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