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; 661 662 /* Should this be the same type as mat? */ 663 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 664 if (!rank) { 665 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 666 } else { 667 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 668 } 669 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 670 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 671 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 672 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 673 674 /* copy over the A part */ 675 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 676 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 677 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 678 679 for (i=0; i<mbs; i++) { 680 rvals[0] = bs*(baij->rstartbs + i); 681 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 682 for (j=ai[i]; j<ai[i+1]; j++) { 683 col = (baij->cstartbs+aj[j])*bs; 684 for (k=0; k<bs; k++) { 685 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 686 col++; 687 a += bs; 688 } 689 } 690 } 691 /* copy over the B part */ 692 Bloc = (Mat_SeqBAIJ*)baij->B->data; 693 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 694 for (i=0; i<mbs; i++) { 695 696 rvals[0] = bs*(baij->rstartbs + i); 697 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 698 for (j=ai[i]; j<ai[i+1]; j++) { 699 col = baij->garray[aj[j]]*bs; 700 for (k=0; k<bs; k++) { 701 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 702 col++; 703 a += bs; 704 } 705 } 706 } 707 ierr = PetscFree(rvals);CHKERRQ(ierr); 708 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 709 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 710 /* 711 Everyone has to call to draw the matrix since the graphics waits are 712 synchronized across all processors that share the PetscDraw object 713 */ 714 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 715 if (!rank) { 716 ierr = MatView_SeqSBAIJ_ASCII(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 717 } 718 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 719 ierr = MatDestroy(&A);CHKERRQ(ierr); 720 } 721 PetscFunctionReturn(0); 722 } 723 724 #undef __FUNCT__ 725 #define __FUNCT__ "MatView_MPISBAIJ" 726 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 727 { 728 PetscErrorCode ierr; 729 PetscBool iascii,isdraw,issocket,isbinary; 730 731 PetscFunctionBegin; 732 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 733 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 734 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 735 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 736 if (iascii || isdraw || issocket || isbinary) { 737 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 738 } 739 PetscFunctionReturn(0); 740 } 741 742 #undef __FUNCT__ 743 #define __FUNCT__ "MatDestroy_MPISBAIJ" 744 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 745 { 746 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 747 PetscErrorCode ierr; 748 749 PetscFunctionBegin; 750 #if defined(PETSC_USE_LOG) 751 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 752 #endif 753 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 754 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 755 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 756 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 757 #if defined(PETSC_USE_CTABLE) 758 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 759 #else 760 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 761 #endif 762 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 763 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 764 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 765 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 766 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 767 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 768 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 770 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 771 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 772 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 773 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 774 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 775 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 776 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 777 #if defined(PETSC_USE_REAL_MAT_SINGLE) 778 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 779 #endif 780 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 781 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 782 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 783 ierr = PetscFree(mat->data);CHKERRQ(ierr); 784 785 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 786 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 787 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 788 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 789 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);CHKERRQ(ierr); 791 PetscFunctionReturn(0); 792 } 793 794 #undef __FUNCT__ 795 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 796 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 797 { 798 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 799 PetscErrorCode ierr; 800 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 801 PetscScalar *x,*from; 802 803 PetscFunctionBegin; 804 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 805 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 806 807 /* diagonal part */ 808 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 809 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 810 811 /* subdiagonal part */ 812 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 813 814 /* copy x into the vec slvec0 */ 815 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 816 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 817 818 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 819 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 823 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 824 /* supperdiagonal part */ 825 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 826 PetscFunctionReturn(0); 827 } 828 829 #undef __FUNCT__ 830 #define __FUNCT__ "MatMult_MPISBAIJ" 831 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 832 { 833 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 834 PetscErrorCode ierr; 835 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 836 PetscScalar *x,*from; 837 838 PetscFunctionBegin; 839 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 840 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 841 842 /* diagonal part */ 843 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 844 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 845 846 /* subdiagonal part */ 847 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 848 849 /* copy x into the vec slvec0 */ 850 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 851 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 852 853 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 854 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 855 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 856 857 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 858 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 859 /* supperdiagonal part */ 860 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 861 PetscFunctionReturn(0); 862 } 863 864 #undef __FUNCT__ 865 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 866 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 867 { 868 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 869 PetscErrorCode ierr; 870 PetscInt nt; 871 872 PetscFunctionBegin; 873 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 874 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 875 876 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 877 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 878 879 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 880 /* do diagonal part */ 881 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 882 /* do supperdiagonal part */ 883 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 884 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 885 /* do subdiagonal part */ 886 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 887 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 888 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 889 PetscFunctionReturn(0); 890 } 891 892 #undef __FUNCT__ 893 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 894 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 