1 2 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 3 #include "mpisbaij.h" 4 #include "src/mat/impls/sbaij/seq/sbaij.h" 5 6 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 8 EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat); 9 EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 10 EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 11 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 13 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 14 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 16 EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 EXTERN PetscErrorCode MatPrintHelp_SeqSBAIJ(Mat); 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 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 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 else if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 102 if (nrow >= rmax) { \ 103 /* there is no extra room in row, therefore enlarge */ \ 104 PetscInt new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 105 MatScalar *new_a; \ 106 \ 107 if (a->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 108 \ 109 /* malloc new storage space */ \ 110 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(PetscInt); \ 111 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 112 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 113 new_i = new_j + new_nz; \ 114 \ 115 /* copy over old data into new slots */ \ 116 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 117 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 118 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 119 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 120 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 121 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 122 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 123 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 124 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 125 /* free up old matrix storage */ \ 126 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 127 if (!a->singlemalloc) { \ 128 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 129 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 130 } \ 131 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 132 a->singlemalloc = PETSC_TRUE; \ 133 \ 134 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 135 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 136 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 137 a->maxnz += bs2*CHUNKSIZE; \ 138 a->reallocs++; \ 139 a->nz++; \ 140 } \ 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 a_noinsert:; \ 151 ailen[brow] = nrow; \ 152 } 153 #ifndef MatSetValues_SeqBAIJ_B_Private 154 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 155 { \ 156 brow = row/bs; \ 157 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 158 rmax = bimax[brow]; nrow = bilen[brow]; \ 159 bcol = col/bs; \ 160 ridx = row % bs; cidx = col % bs; \ 161 low = 0; high = nrow; \ 162 while (high-low > 3) { \ 163 t = (low+high)/2; \ 164 if (rp[t] > bcol) high = t; \ 165 else low = t; \ 166 } \ 167 for (_i=low; _i<high; _i++) { \ 168 if (rp[_i] > bcol) break; \ 169 if (rp[_i] == bcol) { \ 170 bap = ap + bs2*_i + bs*cidx + ridx; \ 171 if (addv == ADD_VALUES) *bap += value; \ 172 else *bap = value; \ 173 goto b_noinsert; \ 174 } \ 175 } \ 176 if (b->nonew == 1) goto b_noinsert; \ 177 else if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 178 if (nrow >= rmax) { \ 179 /* there is no extra room in row, therefore enlarge */ \ 180 PetscInt new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 181 MatScalar *new_a; \ 182 \ 183 if (b->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); \ 184 \ 185 /* malloc new storage space */ \ 186 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(PetscInt); \ 187 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 188 new_j = (PetscInt*)(new_a + bs2*new_nz); \ 189 new_i = new_j + new_nz; \ 190 \ 191 /* copy over old data into new slots */ \ 192 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 193 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 194 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); \ 195 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 196 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); \ 197 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 198 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 199 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 200 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 201 /* free up old matrix storage */ \ 202 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 203 if (!b->singlemalloc) { \ 204 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 205 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 206 } \ 207 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 208 b->singlemalloc = PETSC_TRUE; \ 209 \ 210 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 211 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 212 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); \ 213 b->maxnz += bs2*CHUNKSIZE; \ 214 b->reallocs++; \ 215 b->nz++; \ 216 } \ 217 N = nrow++ - 1; \ 218 /* shift up all the later entries in this row */ \ 219 for (ii=N; ii>=_i; ii--) { \ 220 rp[ii+1] = rp[ii]; \ 221 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 