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 EXTERN_C_BEGIN 24 #undef __FUNCT__ 25 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 26 PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 27 { 28 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 29 PetscErrorCode ierr; 30 31 PetscFunctionBegin; 32 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 33 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 34 PetscFunctionReturn(0); 35 } 36 EXTERN_C_END 37 38 EXTERN_C_BEGIN 39 #undef __FUNCT__ 40 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 41 PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 42 { 43 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data; 44 PetscErrorCode ierr; 45 46 PetscFunctionBegin; 47 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 48 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 49 PetscFunctionReturn(0); 50 } 51 EXTERN_C_END 52 53 54 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 55 { \ 56 \ 57 brow = row/bs; \ 58 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 59 rmax = aimax[brow]; nrow = ailen[brow]; \ 60 bcol = col/bs; \ 61 ridx = row % bs; cidx = col % bs; \ 62 low = 0; high = nrow; \ 63 while (high-low > 3) { \ 64 t = (low+high)/2; \ 65 if (rp[t] > bcol) high = t; \ 66 else low = t; \ 67 } \ 68 for (_i=low; _i<high; _i++) { \ 69 if (rp[_i] > bcol) break; \ 70 if (rp[_i] == bcol) { \ 71 bap = ap + bs2*_i + bs*cidx + ridx; \ 72 if (addv == ADD_VALUES) *bap += value; \ 73 else *bap = value; \ 74 goto a_noinsert; \ 75 } \ 76 } \ 77 if (a->nonew == 1) goto a_noinsert; \ 78 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 79 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 80 N = nrow++ - 1; \ 81 /* shift up all the later entries in this row */ \ 82 for (ii=N; ii>=_i; ii--) { \ 83 rp[ii+1] = rp[ii]; \ 84 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 85 } \ 86 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 87 rp[_i] = bcol; \ 88 ap[bs2*_i + bs*cidx + ridx] = value; \ 89 a_noinsert:; \ 90 ailen[brow] = nrow; \ 91 } 92 93 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 94 { \ 95 brow = row/bs; \ 96 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 97 rmax = bimax[brow]; nrow = bilen[brow]; \ 98 bcol = col/bs; \ 99 ridx = row % bs; cidx = col % bs; \ 100 low = 0; high = nrow; \ 101 while (high-low > 3) { \ 102 t = (low+high)/2; \ 103 if (rp[t] > bcol) high = t; \ 104 else low = t; \ 105 } \ 106 for (_i=low; _i<high; _i++) { \ 107 if (rp[_i] > bcol) break; \ 108 if (rp[_i] == bcol) { \ 109 bap = ap + bs2*_i + bs*cidx + ridx; \ 110 if (addv == ADD_VALUES) *bap += value; \ 111 else *bap = value; \ 112 goto b_noinsert; \ 113 } \ 114 } \ 115 if (b->nonew == 1) goto b_noinsert; \ 116 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 117 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 118 N = nrow++ - 1; \ 119 /* shift up all the later entries in this row */ \ 120 for (ii=N; ii>=_i; ii--) { \ 121 rp[ii+1] = rp[ii]; \ 122 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 123 } \ 124 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 125 rp[_i] = bcol; \ 126 ap[bs2*_i + bs*cidx + ridx] = value; \ 127 b_noinsert:; \ 128 bilen[brow] = nrow; \ 129 } 130 131 /* Only add/insert a(i,j) with i<=j (blocks). 132 Any a(i,j) with i>j input by user is ingored. 133 */ 134 #undef __FUNCT__ 135 #define __FUNCT__ "MatSetValues_MPISBAIJ" 136 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 137 { 138 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 139 MatScalar value; 140 PetscBool roworiented = baij->roworiented; 141 PetscErrorCode ierr; 142 PetscInt i,j,row,col; 143 PetscInt rstart_orig=mat->rmap->rstart; 144 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 145 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 146 147 /* Some Variables required in the macro */ 148 Mat A = baij->A; 149 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 150 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 151 MatScalar *aa =a->a; 152 153 Mat B = baij->B; 154 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 155 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 156 MatScalar *ba =b->a; 157 158 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 159 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 160 MatScalar *ap,*bap; 161 162 /* for stash */ 163 PetscInt n_loc, *in_loc = NULL; 164 MatScalar *v_loc = NULL; 165 166 PetscFunctionBegin; 167 if (v) PetscValidScalarPointer(v,6); 168 if (!baij->donotstash) { 169 if (n > baij->n_loc) { 170 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 171 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 172 ierr = PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);CHKERRQ(ierr); 173 ierr = PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);CHKERRQ(ierr); 174 175 baij->n_loc = n; 176 } 177 in_loc = baij->in_loc; 178 v_loc = baij->v_loc; 179 } 180 181 for (i=0; i<m; i++) { 182 if (im[i] < 0) continue; 183 #if defined(PETSC_USE_DEBUG) 184 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); 185 #endif 186 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 187 row = im[i] - rstart_orig; /* local row index */ 188 for (j=0; j<n; j++) { 189 if (im[i]/bs > in[j]/bs) { 190 if (a->ignore_ltriangular) { 191 continue; /* ignore lower triangular blocks */ 192 } 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)"); 193 } 194 if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */ 195 col = in[j] - cstart_orig; /* local col index */ 196 brow = row/bs; bcol = col/bs; 197 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 198 if (roworiented) value = v[i*n+j]; 199 else value = v[i+j*m]; 200 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 201 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 202 } else if (in[j] < 0) continue; 203 #if defined(PETSC_USE_DEBUG) 204 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); 205 #endif 206 else { /* off-diag entry (B) */ 207 if (mat->was_assembled) { 208 if (!baij->colmap) { 209 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 210 } 211 #if defined(PETSC_USE_CTABLE) 212 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 213 col = col - 1; 214 #else 215 col = baij->colmap[in[j]/bs] - 1; 216 #endif 217 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 218 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 219 col = in[j]; 220 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 221 B = baij->B; 222 b = (Mat_SeqBAIJ*)(B)->data; 223 bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 224 ba = b->a; 225 } else col += in[j]%bs; 226 } else col = in[j]; 227 if (roworiented) value = v[i*n+j]; 228 else value = v[i+j*m]; 229 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 230 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 231 } 232 } 233 } else { /* off processor entry */ 234 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]); 235 if (!baij->donotstash) { 236 mat->assembled = PETSC_FALSE; 237 n_loc = 0; 238 for (j=0; j<n; j++) { 239 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 240 in_loc[n_loc] = in[j]; 241 if (roworiented) { 242 v_loc[n_loc] = v[i*n+j]; 243 } else { 244 v_loc[n_loc] = v[j*m+i]; 245 } 246 n_loc++; 247 } 248 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);CHKERRQ(ierr); 249 } 250 } 251 } 252 PetscFunctionReturn(0); 253 } 254 255 #undef __FUNCT__ 256 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 257 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 258 { 259 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 260 const MatScalar *value; 261 MatScalar *barray =baij->barray; 262 PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular; 263 PetscErrorCode ierr; 264 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 265 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 266 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 267 268 PetscFunctionBegin; 269 if (!barray) { 270 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 271 baij->barray = barray; 272 } 273 274 if (roworiented) { 275 stepval = (n-1)*bs; 276 } else { 277 stepval = (m-1)*bs; 278 } 279 for (i=0; i<m; i++) { 280 if (im[i] < 0) continue; 281 #if defined(PETSC_USE_DEBUG) 282 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); 283 #endif 284 if (im[i] >= rstart && im[i] < rend) { 285 row = im[i] - rstart; 286 for (j=0; j<n; j++) { 287 if (im[i] > in[j]) { 288 if (ignore_ltriangular) continue; /* ignore lower triangular blocks */ 289 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)"); 290 } 291 /* If NumCol = 1 then a copy is not required */ 292 if ((roworiented) && (n == 1)) { 293 barray = (MatScalar*) v + i*bs2; 294 } else if ((!roworiented) && (m == 1)) { 295 barray = (MatScalar*) v + j*bs2; 296 } else { /* Here a copy is required */ 297 if (roworiented) { 298 value = v + i*(stepval+bs)*bs + j*bs; 299 } else { 300 value = v + j*(stepval+bs)*bs + i*bs; 301 } 302 for (ii=0; ii<bs; ii++,value+=stepval) { 303 for (jj=0; jj<bs; jj++) { 304 *barray++ = *value++; 305 } 306 } 307 barray -=bs2; 308 } 309 310 if (in[j] >= cstart && in[j] < cend) { 311 col = in[j] - cstart; 312 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 313 } else if (in[j] < 0) continue; 314 #if defined(PETSC_USE_DEBUG) 315 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); 316 #endif 317 else { 318 if (mat->was_assembled) { 319 if (!baij->colmap) { 320 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 321 } 322 323 #if defined(PETSC_USE_DEBUG) 324 #if defined(PETSC_USE_CTABLE) 325 { PetscInt data; 326 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 327 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 328 } 329 #else 330 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 331 #endif 332 #endif 333 #if defined(PETSC_USE_CTABLE) 334 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 335 col = (col - 1)/bs; 336 #else 337 col = (baij->colmap[in[j]] - 1)/bs; 338 #endif 339 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 340 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 341 col = in[j]; 342 } 343 } else col = in[j]; 344 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 345 } 346 } 347 } else { 348 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]); 349 if (!baij->donotstash) { 350 if (roworiented) { 351 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 352 } else { 353 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 354 } 355 } 356 } 357 } 358 PetscFunctionReturn(0); 359 } 360 361 #undef __FUNCT__ 362 #define __FUNCT__ "MatGetValues_MPISBAIJ" 363 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 364 { 365 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 366 PetscErrorCode ierr; 367 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 368 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 369 370 PetscFunctionBegin; 371 for (i=0; i<m; i++) { 372 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 373 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); 374 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 375 row = idxm[i] - bsrstart; 376 for (j=0; j<n; j++) { 377 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 378 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); 379 if (idxn[j] >= bscstart && idxn[j] < bscend) { 380 col = idxn[j] - bscstart; 381 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 382 } else { 383 if (!baij->colmap) { 384 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 385 } 386 #if defined(PETSC_USE_CTABLE) 387 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 388 data--; 389 #else 390 data = baij->colmap[idxn[j]/bs]-1; 391 #endif 392 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 393 else { 394 col = data + idxn[j]%bs; 395 