1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "mpisbaij.h" 5 #include "src/mat/impls/sbaij/seq/sbaij.h" 6 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 8 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 EXTERN PetscErrorCode DisAssemble_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*); 19 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 20 EXTERN PetscErrorCode MatGetRowMax_MPISBAIJ(Mat,Vec); 21 EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 /* UGLY, ugly, ugly 24 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 25 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 26 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 27 converts the entries into single precision and then calls ..._MatScalar() to put them 28 into the single precision data structures. 29 */ 30 #if defined(PETSC_USE_MAT_SINGLE) 31 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 32 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 33 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 34 EXTERN PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 35 EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 36 #else 37 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 38 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 39 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 40 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 41 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 42 #endif 43 44 EXTERN_C_BEGIN 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 47 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPISBAIJ(Mat mat) 48 { 49 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 EXTERN_C_END 58 59 EXTERN_C_BEGIN 60 #undef __FUNCT__ 61 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 62 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPISBAIJ(Mat mat) 63 { 64 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 65 PetscErrorCode ierr; 66 67 PetscFunctionBegin; 68 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 69 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 70 PetscFunctionReturn(0); 71 } 72 EXTERN_C_END 73 74 75 #define CHUNKSIZE 10 76 77 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 78 { \ 79 \ 80 brow = row/bs; \ 81 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 82 rmax = aimax[brow]; nrow = ailen[brow]; \ 83 bcol = col/bs; \ 84 ridx = row % bs; cidx = col % bs; \ 85 low = 0; high = nrow; \ 86 while (high-low > 3) { \ 87 t = (low+high)/2; \ 88 if (rp[t] > bcol) high = t; \ 89 else low = t; \ 90 } \ 91 for (_i=low; _i<high; _i++) { \ 92 if (rp[_i] > bcol) break; \ 93 if (rp[_i] == bcol) { \ 94 bap = ap + bs2*_i + bs*cidx + ridx; \ 95 if (addv == ADD_VALUES) *bap += value; \ 96 else *bap = value; \ 97 goto a_noinsert; \ 98 } \ 99 } \ 100 if (a->nonew == 1) goto a_noinsert; \ 101 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 102 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew); \ 103 N = nrow++ - 1; \ 104 /* shift up all the later entries in this row */ \ 105 for (ii=N; ii>=_i; ii--) { \ 106 rp[ii+1] = rp[ii]; \ 107 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 108 } \ 109 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 110 rp[_i] = bcol; \ 111 ap[bs2*_i + bs*cidx + ridx] = value; \ 112 a_noinsert:; \ 113 ailen[brow] = nrow; \ 114 } 115 #ifndef MatSetValues_SeqBAIJ_B_Private 116 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 117 { \ 118 brow = row/bs; \ 119 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 120 rmax = bimax[brow]; nrow = bilen[brow]; \ 121 bcol = col/bs; \ 122 ridx = row % bs; cidx = col % bs; \ 123 low = 0; high = nrow; \ 124 while (high-low > 3) { \ 125 t = (low+high)/2; \ 126 if (rp[t] > bcol) high = t; \ 127 else low = t; \ 128 } \ 129 for (_i=low; _i<high; _i++) { \ 130 if (rp[_i] > bcol) break; \ 131 if (rp[_i] == bcol) { \ 132 bap = ap + bs2*_i + bs*cidx + ridx; \ 133 if (addv == ADD_VALUES) *bap += value; \ 134 else *bap = value; \ 135 goto b_noinsert; \ 136 } \ 137 } \ 138 if (b->nonew == 1) goto b_noinsert; \ 139 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 140 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew); \ 141 N = nrow++ - 1; \ 142 /* shift up all the later entries in this row */ \ 143 for (ii=N; ii>=_i; ii--) { \ 144 rp[ii+1] = rp[ii]; \ 145 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 146 } \ 147 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 148 rp[_i] = bcol; \ 149 ap[bs2*_i + bs*cidx + ridx] = value; \ 150 b_noinsert:; \ 151 bilen[brow] = nrow; \ 152 } 153 #endif 154 155 #if defined(PETSC_USE_MAT_SINGLE) 156 #undef __FUNCT__ 157 #define __FUNCT__ "MatSetValues_MPISBAIJ" 158 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 159 { 160 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 161 PetscErrorCode ierr; 162 PetscInt i,N = m*n; 163 MatScalar *vsingle; 164 165 PetscFunctionBegin; 166 if (N > b->setvalueslen) { 167 ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr); 168 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 169 b->setvalueslen = N; 170 } 171 vsingle = b->setvaluescopy; 172 173 for (i=0; i<N; i++) { 174 vsingle[i] = v[i]; 175 } 176 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 177 PetscFunctionReturn(0); 178 } 179 180 #undef __FUNCT__ 181 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 182 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 183 { 184 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 185 PetscErrorCode ierr; 186 PetscInt i,N = m*n*b->bs2; 187 MatScalar *vsingle; 188 189 PetscFunctionBegin; 190 if (N > b->setvalueslen) { 191 ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr); 192 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 193 b->setvalueslen = N; 194 } 195 vsingle = b->setvaluescopy; 196 for (i=0; i<N; i++) { 197 vsingle[i] = v[i]; 198 } 199 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 200 PetscFunctionReturn(0); 201 } 202 #endif 203 204 /* Only add/insert a(i,j) with i<=j (blocks). 205 Any a(i,j) with i>j input by user is ingored. 206 */ 207 #undef __FUNCT__ 208 #define __FUNCT__ "MatSetValues_MPISBAIJ_MatScalar" 209 PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 210 { 211 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 212 MatScalar value; 213 PetscTruth roworiented = baij->roworiented; 214 PetscErrorCode ierr; 215 PetscInt i,j,row,col; 216 PetscInt rstart_orig=mat->rmap.rstart; 217 PetscInt rend_orig=mat->rmap.rend,cstart_orig=mat->cmap.rstart; 218 PetscInt cend_orig=mat->cmap.rend,bs=mat->rmap.bs; 219 220 /* Some Variables required in the macro */ 221 Mat A = baij->A; 222 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 223 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 224 MatScalar *aa=a->a; 225 226 Mat B = baij->B; 227 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 228 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 229 MatScalar *ba=b->a; 230 231 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 232 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 233 MatScalar *ap,*bap; 234 235 /* for stash */ 236 PetscInt n_loc, *in_loc = PETSC_NULL; 237 MatScalar *v_loc = PETSC_NULL; 238 239 PetscFunctionBegin; 240 241 if (!baij->donotstash){ 242 if (n > baij->n_loc) { 243 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 244 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 245 ierr = PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);CHKERRQ(ierr); 246 ierr = PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);CHKERRQ(ierr); 247 baij->n_loc = n; 248 } 249 in_loc = baij->in_loc; 250 v_loc = baij->v_loc; 251 } 252 253 for (i=0; i<m; i++) { 254 if (im[i] < 0) continue; 255 #if defined(PETSC_USE_DEBUG) 256 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 257 #endif 258 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 259 row = im[i] - rstart_orig; /* local row index */ 260 for (j=0; j<n; j++) { 261 if (im[i]/bs > in[j]/bs){ 262 if (a->ignore_ltriangular){ 263 continue; /* ignore lower triangular blocks */ 264 } else { 265 SETERRQ(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)"); 266 } 267 } 268 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 269 col = in[j] - cstart_orig; /* local col index */ 270 brow = row/bs; bcol = col/bs; 271 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 272 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 273 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 274 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 275 } else if (in[j] < 0) continue; 276 #if defined(PETSC_USE_DEBUG) 277 else if (in[j] >= mat->cmap.N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap.N-1);} 278 #endif 279 else { /* off-diag entry (B) */ 280 if (mat->was_assembled) { 281 if (!baij->colmap) { 282 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 283 } 284 #if defined (PETSC_USE_CTABLE) 285 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 286 col = col - 1; 287 #else 288 col = baij->colmap[in[j]/bs] - 1; 289 #endif 290 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 291 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 292 col = in[j]; 293 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 294 B = baij->B; 295 b = (Mat_SeqBAIJ*)(B)->data; 296 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 297 ba=b->a; 298 } else col += in[j]%bs; 299 } else col = in[j]; 300 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 301 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 302 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 303 } 304 } 305 } else { /* off processor entry */ 306 if (!baij->donotstash) { 307 n_loc = 0; 308 for (j=0; j<n; j++){ 309 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 310 in_loc[n_loc] = in[j]; 311 if (roworiented) { 312 v_loc[n_loc] = v[i*n+j]; 313 } else { 314 v_loc[n_loc] = v[j*m+i]; 315 } 316 n_loc++; 317 } 318 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 319 } 320 } 321 } 322 PetscFunctionReturn(0); 323 } 324 325 #undef __FUNCT__ 326 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 327 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 328 { 329 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 330 const MatScalar *value; 331 MatScalar *barray=baij->barray; 332 PetscTruth roworiented = baij->roworiented; 333 PetscErrorCode ierr; 334 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 335 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 336 PetscInt cend=baij->rendbs,bs=mat->rmap.bs,bs2=baij->bs2; 337 338 PetscFunctionBegin; 339 if(!barray) { 340 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 341 baij->barray = barray; 342 } 343 344 if (roworiented) { 345 stepval = (n-1)*bs; 346 } else { 347 stepval = (m-1)*bs; 348 } 349 for (i=0; i<m; i++) { 350 if (im[i] < 0) continue; 351 #if defined(PETSC_USE_DEBUG) 352 