222 } \ 223 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 224 rp[_i] = bcol; \ 225 ap[bs2*_i + bs*cidx + ridx] = value; \ 226 b_noinsert:; \ 227 bilen[brow] = nrow; \ 228 } 229 #endif 230 231 #if defined(PETSC_USE_MAT_SINGLE) 232 #undef __FUNCT__ 233 #define __FUNCT__ "MatSetValues_MPISBAIJ" 234 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 235 { 236 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 237 PetscErrorCode ierr; 238 PetscInt i,N = m*n; 239 MatScalar *vsingle; 240 241 PetscFunctionBegin; 242 if (N > b->setvalueslen) { 243 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 244 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 245 b->setvalueslen = N; 246 } 247 vsingle = b->setvaluescopy; 248 249 for (i=0; i<N; i++) { 250 vsingle[i] = v[i]; 251 } 252 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 258 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 259 { 260 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 261 PetscErrorCode ierr; 262 PetscInt i,N = m*n*b->bs2; 263 MatScalar *vsingle; 264 265 PetscFunctionBegin; 266 if (N > b->setvalueslen) { 267 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 268 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 269 b->setvalueslen = N; 270 } 271 vsingle = b->setvaluescopy; 272 for (i=0; i<N; i++) { 273 vsingle[i] = v[i]; 274 } 275 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 276 PetscFunctionReturn(0); 277 } 278 #endif 279 280 /* Only add/insert a(i,j) with i<=j (blocks). 281 Any a(i,j) with i>j input by user is ingored. 282 */ 283 #undef __FUNCT__ 284 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 285 PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 286 { 287 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 288 MatScalar value; 289 PetscTruth roworiented = baij->roworiented; 290 PetscErrorCode ierr; 291 PetscInt i,j,row,col; 292 PetscInt rstart_orig=baij->rstart_bs; 293 PetscInt rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 294 PetscInt cend_orig=baij->cend_bs,bs=mat->bs; 295 296 /* Some Variables required in the macro */ 297 Mat A = baij->A; 298 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 299 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 300 MatScalar *aa=a->a; 301 302 Mat B = baij->B; 303 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 304 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 305 MatScalar *ba=b->a; 306 307 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 308 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 309 MatScalar *ap,*bap; 310 311 /* for stash */ 312 PetscInt n_loc, *in_loc=0; 313 MatScalar *v_loc=0; 314 315 PetscFunctionBegin; 316 317 if(!baij->donotstash){ 318 ierr = PetscMalloc(n*sizeof(PetscInt),&in_loc);CHKERRQ(ierr); 319 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 320 } 321 322 for (i=0; i<m; i++) { 323 if (im[i] < 0) continue; 324 #if defined(PETSC_USE_DEBUG) 325 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->M-1); 326 #endif 327 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 328 row = im[i] - rstart_orig; /* local row index */ 329 for (j=0; j<n; j++) { 330 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 331 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 332 col = in[j] - cstart_orig; /* local col index */ 333 brow = row/bs; bcol = col/bs; 334 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 335 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 336 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 337 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 338 } else if (in[j] < 0) continue; 339 #if defined(PETSC_USE_DEBUG) 340 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->N-1);} 341 #endif 342 else { /* off-diag entry (B) */ 343 if (mat->was_assembled) { 344 if (!baij->colmap) { 345 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 346 } 347 #if defined (PETSC_USE_CTABLE) 348 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 349 col = col - 1; 350 #else 351 col = baij->colmap[in[j]/bs] - 1; 352 #endif 353 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 354 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 355 col = in[j]; 356 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 357 B = baij->B; 358 b = (Mat_SeqBAIJ*)(B)->data; 359 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 360 ba=b->a; 361 } else col += in[j]%bs; 362 } else col = in[j]; 363 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 364 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 365 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 366 } 367 } 368 } else { /* off processor entry */ 369 if (!baij->donotstash) { 370 n_loc = 0; 371 for (j=0; j<n; j++){ 372 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 373 in_loc[n_loc] = in[j]; 374 if (roworiented) { 375 v_loc[n_loc] = v[i*n+j]; 376 } else { 377 v_loc[n_loc] = v[j*m+i]; 378 } 379 n_loc++; 380 } 381 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 382 } 383 } 384 } 385 386 if(!baij->donotstash){ 387 ierr = PetscFree(in_loc);CHKERRQ(ierr); 388 ierr = PetscFree(v_loc);CHKERRQ(ierr); 389 } 390 PetscFunctionReturn(0); 391 } 392 393 #undef __FUNCT__ 394 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 395 PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 396 { 