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 396 } 397 } 398 } 399 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 400 } 401 PetscFunctionReturn(0); 402 } 403 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatNorm_MPISBAIJ" 406 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 407 { 408 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscReal sum[2],*lnorm2; 411 412 PetscFunctionBegin; 413 if (baij->size == 1) { 414 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 415 } else { 416 if (type == NORM_FROBENIUS) { 417 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 418 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 419 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 420 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 421 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 422 ierr = MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 423 *norm = PetscSqrtReal(sum[0] + 2*sum[1]); 424 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 425 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 426 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 427 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 428 PetscReal *rsum,*rsum2,vabs; 429 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 430 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 431 MatScalar *v; 432 433 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&rsum,mat->cmap->N,PetscReal,&rsum2);CHKERRQ(ierr); 434 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 435 /* Amat */ 436 v = amat->a; jj = amat->j; 437 for (brow=0; brow<mbs; brow++) { 438 grow = bs*(rstart + brow); 439 nz = amat->i[brow+1] - amat->i[brow]; 440 for (bcol=0; bcol<nz; bcol++) { 441 gcol = bs*(rstart + *jj); jj++; 442 for (col=0; col<bs; col++) { 443 for (row=0; row<bs; row++) { 444 vabs = PetscAbsScalar(*v); v++; 445 rsum[gcol+col] += vabs; 446 /* non-diagonal block */ 447 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 448 } 449 } 450 } 451 } 452 /* Bmat */ 453 v = bmat->a; jj = bmat->j; 454 for (brow=0; brow<mbs; brow++) { 455 grow = bs*(rstart + brow); 456 nz = bmat->i[brow+1] - bmat->i[brow]; 457 for (bcol=0; bcol<nz; bcol++) { 458 gcol = bs*garray[*jj]; jj++; 459 for (col=0; col<bs; col++) { 460 for (row=0; row<bs; row++) { 461 vabs = PetscAbsScalar(*v); v++; 462 rsum[gcol+col] += vabs; 463 rsum[grow+row] += vabs; 464 } 465 } 466 } 467 } 468 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 469 *norm = 0.0; 470 for (col=0; col<mat->cmap->N; col++) { 471 if (rsum2[col] > *norm) *norm = rsum2[col]; 472 } 473 ierr = PetscFree2(rsum,rsum2);CHKERRQ(ierr); 474 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet"); 475 } 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 481 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 482 { 483 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 484 PetscErrorCode ierr; 485 PetscInt nstash,reallocs; 486 InsertMode addv; 487 488 PetscFunctionBegin; 489 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 490 491 /* make sure all processors are either in INSERTMODE or ADDMODE */ 492 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 493 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 494 mat->insertmode = addv; /* in case this processor had no cache */ 495 496 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 497 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 498 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 499 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 500 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 501 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 502 PetscFunctionReturn(0); 503 } 504 505 #undef __FUNCT__ 506 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 507 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 508 { 509 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 510 Mat_SeqSBAIJ *a =(Mat_SeqSBAIJ*)baij->A->data; 511 PetscErrorCode ierr; 512 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 513 PetscInt *row,*col; 514 PetscBool other_disassembled; 515 PetscMPIInt n; 516 PetscBool r1,r2,r3; 517 MatScalar *val; 518 InsertMode addv = mat->insertmode; 519 520 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 521 PetscFunctionBegin; 522 if (!baij->donotstash && !mat->nooffprocentries) { 523 while (1) { 524 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 525 if (!flg) break; 526 527 for (i=0; i<n;) { 528 /* Now identify the consecutive vals belonging to the same row */ 529 for (j=i,rstart=row[j]; j<n; j++) { 530 if (row[j] != rstart) break; 531 } 532 if (j < n) ncols = j-i; 533 else ncols = n-i; 534 /* Now assemble all these values with a single function call */ 535 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 536 i = j; 537 } 538 } 539 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 540 /* Now process the block-stash. Since the values are stashed column-oriented, 541 set the roworiented flag to column oriented, and after MatSetValues() 542 restore the original flags */ 543 r1 = baij->roworiented; 544 r2 = a->roworiented; 545 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 546 547 baij->roworiented = PETSC_FALSE; 548 a->roworiented = PETSC_FALSE; 549 550 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 551 while (1) { 552 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 553 if (!flg) break; 554 555 for (i=0; i<n;) { 556 /* Now identify the consecutive vals belonging to the same row */ 557 for (j=i,rstart=row[j]; j<n; j++) { 558 if (row[j] != rstart) break; 559 } 560 if (j < n) ncols = j-i; 561 else ncols = n-i; 562 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 563 i = j; 564 } 565 } 566 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 567 568 baij->roworiented = r1; 569 a->roworiented = r2; 570 571 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 572 } 573 574 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 575 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 576 577 /* determine if any processor has disassembled, if so we must 578 also disassemble ourselfs, in order that we may reassemble. */ 579 /* 580 if nonzero structure of submatrix B cannot change then we know that 581 no processor disassembled thus we can skip this stuff 582 */ 583 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 584 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 585 if (mat->was_assembled && !other_disassembled) { 586 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 587 } 588 } 589 590 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 591 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 592 } 593 ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_TRUE);CHKERRQ(ierr); 594 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 595 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 596 597 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 598 599 baij->rowvalues = 0; 600 PetscFunctionReturn(0); 601 } 602 603 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 604 #include <petscdraw.h> 605 #undef __FUNCT__ 606 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 607 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 608 { 609 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 610 PetscErrorCode ierr; 611 PetscInt bs = mat->rmap->bs; 612 PetscMPIInt size = baij->size,rank = baij->rank; 613 PetscBool iascii,isdraw; 614 PetscViewer sviewer; 615 PetscViewerFormat format; 616 617 PetscFunctionBegin; 618 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 619 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 620 if (iascii) { 621 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 622 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 623 MatInfo info; 624 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 625 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 626 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 627 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 628 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 629 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 630 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 631 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 632 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 633 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 634 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 635 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_INFO) { 638 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 639 PetscFunctionReturn(0); 640 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 641 PetscFunctionReturn(0); 642 } 643 } 644 645 if (isdraw) { 646 PetscDraw draw; 647 PetscBool isnull; 648 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 649 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 650 } 651 652 if (size == 1) { 653 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 654 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 655 } else { 656 /* assemble the entire matrix onto first processor. */ 657 Mat A; 658 Mat_SeqSBAIJ *Aloc; 659 Mat_SeqBAIJ *Bloc; 660 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 661 MatScalar *a; 662 663 /* Should this be the same type as mat? */ 664 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 665 if (!rank) { 666 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 667 } else { 668 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 669 } 670 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 671 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 672 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 674 675 /* copy over the A part */ 676 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 677 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 678 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 679 680 for (i=0; i<mbs; i++) { 681 rvals[0] = bs*(baij->rstartbs + i); 682 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 683 for (j=ai[i]; j<ai[i+1]; j++) { 684 col = (baij->cstartbs+aj[j])*bs; 685 for (k=0; k<bs; k++) { 686 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 687 col++; 688 a += bs; 689 } 690 } 691 } 692 /* copy over the B part */ 693 Bloc = (Mat_SeqBAIJ*)baij->B->data; 694 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 695 for (i=0; i<mbs; i++) { 696 697 rvals[0] = bs*(baij->rstartbs + i); 698 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 699 for (j=ai[i]; j<ai[i+1]; j++) { 700 col = baij->garray[aj[j]]*bs; 701 for (k=0; k<bs; k++) { 702 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 703 col++; 704 a += bs; 705 } 706 } 707 } 708 ierr = PetscFree(rvals);CHKERRQ(ierr); 709 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 710 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 711 /* 712 Everyone has to call to draw the matrix since the graphics waits are 713 synchronized across all processors that share the PetscDraw object 714 */ 715 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 716 if (!rank) { 717 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 718 /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/ 719 PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ); 720 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 721 } 722 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 723 ierr = MatDestroy(&A);CHKERRQ(ierr); 724 } 725 PetscFunctionReturn(0); 726 } 727 728 #undef __FUNCT__ 729 #define __FUNCT__ "MatView_MPISBAIJ" 730 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 731 { 732 PetscErrorCode ierr; 733 PetscBool iascii,isdraw,issocket,isbinary; 734 735 PetscFunctionBegin; 736 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 737 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 738 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 739 