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 353 #endif 354 if (im[i] >= rstart && im[i] < rend) { 355 row = im[i] - rstart; 356 for (j=0; j<n; j++) { 357 /* If NumCol = 1 then a copy is not required */ 358 if ((roworiented) && (n == 1)) { 359 barray = (MatScalar*) v + i*bs2; 360 } else if((!roworiented) && (m == 1)) { 361 barray = (MatScalar*) v + j*bs2; 362 } else { /* Here a copy is required */ 363 if (roworiented) { 364 value = v + i*(stepval+bs)*bs + j*bs; 365 } else { 366 value = v + j*(stepval+bs)*bs + i*bs; 367 } 368 for (ii=0; ii<bs; ii++,value+=stepval) { 369 for (jj=0; jj<bs; jj++) { 370 *barray++ = *value++; 371 } 372 } 373 barray -=bs2; 374 } 375 376 if (in[j] >= cstart && in[j] < cend){ 377 col = in[j] - cstart; 378 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 379 } 380 else if (in[j] < 0) continue; 381 #if defined(PETSC_USE_DEBUG) 382 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 383 #endif 384 else { 385 if (mat->was_assembled) { 386 if (!baij->colmap) { 387 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 388 } 389 390 #if defined(PETSC_USE_DEBUG) 391 #if defined (PETSC_USE_CTABLE) 392 { PetscInt data; 393 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 394 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 395 } 396 #else 397 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 398 #endif 399 #endif 400 #if defined (PETSC_USE_CTABLE) 401 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 402 col = (col - 1)/bs; 403 #else 404 col = (baij->colmap[in[j]] - 1)/bs; 405 #endif 406 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 407 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 408 col = in[j]; 409 } 410 } 411 else col = in[j]; 412 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 413 } 414 } 415 } else { 416 if (!baij->donotstash) { 417 if (roworiented) { 418 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 419 } else { 420 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 421 } 422 } 423 } 424 } 425 PetscFunctionReturn(0); 426 } 427 428 #undef __FUNCT__ 429 #define __FUNCT__ "MatGetValues_MPISBAIJ" 430 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 431 { 432 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 433 PetscErrorCode ierr; 434 PetscInt bs=mat->rmap.bs,i,j,bsrstart = mat->rmap.rstart,bsrend = mat->rmap.rend; 435 PetscInt bscstart = mat->cmap.rstart,bscend = mat->cmap.rend,row,col,data; 436 437 PetscFunctionBegin; 438 for (i=0; i<m; i++) { 439 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); 440 if (idxm[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap.N-1); 441 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 442 row = idxm[i] - bsrstart; 443 for (j=0; j<n; j++) { 444 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); 445 if (idxn[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap.N-1); 446 if (idxn[j] >= bscstart && idxn[j] < bscend){ 447 col = idxn[j] - bscstart; 448 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 449 } else { 450 if (!baij->colmap) { 451 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 452 } 453 #if defined (PETSC_USE_CTABLE) 454 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 455 data --; 456 #else 457 data = baij->colmap[idxn[j]/bs]-1; 458 #endif 459 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 460 else { 461 col = data + idxn[j]%bs; 462 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 463 } 464 } 465 } 466 } else { 467 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 468 } 469 } 470 PetscFunctionReturn(0); 471 } 472 473 #undef __FUNCT__ 474 #define __FUNCT__ "MatNorm_MPISBAIJ" 475 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 476 { 477 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 478 PetscErrorCode ierr; 479 PetscReal sum[2],*lnorm2; 480 481 PetscFunctionBegin; 482 if (baij->size == 1) { 483 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 484 } else { 485 if (type == NORM_FROBENIUS) { 486 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 487 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 488 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 489 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 490 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 491 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 492 *norm = sqrt(sum[0] + 2*sum[1]); 493 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 494 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 495 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 496 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 497 PetscReal *rsum,*rsum2,vabs; 498 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 499 PetscInt brow,bcol,col,bs=baij->A->rmap.bs,row,grow,gcol,mbs=amat->mbs; 500 MatScalar *v; 501 502 ierr = PetscMalloc((2*mat->cmap.N+1)*sizeof(PetscReal),&rsum);CHKERRQ(ierr); 503 rsum2 = rsum + mat->cmap.N; 504 ierr = PetscMemzero(rsum,mat->cmap.N*sizeof(PetscReal));CHKERRQ(ierr); 505 /* Amat */ 506 v = amat->a; jj = amat->j; 507 for (brow=0; brow<mbs; brow++) { 508 grow = bs*(rstart + brow); 509 nz = amat->i[brow+1] - amat->i[brow]; 510 for (bcol=0; bcol<nz; bcol++){ 511 gcol = bs*(rstart + *jj); jj++; 512 for (col=0; col<bs; col++){ 513 for (row=0; row<bs; row++){ 514 vabs = PetscAbsScalar(*v); v++; 515 rsum[gcol+col] += vabs; 516 /* non-diagonal block */ 517 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 518 } 519 } 520 } 521 } 522 /* Bmat */ 523 v = bmat->a; jj = bmat->j; 524 for (brow=0; brow<mbs; brow++) { 525 grow = bs*(rstart + brow); 526 nz = bmat->i[brow+1] - bmat->i[brow]; 527 for (bcol=0; bcol<nz; bcol++){ 528 gcol = bs*garray[*jj]; jj++; 529 for (col=0; col<bs; col++){ 530 for (row=0; row<bs; row++){ 531 vabs = PetscAbsScalar(*v); v++; 532 rsum[gcol+col] += vabs; 533 rsum[grow+row] += vabs; 534 } 535 } 536 } 537 } 538 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap.N,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 539 *norm = 0.0; 540 for (col=0; col<mat->cmap.N; col++) { 541 if (rsum2[col] > *norm) *norm = rsum2[col]; 542 } 543 ierr = PetscFree(rsum);CHKERRQ(ierr); 544 } else { 545 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 546 } 547 } 548 PetscFunctionReturn(0); 549 } 550 551 #undef __FUNCT__ 552 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 553 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 554 { 555 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 556 PetscErrorCode ierr; 557 PetscInt nstash,reallocs; 558 InsertMode addv; 559 560 PetscFunctionBegin; 561 if (baij->donotstash) { 562 PetscFunctionReturn(0); 563 } 564 565 /* make sure all processors are either in INSERTMODE or ADDMODE */ 566 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 567 if (addv == (ADD_VALUES|INSERT_VALUES)) { 568 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 569 } 570 mat->insertmode = addv; /* in case this processor had no cache */ 571 572 ierr = MatStashScatterBegin_Private(&mat->stash,mat->rmap.range);CHKERRQ(ierr); 573 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rangebs);CHKERRQ(ierr); 574 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 575 ierr = PetscInfo2(0,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 576 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 577 ierr = PetscInfo2(0,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 578 PetscFunctionReturn(0); 579 } 580 581 #undef __FUNCT__ 582 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 583 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 584 { 585 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 586 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 587 PetscErrorCode ierr; 588 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 589 PetscInt *row,*col,other_disassembled; 590 PetscMPIInt n; 591 PetscTruth r1,r2,r3; 592 MatScalar *val; 593 InsertMode addv = mat->insertmode; 594 595 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 596 PetscFunctionBegin; 597 598 if (!baij->donotstash) { 599 while (1) { 600 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 601 if (!flg) break; 602 603 for (i=0; i<n;) { 604 /* Now identify the consecutive vals belonging to the same row */ 605 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 606 if (j < n) ncols = j-i; 607 else ncols = n-i; 608 /* Now assemble all these values with a single function call */ 609 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 610 i = j; 611 } 612 } 613 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 614 /* Now process the block-stash. Since the values are stashed column-oriented, 615 set the roworiented flag to column oriented, and after MatSetValues() 616 restore the original flags */ 617 r1 = baij->roworiented; 618 r2 = a->roworiented; 619 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 620 baij->roworiented = PETSC_FALSE; 621 a->roworiented = PETSC_FALSE; 622 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 623 while (1) { 624 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 625 if (!flg) break; 626 627 for (i=0; i<n;) { 628 /* Now identify the consecutive vals belonging to the same row */ 629 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 630 if (j < n) ncols = j-i; 631 else ncols = n-i; 632 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 633 i = j; 634 } 635 } 636 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 637 baij->roworiented = r1; 638 a->roworiented = r2; 639 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 640 } 641 642 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 643 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 644 645 /* determine if any processor has disassembled, if so we must 646 also disassemble ourselfs, in order that we may reassemble. */ 647 /* 648 if nonzero structure of submatrix B cannot change then we know that 649 no processor disassembled thus we can skip this stuff 650 */ 651 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 652 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 653 if (mat->was_assembled && !other_disassembled) { 654 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 655 } 656 } 657 658 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 659 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 660 } 661 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 662 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 663 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 664 665 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 666 baij->rowvalues = 0; 667 668 PetscFunctionReturn(0); 669 } 670 671 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 672 #undef __FUNCT__ 673 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 674 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 675 { 676 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 677 