397 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 398 const MatScalar *value; 399 MatScalar *barray=baij->barray; 400 PetscTruth roworiented = baij->roworiented; 401 PetscErrorCode ierr; 402 PetscInt i,j,ii,jj,row,col,rstart=baij->rstart; 403 PetscInt rend=baij->rend,cstart=baij->cstart,stepval; 404 PetscInt cend=baij->cend,bs=mat->bs,bs2=baij->bs2; 405 406 PetscFunctionBegin; 407 if(!barray) { 408 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 409 baij->barray = barray; 410 } 411 412 if (roworiented) { 413 stepval = (n-1)*bs; 414 } else { 415 stepval = (m-1)*bs; 416 } 417 for (i=0; i<m; i++) { 418 if (im[i] < 0) continue; 419 #if defined(PETSC_USE_DEBUG) 420 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 421 #endif 422 if (im[i] >= rstart && im[i] < rend) { 423 row = im[i] - rstart; 424 for (j=0; j<n; j++) { 425 /* If NumCol = 1 then a copy is not required */ 426 if ((roworiented) && (n == 1)) { 427 barray = (MatScalar*) v + i*bs2; 428 } else if((!roworiented) && (m == 1)) { 429 barray = (MatScalar*) v + j*bs2; 430 } else { /* Here a copy is required */ 431 if (roworiented) { 432 value = v + i*(stepval+bs)*bs + j*bs; 433 } else { 434 value = v + j*(stepval+bs)*bs + i*bs; 435 } 436 for (ii=0; ii<bs; ii++,value+=stepval) { 437 for (jj=0; jj<bs; jj++) { 438 *barray++ = *value++; 439 } 440 } 441 barray -=bs2; 442 } 443 444 if (in[j] >= cstart && in[j] < cend){ 445 col = in[j] - cstart; 446 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 447 } 448 else if (in[j] < 0) continue; 449 #if defined(PETSC_USE_DEBUG) 450 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 451 #endif 452 else { 453 if (mat->was_assembled) { 454 if (!baij->colmap) { 455 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 456 } 457 458 #if defined(PETSC_USE_DEBUG) 459 #if defined (PETSC_USE_CTABLE) 460 { PetscInt data; 461 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 462 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 463 } 464 #else 465 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 466 #endif 467 #endif 468 #if defined (PETSC_USE_CTABLE) 469 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 470 col = (col - 1)/bs; 471 #else 472 col = (baij->colmap[in[j]] - 1)/bs; 473 #endif 474 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 475 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 476 col = in[j]; 477 } 478 } 479 else col = in[j]; 480 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 481 } 482 } 483 } else { 484 if (!baij->donotstash) { 485 if (roworiented) { 486 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 487 } else { 488 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 489 } 490 } 491 } 492 } 493 PetscFunctionReturn(0); 494 } 495 496 #undef __FUNCT__ 497 #define __FUNCT__ "MatGetValues_MPISBAIJ" 498 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 499 { 500 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 501 PetscErrorCode ierr; 502 PetscInt bs=mat->bs,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 503 PetscInt bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 504 505 PetscFunctionBegin; 506 for (i=0; i<m; i++) { 507 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); 508 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->M-1); 509 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 510 row = idxm[i] - bsrstart; 511 for (j=0; j<n; j++) { 512 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); 513 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->N-1); 514 if (idxn[j] >= bscstart && idxn[j] < bscend){ 515 col = idxn[j] - bscstart; 516 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 517 } else { 518 if (!baij->colmap) { 519 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 520 } 521 #if defined (PETSC_USE_CTABLE) 522 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 523 data --; 524 #else 525 data = baij->colmap[idxn[j]/bs]-1; 526 #endif 527 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 528 else { 529 col = data + idxn[j]%bs; 530 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 531 } 532 } 533 } 534 } else { 535 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 536 } 537 } 538 PetscFunctionReturn(0); 539 } 540 541 #undef __FUNCT__ 542 #define __FUNCT__ "MatNorm_MPISBAIJ" 543 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 544 { 545 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 546 PetscErrorCode ierr; 547 PetscReal sum[2],*lnorm2; 548 549 PetscFunctionBegin; 550 if (baij->size == 1) { 551 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 552 } else { 553 if (type == NORM_FROBENIUS) { 554 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 555 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 556 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 557 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 558 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 559 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 560 *norm = sqrt(sum[0] + 2*sum[1]); 561 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 562 } else { 563 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 564 } 565 } 566 PetscFunctionReturn(0); 567 } 568 569 #undef __FUNCT__ 570 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 571 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 