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 740 if (iascii || isdraw || issocket || isbinary) { 741 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 742 } 743 PetscFunctionReturn(0); 744 } 745 746 #undef __FUNCT__ 747 #define __FUNCT__ "MatDestroy_MPISBAIJ" 748 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 749 { 750 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 751 PetscErrorCode ierr; 752 753 PetscFunctionBegin; 754 #if defined(PETSC_USE_LOG) 755 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 756 #endif 757 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 758 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 759 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 760 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 761 #if defined(PETSC_USE_CTABLE) 762 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 763 #else 764 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 765 #endif 766 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 767 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 768 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 770 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 771 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 772 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 773 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 774 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 775 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 776 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 777 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 778 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 779 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 780 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 781 #if defined(PETSC_USE_REAL_MAT_SINGLE) 782 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 783 #endif 784 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 785 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 786 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 787 ierr = PetscFree(mat->data);CHKERRQ(ierr); 788 789 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",NULL);CHKERRQ(ierr); 791 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",NULL);CHKERRQ(ierr); 792 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",NULL);CHKERRQ(ierr); 793 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",NULL);CHKERRQ(ierr); 794 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C","",NULL);CHKERRQ(ierr); 795 PetscFunctionReturn(0); 796 } 797 798 #undef __FUNCT__ 799 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 800 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 801 { 802 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 803 PetscErrorCode ierr; 804 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 805 PetscScalar *x,*from; 806 807 PetscFunctionBegin; 808 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 809 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 810 811 /* diagonal part */ 812 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 813 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 814 815 /* subdiagonal part */ 816 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 817 818 /* copy x into the vec slvec0 */ 819 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 823 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 824 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 825 826 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 827 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 828 /* supperdiagonal part */ 829 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 830 PetscFunctionReturn(0); 831 } 832 833 #undef __FUNCT__ 834 #define __FUNCT__ "MatMult_MPISBAIJ" 835 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 836 { 837 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 838 PetscErrorCode ierr; 839 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 840 PetscScalar *x,*from; 841 842 PetscFunctionBegin; 843 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 844 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 845 846 /* diagonal part */ 847 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 848 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 849 850 /* subdiagonal part */ 851 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 852 853 /* copy x into the vec slvec0 */ 854 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 855 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 856 857 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 858 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 859 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 860 861 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 862 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 863 /* supperdiagonal part */ 864 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 #undef __FUNCT__ 869 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 870 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 871 { 872 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 873 PetscErrorCode ierr; 874 PetscInt nt; 875 876 PetscFunctionBegin; 877 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 878 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 879 880 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 881 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 882 883 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 884 /* do diagonal part */ 885 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 886 /* do supperdiagonal part */ 887 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 888 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 889 /* do subdiagonal part */ 890 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 891 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 892 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 893 PetscFunctionReturn(0); 894 } 895 896 #undef __FUNCT__ 897 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 898 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 899 { 900 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 901 PetscErrorCode ierr; 902 PetscInt mbs=a->mbs,bs=A->rmap->bs; 903 PetscScalar *x,*from,zero=0.0; 904 905 PetscFunctionBegin; 906 /* 907 PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n"); 908 PetscSynchronizedFlush(PetscObjectComm((PetscObject)A)); 909 */ 910 /* diagonal part */ 911 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 912 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 913 914 /* subdiagonal part */ 915 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 916 917 /* copy x into the vec slvec0 */ 918 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 919 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 920 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 921 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 922 923 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 924 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 925 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 926 927 /* supperdiagonal part */ 928 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 929 PetscFunctionReturn(0); 930 } 931 932 #undef __FUNCT__ 933 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 934 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 935 { 936 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 937 PetscErrorCode ierr; 938 939 PetscFunctionBegin; 940 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 941 /* do diagonal part */ 942 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 943 /* do supperdiagonal part */ 944 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 946 947 /* do subdiagonal part */ 948 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 949 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 950 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 951 PetscFunctionReturn(0); 952 } 953 954 /* 955 This only works correctly for square matrices where the subblock A->A is the 956 diagonal block 957 */ 958 #undef __FUNCT__ 959 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 960 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 961 { 962 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 963 PetscErrorCode ierr; 964 965 PetscFunctionBegin; 966 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 967 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 968 PetscFunctionReturn(0); 969 } 970 971 #undef __FUNCT__ 972 #define __FUNCT__ "MatScale_MPISBAIJ" 973 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 974 { 975 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 976 PetscErrorCode ierr; 977 978 PetscFunctionBegin; 979 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 980 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 981 PetscFunctionReturn(0); 982 } 983 984 #undef __FUNCT__ 985 #define __FUNCT__ "MatGetRow_MPISBAIJ" 986 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 987 { 988 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 989 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 990 PetscErrorCode ierr; 991 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 992 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 993 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 994 995 PetscFunctionBegin; 996 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 997 mat->getrowactive = PETSC_TRUE; 998 999 if (!mat->rowvalues && (idx || v)) { 1000 /* 1001 allocate enough space to hold information from the longest row. 1002 */ 1003 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1004 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1005 PetscInt max = 1,mbs = mat->mbs,tmp; 1006 for (i=0; i<mbs; i++) { 1007 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1008 if (max < tmp) max = tmp; 1009 } 1010 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1011 } 1012 1013 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1014 lrow = row - brstart; /* local row index */ 1015 1016 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1017 if (!v) {pvA = 0; pvB = 0;} 1018 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1019 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1020 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1021 nztot = nzA + nzB; 1022 1023 cmap = mat->garray; 1024 if (v || idx) { 1025 if (nztot) { 1026 /* Sort by increasing column numbers, assuming A and B already sorted */ 1027 PetscInt imark = -1; 1028 if (v) { 1029 *v = v_p = mat->rowvalues; 1030 for (i=0; i<nzB; i++) { 1031 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1032 else break; 1033 } 1034 imark = i; 1035 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1036 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1037 } 1038 if (idx) { 1039 *idx = idx_p = mat->rowindices; 1040 if (imark > -1) { 1041 for (i=0; i<imark; i++) { 1042 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1043 } 1044 } else { 1045 for (i=0; i<nzB; i++) { 1046 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1047 else break; 1048 } 1049 imark = i; 1050 } 1051 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1052 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1053 } 1054 } else { 1055 if (idx) *idx = 0; 1056 if (v) *v = 0; 1057 } 1058 } 1059 *nz = nztot; 1060 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1061 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1062 PetscFunctionReturn(0); 1063 } 1064 1065 #undef __FUNCT__ 1066 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1067 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1068 { 1069 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1070 1071 PetscFunctionBegin; 1072 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1073 