PetscErrorCode ierr; 678 PetscInt bs = mat->rmap.bs; 679 PetscMPIInt size = baij->size,rank = baij->rank; 680 PetscTruth iascii,isdraw; 681 PetscViewer sviewer; 682 PetscViewerFormat format; 683 684 PetscFunctionBegin; 685 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 686 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 687 if (iascii) { 688 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 689 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 690 MatInfo info; 691 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 692 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 693 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 694 rank,mat->rmap.N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 695 mat->rmap.bs,(PetscInt)info.memory);CHKERRQ(ierr); 696 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 697 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 698 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 699 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 700 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 701 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 702 PetscFunctionReturn(0); 703 } else if (format == PETSC_VIEWER_ASCII_INFO) { 704 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 705 PetscFunctionReturn(0); 706 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 707 PetscFunctionReturn(0); 708 } 709 } 710 711 if (isdraw) { 712 PetscDraw draw; 713 PetscTruth isnull; 714 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 715 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 716 } 717 718 if (size == 1) { 719 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 720 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 721 } else { 722 /* assemble the entire matrix onto first processor. */ 723 Mat A; 724 Mat_SeqSBAIJ *Aloc; 725 Mat_SeqBAIJ *Bloc; 726 PetscInt M = mat->rmap.N,N = mat->cmap.N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 727 MatScalar *a; 728 729 /* Should this be the same type as mat? */ 730 ierr = MatCreate(mat->comm,&A);CHKERRQ(ierr); 731 if (!rank) { 732 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 733 } else { 734 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 735 } 736 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 737 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap.bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 738 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 739 740 /* copy over the A part */ 741 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 742 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 743 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 744 745 for (i=0; i<mbs; i++) { 746 rvals[0] = bs*(baij->rstartbs + i); 747 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 748 for (j=ai[i]; j<ai[i+1]; j++) { 749 col = (baij->cstartbs+aj[j])*bs; 750 for (k=0; k<bs; k++) { 751 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 752 col++; a += bs; 753 } 754 } 755 } 756 /* copy over the B part */ 757 Bloc = (Mat_SeqBAIJ*)baij->B->data; 758 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 759 for (i=0; i<mbs; i++) { 760 761 rvals[0] = bs*(baij->rstartbs + i); 762 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 763 for (j=ai[i]; j<ai[i+1]; j++) { 764 col = baij->garray[aj[j]]*bs; 765 for (k=0; k<bs; k++) { 766 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 767 col++; a += bs; 768 } 769 } 770 } 771 ierr = PetscFree(rvals);CHKERRQ(ierr); 772 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 773 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 774 /* 775 Everyone has to call to draw the matrix since the graphics waits are 776 synchronized across all processors that share the PetscDraw object 777 */ 778 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 779 if (!rank) { 780 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 781 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 782 } 783 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 784 ierr = MatDestroy(A);CHKERRQ(ierr); 785 } 786 PetscFunctionReturn(0); 787 } 788 789 #undef __FUNCT__ 790 #define __FUNCT__ "MatView_MPISBAIJ" 791 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 792 { 793 PetscErrorCode ierr; 794 PetscTruth iascii,isdraw,issocket,isbinary; 795 796 PetscFunctionBegin; 797 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 798 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 799 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 800 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 801 if (iascii || isdraw || issocket || isbinary) { 802 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 803 } else { 804 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 805 } 806 PetscFunctionReturn(0); 807 } 808 809 #undef __FUNCT__ 810 #define __FUNCT__ "MatDestroy_MPISBAIJ" 811 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 812 { 813 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 814 PetscErrorCode ierr; 815 816 PetscFunctionBegin; 817 #if defined(PETSC_USE_LOG) 818 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap.N,mat->cmap.N); 819 #endif 820 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 821 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 822 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 823 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 824 #if defined (PETSC_USE_CTABLE) 825 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 826 #else 827 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 828 #endif 829 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 830 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 831 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 832 if (baij->slvec0) { 833 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 834 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 835 } 836 if (baij->slvec1) { 837 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 838 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 839 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 840 } 841 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 842 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 843 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 844 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 845 #if defined(PETSC_USE_MAT_SINGLE) 846 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 847 #endif 848 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 849 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 850 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 851 ierr = PetscFree(baij);CHKERRQ(ierr); 852 853 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 854 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 855 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 856 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 857 PetscFunctionReturn(0); 858 } 859 860 #undef __FUNCT__ 861 #define __FUNCT__ "MatMult_MPISBAIJ" 862 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 863 { 864 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 865 PetscErrorCode ierr; 866 PetscInt nt,mbs=a->mbs,bs=A->rmap.bs; 867 PetscScalar *x,*from,zero=0.0; 868 869 PetscFunctionBegin; 870 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 871 if (nt != A->cmap.n) { 872 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 873 } 874 875 /* diagonal part */ 876 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 877 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 878 879 /* subdiagonal part */ 880 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 881 CHKMEMQ; 882 /* copy x into the vec slvec0 */ 883 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 884 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 885 CHKMEMQ; 886 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 887 CHKMEMQ; 888 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 889 890 CHKMEMQ; 891 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 892 CHKMEMQ; 893 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 894 CHKMEMQ; 895 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 896 CHKMEMQ; 897 /* supperdiagonal part */ 898 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 899 CHKMEMQ; 900 PetscFunctionReturn(0); 901 } 902 903 #undef __FUNCT__ 904 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 905 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 906 { 907 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 908 PetscErrorCode ierr; 909 PetscInt nt; 910 911 PetscFunctionBegin; 912 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 913 if (nt != A->cmap.n) { 914 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 915 } 916 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 917 if (nt != A->rmap.N) { 918 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 919 } 920 921 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 922 /* do diagonal part */ 923 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 924 /* do supperdiagonal part */ 925 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 926 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 927 /* do subdiagonal part */ 928 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 929 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 930 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 931 932 PetscFunctionReturn(0); 933 } 934 935 #undef __FUNCT__ 936 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 937 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 938 { 939 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 940 PetscErrorCode ierr; 941 PetscInt mbs=a->mbs,bs=A->rmap.bs; 942 PetscScalar *x,*from,zero=0.0; 943 944 PetscFunctionBegin; 945 /* 946 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 947 PetscSynchronizedFlush(A->comm); 948 */ 949 /* diagonal part */ 950 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 951 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 952 953 /* subdiagonal part */ 954 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 955 956 /* copy x into the vec slvec0 */ 957 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 958 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 959 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 960 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 961 962 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 963 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 964 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 965 966 /* supperdiagonal part */ 967 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 968 969 PetscFunctionReturn(0); 970 } 971 972 #undef __FUNCT__ 973 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 974 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 975 { 976 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 