895 { 896 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 897 PetscErrorCode ierr; 898 PetscInt mbs=a->mbs,bs=A->rmap->bs; 899 PetscScalar *x,*from,zero=0.0; 900 901 PetscFunctionBegin; 902 /* 903 PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n"); 904 PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT); 905 */ 906 /* diagonal part */ 907 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 908 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 909 910 /* subdiagonal part */ 911 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 912 913 /* copy x into the vec slvec0 */ 914 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 915 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 916 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 917 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 918 919 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 920 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 921 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 922 923 /* supperdiagonal part */ 924 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 925 PetscFunctionReturn(0); 926 } 927 928 #undef __FUNCT__ 929 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 930 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 931 { 932 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 933 PetscErrorCode ierr; 934 935 PetscFunctionBegin; 936 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 937 /* do diagonal part */ 938 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 939 /* do supperdiagonal part */ 940 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 941 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 942 943 /* do subdiagonal part */ 944 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 945 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 946 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 947 PetscFunctionReturn(0); 948 } 949 950 /* 951 This only works correctly for square matrices where the subblock A->A is the 952 diagonal block 953 */ 954 #undef __FUNCT__ 955 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 956 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 957 { 958 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 959 PetscErrorCode ierr; 960 961 PetscFunctionBegin; 962 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 963 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 964 PetscFunctionReturn(0); 965 } 966 967 #undef __FUNCT__ 968 #define __FUNCT__ "MatScale_MPISBAIJ" 969 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 970 { 971 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 972 PetscErrorCode ierr; 973 974 PetscFunctionBegin; 975 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 976 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 977 PetscFunctionReturn(0); 978 } 979 980 #undef __FUNCT__ 981 #define __FUNCT__ "MatGetRow_MPISBAIJ" 982 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 983 { 984 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 985 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 986 PetscErrorCode ierr; 987 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 988 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 989 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 990 991 PetscFunctionBegin; 992 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 993 mat->getrowactive = PETSC_TRUE; 994 995 if (!mat->rowvalues && (idx || v)) { 996 /* 997 allocate enough space to hold information from the longest row. 998 */ 999 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1000 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1001 PetscInt max = 1,mbs = mat->mbs,tmp; 1002 for (i=0; i<mbs; i++) { 1003 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1004 if (max < tmp) max = tmp; 1005 } 1006 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1007 } 1008 1009 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1010 lrow = row - brstart; /* local row index */ 1011 1012 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1013 if (!v) {pvA = 0; pvB = 0;} 1014 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1015 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1016 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1017 nztot = nzA + nzB; 1018 1019 cmap = mat->garray; 1020 if (v || idx) { 1021 if (nztot) { 1022 /* Sort by increasing column numbers, assuming A and B already sorted */ 1023 PetscInt imark = -1; 1024 if (v) { 1025 *v = v_p = mat->rowvalues; 1026 for (i=0; i<nzB; i++) { 1027 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1028 else break; 1029 } 1030 imark = i; 1031 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1032 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1033 } 1034 if (idx) { 1035 *idx = idx_p = mat->rowindices; 1036 if (imark > -1) { 1037 for (i=0; i<imark; i++) { 1038 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1039 } 1040 } else { 1041 for (i=0; i<nzB; i++) { 1042 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1043 else break; 1044 } 1045 imark = i; 1046 } 1047 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1048 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1049 } 1050 } else { 1051 if (idx) *idx = 0; 1052 if (v) *v = 0; 1053 } 1054 } 1055 *nz = nztot; 1056 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1057 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1058 PetscFunctionReturn(0); 1059 } 1060 1061 #undef __FUNCT__ 1062 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1063 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1064 { 1065 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1066 1067 PetscFunctionBegin; 1068 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1069 baij->getrowactive = PETSC_FALSE; 1070 PetscFunctionReturn(0); 1071 } 1072 1073 #undef __FUNCT__ 1074 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1075 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1076 { 1077 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1078 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1079 1080 PetscFunctionBegin; 1081 aA->getrow_utriangular = PETSC_TRUE; 1082 PetscFunctionReturn(0); 1083 } 1084 #undef __FUNCT__ 1085 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1086 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1087 { 1088 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1089 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1090 1091 PetscFunctionBegin; 1092 aA->getrow_utriangular = PETSC_FALSE; 1093 PetscFunctionReturn(0); 1094 } 1095 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1098 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1099 { 1100 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1101 PetscErrorCode ierr; 1102 1103 PetscFunctionBegin; 1104 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1105 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1106 PetscFunctionReturn(0); 1107 } 1108 1109 #undef __FUNCT__ 1110 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1111 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1112 { 1113 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1114 PetscErrorCode ierr; 1115 1116 PetscFunctionBegin; 1117 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1118 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1119 PetscFunctionReturn(0); 1120 } 1121 1122 #undef __FUNCT__ 1123 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1124 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1125 { 1126 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1127 PetscErrorCode ierr; 1128 1129 PetscFunctionBegin; 1130 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1131 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1132 PetscFunctionReturn(0); 1133 } 1134 1135 #undef __FUNCT__ 1136 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1137 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1138 { 1139 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1140 Mat A = a->A,B = a->B; 1141 PetscErrorCode ierr; 1142 PetscReal isend[5],irecv[5]; 1143 1144 PetscFunctionBegin; 1145 info->block_size = (PetscReal)matin->rmap->bs; 1146 1147 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1148 1149 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1150 isend[3] = info->memory; isend[4] = info->mallocs; 1151 1152 ierr = MatGetInfo(B,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 if (flag == MAT_LOCAL) { 1157 info->nz_used = isend[0]; 1158 info->nz_allocated = isend[1]; 1159 info->nz_unneeded = isend[2]; 