baij->getrowactive = PETSC_FALSE; 1074 PetscFunctionReturn(0); 1075 } 1076 1077 #undef __FUNCT__ 1078 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1079 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1080 { 1081 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1082 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1083 1084 PetscFunctionBegin; 1085 aA->getrow_utriangular = PETSC_TRUE; 1086 PetscFunctionReturn(0); 1087 } 1088 #undef __FUNCT__ 1089 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1090 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1091 { 1092 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1093 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1094 1095 PetscFunctionBegin; 1096 aA->getrow_utriangular = PETSC_FALSE; 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1102 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1103 { 1104 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 1107 PetscFunctionBegin; 1108 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1109 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1110 PetscFunctionReturn(0); 1111 } 1112 1113 #undef __FUNCT__ 1114 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1115 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1116 { 1117 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1118 PetscErrorCode ierr; 1119 1120 PetscFunctionBegin; 1121 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1122 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1123 PetscFunctionReturn(0); 1124 } 1125 1126 #undef __FUNCT__ 1127 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1128 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1129 { 1130 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1131 PetscErrorCode ierr; 1132 1133 PetscFunctionBegin; 1134 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1135 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1136 PetscFunctionReturn(0); 1137 } 1138 1139 #undef __FUNCT__ 1140 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1141 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1142 { 1143 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1144 Mat A = a->A,B = a->B; 1145 PetscErrorCode ierr; 1146 PetscReal isend[5],irecv[5]; 1147 1148 PetscFunctionBegin; 1149 info->block_size = (PetscReal)matin->rmap->bs; 1150 1151 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1152 1153 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1154 isend[3] = info->memory; isend[4] = info->mallocs; 1155 1156 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1157 1158 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1159 isend[3] += info->memory; isend[4] += info->mallocs; 1160 if (flag == MAT_LOCAL) { 1161 info->nz_used = isend[0]; 1162 info->nz_allocated = isend[1]; 1163 info->nz_unneeded = isend[2]; 1164 info->memory = isend[3]; 1165 info->mallocs = isend[4]; 1166 } else if (flag == MAT_GLOBAL_MAX) { 1167 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1168 1169 info->nz_used = irecv[0]; 1170 info->nz_allocated = irecv[1]; 1171 info->nz_unneeded = irecv[2]; 1172 info->memory = irecv[3]; 1173 info->mallocs = irecv[4]; 1174 } else if (flag == MAT_GLOBAL_SUM) { 1175 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1176 1177 info->nz_used = irecv[0]; 1178 info->nz_allocated = irecv[1]; 1179 info->nz_unneeded = irecv[2]; 1180 info->memory = irecv[3]; 1181 info->mallocs = irecv[4]; 1182 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1183 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1184 info->fill_ratio_needed = 0; 1185 info->factor_mallocs = 0; 1186 PetscFunctionReturn(0); 1187 } 1188 1189 #undef __FUNCT__ 1190 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1191 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1192 { 1193 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1194 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1195 PetscErrorCode ierr; 1196 1197 PetscFunctionBegin; 1198 switch (op) { 1199 case MAT_NEW_NONZERO_LOCATIONS: 1200 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1201 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1202 case MAT_KEEP_NONZERO_PATTERN: 1203 case MAT_NEW_NONZERO_LOCATION_ERR: 1204 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1205 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1206 break; 1207 case MAT_ROW_ORIENTED: 1208 a->roworiented = flg; 1209 1210 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1211 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1212 break; 1213 case MAT_NEW_DIAGONALS: 1214 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1215 break; 1216 case MAT_IGNORE_OFF_PROC_ENTRIES: 1217 a->donotstash = flg; 1218 break; 1219 case MAT_USE_HASH_TABLE: 1220 a->ht_flag = flg; 1221 break; 1222 case MAT_HERMITIAN: 1223 if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first"); 1224 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1225 1226 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1227 break; 1228 case MAT_SPD: 1229 A->spd_set = PETSC_TRUE; 1230 A->spd = flg; 1231 if (flg) { 1232 A->symmetric = PETSC_TRUE; 1233 A->structurally_symmetric = PETSC_TRUE; 1234 A->symmetric_set = PETSC_TRUE; 1235 A->structurally_symmetric_set = PETSC_TRUE; 1236 } 1237 break; 1238 case MAT_SYMMETRIC: 1239 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1240 break; 1241 case MAT_STRUCTURALLY_SYMMETRIC: 1242 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1243 break; 1244 case MAT_SYMMETRY_ETERNAL: 1245 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1246 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1247 break; 1248 case MAT_IGNORE_LOWER_TRIANGULAR: 1249 aA->ignore_ltriangular = flg; 1250 break; 1251 case MAT_ERROR_LOWER_TRIANGULAR: 1252 aA->ignore_ltriangular = flg; 1253 break; 1254 case MAT_GETROW_UPPERTRIANGULAR: 1255 aA->getrow_utriangular = flg; 1256 break; 1257 default: 1258 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1259 } 1260 PetscFunctionReturn(0); 1261 } 1262 1263 #undef __FUNCT__ 1264 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1265 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1266 { 1267 PetscErrorCode ierr; 1268 1269 PetscFunctionBegin; 1270 if (MAT_INITIAL_MATRIX || *B != A) { 1271 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1272 } 1273 PetscFunctionReturn(0); 1274 } 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1278 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1279 { 1280 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1281 Mat a = baij->A, b=baij->B; 1282 PetscErrorCode ierr; 1283 PetscInt nv,m,n; 1284 PetscBool flg; 1285 1286 PetscFunctionBegin; 1287 if (ll != rr) { 1288 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1289 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1290 } 1291 if (!ll) PetscFunctionReturn(0); 1292 1293 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1294 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1295 1296 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1297 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1298 1299 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1300 1301 /* left diagonalscale the off-diagonal part */ 1302 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1303 1304 /* scale the diagonal part */ 1305 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1306 1307 /* right diagonalscale the off-diagonal part */ 1308 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1309 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1310 PetscFunctionReturn(0); 1311 } 1312 1313 #undef __FUNCT__ 1314 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1315 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1316 { 1317 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1318 PetscErrorCode ierr; 1319 1320 PetscFunctionBegin; 1321 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1322 PetscFunctionReturn(0); 1323 } 1324 1325 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*); 1326 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatEqual_MPISBAIJ" 1329 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1330 { 1331 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1332 Mat a,b,c,d; 1333 PetscBool flg; 1334 PetscErrorCode ierr; 1335 1336 PetscFunctionBegin; 1337 a = matA->A; b = matA->B; 1338 c = matB->A; d = matB->B; 1339 1340 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1341 if (flg) { 1342 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1343 } 1344 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1345 PetscFunctionReturn(0); 1346 } 1347 1348 #undef __FUNCT__ 1349 #define __FUNCT__ "MatCopy_MPISBAIJ" 1350 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1351 { 1352 PetscErrorCode ierr; 1353 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1354 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data; 1355 1356 PetscFunctionBegin; 1357 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1358 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1359 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1360 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1361 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1362 } else { 1363 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1364 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1365 } 1366 PetscFunctionReturn(0); 1367 } 1368 1369 #undef __FUNCT__ 1370 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1371 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1372 { 1373 PetscErrorCode ierr; 1374 1375 PetscFunctionBegin; 1376 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1377 PetscFunctionReturn(0); 1378 } 1379 1380 #undef __FUNCT__ 1381 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1382 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1383 { 1384 PetscErrorCode ierr; 1385 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data; 1386 PetscBLASInt bnz,one=1; 1387 Mat_SeqSBAIJ *xa,*ya; 1388 Mat_SeqBAIJ *xb,*yb; 1389 1390 PetscFunctionBegin; 1391 if (str == SAME_NONZERO_PATTERN) { 1392 PetscScalar alpha = a; 1393 xa = (Mat_SeqSBAIJ*)xx->A->data; 1394 ya = (Mat_SeqSBAIJ*)yy->A->data; 1395 ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr); 1396 PetscStackCall("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one)); 1397 xb = (Mat_SeqBAIJ*)xx->B->data; 1398 yb = (Mat_SeqBAIJ*)yy->B->data; 1399 ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr); 1400 PetscStackCall("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one)); 1401 } else { 1402 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1403 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1404 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1405 } 1406 PetscFunctionReturn(0); 1407 } 1408 1409 #undef __FUNCT__ 1410 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1411 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1412 { 1413 PetscErrorCode ierr; 1414 PetscInt i; 1415 PetscBool flg; 1416 1417 PetscFunctionBegin; 1418 for (i=0; i<n; i++) { 1419 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1420 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1421 } 1422 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1423 PetscFunctionReturn(0); 1424 } 1425 1426 1427 /* -------------------------------------------------------------------*/ 1428 static struct _MatOps MatOps_Values = { 1429 MatSetValues_MPISBAIJ, 1430 MatGetRow_MPISBAIJ, 1431 MatRestoreRow_MPISBAIJ, 1432 MatMult_MPISBAIJ, 1433 /* 4*/ MatMultAdd_MPISBAIJ, 1434 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1435 MatMultAdd_MPISBAIJ, 1436 0, 1437 0, 1438 0, 1439 /* 10*/ 0, 1440 0, 1441 0, 1442 MatSOR_MPISBAIJ, 1443 MatTranspose_MPISBAIJ, 1444 /* 15*/ MatGetInfo_MPISBAIJ, 1445 