1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <../src/mat/impls/sbaij/mpi/mpisbaij.h> 4 #include <../src/mat/impls/sbaij/seq/sbaij.h> 5 #include <petscblaslapack.h> 6 7 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 8 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 extern PetscErrorCode MatDisAssemble_MPISBAIJ(Mat); 10 extern PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 11 extern PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 13 extern PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 14 extern PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 16 extern PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 extern PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 18 extern PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*,Vec,Vec); 19 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*,Vec,Vec); 20 extern PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]); 21 extern PetscErrorCode MatSOR_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 #undef __FUNCT__ 24 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 25 PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 26 { 27 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 28 PetscErrorCode ierr; 29 30 PetscFunctionBegin; 31 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 32 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 33 PetscFunctionReturn(0); 34 } 35 36 #undef __FUNCT__ 37 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 38 PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 39 { 40 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 41 PetscErrorCode ierr; 42 43 PetscFunctionBegin; 44 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 45 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 46 PetscFunctionReturn(0); 47 } 48 49 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 50 { \ 51 \ 52 brow = row/bs; \ 53 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 54 rmax = aimax[brow]; nrow = ailen[brow]; \ 55 bcol = col/bs; \ 56 ridx = row % bs; cidx = col % bs; \ 57 low = 0; high = nrow; \ 58 while (high-low > 3) { \ 59 t = (low+high)/2; \ 60 if (rp[t] > bcol) high = t; \ 61 else low = t; \ 62 } \ 63 for (_i=low; _i<high; _i++) { \ 64 if (rp[_i] > bcol) break; \ 65 if (rp[_i] == bcol) { \ 66 bap = ap + bs2*_i + bs*cidx + ridx; \ 67 if (addv == ADD_VALUES) *bap += value; \ 68 else *bap = value; \ 69 goto a_noinsert; \ 70 } \ 71 } \ 72 if (a->nonew == 1) goto a_noinsert; \ 73 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 74 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 75 N = nrow++ - 1; \ 76 /* shift up all the later entries in this row */ \ 77 for (ii=N; ii>=_i; ii--) { \ 78 rp[ii+1] = rp[ii]; \ 79 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 80 } \ 81 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 82 rp[_i] = bcol; \ 83 ap[bs2*_i + bs*cidx + ridx] = value; \ 84 A->nonzerostate++;\ 85 a_noinsert:; \ 86 ailen[brow] = nrow; \ 87 } 88 89 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 90 { \ 91 brow = row/bs; \ 92 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 93 rmax = bimax[brow]; nrow = bilen[brow]; \ 94 bcol = col/bs; \ 95 ridx = row % bs; cidx = col % bs; \ 96 low = 0; high = nrow; \ 97 while (high-low > 3) { \ 98 t = (low+high)/2; \ 99 if (rp[t] > bcol) high = t; \ 100 else low = t; \ 101 } \ 102 for (_i=low; _i<high; _i++) { \ 103 if (rp[_i] > bcol) break; \ 104 if (rp[_i] == bcol) { \ 105 bap = ap + bs2*_i + bs*cidx + ridx; \ 106 if (addv == ADD_VALUES) *bap += value; \ 107 else *bap = value; \ 108 goto b_noinsert; \ 109 } \ 110 } \ 111 if (b->nonew == 1) goto b_noinsert; \ 112 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 113 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 114 N = nrow++ - 1; \ 115 /* shift up all the later entries in this row */ \ 116 for (ii=N; ii>=_i; ii--) { \ 117 rp[ii+1] = rp[ii]; \ 118 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 119 } \ 120 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 121 rp[_i] = bcol; \ 122 ap[bs2*_i + bs*cidx + ridx] = value; \ 123 B->nonzerostate++;\ 124 b_noinsert:; \ 125 bilen[brow] = nrow; \ 126 } 127 128 /* Only add/insert a(i,j) with i<=j (blocks). 129 Any a(i,j) with i>j input by user is ingored. 130 */ 131 #undef __FUNCT__ 132 #define __FUNCT__ "MatSetValues_MPISBAIJ" 133 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 134 { 135 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 136 MatScalar value; 137 PetscBool roworiented = baij->roworiented; 138 PetscErrorCode ierr; 139 PetscInt i,j,row,col; 140 PetscInt rstart_orig=mat->rmap->rstart; 141 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 142 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 143 144 /* Some Variables required in the macro */ 145 Mat A = baij->A; 146 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 147 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 148 MatScalar *aa =a->a; 149 150 Mat B = baij->B; 151 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 152 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 153 MatScalar *ba =b->a; 154 155 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 156 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 157 MatScalar *ap,*bap; 158 159 /* for stash */ 160 PetscInt n_loc, *in_loc = NULL; 161 MatScalar *v_loc = NULL; 162 163 PetscFunctionBegin; 164 if (!baij->donotstash) { 165 if (n > baij->n_loc) { 166 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 167 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 168 ierr = PetscMalloc1(n,&baij->in_loc);CHKERRQ(ierr); 169 ierr = PetscMalloc1(n,&baij->v_loc);CHKERRQ(ierr); 170 171 baij->n_loc = n; 172 } 173 in_loc = baij->in_loc; 174 v_loc = baij->v_loc; 175 } 176 177 for (i=0; i<m; i++) { 178 if (im[i] < 0) continue; 179 #if defined(PETSC_USE_DEBUG) 180 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); 181 #endif 182 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 183 row = im[i] - rstart_orig; /* local row index */ 184 for (j=0; j<n; j++) { 185 if (im[i]/bs > in[j]/bs) { 186 if (a->ignore_ltriangular) { 187 continue; /* ignore lower triangular blocks */ 188 } 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)"); 189 } 190 if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */ 191 col = in[j] - cstart_orig; /* local col index */ 192 brow = row/bs; bcol = col/bs; 193 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 194 if (roworiented) value = v[i*n+j]; 195 else value = v[i+j*m]; 196 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 197 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 198 } else if (in[j] < 0) continue; 199 #if defined(PETSC_USE_DEBUG) 200 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); 201 #endif 202 else { /* off-diag entry (B) */ 203 if (mat->was_assembled) { 204 if (!baij->colmap) { 205 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 206 } 207 #if defined(PETSC_USE_CTABLE) 208 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 209 col = col - 1; 210 #else 211 col = baij->colmap[in[j]/bs] - 1; 212 #endif 213 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 214 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 215 col = in[j]; 216 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 217 B = baij->B; 218 b = (Mat_SeqBAIJ*)(B)->data; 219 bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 220 ba = b->a; 221 } else col += in[j]%bs; 222 } else col = in[j]; 223 if (roworiented) value = v[i*n+j]; 224 else value = v[i+j*m]; 225 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 226 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 227 } 228 } 229 } else { /* off processor entry */ 230 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]); 231 if (!baij->donotstash) { 232 mat->assembled = PETSC_FALSE; 233 n_loc = 0; 234 for (j=0; j<n; j++) { 235 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 236 in_loc[n_loc] = in[j]; 237 if (roworiented) { 238 v_loc[n_loc] = v[i*n+j]; 239 } else { 240 v_loc[n_loc] = v[j*m+i]; 241 } 242 n_loc++; 243 } 244 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);CHKERRQ(ierr); 245 } 246 } 247 } 248 PetscFunctionReturn(0); 249 } 250 251 #undef __FUNCT__ 252 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 253 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 254 { 255 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 256 const MatScalar *value; 257 MatScalar *barray =baij->barray; 258 PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular; 259 PetscErrorCode ierr; 260 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 261 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 262 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 263 264 PetscFunctionBegin; 265 if (!barray) { 266 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 267 baij->barray = barray; 268 } 269 270 if (roworiented) { 271 stepval = (n-1)*bs; 272 } else { 273 stepval = (m-1)*bs; 274 } 275 for (i=0; i<m; i++) { 276 if (im[i] < 0) continue; 277 #if defined(PETSC_USE_DEBUG) 278 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); 279 #endif 280 if (im[i] >= rstart && im[i] < rend) { 281 row = im[i] - rstart; 282 for (j=0; j<n; j++) { 283 if (im[i] > in[j]) { 284 if (ignore_ltriangular) continue; /* ignore lower triangular blocks */ 285 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)"); 286 } 287 /* If NumCol = 1 then a copy is not required */ 288 if ((roworiented) && (n == 1)) { 289 barray = (MatScalar*) v + i*bs2; 290 } else if ((!roworiented) && (m == 1)) { 291 barray = (MatScalar*) v + j*bs2; 292 } else { /* Here a copy is required */ 293 if (roworiented) { 294 value = v + i*(stepval+bs)*bs + j*bs; 295 } else { 296 value = v + j*(stepval+bs)*bs + i*bs; 297 } 298 for (ii=0; ii<bs; ii++,value+=stepval) { 299 for (jj=0; jj<bs; jj++) { 300 *barray++ = *value++; 301 } 302 } 303 barray -=bs2; 304 } 305 306 if (in[j] >= cstart && in[j] < cend) { 307 col = in[j] - cstart; 308 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 309 } else if (in[j] < 0) continue; 310 #if defined(PETSC_USE_DEBUG) 311 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); 312 #endif 313 else { 314 if (mat->was_assembled) { 315 if (!baij->colmap) { 316 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 317 } 318 319 #if defined(PETSC_USE_DEBUG) 320 #if defined(PETSC_USE_CTABLE) 321 { PetscInt data; 322 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 323 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 324 } 325 #else 326 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 327 #endif 328 #endif 329 #if defined(PETSC_USE_CTABLE) 330 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 331 col = (col - 1)/bs; 332 #else 333 col = (baij->colmap[in[j]] - 1)/bs; 334 #endif 335 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 336 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 337 col = in[j]; 338 } 339 } else col = in[j]; 340 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 341 } 342 } 343 } else { 344 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]); 345 if (!baij->donotstash) { 346 if (roworiented) { 347 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 348 } else { 349 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 350 } 351 } 352 } 353 } 354 PetscFunctionReturn(0); 355 } 356 357 #undef __FUNCT__ 358 #define __FUNCT__ "MatGetValues_MPISBAIJ" 359 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 360 { 361 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 362 PetscErrorCode ierr; 363 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 364 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 365 366 PetscFunctionBegin; 367 for (i=0; i<m; i++) { 368 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 369 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); 370 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 371 row = idxm[i] - bsrstart; 372 for (j=0; j<n; j++) { 373 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 374 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); 375 if (idxn[j] >= bscstart && idxn[j] < bscend) { 376 col = idxn[j] - bscstart; 377 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 378 } else { 379 if (!baij->colmap) { 380 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 381 } 382 #if defined(PETSC_USE_CTABLE) 383 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 384 data--; 385 #else 386 data = baij->colmap[idxn[j]/bs]-1; 387 #endif 388 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 389 else { 390 col = data + idxn[j]%bs; 391 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 392 } 393 } 394 } 395 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 396 } 397 PetscFunctionReturn(0); 398 } 399 400 #undef __FUNCT__ 401 #define __FUNCT__ "MatNorm_MPISBAIJ" 402 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 403 { 404 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 405 PetscErrorCode ierr; 406 PetscReal sum[2],*lnorm2; 407 408 PetscFunctionBegin; 409 if (baij->size == 1) { 410 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 411 } else { 412 if (type == NORM_FROBENIUS) { 413 ierr = PetscMalloc1(2,&lnorm2);CHKERRQ(ierr); 414 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 415 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 416 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 417 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 418 ierr = MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 419 *norm = PetscSqrtReal(sum[0] + 2*sum[1]); 420 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 421 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 422 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 423 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 424 PetscReal *rsum,*rsum2,vabs; 425 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 426 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 427 MatScalar *v; 428 429 ierr = PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);CHKERRQ(ierr); 430 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 431 /* Amat */ 432 v = amat->a; jj = amat->j; 433 for (brow=0; brow<mbs; brow++) { 434 grow = bs*(rstart + brow); 435 nz = amat->i[brow+1] - amat->i[brow]; 436 for (bcol=0; bcol<nz; bcol++) { 437 gcol = bs*(rstart + *jj); jj++; 438 for (col=0; col<bs; col++) { 439 for (row=0; row<bs; row++) { 440 vabs = PetscAbsScalar(*v); v++; 441 rsum[gcol+col] += vabs; 442 /* non-diagonal block */ 443 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 444 } 445 } 446 } 447 } 448 /* Bmat */ 449 v = bmat->a; jj = bmat->j; 450 for (brow=0; brow<mbs; brow++) { 451 grow = bs*(rstart + brow); 452 nz = bmat->i[brow+1] - bmat->i[brow]; 453 for (bcol=0; bcol<nz; bcol++) { 454 gcol = bs*garray[*jj]; jj++; 455 for (col=0; col<bs; col++) { 456 for (row=0; row<bs; row++) { 457 vabs = PetscAbsScalar(*v); v++; 458 rsum[gcol+col] += vabs; 459 rsum[grow+row] += vabs; 460 } 461 } 462 } 463 } 464 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 465 *norm = 0.0; 466 for (col=0; col<mat->cmap->N; col++) { 467 if (rsum2[col] > *norm) *norm = rsum2[col]; 468 } 469 ierr = PetscFree2(rsum,rsum2);CHKERRQ(ierr); 470 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet"); 471 } 472 PetscFunctionReturn(0); 473 } 474 475 #undef __FUNCT__ 476 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 477 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 478 { 479 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 480 PetscErrorCode ierr; 481 PetscInt nstash,reallocs; 482 InsertMode addv; 483 484 PetscFunctionBegin; 485 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 486 487 /* make sure all processors are either in INSERTMODE or ADDMODE */ 488 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 489 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 490 mat->insertmode = addv; /* in case this processor had no cache */ 491 492 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 493 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 494 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 495 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 496 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 497 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 498 PetscFunctionReturn(0); 499 } 500 501 #undef __FUNCT__ 502 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 503 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 504 { 505 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 506 Mat_SeqSBAIJ *a =(Mat_SeqSBAIJ*)baij->A->data; 507 PetscErrorCode ierr; 508 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 509 PetscInt *row,*col; 510 PetscBool other_disassembled; 511 PetscMPIInt n; 512 PetscBool r1,r2,r3; 513 MatScalar *val; 514 InsertMode addv = mat->insertmode; 515 516 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 517 PetscFunctionBegin; 518 if (!baij->donotstash && !mat->nooffprocentries) { 519 while (1) { 520 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 521 if (!flg) break; 522 523 for (i=0; i<n;) { 524 /* Now identify the consecutive vals belonging to the same row */ 525 for (j=i,rstart=row[j]; j<n; j++) { 526 if (row[j] != rstart) break; 527 } 528 if (j < n) ncols = j-i; 529 else ncols = n-i; 530 /* Now assemble all these values with a single function call */ 531 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 532 i = j; 533 } 534 } 535 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 536 /* Now process the block-stash. Since the values are stashed column-oriented, 537 set the roworiented flag to column oriented, and after MatSetValues() 538 restore the original flags */ 539 r1 = baij->roworiented; 540 r2 = a->roworiented; 541 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 542 543 baij->roworiented = PETSC_FALSE; 544 a->roworiented = PETSC_FALSE; 545 546 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 547 while (1) { 548 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 549 if (!flg) break; 550 551 for (i=0; i<n;) { 552 /* Now identify the consecutive vals belonging to the same row */ 553 for (j=i,rstart=row[j]; j<n; j++) { 554 if (row[j] != rstart) break; 555 } 556 if (j < n) ncols = j-i; 557 else ncols = n-i; 558 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 559 i = j; 560 } 561 } 562 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 563 564 baij->roworiented = r1; 565 a->roworiented = r2; 566 567 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 568 } 569 570 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 571 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 572 573 /* determine if any processor has disassembled, if so we must 574 also disassemble ourselfs, in order that we may reassemble. */ 575 /* 576 if nonzero structure of submatrix B cannot change then we know that 577 no processor disassembled thus we can skip this stuff 578 */ 579 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 580 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 581 if (mat->was_assembled && !other_disassembled) { 582 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 583 } 584 } 585 586 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 587 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 588 } 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; 595 596 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 597 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 598 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 599 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 600 } 601 PetscFunctionReturn(0); 602 } 603 604 extern PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat,PetscViewer); 605 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 606 #include <petscdraw.h> 607 #undef __FUNCT__ 608 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 609 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 610 { 611 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 612 PetscErrorCode ierr; 613 PetscInt bs = mat->rmap->bs; 614 PetscMPIInt rank = baij->rank; 615 PetscBool iascii,isdraw; 616 PetscViewer sviewer; 617 PetscViewerFormat format; 618 619 PetscFunctionBegin; 620 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 621 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 622 if (iascii) { 623 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 624 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 625 MatInfo info; 626 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 627 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 628 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 629 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); 630 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 631 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 632 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 633 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 634 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 635 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 636 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 637 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 638 PetscFunctionReturn(0); 639 } else if (format == PETSC_VIEWER_ASCII_INFO) { 640 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 641 PetscFunctionReturn(0); 642 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 643 PetscFunctionReturn(0); 644 } 645 } 646 647 if (isdraw) { 648 PetscDraw draw; 649 PetscBool isnull; 650 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 651 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 652 } 653 654 { 655 /* assemble the entire matrix onto first processor. */ 656 Mat A; 657 Mat_SeqSBAIJ *Aloc; 658 Mat_SeqBAIJ *Bloc; 659 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 660 MatScalar *a; 661 const char *matname; 662 663 /* Should this be the same type as mat? */ 664 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 665 if (!rank) { 666 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 667 } else { 668 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 669 } 670 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 671 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 672 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 674 675 /* copy over the A part */ 676 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 677 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 678 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 679 680 for (i=0; i<mbs; i++) { 681 rvals[0] = bs*(baij->rstartbs + i); 682 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 683 for (j=ai[i]; j<ai[i+1]; j++) { 684 col = (baij->cstartbs+aj[j])*bs; 685 for (k=0; k<bs; k++) { 686 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 687 col++; 688 a += bs; 689 } 690 } 691 } 692 /* copy over the B part */ 693 Bloc = (Mat_SeqBAIJ*)baij->B->data; 694 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 695 for (i=0; i<mbs; i++) { 696 697 rvals[0] = bs*(baij->rstartbs + i); 698 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 699 for (j=ai[i]; j<ai[i+1]; j++) { 700 col = baij->garray[aj[j]]*bs; 701 for (k=0; k<bs; k++) { 702 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 703 col++; 704 a += bs; 705 } 706 } 707 } 708 ierr = PetscFree(rvals);CHKERRQ(ierr); 709 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 710 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 711 /* 712 Everyone has to call to draw the matrix since the graphics waits are 713 synchronized across all processors that share the PetscDraw object 714 */ 715 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 716 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 717 if (!rank) { 718 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 719 ierr = MatView_SeqSBAIJ_ASCII(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 720 } 721 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 722 ierr = MatDestroy(&A);CHKERRQ(ierr); 723 } 724 PetscFunctionReturn(0); 725 } 726 727 #undef __FUNCT__ 728 #define __FUNCT__ "MatView_MPISBAIJ" 729 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 730 { 731 PetscErrorCode ierr; 732 PetscBool iascii,isdraw,issocket,isbinary; 733 734 PetscFunctionBegin; 735 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 736 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 737 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 738 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 