1160 info->memory = isend[3]; 1161 info->mallocs = isend[4]; 1162 } else if (flag == MAT_GLOBAL_MAX) { 1163 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1164 1165 info->nz_used = irecv[0]; 1166 info->nz_allocated = irecv[1]; 1167 info->nz_unneeded = irecv[2]; 1168 info->memory = irecv[3]; 1169 info->mallocs = irecv[4]; 1170 } else if (flag == MAT_GLOBAL_SUM) { 1171 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1172 1173 info->nz_used = irecv[0]; 1174 info->nz_allocated = irecv[1]; 1175 info->nz_unneeded = irecv[2]; 1176 info->memory = irecv[3]; 1177 info->mallocs = irecv[4]; 1178 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1179 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1180 info->fill_ratio_needed = 0; 1181 info->factor_mallocs = 0; 1182 PetscFunctionReturn(0); 1183 } 1184 1185 #undef __FUNCT__ 1186 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1187 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1188 { 1189 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1190 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1191 PetscErrorCode ierr; 1192 1193 PetscFunctionBegin; 1194 switch (op) { 1195 case MAT_NEW_NONZERO_LOCATIONS: 1196 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1197 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1198 case MAT_KEEP_NONZERO_PATTERN: 1199 case MAT_NEW_NONZERO_LOCATION_ERR: 1200 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1201 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1202 break; 1203 case MAT_ROW_ORIENTED: 1204 a->roworiented = flg; 1205 1206 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1207 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1208 break; 1209 case MAT_NEW_DIAGONALS: 1210 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1211 break; 1212 case MAT_IGNORE_OFF_PROC_ENTRIES: 1213 a->donotstash = flg; 1214 break; 1215 case MAT_USE_HASH_TABLE: 1216 a->ht_flag = flg; 1217 break; 1218 case MAT_HERMITIAN: 1219 if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first"); 1220 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1221 1222 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1223 break; 1224 case MAT_SPD: 1225 A->spd_set = PETSC_TRUE; 1226 A->spd = flg; 1227 if (flg) { 1228 A->symmetric = PETSC_TRUE; 1229 A->structurally_symmetric = PETSC_TRUE; 1230 A->symmetric_set = PETSC_TRUE; 1231 A->structurally_symmetric_set = PETSC_TRUE; 1232 } 1233 break; 1234 case MAT_SYMMETRIC: 1235 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1236 break; 1237 case MAT_STRUCTURALLY_SYMMETRIC: 1238 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1239 break; 1240 case MAT_SYMMETRY_ETERNAL: 1241 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1242 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1243 break; 1244 case MAT_IGNORE_LOWER_TRIANGULAR: 1245 aA->ignore_ltriangular = flg; 1246 break; 1247 case MAT_ERROR_LOWER_TRIANGULAR: 1248 aA->ignore_ltriangular = flg; 1249 break; 1250 case MAT_GETROW_UPPERTRIANGULAR: 1251 aA->getrow_utriangular = flg; 1252 break; 1253 default: 1254 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1255 } 1256 PetscFunctionReturn(0); 1257 } 1258 1259 #undef __FUNCT__ 1260 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1261 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1262 { 1263 PetscErrorCode ierr; 1264 1265 PetscFunctionBegin; 1266 if (MAT_INITIAL_MATRIX || *B != A) { 1267 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1268 } 1269 PetscFunctionReturn(0); 1270 } 1271 1272 #undef __FUNCT__ 1273 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1274 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1275 { 1276 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1277 Mat a = baij->A, b=baij->B; 1278 PetscErrorCode ierr; 1279 PetscInt nv,m,n; 1280 PetscBool flg; 1281 1282 PetscFunctionBegin; 1283 if (ll != rr) { 1284 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1285 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1286 } 1287 if (!ll) PetscFunctionReturn(0); 1288 1289 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1290 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1291 1292 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1293 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1294 1295 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1296 1297 /* left diagonalscale the off-diagonal part */ 1298 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1299 1300 /* scale the diagonal part */ 1301 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1302 1303 /* right diagonalscale the off-diagonal part */ 1304 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1305 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1306 PetscFunctionReturn(0); 1307 } 1308 1309 #undef __FUNCT__ 1310 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1311 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1312 { 1313 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1314 PetscErrorCode ierr; 1315 1316 PetscFunctionBegin; 1317 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1318 PetscFunctionReturn(0); 1319 } 1320 1321 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*); 1322 1323 #undef __FUNCT__ 1324 #define __FUNCT__ "MatEqual_MPISBAIJ" 1325 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1326 { 1327 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1328 Mat a,b,c,d; 1329 PetscBool flg; 1330 PetscErrorCode ierr; 1331 1332 PetscFunctionBegin; 1333 a = matA->A; b = matA->B; 1334 c = matB->A; d = matB->B; 1335 1336 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1337 if (flg) { 1338 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1339 } 1340 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1341 PetscFunctionReturn(0); 1342 } 1343 1344 #undef __FUNCT__ 1345 #define __FUNCT__ "MatCopy_MPISBAIJ" 1346 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1347 { 1348 PetscErrorCode ierr; 1349 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1350 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data; 1351 1352 PetscFunctionBegin; 1353 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1354 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1355 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1356 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1357 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1358 } else { 1359 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1360 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1361 } 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNCT__ 1366 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1367 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1368 { 1369 PetscErrorCode ierr; 1370 1371 PetscFunctionBegin; 1372 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1373 PetscFunctionReturn(0); 1374 } 1375 1376 #undef __FUNCT__ 1377 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1378 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1379 { 1380 PetscErrorCode ierr; 1381 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data; 1382 PetscBLASInt bnz,one=1; 1383 Mat_SeqSBAIJ *xa,*ya; 1384 Mat_SeqBAIJ *xb,*yb; 1385 1386 PetscFunctionBegin; 1387 if (str == SAME_NONZERO_PATTERN) { 1388 PetscScalar alpha = a; 1389 xa = (Mat_SeqSBAIJ*)xx->A->data; 1390 ya = (Mat_SeqSBAIJ*)yy->A->data; 1391 ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr); 1392 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one)); 1393 xb = (Mat_SeqBAIJ*)xx->B->data; 1394 yb = (Mat_SeqBAIJ*)yy->B->data; 1395 ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr); 1396 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one)); 1397 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 1398 } else { 1399 Mat B; 1400 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 1401 if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size"); 1402 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1403 ierr = MatGetRowUpperTriangular(Y);CHKERRQ(ierr); 1404 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 1405 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 1406 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 1407 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 1408 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 1409 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 1410 ierr = MatSetType(B,MATMPISBAIJ);CHKERRQ(ierr); 1411 ierr = MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 1412 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 1413 ierr = MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 