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 = PETSC_NULL; 164 MatScalar *v_loc = PETSC_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 baij->n_loc = n; 175 } 176 in_loc = baij->in_loc; 177 v_loc = baij->v_loc; 178 } 179 180 for (i=0; i<m; i++) { 181 if (im[i] < 0) continue; 182 #if defined(PETSC_USE_DEBUG) 183 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); 184 #endif 185 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 186 row = im[i] - rstart_orig; /* local row index */ 187 for (j=0; j<n; j++) { 188 if (im[i]/bs > in[j]/bs) { 189 if (a->ignore_ltriangular) { 190 continue; /* ignore lower triangular blocks */ 191 } else { 192 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 } 195 if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */ 196 col = in[j] - cstart_orig; /* local col index */ 197 brow = row/bs; bcol = col/bs; 198 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 199 if (roworiented) value = v[i*n+j]; 200 else value = v[i+j*m]; 201 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 202 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 203 } else if (in[j] < 0) continue; 204 #if defined(PETSC_USE_DEBUG) 205 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); 206 #endif 207 else { /* off-diag entry (B) */ 208 if (mat->was_assembled) { 209 if (!baij->colmap) { 210 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 211 } 212 #if defined (PETSC_USE_CTABLE) 213 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 214 col = col - 1; 215 #else 216 col = baij->colmap[in[j]/bs] - 1; 217 #endif 218 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 219 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 220 col = in[j]; 221 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 222 B = baij->B; 223 b = (Mat_SeqBAIJ*)(B)->data; 224 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 225 ba=b->a; 226 } else col += in[j]%bs; 227 } else col = in[j]; 228 if (roworiented) value = v[i*n+j]; 229 else value = v[i+j*m]; 230 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 231 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 232 } 233 } 234 } else { /* off processor entry */ 235 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]); 236 if (!baij->donotstash) { 237 mat->assembled = PETSC_FALSE; 238 n_loc = 0; 239 for (j=0; j<n; j++) { 240 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 241 in_loc[n_loc] = in[j]; 242 if (roworiented) { 243 v_loc[n_loc] = v[i*n+j]; 244 } else { 245 v_loc[n_loc] = v[j*m+i]; 246 } 247 n_loc++; 248 } 249 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);CHKERRQ(ierr); 250 } 251 } 252 } 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 258 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 259 { 260 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 261 const MatScalar *value; 262 MatScalar *barray=baij->barray; 263 PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular; 264 PetscErrorCode ierr; 265 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 266 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 267 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 268 269 PetscFunctionBegin; 270 if (!barray) { 271 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 272 baij->barray = barray; 273 } 274 275 if (roworiented) { 276 stepval = (n-1)*bs; 277 } else { 278 stepval = (m-1)*bs; 279 } 280 for (i=0; i<m; i++) { 281 if (im[i] < 0) continue; 282 #if defined(PETSC_USE_DEBUG) 283 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); 284 #endif 285 if (im[i] >= rstart && im[i] < rend) { 286 row = im[i] - rstart; 287 for (j=0; j<n; j++) { 288 if (im[i] > in[j]) { 289 if (ignore_ltriangular) continue; /* ignore lower triangular blocks */ 290 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)"); 291 } 292 /* If NumCol = 1 then a copy is not required */ 293 if ((roworiented) && (n == 1)) { 294 barray = (MatScalar*) v + i*bs2; 295 } else if ((!roworiented) && (m == 1)) { 296 barray = (MatScalar*) v + j*bs2; 297 } else { /* Here a copy is required */ 298 if (roworiented) { 299 value = v + i*(stepval+bs)*bs + j*bs; 300 } else { 301 value = v + j*(stepval+bs)*bs + i*bs; 302 } 303 for (ii=0; ii<bs; ii++,value+=stepval) { 304 for (jj=0; jj<bs; jj++) { 305 *barray++ = *value++; 306 } 307 } 308 barray -=bs2; 309 } 310 311 if (in[j] >= cstart && in[j] < cend) { 312 col = in[j] - cstart; 313 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 314 } 315 else if (in[j] < 0) continue; 316 #if defined(PETSC_USE_DEBUG) 317 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); 318 #endif 319 else { 320 if (mat->was_assembled) { 321 if (!baij->colmap) { 322 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 323 } 324 325 #if defined(PETSC_USE_DEBUG) 326 #if defined (PETSC_USE_CTABLE) 327 { PetscInt data; 328 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 329 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 330 } 331 #else 332 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 333 #endif 334 #endif 335 #if defined (PETSC_USE_CTABLE) 336 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 337 col = (col - 1)/bs; 338 #else 339 col = (baij->colmap[in[j]] - 1)/bs; 340 #endif 341 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 342 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 343 col = in[j]; 344 } 345 } 346 else col = in[j]; 347 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 348 } 349 } 350 } else { 351 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]); 352 if (!baij->donotstash) { 353 if (roworiented) { 354 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 355 } else { 356 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 357 } 358 } 359 } 360 } 361 PetscFunctionReturn(0); 362 } 363 364 #undef __FUNCT__ 365 #define __FUNCT__ "MatGetValues_MPISBAIJ" 366 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 367 { 368 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 369 PetscErrorCode ierr; 370 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 371 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 372 373 PetscFunctionBegin; 374 for (i=0; i<m; i++) { 375 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 376 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); 377 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 378 row = idxm[i] - bsrstart; 379 for (j=0; j<n; j++) { 380 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 381 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); 382 if (idxn[j] >= bscstart && idxn[j] < bscend) { 383 col = idxn[j] - bscstart; 384 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 385 } else { 386 if (!baij->colmap) { 387 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 388 } 389 #if defined (PETSC_USE_CTABLE) 390 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 391 data --; 392 #else 393 data = baij->colmap[idxn[j]/bs]-1; 394 #endif 395 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 396 else { 397 col = data + idxn[j]%bs; 398 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 399 } 400 } 401 } 402 } else { 403 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 404 } 405 } 406 PetscFunctionReturn(0); 407 } 408 409 #undef __FUNCT__ 410 #define __FUNCT__ "MatNorm_MPISBAIJ" 411 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 412 { 413 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 414 PetscErrorCode ierr; 415 PetscReal sum[2],*lnorm2; 416 417 PetscFunctionBegin; 418 if (baij->size == 1) { 419 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 420 } else { 421 if (type == NORM_FROBENIUS) { 422 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 423 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 424 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 425 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 426 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 427 ierr = MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 428 *norm = PetscSqrtReal(sum[0] + 2*sum[1]); 429 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 430 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 431 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 432 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 433 PetscReal *rsum,*rsum2,vabs; 434 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 435 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 436 MatScalar *v; 437 438 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&rsum,mat->cmap->N,PetscReal,&rsum2);CHKERRQ(ierr); 439 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 440 /* Amat */ 441 v = amat->a; jj = amat->j; 442 for (brow=0; brow<mbs; brow++) { 443 grow = bs*(rstart + brow); 444 nz = amat->i[brow+1] - amat->i[brow]; 445 for (bcol=0; bcol<nz; bcol++) { 446 gcol = bs*(rstart + *jj); jj++; 447 for (col=0; col<bs; col++) { 448 for (row=0; row<bs; row++) { 449 vabs = PetscAbsScalar(*v); v++; 450 rsum[gcol+col] += vabs; 451 /* non-diagonal block */ 452 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 453 } 454 } 455 } 456 } 457 /* Bmat */ 458 v = bmat->a; jj = bmat->j; 459 for (brow=0; brow<mbs; brow++) { 460 grow = bs*(rstart + brow); 461 nz = bmat->i[brow+1] - bmat->i[brow]; 462 for (bcol=0; bcol<nz; bcol++) { 463 gcol = bs*garray[*jj]; jj++; 464 for (col=0; col<bs; col++) { 465 for (row=0; row<bs; row++) { 466 vabs = PetscAbsScalar(*v); v++; 467 rsum[gcol+col] += vabs; 468 rsum[grow+row] += vabs; 469 } 470 } 471 } 472 } 473 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 474 *norm = 0.0; 475 for (col=0; col<mat->cmap->N; col++) { 476 if (rsum2[col] > *norm) *norm = rsum2[col]; 477 } 478 ierr = PetscFree2(rsum,rsum2);CHKERRQ(ierr); 479 } else { 480 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet"); 481 } 482 } 483 PetscFunctionReturn(0); 484 } 485 486 #undef __FUNCT__ 487 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 488 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 489 { 490 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 491 PetscErrorCode ierr; 492 PetscInt nstash,reallocs; 493 InsertMode addv; 494 495 PetscFunctionBegin; 496 if (baij->donotstash || mat->nooffprocentries) { 497 PetscFunctionReturn(0); 498 } 499 500 /* make sure all processors are either in INSERTMODE or ADDMODE */ 501 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 502 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 503 mat->insertmode = addv; /* in case this processor had no cache */ 504 505 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 506 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 507 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 508 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 509 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 510 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 511 PetscFunctionReturn(0); 512 } 513 514 #undef __FUNCT__ 515 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 516 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 517 { 518 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 