739 if (iascii || isdraw || issocket || isbinary) { 740 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 741 } 742 PetscFunctionReturn(0); 743 } 744 745 #undef __FUNCT__ 746 #define __FUNCT__ "MatDestroy_MPISBAIJ" 747 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 748 { 749 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 750 PetscErrorCode ierr; 751 752 PetscFunctionBegin; 753 #if defined(PETSC_USE_LOG) 754 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 755 #endif 756 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 757 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 758 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 759 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 760 #if defined(PETSC_USE_CTABLE) 761 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 762 #else 763 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 764 #endif 765 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 766 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 767 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 768 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 770 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 771 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 772 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 773 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 774 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 775 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 776 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 777 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 778 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 779 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 780 #if defined(PETSC_USE_REAL_MAT_SINGLE) 781 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 782 #endif 783 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 784 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 785 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 786 ierr = PetscFree(mat->data);CHKERRQ(ierr); 787 788 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 789 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 791 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 792 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 793 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);CHKERRQ(ierr); 794 PetscFunctionReturn(0); 795 } 796 797 #undef __FUNCT__ 798 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 799 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 800 { 801 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 802 PetscErrorCode ierr; 803 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 804 PetscScalar *x,*from; 805 806 PetscFunctionBegin; 807 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 808 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 809 810 /* diagonal part */ 811 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 812 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 813 814 /* subdiagonal part */ 815 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 816 817 /* copy x into the vec slvec0 */ 818 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 819 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 820 821 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 822 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 823 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 824 825 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 826 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 827 /* supperdiagonal part */ 828 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 829 PetscFunctionReturn(0); 830 } 831 832 #undef __FUNCT__ 833 #define __FUNCT__ "MatMult_MPISBAIJ" 834 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 835 { 836 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 837 PetscErrorCode ierr; 838 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 839 PetscScalar *from; 840 const PetscScalar *x; 841 842 PetscFunctionBegin; 843 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 844 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 845 846 /* diagonal part */ 847 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 848 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 849 850 /* subdiagonal part */ 851 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 852 853 /* copy x into the vec slvec0 */ 854 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 855 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 856 857 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 858 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 859 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 860 861 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 862 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 863 /* supperdiagonal part */ 864 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 #undef __FUNCT__ 869 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 870 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 871 { 872 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 873 PetscErrorCode ierr; 874 PetscInt nt; 875 876 PetscFunctionBegin; 877 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 878 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 879 880 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 881 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 882 883 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 884 /* do diagonal part */ 885 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 886 /* do supperdiagonal part */ 887 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 888 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 889 /* do subdiagonal part */ 890 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 891 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 892 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 893 PetscFunctionReturn(0); 894 } 895 896 #undef __FUNCT__ 897 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 898 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 899 { 900 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 901 PetscErrorCode ierr; 902 PetscInt mbs=a->mbs,bs=A->rmap->bs; 903 PetscScalar *from,zero=0.0; 904 const PetscScalar *x; 905 906 PetscFunctionBegin; 907 /* 908 PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n"); 909 PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT); 910 */ 911 /* diagonal part */ 912 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 913 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 914 915 /* subdiagonal part */ 916 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 917 918 /* copy x into the vec slvec0 */ 919 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 920 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 921 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 922 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 923 924 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 925 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 926 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 927 928 /* supperdiagonal part */ 929 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 930 PetscFunctionReturn(0); 931 } 932 933 #undef __FUNCT__ 934 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 935 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 936 { 937 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 938 PetscErrorCode ierr; 939 940 PetscFunctionBegin; 941 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 942 /* do diagonal part */ 943 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 944 /* do supperdiagonal part */ 945 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 946 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 947 948 /* do subdiagonal part */ 949 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 950 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 951 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 952 PetscFunctionReturn(0); 953 } 954 955 /* 956 This only works correctly for square matrices where the subblock A->A is the 957 diagonal block 958 */ 959 #undef __FUNCT__ 960 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 961 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 962 { 963 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 964 PetscErrorCode ierr; 965 966 PetscFunctionBegin; 967 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 968 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } 971 972 #undef __FUNCT__ 973 #define __FUNCT__ "MatScale_MPISBAIJ" 974 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 975 { 976 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 977 PetscErrorCode ierr; 978 979 PetscFunctionBegin; 980 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 981 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 982 PetscFunctionReturn(0); 983 } 984 985 #undef __FUNCT__ 986 #define __FUNCT__ "MatGetRow_MPISBAIJ" 987 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 988 { 989 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 990 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 991 PetscErrorCode ierr; 992 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 993 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 994 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 995 996 PetscFunctionBegin; 997 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 998 mat->getrowactive = PETSC_TRUE; 999 1000 if (!mat->rowvalues && (idx || v)) { 1001 /* 1002 allocate enough space to hold information from the longest row. 1003 */ 1004 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1005 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1006 PetscInt max = 1,mbs = mat->mbs,tmp; 1007 for (i=0; i<mbs; i++) { 1008 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1009 if (max < tmp) max = tmp; 1010 } 1011 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1012 } 1013 1014 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1015 lrow = row - brstart; /* local row index */ 1016 1017 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1018 if (!v) {pvA = 0; pvB = 0;} 1019 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1020 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1021 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1022 nztot = nzA + nzB; 1023 1024 cmap = mat->garray; 1025 if (v || idx) { 1026 if (nztot) { 1027 /* Sort by increasing column numbers, assuming A and B already sorted */ 1028 PetscInt imark = -1; 1029 if (v) { 1030 *v = v_p = mat->rowvalues; 1031 for (i=0; i<nzB; i++) { 1032 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1033 else break; 1034 } 1035 imark = i; 1036 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1037 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1038 } 1039 if (idx) { 1040 *idx = idx_p = mat->rowindices; 1041 if (imark > -1) { 1042 for (i=0; i<imark; i++) { 1043 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1044 } 1045 } else { 1046 for (i=0; i<nzB; i++) { 1047 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1048 else break; 1049 } 1050 imark = i; 1051 } 1052 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1053 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1054 } 1055 } else { 1056 if (idx) *idx = 0; 1057 if (v) *v = 0; 1058 } 1059 } 1060 *nz = nztot; 1061 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1062 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1063 PetscFunctionReturn(0); 1064 } 1065 1066 #undef __FUNCT__ 1067 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1068 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1069 { 1070 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1071 1072 PetscFunctionBegin; 1073 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1074 baij->getrowactive = PETSC_FALSE; 1075 PetscFunctionReturn(0); 1076 } 1077 1078 #undef __FUNCT__ 1079 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1080 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1081 { 1082 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1083 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1084 1085 PetscFunctionBegin; 