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 #undef __FUNCT__ 605 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 606 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 607 { 608 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 609 PetscErrorCode ierr; 610 PetscInt bs = mat->rmap->bs; 611 PetscMPIInt size = baij->size,rank = baij->rank; 612 PetscBool iascii,isdraw; 613 PetscViewer sviewer; 614 PetscViewerFormat format; 615 616 PetscFunctionBegin; 617 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 618 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 619 if (iascii) { 620 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 621 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 622 MatInfo info; 623 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 624 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 625 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 626 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); 627 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 628 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 629 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 630 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 631 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 632 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 633 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 634 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 635 PetscFunctionReturn(0); 636 } else if (format == PETSC_VIEWER_ASCII_INFO) { 637 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 638 PetscFunctionReturn(0); 639 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 640 PetscFunctionReturn(0); 641 } 642 } 643 644 if (isdraw) { 645 PetscDraw draw; 646 PetscBool isnull; 647 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 648 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 649 } 650 651 if (size == 1) { 652 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 653 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 654 } else { 655 /* assemble the entire matrix onto first processor. */ 656 Mat A; 657 Mat_SeqSBAIJ *Aloc; 658 Mat_SeqBAIJ *Bloc; 659 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 660 MatScalar *a; 661 662 /* Should this be the same type as mat? */ 663 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 664 if (!rank) { 665 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 666 } else { 667 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 668 } 669 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 670 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 671 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 672 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 673 674 /* copy over the A part */ 675 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 676 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 677 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 678 679 for (i=0; i<mbs; i++) { 680 rvals[0] = bs*(baij->rstartbs + i); 681 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 682 for (j=ai[i]; j<ai[i+1]; j++) { 683 col = (baij->cstartbs+aj[j])*bs; 684 for (k=0; k<bs; k++) { 685 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 686 col++; 687 a += bs; 688 } 689 } 690 } 691 /* copy over the B part */ 692 Bloc = (Mat_SeqBAIJ*)baij->B->data; 693 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 694 for (i=0; i<mbs; i++) { 695 696 rvals[0] = bs*(baij->rstartbs + i); 697 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 698 for (j=ai[i]; j<ai[i+1]; j++) { 699 col = baij->garray[aj[j]]*bs; 700 for (k=0; k<bs; k++) { 701 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 702 col++; 703 a += bs; 704 } 705 } 706 } 707 ierr = PetscFree(rvals);CHKERRQ(ierr); 708 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 709 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 710 /* 711 Everyone has to call to draw the matrix since the graphics waits are 712 synchronized across all processors that share the PetscDraw object 713 */ 714 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 715 if (!rank) { 716 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 717 /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/ 718 PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ); 719 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 720 } 721 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 722 ierr = MatDestroy(&A);CHKERRQ(ierr); 723 } 724 PetscFunctionReturn(0); 725 } 726 727 #undef __FUNCT__ 728 #define __FUNCT__ "MatView_MPISBAIJ" 729 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 730 { 731 PetscErrorCode ierr; 732 PetscBool iascii,isdraw,issocket,isbinary; 733 734 PetscFunctionBegin; 735 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 736 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 737 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 738 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 739 if (iascii || isdraw || issocket || isbinary) { 740 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 741 } 742 PetscFunctionReturn(0); 743 } 744 745 #undef __FUNCT__ 746 #define __FUNCT__ "MatDestroy_MPISBAIJ" 747 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 748 { 749 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 750 PetscErrorCode ierr; 751 752 PetscFunctionBegin; 753 #if defined(PETSC_USE_LOG) 754 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 755 #endif 756 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 757 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 758 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 759 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 760 #if defined(PETSC_USE_CTABLE) 761 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 762 #else 763 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 764 #endif 765 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 766 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 767 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 768 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 770 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 771 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 772 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 773 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 774 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 775 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 776 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 777 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 778 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 779 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 780 #if defined(PETSC_USE_REAL_MAT_SINGLE) 781 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 782 #endif 783 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 784 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 785 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 786 ierr = PetscFree(mat->data);CHKERRQ(ierr); 787 788 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 789 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",NULL);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",NULL);CHKERRQ(ierr); 791 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",NULL);CHKERRQ(ierr); 792 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",NULL);CHKERRQ(ierr); 793 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C","",NULL);CHKERRQ(ierr); 794 PetscFunctionReturn(0); 795 } 796 797 #undef __FUNCT__ 798 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 799 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 800 { 801 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 802 PetscErrorCode ierr; 803 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 804 PetscScalar *x,*from; 805 806 PetscFunctionBegin; 807 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 808 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 809 810 /* diagonal part */ 811 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 812 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 813 814 /* subdiagonal part */ 815 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 816 817 /* copy x into the vec slvec0 */ 818 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 819 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 820 821 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 822 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 823 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 824 825 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 826 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 827 /* supperdiagonal part */ 828 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 829 PetscFunctionReturn(0); 830 } 831 832 #undef __FUNCT__ 833 #define __FUNCT__ "MatMult_MPISBAIJ" 834 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 835 { 836 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 837 PetscErrorCode ierr; 838 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 839 PetscScalar *x,*from; 840 841 PetscFunctionBegin; 842 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 843 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 844 845 /* diagonal part */ 846 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 847 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 848 849 /* subdiagonal part */ 850 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 851 852 /* copy x into the vec slvec0 */ 853 