977 PetscErrorCode ierr; 978 979 PetscFunctionBegin; 980 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 981 /* do diagonal part */ 982 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 983 /* do supperdiagonal part */ 984 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 985 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 986 987 /* do subdiagonal part */ 988 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 989 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 990 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 991 992 PetscFunctionReturn(0); 993 } 994 995 /* 996 This only works correctly for square matrices where the subblock A->A is the 997 diagonal block 998 */ 999 #undef __FUNCT__ 1000 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1001 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1002 { 1003 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1004 PetscErrorCode ierr; 1005 1006 PetscFunctionBegin; 1007 /* if (a->rmap.N != a->cmap.N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1008 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1009 PetscFunctionReturn(0); 1010 } 1011 1012 #undef __FUNCT__ 1013 #define __FUNCT__ "MatScale_MPISBAIJ" 1014 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 1015 { 1016 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1017 PetscErrorCode ierr; 1018 1019 PetscFunctionBegin; 1020 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1021 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1022 PetscFunctionReturn(0); 1023 } 1024 1025 #undef __FUNCT__ 1026 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1027 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1028 { 1029 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1030 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1031 PetscErrorCode ierr; 1032 PetscInt bs = matin->rmap.bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1033 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap.rstart,brend = matin->rmap.rend; 1034 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 1035 1036 PetscFunctionBegin; 1037 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1038 mat->getrowactive = PETSC_TRUE; 1039 1040 if (!mat->rowvalues && (idx || v)) { 1041 /* 1042 allocate enough space to hold information from the longest row. 1043 */ 1044 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1045 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1046 PetscInt max = 1,mbs = mat->mbs,tmp; 1047 for (i=0; i<mbs; i++) { 1048 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1049 if (max < tmp) { max = tmp; } 1050 } 1051 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1052 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1053 } 1054 1055 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1056 lrow = row - brstart; /* local row index */ 1057 1058 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1059 if (!v) {pvA = 0; pvB = 0;} 1060 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1061 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1062 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1063 nztot = nzA + nzB; 1064 1065 cmap = mat->garray; 1066 if (v || idx) { 1067 if (nztot) { 1068 /* Sort by increasing column numbers, assuming A and B already sorted */ 1069 PetscInt imark = -1; 1070 if (v) { 1071 *v = v_p = mat->rowvalues; 1072 for (i=0; i<nzB; i++) { 1073 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1074 else break; 1075 } 1076 imark = i; 1077 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1078 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1079 } 1080 if (idx) { 1081 *idx = idx_p = mat->rowindices; 1082 if (imark > -1) { 1083 for (i=0; i<imark; i++) { 1084 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1085 } 1086 } else { 1087 for (i=0; i<nzB; i++) { 1088 if (cmap[cworkB[i]/bs] < cstart) 1089 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1090 else break; 1091 } 1092 imark = i; 1093 } 1094 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1095 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1096 } 1097 } else { 1098 if (idx) *idx = 0; 1099 if (v) *v = 0; 1100 } 1101 } 1102 *nz = nztot; 1103 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1104 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1105 PetscFunctionReturn(0); 1106 } 1107 1108 #undef __FUNCT__ 1109 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1110 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1111 { 1112 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1113 1114 PetscFunctionBegin; 1115 if (!baij->getrowactive) { 1116 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1117 } 1118 baij->getrowactive = PETSC_FALSE; 1119 PetscFunctionReturn(0); 1120 } 1121 1122 #undef __FUNCT__ 1123 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1124 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1125 { 1126 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1127 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1128 1129 PetscFunctionBegin; 1130 aA->getrow_utriangular = PETSC_TRUE; 1131 PetscFunctionReturn(0); 1132 } 1133 #undef __FUNCT__ 1134 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1135 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1136 { 1137 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1138 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1139 1140 PetscFunctionBegin; 1141 aA->getrow_utriangular = PETSC_FALSE; 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1147 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1148 { 1149 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 1152 PetscFunctionBegin; 1153 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1154 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1155 PetscFunctionReturn(0); 1156 } 1157 1158 #undef __FUNCT__ 1159 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1160 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1161 { 1162 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1163 PetscErrorCode ierr; 1164 1165 PetscFunctionBegin; 1166 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1167 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1168 PetscFunctionReturn(0); 1169 } 1170 1171 #undef __FUNCT__ 1172 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1173 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1174 { 1175 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1176 PetscErrorCode ierr; 1177 1178 PetscFunctionBegin; 1179 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1180 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1181 PetscFunctionReturn(0); 1182 } 1183 1184 #undef __FUNCT__ 1185 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1186 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1187 { 1188 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1189 Mat A = a->A,B = a->B; 1190 PetscErrorCode ierr; 1191 PetscReal isend[5],irecv[5]; 1192 1193 PetscFunctionBegin; 1194 info->block_size = (PetscReal)matin->rmap.bs; 1195 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1196 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1197 isend[3] = info->memory; isend[4] = info->mallocs; 1198 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1199 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1200 isend[3] += info->memory; isend[4] += info->mallocs; 1201 if (flag == MAT_LOCAL) { 1202 info->nz_used = isend[0]; 1203 info->nz_allocated = isend[1]; 1204 info->nz_unneeded = isend[2]; 1205 info->memory = isend[3]; 1206 info->mallocs = isend[4]; 1207 } else if (flag == MAT_GLOBAL_MAX) { 1208 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1209 info->nz_used = irecv[0]; 1210 info->nz_allocated = irecv[1]; 1211 info->nz_unneeded = irecv[2]; 1212 info->memory = irecv[3]; 1213 info->mallocs = irecv[4]; 1214 } else if (flag == MAT_GLOBAL_SUM) { 1215 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1216 info->nz_used = irecv[0]; 1217 info->nz_allocated = irecv[1]; 1218 info->nz_unneeded = irecv[2]; 1219 info->memory = irecv[3]; 1220 info->mallocs = irecv[4]; 1221 } else { 1222 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1223 } 1224 info->rows_global = (PetscReal)A->rmap.N; 1225 info->columns_global = (PetscReal)A->cmap.N; 1226 info->rows_local = (PetscReal)A->rmap.N; 1227 info->columns_local = (PetscReal)A->cmap.N; 1228 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1229 info->fill_ratio_needed = 0; 1230 info->factor_mallocs = 0; 1231 PetscFunctionReturn(0); 1232 } 1233 1234 #undef __FUNCT__ 1235 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1236 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1237 { 1238 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1239 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1240 PetscErrorCode ierr; 1241 1242 PetscFunctionBegin; 1243 switch (op) { 1244 case MAT_NO_NEW_NONZERO_LOCATIONS: 1245 case MAT_YES_NEW_NONZERO_LOCATIONS: 1246 case MAT_COLUMNS_UNSORTED: 1247 case MAT_COLUMNS_SORTED: 1248 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1249 case MAT_KEEP_ZEROED_ROWS: 1250 case MAT_NEW_NONZERO_LOCATION_ERR: 1251 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1252 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1253 break; 1254 case MAT_ROW_ORIENTED: 1255 a->roworiented = PETSC_TRUE; 1256 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1257 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1258 break; 1259 case MAT_ROWS_SORTED: 1260 case MAT_ROWS_UNSORTED: 1261 case MAT_YES_NEW_DIAGONALS: 1262 ierr = PetscInfo1(A,"Option %d ignored\n",op);CHKERRQ(ierr); 1263 break; 1264 case MAT_COLUMN_ORIENTED: 1265 a->roworiented = PETSC_FALSE; 1266 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1267 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1268 break; 1269 case MAT_IGNORE_OFF_PROC_ENTRIES: 1270 a->donotstash = PETSC_TRUE; 1271 break; 1272 case MAT_NO_NEW_DIAGONALS: 1273 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1274 case MAT_USE_HASH_TABLE: 1275 a->ht_flag = PETSC_TRUE; 1276 break; 1277 case MAT_NOT_SYMMETRIC: 1278 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1279 case MAT_HERMITIAN: 1280 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1281 case MAT_SYMMETRIC: 1282 case MAT_STRUCTURALLY_SYMMETRIC: 1283 case MAT_NOT_HERMITIAN: 1284 case MAT_SYMMETRY_ETERNAL: 1285 case MAT_NOT_SYMMETRY_ETERNAL: 1286 break; 1287 case MAT_IGNORE_LOWER_TRIANGULAR: 1288 aA->ignore_ltriangular = PETSC_TRUE; 1289 break; 1290 case MAT_ERROR_LOWER_TRIANGULAR: 1291 aA->ignore_ltriangular = PETSC_FALSE; 1292 break; 1293 case MAT_GETROW_UPPERTRIANGULAR: 1294 aA->getrow_utriangular = PETSC_TRUE; 1295 break; 1296 default: 1297 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1298 } 1299 PetscFunctionReturn(0); 1300 } 1301 1302 #undef __FUNCT__ 1303 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1304 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1305 { 1306 PetscErrorCode ierr; 1307 PetscFunctionBegin; 1308 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1309 PetscFunctionReturn(0); 1310 } 1311 1312 #undef __FUNCT__ 1313 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1314 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1315 { 1316 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1317 Mat a=baij->A, b=baij->B; 1318 PetscErrorCode ierr; 1319 PetscInt nv,m,n; 1320 PetscTruth flg; 1321 1322 PetscFunctionBegin; 1323 if (ll != rr){ 1324 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1325 if (!flg) 1326 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1327 } 1328 if (!ll) PetscFunctionReturn(0); 1329 1330 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1331 if (m != n) SETERRQ2(PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1332 1333 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1334 if (nv!