1086 aA->getrow_utriangular = PETSC_TRUE; 1087 PetscFunctionReturn(0); 1088 } 1089 #undef __FUNCT__ 1090 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1091 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1092 { 1093 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1094 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1095 1096 PetscFunctionBegin; 1097 aA->getrow_utriangular = PETSC_FALSE; 1098 PetscFunctionReturn(0); 1099 } 1100 1101 #undef __FUNCT__ 1102 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1103 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1104 { 1105 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1106 PetscErrorCode ierr; 1107 1108 PetscFunctionBegin; 1109 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1110 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1111 PetscFunctionReturn(0); 1112 } 1113 1114 #undef __FUNCT__ 1115 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1116 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1117 { 1118 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1119 PetscErrorCode ierr; 1120 1121 PetscFunctionBegin; 1122 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1123 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1124 PetscFunctionReturn(0); 1125 } 1126 1127 #undef __FUNCT__ 1128 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1129 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1130 { 1131 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1132 PetscErrorCode ierr; 1133 1134 PetscFunctionBegin; 1135 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1136 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1137 PetscFunctionReturn(0); 1138 } 1139 1140 #undef __FUNCT__ 1141 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1142 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1143 { 1144 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1145 Mat A = a->A,B = a->B; 1146 PetscErrorCode ierr; 1147 PetscReal isend[5],irecv[5]; 1148 1149 PetscFunctionBegin; 1150 info->block_size = (PetscReal)matin->rmap->bs; 1151 1152 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1153 1154 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1155 isend[3] = info->memory; isend[4] = info->mallocs; 1156 1157 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1158 1159 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1160 isend[3] += info->memory; isend[4] += info->mallocs; 1161 if (flag == MAT_LOCAL) { 1162 info->nz_used = isend[0]; 1163 info->nz_allocated = isend[1]; 1164 info->nz_unneeded = isend[2]; 1165 info->memory = isend[3]; 1166 info->mallocs = isend[4]; 1167 } else if (flag == MAT_GLOBAL_MAX) { 1168 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1169 1170 info->nz_used = irecv[0]; 1171 info->nz_allocated = irecv[1]; 1172 info->nz_unneeded = irecv[2]; 1173 info->memory = irecv[3]; 1174 info->mallocs = irecv[4]; 1175 } else if (flag == MAT_GLOBAL_SUM) { 1176 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1177 1178 info->nz_used = irecv[0]; 1179 info->nz_allocated = irecv[1]; 1180 info->nz_unneeded = irecv[2]; 1181 info->memory = irecv[3]; 1182 info->mallocs = irecv[4]; 1183 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1184 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1185 info->fill_ratio_needed = 0; 1186 info->factor_mallocs = 0; 1187 PetscFunctionReturn(0); 1188 } 1189 1190 #undef __FUNCT__ 1191 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1192 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1193 { 1194 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1195 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1196 PetscErrorCode ierr; 1197 1198 PetscFunctionBegin; 1199 switch (op) { 1200 case MAT_NEW_NONZERO_LOCATIONS: 1201 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1202 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1203 case MAT_KEEP_NONZERO_PATTERN: 1204 case MAT_NEW_NONZERO_LOCATION_ERR: 1205 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1206 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1207 break; 1208 case MAT_ROW_ORIENTED: 1209 a->roworiented = flg; 1210 1211 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1212 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1213 break; 1214 case MAT_NEW_DIAGONALS: 1215 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1216 break; 1217 case MAT_IGNORE_OFF_PROC_ENTRIES: 1218 a->donotstash = flg; 1219 break; 1220 case MAT_USE_HASH_TABLE: 1221 a->ht_flag = flg; 1222 break; 1223 case MAT_HERMITIAN: 1224 if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first"); 1225 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1226 1227 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1228 break; 1229 case MAT_SPD: 1230 A->spd_set = PETSC_TRUE; 1231 A->spd = flg; 1232 if (flg) { 1233 A->symmetric = PETSC_TRUE; 1234 A->structurally_symmetric = PETSC_TRUE; 1235 A->symmetric_set = PETSC_TRUE; 1236 A->structurally_symmetric_set = PETSC_TRUE; 1237 } 1238 break; 1239 case MAT_SYMMETRIC: 1240 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1241 break; 1242 case MAT_STRUCTURALLY_SYMMETRIC: 1243 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1244 break; 1245 case MAT_SYMMETRY_ETERNAL: 1246 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1247 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1248 break; 1249 case MAT_IGNORE_LOWER_TRIANGULAR: 1250 aA->ignore_ltriangular = flg; 1251 break; 1252 case MAT_ERROR_LOWER_TRIANGULAR: 1253 aA->ignore_ltriangular = flg; 1254 break; 1255 case MAT_GETROW_UPPERTRIANGULAR: 1256 aA->getrow_utriangular = flg; 1257 break; 1258 default: 1259 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1260 } 1261 PetscFunctionReturn(0); 1262 } 1263 1264 #undef __FUNCT__ 1265 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1266 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1267 { 1268 PetscErrorCode ierr; 1269 1270 PetscFunctionBegin; 1271 if (MAT_INITIAL_MATRIX || *B != A) { 1272 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1273 } 1274 PetscFunctionReturn(0); 1275 } 1276 1277 #undef __FUNCT__ 1278 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1279 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1280 { 1281 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1282 Mat a = baij->A, b=baij->B; 1283 PetscErrorCode ierr; 1284 PetscInt nv,m,n; 1285 PetscBool flg; 1286 1287 PetscFunctionBegin; 1288 if (ll != rr) { 1289 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1290 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1291 } 1292 if (!ll) PetscFunctionReturn(0); 1293 1294 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1295 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1296 1297 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1298 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1299 1300 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1301 1302 /* left diagonalscale the off-diagonal part */ 1303 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1304 1305 /* scale the diagonal part */ 1306 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1307 1308 /* right diagonalscale the off-diagonal part */ 1309 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1310 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1311 PetscFunctionReturn(0); 1312 } 1313 1314 #undef __FUNCT__ 1315 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1316 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1317 { 1318 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1319 PetscErrorCode ierr; 1320 1321 PetscFunctionBegin; 1322 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*); 1327 1328 #undef __FUNCT__ 1329 #define __FUNCT__ "MatEqual_MPISBAIJ" 1330 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1331 { 1332 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1333 Mat a,b,c,d; 1334 PetscBool flg; 1335 PetscErrorCode ierr; 1336 1337 PetscFunctionBegin; 1338 a = matA->A; b = matA->B; 1339 c = matB->A; d = matB->B; 1340 1341 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1342 if (flg) { 1343 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1344 } 1345 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1346 PetscFunctionReturn(0); 1347 } 1348 1349 #undef __FUNCT__ 1350 #define __FUNCT__ "MatCopy_MPISBAIJ" 1351 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1352 { 1353 PetscErrorCode ierr; 1354 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1355 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data; 1356 1357 PetscFunctionBegin; 1358 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1359 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1360 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1361 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1362 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1363 } else { 1364 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1365 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1366 } 1367 PetscFunctionReturn(0); 1368 } 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1372 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1373 { 1374 PetscErrorCode ierr; 1375 1376 PetscFunctionBegin; 1377 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1378 PetscFunctionReturn(0); 1379 } 1380 1381 #undef __FUNCT__ 1382 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1383 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1384 { 1385 PetscErrorCode ierr; 1386 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data; 1387 PetscBLASInt bnz,one=1; 1388 Mat_SeqSBAIJ *xa,*ya; 1389 Mat_SeqBAIJ *xb,*yb; 1390 1391 PetscFunctionBegin; 1392 if (str == SAME_NONZERO_PATTERN) { 1393 PetscScalar alpha = a; 1394 xa = (Mat_SeqSBAIJ*)xx->A->data; 1395 ya = (Mat_SeqSBAIJ*)yy->A->data; 1396 ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr); 1397 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one)); 1398 xb = (Mat_SeqBAIJ*)xx->B->data; 1399 yb = (Mat_SeqBAIJ*)yy->B->data; 1400 ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr); 1401 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one)); 1402 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 1403 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 1404 ierr = MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 1405 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1406 ierr = MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);CHKERRQ(ierr); 1407 } else { 1408 Mat B; 1409 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 1410 if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size"); 1411 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1412 ierr = MatGetRowUpperTriangular(Y);CHKERRQ(ierr); 1413 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 1414 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 1415 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 1416 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 1417 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 1418 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 1419 ierr = MatSetType(B,MATMPISBAIJ);CHKERRQ(ierr); 1420 ierr = MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 1421 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 1422 ierr = MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 1423 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 1424 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 1425 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 1426 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 1427 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1428 ierr = MatRestoreRowUpperTriangular(Y);CHKERRQ(ierr); 1429 } 1430 PetscFunctionReturn(0); 1431 } 1432 1433 #undef __FUNCT__ 1434 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1435 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1436 { 1437 PetscErrorCode ierr; 1438 PetscInt i; 1439 PetscBool flg; 1440 1441 PetscFunctionBegin; 1442 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1443 for (i=0; i<n; i++) { 1444 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1445 if (!flg) { /* *B[i] is non-symmetric, set flag */ 1446 ierr = MatSetOption(*B[i],MAT_SYMMETRIC,PETSC_FALSE);CHKERRQ(ierr); 