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 854 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 855 856 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 857 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 858 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 859 860 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 861 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 862 /* supperdiagonal part */ 863 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 864 PetscFunctionReturn(0); 865 } 866 867 #undef __FUNCT__ 868 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 869 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 870 { 871 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 872 PetscErrorCode ierr; 873 PetscInt nt; 874 875 PetscFunctionBegin; 876 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 877 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 878 879 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 880 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 881 882 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 883 /* do diagonal part */ 884 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 885 /* do supperdiagonal part */ 886 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 887 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 888 /* do subdiagonal part */ 889 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 890 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 891 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 892 PetscFunctionReturn(0); 893 } 894 895 #undef __FUNCT__ 896 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 897 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 898 { 899 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 900 PetscErrorCode ierr; 901 PetscInt mbs=a->mbs,bs=A->rmap->bs; 902 PetscScalar *x,*from,zero=0.0; 903 904 PetscFunctionBegin; 905 /* 906 PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n"); 907 PetscSynchronizedFlush(PetscObjectComm((PetscObject)A)); 908 */ 909 /* diagonal part */ 910 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 911 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 912 913 /* subdiagonal part */ 914 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 915 916 /* copy x into the vec slvec0 */ 917 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 918 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 919 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 920 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 921 922 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 923 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 924 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 925 926 /* supperdiagonal part */ 927 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 928 PetscFunctionReturn(0); 929 } 930 931 #undef __FUNCT__ 932 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 933 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 934 { 935 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 936 PetscErrorCode ierr; 937 938 PetscFunctionBegin; 939 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 940 /* do diagonal part */ 941 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 942 /* do supperdiagonal part */ 943 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 944 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 945 946 /* do subdiagonal part */ 947 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 948 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 949 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 950 PetscFunctionReturn(0); 951 } 952 953 /* 954 This only works correctly for square matrices where the subblock A->A is the 955 diagonal block 956 */ 957 #undef __FUNCT__ 958 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 959 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 960 { 961 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 962 PetscErrorCode ierr; 963 964 PetscFunctionBegin; 965 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 966 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 967 PetscFunctionReturn(0); 968 } 969 970 #undef __FUNCT__ 971 #define __FUNCT__ "MatScale_MPISBAIJ" 972 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 973 { 974 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 975 PetscErrorCode ierr; 976 977 PetscFunctionBegin; 978 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 979 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 980 PetscFunctionReturn(0); 981 } 982 983 #undef __FUNCT__ 984 #define __FUNCT__ "MatGetRow_MPISBAIJ" 985 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 986 { 987 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 988 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 989 PetscErrorCode ierr; 990 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 991 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 992 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 993 994 PetscFunctionBegin; 995 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 996 mat->getrowactive = PETSC_TRUE; 997 998 if (!mat->rowvalues && (idx || v)) { 999 /* 1000 allocate enough space to hold information from the longest row. 1001 */ 1002 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1003 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1004 PetscInt max = 1,mbs = mat->mbs,tmp; 1005 for (i=0; i<mbs; i++) { 1006 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1007 if (max < tmp) max = tmp; 1008 } 1009 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1010 } 1011 1012 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1013 lrow = row - brstart; /* local row index */ 1014 1015 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1016 if (!v) {pvA = 0; pvB = 0;} 1017 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1018 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1019 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1020 nztot = nzA + nzB; 1021 1022 cmap = mat->garray; 1023 if (v || idx) { 1024 if (nztot) { 1025 /* Sort by increasing column numbers, assuming A and B already sorted */ 1026 PetscInt imark = -1; 1027 if (v) { 1028 *v = v_p = mat->rowvalues; 1029 for (i=0; i<nzB; i++) { 1030 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1031 else break; 1032 } 1033 imark = i; 1034 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1035 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1036 } 1037 if (idx) { 1038 *idx = idx_p = mat->rowindices; 1039 if (imark > -1) { 1040 for (i=0; i<imark; i++) { 1041 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1042 } 1043 } else { 1044 for (i=0; i<nzB; i++) { 1045 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1046 else break; 1047 } 1048 imark = i; 1049 } 1050 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1051 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1052 } 1053 } else { 1054 if (idx) *idx = 0; 1055 if (v) *v = 0; 1056 } 1057 } 1058 *nz = nztot; 1059 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1060 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1061 PetscFunctionReturn(0); 1062 } 1063 1064 #undef __FUNCT__ 1065 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1066 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1067 { 1068 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1069 1070 PetscFunctionBegin; 1071 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1072 baij->getrowactive = PETSC_FALSE; 1073 PetscFunctionReturn(0); 1074 } 1075 1076 #undef __FUNCT__ 1077 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1078 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1079 { 1080 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1081 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1082 1083 PetscFunctionBegin; 1084 aA->getrow_utriangular = PETSC_TRUE; 1085 PetscFunctionReturn(0); 1086 } 1087 #undef __FUNCT__ 1088 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1089 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1090 { 1091 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1092 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1093 1094 PetscFunctionBegin; 1095 aA->getrow_utriangular = PETSC_FALSE; 1096 PetscFunctionReturn(0); 1097 } 1098 1099 #undef __FUNCT__ 1100 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1101 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1102 { 1103 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1104 PetscErrorCode ierr; 1105 1106 PetscFunctionBegin; 1107 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1108 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1109 PetscFunctionReturn(0); 1110 } 1111 1112 #undef __FUNCT__ 1113 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1114 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1115 { 1116 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1117 PetscErrorCode ierr; 1118 1119 PetscFunctionBegin; 1120 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1121 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1122 PetscFunctionReturn(0); 1123 } 1124 1125 #undef __FUNCT__ 1126 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1127 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1128 { 1129 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1130 PetscErrorCode ierr; 1131 1132 PetscFunctionBegin; 1133 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1134 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1135 