MatEqual_MPISBAIJ, 1446 MatGetDiagonal_MPISBAIJ, 1447 MatDiagonalScale_MPISBAIJ, 1448 MatNorm_MPISBAIJ, 1449 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1450 MatAssemblyEnd_MPISBAIJ, 1451 MatSetOption_MPISBAIJ, 1452 MatZeroEntries_MPISBAIJ, 1453 /* 24*/ 0, 1454 0, 1455 0, 1456 0, 1457 0, 1458 /* 29*/ MatSetUp_MPISBAIJ, 1459 0, 1460 0, 1461 0, 1462 0, 1463 /* 34*/ MatDuplicate_MPISBAIJ, 1464 0, 1465 0, 1466 0, 1467 0, 1468 /* 39*/ MatAXPY_MPISBAIJ, 1469 MatGetSubMatrices_MPISBAIJ, 1470 MatIncreaseOverlap_MPISBAIJ, 1471 MatGetValues_MPISBAIJ, 1472 MatCopy_MPISBAIJ, 1473 /* 44*/ 0, 1474 MatScale_MPISBAIJ, 1475 0, 1476 0, 1477 0, 1478 /* 49*/ 0, 1479 0, 1480 0, 1481 0, 1482 0, 1483 /* 54*/ 0, 1484 0, 1485 MatSetUnfactored_MPISBAIJ, 1486 0, 1487 MatSetValuesBlocked_MPISBAIJ, 1488 /* 59*/ 0, 1489 0, 1490 0, 1491 0, 1492 0, 1493 /* 64*/ 0, 1494 0, 1495 0, 1496 0, 1497 0, 1498 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1499 0, 1500 0, 1501 0, 1502 0, 1503 /* 74*/ 0, 1504 0, 1505 0, 1506 0, 1507 0, 1508 /* 79*/ 0, 1509 0, 1510 0, 1511 0, 1512 MatLoad_MPISBAIJ, 1513 /* 84*/ 0, 1514 0, 1515 0, 1516 0, 1517 0, 1518 /* 89*/ 0, 1519 0, 1520 0, 1521 0, 1522 0, 1523 /* 94*/ 0, 1524 0, 1525 0, 1526 0, 1527 0, 1528 /* 99*/ 0, 1529 0, 1530 0, 1531 0, 1532 0, 1533 /*104*/ 0, 1534 MatRealPart_MPISBAIJ, 1535 MatImaginaryPart_MPISBAIJ, 1536 MatGetRowUpperTriangular_MPISBAIJ, 1537 MatRestoreRowUpperTriangular_MPISBAIJ, 1538 /*109*/ 0, 1539 0, 1540 0, 1541 0, 1542 0, 1543 /*114*/ 0, 1544 0, 1545 0, 1546 0, 1547 0, 1548 /*119*/ 0, 1549 0, 1550 0, 1551 0 1552 }; 1553 1554 1555 EXTERN_C_BEGIN 1556 #undef __FUNCT__ 1557 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1558 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1559 { 1560 PetscFunctionBegin; 1561 *a = ((Mat_MPISBAIJ*)A->data)->A; 1562 PetscFunctionReturn(0); 1563 } 1564 EXTERN_C_END 1565 1566 EXTERN_C_BEGIN 1567 #undef __FUNCT__ 1568 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1569 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1570 { 1571 Mat_MPISBAIJ *b; 1572 PetscErrorCode ierr; 1573 PetscInt i,mbs,Mbs; 1574 1575 PetscFunctionBegin; 1576 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1577 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1578 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1579 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1580 1581 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1582 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1583 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1584 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1585 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1586 1587 if (d_nnz) { 1588 for (i=0; i<B->rmap->n/bs; i++) { 1589 if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 1590 } 1591 } 1592 if (o_nnz) { 1593 for (i=0; i<B->rmap->n/bs; i++) { 1594 if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 1595 } 1596 } 1597 1598 b = (Mat_MPISBAIJ*)B->data; 1599 mbs = B->rmap->n/bs; 1600 Mbs = B->rmap->N/bs; 1601 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); 1602 1603 B->rmap->bs = bs; 1604 b->bs2 = bs*bs; 1605 b->mbs = mbs; 1606 b->nbs = mbs; 1607 b->Mbs = Mbs; 1608 b->Nbs = Mbs; 1609 1610 for (i=0; i<=b->size; i++) { 1611 b->rangebs[i] = B->rmap->range[i]/bs; 1612 } 1613 b->rstartbs = B->rmap->rstart/bs; 1614 b->rendbs = B->rmap->rend/bs; 1615 1616 b->cstartbs = B->cmap->rstart/bs; 1617 b->cendbs = B->cmap->rend/bs; 1618 1619 if (!B->preallocated) { 1620 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1621 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1622 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1623 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1624 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1625 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1626 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1627 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1628 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 1629 } 1630 1631 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1632 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1633 1634 B->preallocated = PETSC_TRUE; 1635 PetscFunctionReturn(0); 1636 } 1637 EXTERN_C_END 1638 1639 EXTERN_C_BEGIN 1640 #undef __FUNCT__ 1641 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1642 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1643 { 1644 PetscInt m,rstart,cstart,cend; 1645 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1646 const PetscInt *JJ =0; 1647 PetscScalar *values=0; 1648 PetscErrorCode ierr; 1649 1650 PetscFunctionBegin; 1651 if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1652 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1653 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1654 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1655 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1656 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1657 m = B->rmap->n/bs; 1658 rstart = B->rmap->rstart/bs; 1659 cstart = B->cmap->rstart/bs; 1660 cend = B->cmap->rend/bs; 1661 1662 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1663 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 1664 for (i=0; i<m; i++) { 1665 nz = ii[i+1] - ii[i]; 1666 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1667 nz_max = PetscMax(nz_max,nz); 1668 JJ = jj + ii[i]; 1669 for (j=0; j<nz; j++) { 1670 if (*JJ >= cstart) break; 1671 JJ++; 1672 } 1673 d = 0; 1674 for (; j<nz; j++) { 1675 if (*JJ++ >= cend) break; 1676 d++; 1677 } 1678 d_nnz[i] = d; 1679 o_nnz[i] = nz - d; 1680 } 1681 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1682 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1683 1684 values = (PetscScalar*)V; 1685 if (!values) { 1686 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 1687 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1688 } 1689 for (i=0; i<m; i++) { 1690 PetscInt row = i + rstart; 1691 PetscInt ncols = ii[i+1] - ii[i]; 1692 const PetscInt *icols = jj + ii[i]; 1693 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1694 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1695 } 1696 1697 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1698 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1699 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1700 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1701 PetscFunctionReturn(0); 1702 } 1703 EXTERN_C_END 1704 1705 EXTERN_C_BEGIN 1706 #if defined(PETSC_HAVE_MUMPS) 1707 extern PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*); 1708 #endif 1709 #if defined(PETSC_HAVE_PASTIX) 1710 extern PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1711 #endif 1712 EXTERN_C_END 1713 1714 /*MC 1715 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1716 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1717 the matrix is stored. 1718 1719 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1720 can call MatSetOption(Mat, MAT_HERMITIAN); 1721 1722 Options Database Keys: 1723 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1724 1725 Level: beginner 1726 1727 .seealso: MatCreateMPISBAIJ 1728 M*/ 1729 1730 EXTERN_C_BEGIN 1731 extern PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1732 EXTERN_C_END 1733 1734 EXTERN_C_BEGIN 1735 #undef __FUNCT__ 1736 #define __FUNCT__ "MatCreate_MPISBAIJ" 1737 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1738 { 1739 Mat_MPISBAIJ *b; 1740 PetscErrorCode ierr; 1741 PetscBool flg; 1742 1743 PetscFunctionBegin; 1744 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1745 B->data = (void*)b; 1746 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1747 1748 B->ops->destroy = MatDestroy_MPISBAIJ; 1749 B->ops->view = MatView_MPISBAIJ; 1750 B->assembled = PETSC_FALSE; 1751 B->insertmode = NOT_SET_VALUES; 1752 1753 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 1754 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 1755 1756 /* build local table of row and column ownerships */ 1757 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1758 1759 /* build cache for off array entries formed */ 1760 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 1761 1762 b->donotstash = PETSC_FALSE; 1763 b->colmap = NULL; 1764 b->garray = NULL; 1765 b->roworiented = PETSC_TRUE; 1766 1767 /* stuff used in block assembly */ 1768 b->barray = 0; 1769 1770 /* stuff used for matrix vector multiply */ 1771 b->lvec = 0; 1772 b->Mvctx = 0; 1773 b->slvec0 = 0; 1774 b->slvec0b = 0; 1775 b->slvec1 = 0; 1776 b->slvec1a = 0; 1777 b->slvec1b = 0; 1778 b->sMvctx = 0; 1779 1780 /* stuff for MatGetRow() */ 1781 b->rowindices = 0; 1782 b->rowvalues = 0; 1783 b->getrowactive = PETSC_FALSE; 1784 1785 /* hash table stuff */ 1786 b->ht = 0; 1787 b->hd = 0; 1788 b->ht_size = 0; 1789 b->ht_flag = PETSC_FALSE; 1790 b->ht_fact = 0; 1791 b->ht_total_ct = 0; 1792 b->ht_insert_ct = 0; 1793 1794 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1795 b->ijonly = PETSC_FALSE; 1796 1797 b->in_loc = 0; 1798 b->v_loc = 0; 1799 b->n_loc = 0; 1800 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1801 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 1802 if (flg) { 1803 PetscReal fact = 1.39; 1804 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1805 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 1806 if (fact <= 1.0) fact = 1.39; 1807 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1808 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1809 } 1810 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1811 1812 #if defined(PETSC_HAVE_PASTIX) 1813 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C","MatGetFactor_mpisbaij_pastix",MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1814 #endif 1815 #if defined(PETSC_HAVE_MUMPS) 1816 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C","MatGetFactor_sbaij_mumps",MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 1817 #endif 1818 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C","MatStoreValues_MPISBAIJ",MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1819 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C","MatRetrieveValues_MPISBAIJ",MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1820 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C","MatGetDiagonalBlock_MPISBAIJ",MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1821 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C","MatMPISBAIJSetPreallocation_MPISBAIJ",MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1822 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C","MatMPISBAIJSetPreallocationCSR_MPISBAIJ",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1823 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C","MatConvert_MPISBAIJ_MPISBSTRM",MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1824 1825 B->symmetric = PETSC_TRUE; 1826 B->structurally_symmetric = PETSC_TRUE; 1827 B->symmetric_set = PETSC_TRUE; 1828 B->structurally_symmetric_set = PETSC_TRUE; 1829 1830 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1831 PetscFunctionReturn(0); 1832 } 1833 EXTERN_C_END 1834 1835 /*MC 1836 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1837 1838 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1839 and MATMPISBAIJ otherwise. 1840 1841 Options Database Keys: 1842 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1843 1844 Level: beginner 1845 1846 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1847 M*/ 1848 1849 #undef __FUNCT__ 1850 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1851 /*@C 1852 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1853 the user should preallocate the matrix storage by setting the parameters 1854 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1855 performance can be increased by more than a factor of 50. 