2587 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2588 2589 /* upper triangular part: bb1 = bb1 - B*x */ 2590 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2591 2592 /* local diagonal sweep */ 2593 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2594 } 2595 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2596 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2597 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2598 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2599 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2600 } else if (flag & SOR_EISENSTAT) { 2601 Vec xx1; 2602 PetscBool hasop; 2603 const PetscScalar *diag; 2604 PetscScalar *sl,scale = (omega - 2.0)/omega; 2605 PetscInt i,n; 2606 2607 if (!mat->xx1) { 2608 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2609 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2610 } 2611 xx1 = mat->xx1; 2612 bb1 = mat->bb1; 2613 2614 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2615 2616 if (!mat->diag) { 2617 /* this is wrong for same matrix with new nonzero values */ 2618 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 2619 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2620 } 2621 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2622 2623 if (hasop) { 2624 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2625 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2626 } else { 2627 /* 2628 These two lines are replaced by code that may be a bit faster for a good compiler 2629 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2630 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2631 */ 2632 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2633 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2634 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2635 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2636 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2637 if (omega == 1.0) { 2638 for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i]; 2639 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2640 } else { 2641 for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i]; 2642 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2643 } 2644 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2645 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2646 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2647 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2648 } 2649 2650 /* multiply off-diagonal portion of matrix */ 2651 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2652 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2653 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2654 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2655 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2656 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2657 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2658 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2659 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2660 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2661 2662 /* local sweep */ 2663 ierr = (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 2664 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2665 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2666 PetscFunctionReturn(0); 2667 } 2668 2669 #undef __FUNCT__ 2670 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2671 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2672 { 2673 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2674 PetscErrorCode ierr; 2675 Vec lvec1,bb1; 2676 2677 PetscFunctionBegin; 2678 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2679 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2680 2681 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2682 if (flag & SOR_ZERO_INITIAL_GUESS) { 2683 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2684 its--; 2685 } 2686 2687 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2688 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2689 while (its--) { 2690 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2691 2692 /* lower diagonal part: bb1 = bb - B^T*xx */ 2693 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2694 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2695 2696 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2697 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2698 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2699 2700 /* upper diagonal part: bb1 = bb1 - B*x */ 2701 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2702 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2703 2704 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2705 2706 /* diagonal sweep */ 2707 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2708 } 2709 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2710 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2711 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2712 PetscFunctionReturn(0); 2713 } 2714 2715 #undef __FUNCT__ 2716 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2717 /*@ 2718 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2719 CSR format the local rows. 2720 2721 Collective on MPI_Comm 2722 2723 Input Parameters: 2724 + comm - MPI communicator 2725 . bs - the block size, only a block size of 1 is supported 2726 . m - number of local rows (Cannot be PETSC_DECIDE) 2727 . n - This value should be the same as the local size used in creating the 2728 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2729 calculated if N is given) For square matrices n is almost always m. 2730 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2731 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2732 . i - row indices 2733 . j - column indices 2734 - a - matrix values 2735 2736 Output Parameter: 2737 . mat - the matrix 2738 2739 Level: intermediate 2740 2741 Notes: 2742 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2743 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2744 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2745 2746 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2747 2748 .keywords: matrix, aij, compressed row, sparse, parallel 2749 2750 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2751 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2752 @*/ 2753 PetscErrorCode MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 2754 { 2755 PetscErrorCode ierr; 2756 2757 2758 PetscFunctionBegin; 2759 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2760 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2761 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2762 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2763 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2764 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2765 PetscFunctionReturn(0); 2766 } 2767 2768 2769 #undef __FUNCT__ 2770 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2771 /*@C 2772 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2773 (the default parallel PETSc format). 2774 2775 Collective on MPI_Comm 2776 2777 Input Parameters: 2778 + A - the matrix 2779 . bs - the block size 2780 . i - the indices into j for the start of each local row (starts with zero) 2781 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2782 - v - optional values in the matrix 2783 2784 Level: developer 2785 2786 .keywords: matrix, aij, compressed row, sparse, parallel 2787 2788 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2789 @*/ 2790 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2791 { 2792 PetscErrorCode ierr; 2793 2794 PetscFunctionBegin; 2795 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2796 PetscFunctionReturn(0); 2797 } 2798 2799 2800