PetscFunctionReturn(0); 1136 } 1137 1138 #undef __FUNCT__ 1139 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1140 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1141 { 1142 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1143 Mat A = a->A,B = a->B; 1144 PetscErrorCode ierr; 1145 PetscReal isend[5],irecv[5]; 1146 1147 PetscFunctionBegin; 1148 info->block_size = (PetscReal)matin->rmap->bs; 1149 1150 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1151 1152 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1153 isend[3] = info->memory; isend[4] = info->mallocs; 1154 1155 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1156 1157 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1158 isend[3] += info->memory; isend[4] += info->mallocs; 1159 if (flag == MAT_LOCAL) { 1160 info->nz_used = isend[0]; 1161 info->nz_allocated = isend[1]; 1162 info->nz_unneeded = isend[2]; 1163 info->memory = isend[3]; 1164 info->mallocs = isend[4]; 1165 } else if (flag == MAT_GLOBAL_MAX) { 1166 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1167 1168 info->nz_used = irecv[0]; 1169 info->nz_allocated = irecv[1]; 1170 info->nz_unneeded = irecv[2]; 1171 info->memory = irecv[3]; 1172 info->mallocs = irecv[4]; 1173 } else if (flag == MAT_GLOBAL_SUM) { 1174 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1175 1176 info->nz_used = irecv[0]; 1177 info->nz_allocated = irecv[1]; 1178 info->nz_unneeded = irecv[2]; 1179 info->memory = irecv[3]; 1180 info->mallocs = irecv[4]; 1181 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1182 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1183 info->fill_ratio_needed = 0; 1184 info->factor_mallocs = 0; 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #undef __FUNCT__ 1189 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1190 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1191 { 1192 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1193 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1194 PetscErrorCode ierr; 1195 1196 PetscFunctionBegin; 1197 switch (op) { 1198 case MAT_NEW_NONZERO_LOCATIONS: 1199 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1200 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1201 case MAT_KEEP_NONZERO_PATTERN: 1202 case MAT_NEW_NONZERO_LOCATION_ERR: 1203 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1204 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1205 break; 1206 case MAT_ROW_ORIENTED: 1207 a->roworiented = flg; 1208 1209 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1210 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1211 break; 1212 case MAT_NEW_DIAGONALS: 1213 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1214 break; 1215 case MAT_IGNORE_OFF_PROC_ENTRIES: 1216 a->donotstash = flg; 1217 break; 1218 case MAT_USE_HASH_TABLE: 1219 a->ht_flag = flg; 1220 break; 1221 case MAT_HERMITIAN: 1222 if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first"); 1223 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1224 1225 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1226 break; 1227 case MAT_SPD: 1228 A->spd_set = PETSC_TRUE; 1229 A->spd = flg; 1230 if (flg) { 1231 A->symmetric = PETSC_TRUE; 1232 A->structurally_symmetric = PETSC_TRUE; 1233 A->symmetric_set = PETSC_TRUE; 1234 A->structurally_symmetric_set = PETSC_TRUE; 1235 } 1236 break; 1237 case MAT_SYMMETRIC: 1238 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1239 break; 1240 case MAT_STRUCTURALLY_SYMMETRIC: 1241 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1242 break; 1243 case MAT_SYMMETRY_ETERNAL: 1244 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1245 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1246 break; 1247 case MAT_IGNORE_LOWER_TRIANGULAR: 1248 aA->ignore_ltriangular = flg; 1249 break; 1250 case MAT_ERROR_LOWER_TRIANGULAR: 1251 aA->ignore_ltriangular = flg; 1252 break; 1253 case MAT_GETROW_UPPERTRIANGULAR: 1254 aA->getrow_utriangular = flg; 1255 break; 1256 default: 1257 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1258 } 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #undef __FUNCT__ 1263 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1264 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1265 { 1266 PetscErrorCode ierr; 1267 1268 PetscFunctionBegin; 1269 if (MAT_INITIAL_MATRIX || *B != A) { 1270 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1271 } 1272 PetscFunctionReturn(0); 1273 } 1274 1275 #undef __FUNCT__ 1276 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1277 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1278 { 1279 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1280 Mat a = baij->A, b=baij->B; 1281 PetscErrorCode ierr; 1282 PetscInt nv,m,n; 1283 PetscBool flg; 1284 1285 PetscFunctionBegin; 1286 if (ll != rr) { 1287 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1288 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1289 } 1290 if (!ll) PetscFunctionReturn(0); 1291 1292 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1293 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1294 1295 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1296 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1297 1298 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1299 1300 /* left diagonalscale the off-diagonal part */ 1301 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1302 1303 /* scale the diagonal part */ 1304 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1305 1306 /* right diagonalscale the off-diagonal part */ 1307 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1308 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1309 PetscFunctionReturn(0); 1310 } 1311 1312 #undef __FUNCT__ 1313 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1314 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1315 { 1316 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1317 PetscErrorCode ierr; 1318 1319 PetscFunctionBegin; 1320 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1321 PetscFunctionReturn(0); 1322 } 1323 1324 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*); 1325 1326 #undef __FUNCT__ 1327 #define __FUNCT__ "MatEqual_MPISBAIJ" 1328 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1329 { 1330 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1331 Mat a,b,c,d; 1332 PetscBool flg; 1333 PetscErrorCode ierr; 1334 1335 PetscFunctionBegin; 1336 a = matA->A; b = matA->B; 1337 c = matB->A; d = matB->B; 1338 1339 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1340 if (flg) { 1341 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1342 } 1343 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1344 PetscFunctionReturn(0); 1345 } 1346 1347 #undef __FUNCT__ 1348 #define __FUNCT__ "MatCopy_MPISBAIJ" 1349 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1350 { 1351 PetscErrorCode ierr; 1352 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1353 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data; 1354 1355 PetscFunctionBegin; 1356 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1357 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1358 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1359 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1360 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1361 } else { 1362 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1363 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1364 } 1365 PetscFunctionReturn(0); 1366 } 1367 1368 #undef __FUNCT__ 1369 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1370 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1371 { 1372 PetscErrorCode ierr; 1373 1374 PetscFunctionBegin; 1375 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1376 PetscFunctionReturn(0); 1377 } 1378 1379 #undef __FUNCT__ 1380 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1381 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1382 { 1383 PetscErrorCode ierr; 1384 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data; 1385 PetscBLASInt bnz,one=1; 1386 Mat_SeqSBAIJ *xa,*ya; 1387 Mat_SeqBAIJ *xb,*yb; 1388 1389 PetscFunctionBegin; 1390 if (str == SAME_NONZERO_PATTERN) { 1391 PetscScalar alpha = a; 1392 xa = (Mat_SeqSBAIJ*)xx->A->data; 1393 ya = (Mat_SeqSBAIJ*)yy->A->data; 1394 ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr); 1395 PetscStackCall("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one)); 1396 xb = (Mat_SeqBAIJ*)xx->B->data; 1397 yb = (Mat_SeqBAIJ*)yy->B->data; 1398 ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr); 1399 PetscStackCall("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one)); 1400 } else { 1401 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1402 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1403 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1404 } 1405 PetscFunctionReturn(0); 1406 } 1407 1408 #undef __FUNCT__ 1409 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1410 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1411 { 1412 PetscErrorCode ierr; 1413 PetscInt i; 1414 PetscBool flg; 1415 1416 PetscFunctionBegin; 1417 for (i=0; i<n; i++) { 1418 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1419 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1420 } 1421 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1422 PetscFunctionReturn(0); 1423 } 1424 1425 1426 /* -------------------------------------------------------------------*/ 1427 static struct _MatOps