519 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 520 PetscErrorCode ierr; 521 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 522 PetscInt *row,*col; 523 PetscBool other_disassembled; 524 PetscMPIInt n; 525 PetscBool r1,r2,r3; 526 MatScalar *val; 527 InsertMode addv = mat->insertmode; 528 529 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 530 PetscFunctionBegin; 531 if (!baij->donotstash && !mat->nooffprocentries) { 532 while (1) { 533 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 534 if (!flg) break; 535 536 for (i=0; i<n;) { 537 /* Now identify the consecutive vals belonging to the same row */ 538 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 539 if (j < n) ncols = j-i; 540 else ncols = n-i; 541 /* Now assemble all these values with a single function call */ 542 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 543 i = j; 544 } 545 } 546 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 547 /* Now process the block-stash. Since the values are stashed column-oriented, 548 set the roworiented flag to column oriented, and after MatSetValues() 549 restore the original flags */ 550 r1 = baij->roworiented; 551 r2 = a->roworiented; 552 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 553 baij->roworiented = PETSC_FALSE; 554 a->roworiented = PETSC_FALSE; 555 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 556 while (1) { 557 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 558 if (!flg) break; 559 560 for (i=0; i<n;) { 561 /* Now identify the consecutive vals belonging to the same row */ 562 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 563 if (j < n) ncols = j-i; 564 else ncols = n-i; 565 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 566 i = j; 567 } 568 } 569 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 570 baij->roworiented = r1; 571 a->roworiented = r2; 572 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 573 } 574 575 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 576 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 577 578 /* determine if any processor has disassembled, if so we must 579 also disassemble ourselfs, in order that we may reassemble. */ 580 /* 581 if nonzero structure of submatrix B cannot change then we know that 582 no processor disassembled thus we can skip this stuff 583 */ 584 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 585 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 586 if (mat->was_assembled && !other_disassembled) { 587 ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 588 } 589 } 590 591 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 592 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 593 } 594 ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_TRUE);CHKERRQ(ierr); 595 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 596 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 597 598 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 599 baij->rowvalues = 0; 600 601 PetscFunctionReturn(0); 602 } 603 604 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 605 #undef __FUNCT__ 606 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 607 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 608 { 609 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 610 PetscErrorCode ierr; 611 PetscInt bs = mat->rmap->bs; 612 PetscMPIInt size = baij->size,rank = baij->rank; 613 PetscBool iascii,isdraw; 614 PetscViewer sviewer; 615 PetscViewerFormat format; 616 617 PetscFunctionBegin; 618 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 619 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 620 if (iascii) { 621 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 622 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 623 MatInfo info; 624 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 625 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 626 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 627 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 628 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 629 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 630 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 631 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 632 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 633 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 634 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 635 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_INFO) { 638 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 639 PetscFunctionReturn(0); 640 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 641 PetscFunctionReturn(0); 642 } 643 } 644 645 if (isdraw) { 646 PetscDraw draw; 647 PetscBool isnull; 648 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 649 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 650 } 651 652 if (size == 1) { 653 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 654 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 655 } else { 656 /* assemble the entire matrix onto first processor. */ 657 Mat A; 658 Mat_SeqSBAIJ *Aloc; 659 Mat_SeqBAIJ *Bloc; 660 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 661 MatScalar *a; 662 663 /* Should this be the same type as mat? */ 664 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 665 if (!rank) { 666 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 667 } else { 668 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 669 } 670 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 671 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 672 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 674 675 /* copy over the A part */ 676 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 677 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 678 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 679 680 for (i=0; i<mbs; i++) { 681 rvals[0] = bs*(baij->rstartbs + i); 682 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 683 for (j=ai[i]; j<ai[i+1]; j++) { 684 col = (baij->cstartbs+aj[j])*bs; 685 for (k=0; k<bs; k++) { 686 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 687 col++; 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++; a += bs; 703 } 704 } 705 } 706 ierr = PetscFree(rvals);CHKERRQ(ierr); 707 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 708 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 709 /* 710 Everyone has to call to draw the matrix since the graphics waits are 711 synchronized across all processors that share the PetscDraw object 712 */ 713 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 714 if (!rank) { 715 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 716 /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/ 717 PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ); 718 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 719 } 720 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 721 ierr = MatDestroy(&A);CHKERRQ(ierr); 722 } 723 PetscFunctionReturn(0); 724 } 725 726 #undef __FUNCT__ 727 #define __FUNCT__ "MatView_MPISBAIJ" 728 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 729 { 730 PetscErrorCode ierr; 731 PetscBool iascii,isdraw,issocket,isbinary; 732 733 PetscFunctionBegin; 734 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 735 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 736 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 737 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 738 if (iascii || isdraw || issocket || isbinary) { 739 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 740 } else { 741 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 742 } 743 PetscFunctionReturn(0); 744 } 745 746 #undef __FUNCT__ 747 #define __FUNCT__ "MatDestroy_MPISBAIJ" 748 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 749 { 750 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 751 PetscErrorCode ierr; 752 753 PetscFunctionBegin; 754 #if defined(PETSC_USE_LOG) 755 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 756 #endif 757 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 758 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 759 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 760 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 761 #if defined (PETSC_USE_CTABLE) 762 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 763 #else 764 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 765 #endif 766 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 767 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 768 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 769 ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr); 770 ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr); 771 ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr); 772 ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr); 773 ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr); 774 ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr); 775 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 776 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 777 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 778 ierr = VecDestroy(&baij->diag);CHKERRQ(ierr); 779 ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr); 780 ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr); 781 #if defined(PETSC_USE_REAL_MAT_SINGLE) 782 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 783 #endif 784 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 785 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 786 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 787 ierr = PetscFree(mat->data);CHKERRQ(ierr); 788 789 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 790 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 791 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 792 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 793 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 794 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C","",PETSC_NULL);CHKERRQ(ierr); 795 PetscFunctionReturn(0); 796 } 797 798 #undef __FUNCT__ 799 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian" 800 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy) 801 { 802 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 803 PetscErrorCode ierr; 804 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 805 PetscScalar *x,*from; 806 807 PetscFunctionBegin; 808 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 809 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 810 811 /* diagonal part */ 812 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 813 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 814 815 /* subdiagonal part */ 816 ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 817 818 /* copy x into the vec slvec0 */ 819 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 823 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 824 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 825 826 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 