=n) SETERRQ(PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1335 1336 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1337 1338 /* left diagonalscale the off-diagonal part */ 1339 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1340 1341 /* scale the diagonal part */ 1342 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1343 1344 /* right diagonalscale the off-diagonal part */ 1345 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1346 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1347 PetscFunctionReturn(0); 1348 } 1349 1350 #undef __FUNCT__ 1351 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1352 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1353 { 1354 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1355 PetscErrorCode ierr; 1356 1357 PetscFunctionBegin; 1358 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1359 PetscFunctionReturn(0); 1360 } 1361 1362 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1363 1364 #undef __FUNCT__ 1365 #define __FUNCT__ "MatEqual_MPISBAIJ" 1366 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1367 { 1368 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1369 Mat a,b,c,d; 1370 PetscTruth flg; 1371 PetscErrorCode ierr; 1372 1373 PetscFunctionBegin; 1374 a = matA->A; b = matA->B; 1375 c = matB->A; d = matB->B; 1376 1377 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1378 if (flg) { 1379 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1380 } 1381 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1382 PetscFunctionReturn(0); 1383 } 1384 1385 #undef __FUNCT__ 1386 #define __FUNCT__ "MatCopy_MPISBAIJ" 1387 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1388 { 1389 PetscErrorCode ierr; 1390 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1391 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1392 1393 PetscFunctionBegin; 1394 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1395 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1396 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1397 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1398 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1399 } else { 1400 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1401 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1402 } 1403 PetscFunctionReturn(0); 1404 } 1405 1406 #undef __FUNCT__ 1407 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1408 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1409 { 1410 PetscErrorCode ierr; 1411 1412 PetscFunctionBegin; 1413 ierr = MatMPISBAIJSetPreallocation(A,PetscMax(A->rmap.bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1414 PetscFunctionReturn(0); 1415 } 1416 1417 #include "petscblaslapack.h" 1418 #undef __FUNCT__ 1419 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1420 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1421 { 1422 PetscErrorCode ierr; 1423 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data; 1424 PetscBLASInt bnz,one=1; 1425 Mat_SeqSBAIJ *xa,*ya; 1426 Mat_SeqBAIJ *xb,*yb; 1427 1428 PetscFunctionBegin; 1429 if (str == SAME_NONZERO_PATTERN) { 1430 PetscScalar alpha = a; 1431 xa = (Mat_SeqSBAIJ *)xx->A->data; 1432 ya = (Mat_SeqSBAIJ *)yy->A->data; 1433 bnz = (PetscBLASInt)xa->nz; 1434 BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one); 1435 xb = (Mat_SeqBAIJ *)xx->B->data; 1436 yb = (Mat_SeqBAIJ *)yy->B->data; 1437 bnz = (PetscBLASInt)xb->nz; 1438 BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one); 1439 } else { 1440 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1441 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1442 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1443 } 1444 PetscFunctionReturn(0); 1445 } 1446 1447 #undef __FUNCT__ 1448 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1449 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1450 { 1451 PetscErrorCode ierr; 1452 PetscInt i; 1453 PetscTruth flg; 1454 1455 PetscFunctionBegin; 1456 for (i=0; i<n; i++) { 1457 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1458 if (!flg) { 1459 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1460 } 1461 } 1462 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1463 PetscFunctionReturn(0); 1464 } 1465 1466 1467 /* -------------------------------------------------------------------*/ 1468 static struct _MatOps MatOps_Values = { 1469 MatSetValues_MPISBAIJ, 1470 MatGetRow_MPISBAIJ, 1471 MatRestoreRow_MPISBAIJ, 1472 MatMult_MPISBAIJ, 1473 /* 4*/ MatMultAdd_MPISBAIJ, 1474 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1475 MatMultAdd_MPISBAIJ, 1476 0, 1477 0, 1478 0, 1479 /*10*/ 0, 1480 0, 1481 0, 1482 MatRelax_MPISBAIJ, 1483 MatTranspose_MPISBAIJ, 1484 /*15*/ MatGetInfo_MPISBAIJ, 1485 MatEqual_MPISBAIJ, 1486 MatGetDiagonal_MPISBAIJ, 1487 MatDiagonalScale_MPISBAIJ, 1488 MatNorm_MPISBAIJ, 1489 /*20*/ MatAssemblyBegin_MPISBAIJ, 1490 MatAssemblyEnd_MPISBAIJ, 1491 0, 1492 MatSetOption_MPISBAIJ, 1493 MatZeroEntries_MPISBAIJ, 1494 /*25*/ 0, 1495 0, 1496 0, 1497 0, 1498 0, 1499 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1500 0, 1501 0, 1502 0, 1503 0, 1504 /*35*/ MatDuplicate_MPISBAIJ, 1505 0, 1506 0, 1507 0, 1508 0, 1509 /*40*/ MatAXPY_MPISBAIJ, 1510 MatGetSubMatrices_MPISBAIJ, 1511 MatIncreaseOverlap_MPISBAIJ, 1512 MatGetValues_MPISBAIJ, 1513 MatCopy_MPISBAIJ, 1514 /*45*/ 0, 1515 MatScale_MPISBAIJ, 1516 0, 1517 0, 1518 0, 1519 /*50*/ 0, 1520 0, 1521 0, 1522 0, 1523 0, 1524 /*55*/ 0, 1525 0, 1526 MatSetUnfactored_MPISBAIJ, 1527 0, 1528 MatSetValuesBlocked_MPISBAIJ, 1529 /*60*/ 0, 1530 0, 1531 0, 1532 0, 1533 0, 1534 /*65*/ 0, 1535 0, 1536 0, 1537 0, 1538 0, 1539 /*70*/ MatGetRowMax_MPISBAIJ, 1540 0, 1541 0, 1542 0, 1543 0, 1544 /*75*/ 0, 1545 0, 1546 0, 1547 0, 1548 0, 1549 /*80*/ 0, 1550 0, 1551 0, 1552 0, 1553 MatLoad_MPISBAIJ, 1554 /*85*/ 0, 1555 0, 1556 0, 1557 0, 1558 0, 1559 /*90*/ 0, 1560 0, 1561 0, 1562 0, 1563 0, 1564 /*95*/ 0, 1565 0, 1566 0, 1567 0, 1568 0, 1569 /*100*/0, 1570 0, 1571 0, 1572 0, 1573 0, 1574 /*105*/0, 1575 MatRealPart_MPISBAIJ, 1576 MatImaginaryPart_MPISBAIJ, 1577 MatGetRowUpperTriangular_MPISBAIJ, 1578 MatRestoreRowUpperTriangular_MPISBAIJ 1579 }; 1580 1581 1582 EXTERN_C_BEGIN 1583 #undef __FUNCT__ 1584 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1585 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1586 { 1587 PetscFunctionBegin; 1588 *a = ((Mat_MPISBAIJ *)A->data)->A; 1589 *iscopy = PETSC_FALSE; 1590 PetscFunctionReturn(0); 1591 } 1592 EXTERN_C_END 1593 1594 EXTERN_C_BEGIN 1595 #undef __FUNCT__ 1596 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1597 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1598 { 1599 Mat_MPISBAIJ *b; 1600 PetscErrorCode ierr; 1601 PetscInt i,mbs,Mbs; 1602 1603 PetscFunctionBegin; 1604 ierr = PetscOptionsBegin(B->comm,B->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 1605 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 1606 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1607 1608 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1609 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1610 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1611 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1612 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1613 1614 B->rmap.bs = B->cmap.bs = bs; 1615 ierr = PetscMapInitialize(B->comm,&B->rmap);CHKERRQ(ierr); 1616 ierr = PetscMapInitialize(B->comm,&B->cmap);CHKERRQ(ierr); 1617 1618 if (d_nnz) { 1619 for (i=0; i<B->rmap.n/bs; i++) { 1620 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 1621 } 1622 } 1623 if (o_nnz) { 1624 for (i=0; i<B->rmap.n/bs; i++) { 1625 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 1626 } 1627 } 1628 B->preallocated = PETSC_TRUE; 1629 1630 b = (Mat_MPISBAIJ*)B->data; 1631 mbs = B->rmap.n/bs; 1632 Mbs = B->rmap.N/bs; 1633 if (mbs*bs != B->rmap.n) { 1634 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap.N,bs); 1635 } 1636 1637 B->rmap.bs = bs; 1638 b->bs2 = bs*bs; 1639 b->mbs = mbs; 1640 b->nbs = mbs; 1641 b->Mbs = Mbs; 1642 b->Nbs = Mbs; 1643 1644 for (i=0; i<=b->size; i++) { 1645 b->rangebs[i] = B->rmap.range[i]/bs; 1646 } 1647 b->rstartbs = B->rmap.rstart/bs; 1648 b->rendbs = B->rmap.rend/bs; 1649 1650 b->cstartbs = B->cmap.rstart/bs; 1651 b->cendbs = B->cmap.rend/bs; 1652 1653 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1654 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 1655 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1656 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1657 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1658 1659 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1660 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 1661 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1662 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1663 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1664 1665 /* build cache for off array entries formed */ 1666 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1667 1668 PetscFunctionReturn(0); 1669 } 1670 EXTERN_C_END 1671 1672 /*MC 1673 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1674 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1675 1676 Options Database Keys: 1677 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1678 1679 Level: beginner 1680 1681 .seealso: MatCreateMPISBAIJ 1682 M*/ 1683 1684 EXTERN_C_BEGIN 1685 #undef __FUNCT__ 1686 #define __FUNCT__ "MatCreate_MPISBAIJ" 1687 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPISBAIJ(Mat B) 1688 { 1689 Mat_MPISBAIJ *b; 1690 PetscErrorCode ierr; 1691 PetscTruth flg; 1692 1693 PetscFunctionBegin; 1694 1695 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1696 B->data = (void*)b; 1697 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1698 