1856 1857 Collective on Mat 1858 1859 Input Parameters: 1860 + A - the matrix 1861 . bs - size of blockk 1862 . d_nz - number of block nonzeros per block row in diagonal portion of local 1863 submatrix (same for all local rows) 1864 . d_nnz - array containing the number of block nonzeros in the various block rows 1865 in the upper triangular and diagonal part of the in diagonal portion of the local 1866 (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room 1867 for the diagonal entry and set a value even if it is zero. 1868 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1869 submatrix (same for all local rows). 1870 - o_nnz - array containing the number of nonzeros in the various block rows of the 1871 off-diagonal portion of the local submatrix that is right of the diagonal 1872 (possibly different for each block row) or NULL. 1873 1874 1875 Options Database Keys: 1876 . -mat_no_unroll - uses code that does not unroll the loops in the 1877 block calculations (much slower) 1878 . -mat_block_size - size of the blocks to use 1879 1880 Notes: 1881 1882 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1883 than it must be used on all processors that share the object for that argument. 1884 1885 If the *_nnz parameter is given then the *_nz parameter is ignored 1886 1887 Storage Information: 1888 For a square global matrix we define each processor's diagonal portion 1889 to be its local rows and the corresponding columns (a square submatrix); 1890 each processor's off-diagonal portion encompasses the remainder of the 1891 local matrix (a rectangular submatrix). 1892 1893 The user can specify preallocated storage for the diagonal part of 1894 the local submatrix with either d_nz or d_nnz (not both). Set 1895 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 1896 memory allocation. Likewise, specify preallocated storage for the 1897 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1898 1899 You can call MatGetInfo() to get information on how effective the preallocation was; 1900 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1901 You can also run with the option -info and look for messages with the string 1902 malloc in them to see if additional memory allocation was needed. 1903 1904 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1905 the figure below we depict these three local rows and all columns (0-11). 1906 1907 .vb 1908 0 1 2 3 4 5 6 7 8 9 10 11 1909 ------------------- 1910 row 3 | . . . d d d o o o o o o 1911 row 4 | . . . d d d o o o o o o 1912 row 5 | . . . d d d o o o o o o 1913 ------------------- 1914 .ve 1915 1916 Thus, any entries in the d locations are stored in the d (diagonal) 1917 submatrix, and any entries in the o locations are stored in the 1918 o (off-diagonal) submatrix. Note that the d matrix is stored in 1919 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1920 1921 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1922 plus the diagonal part of the d matrix, 1923 and o_nz should indicate the number of block nonzeros per row in the o matrix 1924 1925 In general, for PDE problems in which most nonzeros are near the diagonal, 1926 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1927 or you will get TERRIBLE performance; see the users' manual chapter on 1928 matrices. 1929 1930 Level: intermediate 1931 1932 .keywords: matrix, block, aij, compressed row, sparse, parallel 1933 1934 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership() 1935 @*/ 1936 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1937 { 1938 PetscErrorCode ierr; 1939 1940 PetscFunctionBegin; 1941 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 1942 PetscValidType(B,1); 1943 PetscValidLogicalCollectiveInt(B,bs,2); 1944 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); 1945 PetscFunctionReturn(0); 1946 } 1947 1948 #undef __FUNCT__ 1949 #define __FUNCT__ "MatCreateSBAIJ" 1950 /*@C 1951 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1952 (block compressed row). For good matrix assembly performance 1953 the user should preallocate the matrix storage by setting the parameters 1954 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1955 performance can be increased by more than a factor of 50. 1956 1957 Collective on MPI_Comm 1958 1959 Input Parameters: 1960 + comm - MPI communicator 1961 . bs - size of blockk 1962 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1963 This value should be the same as the local size used in creating the 1964 y vector for the matrix-vector product y = Ax. 1965 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1966 This value should be the same as the local size used in creating the 1967 x vector for the matrix-vector product y = Ax. 1968 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1969 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1970 . d_nz - number of block nonzeros per block row in diagonal portion of local 1971 submatrix (same for all local rows) 1972 . d_nnz - array containing the number of block nonzeros in the various block rows 1973 in the upper triangular portion of the in diagonal portion of the local 1974 (possibly different for each block block row) or NULL. 1975 If you plan to factor the matrix you must leave room for the diagonal entry and 1976 set its value even if it is zero. 1977 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1978 submatrix (same for all local rows). 1979 - o_nnz - array containing the number of nonzeros in the various block rows of the 1980 off-diagonal portion of the local submatrix (possibly different for 1981 each block row) or NULL. 1982 1983 Output Parameter: 1984 . A - the matrix 1985 1986 Options Database Keys: 1987 . -mat_no_unroll - uses code that does not unroll the loops in the 1988 block calculations (much slower) 1989 . -mat_block_size - size of the blocks to use 1990 . -mat_mpi - use the parallel matrix data structures even on one processor 1991 (defaults to using SeqBAIJ format on one processor) 1992 1993 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1994 MatXXXXSetPreallocation() paradgm instead of this routine directly. 1995 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1996 1997 Notes: 1998 The number of rows and columns must be divisible by blocksize. 1999 This matrix type does not support complex Hermitian operation. 2000 2001 The user MUST specify either the local or global matrix dimensions 2002 (possibly both). 2003 2004 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2005 than it must be used on all processors that share the object for that argument. 2006 2007 If the *_nnz parameter is given then the *_nz parameter is ignored 2008 2009 Storage Information: 2010 For a square global matrix we define each processor's diagonal portion 2011 to be its local rows and the corresponding columns (a square submatrix); 2012 each processor's off-diagonal portion encompasses the remainder of the 2013 local matrix (a rectangular submatrix). 2014 2015 The user can specify preallocated storage for the diagonal part of 2016 the local submatrix with either d_nz or d_nnz (not both). Set 2017 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 2018 memory allocation. Likewise, specify preallocated storage for the 2019 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2020 2021 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2022 the figure below we depict these three local rows and all columns (0-11). 2023 2024 .vb 2025 0 1 2 3 4 5 6 7 8 9 10 11 2026 ------------------- 2027 row 3 | . . . d d d o o o o o o 2028 row 4 | . . . d d d o o o o o o 2029 row 5 | . . . d d d o o o o o o 2030 ------------------- 2031 .ve 2032 2033 Thus, any entries in the d locations are stored in the d (diagonal) 2034 submatrix, and any entries in the o locations are stored in the 2035 o (off-diagonal) submatrix. Note that the d matrix is stored in 2036 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2037 2038 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2039 plus the diagonal part of the d matrix, 2040 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2041 In general, for PDE problems in which most nonzeros are near the diagonal, 2042 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2043 or you will get TERRIBLE performance; see the users' manual chapter on 2044 matrices. 2045 2046 Level: intermediate 2047 2048 .keywords: matrix, block, aij, compressed row, sparse, parallel 2049 2050 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2051 @*/ 2052 2053 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) 2054 { 2055 PetscErrorCode ierr; 2056 PetscMPIInt size; 2057 2058 PetscFunctionBegin; 2059 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2060 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2061 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2062 if (size > 1) { 2063 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2064 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2065 } else { 2066 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2067 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2068 } 2069 PetscFunctionReturn(0); 2070 } 2071 2072 2073 #undef __FUNCT__ 2074 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2075 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2076 { 2077 Mat mat; 2078 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2079 PetscErrorCode ierr; 2080 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2081 PetscScalar *array; 2082 2083 PetscFunctionBegin; 2084 *newmat = 0; 2085 2086 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2087 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2088 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2089 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2090 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2091 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2092 2093 mat->factortype = matin->factortype; 2094 mat->preallocated = PETSC_TRUE; 2095 mat->assembled = PETSC_TRUE; 2096 mat->insertmode = NOT_SET_VALUES; 2097 2098 a = (Mat_MPISBAIJ*)mat->data; 2099 a->bs2 = oldmat->bs2; 2100 a->mbs = oldmat->mbs; 2101 a->nbs = oldmat->nbs; 2102 a->Mbs = oldmat->Mbs; 2103 a->Nbs = oldmat->Nbs; 2104 2105 2106 a->size = oldmat->size; 2107 a->rank = oldmat->rank; 2108 a->donotstash = oldmat->donotstash; 2109 a->roworiented = oldmat->roworiented; 2110 a->rowindices = 0; 2111 a->rowvalues = 0; 2112 a->getrowactive = PETSC_FALSE; 2113 a->barray = 0; 2114 a->rstartbs = oldmat->rstartbs; 2115 a->rendbs = oldmat->rendbs; 2116 a->cstartbs = oldmat->cstartbs; 2117 a->cendbs = oldmat->cendbs; 2118 2119 /* hash table stuff */ 2120 a->ht = 0; 2121 a->hd = 0; 2122 a->ht_size = 0; 2123 a->ht_flag = oldmat->ht_flag; 2124 a->ht_fact = oldmat->ht_fact; 2125 a->ht_total_ct = 0; 2126 a->ht_insert_ct = 0; 2127 2128 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2129 if (oldmat->colmap) { 2130 #if defined(PETSC_USE_CTABLE) 2131 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2132 #else 2133 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2134 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2135 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2136 #endif 2137 } else a->colmap = 0; 2138 2139 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2140 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2141 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2142 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2143 } else a->garray = 0; 2144 2145 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2146 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2147 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2148 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2149 