827 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 828 /* supperdiagonal part */ 829 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 830 PetscFunctionReturn(0); 831 } 832 833 #undef __FUNCT__ 834 #define __FUNCT__ "MatMult_MPISBAIJ" 835 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 836 { 837 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 838 PetscErrorCode ierr; 839 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 840 PetscScalar *x,*from; 841 842 PetscFunctionBegin; 843 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 844 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 845 846 /* diagonal part */ 847 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 848 ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr); 849 850 /* subdiagonal part */ 851 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 852 853 /* copy x into the vec slvec0 */ 854 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 855 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 856 857 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 858 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 859 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 860 861 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 862 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 863 /* supperdiagonal part */ 864 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 #undef __FUNCT__ 869 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 870 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 871 { 872 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 873 PetscErrorCode ierr; 874 PetscInt nt; 875 876 PetscFunctionBegin; 877 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 878 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 879 880 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 881 if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 882 883 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 884 /* do diagonal part */ 885 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 886 /* do supperdiagonal part */ 887 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 888 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 889 /* do subdiagonal part */ 890 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 891 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 892 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 893 894 PetscFunctionReturn(0); 895 } 896 897 #undef __FUNCT__ 898 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 899 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 900 { 901 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 902 PetscErrorCode ierr; 903 PetscInt mbs=a->mbs,bs=A->rmap->bs; 904 PetscScalar *x,*from,zero=0.0; 905 906 PetscFunctionBegin; 907 /* 908 PetscSynchronizedPrintf(((PetscObject)A)->comm," MatMultAdd is called ...\n"); 909 PetscSynchronizedFlush(((PetscObject)A)->comm); 910 */ 911 /* diagonal part */ 912 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 913 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 914 915 /* subdiagonal part */ 916 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 917 918 /* copy x into the vec slvec0 */ 919 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 920 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 921 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 922 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 923 924 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 925 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 926 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 927 928 /* supperdiagonal part */ 929 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 930 931 PetscFunctionReturn(0); 932 } 933 934 #undef __FUNCT__ 935 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 936 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 937 { 938 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 939 PetscErrorCode ierr; 940 941 PetscFunctionBegin; 942 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 943 /* do diagonal part */ 944 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 945 /* do supperdiagonal part */ 946 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 947 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 948 949 /* do subdiagonal part */ 950 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 951 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 952 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 953 954 PetscFunctionReturn(0); 955 } 956 957 /* 958 This only works correctly for square matrices where the subblock A->A is the 959 diagonal block 960 */ 961 #undef __FUNCT__ 962 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 963 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 964 { 965 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 966 PetscErrorCode ierr; 967 968 PetscFunctionBegin; 969 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 970 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 #undef __FUNCT__ 975 #define __FUNCT__ "MatScale_MPISBAIJ" 976 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 977 { 978 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 979 PetscErrorCode ierr; 980 981 PetscFunctionBegin; 982 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 983 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 984 PetscFunctionReturn(0); 985 } 986 987 #undef __FUNCT__ 988 #define __FUNCT__ "MatGetRow_MPISBAIJ" 989 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 990 { 991 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 992 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 993 PetscErrorCode ierr; 994 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 995 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 996 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 997 998 PetscFunctionBegin; 999 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1000 mat->getrowactive = PETSC_TRUE; 1001 1002 if (!mat->rowvalues && (idx || v)) { 1003 /* 1004 allocate enough space to hold information from the longest row. 1005 */ 1006 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1007 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1008 PetscInt max = 1,mbs = mat->mbs,tmp; 1009 for (i=0; i<mbs; i++) { 1010 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1011 if (max < tmp) { max = tmp; } 1012 } 1013 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1014 } 1015 1016 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1017 lrow = row - brstart; /* local row index */ 1018 1019 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1020 if (!v) {pvA = 0; pvB = 0;} 1021 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1022 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1023 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1024 nztot = nzA + nzB; 1025 1026 cmap = mat->garray; 1027 if (v || idx) { 1028 if (nztot) { 1029 /* Sort by increasing column numbers, assuming A and B already sorted */ 1030 PetscInt imark = -1; 1031 if (v) { 1032 *v = v_p = mat->rowvalues; 1033 for (i=0; i<nzB; i++) { 1034 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1035 else break; 1036 } 1037 imark = i; 1038 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1039 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1040 } 1041 if (idx) { 1042 *idx = idx_p = mat->rowindices; 1043 if (imark > -1) { 1044 for (i=0; i<imark; i++) { 1045 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1046 } 1047 } else { 1048 for (i=0; i<nzB; i++) { 1049 if (cmap[cworkB[i]/bs] < cstart) 1050 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1051 else break; 1052 } 1053 imark = i; 1054 } 1055 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1056 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1057 } 1058 } else { 1059 if (idx) *idx = 0; 1060 if (v) *v = 0; 1061 } 1062 } 1063 *nz = nztot; 1064 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1065 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1071 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1072 { 1073 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1074 1075 PetscFunctionBegin; 1076 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1077 baij->getrowactive = PETSC_FALSE; 1078 PetscFunctionReturn(0); 1079 } 1080 1081 #undef __FUNCT__ 1082 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1083 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1084 { 1085 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1086 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1087 1088 PetscFunctionBegin; 1089 aA->getrow_utriangular = PETSC_TRUE; 1090 PetscFunctionReturn(0); 1091 } 1092 #undef __FUNCT__ 1093 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1094 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1095 { 1096 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1097 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1098 1099 PetscFunctionBegin; 1100 aA->getrow_utriangular = PETSC_FALSE; 1101 PetscFunctionReturn(0); 1102 } 1103 1104 #undef __FUNCT__ 1105 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1106 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1107 { 1108 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1109 PetscErrorCode ierr; 1110 1111 PetscFunctionBegin; 1112 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1113 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1114 PetscFunctionReturn(0); 1115 } 1116 1117 #undef __FUNCT__ 1118 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1119 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1120 { 1121 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1122 PetscErrorCode ierr; 1123 1124 PetscFunctionBegin; 1125 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1126 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1132 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1133 { 1134 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1139 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1145 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1146 { 1147 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1148 Mat A = a->A,B = a->B; 1149 PetscErrorCode ierr; 1150 PetscReal isend[5],irecv[5]; 1151 1152 PetscFunctionBegin; 1153 info->block_size = (PetscReal)matin->rmap->bs; 1154 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1155 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1156 isend[3] = info->memory; isend[4] = info->mallocs; 1157 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1158 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1159 isend[3] += info->memory; isend[4] += info->mallocs; 1160 if (flag == MAT_LOCAL) { 1161 info->nz_used = isend[0]; 1162 info->nz_allocated = isend[1]; 1163 info->nz_unneeded = isend[2]; 1164 info->memory = isend[3]; 1165 info->mallocs = isend[4]; 1166 } else if (flag == MAT_GLOBAL_MAX) { 1167 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 