1414 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 1415 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 1416 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 1417 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 1418 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1419 ierr = MatRestoreRowUpperTriangular(Y);CHKERRQ(ierr); 1420 } 1421 PetscFunctionReturn(0); 1422 } 1423 1424 #undef __FUNCT__ 1425 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1426 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1427 { 1428 PetscErrorCode ierr; 1429 PetscInt i; 1430 PetscBool flg; 1431 1432 PetscFunctionBegin; 1433 for (i=0; i<n; i++) { 1434 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1435 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1436 } 1437 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 1442 /* -------------------------------------------------------------------*/ 1443 static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ, 1444 MatGetRow_MPISBAIJ, 1445 MatRestoreRow_MPISBAIJ, 1446 MatMult_MPISBAIJ, 1447 /* 4*/ MatMultAdd_MPISBAIJ, 1448 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1449 MatMultAdd_MPISBAIJ, 1450 0, 1451 0, 1452 0, 1453 /* 10*/ 0, 1454 0, 1455 0, 1456 MatSOR_MPISBAIJ, 1457 MatTranspose_MPISBAIJ, 1458 /* 15*/ MatGetInfo_MPISBAIJ, 1459 MatEqual_MPISBAIJ, 1460 MatGetDiagonal_MPISBAIJ, 1461 MatDiagonalScale_MPISBAIJ, 1462 MatNorm_MPISBAIJ, 1463 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1464 MatAssemblyEnd_MPISBAIJ, 1465 MatSetOption_MPISBAIJ, 1466 MatZeroEntries_MPISBAIJ, 1467 /* 24*/ 0, 1468 0, 1469 0, 1470 0, 1471 0, 1472 /* 29*/ MatSetUp_MPISBAIJ, 1473 0, 1474 0, 1475 0, 1476 0, 1477 /* 34*/ MatDuplicate_MPISBAIJ, 1478 0, 1479 0, 1480 0, 1481 0, 1482 /* 39*/ MatAXPY_MPISBAIJ, 1483 MatGetSubMatrices_MPISBAIJ, 1484 MatIncreaseOverlap_MPISBAIJ, 1485 MatGetValues_MPISBAIJ, 1486 MatCopy_MPISBAIJ, 1487 /* 44*/ 0, 1488 MatScale_MPISBAIJ, 1489 0, 1490 0, 1491 0, 1492 /* 49*/ 0, 1493 0, 1494 0, 1495 0, 1496 0, 1497 /* 54*/ 0, 1498 0, 1499 MatSetUnfactored_MPISBAIJ, 1500 0, 1501 MatSetValuesBlocked_MPISBAIJ, 1502 /* 59*/ 0, 1503 0, 1504 0, 1505 0, 1506 0, 1507 /* 64*/ 0, 1508 0, 1509 0, 1510 0, 1511 0, 1512 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1513 0, 1514 0, 1515 0, 1516 0, 1517 /* 74*/ 0, 1518 0, 1519 0, 1520 0, 1521 0, 1522 /* 79*/ 0, 1523 0, 1524 0, 1525 0, 1526 MatLoad_MPISBAIJ, 1527 /* 84*/ 0, 1528 0, 1529 0, 1530 0, 1531 0, 1532 /* 89*/ 0, 1533 0, 1534 0, 1535 0, 1536 0, 1537 /* 94*/ 0, 1538 0, 1539 0, 1540 0, 1541 0, 1542 /* 99*/ 0, 1543 0, 1544 0, 1545 0, 1546 0, 1547 /*104*/ 0, 1548 MatRealPart_MPISBAIJ, 1549 MatImaginaryPart_MPISBAIJ, 1550 MatGetRowUpperTriangular_MPISBAIJ, 1551 MatRestoreRowUpperTriangular_MPISBAIJ, 1552 /*109*/ 0, 1553 0, 1554 0, 1555 0, 1556 0, 1557 /*114*/ 0, 1558 0, 1559 0, 1560 0, 1561 0, 1562 /*119*/ 0, 1563 0, 1564 0, 1565 0, 1566 0, 1567 /*124*/ 0, 1568 0, 1569 0, 1570 0, 1571 0, 1572 /*129*/ 0, 1573 0, 1574 0, 1575 0, 1576 0, 1577 /*134*/ 0, 1578 0, 1579 0, 1580 0, 1581 0, 1582 /*139*/ 0, 1583 0, 1584 0 1585 }; 1586 1587 1588 #undef __FUNCT__ 1589 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1590 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1591 { 1592 PetscFunctionBegin; 1593 *a = ((Mat_MPISBAIJ*)A->data)->A; 1594 PetscFunctionReturn(0); 1595 } 1596 1597 #undef __FUNCT__ 1598 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1599 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 1600 { 1601 Mat_MPISBAIJ *b; 1602 PetscErrorCode ierr; 1603 PetscInt i,mbs,Mbs; 1604 1605 PetscFunctionBegin; 1606 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 1607 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1608 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1609 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1610 1611 b = (Mat_MPISBAIJ*)B->data; 1612 mbs = B->rmap->n/bs; 1613 Mbs = B->rmap->N/bs; 1614 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); 1615 1616 B->rmap->bs = bs; 1617 b->bs2 = bs*bs; 1618 b->mbs = mbs; 1619 b->nbs = mbs; 1620 b->Mbs = Mbs; 1621 b->Nbs = Mbs; 1622 1623 for (i=0; i<=b->size; i++) { 1624 b->rangebs[i] = B->rmap->range[i]/bs; 1625 } 1626 b->rstartbs = B->rmap->rstart/bs; 1627 b->rendbs = B->rmap->rend/bs; 1628 1629 b->cstartbs = B->cmap->rstart/bs; 1630 b->cendbs = B->cmap->rend/bs; 1631 1632 if (!B->preallocated) { 1633 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1634 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1635 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1636 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 1637 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1638 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1639 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1640 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 1641 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 1642 } 1643 1644 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1645 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1646 1647 B->preallocated = PETSC_TRUE; 1648 PetscFunctionReturn(0); 1649 } 1650 1651 #undef __FUNCT__ 1652 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1653 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1654 { 1655 PetscInt m,rstart,cstart,cend; 1656 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1657 const PetscInt *JJ =0; 1658 PetscScalar *values=0; 1659 PetscErrorCode ierr; 1660 1661 PetscFunctionBegin; 1662 if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1663 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1664 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1665 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1666 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1667 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1668 m = B->rmap->n/bs; 1669 rstart = B->rmap->rstart/bs; 1670 cstart = B->cmap->rstart/bs; 1671 cend = B->cmap->rend/bs; 1672 1673 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1674 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 1675 for (i=0; i<m; i++) { 1676 nz = ii[i+1] - ii[i]; 1677 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1678 nz_max = PetscMax(nz_max,nz); 1679 JJ = jj + ii[i]; 1680 for (j=0; j<nz; j++) { 1681 if (*JJ >= cstart) break; 1682 JJ++; 1683 } 1684 d = 0; 1685 for (; j<nz; j++) { 1686 if (*JJ++ >= cend) break; 1687 d++; 1688 } 1689 d_nnz[i] = d; 1690 o_nnz[i] = nz - d; 1691 } 1692 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1693 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1694 1695 values = (PetscScalar*)V; 1696 if (!values) { 1697 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 1698 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1699 } 1700 for (i=0; i<m; i++) { 1701 PetscInt row = i + rstart; 1702 PetscInt ncols = ii[i+1] - ii[i]; 1703 const PetscInt *icols = jj + ii[i]; 1704 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1705 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1706 } 1707 1708 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1709 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1710 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1711 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1712 PetscFunctionReturn(0); 1713 } 1714 1715 #if defined(PETSC_HAVE_MUMPS) 1716 PETSC_EXTERN PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*); 1717 #endif 1718 #if defined(PETSC_HAVE_PASTIX) 1719 PETSC_EXTERN PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1720 #endif 1721 1722 /*MC 1723 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1724 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1725 the matrix is stored. 