572 { 573 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 574 PetscErrorCode ierr; 575 PetscInt nstash,reallocs; 576 InsertMode addv; 577 578 PetscFunctionBegin; 579 if (baij->donotstash) { 580 PetscFunctionReturn(0); 581 } 582 583 /* make sure all processors are either in INSERTMODE or ADDMODE */ 584 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 585 if (addv == (ADD_VALUES|INSERT_VALUES)) { 586 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 587 } 588 mat->insertmode = addv; /* in case this processor had no cache */ 589 590 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 591 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 592 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 593 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %D entries,uses %D mallocs.\n",nstash,reallocs); 594 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 595 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs); 596 PetscFunctionReturn(0); 597 } 598 599 #undef __FUNCT__ 600 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 601 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 602 { 603 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 604 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 605 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 606 PetscErrorCode ierr; 607 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 608 PetscInt *row,*col,other_disassembled; 609 PetscMPIInt n; 610 PetscTruth r1,r2,r3; 611 MatScalar *val; 612 InsertMode addv = mat->insertmode; 613 614 PetscFunctionBegin; 615 616 if (!baij->donotstash) { 617 while (1) { 618 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 619 if (!flg) break; 620 621 for (i=0; i<n;) { 622 /* Now identify the consecutive vals belonging to the same row */ 623 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 624 if (j < n) ncols = j-i; 625 else ncols = n-i; 626 /* Now assemble all these values with a single function call */ 627 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 628 i = j; 629 } 630 } 631 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 632 /* Now process the block-stash. Since the values are stashed column-oriented, 633 set the roworiented flag to column oriented, and after MatSetValues() 634 restore the original flags */ 635 r1 = baij->roworiented; 636 r2 = a->roworiented; 637 r3 = b->roworiented; 638 baij->roworiented = PETSC_FALSE; 639 a->roworiented = PETSC_FALSE; 640 b->roworiented = PETSC_FALSE; 641 while (1) { 642 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 643 if (!flg) break; 644 645 for (i=0; i<n;) { 646 /* Now identify the consecutive vals belonging to the same row */ 647 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 648 if (j < n) ncols = j-i; 649 else ncols = n-i; 650 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 651 i = j; 652 } 653 } 654 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 655 baij->roworiented = r1; 656 a->roworiented = r2; 657 b->roworiented = r3; 658 } 659 660 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 661 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 662 663 /* determine if any processor has disassembled, if so we must 664 also disassemble ourselfs, in order that we may reassemble. */ 665 /* 666 if nonzero structure of submatrix B cannot change then we know that 667 no processor disassembled thus we can skip this stuff 668 */ 669 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 670 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 671 if (mat->was_assembled && !other_disassembled) { 672 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 673 } 674 } 675 676 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 677 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 678 } 679 /* b->compressedrow.use = PETSC_TRUE; -- cannot be used on baij->B without customization, 680 because MatMult_MPISBAIJ uses very different algorithm than MatMult_MPIBAIJ() */ 681 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 682 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 683 684 if (baij->rowvalues) { 685 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 686 baij->rowvalues = 0; 687 } 688 689 PetscFunctionReturn(0); 690 } 691 692 #undef __FUNCT__ 693 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 694 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 695 { 696 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 697 PetscErrorCode ierr; 698 PetscInt bs = mat->bs; 699 PetscMPIInt size = baij->size,rank = baij->rank; 700 PetscTruth iascii,isdraw; 701 PetscViewer sviewer; 702 PetscViewerFormat format; 703 704 PetscFunctionBegin; 705 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 706 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 707 if (iascii) { 708 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 709 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 710 MatInfo info; 711 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 712 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 713 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 714 rank,mat->m,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 715 mat->bs,(PetscInt)info.memory);CHKERRQ(ierr); 716 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 717 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 