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,((PetscObject)matin)->comm);CHKERRQ(ierr); 1175 info->nz_used = irecv[0]; 1176 info->nz_allocated = irecv[1]; 1177 info->nz_unneeded = irecv[2]; 1178 info->memory = irecv[3]; 1179 info->mallocs = irecv[4]; 1180 } else { 1181 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1182 } 1183 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1184 info->fill_ratio_needed = 0; 1185 info->factor_mallocs = 0; 1186 PetscFunctionReturn(0); 1187 } 1188 1189 #undef __FUNCT__ 1190 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1191 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg) 1192 { 1193 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1194 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1195 PetscErrorCode ierr; 1196 1197 PetscFunctionBegin; 1198 switch (op) { 1199 case MAT_NEW_NONZERO_LOCATIONS: 1200 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1201 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1202 case MAT_KEEP_NONZERO_PATTERN: 1203 case MAT_NEW_NONZERO_LOCATION_ERR: 1204 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1205 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1206 break; 1207 case MAT_ROW_ORIENTED: 1208 a->roworiented = flg; 1209 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 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1225 break; 1226 case MAT_SPD: 1227 A->spd_set = PETSC_TRUE; 1228 A->spd = flg; 1229 if (flg) { 1230 A->symmetric = PETSC_TRUE; 1231 A->structurally_symmetric = PETSC_TRUE; 1232 A->symmetric_set = PETSC_TRUE; 1233 A->structurally_symmetric_set = PETSC_TRUE; 1234 } 1235 break; 1236 case MAT_SYMMETRIC: 1237 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1238 break; 1239 case MAT_STRUCTURALLY_SYMMETRIC: 1240 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1241 break; 1242 case MAT_SYMMETRY_ETERNAL: 1243 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric"); 1244 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1245 break; 1246 case MAT_IGNORE_LOWER_TRIANGULAR: 1247 aA->ignore_ltriangular = flg; 1248 break; 1249 case MAT_ERROR_LOWER_TRIANGULAR: 1250 aA->ignore_ltriangular = flg; 1251 break; 1252 case MAT_GETROW_UPPERTRIANGULAR: 1253 aA->getrow_utriangular = flg; 1254 break; 1255 default: 1256 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1257 } 1258 PetscFunctionReturn(0); 1259 } 1260 1261 #undef __FUNCT__ 1262 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1263 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1264 { 1265 PetscErrorCode ierr; 1266 1267 PetscFunctionBegin; 1268 if (MAT_INITIAL_MATRIX || *B != A) { 1269 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1270 } 1271 PetscFunctionReturn(0); 1272 } 1273 1274 #undef __FUNCT__ 1275 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1276 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1277 { 1278 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1279 Mat a=baij->A, b=baij->B; 1280 PetscErrorCode ierr; 1281 PetscInt nv,m,n; 1282 PetscBool flg; 1283 1284 PetscFunctionBegin; 1285 if (ll != rr) { 1286 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1287 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1288 } 1289 if (!ll) PetscFunctionReturn(0); 1290 1291 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1292 if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1293 1294 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1295 if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1296 1297 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1298 1299 /* left diagonalscale the off-diagonal part */ 1300 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1301 1302 /* scale the diagonal part */ 1303 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1304 1305 /* right diagonalscale the off-diagonal part */ 1306 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1307 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1308 PetscFunctionReturn(0); 1309 } 1310 1311 #undef __FUNCT__ 1312 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1313 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1314 { 1315 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1316 PetscErrorCode ierr; 1317 1318 PetscFunctionBegin; 1319 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1320 PetscFunctionReturn(0); 1321 } 1322 1323 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1324 1325 #undef __FUNCT__ 1326 #define __FUNCT__ "MatEqual_MPISBAIJ" 1327 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag) 1328 { 1329 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1330 Mat a,b,c,d; 1331 PetscBool flg; 1332 PetscErrorCode ierr; 1333 1334 PetscFunctionBegin; 1335 a = matA->A; b = matA->B; 1336 c = matB->A; d = matB->B; 1337 1338 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1339 if (flg) { 1340 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1341 } 1342 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1343 PetscFunctionReturn(0); 1344 } 1345 1346 #undef __FUNCT__ 1347 #define __FUNCT__ "MatCopy_MPISBAIJ" 1348 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1349 { 1350 PetscErrorCode ierr; 1351 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1352 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1353 1354 PetscFunctionBegin; 1355 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1356 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1357 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1358 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1359 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1360 } else { 1361 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1362 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1363 } 1364 PetscFunctionReturn(0); 1365 } 1366 1367 #undef __FUNCT__ 1368 #define __FUNCT__ "MatSetUp_MPISBAIJ" 1369 PetscErrorCode MatSetUp_MPISBAIJ(Mat A) 1370 { 1371 PetscErrorCode ierr; 1372 1373 PetscFunctionBegin; 1374 ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1375 PetscFunctionReturn(0); 1376 } 1377 1378 #undef __FUNCT__ 1379 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1380 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1381 { 1382 PetscErrorCode ierr; 1383 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data; 1384 PetscBLASInt bnz,one=1; 1385 Mat_SeqSBAIJ *xa,*ya; 1386 Mat_SeqBAIJ *xb,*yb; 1387 1388 PetscFunctionBegin; 1389 if (str == SAME_NONZERO_PATTERN) { 1390 PetscScalar alpha = a; 1391 xa = (Mat_SeqSBAIJ *)xx->A->data; 1392 ya = (Mat_SeqSBAIJ *)yy->A->data; 1393 bnz = PetscBLASIntCast(xa->nz); 1394 BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one); 1395 xb = (Mat_SeqBAIJ *)xx->B->data; 1396 yb = (Mat_SeqBAIJ *)yy->B->data; 1397 bnz = PetscBLASIntCast(xb->nz); 1398 BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one); 1399 } else { 1400 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1401 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1402 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1403 } 1404 PetscFunctionReturn(0); 1405 } 1406 1407 #undef __FUNCT__ 1408 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1409 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1410 { 1411 PetscErrorCode ierr; 1412 PetscInt i; 1413 PetscBool flg; 1414 1415 PetscFunctionBegin; 1416 for (i=0; i<n; i++) { 1417 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1418 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1419 } 1420 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1421 PetscFunctionReturn(0); 1422 } 1423 1424 1425 /* -------------------------------------------------------------------*/ 1426 static struct _MatOps MatOps_Values = { 1427 MatSetValues_MPISBAIJ, 1428 MatGetRow_MPISBAIJ, 1429 MatRestoreRow_MPISBAIJ, 1430 MatMult_MPISBAIJ, 1431 /* 4*/ MatMultAdd_MPISBAIJ, 1432 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1433 MatMultAdd_MPISBAIJ, 1434 0, 1435 0, 1436 0, 1437 /*10*/ 0, 1438 0, 1439 0, 1440 MatSOR_MPISBAIJ, 1441 MatTranspose_MPISBAIJ, 1442 /*15*/ MatGetInfo_MPISBAIJ, 1443 MatEqual_MPISBAIJ, 1444 MatGetDiagonal_MPISBAIJ, 1445 MatDiagonalScale_MPISBAIJ, 1446 MatNorm_MPISBAIJ, 1447 /*20*/ MatAssemblyBegin_MPISBAIJ, 1448 MatAssemblyEnd_MPISBAIJ, 1449 MatSetOption_MPISBAIJ, 1450 MatZeroEntries_MPISBAIJ, 1451 /*24*/ 0, 1452 0, 1453 0, 1454 0, 1455 0, 1456 /*29*/ MatSetUp_MPISBAIJ, 1457 0, 1458 0, 1459 0, 1460 0, 1461 /*34*/ MatDuplicate_MPISBAIJ, 1462 0, 1463 0, 1464 0, 1465 0, 1466 /*39*/ MatAXPY_MPISBAIJ, 1467 MatGetSubMatrices_MPISBAIJ, 1468 MatIncreaseOverlap_MPISBAIJ, 1469 MatGetValues_MPISBAIJ, 1470 MatCopy_MPISBAIJ, 1471 /*44*/ 0, 1472 MatScale_MPISBAIJ, 1473 0, 1474 0, 1475 0, 1476 /*49*/ 0, 1477 0, 1478 0, 1479 0, 1480 0, 1481 /*54*/ 0, 1482 0, 1483 MatSetUnfactored_MPISBAIJ, 1484 0, 1485 MatSetValuesBlocked_MPISBAIJ, 1486 /*59*/ 0, 1487 0, 1488 0, 1489 0, 1490 0, 1491 /*64*/ 0, 1492 0, 1493 0, 1494 0, 1495 0, 1496 /*69*/ MatGetRowMaxAbs_MPISBAIJ, 1497 0, 1498 0, 1499 0, 1500 0, 1501 /*74*/ 0, 1502 0, 1503 0, 1504 0, 1505 0, 1506 /*79*/ 0, 1507 0, 1508 0, 1509 0, 1510 MatLoad_MPISBAIJ, 1511 /*84*/ 0, 1512 0, 1513 0, 1514 0, 1515 0, 1516 /*89*/ 0, 1517 0, 1518 0, 1519 0, 1520 0, 1521 /*94*/ 0, 1522 0, 1523 0, 1524 0, 1525 0, 1526 /*99*/ 0, 1527 0, 1528 0, 1529 0, 1530 0, 1531 /*104*/0, 1532 MatRealPart_MPISBAIJ, 1533 MatImaginaryPart_MPISBAIJ, 1534 MatGetRowUpperTriangular_MPISBAIJ, 1535 MatRestoreRowUpperTriangular_MPISBAIJ, 1536 /*109*/0, 1537 0, 1538 0, 1539 0, 1540 0, 1541 /*114*/0, 1542 0, 1543 0, 1544 0, 1545 0, 1546 /*119*/0, 1547 0, 1548 0, 1549 0 1550 }; 1551 1552 1553 EXTERN_C_BEGIN 1554 #undef __FUNCT__ 1555 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1556 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a) 1557 { 1558 PetscFunctionBegin; 1559 *a = ((Mat_MPISBAIJ *)A->data)->A; 1560 PetscFunctionReturn(0); 1561 } 1562 EXTERN_C_END 1563 1564 EXTERN_C_BEGIN 1565 #undef __FUNCT__ 1566 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1567 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1568 { 1569 Mat_MPISBAIJ *b; 1570 PetscErrorCode ierr; 1571 PetscInt i,mbs,Mbs; 1572 1573 PetscFunctionBegin; 1574 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1575 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1576 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1577 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1578 1579 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1580 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1581 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1582 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1583 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1584 1585 if (d_nnz) { 1586 for (i=0; i<B->rmap->n/bs; i++) { 1587 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]); 1588 } 1589 } 1590 if (o_nnz) { 1591 for (i=0; i<B->rmap->n/bs; i++) { 1592 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]); 1593 } 1594 } 1595 1596 b = (Mat_MPISBAIJ*)B->data; 1597 mbs = B->rmap->n/bs; 1598 Mbs = B->rmap->N/bs; 1599 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); 