MatOps_Values = { 1428 MatSetValues_MPISBAIJ, 1429 MatGetRow_MPISBAIJ, 1430 MatRestoreRow_MPISBAIJ, 1431 MatMult_MPISBAIJ, 1432 /* 4*/ MatMultAdd_MPISBAIJ, 1433 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1434 MatMultAdd_MPISBAIJ, 1435 0, 1436 0, 1437 0, 1438 /* 10*/ 0, 1439 0, 1440 0, 1441 MatSOR_MPISBAIJ, 1442 MatTranspose_MPISBAIJ, 1443 /* 15*/ MatGetInfo_MPISBAIJ, 1444 MatEqual_MPISBAIJ, 1445 MatGetDiagonal_MPISBAIJ, 1446 MatDiagonalScale_MPISBAIJ, 1447 MatNorm_MPISBAIJ, 1448 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1449 MatAssemblyEnd_MPISBAIJ, 1450 MatSetOption_MPISBAIJ, 1451 MatZeroEntries_MPISBAIJ, 1452 /* 24*/ 0, 1453 0, 1454 0, 1455 0, 1456 0, 1457 /* 29*/ MatSetUp_MPISBAIJ, 1458 0, 1459 0, 1460 0, 1461 0, 1462 /* 34*/ MatDuplicate_MPISBAIJ, 1463 0, 1464 0, 1465 0, 1466 0, 1467 /* 39*/ MatAXPY_MPISBAIJ, 1468 MatGetSubMatrices_MPISBAIJ, 1469 MatIncreaseOverlap_MPISBAIJ, 1470 MatGetValues_MPISBAIJ, 1471 MatCopy_MPISBAIJ, 1472 /* 44*/ 0, 1473 MatScale_MPISBAIJ, 1474 0, 1475 0, 1476 0, 1477 /* 49*/ 0, 1478 0, 1479 0, 1480 0, 1481 0, 1482 /* 54*/ 0, 1483 0, 1484 MatSetUnfactored_MPISBAIJ, 1485 0, 1486 MatSetValuesBlocked_MPISBAIJ, 1487 /* 59*/ 0, 1488 0, 1489 0, 1490 0, 1491 0, 1492 /* 64*/ 0, 1493 0, 1494 0, 1495 0, 1496 0, 1497 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1498 0, 1499 0, 1500 0, 1501 0, 1502 /* 74*/ 0, 1503 0, 1504 0, 1505 0, 1506 0, 1507 /* 79*/ 0, 1508 0, 1509 0, 1510 0, 1511 MatLoad_MPISBAIJ, 1512 /* 84*/ 0, 1513 0, 1514 0, 1515 0, 1516 0, 1517 /* 89*/ 0, 1518 0, 1519 0, 1520 0, 1521 0, 1522 /* 94*/ 0, 1523 0, 1524 0, 1525 0, 1526 0, 1527 /* 99*/ 0, 1528 0, 1529 0, 1530 0, 1531 0, 1532 /*104*/ 0, 1533 MatRealPart_MPISBAIJ, 1534 MatImaginaryPart_MPISBAIJ, 1535 MatGetRowUpperTriangular_MPISBAIJ, 1536 MatRestoreRowUpperTriangular_MPISBAIJ, 1537 /*109*/ 0, 1538 0, 1539 0, 1540 0, 1541 0, 1542 /*114*/ 0, 1543 0, 1544 0, 1545 0, 1546 0, 1547 /*119*/ 0, 1548 0, 1549 0, 1550 0 1551 }; 1552 1553 1554 EXTERN_C_BEGIN 1555 #undef __FUNCT__ 1556 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1557 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1558 { 1559 PetscFunctionBegin; 1560 *a = ((Mat_MPISBAIJ*)A->data)->A; 1561 PetscFunctionReturn(0); 1562 } 1563 EXTERN_C_END 1564 1565 EXTERN_C_BEGIN 1566 #undef __FUNCT__ 1567 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1568 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1569 { 1570 Mat_MPISBAIJ *b; 1571 PetscErrorCode ierr; 1572 PetscInt i,mbs,Mbs; 1573 1574 PetscFunctionBegin; 1575 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1576 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1577 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1578 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1579 1580 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1581 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1582 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1583 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1584 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1585 1586 if (d_nnz) { 1587 for (i=0; i<B->rmap->n/bs; i++) { 1588 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]); 1589 } 1590 } 1591 if (o_nnz) { 1592 for (i=0; i<B->rmap->n/bs; i++) { 1593 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]); 1594 } 1595 } 1596 1597 b = (Mat_MPISBAIJ*)B->data; 1598 mbs = B->rmap->n/bs; 1599 Mbs = B->rmap->N/bs; 1600 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); 1601 1602 B->rmap->bs = bs; 1603 b->bs2 = bs*bs; 1604 b->mbs = mbs; 1605 b->nbs = mbs; 1606 b->Mbs = Mbs; 1607 b->Nbs = Mbs; 1608 1609 for (i=0; i<=b->size; i++) { 1610 b->rangebs[i] = B->rmap->range[i]/bs; 1611 } 1612 b->rstartbs = B->rmap->rstart/bs; 1613 b->rendbs = B->rmap->rend/bs; 1614 1615 b->cstartbs = B->cmap->rstart/bs; 1616 b->cendbs = B->cmap->rend/bs; 1617 1618 if (!B->preallocated) { 1619 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1620 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1621 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1622 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1623 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1624 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1625 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1626 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1627 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 1628 } 1629 1630 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1631 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1632 1633 B->preallocated = PETSC_TRUE; 1634 PetscFunctionReturn(0); 1635 } 1636 EXTERN_C_END 1637 1638 EXTERN_C_BEGIN 1639 #undef __FUNCT__ 1640 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1641 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1642 { 1643 PetscInt m,rstart,cstart,cend; 1644 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1645 const PetscInt *JJ =0; 1646 PetscScalar *values=0; 1647 PetscErrorCode ierr; 1648 1649 PetscFunctionBegin; 1650 if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1651 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1652 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1653 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1654 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1655 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1656 m = B->rmap->n/bs; 1657 rstart = B->rmap->rstart/bs; 1658 cstart = B->cmap->rstart/bs; 1659 cend = B->cmap->rend/bs; 1660 1661 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1662 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 1663 for (i=0; i<m; i++) { 1664 nz = ii[i+1] - ii[i]; 1665 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1666 nz_max = PetscMax(nz_max,nz); 1667 JJ = jj + ii[i]; 1668 for (j=0; j<nz; j++) { 1669 if (*JJ >= cstart) break; 1670 JJ++; 1671 } 1672 d = 0; 1673 for (; j<nz; j++) { 1674 if (*JJ++ >= cend) break; 1675 d++; 1676 } 1677 d_nnz[i] = d; 1678 o_nnz[i] = nz - d; 1679 } 1680 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1681 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1682 1683 values = (PetscScalar*)V; 1684 if (!values) { 1685 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 1686 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1687 } 1688 for (i=0; i<m; i++) { 1689 PetscInt row = i + rstart; 1690 PetscInt ncols = ii[i+1] - ii[i]; 1691 const PetscInt *icols = jj + ii[i]; 1692 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1693 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1694 } 1695 1696 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1697 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1698 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1699 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1700 PetscFunctionReturn(0); 1701 } 1702 EXTERN_C_END 1703 1704 EXTERN_C_BEGIN 1705 #if defined(PETSC_HAVE_MUMPS) 1706 extern PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*); 1707 #endif 1708 #if defined(PETSC_HAVE_PASTIX) 1709 extern PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1710 #endif 1711 EXTERN_C_END 1712 1713 /*MC 1714 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1715 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1716 the matrix is stored. 1717 1718 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1719 can call MatSetOption(Mat, MAT_HERMITIAN); 1720 1721 Options Database Keys: 1722 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1723 1724 Level: beginner 1725 1726 .seealso: MatCreateMPISBAIJ 1727 M*/ 1728 1729 EXTERN_C_BEGIN 1730 extern PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1731 EXTERN_C_END 1732 1733 EXTERN_C_BEGIN 1734 #undef __FUNCT__ 1735 #define __FUNCT__ "MatCreate_MPISBAIJ" 1736 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1737 { 1738 Mat_MPISBAIJ *b; 1739 PetscErrorCode ierr; 1740 PetscBool flg; 1741 1742 PetscFunctionBegin; 1743 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1744 B->data = (void*)b; 1745 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1746 1747 B->ops->destroy = MatDestroy_MPISBAIJ; 1748 B->ops->view = MatView_MPISBAIJ; 1749 B->assembled = PETSC_FALSE; 1750 B->insertmode = NOT_SET_VALUES; 1751 1752 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 1753 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 1754 1755 /* build local table of row and column ownerships */ 1756 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1757 1758 /* build cache for off array entries formed */ 1759 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 1760 1761 b->donotstash = PETSC_FALSE; 1762 b->colmap = NULL; 1763 b->garray = NULL; 1764 b->roworiented = PETSC_TRUE; 1765 1766 /* stuff used in block assembly */ 1767 b->barray = 0; 1768 1769 /* stuff used for matrix vector multiply */ 1770 b->lvec = 0; 1771 b->Mvctx = 0; 1772 b->slvec0 = 0; 1773 b->slvec0b = 0; 1774 b->slvec1 = 0; 1775 b->slvec1a = 0; 1776 b->slvec1b = 0; 1777 b->sMvctx = 0; 1778 1779 /* stuff for MatGetRow() */ 1780 b->rowindices = 0; 1781 b->rowvalues = 0; 1782 b->getrowactive = PETSC_FALSE; 1783 1784 /* hash table stuff */ 1785 b->ht = 0; 1786 b->hd = 0; 1787 b->ht_size = 0; 1788 b->ht_flag = PETSC_FALSE; 1789 b->ht_fact = 0; 1790 b->ht_total_ct = 0; 1791 b->ht_insert_ct = 0; 1792 1793 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1794 b->ijonly = PETSC_FALSE; 1795 1796 b->in_loc = 0; 1797 b->v_loc = 0; 1798 b->n_loc = 0; 1799 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1800 