1447 } 1448 } 1449 PetscFunctionReturn(0); 1450 } 1451 1452 /* -------------------------------------------------------------------*/ 1453 static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ, 1454 MatGetRow_MPISBAIJ, 1455 MatRestoreRow_MPISBAIJ, 1456 MatMult_MPISBAIJ, 1457 /* 4*/ MatMultAdd_MPISBAIJ, 1458 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1459 MatMultAdd_MPISBAIJ, 1460 0, 1461 0, 1462 0, 1463 /* 10*/ 0, 1464 0, 1465 0, 1466 MatSOR_MPISBAIJ, 1467 MatTranspose_MPISBAIJ, 1468 /* 15*/ MatGetInfo_MPISBAIJ, 1469 MatEqual_MPISBAIJ, 1470 MatGetDiagonal_MPISBAIJ, 1471 MatDiagonalScale_MPISBAIJ, 1472 MatNorm_MPISBAIJ, 1473 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1474 MatAssemblyEnd_MPISBAIJ, 1475 MatSetOption_MPISBAIJ, 1476 MatZeroEntries_MPISBAIJ, 1477 /* 24*/ 0, 1478 0, 1479 0, 1480 0, 1481 0, 1482 /* 29*/ MatSetUp_MPISBAIJ, 1483 0, 1484 0, 1485 0, 1486 0, 1487 /* 34*/ MatDuplicate_MPISBAIJ, 1488 0, 1489 0, 1490 0, 1491 0, 1492 /* 39*/ MatAXPY_MPISBAIJ, 1493 MatGetSubMatrices_MPISBAIJ, 1494 MatIncreaseOverlap_MPISBAIJ, 1495 MatGetValues_MPISBAIJ, 1496 MatCopy_MPISBAIJ, 1497 /* 44*/ 0, 1498 MatScale_MPISBAIJ, 1499 0, 1500 0, 1501 0, 1502 /* 49*/ 0, 1503 0, 1504 0, 1505 0, 1506 0, 1507 /* 54*/ 0, 1508 0, 1509 MatSetUnfactored_MPISBAIJ, 1510 0, 1511 MatSetValuesBlocked_MPISBAIJ, 1512 /* 59*/ 0, 1513 0, 1514 0, 1515 0, 1516 0, 1517 /* 64*/ 0, 1518 0, 1519 0, 1520 0, 1521 0, 1522 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1523 0, 1524 0, 1525 0, 1526 0, 1527 /* 74*/ 0, 1528 0, 1529 0, 1530 0, 1531 0, 1532 /* 79*/ 0, 1533 0, 1534 0, 1535 0, 1536 MatLoad_MPISBAIJ, 1537 /* 84*/ 0, 1538 0, 1539 0, 1540 0, 1541 0, 1542 /* 89*/ 0, 1543 0, 1544 0, 1545 0, 1546 0, 1547 /* 94*/ 0, 1548 0, 1549 0, 1550 0, 1551 0, 1552 /* 99*/ 0, 1553 0, 1554 0, 1555 0, 1556 0, 1557 /*104*/ 0, 1558 MatRealPart_MPISBAIJ, 1559 MatImaginaryPart_MPISBAIJ, 1560 MatGetRowUpperTriangular_MPISBAIJ, 1561 MatRestoreRowUpperTriangular_MPISBAIJ, 1562 /*109*/ 0, 1563 0, 1564 0, 1565 0, 1566 0, 1567 /*114*/ 0, 1568 0, 1569 0, 1570 0, 1571 0, 1572 /*119*/ 0, 1573 0, 1574 0, 1575 0, 1576 0, 1577 /*124*/ 0, 1578 0, 1579 0, 1580 0, 1581 0, 1582 /*129*/ 0, 1583 0, 1584 0, 1585 0, 1586 0, 1587 /*134*/ 0, 1588 0, 1589 0, 1590 0, 1591 0, 1592 /*139*/ 0, 1593 0, 1594 0, 1595 0, 1596 0, 1597 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ 1598 }; 1599 1600 #undef __FUNCT__ 1601 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1602 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1603 { 1604 PetscFunctionBegin; 1605 *a = ((Mat_MPISBAIJ*)A->data)->A; 1606 PetscFunctionReturn(0); 1607 } 1608 1609 #undef __FUNCT__ 1610 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1611 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 1612 { 1613 Mat_MPISBAIJ *b; 1614 PetscErrorCode ierr; 1615 PetscInt i,mbs,Mbs; 1616 1617 PetscFunctionBegin; 1618 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 1619 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1620 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1621 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1622 1623 b = (Mat_MPISBAIJ*)B->data; 1624 mbs = B->rmap->n/bs; 1625 Mbs = B->rmap->N/bs; 1626 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); 1627 1628 B->rmap->bs = bs; 1629 b->bs2 = bs*bs; 1630 b->mbs = mbs; 1631 b->Mbs = Mbs; 1632 b->nbs = B->cmap->n/bs; 1633 b->Nbs = B->cmap->N/bs; 1634 1635 for (i=0; i<=b->size; i++) { 1636 b->rangebs[i] = B->rmap->range[i]/bs; 1637 } 1638 b->rstartbs = B->rmap->rstart/bs; 1639 b->rendbs = B->rmap->rend/bs; 1640 1641 b->cstartbs = B->cmap->rstart/bs; 1642 b->cendbs = B->cmap->rend/bs; 1643 1644 if (!B->preallocated) { 1645 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1646 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1647 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1648 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 1649 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1650 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1651 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1652 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 1653 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 1654 } 1655 1656 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1657 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1658 1659 B->preallocated = PETSC_TRUE; 1660 PetscFunctionReturn(0); 1661 } 1662 1663 #undef __FUNCT__ 1664 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1665 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1666 { 1667 PetscInt m,rstart,cstart,cend; 1668 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1669 const PetscInt *JJ =0; 1670 PetscScalar *values=0; 1671 PetscErrorCode ierr; 1672 1673 PetscFunctionBegin; 1674 if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1675 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1676 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1677 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1678 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1679 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1680 m = B->rmap->n/bs; 1681 rstart = B->rmap->rstart/bs; 1682 cstart = B->cmap->rstart/bs; 1683 cend = B->cmap->rend/bs; 1684 1685 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1686 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 1687 for (i=0; i<m; i++) { 1688 nz = ii[i+1] - ii[i]; 1689 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1690 nz_max = PetscMax(nz_max,nz); 1691 JJ = jj + ii[i]; 1692 for (j=0; j<nz; j++) { 1693 if (*JJ >= cstart) break; 1694 JJ++; 1695 } 1696 d = 0; 1697 for (; j<nz; j++) { 1698 if (*JJ++ >= cend) break; 1699 d++; 1700 } 1701 d_nnz[i] = d; 1702 o_nnz[i] = nz - d; 1703 } 1704 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1705 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1706 1707 values = (PetscScalar*)V; 1708 if (!values) { 1709 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 1710 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1711 } 1712 for (i=0; i<m; i++) { 1713 PetscInt row = i + rstart; 1714 PetscInt ncols = ii[i+1] - ii[i]; 1715 const PetscInt *icols = jj + ii[i]; 1716 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1717 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1718 } 1719 1720 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1721 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1722 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1723 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1724 PetscFunctionReturn(0); 1725 } 1726 1727 /*MC 1728 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1729 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1730 the matrix is stored. 1731 1732 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1733 can call MatSetOption(Mat, MAT_HERMITIAN); 1734 1735 Options Database Keys: 1736 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1737 1738 Level: beginner 1739 1740 .seealso: MatCreateMPISBAIJ 1741 M*/ 1742 1743 PETSC_EXTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1744 1745 #undef __FUNCT__ 1746 #define __FUNCT__ "MatCreate_MPISBAIJ" 1747 PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1748 { 1749 Mat_MPISBAIJ *b; 1750 PetscErrorCode ierr; 1751 PetscBool flg = PETSC_FALSE; 1752 1753 PetscFunctionBegin; 1754 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 1755 B->data = (void*)b; 1756 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1757 1758 B->ops->destroy = MatDestroy_MPISBAIJ; 1759 B->ops->view = MatView_MPISBAIJ; 1760 B->assembled = PETSC_FALSE; 1761 B->insertmode = NOT_SET_VALUES; 1762 1763 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 1764 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 1765 1766 /* build local table of row and column ownerships */ 1767 ierr = PetscMalloc1(b->size+2,&b->rangebs);CHKERRQ(ierr); 1768 1769 /* build cache for off array entries formed */ 1770 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 1771 1772 b->donotstash = PETSC_FALSE; 1773 b->colmap = NULL; 1774 b->garray = NULL; 1775 b->roworiented = PETSC_TRUE; 1776 1777 /* stuff used in block assembly */ 1778 b->barray = 0; 1779 1780 /* stuff used for matrix vector multiply */ 1781 b->lvec = 0; 1782 b->Mvctx = 0; 1783 b->slvec0 = 0; 1784 b->slvec0b = 0; 1785 b->slvec1 = 0; 1786 b->slvec1a = 0; 1787 b->slvec1b = 0; 1788 b->sMvctx = 0; 1789 1790 /* stuff for MatGetRow() */ 1791 b->rowindices = 0; 1792 b->rowvalues = 0; 1793 b->getrowactive = PETSC_FALSE; 1794 1795 /* hash table stuff */ 1796 b->ht = 0; 1797 b->hd = 0; 1798 b->ht_size = 0; 1799 b->ht_flag = PETSC_FALSE; 1800 b->ht_fact = 0; 1801 b->ht_total_ct = 0; 1802 b->ht_insert_ct = 0; 1803 1804 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1805 b->ijonly = PETSC_FALSE; 1806 1807 b->in_loc = 0; 1808 b->v_loc = 0; 1809 b->n_loc = 0; 1810 1811 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1812 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1813 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1814 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1815 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1816 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1817 1818 B->symmetric = PETSC_TRUE; 1819 B->structurally_symmetric = PETSC_TRUE; 1820 B->symmetric_set = PETSC_TRUE; 1821 B->structurally_symmetric_set = PETSC_TRUE; 1822 1823 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1824 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1825 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);CHKERRQ(ierr); 1826 if (flg) { 1827 PetscReal fact = 1.39; 1828 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1829 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 1830 if (fact <= 1.0) fact = 1.39; 1831 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1832 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1833 } 1834 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1835 PetscFunctionReturn(0); 1836 } 1837 1838 /*MC 1839 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1840 1841 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1842 and MATMPISBAIJ otherwise. 1843 1844 Options Database Keys: 1845 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1846 1847 Level: beginner 1848 1849 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1850 M*/ 1851 1852 #undef __FUNCT__ 1853 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1854 /*@C 1855 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1856 the user should preallocate the matrix storage by setting the parameters 1857 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1858 performance can be increased by more than a factor of 50. 1859 1860 Collective on Mat 1861 1862 Input Parameters: 1863 + B - the matrix 1864 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 1865 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 1866 . d_nz - number of block nonzeros per block row in diagonal portion of local 1867 submatrix (same for all local rows) 1868 . d_nnz - array containing the number of block nonzeros in the various block rows 1869 in the upper triangular and diagonal part of the in diagonal portion of the local 1870 (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room 1871 for the diagonal entry and set a value even if it is zero. 1872 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1873 submatrix (same for all local rows). 1874 - o_nnz - array containing the number of nonzeros in the various block rows of the 1875 off-diagonal portion of the local submatrix that is right of the diagonal 1876 (possibly different for each block row) or NULL. 1877 1878 1879 Options Database Keys: 1880 . -mat_no_unroll - uses code that does not unroll the loops in the 1881 block calculations (much slower) 1882 . -mat_block_size - size of the blocks to use 1883 1884 Notes: 1885 1886 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1887 than it must be used on all processors that share the object for that argument. 