1600 1601 B->rmap->bs = bs; 1602 b->bs2 = bs*bs; 1603 b->mbs = mbs; 1604 b->nbs = mbs; 1605 b->Mbs = Mbs; 1606 b->Nbs = Mbs; 1607 1608 for (i=0; i<=b->size; i++) { 1609 b->rangebs[i] = B->rmap->range[i]/bs; 1610 } 1611 b->rstartbs = B->rmap->rstart/bs; 1612 b->rendbs = B->rmap->rend/bs; 1613 1614 b->cstartbs = B->cmap->rstart/bs; 1615 b->cendbs = B->cmap->rend/bs; 1616 1617 if (!B->preallocated) { 1618 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1619 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1620 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1621 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1622 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1623 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1624 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1625 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1626 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 1627 } 1628 1629 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1630 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1631 B->preallocated = PETSC_TRUE; 1632 PetscFunctionReturn(0); 1633 } 1634 EXTERN_C_END 1635 1636 EXTERN_C_BEGIN 1637 #undef __FUNCT__ 1638 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ" 1639 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1640 { 1641 PetscInt m,rstart,cstart,cend; 1642 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1643 const PetscInt *JJ=0; 1644 PetscScalar *values=0; 1645 PetscErrorCode ierr; 1646 1647 PetscFunctionBegin; 1648 if (bs < 1) SETERRQ1(((PetscObject)B)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1649 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 1650 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 1651 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 1652 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 1653 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 1654 m = B->rmap->n/bs; 1655 rstart = B->rmap->rstart/bs; 1656 cstart = B->cmap->rstart/bs; 1657 cend = B->cmap->rend/bs; 1658 1659 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1660 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 1661 for (i=0; i<m; i++) { 1662 nz = ii[i+1] - ii[i]; 1663 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1664 nz_max = PetscMax(nz_max,nz); 1665 JJ = jj + ii[i]; 1666 for (j=0; j<nz; j++) { 1667 if (*JJ >= cstart) break; 1668 JJ++; 1669 } 1670 d = 0; 1671 for (; j<nz; j++) { 1672 if (*JJ++ >= cend) break; 1673 d++; 1674 } 1675 d_nnz[i] = d; 1676 o_nnz[i] = nz - d; 1677 } 1678 ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1679 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 1680 1681 values = (PetscScalar*)V; 1682 if (!values) { 1683 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 1684 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 1685 } 1686 for (i=0; i<m; i++) { 1687 PetscInt row = i + rstart; 1688 PetscInt ncols = ii[i+1] - ii[i]; 1689 const PetscInt *icols = jj + ii[i]; 1690 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 1691 ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 1692 } 1693 1694 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 1695 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1696 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1697 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1698 PetscFunctionReturn(0); 1699 } 1700 EXTERN_C_END 1701 1702 EXTERN_C_BEGIN 1703 #if defined(PETSC_HAVE_MUMPS) 1704 extern PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*); 1705 #endif 1706 #if defined(PETSC_HAVE_PASTIX) 1707 extern PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1708 #endif 1709 EXTERN_C_END 1710 1711 /*MC 1712 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1713 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 1714 the matrix is stored. 1715 1716 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 1717 can call MatSetOption(Mat, MAT_HERMITIAN); 1718 1719 Options Database Keys: 1720 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1721 1722 Level: beginner 1723 1724 .seealso: MatCreateMPISBAIJ 1725 M*/ 1726 1727 EXTERN_C_BEGIN 1728 extern PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*); 1729 EXTERN_C_END 1730 1731 EXTERN_C_BEGIN 1732 #undef __FUNCT__ 1733 #define __FUNCT__ "MatCreate_MPISBAIJ" 1734 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1735 { 1736 Mat_MPISBAIJ *b; 1737 PetscErrorCode ierr; 1738 PetscBool flg; 1739 1740 PetscFunctionBegin; 1741 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1742 B->data = (void*)b; 1743 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1744 1745 B->ops->destroy = MatDestroy_MPISBAIJ; 1746 B->ops->view = MatView_MPISBAIJ; 1747 B->assembled = PETSC_FALSE; 1748 1749 B->insertmode = NOT_SET_VALUES; 1750 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 1751 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 1752 1753 /* build local table of row and column ownerships */ 1754 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1755 1756 /* build cache for off array entries formed */ 1757 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 1758 b->donotstash = PETSC_FALSE; 1759 b->colmap = PETSC_NULL; 1760 b->garray = PETSC_NULL; 1761 b->roworiented = PETSC_TRUE; 1762 1763 /* stuff used in block assembly */ 1764 b->barray = 0; 1765 1766 /* stuff used for matrix vector multiply */ 1767 b->lvec = 0; 1768 b->Mvctx = 0; 1769 b->slvec0 = 0; 1770 b->slvec0b = 0; 1771 b->slvec1 = 0; 1772 b->slvec1a = 0; 1773 b->slvec1b = 0; 1774 b->sMvctx = 0; 1775 1776 /* stuff for MatGetRow() */ 1777 b->rowindices = 0; 1778 b->rowvalues = 0; 1779 b->getrowactive = PETSC_FALSE; 1780 1781 /* hash table stuff */ 1782 b->ht = 0; 1783 b->hd = 0; 1784 b->ht_size = 0; 1785 b->ht_flag = PETSC_FALSE; 1786 b->ht_fact = 0; 1787 b->ht_total_ct = 0; 1788 b->ht_insert_ct = 0; 1789 1790 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 1791 b->ijonly = PETSC_FALSE; 1792 1793 b->in_loc = 0; 1794 b->v_loc = 0; 1795 b->n_loc = 0; 1796 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1797 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1798 if (flg) { 1799 PetscReal fact = 1.39; 1800 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1801 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1802 if (fact <= 1.0) fact = 1.39; 1803 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1804 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1805 } 1806 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1807 1808 #if defined(PETSC_HAVE_PASTIX) 1809 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 1810 "MatGetFactor_mpisbaij_pastix", 1811 MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1812 #endif 1813 #if defined(PETSC_HAVE_MUMPS) 1814 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 1815 "MatGetFactor_sbaij_mumps", 1816 MatGetFactor_sbaij_mumps);CHKERRQ(ierr); 1817 #endif 1818 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1819 "MatStoreValues_MPISBAIJ", 1820 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1821 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1822 "MatRetrieveValues_MPISBAIJ", 1823 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1824 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1825 "MatGetDiagonalBlock_MPISBAIJ", 1826 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1827 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1828 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1829 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1830 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C", 1831 "MatMPISBAIJSetPreallocationCSR_MPISBAIJ", 1832 MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr); 1833 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C", 1834 "MatConvert_MPISBAIJ_MPISBSTRM", 1835 MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr); 1836 1837 B->symmetric = PETSC_TRUE; 1838 B->structurally_symmetric = PETSC_TRUE; 1839 B->symmetric_set = PETSC_TRUE; 1840 B->structurally_symmetric_set = PETSC_TRUE; 1841 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1842 PetscFunctionReturn(0); 1843 } 1844 EXTERN_C_END 1845 1846 /*MC 1847 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1848 1849 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1850 and MATMPISBAIJ otherwise. 1851 1852 Options Database Keys: 1853 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1854 1855 Level: beginner 1856 1857 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1858 M*/ 1859 1860 #undef __FUNCT__ 1861 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1862 /*@C 1863 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1864 the user should preallocate the matrix storage by setting the parameters 1865 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1866 performance can be increased by more than a factor of 50. 1867 1868 Collective on Mat 1869 1870 Input Parameters: 1871 + A - the matrix 1872 . bs - size of blockk 1873 . d_nz - number of block nonzeros per block row in diagonal portion of local 1874 submatrix (same for all local rows) 1875 . d_nnz - array containing the number of block nonzeros in the various block rows 1876 in the upper triangular and diagonal part of the in diagonal portion of the local 1877 (possibly different for each block row) or PETSC_NULL. If you plan to factor the matrix you must leave room 1878 for the diagonal entry and set a value even if it is zero. 1879 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1880 submatrix (same for all local rows). 1881 - o_nnz - array containing the number of nonzeros in the various block rows of the 1882 off-diagonal portion of the local submatrix that is right of the diagonal 1883 (possibly different for each block row) or PETSC_NULL. 1884 1885 1886 Options Database Keys: 1887 . -mat_no_unroll - uses code that does not unroll the loops in the 1888 block calculations (much slower) 1889 . -mat_block_size - size of the blocks to use 1890 1891 Notes: 1892 1893 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1894 than it must be used on all processors that share the object for that argument. 1895 1896 If the *_nnz parameter is given then the *_nz parameter is ignored 1897 1898 Storage Information: 1899 For a square global matrix we define each processor's diagonal portion 1900 to be its local rows and the corresponding columns (a square submatrix); 1901 each processor's off-diagonal portion encompasses the remainder of the 1902 local matrix (a rectangular submatrix). 1903 1904 The user can specify preallocated storage for the diagonal part of 1905 the local submatrix with either d_nz or d_nnz (not both). Set 1906 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1907 memory allocation. Likewise, specify preallocated storage for the 1908 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1909 1910 You can call MatGetInfo() to get information on how effective the preallocation was; 1911 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1912 You can also run with the option -info and look for messages with the string 1913 malloc in them to see if additional memory allocation was needed. 