1726 1727 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1728 can call MatSetOption(Mat, MAT_HERMITIAN); 1729 1730 Options Database Keys: 1731 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1732 1733 Level: beginner 1734 1735 .seealso: MatCreateMPISBAIJ 1736 M*/ 1737 1738 PETSC_EXTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1739 1740 #undef __FUNCT__ 1741 #define __FUNCT__ "MatCreate_MPISBAIJ" 1742 PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1743 { 1744 Mat_MPISBAIJ *b; 1745 PetscErrorCode ierr; 1746 PetscBool flg; 1747 1748 PetscFunctionBegin; 1749 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 1750 B->data = (void*)b; 1751 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1752 1753 B->ops->destroy = MatDestroy_MPISBAIJ; 1754 B->ops->view = MatView_MPISBAIJ; 1755 B->assembled = PETSC_FALSE; 1756 B->insertmode = NOT_SET_VALUES; 1757 1758 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 1759 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 1760 1761 /* build local table of row and column ownerships */ 1762 ierr = PetscMalloc1((b->size+2),&b->rangebs);CHKERRQ(ierr); 1763 1764 /* build cache for off array entries formed */ 1765 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 1766 1767 b->donotstash = PETSC_FALSE; 1768 b->colmap = NULL; 1769 b->garray = NULL; 1770 b->roworiented = PETSC_TRUE; 1771 1772 /* stuff used in block assembly */ 1773 b->barray = 0; 1774 1775 /* stuff used for matrix vector multiply */ 1776 b->lvec = 0; 1777 b->Mvctx = 0; 1778 b->slvec0 = 0; 1779 b->slvec0b = 0; 1780 b->slvec1 = 0; 1781 b->slvec1a = 0; 1782 b->slvec1b = 0; 1783 b->sMvctx = 0; 1784 1785 /* stuff for MatGetRow() */ 1786 b->rowindices = 0; 1787 b->rowvalues = 0; 1788 b->getrowactive = PETSC_FALSE; 1789 1790 /* hash table stuff */ 1791 b->ht = 0; 1792 b->hd = 0; 1793 b->ht_size = 0; 1794 b->ht_flag = PETSC_FALSE; 1795 b->ht_fact = 0; 1796 b->ht_total_ct = 0; 1797 b->ht_insert_ct = 0; 1798 1799 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1800 b->ijonly = PETSC_FALSE; 1801 1802 b->in_loc = 0; 1803 b->v_loc = 0; 1804 b->n_loc = 0; 1805 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1806 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 1807 if (flg) { 1808 PetscReal fact = 1.39; 1809 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1810 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 1811 if (fact <= 1.0) fact = 1.39; 1812 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1813 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1814 } 1815 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1816 1817 #if defined(PETSC_HAVE_PASTIX) 1818 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1819 #endif 1820 #if defined(PETSC_HAVE_MUMPS) 1821 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 1822 #endif 1823 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1824 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1825 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1826 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1827 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1828 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1829 1830 B->symmetric = PETSC_TRUE; 1831 B->structurally_symmetric = PETSC_TRUE; 1832 B->symmetric_set = PETSC_TRUE; 1833 B->structurally_symmetric_set = PETSC_TRUE; 1834 1835 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1836 PetscFunctionReturn(0); 1837 } 1838 1839 /*MC 1840 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1841 1842 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1843 and MATMPISBAIJ otherwise. 1844 1845 Options Database Keys: 1846 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1847 1848 Level: beginner 1849 1850 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1851 M*/ 1852 1853 #undef __FUNCT__ 1854 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1855 /*@C 1856 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1857 the user should preallocate the matrix storage by setting the parameters 1858 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1859 performance can be increased by more than a factor of 50. 1860 1861 Collective on Mat 1862 1863 Input Parameters: 1864 + B - the matrix 1865 . bs - size of blockk 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 blockk 1966 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1967 This value should be the same as the local size used in creating the 1968 y vector for the matrix-vector product y = Ax. 1969 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1970 This value should be the same as the local size used in creating the 1971 x vector for the matrix-vector product y = Ax. 1972 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1973 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1974 . d_nz - number of block nonzeros per block row in diagonal portion of local 1975 submatrix (same for all local rows) 1976 . d_nnz - array containing the number of block nonzeros in the various block rows 1977 in the upper triangular portion of the in diagonal portion of the local 1978 (possibly different for each block block row) or NULL. 1979 If you plan to factor the matrix you must leave room for the diagonal entry and 1980 set its value even if it is zero. 1981 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1982 submatrix (same for all local rows). 1983 - o_nnz - array containing the number of nonzeros in the various block rows of the 1984 off-diagonal portion of the local submatrix (possibly different for 1985 each block row) or NULL. 1986 1987 Output Parameter: 1988 . A - the matrix 1989 1990 Options Database Keys: 1991 . -mat_no_unroll - uses code that does not unroll the loops in the 1992 block calculations (much slower) 1993 . -mat_block_size - size of the blocks to use 1994 . -mat_mpi - use the parallel matrix data structures even on one processor 1995 (defaults to using SeqBAIJ format on one processor) 1996 1997 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1998 MatXXXXSetPreallocation() paradgm instead of this routine directly. 1999 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2000 2001 Notes: 2002 The number of rows and columns must be divisible by blocksize. 2003 This matrix type does not support complex Hermitian operation. 2004 2005 The user MUST specify either the local or global matrix dimensions 2006 (possibly both). 2007 2008 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2009 than it must be used on all processors that share the object for that argument. 2010 2011 If the *_nnz parameter is given then the *_nz parameter is ignored 2012 2013 Storage Information: 2014 For a square global matrix we define each processor's diagonal portion 2015 to be its local rows and the corresponding columns (a square submatrix); 2016 each processor's off-diagonal portion encompasses the remainder of the 2017 local matrix (a rectangular submatrix). 2018 2019 The user can specify preallocated storage for the diagonal part of 2020 the local submatrix with either d_nz or d_nnz (not both). Set 2021 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 2022 memory allocation. Likewise, specify preallocated storage for the 2023 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2024 2025 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2026 the figure below we depict these three local rows and all columns (0-11). 2027 2028 .vb 2029 0 1 2 3 4 5 6 7 8 9 10 11 2030 -------------------------- 2031 row 3 |. . . d d d o o o o o o 2032 row 4 |. . . d d d o o o o o o 2033 row 5 |. . . d d d o o o o o o 2034 -------------------------- 2035 .ve 2036 2037 Thus, any entries in the d locations are stored in the d (diagonal) 2038 submatrix, and any entries in the o locations are stored in the 2039 o (off-diagonal) submatrix. Note that the d matrix is stored in 2040 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2041 2042 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2043 plus the diagonal part of the d matrix, 2044 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2045 In general, for PDE problems in which most nonzeros are near the diagonal, 2046 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2047 or you will get TERRIBLE performance; see the users' manual chapter on 2048 matrices. 