1699 B->ops->destroy = MatDestroy_MPISBAIJ; 1700 B->ops->view = MatView_MPISBAIJ; 1701 B->mapping = 0; 1702 B->factor = 0; 1703 B->assembled = PETSC_FALSE; 1704 1705 B->insertmode = NOT_SET_VALUES; 1706 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1707 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1708 1709 /* build local table of row and column ownerships */ 1710 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1711 1712 /* build cache for off array entries formed */ 1713 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1714 b->donotstash = PETSC_FALSE; 1715 b->colmap = PETSC_NULL; 1716 b->garray = PETSC_NULL; 1717 b->roworiented = PETSC_TRUE; 1718 1719 #if defined(PETSC_USE_MAT_SINGLE) 1720 /* stuff for MatSetValues_XXX in single precision */ 1721 b->setvalueslen = 0; 1722 b->setvaluescopy = PETSC_NULL; 1723 #endif 1724 1725 /* stuff used in block assembly */ 1726 b->barray = 0; 1727 1728 /* stuff used for matrix vector multiply */ 1729 b->lvec = 0; 1730 b->Mvctx = 0; 1731 b->slvec0 = 0; 1732 b->slvec0b = 0; 1733 b->slvec1 = 0; 1734 b->slvec1a = 0; 1735 b->slvec1b = 0; 1736 b->sMvctx = 0; 1737 1738 /* stuff for MatGetRow() */ 1739 b->rowindices = 0; 1740 b->rowvalues = 0; 1741 b->getrowactive = PETSC_FALSE; 1742 1743 /* hash table stuff */ 1744 b->ht = 0; 1745 b->hd = 0; 1746 b->ht_size = 0; 1747 b->ht_flag = PETSC_FALSE; 1748 b->ht_fact = 0; 1749 b->ht_total_ct = 0; 1750 b->ht_insert_ct = 0; 1751 1752 b->in_loc = 0; 1753 b->v_loc = 0; 1754 b->n_loc = 0; 1755 ierr = PetscOptionsBegin(B->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix","Mat");CHKERRQ(ierr); 1756 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1757 if (flg) { 1758 PetscReal fact = 1.39; 1759 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1760 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1761 if (fact <= 1.0) fact = 1.39; 1762 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1763 ierr = PetscInfo1(0,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1764 } 1765 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1766 1767 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1768 "MatStoreValues_MPISBAIJ", 1769 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1770 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1771 "MatRetrieveValues_MPISBAIJ", 1772 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1773 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1774 "MatGetDiagonalBlock_MPISBAIJ", 1775 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1776 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1777 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1778 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1779 B->symmetric = PETSC_TRUE; 1780 B->structurally_symmetric = PETSC_TRUE; 1781 B->symmetric_set = PETSC_TRUE; 1782 B->structurally_symmetric_set = PETSC_TRUE; 1783 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1784 PetscFunctionReturn(0); 1785 } 1786 EXTERN_C_END 1787 1788 /*MC 1789 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1790 1791 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1792 and MATMPISBAIJ otherwise. 1793 1794 Options Database Keys: 1795 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1796 1797 Level: beginner 1798 1799 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1800 M*/ 1801 1802 EXTERN_C_BEGIN 1803 #undef __FUNCT__ 1804 #define __FUNCT__ "MatCreate_SBAIJ" 1805 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SBAIJ(Mat A) 1806 { 1807 PetscErrorCode ierr; 1808 PetscMPIInt size; 1809 1810 PetscFunctionBegin; 1811 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1812 if (size == 1) { 1813 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1814 } else { 1815 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1816 } 1817 PetscFunctionReturn(0); 1818 } 1819 EXTERN_C_END 1820 1821 #undef __FUNCT__ 1822 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1823 /*@C 1824 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1825 the user should preallocate the matrix storage by setting the parameters 1826 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1827 performance can be increased by more than a factor of 50. 1828 1829 Collective on Mat 1830 1831 Input Parameters: 1832 + A - the matrix 1833 . bs - size of blockk 1834 . d_nz - number of block nonzeros per block row in diagonal portion of local 1835 submatrix (same for all local rows) 1836 . d_nnz - array containing the number of block nonzeros in the various block rows 1837 in the upper triangular and diagonal part of the in diagonal portion of the local 1838 (possibly different for each block row) or PETSC_NULL. You must leave room 1839 for the diagonal entry even if it is zero. 1840 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1841 submatrix (same for all local rows). 1842 - o_nnz - array containing the number of nonzeros in the various block rows of the 1843 off-diagonal portion of the local submatrix (possibly different for 1844 each block row) or PETSC_NULL. 1845 1846 1847 Options Database Keys: 1848 . -mat_no_unroll - uses code that does not unroll the loops in the 1849 block calculations (much slower) 1850 . -mat_block_size - size of the blocks to use 1851 1852 Notes: 1853 1854 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1855 than it must be used on all processors that share the object for that argument. 1856 1857 If the *_nnz parameter is given then the *_nz parameter is ignored 1858 1859 Storage Information: 1860 For a square global matrix we define each processor's diagonal portion 1861 to be its local rows and the corresponding columns (a square submatrix); 1862 each processor's off-diagonal portion encompasses the remainder of the 1863 local matrix (a rectangular submatrix). 1864 1865 The user can specify preallocated storage for the diagonal part of 1866 the local submatrix with either d_nz or d_nnz (not both). Set 1867 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1868 memory allocation. Likewise, specify preallocated storage for the 1869 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1870 1871 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1872 the figure below we depict these three local rows and all columns (0-11). 1873 1874 .vb 1875 0 1 2 3 4 5 6 7 8 9 10 11 1876 ------------------- 1877 row 3 | o o o d d d o o o o o o 1878 row 4 | o o o d d d o o o o o o 1879 row 5 | o o o d d d o o o o o o 1880 ------------------- 1881 .ve 1882 1883 Thus, any entries in the d locations are stored in the d (diagonal) 1884 submatrix, and any entries in the o locations are stored in the 1885 o (off-diagonal) submatrix. Note that the d matrix is stored in 1886 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1887 1888 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1889 plus the diagonal part of the d matrix, 1890 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1891 In general, for PDE problems in which most nonzeros are near the diagonal, 1892 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1893 or you will get TERRIBLE performance; see the users' manual chapter on 1894 matrices. 1895 1896 Level: intermediate 1897 1898 .keywords: matrix, block, aij, compressed row, sparse, parallel 1899 1900 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1901 @*/ 1902 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1903 { 1904 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1905 1906 PetscFunctionBegin; 1907 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1908 if (f) { 1909 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1910 } 1911 PetscFunctionReturn(0); 1912 } 1913 1914 #undef __FUNCT__ 1915 #define __FUNCT__ "MatCreateMPISBAIJ" 1916 /*@C 1917 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1918 (block compressed row). For good matrix assembly performance 1919 the user should preallocate the matrix storage by setting the parameters 1920 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1921 performance can be increased by more than a factor of 50. 1922 1923 Collective on MPI_Comm 1924 1925 Input Parameters: 1926 + comm - MPI communicator 1927 . bs - size of blockk 1928 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1929 This value should be the same as the local size used in creating the 1930 y vector for the matrix-vector product y = Ax. 1931 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1932 This value should be the same as the local size used in creating the 1933 x vector for the matrix-vector product y = Ax. 1934 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1935 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1936 . d_nz - number of block nonzeros per block row in diagonal portion of local 1937 submatrix (same for all local rows) 1938 . d_nnz - array containing the number of block nonzeros in the various block rows 1939 in the upper triangular portion of the in diagonal portion of the local 1940 (possibly different for each block block row) or PETSC_NULL. 1941 You must leave room for the diagonal entry even if it is zero. 1942 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1943 submatrix (same for all local rows). 1944 - o_nnz - array containing the number of nonzeros in the various block rows of the 1945 off-diagonal portion of the local submatrix (possibly different for 1946 each block row) or PETSC_NULL. 1947 1948 Output Parameter: 1949 . A - the matrix 1950 1951 Options Database Keys: 1952 . -mat_no_unroll - uses code that does not unroll the loops in the 1953 block calculations (much slower) 1954 . -mat_block_size - size of the blocks to use 1955 . -mat_mpi - use the parallel matrix data structures even on one processor 1956 (defaults to using SeqBAIJ format on one processor) 1957 1958 Notes: 1959 The number of rows and columns must be divisible by blocksize. 1960 1961 The user MUST specify either the local or global matrix dimensions 1962 (possibly both). 1963 1964 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1965 than it must be used on all processors that share the object for that argument. 1966 1967 If the *_nnz parameter is given then the *_nz parameter is ignored 1968 1969 Storage Information: 1970 For a square global matrix we define each processor's diagonal portion 1971 to be its local rows and the corresponding columns (a square submatrix); 1972 each processor's off-diagonal portion encompasses the remainder of the 1973 local matrix (a rectangular submatrix). 1974 1975 The user can specify preallocated storage for the diagonal part of 1976 the local submatrix with either d_nz or d_nnz (not both). Set 1977 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1978 memory allocation. Likewise, specify preallocated storage for the 1979 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1980 1981 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1982 the figure below we depict these three local rows and all columns (0-11). 