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 1801 if (flg) { 1802 PetscReal fact = 1.39; 1803 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1804 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 1805 if (fact <= 1.0) fact = 1.39; 1806 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1807 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1808 } 1809 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1810 1811 #if defined(PETSC_HAVE_PASTIX) 1812 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 1813 "MatGetFactor_mpisbaij_pastix", 1814 MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1815 #endif 1816 #if defined(PETSC_HAVE_MUMPS) 1817 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 1818 "MatGetFactor_sbaij_mumps", 1819 MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 1820 #endif 1821 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1822 "MatStoreValues_MPISBAIJ", 1823 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1824 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1825 "MatRetrieveValues_MPISBAIJ", 1826 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1827 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1828 "MatGetDiagonalBlock_MPISBAIJ", 1829 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1830 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1831 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1832 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1833 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C", 1834 "MatMPISBAIJSetPreallocationCSR_MPISBAIJ", 1835 MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1836 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C", 1837 "MatConvert_MPISBAIJ_MPISBSTRM", 1838 MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1839 1840 B->symmetric = PETSC_TRUE; 1841 B->structurally_symmetric = PETSC_TRUE; 1842 B->symmetric_set = PETSC_TRUE; 1843 B->structurally_symmetric_set = PETSC_TRUE; 1844 1845 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1846 PetscFunctionReturn(0); 1847 } 1848 EXTERN_C_END 1849 1850 /*MC 1851 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1852 1853 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1854 and MATMPISBAIJ otherwise. 1855 1856 Options Database Keys: 1857 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1858 1859 Level: beginner 1860 1861 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1862 M*/ 1863 1864 #undef __FUNCT__ 1865 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1866 /*@C 1867 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1868 the user should preallocate the matrix storage by setting the parameters 1869 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1870 performance can be increased by more than a factor of 50. 1871 1872 Collective on Mat 1873 1874 Input Parameters: 1875 + A - the matrix 1876 . bs - size of blockk 1877 . d_nz - number of block nonzeros per block row in diagonal portion of local 1878 submatrix (same for all local rows) 1879 . d_nnz - array containing the number of block nonzeros in the various block rows 1880 in the upper triangular and diagonal part of the in diagonal portion of the local 1881 (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room 1882 for the diagonal entry and set a value even if it is zero. 1883 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1884 submatrix (same for all local rows). 1885 - o_nnz - array containing the number of nonzeros in the various block rows of the 1886 off-diagonal portion of the local submatrix that is right of the diagonal 1887 (possibly different for each block row) or NULL. 1888 1889 1890 Options Database Keys: 1891 . -mat_no_unroll - uses code that does not unroll the loops in the 1892 block calculations (much slower) 1893 . -mat_block_size - size of the blocks to use 1894 1895 Notes: 1896 1897 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1898 than it must be used on all processors that share the object for that argument. 1899 1900 If the *_nnz parameter is given then the *_nz parameter is ignored 1901 1902 Storage Information: 1903 For a square global matrix we define each processor's diagonal portion 1904 to be its local rows and the corresponding columns (a square submatrix); 1905 each processor's off-diagonal portion encompasses the remainder of the 1906 local matrix (a rectangular submatrix). 1907 1908 The user can specify preallocated storage for the diagonal part of 1909 the local submatrix with either d_nz or d_nnz (not both). Set 1910 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 1911 memory allocation. Likewise, specify preallocated storage for the 1912 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1913 1914 You can call MatGetInfo() to get information on how effective the preallocation was; 1915 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1916 You can also run with the option -info and look for messages with the string 1917 malloc in them to see if additional memory allocation was needed. 1918 1919 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1920 the figure below we depict these three local rows and all columns (0-11). 1921 1922 .vb 1923 0 1 2 3 4 5 6 7 8 9 10 11 1924 ------------------- 1925 row 3 | . . . d d d o o o o o o 1926 row 4 | . . . d d d o o o o o o 1927 row 5 | . . . d d d o o o o o o 1928 ------------------- 1929 .ve 1930 1931 Thus, any entries in the d locations are stored in the d (diagonal) 1932 submatrix, and any entries in the o locations are stored in the 1933 o (off-diagonal) submatrix. Note that the d matrix is stored in 1934 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1935 1936 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1937 plus the diagonal part of the d matrix, 1938 and o_nz should indicate the number of block nonzeros per row in the o matrix 1939 1940 In general, for PDE problems in which most nonzeros are near the diagonal, 1941 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1942 or you will get TERRIBLE performance; see the users' manual chapter on 1943 matrices. 1944 1945 Level: intermediate 1946 1947 .keywords: matrix, block, aij, compressed row, sparse, parallel 1948 1949 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership() 1950 @*/ 1951 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1952 { 1953 PetscErrorCode ierr; 1954 1955 PetscFunctionBegin; 1956 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 1957 PetscValidType(B,1); 1958 PetscValidLogicalCollectiveInt(B,bs,2); 1959 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); 1960 PetscFunctionReturn(0); 1961 } 1962 1963 #undef __FUNCT__ 1964 #define __FUNCT__ "MatCreateSBAIJ" 1965 /*@C 1966 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1967 (block compressed row). For good matrix assembly performance 1968 the user should preallocate the matrix storage by setting the parameters 1969 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1970 performance can be increased by more than a factor of 50. 1971 1972 Collective on MPI_Comm 1973 1974 Input Parameters: 1975 + comm - MPI communicator 1976 . bs - size of blockk 1977 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1978 This value should be the same as the local size used in creating the 1979 y vector for the matrix-vector product y = Ax. 1980 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1981 This value should be the same as the local size used in creating the 1982 x vector for the matrix-vector product y = Ax. 1983 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1984 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1985 . d_nz - number of block nonzeros per block row in diagonal portion of local 1986 submatrix (same for all local rows) 1987 . d_nnz - array containing the number of block nonzeros in the various block rows 1988 in the upper triangular portion of the in diagonal portion of the local 1989 (possibly different for each block block row) or NULL. 1990 If you plan to factor the matrix you must leave room for the diagonal entry and 1991 set its value even if it is zero. 1992 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1993 submatrix (same for all local rows). 1994 - o_nnz - array containing the number of nonzeros in the various block rows of the 1995 off-diagonal portion of the local submatrix (possibly different for 1996 each block row) or NULL. 1997 1998 Output Parameter: 1999 . A - the matrix 2000 2001 Options Database Keys: 2002 . -mat_no_unroll - uses code that does not unroll the loops in the 2003 block calculations (much slower) 2004 . -mat_block_size - size of the blocks to use 2005 . -mat_mpi - use the parallel matrix data structures even on one processor 2006 (defaults to using SeqBAIJ format on one processor) 2007 2008 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2009 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2010 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2011 2012 Notes: 2013 The number of rows and columns must be divisible by blocksize. 2014 This matrix type does not support complex Hermitian operation. 2015 2016 The user MUST specify either the local or global matrix dimensions 2017 (possibly both). 2018 2019 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2020 than it must be used on all processors that share the object for that argument. 