2049 2050 Level: intermediate 2051 2052 .keywords: matrix, block, aij, compressed row, sparse, parallel 2053 2054 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2055 @*/ 2056 2057 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) 2058 { 2059 PetscErrorCode ierr; 2060 PetscMPIInt size; 2061 2062 PetscFunctionBegin; 2063 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2064 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2065 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2066 if (size > 1) { 2067 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2068 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2069 } else { 2070 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2071 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 2077 #undef __FUNCT__ 2078 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2079 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2080 { 2081 Mat mat; 2082 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2083 PetscErrorCode ierr; 2084 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2085 PetscScalar *array; 2086 2087 PetscFunctionBegin; 2088 *newmat = 0; 2089 2090 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2091 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2092 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2093 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2094 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2095 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2096 2097 mat->factortype = matin->factortype; 2098 mat->preallocated = PETSC_TRUE; 2099 mat->assembled = PETSC_TRUE; 2100 mat->insertmode = NOT_SET_VALUES; 2101 2102 a = (Mat_MPISBAIJ*)mat->data; 2103 a->bs2 = oldmat->bs2; 2104 a->mbs = oldmat->mbs; 2105 a->nbs = oldmat->nbs; 2106 a->Mbs = oldmat->Mbs; 2107 a->Nbs = oldmat->Nbs; 2108 2109 2110 a->size = oldmat->size; 2111 a->rank = oldmat->rank; 2112 a->donotstash = oldmat->donotstash; 2113 a->roworiented = oldmat->roworiented; 2114 a->rowindices = 0; 2115 a->rowvalues = 0; 2116 a->getrowactive = PETSC_FALSE; 2117 a->barray = 0; 2118 a->rstartbs = oldmat->rstartbs; 2119 a->rendbs = oldmat->rendbs; 2120 a->cstartbs = oldmat->cstartbs; 2121 a->cendbs = oldmat->cendbs; 2122 2123 /* hash table stuff */ 2124 a->ht = 0; 2125 a->hd = 0; 2126 a->ht_size = 0; 2127 a->ht_flag = oldmat->ht_flag; 2128 a->ht_fact = oldmat->ht_fact; 2129 a->ht_total_ct = 0; 2130 a->ht_insert_ct = 0; 2131 2132 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2133 if (oldmat->colmap) { 2134 #if defined(PETSC_USE_CTABLE) 2135 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2136 #else 2137 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 2138 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2139 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2140 #endif 2141 } else a->colmap = 0; 2142 2143 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2144 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 2145 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2146 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2147 } else a->garray = 0; 2148 2149 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2150 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2151 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2152 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2153 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2154 2155 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2156 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2157 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2158 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2159 2160 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2161 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2162 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2163 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2164 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2165 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2166 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2167 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2168 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr); 2169 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr); 2170 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);CHKERRQ(ierr); 2171 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);CHKERRQ(ierr); 2172 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);CHKERRQ(ierr); 2173 2174 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2175 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2176 a->sMvctx = oldmat->sMvctx; 2177 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);CHKERRQ(ierr); 2178 2179 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2180 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2181 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2182 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2183 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2184 *newmat = mat; 2185 PetscFunctionReturn(0); 2186 } 2187 2188 #undef __FUNCT__ 2189 #define __FUNCT__ "MatLoad_MPISBAIJ" 2190 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2191 { 2192 PetscErrorCode ierr; 2193 PetscInt i,nz,j,rstart,rend; 2194 PetscScalar *vals,*buf; 2195 MPI_Comm comm; 2196 MPI_Status status; 2197 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2198 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2199 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2200 PetscInt bs = newmat->rmap->bs,Mbs,mbs,extra_rows; 2201 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2202 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2203 int fd; 2204 2205 PetscFunctionBegin; 2206 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2207 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2208 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2209 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2210 if (bs < 0) bs = 1; 2211 2212 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2213 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2214 if (!rank) { 2215 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2216 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2217 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2218 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2219 } 2220 2221 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2222 2223 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2224 M = header[1]; 2225 N = header[2]; 2226 2227 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2228 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2229 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2230 2231 /* If global sizes are set, check if they are consistent with that given in the file */ 2232 if (sizesset) { 2233 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2234 } 2235 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); 2236 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); 2237 2238 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2239 2240 /* 2241 This code adds extra rows to make sure the number of rows is 2242 divisible by the blocksize 2243 */ 2244 Mbs = M/bs; 2245 extra_rows = bs - M + bs*(Mbs); 2246 if (extra_rows == bs) extra_rows = 0; 2247 else Mbs++; 2248 if (extra_rows &&!rank) { 2249 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2250 } 2251 2252 /* determine ownership of all rows */ 2253 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2254 mbs = Mbs/size + ((Mbs % size) > rank); 2255 m = mbs*bs; 2256 } else { /* User Set */ 2257 m = newmat->rmap->n; 2258 mbs = m/bs; 2259 } 2260 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 2261 ierr = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr); 2262 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2263 rowners[0] = 0; 2264 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2265 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2266 rstart = rowners[rank]; 2267 rend = rowners[rank+1]; 2268 2269 /* distribute row lengths to all processors */ 2270 ierr = PetscMalloc1((rend-rstart)*bs,&locrowlens);CHKERRQ(ierr); 2271 if (!rank) { 2272 ierr = PetscMalloc1((M+extra_rows),&rowlengths);CHKERRQ(ierr); 2273 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2274 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2275 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 2276 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2277 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2278 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2279 } else { 2280 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2281 } 2282 2283 if (!rank) { /* procs[0] */ 2284 /* calculate the number of nonzeros on each processor */ 2285 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 2286 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2287 for (i=0; i<size; i++) { 2288 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2289 procsnz[i] += rowlengths[j]; 2290 } 2291 } 2292 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2293 2294 /* determine max buffer needed and allocate it */ 2295 maxnz = 0; 2296 for (i=0; i<size; i++) { 2297 maxnz = PetscMax(maxnz,procsnz[i]); 2298 } 2299 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2300 2301 /* read in my part of the matrix column indices */ 2302 nz = procsnz[0]; 2303 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2304 mycols = ibuf; 2305 if (size == 1) nz -= extra_rows; 2306 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2307 if (size == 1) { 2308 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 2309 } 2310 2311 /* read in every ones (except the last) and ship off */ 2312 for (i=1; i<size-1; i++) { 2313 nz = procsnz[i]; 2314 