1914 1915 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1916 the figure below we depict these three local rows and all columns (0-11). 1917 1918 .vb 1919 0 1 2 3 4 5 6 7 8 9 10 11 1920 ------------------- 1921 row 3 | . . . d d d o o o o o o 1922 row 4 | . . . d d d o o o o o o 1923 row 5 | . . . d d d o o o o o o 1924 ------------------- 1925 .ve 1926 1927 Thus, any entries in the d locations are stored in the d (diagonal) 1928 submatrix, and any entries in the o locations are stored in the 1929 o (off-diagonal) submatrix. Note that the d matrix is stored in 1930 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1931 1932 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1933 plus the diagonal part of the d matrix, 1934 and o_nz should indicate the number of block nonzeros per row in the o matrix 1935 1936 In general, for PDE problems in which most nonzeros are near the diagonal, 1937 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1938 or you will get TERRIBLE performance; see the users' manual chapter on 1939 matrices. 1940 1941 Level: intermediate 1942 1943 .keywords: matrix, block, aij, compressed row, sparse, parallel 1944 1945 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership() 1946 @*/ 1947 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1948 { 1949 PetscErrorCode ierr; 1950 1951 PetscFunctionBegin; 1952 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 1953 PetscValidType(B,1); 1954 PetscValidLogicalCollectiveInt(B,bs,2); 1955 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); 1956 PetscFunctionReturn(0); 1957 } 1958 1959 #undef __FUNCT__ 1960 #define __FUNCT__ "MatCreateSBAIJ" 1961 /*@C 1962 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1963 (block compressed row). For good matrix assembly performance 1964 the user should preallocate the matrix storage by setting the parameters 1965 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1966 performance can be increased by more than a factor of 50. 1967 1968 Collective on MPI_Comm 1969 1970 Input Parameters: 1971 + comm - MPI communicator 1972 . bs - size of blockk 1973 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1974 This value should be the same as the local size used in creating the 1975 y vector for the matrix-vector product y = Ax. 1976 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1977 This value should be the same as the local size used in creating the 1978 x vector for the matrix-vector product y = Ax. 1979 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1980 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1981 . d_nz - number of block nonzeros per block row in diagonal portion of local 1982 submatrix (same for all local rows) 1983 . d_nnz - array containing the number of block nonzeros in the various block rows 1984 in the upper triangular portion of the in diagonal portion of the local 1985 (possibly different for each block block row) or PETSC_NULL. 1986 If you plan to factor the matrix you must leave room for the diagonal entry and 1987 set its value even if it is zero. 1988 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1989 submatrix (same for all local rows). 1990 - o_nnz - array containing the number of nonzeros in the various block rows of the 1991 off-diagonal portion of the local submatrix (possibly different for 1992 each block row) or PETSC_NULL. 1993 1994 Output Parameter: 1995 . A - the matrix 1996 1997 Options Database Keys: 1998 . -mat_no_unroll - uses code that does not unroll the loops in the 1999 block calculations (much slower) 2000 . -mat_block_size - size of the blocks to use 2001 . -mat_mpi - use the parallel matrix data structures even on one processor 2002 (defaults to using SeqBAIJ format on one processor) 2003 2004 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2005 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2006 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2007 2008 Notes: 2009 The number of rows and columns must be divisible by blocksize. 2010 This matrix type does not support complex Hermitian operation. 2011 2012 The user MUST specify either the local or global matrix dimensions 2013 (possibly both). 2014 2015 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2016 than it must be used on all processors that share the object for that argument. 2017 2018 If the *_nnz parameter is given then the *_nz parameter is ignored 2019 2020 Storage Information: 2021 For a square global matrix we define each processor's diagonal portion 2022 to be its local rows and the corresponding columns (a square submatrix); 2023 each processor's off-diagonal portion encompasses the remainder of the 2024 local matrix (a rectangular submatrix). 2025 2026 The user can specify preallocated storage for the diagonal part of 2027 the local submatrix with either d_nz or d_nnz (not both). Set 2028 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2029 memory allocation. Likewise, specify preallocated storage for the 2030 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2031 2032 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2033 the figure below we depict these three local rows and all columns (0-11). 2034 2035 .vb 2036 0 1 2 3 4 5 6 7 8 9 10 11 2037 ------------------- 2038 row 3 | . . . d d d o o o o o o 2039 row 4 | . . . d d d o o o o o o 2040 row 5 | . . . d d d o o o o o o 2041 ------------------- 2042 .ve 2043 2044 Thus, any entries in the d locations are stored in the d (diagonal) 2045 submatrix, and any entries in the o locations are stored in the 2046 o (off-diagonal) submatrix. Note that the d matrix is stored in 2047 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 2048 2049 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 2050 plus the diagonal part of the d matrix, 2051 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2052 In general, for PDE problems in which most nonzeros are near the diagonal, 2053 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2054 or you will get TERRIBLE performance; see the users' manual chapter on 2055 matrices. 2056 2057 Level: intermediate 2058 2059 .keywords: matrix, block, aij, compressed row, sparse, parallel 2060 2061 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ() 2062 @*/ 2063 2064 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) 2065 { 2066 PetscErrorCode ierr; 2067 PetscMPIInt size; 2068 2069 PetscFunctionBegin; 2070 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2071 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2072 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2073 if (size > 1) { 2074 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2075 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2076 } else { 2077 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2078 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2079 } 2080 PetscFunctionReturn(0); 2081 } 2082 2083 2084 #undef __FUNCT__ 2085 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2086 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2087 { 2088 Mat mat; 2089 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2090 PetscErrorCode ierr; 2091 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 2092 PetscScalar *array; 2093 2094 PetscFunctionBegin; 2095 *newmat = 0; 2096 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2097 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2098 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2099 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2100 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2101 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2102 2103 mat->factortype = matin->factortype; 2104 mat->preallocated = PETSC_TRUE; 2105 mat->assembled = PETSC_TRUE; 2106 mat->insertmode = NOT_SET_VALUES; 2107 2108 a = (Mat_MPISBAIJ*)mat->data; 2109 a->bs2 = oldmat->bs2; 2110 a->mbs = oldmat->mbs; 2111 a->nbs = oldmat->nbs; 2112 a->Mbs = oldmat->Mbs; 2113 a->Nbs = oldmat->Nbs; 2114 2115 2116 a->size = oldmat->size; 2117 a->rank = oldmat->rank; 2118 a->donotstash = oldmat->donotstash; 2119 a->roworiented = oldmat->roworiented; 2120 a->rowindices = 0; 2121 a->rowvalues = 0; 2122 a->getrowactive = PETSC_FALSE; 2123 a->barray = 0; 2124 a->rstartbs = oldmat->rstartbs; 2125 a->rendbs = oldmat->rendbs; 2126 a->cstartbs = oldmat->cstartbs; 2127 a->cendbs = oldmat->cendbs; 2128 2129 /* hash table stuff */ 2130 a->ht = 0; 2131 a->hd = 0; 2132 a->ht_size = 0; 2133 a->ht_flag = oldmat->ht_flag; 2134 a->ht_fact = oldmat->ht_fact; 2135 a->ht_total_ct = 0; 2136 a->ht_insert_ct = 0; 2137 2138 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2139 if (oldmat->colmap) { 2140 #if defined (PETSC_USE_CTABLE) 2141 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2142 #else 2143 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2144 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2145 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2146 #endif 2147 } else a->colmap = 0; 2148 2149 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2150 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2151 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2152 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2153 } else a->garray = 0; 2154 2155 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2156 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2157 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2158 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2159 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2160 2161 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2162 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2163 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2164 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2165 2166 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2167 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2168 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2169 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2170 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2171 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2172 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2173 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2174 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2175 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2176 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2177 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2178 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2179 2180 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2181 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2182 a->sMvctx = oldmat->sMvctx; 2183 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2184 2185 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2186 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2187 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2188 