1983 1984 .vb 1985 0 1 2 3 4 5 6 7 8 9 10 11 1986 ------------------- 1987 row 3 | o o o d d d o o o o o o 1988 row 4 | o o o d d d o o o o o o 1989 row 5 | o o o d d d o o o o o o 1990 ------------------- 1991 .ve 1992 1993 Thus, any entries in the d locations are stored in the d (diagonal) 1994 submatrix, and any entries in the o locations are stored in the 1995 o (off-diagonal) submatrix. Note that the d matrix is stored in 1996 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1997 1998 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1999 plus the diagonal part of the d matrix, 2000 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2001 In general, for PDE problems in which most nonzeros are near the diagonal, 2002 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2003 or you will get TERRIBLE performance; see the users' manual chapter on 2004 matrices. 2005 2006 Level: intermediate 2007 2008 .keywords: matrix, block, aij, compressed row, sparse, parallel 2009 2010 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2011 @*/ 2012 2013 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPISBAIJ(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) 2014 { 2015 PetscErrorCode ierr; 2016 PetscMPIInt size; 2017 2018 PetscFunctionBegin; 2019 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2020 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2021 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2022 if (size > 1) { 2023 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2024 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2025 } else { 2026 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2027 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2028 } 2029 PetscFunctionReturn(0); 2030 } 2031 2032 2033 #undef __FUNCT__ 2034 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2035 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2036 { 2037 Mat mat; 2038 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2039 PetscErrorCode ierr; 2040 PetscInt len=0,nt,bs=matin->rmap.bs,mbs=oldmat->mbs; 2041 PetscScalar *array; 2042 2043 PetscFunctionBegin; 2044 *newmat = 0; 2045 ierr = MatCreate(matin->comm,&mat);CHKERRQ(ierr); 2046 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2047 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2048 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2049 ierr = PetscMapCopy(matin->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2050 ierr = PetscMapCopy(matin->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2051 2052 mat->factor = matin->factor; 2053 mat->preallocated = PETSC_TRUE; 2054 mat->assembled = PETSC_TRUE; 2055 mat->insertmode = NOT_SET_VALUES; 2056 2057 a = (Mat_MPISBAIJ*)mat->data; 2058 a->bs2 = oldmat->bs2; 2059 a->mbs = oldmat->mbs; 2060 a->nbs = oldmat->nbs; 2061 a->Mbs = oldmat->Mbs; 2062 a->Nbs = oldmat->Nbs; 2063 2064 2065 a->size = oldmat->size; 2066 a->rank = oldmat->rank; 2067 a->donotstash = oldmat->donotstash; 2068 a->roworiented = oldmat->roworiented; 2069 a->rowindices = 0; 2070 a->rowvalues = 0; 2071 a->getrowactive = PETSC_FALSE; 2072 a->barray = 0; 2073 a->rstartbs = oldmat->rstartbs; 2074 a->rendbs = oldmat->rendbs; 2075 a->cstartbs = oldmat->cstartbs; 2076 a->cendbs = oldmat->cendbs; 2077 2078 /* hash table stuff */ 2079 a->ht = 0; 2080 a->hd = 0; 2081 a->ht_size = 0; 2082 a->ht_flag = oldmat->ht_flag; 2083 a->ht_fact = oldmat->ht_fact; 2084 a->ht_total_ct = 0; 2085 a->ht_insert_ct = 0; 2086 2087 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2088 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2089 ierr = MatStashCreate_Private(matin->comm,matin->rmap.bs,&mat->bstash);CHKERRQ(ierr); 2090 if (oldmat->colmap) { 2091 #if defined (PETSC_USE_CTABLE) 2092 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2093 #else 2094 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2095 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2096 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2097 #endif 2098 } else a->colmap = 0; 2099 2100 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2101 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2102 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2103 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2104 } else a->garray = 0; 2105 2106 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2107 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2108 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2109 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2110 2111 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2112 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2113 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2114 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2115 2116 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2117 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2118 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2119 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2120 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2121 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2122 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2123 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2124 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2125 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2126 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2127 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2128 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2129 2130 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2131 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2132 a->sMvctx = oldmat->sMvctx; 2133 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2134 2135 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2136 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2137 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2138 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2139 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2140 *newmat = mat; 2141 PetscFunctionReturn(0); 2142 } 2143 2144 #include "petscsys.h" 2145 2146 #undef __FUNCT__ 2147 #define __FUNCT__ "MatLoad_MPISBAIJ" 2148 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2149 { 2150 Mat A; 2151 PetscErrorCode ierr; 2152 PetscInt i,nz,j,rstart,rend; 2153 PetscScalar *vals,*buf; 2154 MPI_Comm comm = ((PetscObject)viewer)->comm; 2155 MPI_Status status; 2156 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens; 2157 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2158 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2159 PetscInt bs=1,Mbs,mbs,extra_rows; 2160 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2161 PetscInt dcount,kmax,k,nzcount,tmp; 2162 int fd; 2163 2164 PetscFunctionBegin; 2165 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2166 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2167 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2168 2169 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2170 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2171 if (!rank) { 2172 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2173 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2174 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2175 if (header[3] < 0) { 2176 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2177 } 2178 } 2179 2180 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2181 M = header[1]; N = header[2]; 2182 2183 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2184 2185 /* 2186 This code adds extra rows to make sure the number of rows is 2187 divisible by the blocksize 2188 */ 2189 Mbs = M/bs; 2190 extra_rows = bs - M + bs*(Mbs); 2191 if (extra_rows == bs) extra_rows = 0; 2192 else Mbs++; 2193 if (extra_rows &&!rank) { 2194 ierr = PetscInfo(0,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2195 } 2196 2197 /* determine ownership of all rows */ 2198 mbs = Mbs/size + ((Mbs % size) > rank); 2199 m = mbs*bs; 2200 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2201 browners = rowners + size + 1; 2202 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2203 rowners[0] = 0; 2204 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2205 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2206 rstart = rowners[rank]; 2207 rend = rowners[rank+1]; 2208 2209 /* distribute row lengths to all processors */ 2210 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);CHKERRQ(ierr); 2211 if (!rank) { 2212 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2213 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2214 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2215 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2216 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2217 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2218 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2219 } else { 2220 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2221 } 2222 2223 if (!rank) { /* procs[0] */ 2224 /* calculate the number of nonzeros on each processor */ 2225 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2226 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2227 for (i=0; i<size; i++) { 2228 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2229 procsnz[i] += rowlengths[j]; 2230 } 2231 } 2232 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2233 2234 /* determine max buffer needed and allocate it */ 2235 maxnz = 0; 2236 for (i=0; i<size; i++) { 2237 maxnz = PetscMax(maxnz,procsnz[i]); 2238 } 2239 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2240 2241 /* read in my part of the matrix column indices */ 2242 nz = procsnz[0]; 2243 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2244 mycols = ibuf; 2245 if (size == 1) nz -= extra_rows; 2246 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2247 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2248 2249 /* read in every ones (except the last) and ship off */ 2250 for (i=1; i<size-1; i++) { 2251 nz = procsnz[i]; 2252 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2253 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2254 } 2255 /* read in the stuff for the last proc */ 2256 if (size != 1) { 2257 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2258 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2259 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2260 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2261 } 2262 ierr = PetscFree(cols);CHKERRQ(ierr); 2263 } else { /* procs[i], i>0 */ 2264 /* determine buffer space needed for message */ 2265 nz = 0; 2266 for (i=0; i<m; i++) { 2267 nz += locrowlens[i]; 2268 } 2269 