1888 1889 If the *_nnz parameter is given then the *_nz parameter is ignored 1890 1891 Storage Information: 1892 For a square global matrix we define each processor's diagonal portion 1893 to be its local rows and the corresponding columns (a square submatrix); 1894 each processor's off-diagonal portion encompasses the remainder of the 1895 local matrix (a rectangular submatrix). 1896 1897 The user can specify preallocated storage for the diagonal part of 1898 the local submatrix with either d_nz or d_nnz (not both). Set 1899 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 1900 memory allocation. Likewise, specify preallocated storage for the 1901 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1902 1903 You can call MatGetInfo() to get information on how effective the preallocation was; 1904 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1905 You can also run with the option -info and look for messages with the string 1906 malloc in them to see if additional memory allocation was needed. 1907 1908 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1909 the figure below we depict these three local rows and all columns (0-11). 1910 1911 .vb 1912 0 1 2 3 4 5 6 7 8 9 10 11 1913 -------------------------- 1914 row 3 |. . . d d d o o o o o o 1915 row 4 |. . . d d d o o o o o o 1916 row 5 |. . . d d d o o o o o o 1917 -------------------------- 1918 .ve 1919 1920 Thus, any entries in the d locations are stored in the d (diagonal) 1921 submatrix, and any entries in the o locations are stored in the 1922 o (off-diagonal) submatrix. Note that the d matrix is stored in 1923 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1924 1925 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1926 plus the diagonal part of the d matrix, 1927 and o_nz should indicate the number of block nonzeros per row in the o matrix 1928 1929 In general, for PDE problems in which most nonzeros are near the diagonal, 1930 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1931 or you will get TERRIBLE performance; see the users' manual chapter on 1932 matrices. 1933 1934 Level: intermediate 1935 1936 .keywords: matrix, block, aij, compressed row, sparse, parallel 1937 1938 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership() 1939 @*/ 1940 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1941 { 1942 PetscErrorCode ierr; 1943 1944 PetscFunctionBegin; 1945 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 1946 PetscValidType(B,1); 1947 PetscValidLogicalCollectiveInt(B,bs,2); 1948 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); 1949 PetscFunctionReturn(0); 1950 } 1951 1952 #undef __FUNCT__ 1953 #define __FUNCT__ "MatCreateSBAIJ" 1954 /*@C 1955 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1956 (block compressed row). For good matrix assembly performance 1957 the user should preallocate the matrix storage by setting the parameters 1958 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1959 performance can be increased by more than a factor of 50. 1960 1961 Collective on MPI_Comm 1962 1963 Input Parameters: 1964 + comm - MPI communicator 1965 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 1966 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 1967 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1968 This value should be the same as the local size used in creating the 1969 y vector for the matrix-vector product y = Ax. 1970 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1971 This value should be the same as the local size used in creating the 1972 x vector for the matrix-vector product y = Ax. 1973 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1974 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1975 . d_nz - number of block nonzeros per block row in diagonal portion of local 1976 submatrix (same for all local rows) 1977 . d_nnz - array containing the number of block nonzeros in the various block rows 1978 in the upper triangular portion of the in diagonal portion of the local 1979 (possibly different for each block block row) or NULL. 1980 If you plan to factor the matrix you must leave room for the diagonal entry and 1981 set its value even if it is zero. 1982 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1983 submatrix (same for all local rows). 1984 - o_nnz - array containing the number of nonzeros in the various block rows of the 1985 off-diagonal portion of the local submatrix (possibly different for 1986 each block row) or NULL. 1987 1988 Output Parameter: 1989 . A - the matrix 1990 1991 Options Database Keys: 1992 . -mat_no_unroll - uses code that does not unroll the loops in the 1993 block calculations (much slower) 1994 . -mat_block_size - size of the blocks to use 1995 . -mat_mpi - use the parallel matrix data structures even on one processor 1996 (defaults to using SeqBAIJ format on one processor) 1997 1998 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1999 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2000 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2001 2002 Notes: 2003 The number of rows and columns must be divisible by blocksize. 2004 This matrix type does not support complex Hermitian operation. 2005 2006 The user MUST specify either the local or global matrix dimensions 2007 (possibly both). 2008 2009 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2010 than it must be used on all processors that share the object for that argument. 2011 2012 If the *_nnz parameter is given then the *_nz parameter is ignored 2013 2014 Storage Information: 2015 For a square global matrix we define each processor's diagonal portion 2016 to be its local rows and the corresponding columns (a square submatrix); 2017 each processor's off-diagonal portion encompasses the remainder of the 2018 local matrix (a rectangular submatrix). 2019 2020 The user can specify preallocated storage for the diagonal part of 2021 the local submatrix with either d_nz or d_nnz (not both). Set 2022 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 2023 memory allocation. Likewise, specify preallocated storage for the 2024 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2025 2026 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2027 the figure below we depict these three local rows and all columns (0-11). 2028 2029 .vb 2030 0 1 2 3 4 5 6 7 8 9 10 11 2031 -------------------------- 2032 row 3 |. . . d d d o o o o o o 2033 row 4 |. . . d d d o o o o o o 2034 row 5 |. . . d d d o o o o o o 2035 -------------------------- 2036 .ve 2037 2038 Thus, any entries in the d locations are stored in the d (diagonal) 2039 submatrix, and any entries in the o locations are stored in the 2040 o (off-diagonal) submatrix. Note that the d matrix is stored in 2041 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2042 2043 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2044 plus the diagonal part of the d matrix, 2045 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2046 In general, for PDE problems in which most nonzeros are near the diagonal, 2047 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2048 or you will get TERRIBLE performance; see the users' manual chapter on 2049 matrices. 2050 2051 Level: intermediate 2052 2053 .keywords: matrix, block, aij, compressed row, sparse, parallel 2054 2055 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2056 @*/ 2057 2058 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) 2059 { 2060 PetscErrorCode ierr; 2061 PetscMPIInt size; 2062 2063 PetscFunctionBegin; 2064 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2065 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2066 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2067 if (size > 1) { 2068 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2069 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2070 } else { 2071 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2072 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2073 } 2074 PetscFunctionReturn(0); 2075 } 2076 2077 2078 #undef __FUNCT__ 2079 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2080 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2081 { 2082 Mat mat; 2083 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2084 PetscErrorCode ierr; 2085 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2086 PetscScalar *array; 2087 2088 PetscFunctionBegin; 2089 *newmat = 0; 2090 2091 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2092 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2093 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2094 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2095 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2096 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2097 2098 mat->factortype = matin->factortype; 2099 mat->preallocated = PETSC_TRUE; 2100 mat->assembled = PETSC_TRUE; 2101 mat->insertmode = NOT_SET_VALUES; 2102 2103 a = (Mat_MPISBAIJ*)mat->data; 2104 a->bs2 = oldmat->bs2; 2105 a->mbs = oldmat->mbs; 2106 a->nbs = oldmat->nbs; 2107 a->Mbs = oldmat->Mbs; 2108 a->Nbs = oldmat->Nbs; 2109 2110 2111 a->size = oldmat->size; 2112 a->rank = oldmat->rank; 2113 a->donotstash = oldmat->donotstash; 2114 a->roworiented = oldmat->roworiented; 2115 a->rowindices = 0; 2116 a->rowvalues = 0; 2117 a->getrowactive = PETSC_FALSE; 2118 a->barray = 0; 2119 a->rstartbs = oldmat->rstartbs; 2120 a->rendbs = oldmat->rendbs; 2121 a->cstartbs = oldmat->cstartbs; 2122 a->cendbs = oldmat->cendbs; 2123 2124 /* hash table stuff */ 2125 a->ht = 0; 2126 a->hd = 0; 2127 a->ht_size = 0; 2128 a->ht_flag = oldmat->ht_flag; 2129 a->ht_fact = oldmat->ht_fact; 2130 a->ht_total_ct = 0; 2131 a->ht_insert_ct = 0; 2132 2133 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2134 if (oldmat->colmap) { 2135 #if defined(PETSC_USE_CTABLE) 2136 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2137 #else 2138 ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr); 2139 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2140 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2141 #endif 2142 } else a->colmap = 0; 2143 2144 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2145 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 2146 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2147 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2148 } else a->garray = 0; 2149 2150 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2151 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2152 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2153 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2154 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2155 2156 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2157 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2158 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2159 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2160 2161 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2162 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2163 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2164 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2165 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2166 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2167 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2168 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2169 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2170 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2171 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);CHKERRQ(ierr); 2172 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);CHKERRQ(ierr); 2173 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);CHKERRQ(ierr); 2174 2175 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2176 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2177 a->sMvctx = oldmat->sMvctx; 2178 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);CHKERRQ(ierr); 2179 2180 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2181 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2182 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2183 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2184 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2185 *newmat = mat; 2186 PetscFunctionReturn(0); 2187 } 2188 2189 #undef __FUNCT__ 2190 #define __FUNCT__ "MatLoad_MPISBAIJ" 2191 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2192 { 2193 PetscErrorCode ierr; 2194 PetscInt i,nz,j,rstart,rend; 2195 PetscScalar *vals,*buf; 2196 MPI_Comm comm; 2197 MPI_Status status; 2198 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2199 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2200 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2201 PetscInt bs = newmat->rmap->bs,Mbs,mbs,extra_rows; 2202 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2203 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2204 int fd; 2205 2206 PetscFunctionBegin; 2207 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2208 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2209 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2210 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2211 if (bs < 0) bs = 1; 2212 2213 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2214 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2215 if (!rank) { 2216 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2217 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2218 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2219 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2220 } 2221 2222 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2223 2224 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2225 M = header[1]; 2226 N = header[2]; 2227 2228 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2229 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2230 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2231 2232 /* If global sizes are set, check if they are consistent with that given in the file */ 2233 if (sizesset) { 2234 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2235 } 2236 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); 2237 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); 2238 2239 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2240 2241 /* 2242 This code adds extra rows to make sure the number of rows is 2243 divisible by the blocksize 2244 */ 2245 Mbs = M/bs; 2246 extra_rows = bs - M + bs*(Mbs); 2247 if (extra_rows == bs) extra_rows = 0; 2248 else Mbs++; 2249 if (extra_rows &&!rank) { 2250 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2251 } 2252 2253 /* determine ownership of all rows */ 2254 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2255 mbs = Mbs/size + ((Mbs % size) > rank); 2256 m = mbs*bs; 2257 } else { /* User Set */ 2258 m = newmat->rmap->n; 2259 mbs = m/bs; 2260 } 2261 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 2262 ierr = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr); 2263 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2264 rowners[0] = 0; 2265 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2266 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2267 rstart = rowners[rank]; 2268 rend = rowners[rank+1]; 2269 2270 /* distribute row lengths to all processors */ 2271 ierr = PetscMalloc1((rend-rstart)*bs,&locrowlens);CHKERRQ(ierr); 2272 if (!rank) { 2273 ierr = PetscMalloc1(M+extra_rows,&rowlengths);CHKERRQ(ierr); 2274 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2275 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2276 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 2277 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2278 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2279 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2280 } else { 2281 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2282 } 2283 2284 if (!rank) { /* procs[0] */ 2285 /* calculate the number of nonzeros on each processor */ 2286 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 2287 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2288 for (i=0; i<size; i++) { 2289 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2290 procsnz[i] += rowlengths[j]; 2291 } 2292 } 2293 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2294 2295 /* determine max buffer needed and allocate it */ 2296 maxnz = 0; 2297 for (i=0; i<size; i++) { 2298 maxnz = PetscMax(maxnz,procsnz[i]); 2299 } 2300 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2301 2302 /* read in my part of the matrix column indices */ 2303 nz = procsnz[0]; 2304 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2305 mycols = ibuf; 2306 if (size == 1) nz -= extra_rows; 2307 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2308 if (size == 1) { 2309 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 2310 } 2311 2312 /* read in every ones (except the last) and ship off */ 2313 for (i=1; i<size-1; i++) { 2314 nz = procsnz[i]; 2315 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2316 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2317 } 2318 /* read in the stuff for the last proc */ 2319 if (size != 1) { 2320 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2321 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2322 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2323 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2324 } 2325 ierr = PetscFree(cols);CHKERRQ(ierr); 2326 } else { /* procs[i], i>0 */ 2327 /* determine buffer space needed for message */ 2328 nz = 0; 2329 for (i=0; i<m; i++) nz += locrowlens[i]; 2330 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2331 mycols = ibuf; 2332 /* receive message of column indices*/ 2333 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2334 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2335 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2336 } 2337 2338 /* loop over local rows, determining number of off diagonal entries */ 2339 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 2340 ierr = PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 2341 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2342 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2343 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2344 rowcount = 0; 2345 nzcount = 0; 2346 for (i=0; i<mbs; i++) { 2347 dcount = 0; 2348 odcount = 0; 2349 for (j=0; j<bs; j++) { 2350 kmax = locrowlens[rowcount]; 2351 for (k=0; k<kmax; k++) { 2352 tmp = mycols[nzcount++]/bs; /* block col. index */ 2353 if (!mask[tmp]) { 2354 mask[tmp] = 1; 2355 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2356 else masked1[dcount++] = tmp; /* entry in diag portion */ 2357 } 2358 } 2359 rowcount++; 2360 } 2361 2362 dlens[i] = dcount; /* d_nzz[i] */ 2363 odlens[i] = odcount; /* o_nzz[i] */ 2364 2365 /* zero out the mask elements we set */ 2366 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2367 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2368 } 2369 if (!sizesset) { 2370 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2371 } 2372 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2373 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2374 2375 if (!rank) { 2376 ierr = PetscMalloc1(maxnz,&buf);CHKERRQ(ierr); 2377 /* read in my part of the matrix numerical values */ 2378 nz = procsnz[0]; 2379 vals = buf; 2380 mycols = ibuf; 2381 if (size == 1) nz -= extra_rows; 2382 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2383 if (size == 1) { 2384 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 2385 } 2386 2387 /* insert into matrix */ 2388 jj = rstart*bs; 2389 for (i=0; i<m; i++) { 2390 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2391 mycols += locrowlens[i]; 2392 vals += locrowlens[i]; 2393 jj++; 2394 } 2395 2396 /* read in other processors (except the last one) and ship out */ 2397 for (i=1; i<size-1; i++) { 2398 nz = procsnz[i]; 2399 vals = buf; 2400 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2401 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2402 } 2403 /* the last proc */ 2404 if (size != 1) { 2405 nz = procsnz[i] - extra_rows; 2406 vals = buf; 2407 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2408 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2409 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2410 } 2411 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2412 2413 } else { 2414 /* receive numeric values */ 2415 ierr = PetscMalloc1(nz,&buf);CHKERRQ(ierr); 2416 2417 /* receive message of values*/ 2418 vals = buf; 2419 mycols = ibuf; 2420 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2421 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2422 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2423 2424 /* insert into matrix */ 2425 jj = rstart*bs; 2426 for (i=0; i<m; i++) { 2427 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2428 mycols += locrowlens[i]; 2429 vals += locrowlens[i]; 2430 jj++; 2431 } 2432 } 2433 2434 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2435 ierr = PetscFree(buf);CHKERRQ(ierr); 2436 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2437 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2438 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2439 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2440 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2441 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2442 PetscFunctionReturn(0); 2443 } 2444 2445 #undef __FUNCT__ 2446 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2447 /*XXXXX@ 2448 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2449 2450 Input Parameters: 2451 . mat - the matrix 2452 . fact - factor 2453 2454 Not Collective on Mat, each process can have a different hash factor 2455 2456 Level: advanced 2457 2458 Notes: 2459 This can also be set by the command line option: -mat_use_hash_table fact 2460 2461 .keywords: matrix, hashtable, factor, HT 2462 2463 .seealso: MatSetOption() 2464 @XXXXX*/ 2465 2466 2467 #undef __FUNCT__ 2468 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2469 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2470 { 2471 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2472 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2473 PetscReal atmp; 2474 PetscReal *work,*svalues,*rvalues; 2475 PetscErrorCode ierr; 2476 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2477 PetscMPIInt rank,size; 2478 PetscInt *rowners_bs,dest,count,source; 2479 PetscScalar *va; 2480 MatScalar *ba; 2481 MPI_Status stat; 2482 2483 PetscFunctionBegin; 2484 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2485 ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr); 2486 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2487 2488 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2489 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2490 2491 bs = A->rmap->bs; 2492 mbs = a->mbs; 2493 Mbs = a->Mbs; 2494 ba = b->a; 2495 bi = b->i; 2496 bj = b->j; 2497 2498 /* find ownerships */ 2499 rowners_bs = A->rmap->range; 2500 2501 /* each proc creates an array to be distributed */ 2502 ierr = PetscMalloc1(bs*Mbs,&work);CHKERRQ(ierr); 2503 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2504 2505 /* row_max for B */ 2506 if (rank != size-1) { 2507 for (i=0; i<mbs; i++) { 2508 ncols = bi[1] - bi[0]; bi++; 2509 brow = bs*i; 2510 for (j=0; j<ncols; j++) { 2511 bcol = bs*(*bj); 2512 for (kcol=0; kcol<bs; kcol++) { 2513 col = bcol + kcol; /* local col index */ 2514 col += rowners_bs[rank+1]; /* global col index */ 2515 for (krow=0; krow<bs; krow++) { 2516 atmp = PetscAbsScalar(*ba); ba++; 2517 row = brow + krow; /* local row index */ 2518 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2519 if (work[col] < atmp) work[col] = atmp; 2520 } 2521 } 2522 bj++; 2523 } 2524 } 2525 2526 /* send values to its owners */ 2527 for (dest=rank+1; dest<size; dest++) { 2528 svalues = work + rowners_bs[dest]; 2529 count = rowners_bs[dest+1]-rowners_bs[dest]; 2530 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2531 } 2532 } 2533 2534 /* receive values */ 2535 if (rank) { 2536 rvalues = work; 2537 count = rowners_bs[rank+1]-rowners_bs[rank]; 2538 for (source=0; source<rank; source++) { 2539 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr); 2540 /* process values */ 2541 for (i=0; i<count; i++) { 2542 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2543 } 2544 } 2545 } 2546 2547 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2548 ierr = PetscFree(work);CHKERRQ(ierr); 2549 PetscFunctionReturn(0); 2550 } 2551 2552 #undef __FUNCT__ 2553 #define __FUNCT__ "MatSOR_MPISBAIJ" 2554 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2555 { 2556 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2557 PetscErrorCode ierr; 2558 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2559 PetscScalar *x,*ptr,*from; 2560 Vec bb1; 2561 const PetscScalar *b; 2562 2563 PetscFunctionBegin; 2564 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); 2565 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2566 2567 if (flag == SOR_APPLY_UPPER) { 2568 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2573 if (flag & SOR_ZERO_INITIAL_GUESS) { 2574 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2575 its--; 2576 } 2577 2578 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2579 while (its--) { 2580 2581 /* lower triangular part: slvec0b = - B^T*xx */ 2582 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2583 2584 /* copy xx into slvec0a */ 2585 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2586 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2587 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2588 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2589 2590 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2591 2592 /* copy bb into slvec1a */ 2593 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2594 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2595 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2596 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2597 2598 /* set slvec1b = 0 */ 2599 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2600 2601 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2602 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2603 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2604 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2605 2606 /* upper triangular part: bb1 = bb1 - B*x */ 2607 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2608 2609 /* local diagonal sweep */ 2610 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2611 } 2612 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2613 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2614 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2615 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2616 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2617 } else if (flag & SOR_EISENSTAT) { 2618 Vec xx1; 2619 PetscBool hasop; 2620 const PetscScalar *diag; 2621 PetscScalar *sl,scale = (omega - 2.0)/omega; 2622 PetscInt i,n; 2623 2624 if (!mat->xx1) { 2625 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2626 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2627 } 2628 xx1 = mat->xx1; 2629 bb1 = mat->bb1; 2630 2631 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2632 2633 if (!mat->diag) { 2634 /* this is wrong for same matrix with new nonzero values */ 2635 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 2636 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2637 } 2638 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2639 2640 if (hasop) { 2641 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2642 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2643 } else { 2644 /* 2645 These two lines are replaced by code that may be a bit faster for a good compiler 2646 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2647 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2648 */ 2649 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2650 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2651 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2652 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2653 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2654 if (omega == 1.0) { 2655 for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i]; 2656 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2657 } else { 2658 for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i]; 2659 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2660 } 2661 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2662 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2663 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2664 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2665 } 2666 2667 /* multiply off-diagonal portion of matrix */ 2668 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2669 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2670 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2671 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2672 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2673 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2674 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2675 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2676 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2677 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2678 2679 /* local sweep */ 2680 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); 2681 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2682 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2683 PetscFunctionReturn(0); 2684 } 2685 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2688 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2689 { 2690 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2691 PetscErrorCode ierr; 2692 Vec lvec1,bb1; 2693 2694 PetscFunctionBegin; 2695 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); 2696 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2697 2698 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2699 if (flag & SOR_ZERO_INITIAL_GUESS) { 2700 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2701 its--; 2702 } 2703 2704 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2705 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2706 while (its--) { 2707 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2708 2709 /* lower diagonal part: bb1 = bb - B^T*xx */ 2710 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2711 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2712 2713 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2714 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2715 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2716 2717 /* upper diagonal part: bb1 = bb1 - B*x */ 2718 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2719 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2720 2721 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2722 2723 /* diagonal sweep */ 2724 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2725 } 2726 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2727 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2728 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2729 PetscFunctionReturn(0); 2730 } 2731 2732 #undef __FUNCT__ 2733 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2734 /*@ 2735 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2736 CSR format the local rows. 2737 2738 Collective on MPI_Comm 2739 2740 Input Parameters: 2741 + comm - MPI communicator 2742 . bs - the block size, only a block size of 1 is supported 2743 . m - number of local rows (Cannot be PETSC_DECIDE) 2744 . n - This value should be the same as the local size used in creating the 2745 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2746 calculated if N is given) For square matrices n is almost always m. 2747 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2748 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2749 . i - row indices 2750 . j - column indices 2751 - a - matrix values 2752 2753 Output Parameter: 2754 . mat - the matrix 2755 2756 Level: intermediate 2757 2758 Notes: 2759 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2760 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2761 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2762 2763 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2764 2765 .keywords: matrix, aij, compressed row, sparse, parallel 2766 2767 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2768 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2769 @*/ 2770 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) 2771 { 2772 PetscErrorCode ierr; 2773 2774 2775 PetscFunctionBegin; 2776 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2777 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2778 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2779 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2780 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2781 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2782 PetscFunctionReturn(0); 2783 } 2784 2785 2786 #undef __FUNCT__ 2787 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2788 /*@C 2789 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2790 (the default parallel PETSc format). 2791 2792 Collective on MPI_Comm 2793 2794 Input Parameters: 2795 + B - the matrix 2796 . bs - the block size 2797 . i - the indices into j for the start of each local row (starts with zero) 2798 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2799 - v - optional values in the matrix 2800 2801 Level: developer 2802 2803 .keywords: matrix, aij, compressed row, sparse, parallel 2804 2805 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2806 @*/ 2807 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2808 { 2809 PetscErrorCode ierr; 2810 2811 PetscFunctionBegin; 2812 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2813 PetscFunctionReturn(0); 2814 } 2815 2816 #undef __FUNCT__ 2817 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPISBAIJ" 2818 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 2819 { 2820 PetscErrorCode ierr; 2821 PetscInt m,N,i,rstart,nnz,Ii,bs,cbs; 2822 PetscInt *indx; 2823 PetscScalar *values; 2824 2825 PetscFunctionBegin; 2826 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 2827 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 2828 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)inmat->data; 2829 PetscInt *dnz,*onz,sum,bs,cbs,mbs,Nbs; 2830 PetscInt *bindx,rmax=a->rmax,j; 2831 2832 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 2833 mbs = m/bs; Nbs = N/cbs; 2834 if (n == PETSC_DECIDE) { 2835 ierr = PetscSplitOwnership(comm,&n,&Nbs);CHKERRQ(ierr); 2836 } 2837 /* Check sum(n) = Nbs */ 2838 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2839 if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs); 2840 2841 ierr = MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2842 rstart -= mbs; 2843 2844 ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr); 2845 ierr = MatPreallocateInitialize(comm,mbs,n,dnz,onz);CHKERRQ(ierr); 2846 ierr = MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2847 for (i=0; i<mbs; i++) { 2848 ierr = MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */ 2849 nnz = nnz/bs; 2850 for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs; 2851 ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr); 2852 ierr = MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); 2853 } 2854 ierr = MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);CHKERRQ(ierr); 2855 ierr = PetscFree(bindx);CHKERRQ(ierr); 2856 2857 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 2858 ierr = MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2859 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 2860 ierr = MatSetType(*outmat,MATMPISBAIJ);CHKERRQ(ierr); 2861 ierr = MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr); 2862 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 2863 } 2864 2865 /* numeric phase */ 2866 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 2867 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 2868 2869 ierr = MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2870 for (i=0; i<m; i++) { 2871 ierr = MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2872 Ii = i + rstart; 2873 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 2874 ierr = MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2875 } 2876 ierr = MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);CHKERRQ(ierr); 2877 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2878 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2879 PetscFunctionReturn(0); 2880 } 2881