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2189 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2190 *newmat = mat; 2191 PetscFunctionReturn(0); 2192 } 2193 2194 #undef __FUNCT__ 2195 #define __FUNCT__ "MatLoad_MPISBAIJ" 2196 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer) 2197 { 2198 PetscErrorCode ierr; 2199 PetscInt i,nz,j,rstart,rend; 2200 PetscScalar *vals,*buf; 2201 MPI_Comm comm = ((PetscObject)viewer)->comm; 2202 MPI_Status status; 2203 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs; 2204 PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens; 2205 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2206 PetscInt bs=1,Mbs,mbs,extra_rows; 2207 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2208 PetscInt dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols; 2209 int fd; 2210 2211 PetscFunctionBegin; 2212 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2213 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2214 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2215 2216 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2217 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2218 if (!rank) { 2219 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2220 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2221 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2222 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2223 } 2224 2225 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 2226 2227 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2228 M = header[1]; N = header[2]; 2229 2230 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2231 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 2232 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 2233 2234 /* If global sizes are set, check if they are consistent with that given in the file */ 2235 if (sizesset) { 2236 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 2237 } 2238 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); 2239 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); 2240 2241 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 2242 2243 /* 2244 This code adds extra rows to make sure the number of rows is 2245 divisible by the blocksize 2246 */ 2247 Mbs = M/bs; 2248 extra_rows = bs - M + bs*(Mbs); 2249 if (extra_rows == bs) extra_rows = 0; 2250 else Mbs++; 2251 if (extra_rows &&!rank) { 2252 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2253 } 2254 2255 /* determine ownership of all rows */ 2256 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 2257 mbs = Mbs/size + ((Mbs % size) > rank); 2258 m = mbs*bs; 2259 } else { /* User Set */ 2260 m = newmat->rmap->n; 2261 mbs = m/bs; 2262 } 2263 ierr = PetscMalloc2(size+1,PetscMPIInt,&rowners,size+1,PetscMPIInt,&browners);CHKERRQ(ierr); 2264 mmbs = PetscMPIIntCast(mbs); 2265 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2266 rowners[0] = 0; 2267 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2268 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2269 rstart = rowners[rank]; 2270 rend = rowners[rank+1]; 2271 2272 /* distribute row lengths to all processors */ 2273 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2274 if (!rank) { 2275 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2276 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2277 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2278 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2279 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2280 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2281 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2282 } else { 2283 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2284 } 2285 2286 if (!rank) { /* procs[0] */ 2287 /* calculate the number of nonzeros on each processor */ 2288 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2289 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2290 for (i=0; i<size; i++) { 2291 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2292 procsnz[i] += rowlengths[j]; 2293 } 2294 } 2295 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2296 2297 /* determine max buffer needed and allocate it */ 2298 maxnz = 0; 2299 for (i=0; i<size; i++) { 2300 maxnz = PetscMax(maxnz,procsnz[i]); 2301 } 2302 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2303 2304 /* read in my part of the matrix column indices */ 2305 nz = procsnz[0]; 2306 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2307 mycols = ibuf; 2308 if (size == 1) nz -= extra_rows; 2309 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2310 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2311 2312 /* read in every ones (except the last) and ship off */ 2313 for (i=1; i<size-1; i++) { 2314 nz = procsnz[i]; 2315 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2316 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2317 } 2318 /* read in the stuff for the last proc */ 2319 if (size != 1) { 2320 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2321 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2322 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2323 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2324 } 2325 ierr = PetscFree(cols);CHKERRQ(ierr); 2326 } else { /* procs[i], i>0 */ 2327 /* determine buffer space needed for message */ 2328 nz = 0; 2329 for (i=0; i<m; i++) { 2330 nz += locrowlens[i]; 2331 } 2332 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2333 mycols = ibuf; 2334 /* receive message of column indices*/ 2335 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2336 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2337 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2338 } 2339 2340 /* loop over local rows, determining number of off diagonal entries */ 2341 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2342 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2343 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2344 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2345 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2346 rowcount = 0; 2347 nzcount = 0; 2348 for (i=0; i<mbs; i++) { 2349 dcount = 0; 2350 odcount = 0; 2351 for (j=0; j<bs; j++) { 2352 kmax = locrowlens[rowcount]; 2353 for (k=0; k<kmax; k++) { 2354 tmp = mycols[nzcount++]/bs; /* block col. index */ 2355 if (!mask[tmp]) { 2356 mask[tmp] = 1; 2357 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2358 else masked1[dcount++] = tmp; /* entry in diag portion */ 2359 } 2360 } 2361 rowcount++; 2362 } 2363 2364 dlens[i] = dcount; /* d_nzz[i] */ 2365 odlens[i] = odcount; /* o_nzz[i] */ 2366 2367 /* zero out the mask elements we set */ 2368 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2369 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2370 } 2371 if (!sizesset) { 2372 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2373 } 2374 ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2375 ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr); 2376 2377 if (!rank) { 2378 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2379 /* read in my part of the matrix numerical values */ 2380 nz = procsnz[0]; 2381 vals = buf; 2382 mycols = ibuf; 2383 if (size == 1) nz -= extra_rows; 2384 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2385 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2386 2387 /* insert into matrix */ 2388 jj = rstart*bs; 2389 for (i=0; i<m; i++) { 2390 ierr = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2391 mycols += locrowlens[i]; 2392 vals += locrowlens[i]; 2393 jj++; 2394 } 2395 2396 /* read in other processors (except the last one) and ship out */ 2397 for (i=1; i<size-1; i++) { 2398 nz = procsnz[i]; 2399 vals = buf; 2400 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2401 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2402 } 2403 /* the last proc */ 2404 if (size != 1) { 2405 nz = procsnz[i] - extra_rows; 2406 vals = buf; 2407 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2408 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2409 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 2410 } 2411 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2412 2413 } else { 2414 /* receive numeric values */ 2415 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2416 2417 /* receive message of values*/ 2418 vals = buf; 2419 mycols = ibuf; 2420 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 2421 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2422 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2423 2424 /* insert into matrix */ 2425 jj = rstart*bs; 2426 for (i=0; i<m; i++) { 2427 ierr = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2428 mycols += locrowlens[i]; 2429 vals += locrowlens[i]; 2430 jj++; 2431 } 2432 } 2433 2434 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2435 ierr = PetscFree(buf);CHKERRQ(ierr); 2436 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2437 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2438 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2439 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2440 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2441 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2442 PetscFunctionReturn(0); 2443 } 2444 2445 #undef __FUNCT__ 2446 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2447 /*XXXXX@ 2448 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2449 2450 Input Parameters: 2451 . mat - the matrix 2452 . fact - factor 2453 2454 Not Collective on Mat, each process can have a different hash factor 2455 2456 Level: advanced 2457 2458 Notes: 2459 This can also be set by the command line option: -mat_use_hash_table fact 2460 2461 .keywords: matrix, hashtable, factor, HT 2462 2463 .seealso: MatSetOption() 2464 @XXXXX*/ 2465 2466 2467 #undef __FUNCT__ 2468 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2469 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2470 { 2471 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2472 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2473 PetscReal atmp; 2474 PetscReal *work,*svalues,*rvalues; 2475 PetscErrorCode ierr; 2476 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2477 PetscMPIInt rank,size; 2478 PetscInt *rowners_bs,dest,count,source; 2479 PetscScalar *va; 2480 MatScalar *ba; 2481 MPI_Status stat; 2482 2483 PetscFunctionBegin; 2484 if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2485 ierr = MatGetRowMaxAbs(a->A,v,PETSC_NULL);CHKERRQ(ierr); 2486 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2487 2488 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2489 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2490 2491 bs = A->rmap->bs; 2492 mbs = a->mbs; 2493 Mbs = a->Mbs; 2494 ba = b->a; 2495 bi = b->i; 2496 bj = b->j; 2497 2498 /* find ownerships */ 2499 rowners_bs = A->rmap->range; 2500 2501 /* each proc creates an array to be distributed */ 2502 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2503 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2504 