2021 2022 If the *_nnz parameter is given then the *_nz parameter is ignored 2023 2024 Storage Information: 2025 For a square global matrix we define each processor's diagonal portion 2026 to be its local rows and the corresponding columns (a square submatrix); 2027 each processor's off-diagonal portion encompasses the remainder of the 2028 local matrix (a rectangular submatrix). 2029 2030 The user can specify preallocated storage for the diagonal part of 2031 the local submatrix with either d_nz or d_nnz (not both). Set 2032 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 2033 memory allocation. Likewise, specify preallocated storage for the 2034 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2035 2036 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2037 the figure below we depict these three local rows and all columns (0-11). 2038 2039 .vb 2040 0 1 2 3 4 5 6 7 8 9 10 11 2041 ------------------- 2042 row 3 | . . . d d d o o o o o o 2043 row 4 | . . . d d d o o o o o o 2044 row 5 | . . . d d d o o o o o o 2045 ------------------- 2046 .ve 2047 2048 Thus, any entries in the d locations are stored in the d (diagonal) 2049 submatrix, and any entries in the o locations are stored in the 2050 o (off-diagonal) submatrix. Note that the d matrix is stored in 2051 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2052 2053 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2054 plus the diagonal part of the d matrix, 2055 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2056 In general, for PDE problems in which most nonzeros are near the diagonal, 2057 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2058 or you will get TERRIBLE performance; see the users' manual chapter on 2059 matrices. 2060 2061 Level: intermediate 2062 2063 .keywords: matrix, block, aij, compressed row, sparse, parallel 2064 2065 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2066 @*/ 2067 2068 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) 2069 { 2070 PetscErrorCode ierr; 2071 PetscMPIInt size; 2072 2073 PetscFunctionBegin; 2074 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2075 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2076 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2077 if (size > 1) { 2078 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2079 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2080 } else { 2081 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2082 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2083 } 2084 PetscFunctionReturn(0); 2085 } 2086 2087 2088 #undef __FUNCT__ 2089 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2090 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2091 { 2092 Mat mat; 2093 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2094 PetscErrorCode ierr; 2095 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2096 PetscScalar *array; 2097 2098 PetscFunctionBegin; 2099 *newmat = 0; 2100 2101 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2102 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2103 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2104 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2105 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2106 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2107 2108 mat->factortype = matin->factortype; 2109 mat->preallocated = PETSC_TRUE; 2110 mat->assembled = PETSC_TRUE; 2111 mat->insertmode = NOT_SET_VALUES; 2112 2113 a = (Mat_MPISBAIJ*)mat->data; 2114 a->bs2 = oldmat->bs2; 2115 a->mbs = oldmat->mbs; 2116 a->nbs = oldmat->nbs; 2117 a->Mbs = oldmat->Mbs; 2118 a->Nbs = oldmat->Nbs; 2119 2120 2121 a->size = oldmat->size; 2122 a->rank = oldmat->rank; 2123 a->donotstash = oldmat->donotstash; 2124 a->roworiented = oldmat->roworiented; 2125 a->rowindices = 0; 2126 a->rowvalues = 0; 2127 a->getrowactive = PETSC_FALSE; 2128 a->barray = 0; 2129 a->rstartbs = oldmat->rstartbs; 2130 a->rendbs = oldmat->rendbs; 2131 a->cstartbs = oldmat->cstartbs; 2132 a->cendbs = oldmat->cendbs; 2133 2134 /* hash table stuff */ 2135 a->ht = 0; 2136 a->hd = 0; 2137 a->ht_size = 0; 2138 a->ht_flag = oldmat->ht_flag; 2139 a->ht_fact = oldmat->ht_fact; 2140 a->ht_total_ct = 0; 2141 a->ht_insert_ct = 0; 2142 2143 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2144 if (oldmat->colmap) { 2145 #if defined(PETSC_USE_CTABLE) 2146 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2147 #else 2148 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2149 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2150 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2151 #endif 2152 } else a->colmap = 0; 2153 2154 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2155 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2156 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2157 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2158 } else a->garray = 0; 2159 2160 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2161 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2162 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2163 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2164 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2165 2166 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2167 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2168 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2169 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2170 2171 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2172 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2173 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2174 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2175 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2176 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2177 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2178 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2179 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2180 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2181 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2182 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2183 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2184 2185 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2186 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2187 a->sMvctx = oldmat->sMvctx; 2188 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2189 2190 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2191 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2192 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2193 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2194 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2195 *newmat = mat; 2196 PetscFunctionReturn(0); 2197 } 2198 2199 #undef __FUNCT__ 2200 #define __FUNCT__ "MatLoad_MPISBAIJ" 2201 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2202 { 2203 PetscErrorCode ierr; 2204 PetscInt i,nz,j,rstart,rend; 2205 PetscScalar *vals,*buf; 2206 MPI_Comm comm; 2207 MPI_Status status; 2208 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2209 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2210 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2211 PetscInt bs =1,Mbs,mbs,extra_rows; 2212 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2213 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2214 int fd; 2215 2216 PetscFunctionBegin; 2217 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2218 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2219 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2220 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2221 2222 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2223 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2224 if (!rank) { 2225 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2226 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2227 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2228 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2229 } 2230 2231 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2232 2233 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2234 M = header[1]; 2235 N = header[2]; 2236 2237 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2238 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2239 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2240 2241 /* If global sizes are set, check if they are consistent with that given in the file */ 2242 if (sizesset) { 2243 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2244 } 2245 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); 2246 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); 2247 2248 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2249 2250 /* 2251 This code adds extra rows to make sure the number of rows is 2252 divisible by the blocksize 2253 */ 2254 Mbs = M/bs; 2255 extra_rows = bs - M + bs*(Mbs); 2256 if (extra_rows == bs) extra_rows = 0; 2257 else Mbs++; 2258 if (extra_rows &&!rank) { 2259 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2260 } 2261 2262 /* determine ownership of all rows */ 2263 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2264 mbs = Mbs/size + ((Mbs % size) > rank); 2265 m = mbs*bs; 2266 } else { /* User Set */ 2267 m = newmat->rmap->n; 2268 mbs = m/bs; 2269 } 2270 ierr = PetscMalloc2(size+1,PetscMPIInt,&rowners,size+1,PetscMPIInt,&browners);CHKERRQ(ierr); 2271 ierr = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr); 2272 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2273 rowners[0] = 0; 2274 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2275 