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2315 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2316 } 2317 /* read in the stuff for the last proc */ 2318 if (size != 1) { 2319 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2320 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2321 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2322 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2323 } 2324 ierr = PetscFree(cols);CHKERRQ(ierr); 2325 } else { /* procs[i], i>0 */ 2326 /* determine buffer space needed for message */ 2327 nz = 0; 2328 for (i=0; i<m; i++) nz += locrowlens[i]; 2329 ierr = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr); 2330 mycols = ibuf; 2331 /* receive message of column indices*/ 2332 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2333 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2334 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2335 } 2336 2337 /* loop over local rows, determining number of off diagonal entries */ 2338 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 2339 ierr = PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 2340 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2341 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2342 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2343 rowcount = 0; 2344 nzcount = 0; 2345 for (i=0; i<mbs; i++) { 2346 dcount = 0; 2347 odcount = 0; 2348 for (j=0; j<bs; j++) { 2349 kmax = locrowlens[rowcount]; 2350 for (k=0; k<kmax; k++) { 2351 tmp = mycols[nzcount++]/bs; /* block col. index */ 2352 if (!mask[tmp]) { 2353 mask[tmp] = 1; 2354 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2355 else masked1[dcount++] = tmp; /* entry in diag portion */ 2356 } 2357 } 2358 rowcount++; 2359 } 2360 2361 dlens[i] = dcount; /* d_nzz[i] */ 2362 odlens[i] = odcount; /* o_nzz[i] */ 2363 2364 /* zero out the mask elements we set */ 2365 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2366 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2367 } 2368 if (!sizesset) { 2369 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2370 } 2371 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2372 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2373 2374 if (!rank) { 2375 ierr = PetscMalloc1(maxnz,&buf);CHKERRQ(ierr); 2376 /* read in my part of the matrix numerical values */ 2377 nz = procsnz[0]; 2378 vals = buf; 2379 mycols = ibuf; 2380 if (size == 1) nz -= extra_rows; 2381 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2382 if (size == 1) { 2383 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 2384 } 2385 2386 /* insert into matrix */ 2387 jj = rstart*bs; 2388 for (i=0; i<m; i++) { 2389 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2390 mycols += locrowlens[i]; 2391 vals += locrowlens[i]; 2392 jj++; 2393 } 2394 2395 /* read in other processors (except the last one) and ship out */ 2396 for (i=1; i<size-1; i++) { 2397 nz = procsnz[i]; 2398 vals = buf; 2399 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2400 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2401 } 2402 /* the last proc */ 2403 if (size != 1) { 2404 nz = procsnz[i] - extra_rows; 2405 vals = buf; 2406 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2407 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2408 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2409 } 2410 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2411 2412 } else { 2413 /* receive numeric values */ 2414 ierr = PetscMalloc1(nz,&buf);CHKERRQ(ierr); 2415 2416 /* receive message of values*/ 2417 vals = buf; 2418 mycols = ibuf; 2419 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2420 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2421 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2422 2423 /* insert into matrix */ 2424 jj = rstart*bs; 2425 for (i=0; i<m; i++) { 2426 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2427 mycols += locrowlens[i]; 2428 vals += locrowlens[i]; 2429 jj++; 2430 } 2431 } 2432 2433 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2434 ierr = PetscFree(buf);CHKERRQ(ierr); 2435 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2436 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2437 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2438 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2439 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2440 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2441 PetscFunctionReturn(0); 2442 } 2443 2444 #undef __FUNCT__ 2445 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2446 /*XXXXX@ 2447 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2448 2449 Input Parameters: 2450 . mat - the matrix 2451 . fact - factor 2452 2453 Not Collective on Mat, each process can have a different hash factor 2454 2455 Level: advanced 2456 2457 Notes: 2458 This can also be set by the command line option: -mat_use_hash_table fact 2459 2460 .keywords: matrix, hashtable, factor, HT 2461 2462 .seealso: MatSetOption() 2463 @XXXXX*/ 2464 2465 2466 #undef __FUNCT__ 2467 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2468 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2469 { 2470 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2471 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2472 PetscReal atmp; 2473 PetscReal *work,*svalues,*rvalues; 2474 PetscErrorCode ierr; 2475 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2476 PetscMPIInt rank,size; 2477 PetscInt *rowners_bs,dest,count,source; 2478 PetscScalar *va; 2479 MatScalar *ba; 2480 MPI_Status stat; 2481 2482 PetscFunctionBegin; 2483 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2484 ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr); 2485 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2486 2487 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2488 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2489 2490 bs = A->rmap->bs; 2491 mbs = a->mbs; 2492 Mbs = a->Mbs; 2493 ba = b->a; 2494 bi = b->i; 2495 bj = b->j; 2496 2497 /* find ownerships */ 2498 rowners_bs = A->rmap->range; 2499 2500 /* each proc creates an array to be distributed */ 2501 ierr = PetscMalloc1(bs*Mbs,&work);CHKERRQ(ierr); 2502 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2503 2504 /* row_max for B */ 2505 if (rank != size-1) { 2506 for (i=0; i<mbs; i++) { 2507 ncols = bi[1] - bi[0]; bi++; 2508 brow = bs*i; 2509 for (j=0; j<ncols; j++) { 2510 bcol = bs*(*bj); 2511 for (kcol=0; kcol<bs; kcol++) { 2512 col = bcol + kcol; /* local col index */ 2513 col += rowners_bs[rank+1]; /* global col index */ 2514 for (krow=0; krow<bs; krow++) { 2515 atmp = PetscAbsScalar(*ba); ba++; 2516 row = brow + krow; /* local row index */ 2517 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2518 if (work[col] < atmp) work[col] = atmp; 2519 } 2520 } 2521 bj++; 2522 } 2523 } 2524 2525 /* send values to its owners */ 2526 for (dest=rank+1; dest<size; dest++) { 2527 svalues = work + rowners_bs[dest]; 2528 count = rowners_bs[dest+1]-rowners_bs[dest]; 2529 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2530 } 2531 } 2532 2533 /* receive values */ 2534 if (rank) { 2535 rvalues = work; 2536 count = rowners_bs[rank+1]-rowners_bs[rank]; 2537 for (source=0; source<rank; source++) { 2538 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr); 2539 /* process values */ 2540 for (i=0; i<count; i++) { 2541 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2542 } 2543 } 2544 } 2545 2546 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2547 ierr = PetscFree(work);CHKERRQ(ierr); 2548 PetscFunctionReturn(0); 2549 } 2550 2551 #undef __FUNCT__ 2552 #define __FUNCT__ "MatSOR_MPISBAIJ" 2553 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2554 { 2555 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2556 PetscErrorCode ierr; 2557 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2558 PetscScalar *x,*ptr,*from; 2559 Vec bb1; 2560 const PetscScalar *b; 2561 2562 PetscFunctionBegin; 2563 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); 2564 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2565 2566 if (flag == SOR_APPLY_UPPER) { 2567 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2568 PetscFunctionReturn(0); 2569 } 2570 2571 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2572 if (flag & SOR_ZERO_INITIAL_GUESS) { 2573 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2574 its--; 2575 } 2576 2577 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2578 while (its--) { 2579 2580 /* lower triangular part: slvec0b = - B^T*xx */ 2581 