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2150 2151 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2152 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2153 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2154 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2155 2156 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2157 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2158 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2159 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2160 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2161 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2162 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2163 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2164 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2165 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2166 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2167 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2168 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2169 2170 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2171 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2172 a->sMvctx = oldmat->sMvctx; 2173 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2174 2175 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2176 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2177 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2178 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2179 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2180 *newmat = mat; 2181 PetscFunctionReturn(0); 2182 } 2183 2184 #undef __FUNCT__ 2185 #define __FUNCT__ "MatLoad_MPISBAIJ" 2186 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2187 { 2188 PetscErrorCode ierr; 2189 PetscInt i,nz,j,rstart,rend; 2190 PetscScalar *vals,*buf; 2191 MPI_Comm comm; 2192 MPI_Status status; 2193 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2194 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2195 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2196 PetscInt bs =1,Mbs,mbs,extra_rows; 2197 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2198 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2199 int fd; 2200 2201 PetscFunctionBegin; 2202 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2203 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2204 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2205 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2206 2207 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2208 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2209 if (!rank) { 2210 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2211 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2212 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2213 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2214 } 2215 2216 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2217 2218 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2219 M = header[1]; 2220 N = header[2]; 2221 2222 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2223 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2224 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2225 2226 /* If global sizes are set, check if they are consistent with that given in the file */ 2227 if (sizesset) { 2228 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2229 } 2230 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); 2231 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); 2232 2233 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2234 2235 /* 2236 This code adds extra rows to make sure the number of rows is 2237 divisible by the blocksize 2238 */ 2239 Mbs = M/bs; 2240 extra_rows = bs - M + bs*(Mbs); 2241 if (extra_rows == bs) extra_rows = 0; 2242 else Mbs++; 2243 if (extra_rows &&!rank) { 2244 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2245 } 2246 2247 /* determine ownership of all rows */ 2248 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2249 mbs = Mbs/size + ((Mbs % size) > rank); 2250 m = mbs*bs; 2251 } else { /* User Set */ 2252 m = newmat->rmap->n; 2253 mbs = m/bs; 2254 } 2255 ierr = PetscMalloc2(size+1,PetscMPIInt,&rowners,size+1,PetscMPIInt,&browners);CHKERRQ(ierr); 2256 ierr = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr); 2257 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2258 rowners[0] = 0; 2259 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2260 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2261 rstart = rowners[rank]; 2262 rend = rowners[rank+1]; 2263 2264 /* distribute row lengths to all processors */ 2265 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2266 if (!rank) { 2267 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2268 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2269 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2270 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2271 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2272 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2273 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2274 } else { 2275 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2276 } 2277 2278 if (!rank) { /* procs[0] */ 2279 /* calculate the number of nonzeros on each processor */ 2280 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2281 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2282 for (i=0; i<size; i++) { 2283 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2284 procsnz[i] += rowlengths[j]; 2285 } 2286 } 2287 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2288 2289 /* determine max buffer needed and allocate it */ 2290 maxnz = 0; 2291 for (i=0; i<size; i++) { 2292 maxnz = PetscMax(maxnz,procsnz[i]); 2293 } 2294 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2295 2296 /* read in my part of the matrix column indices */ 2297 nz = procsnz[0]; 2298 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2299 mycols = ibuf; 2300 if (size == 1) nz -= extra_rows; 2301 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2302 if (size == 1) { 2303 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 2304 } 2305 2306 /* read in every ones (except the last) and ship off */ 2307 for (i=1; i<size-1; i++) { 2308 nz = procsnz[i]; 2309 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2310 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2311 } 2312 /* read in the stuff for the last proc */ 2313 if (size != 1) { 2314 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2315 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2316 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2317 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2318 } 2319 ierr = PetscFree(cols);CHKERRQ(ierr); 2320 } else { /* procs[i], i>0 */ 2321 /* determine buffer space needed for message */ 2322 nz = 0; 2323 for (i=0; i<m; i++) nz += locrowlens[i]; 2324 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2325 mycols = ibuf; 2326 /* receive message of column indices*/ 2327 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2328 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2329 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2330 } 2331 2332 /* loop over local rows, determining number of off diagonal entries */ 2333 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2334 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2335 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2336 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2337 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2338 rowcount = 0; 2339 nzcount = 0; 2340 for (i=0; i<mbs; i++) { 2341 dcount = 0; 2342 odcount = 0; 2343 for (j=0; j<bs; j++) { 2344 kmax = locrowlens[rowcount]; 2345 for (k=0; k<kmax; k++) { 2346 tmp = mycols[nzcount++]/bs; /* block col. index */ 2347 if (!mask[tmp]) { 2348 mask[tmp] = 1; 2349 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2350 else masked1[dcount++] = tmp; /* entry in diag portion */ 2351 } 2352 } 2353 rowcount++; 2354 } 2355 2356 dlens[i] = dcount; /* d_nzz[i] */ 2357 odlens[i] = odcount; /* o_nzz[i] */ 2358 2359 /* zero out the mask elements we set */ 2360 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2361 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2362 } 2363 if (!sizesset) { 2364 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2365 } 2366 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2367 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2368 2369 if (!rank) { 2370 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2371 /* read in my part of the matrix numerical values */ 2372 nz = procsnz[0]; 2373 vals = buf; 2374 mycols = ibuf; 2375 if (size == 1) nz -= extra_rows; 2376 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2377 if (size == 1) { 2378 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 2379 } 2380 2381 /* insert into matrix */ 2382 jj = rstart*bs; 2383 for (i=0; i<m; i++) { 2384 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2385 mycols += locrowlens[i]; 2386 vals += locrowlens[i]; 2387 jj++; 2388 } 2389 2390 /* read in other processors (except the last one) and ship out */ 2391 for (i=1; i<size-1; i++) { 2392 nz = procsnz[i]; 2393 vals = buf; 2394 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2395 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2396 } 2397 /* the last proc */ 2398 if (size != 1) { 2399 nz = procsnz[i] - extra_rows; 2400 vals = buf; 2401 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2402 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2403 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2404 } 2405 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2406 2407 } else { 2408 /* receive numeric values */ 2409 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2410 2411 /* receive message of values*/ 2412 vals = buf; 2413 mycols = ibuf; 2414 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2415 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2416 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2417 2418 /* insert into matrix */ 2419 jj = rstart*bs; 2420 for (i=0; i<m; i++) { 2421 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2422 mycols += locrowlens[i]; 2423 vals += locrowlens[i]; 2424 jj++; 2425 } 2426 } 2427 2428 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2429 ierr = PetscFree(buf);CHKERRQ(ierr); 2430 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2431 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2432 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2433 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2434 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2435 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2436 PetscFunctionReturn(0); 2437 } 2438 2439 #undef __FUNCT__ 2440 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2441 /*XXXXX@ 2442 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2443 2444 Input Parameters: 2445 . mat - the matrix 2446 . fact - factor 2447 2448 Not Collective on Mat, each process can have a different hash factor 2449 2450 Level: advanced 2451 2452 Notes: 2453 This can also be set by the command line option: -mat_use_hash_table fact 2454 2455 .keywords: matrix, hashtable, factor, HT 2456 2457 .seealso: MatSetOption() 2458 @XXXXX*/ 2459 2460 2461 #undef __FUNCT__ 2462 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2463 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2464 { 2465 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2466 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2467 PetscReal atmp; 2468 PetscReal *work,*svalues,*rvalues; 2469 PetscErrorCode ierr; 2470 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2471 PetscMPIInt rank,size; 2472 PetscInt *rowners_bs,dest,count,source; 2473 PetscScalar *va; 2474 MatScalar *ba; 2475 MPI_Status stat; 2476 2477 PetscFunctionBegin; 2478 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2479 ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr); 2480 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2481 2482 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2483 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2484 2485 bs = A->rmap->bs; 2486 mbs = a->mbs; 2487 Mbs = a->Mbs; 2488 ba = b->a; 2489 bi = b->i; 2490 bj = b->j; 2491 2492 /* find ownerships */ 2493 rowners_bs = A->rmap->range; 2494 2495 /* each proc creates an array to be distributed */ 2496 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2497 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2498 2499 /* row_max for B */ 2500 if (rank != size-1) { 2501 for (i=0; i<mbs; i++) { 2502 ncols = bi[1] - bi[0]; bi++; 2503 brow = bs*i; 2504 for (j=0; j<ncols; j++) { 2505 bcol = bs*(*bj); 2506 for (kcol=0; kcol<bs; kcol++) { 2507 col = bcol + kcol; /* local col index */ 2508 col += rowners_bs[rank+1]; /* global col index */ 2509 for (krow=0; krow<bs; krow++) { 2510 atmp = PetscAbsScalar(*ba); ba++; 2511 row = brow + krow; /* local row index */ 2512 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2513 if (work[col] < atmp) work[col] = atmp; 2514 } 2515 } 2516 bj++; 2517 } 2518 } 2519 2520 /* send values to its owners */ 2521 for (dest=rank+1; dest<size; dest++) { 2522 svalues = work + rowners_bs[dest]; 2523 count = rowners_bs[dest+1]-rowners_bs[dest]; 2524 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2525 } 2526 } 2527 2528 /* receive values */ 2529 if (rank) { 2530 rvalues = work; 2531 count = rowners_bs[rank+1]-rowners_bs[rank]; 2532 for (source=0; source<rank; source++) { 2533 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr); 2534 /* process values */ 2535 for (i=0; i<count; i++) { 2536 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2537 } 2538 } 2539 } 2540 2541 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2542 ierr = PetscFree(work);CHKERRQ(ierr); 2543 PetscFunctionReturn(0); 2544 } 2545 2546 #undef __FUNCT__ 2547 #define __FUNCT__ "MatSOR_MPISBAIJ" 2548 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2549 { 2550 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2551 PetscErrorCode ierr; 2552 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2553 PetscScalar *x,*ptr,*from; 2554 Vec bb1; 2555 const PetscScalar *b; 2556 2557 PetscFunctionBegin; 2558 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); 2559 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2560 2561 if (flag == SOR_APPLY_UPPER) { 2562 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2563 PetscFunctionReturn(0); 2564 } 2565 2566 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2567 if (flag & SOR_ZERO_INITIAL_GUESS) { 2568 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2569 its--; 2570 } 2571 2572 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2573 while (its--) { 2574 2575 /* lower triangular part: slvec0b = - B^T*xx */ 2576 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2577 2578 /* copy xx into slvec0a */ 2579 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2580 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2581 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2582 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2583 2584 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2585 2586 /* copy bb into slvec1a */ 2587 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2588 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2589 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2590 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2591 2592 /* set slvec1b = 0 */ 2593 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2594 2595 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2596 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2597 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2598 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2599 2600 /* upper triangular part: bb1 = bb1 - B*x */ 2601 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2602 2603 /* local diagonal sweep */ 2604 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2605 } 2606 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2607 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2608 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2609 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2610 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2611 } else if (flag & SOR_EISENSTAT) { 2612 Vec xx1; 2613 PetscBool hasop; 2614 const PetscScalar *diag; 2615 PetscScalar *sl,scale = (omega - 2.0)/omega; 2616 PetscInt i,n; 2617 2618 if (!mat->xx1) { 2619 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2620 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2621 } 2622 xx1 = mat->xx1; 2623 bb1 = mat->bb1; 2624 2625 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2626 2627 if (!mat->diag) { 2628 /* this is wrong for same matrix with new nonzero values */ 2629 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 2630 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2631 } 2632 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2633 2634 if (hasop) { 2635 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2636 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2637 } else { 2638 /* 2639 These two lines are replaced by code that may be a bit faster for a good compiler 2640 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2641 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2642 */ 2643 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2644 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2645 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2646 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2647 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2648 if (omega == 1.0) { 2649 for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i]; 2650 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2651 } else { 2652 for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i]; 2653 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2654 } 2655 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2656 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2657 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2658 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2659 } 2660 2661 /* multiply off-diagonal portion of matrix */ 2662 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2663 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2664 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2665 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2666 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2667 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2668 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2669 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2670 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2671 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2672 2673 /* local sweep */ 2674 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); 2675 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2676 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2677 PetscFunctionReturn(0); 2678 } 2679 2680 #undef __FUNCT__ 2681 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2682 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2683 { 2684 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2685 PetscErrorCode ierr; 2686 Vec lvec1,bb1; 2687 2688 PetscFunctionBegin; 2689 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); 2690 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2691 2692 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2693 if (flag & SOR_ZERO_INITIAL_GUESS) { 2694 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2695 its--; 2696 } 2697 2698 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2699 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2700 while (its--) { 2701 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2702 2703 /* lower diagonal part: bb1 = bb - B^T*xx */ 2704 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2705 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2706 2707 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2708 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2709 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2710 2711 /* upper diagonal part: bb1 = bb1 - B*x */ 2712 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2713 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2714 2715 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2716 2717 /* diagonal sweep */ 2718 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2719 } 2720 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2721 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2722 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2723 PetscFunctionReturn(0); 2724 } 2725 2726 #undef __FUNCT__ 2727 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2728 /*@ 2729 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2730 CSR format the local rows. 2731 2732 Collective on MPI_Comm 2733 2734 Input Parameters: 2735 + comm - MPI communicator 2736 . bs - the block size, only a block size of 1 is supported 2737 . m - number of local rows (Cannot be PETSC_DECIDE) 2738 . n - This value should be the same as the local size used in creating the 2739 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2740 calculated if N is given) For square matrices n is almost always m. 2741 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2742 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2743 . i - row indices 2744 . j - column indices 2745 - a - matrix values 2746 2747 Output Parameter: 2748 . mat - the matrix 2749 2750 Level: intermediate 2751 2752 Notes: 2753 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2754 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2755 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2756 2757 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2758 2759 .keywords: matrix, aij, compressed row, sparse, parallel 2760 2761 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2762 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2763 @*/ 2764 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) 2765 { 2766 PetscErrorCode ierr; 2767 2768 2769 PetscFunctionBegin; 2770 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2771 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2772 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2773 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2774 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2775 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2776 PetscFunctionReturn(0); 2777 } 2778 2779 2780 #undef __FUNCT__ 2781 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2782 /*@C 2783 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2784 (the default parallel PETSc format). 2785 2786 Collective on MPI_Comm 2787 2788 Input Parameters: 2789 + A - the matrix 2790 . bs - the block size 2791 . i - the indices into j for the start of each local row (starts with zero) 2792 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2793 - v - optional values in the matrix 2794 2795 Level: developer 2796 2797 .keywords: matrix, aij, compressed row, sparse, parallel 2798 2799 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2800 @*/ 2801 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2802 { 2803 PetscErrorCode ierr; 2804 2805 PetscFunctionBegin; 2806 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2807 PetscFunctionReturn(0); 2808 } 2809 2810 2811