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2276 rstart = rowners[rank]; 2277 rend = rowners[rank+1]; 2278 2279 /* distribute row lengths to all processors */ 2280 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2281 if (!rank) { 2282 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2283 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2284 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2285 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2286 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2287 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2288 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2289 } else { 2290 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2291 } 2292 2293 if (!rank) { /* procs[0] */ 2294 /* calculate the number of nonzeros on each processor */ 2295 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2296 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2297 for (i=0; i<size; i++) { 2298 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2299 procsnz[i] += rowlengths[j]; 2300 } 2301 } 2302 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2303 2304 /* determine max buffer needed and allocate it */ 2305 maxnz = 0; 2306 for (i=0; i<size; i++) { 2307 maxnz = PetscMax(maxnz,procsnz[i]); 2308 } 2309 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2310 2311 /* read in my part of the matrix column indices */ 2312 nz = procsnz[0]; 2313 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2314 mycols = ibuf; 2315 if (size == 1) nz -= extra_rows; 2316 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2317 if (size == 1) { 2318 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 2319 } 2320 2321 /* read in every ones (except the last) and ship off */ 2322 for (i=1; i<size-1; i++) { 2323 nz = procsnz[i]; 2324 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2325 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2326 } 2327 /* read in the stuff for the last proc */ 2328 if (size != 1) { 2329 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2330 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2331 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2332 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2333 } 2334 ierr = PetscFree(cols);CHKERRQ(ierr); 2335 } else { /* procs[i], i>0 */ 2336 /* determine buffer space needed for message */ 2337 nz = 0; 2338 for (i=0; i<m; i++) nz += locrowlens[i]; 2339 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2340 mycols = ibuf; 2341 /* receive message of column indices*/ 2342 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2343 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2344 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2345 } 2346 2347 /* loop over local rows, determining number of off diagonal entries */ 2348 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2349 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2350 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2351 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2352 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2353 rowcount = 0; 2354 nzcount = 0; 2355 for (i=0; i<mbs; i++) { 2356 dcount = 0; 2357 odcount = 0; 2358 for (j=0; j<bs; j++) { 2359 kmax = locrowlens[rowcount]; 2360 for (k=0; k<kmax; k++) { 2361 tmp = mycols[nzcount++]/bs; /* block col. index */ 2362 if (!mask[tmp]) { 2363 mask[tmp] = 1; 2364 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2365 else masked1[dcount++] = tmp; /* entry in diag portion */ 2366 } 2367 } 2368 rowcount++; 2369 } 2370 2371 dlens[i] = dcount; /* d_nzz[i] */ 2372 odlens[i] = odcount; /* o_nzz[i] */ 2373 2374 /* zero out the mask elements we set */ 2375 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2376 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2377 } 2378 if (!sizesset) { 2379 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2380 } 2381 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2382 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2383 2384 if (!rank) { 2385 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2386 /* read in my part of the matrix numerical values */ 2387 nz = procsnz[0]; 2388 vals = buf; 2389 mycols = ibuf; 2390 if (size == 1) nz -= extra_rows; 2391 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2392 if (size == 1) { 2393 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 2394 } 2395 2396 /* insert into matrix */ 2397 jj = rstart*bs; 2398 for (i=0; i<m; i++) { 2399 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2400 mycols += locrowlens[i]; 2401 vals += locrowlens[i]; 2402 jj++; 2403 } 2404 2405 /* read in other processors (except the last one) and ship out */ 2406 for (i=1; i<size-1; i++) { 2407 nz = procsnz[i]; 2408 vals = buf; 2409 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2410 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2411 } 2412 /* the last proc */ 2413 if (size != 1) { 2414 nz = procsnz[i] - extra_rows; 2415 vals = buf; 2416 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2417 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2418 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2419 } 2420 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2421 2422 } else { 2423 /* receive numeric values */ 2424 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2425 2426 /* receive message of values*/ 2427 vals = buf; 2428 mycols = ibuf; 2429 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2430 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2431 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2432 2433 /* insert into matrix */ 2434 jj = rstart*bs; 2435 for (i=0; i<m; i++) { 2436 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2437 mycols += locrowlens[i]; 2438 vals += locrowlens[i]; 2439 jj++; 2440 } 2441 } 2442 2443 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2444 ierr = PetscFree(buf);CHKERRQ(ierr); 2445 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2446 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2447 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2448 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2449 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2450 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2451 PetscFunctionReturn(0); 2452 } 2453 2454 #undef __FUNCT__ 2455 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2456 /*XXXXX@ 2457 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2458 2459 Input Parameters: 2460 . mat - the matrix 2461 . fact - factor 2462 2463 Not Collective on Mat, each process can have a different hash factor 2464 2465 Level: advanced 2466 2467 Notes: 2468 This can also be set by the command line option: -mat_use_hash_table fact 2469 2470 .keywords: matrix, hashtable, factor, HT 2471 2472 .seealso: MatSetOption() 2473 @XXXXX*/ 2474 2475 2476 #undef __FUNCT__ 2477 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2478 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2479 { 2480 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2481 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2482 PetscReal atmp; 2483 PetscReal *work,*svalues,*rvalues; 2484 PetscErrorCode ierr; 2485 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2486 PetscMPIInt rank,size; 2487 PetscInt *rowners_bs,dest,count,source; 2488 PetscScalar *va; 2489 MatScalar *ba; 2490 MPI_Status stat; 2491 2492 PetscFunctionBegin; 2493 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2494 ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr); 2495 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2496 2497 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2498 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2499 2500 bs = A->rmap->bs; 2501 mbs = a->mbs; 2502 Mbs = a->Mbs; 2503 ba = b->a; 2504 bi = b->i; 2505 bj = b->j; 2506 2507 /* find ownerships */ 2508 rowners_bs = A->rmap->range; 2509 2510 /* each proc creates an array to be distributed */ 2511 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2512 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2513 2514 /* row_max for B */ 2515 if (rank != size-1) { 2516 for (i=0; i<mbs; i++) { 2517 ncols = bi[1] - bi[0]; bi++; 2518 brow = bs*i; 2519 for (j=0; j<ncols; j++) { 2520 bcol = bs*(*bj); 2521 for (kcol=0; kcol<bs; kcol++) { 2522 col = bcol + kcol; /* local col index */ 2523 col += rowners_bs[rank+1]; /* global col index */ 2524 for (krow=0; krow<bs; krow++) { 2525 atmp = PetscAbsScalar(*ba); ba++; 2526 row = brow + krow; /* local row index */ 2527 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2528 if (work[col] < atmp) work[col] = atmp; 2529 } 2530 } 2531 bj++; 2532 } 2533 } 2534 2535 /* send values to its owners */ 2536 for (dest=rank+1; dest<size; dest++) { 2537 svalues = work + rowners_bs[dest]; 2538 count = rowners_bs[dest+1]-rowners_bs[dest]; 2539 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2540 } 2541 } 2542 2543 /* receive values */ 2544 if (rank) { 2545 rvalues = work; 2546 count = rowners_bs[rank+1]-rowners_bs[rank]; 2547 for (source=0; source<rank; source++) { 2548 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr); 2549 /* process values */ 2550 for (i=0; i<count; i++) { 2551 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2552 } 2553 } 2554 } 2555 2556 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2557 ierr = PetscFree(work);CHKERRQ(ierr); 2558 PetscFunctionReturn(0); 2559 } 2560 2561 #undef __FUNCT__ 2562 #define __FUNCT__ "MatSOR_MPISBAIJ" 2563 