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2582 2583 /* copy xx into slvec0a */ 2584 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2585 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2586 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2587 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2588 2589 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2590 2591 /* copy bb into slvec1a */ 2592 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2593 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2594 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2595 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2596 2597 /* set slvec1b = 0 */ 2598 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2599 2600 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2601 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2602 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2603 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2604 2605 /* upper triangular part: bb1 = bb1 - B*x */ 2606 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2607 2608 /* local diagonal sweep */ 2609 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2610 } 2611 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2612 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2614 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2615 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2616 } else if (flag & SOR_EISENSTAT) { 2617 Vec xx1; 2618 PetscBool hasop; 2619 const PetscScalar *diag; 2620 PetscScalar *sl,scale = (omega - 2.0)/omega; 2621 PetscInt i,n; 2622 2623 if (!mat->xx1) { 2624 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2625 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2626 } 2627 xx1 = mat->xx1; 2628 bb1 = mat->bb1; 2629 2630 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2631 2632 if (!mat->diag) { 2633 /* this is wrong for same matrix with new nonzero values */ 2634 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 2635 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2636 } 2637 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2638 2639 if (hasop) { 2640 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2641 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2642 } else { 2643 /* 2644 These two lines are replaced by code that may be a bit faster for a good compiler 2645 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2646 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2647 */ 2648 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2649 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2650 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2651 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2652 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2653 if (omega == 1.0) { 2654 for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i]; 2655 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2656 } else { 2657 for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i]; 2658 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2659 } 2660 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2661 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2662 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2663 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2664 } 2665 2666 /* multiply off-diagonal portion of matrix */ 2667 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2668 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2669 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2670 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2671 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2672 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2673 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2674 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2675 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2676 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2677 2678 /* local sweep */ 2679 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); 2680 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2681 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2682 PetscFunctionReturn(0); 2683 } 2684 2685 #undef __FUNCT__ 2686 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2687 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2688 { 2689 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2690 PetscErrorCode ierr; 2691 Vec lvec1,bb1; 2692 2693 PetscFunctionBegin; 2694 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); 2695 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2696 2697 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2698 if (flag & SOR_ZERO_INITIAL_GUESS) { 2699 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2700 its--; 2701 } 2702 2703 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2704 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2705 while (its--) { 2706 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2707 2708 /* lower diagonal part: bb1 = bb - B^T*xx */ 2709 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2710 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2711 2712 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2713 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2714 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2715 2716 /* upper diagonal part: bb1 = bb1 - B*x */ 2717 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2718 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2719 2720 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2721 2722 /* diagonal sweep */ 2723 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2724 } 2725 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2726 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2727 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2728 PetscFunctionReturn(0); 2729 } 2730 2731 #undef __FUNCT__ 2732 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2733 /*@ 2734 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2735 CSR format the local rows. 2736 2737 Collective on MPI_Comm 2738 2739 Input Parameters: 2740 + comm - MPI communicator 2741 . bs - the block size, only a block size of 1 is supported 2742 . m - number of local rows (Cannot be PETSC_DECIDE) 2743 . n - This value should be the same as the local size used in creating the 2744 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2745 calculated if N is given) For square matrices n is almost always m. 2746 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2747 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2748 . i - row indices 2749 . j - column indices 2750 - a - matrix values 2751 2752 Output Parameter: 2753 . mat - the matrix 2754 2755 Level: intermediate 2756 2757 Notes: 2758 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2759 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2760 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2761 2762 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2763 2764 .keywords: matrix, aij, compressed row, sparse, parallel 2765 2766 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2767 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2768 @*/ 2769 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) 2770 { 2771 PetscErrorCode ierr; 2772 2773 2774 PetscFunctionBegin; 2775 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2776 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2777 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2778 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2779 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2780 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2781 PetscFunctionReturn(0); 2782 } 2783 2784 2785 #undef __FUNCT__ 2786 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2787 /*@C 2788 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2789 (the default parallel PETSc format). 2790 2791 Collective on MPI_Comm 2792 2793 Input Parameters: 2794 + B - the matrix 2795 . bs - the block size 2796 . i - the indices into j for the start of each local row (starts with zero) 2797 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2798 - v - optional values in the matrix 2799 2800 Level: developer 2801 2802 .keywords: matrix, aij, compressed row, sparse, parallel 2803 2804 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2805 @*/ 2806 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2807 { 2808 PetscErrorCode ierr; 2809 2810 PetscFunctionBegin; 2811 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2812 PetscFunctionReturn(0); 2813 } 2814 2815 2816