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2270 mycols = ibuf; 2271 /* receive message of column indices*/ 2272 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2273 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2274 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2275 } 2276 2277 /* loop over local rows, determining number of off diagonal entries */ 2278 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2279 odlens = dlens + (rend-rstart); 2280 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2281 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2282 masked1 = mask + Mbs; 2283 masked2 = masked1 + Mbs; 2284 rowcount = 0; nzcount = 0; 2285 for (i=0; i<mbs; i++) { 2286 dcount = 0; 2287 odcount = 0; 2288 for (j=0; j<bs; j++) { 2289 kmax = locrowlens[rowcount]; 2290 for (k=0; k<kmax; k++) { 2291 tmp = mycols[nzcount++]/bs; /* block col. index */ 2292 if (!mask[tmp]) { 2293 mask[tmp] = 1; 2294 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2295 else masked1[dcount++] = tmp; /* entry in diag portion */ 2296 } 2297 } 2298 rowcount++; 2299 } 2300 2301 dlens[i] = dcount; /* d_nzz[i] */ 2302 odlens[i] = odcount; /* o_nzz[i] */ 2303 2304 /* zero out the mask elements we set */ 2305 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2306 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2307 } 2308 2309 /* create our matrix */ 2310 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2311 ierr = MatSetSizes(A,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2312 ierr = MatSetType(A,type);CHKERRQ(ierr); 2313 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2314 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2315 2316 if (!rank) { 2317 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2318 /* read in my part of the matrix numerical values */ 2319 nz = procsnz[0]; 2320 vals = buf; 2321 mycols = ibuf; 2322 if (size == 1) nz -= extra_rows; 2323 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2324 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2325 2326 /* insert into matrix */ 2327 jj = rstart*bs; 2328 for (i=0; i<m; i++) { 2329 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2330 mycols += locrowlens[i]; 2331 vals += locrowlens[i]; 2332 jj++; 2333 } 2334 2335 /* read in other processors (except the last one) and ship out */ 2336 for (i=1; i<size-1; i++) { 2337 nz = procsnz[i]; 2338 vals = buf; 2339 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2340 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2341 } 2342 /* the last proc */ 2343 if (size != 1){ 2344 nz = procsnz[i] - extra_rows; 2345 vals = buf; 2346 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2347 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2348 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2349 } 2350 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2351 2352 } else { 2353 /* receive numeric values */ 2354 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2355 2356 /* receive message of values*/ 2357 vals = buf; 2358 mycols = ibuf; 2359 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2360 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2361 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2362 2363 /* insert into matrix */ 2364 jj = rstart*bs; 2365 for (i=0; i<m; i++) { 2366 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2367 mycols += locrowlens[i]; 2368 vals += locrowlens[i]; 2369 jj++; 2370 } 2371 } 2372 2373 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2374 ierr = PetscFree(buf);CHKERRQ(ierr); 2375 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2376 ierr = PetscFree(rowners);CHKERRQ(ierr); 2377 ierr = PetscFree(dlens);CHKERRQ(ierr); 2378 ierr = PetscFree(mask);CHKERRQ(ierr); 2379 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2380 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2381 *newmat = A; 2382 PetscFunctionReturn(0); 2383 } 2384 2385 #undef __FUNCT__ 2386 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2387 /*XXXXX@ 2388 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2389 2390 Input Parameters: 2391 . mat - the matrix 2392 . fact - factor 2393 2394 Collective on Mat 2395 2396 Level: advanced 2397 2398 Notes: 2399 This can also be set by the command line option: -mat_use_hash_table fact 2400 2401 .keywords: matrix, hashtable, factor, HT 2402 2403 .seealso: MatSetOption() 2404 @XXXXX*/ 2405 2406 2407 #undef __FUNCT__ 2408 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2409 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2410 { 2411 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2412 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2413 PetscReal atmp; 2414 PetscReal *work,*svalues,*rvalues; 2415 PetscErrorCode ierr; 2416 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2417 PetscMPIInt rank,size; 2418 PetscInt *rowners_bs,dest,count,source; 2419 PetscScalar *va; 2420 MatScalar *ba; 2421 MPI_Status stat; 2422 2423 PetscFunctionBegin; 2424 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2425 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2426 2427 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2428 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2429 2430 bs = A->rmap.bs; 2431 mbs = a->mbs; 2432 Mbs = a->Mbs; 2433 ba = b->a; 2434 bi = b->i; 2435 bj = b->j; 2436 2437 /* find ownerships */ 2438 rowners_bs = A->rmap.range; 2439 2440 /* each proc creates an array to be distributed */ 2441 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2442 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2443 2444 /* row_max for B */ 2445 if (rank != size-1){ 2446 for (i=0; i<mbs; i++) { 2447 ncols = bi[1] - bi[0]; bi++; 2448 brow = bs*i; 2449 for (j=0; j<ncols; j++){ 2450 bcol = bs*(*bj); 2451 for (kcol=0; kcol<bs; kcol++){ 2452 col = bcol + kcol; /* local col index */ 2453 col += rowners_bs[rank+1]; /* global col index */ 2454 for (krow=0; krow<bs; krow++){ 2455 atmp = PetscAbsScalar(*ba); ba++; 2456 row = brow + krow; /* local row index */ 2457 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2458 if (work[col] < atmp) work[col] = atmp; 2459 } 2460 } 2461 bj++; 2462 } 2463 } 2464 2465 /* send values to its owners */ 2466 for (dest=rank+1; dest<size; dest++){ 2467 svalues = work + rowners_bs[dest]; 2468 count = rowners_bs[dest+1]-rowners_bs[dest]; 2469 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2470 } 2471 } 2472 2473 /* receive values */ 2474 if (rank){ 2475 rvalues = work; 2476 count = rowners_bs[rank+1]-rowners_bs[rank]; 2477 for (source=0; source<rank; source++){ 2478 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2479 /* process values */ 2480 for (i=0; i<count; i++){ 2481 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2482 } 2483 } 2484 } 2485 2486 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2487 ierr = PetscFree(work);CHKERRQ(ierr); 2488 PetscFunctionReturn(0); 2489 } 2490 2491 #undef __FUNCT__ 2492 #define __FUNCT__ "MatRelax_MPISBAIJ" 2493 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2494 { 2495 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2496 PetscErrorCode ierr; 2497 PetscInt mbs=mat->mbs,bs=matin->rmap.bs; 2498 PetscScalar *x,*b,*ptr,zero=0.0; 2499 Vec bb1; 2500 2501 PetscFunctionBegin; 2502 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2503 if (bs > 1) 2504 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2505 2506 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2507 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2508 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2509 its--; 2510 } 2511 2512 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2513 while (its--){ 2514 2515 /* lower triangular part: slvec0b = - B^T*xx */ 2516 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2517 2518 /* copy xx into slvec0a */ 2519 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2520 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2521 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2522 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2523 2524 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2525 2526 /* copy bb into slvec1a */ 2527 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2528 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2529 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2530 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2531 2532 /* set slvec1b = 0 */ 2533 ierr = VecSet(mat->slvec1b,zero);CHKERRQ(ierr); 2534 2535 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2536 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2537 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2538 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2539 2540 /* upper triangular part: bb1 = bb1 - B*x */ 2541 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2542 2543 /* local diagonal sweep */ 2544 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2545 } 2546 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2547 } else { 2548 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2549 } 2550 PetscFunctionReturn(0); 2551 } 2552 2553 #undef __FUNCT__ 2554 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2555 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2556 { 2557 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2558 PetscErrorCode ierr; 2559 Vec lvec1,bb1; 2560 2561 PetscFunctionBegin; 2562 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2563 if (matin->rmap.bs > 1) 2564 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2565 2566 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2567 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2568 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2569 its--; 2570 } 2571 2572 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2573 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2574 while (its--){ 2575 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2576 2577 /* lower diagonal part: bb1 = bb - B^T*xx */ 2578 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2579 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2580 2581 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2582 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2583 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2584 2585 /* upper diagonal part: bb1 = bb1 - B*x */ 2586 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2587 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2588 2589 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2590 2591 /* diagonal sweep */ 2592 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2593 } 2594 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2595 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2596 } else { 2597 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2598 } 2599 PetscFunctionReturn(0); 2600 } 2601 2602