2505 /* row_max for B */ 2506 if (rank != size-1) { 2507 for (i=0; i<mbs; i++) { 2508 ncols = bi[1] - bi[0]; bi++; 2509 brow = bs*i; 2510 for (j=0; j<ncols; j++) { 2511 bcol = bs*(*bj); 2512 for (kcol=0; kcol<bs; kcol++) { 2513 col = bcol + kcol; /* local col index */ 2514 col += rowners_bs[rank+1]; /* global col index */ 2515 for (krow=0; krow<bs; krow++) { 2516 atmp = PetscAbsScalar(*ba); ba++; 2517 row = brow + krow; /* local row index */ 2518 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2519 if (work[col] < atmp) work[col] = atmp; 2520 } 2521 } 2522 bj++; 2523 } 2524 } 2525 2526 /* send values to its owners */ 2527 for (dest=rank+1; dest<size; dest++) { 2528 svalues = work + rowners_bs[dest]; 2529 count = rowners_bs[dest+1]-rowners_bs[dest]; 2530 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);CHKERRQ(ierr); 2531 } 2532 } 2533 2534 /* receive values */ 2535 if (rank) { 2536 rvalues = work; 2537 count = rowners_bs[rank+1]-rowners_bs[rank]; 2538 for (source=0; source<rank; source++) { 2539 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);CHKERRQ(ierr); 2540 /* process values */ 2541 for (i=0; i<count; i++) { 2542 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2543 } 2544 } 2545 } 2546 2547 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2548 ierr = PetscFree(work);CHKERRQ(ierr); 2549 PetscFunctionReturn(0); 2550 } 2551 2552 #undef __FUNCT__ 2553 #define __FUNCT__ "MatSOR_MPISBAIJ" 2554 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2555 { 2556 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2557 PetscErrorCode ierr; 2558 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2559 PetscScalar *x,*ptr,*from; 2560 Vec bb1; 2561 const PetscScalar *b; 2562 2563 PetscFunctionBegin; 2564 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2565 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2566 2567 if (flag == SOR_APPLY_UPPER) { 2568 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2573 if (flag & SOR_ZERO_INITIAL_GUESS) { 2574 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2575 its--; 2576 } 2577 2578 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2579 while (its--) { 2580 2581 /* lower triangular part: slvec0b = - B^T*xx */ 2582 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2583 2584 /* copy xx into slvec0a */ 2585 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2586 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2587 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2588 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2589 2590 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2591 2592 /* copy bb into slvec1a */ 2593 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2594 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2595 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2596 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2597 2598 /* set slvec1b = 0 */ 2599 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2600 2601 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2602 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2603 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2604 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2605 2606 /* upper triangular part: bb1 = bb1 - B*x */ 2607 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2608 2609 /* local diagonal sweep */ 2610 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2611 } 2612 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2613 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2614 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2615 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2616 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2617 } else if (flag & SOR_EISENSTAT) { 2618 Vec xx1; 2619 PetscBool hasop; 2620 const PetscScalar *diag; 2621 PetscScalar *sl,scale = (omega - 2.0)/omega; 2622 PetscInt i,n; 2623 2624 if (!mat->xx1) { 2625 ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr); 2626 ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr); 2627 } 2628 xx1 = mat->xx1; 2629 bb1 = mat->bb1; 2630 2631 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 2632 2633 if (!mat->diag) { 2634 /* this is wrong for same matrix with new nonzero values */ 2635 ierr = MatGetVecs(matin,&mat->diag,PETSC_NULL);CHKERRQ(ierr); 2636 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 2637 } 2638 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 2639 2640 if (hasop) { 2641 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 2642 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2643 } else { 2644 /* 2645 These two lines are replaced by code that may be a bit faster for a good compiler 2646 ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr); 2647 ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr); 2648 */ 2649 ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2650 ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2651 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 2652 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2653 ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr); 2654 if (omega == 1.0) { 2655 for (i=0; i<n; i++) { 2656 sl[i] = b[i] - diag[i]*x[i]; 2657 } 2658 ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr); 2659 } else { 2660 for (i=0; i<n; i++) { 2661 sl[i] = b[i] + scale*diag[i]*x[i]; 2662 } 2663 ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr); 2664 } 2665 ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr); 2666 ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr); 2667 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2668 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2669 } 2670 2671 /* multiply off-diagonal portion of matrix */ 2672 ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr); 2673 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2674 ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr); 2675 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2676 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2677 ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr); 2678 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2679 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2680 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2681 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr); 2682 2683 /* local sweep */ 2684 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); 2685 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 2686 } else { 2687 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2688 } 2689 PetscFunctionReturn(0); 2690 } 2691 2692 #undef __FUNCT__ 2693 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm" 2694 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2695 { 2696 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2697 PetscErrorCode ierr; 2698 Vec lvec1,bb1; 2699 2700 PetscFunctionBegin; 2701 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); 2702 if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2703 2704 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2705 if (flag & SOR_ZERO_INITIAL_GUESS) { 2706 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2707 its--; 2708 } 2709 2710 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2711 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2712 while (its--) { 2713 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2714 2715 /* lower diagonal part: bb1 = bb - B^T*xx */ 2716 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2717 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2718 2719 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2720 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2721 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2722 2723 /* upper diagonal part: bb1 = bb1 - B*x */ 2724 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2725 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2726 2727 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2728 2729 /* diagonal sweep */ 2730 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2731 } 2732 ierr = VecDestroy(&lvec1);CHKERRQ(ierr); 2733 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2734 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2735 PetscFunctionReturn(0); 2736 } 2737 2738 #undef __FUNCT__ 2739 #define __FUNCT__ "MatCreateMPISBAIJWithArrays" 2740 /*@ 2741 MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard 2742 CSR format the local rows. 2743 2744 Collective on MPI_Comm 2745 2746 Input Parameters: 2747 + comm - MPI communicator 2748 . bs - the block size, only a block size of 1 is supported 2749 . m - number of local rows (Cannot be PETSC_DECIDE) 2750 . n - This value should be the same as the local size used in creating the 2751 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2752 calculated if N is given) For square matrices n is almost always m. 2753 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2754 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2755 . i - row indices 2756 . j - column indices 2757 - a - matrix values 2758 2759 Output Parameter: 2760 . mat - the matrix 2761 2762 Level: intermediate 2763 2764 Notes: 2765 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2766 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2767 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2768 2769 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2770 2771 .keywords: matrix, aij, compressed row, sparse, parallel 2772 2773 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 2774 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 2775 @*/ 2776 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) 2777 { 2778 PetscErrorCode ierr; 2779 2780 2781 PetscFunctionBegin; 2782 if (i[0]) { 2783 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 2784 } 2785 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2786 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 2787 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 2788 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 2789 ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 2790 PetscFunctionReturn(0); 2791 } 2792 2793 2794 #undef __FUNCT__ 2795 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR" 2796 /*@C 2797 MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2798 (the default parallel PETSc format). 2799 2800 Collective on MPI_Comm 2801 2802 Input Parameters: 2803 + A - the matrix 2804 . bs - the block size 2805 . i - the indices into j for the start of each local row (starts with zero) 2806 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2807 - v - optional values in the matrix 2808 2809 Level: developer 2810 2811 .keywords: matrix, aij, compressed row, sparse, parallel 2812 2813 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2814 @*/ 2815 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2816 { 2817 PetscErrorCode ierr; 2818 2819 PetscFunctionBegin; 2820 ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2821 PetscFunctionReturn(0); 2822 } 2823 2824 2825