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2564 { 2565 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2566 PetscErrorCode ierr; 2567 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2568 PetscScalar *x,*ptr,*from; 2569 Vec bb1; 2570 const PetscScalar *b; 2571 2572 PetscFunctionBegin; 2573 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); 2574 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2575 2576 if (flag == SOR_APPLY_UPPER) { 2577 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2578 PetscFunctionReturn(0); 2579 } 2580 2581 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2582 if (flag & SOR_ZERO_INITIAL_GUESS) { 2583 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2584 its--; 2585 } 2586 2587 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2588 while (its--) { 2589 2590 /* lower triangular part: slvec0b = - B^T*xx */ 2591 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2592 2593 /* copy xx into slvec0a */ 2594 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2595 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2596 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2597 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2598 2599 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2600 2601 /* copy bb into slvec1a */ 2602 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2603 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2604 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2605 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2606 2607 /* set slvec1b = 0 */ 2608 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2609 2610 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2611 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2612 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2613 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2614 2615 /* upper triangular part: bb1 = bb1 - B*x */ 2616 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2617 2618 /* local diagonal sweep */ 2619 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2620 } 2621 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2622 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2624 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2625 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2626 } else if (flag & SOR_EISENSTAT) { 2627 Vec xx1; 2628 PetscBool hasop; 2629 const PetscScalar *diag; 2630 PetscScalar *sl,scale = (omega - 2.0)/omega; 2631 PetscInt i,n; 2632 2633 if (!mat->xx1) { 2634 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2635 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2636 } 2637 xx1 = mat->xx1; 2638 bb1 = mat->bb1; 2639 2640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2641 2642 if (!mat->diag) { 2643 /* this is wrong for same matrix with new nonzero values */ 2644 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 2645 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2646 } 2647 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2648 2649 if (hasop) { 2650 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2651 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2652 } else { 2653 /* 2654 These two lines are replaced by code that may be a bit faster for a good compiler 2655 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2656 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2657 */ 2658 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2659 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2660 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2661 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2662 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2663 if (omega == 1.0) { 2664 for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i]; 2665 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2666 } else { 2667 for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i]; 2668 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2669 } 2670 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2671 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2672 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2673 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2674 } 2675 2676 /* multiply off-diagonal portion of matrix */ 2677 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2678 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2679 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2680 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2681 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2682 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2683 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2684 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2685 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2686 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2687 2688 /* local sweep */ 2689 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); 2690 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2691 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2692 PetscFunctionReturn(0); 2693 } 2694 2695 #undef __FUNCT__ 2696 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2697 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2698 { 2699 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2700 PetscErrorCode ierr; 2701 Vec lvec1,bb1; 2702 2703 PetscFunctionBegin; 2704 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); 2705 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2706 2707 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2708 if (flag & SOR_ZERO_INITIAL_GUESS) { 2709 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2710 its--; 2711 } 2712 2713 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2714 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2715 while (its--) { 2716 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2717 2718 /* lower diagonal part: bb1 = bb - B^T*xx */ 2719 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2720 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2721 2722 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2723 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2724 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2725 2726 /* upper diagonal part: bb1 = bb1 - B*x */ 2727 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2728 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2729 2730 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2731 2732 /* diagonal sweep */ 2733 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2734 } 2735 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2736 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2737 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2738 PetscFunctionReturn(0); 2739 } 2740 2741 #undef __FUNCT__ 2742 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2743 /*@ 2744 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2745 CSR format the local rows. 2746 2747 Collective on MPI_Comm 2748 2749 Input Parameters: 2750 + comm - MPI communicator 2751 . bs - the block size, only a block size of 1 is supported 2752 . m - number of local rows (Cannot be PETSC_DECIDE) 2753 . n - This value should be the same as the local size used in creating the 2754 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2755 calculated if N is given) For square matrices n is almost always m. 2756 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2757 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2758 . i - row indices 2759 . j - column indices 2760 - a - matrix values 2761 2762 Output Parameter: 2763 . mat - the matrix 2764 2765 Level: intermediate 2766 2767 Notes: 2768 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2769 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2770 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2771 2772 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2773 2774 .keywords: matrix, aij, compressed row, sparse, parallel 2775 2776 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2777 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2778 @*/ 2779 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) 2780 { 2781 PetscErrorCode ierr; 2782 2783 2784 PetscFunctionBegin; 2785 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2786 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2787 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2788 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2789 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2790 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2791 PetscFunctionReturn(0); 2792 } 2793 2794 2795 #undef __FUNCT__ 2796 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2797 /*@C 2798 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2799 (the default parallel PETSc format). 2800 2801 Collective on MPI_Comm 2802 2803 Input Parameters: 2804 + A - the matrix 2805 . bs - the block size 2806 . i - the indices into j for the start of each local row (starts with zero) 2807 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2808 - v - optional values in the matrix 2809 2810 Level: developer 2811 2812 .keywords: matrix, aij, compressed row, sparse, parallel 2813 2814 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2815 @*/ 2816 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2817 { 2818 PetscErrorCode ierr; 2819 2820 PetscFunctionBegin; 2821 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2822 PetscFunctionReturn(0); 2823 } 2824 2825 2826