718 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 719 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 720 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 721 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 722 PetscFunctionReturn(0); 723 } else if (format == PETSC_VIEWER_ASCII_INFO) { 724 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 725 PetscFunctionReturn(0); 726 } 727 } 728 729 if (isdraw) { 730 PetscDraw draw; 731 PetscTruth isnull; 732 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 733 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 734 } 735 736 if (size == 1) { 737 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 738 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 739 } else { 740 /* assemble the entire matrix onto first processor. */ 741 Mat A; 742 Mat_SeqSBAIJ *Aloc; 743 Mat_SeqBAIJ *Bloc; 744 PetscInt M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 745 MatScalar *a; 746 747 /* Should this be the same type as mat? */ 748 if (!rank) { 749 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 750 } else { 751 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 752 } 753 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 754 ierr = MatMPISBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 755 PetscLogObjectParent(mat,A); 756 757 /* copy over the A part */ 758 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 759 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 760 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 761 762 for (i=0; i<mbs; i++) { 763 rvals[0] = bs*(baij->rstart + i); 764 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 765 for (j=ai[i]; j<ai[i+1]; j++) { 766 col = (baij->cstart+aj[j])*bs; 767 for (k=0; k<bs; k++) { 768 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 769 col++; a += bs; 770 } 771 } 772 } 773 /* copy over the B part */ 774 Bloc = (Mat_SeqBAIJ*)baij->B->data; 775 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 776 for (i=0; i<mbs; i++) { 777 rvals[0] = bs*(baij->rstart + i); 778 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 779 for (j=ai[i]; j<ai[i+1]; j++) { 780 col = baij->garray[aj[j]]*bs; 781 for (k=0; k<bs; k++) { 782 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 783 col++; a += bs; 784 } 785 } 786 } 787 ierr = PetscFree(rvals);CHKERRQ(ierr); 788 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 789 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 790 /* 791 Everyone has to call to draw the matrix since the graphics waits are 792 synchronized across all processors that share the PetscDraw object 793 */ 794 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 795 if (!rank) { 796 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 797 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 798 } 799 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 800 ierr = MatDestroy(A);CHKERRQ(ierr); 801 } 802 PetscFunctionReturn(0); 803 } 804 805 #undef __FUNCT__ 806 #define __FUNCT__ "MatView_MPISBAIJ" 807 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 808 { 809 PetscErrorCode ierr; 810 PetscTruth iascii,isdraw,issocket,isbinary; 811 812 PetscFunctionBegin; 813 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 814 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 815 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 816 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 817 if (iascii || isdraw || issocket || isbinary) { 818 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 819 } else { 820 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 821 } 822 PetscFunctionReturn(0); 823 } 824 825 #undef __FUNCT__ 826 #define __FUNCT__ "MatDestroy_MPISBAIJ" 827 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 828 { 829 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 830 PetscErrorCode ierr; 831 832 PetscFunctionBegin; 833 #if defined(PETSC_USE_LOG) 834 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 835 #endif 836 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 837 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 838 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 839 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 840 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 841 #if defined (PETSC_USE_CTABLE) 842 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 843 #else 844 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 845 #endif 846 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 847 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 848 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 849 if (baij->slvec0) { 850 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 851 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 852 } 853 if (baij->slvec1) { 854 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 855 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 856 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 857 } 858 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 859 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 860 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 861 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 862 #if defined(PETSC_USE_MAT_SINGLE) 863 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 864 #endif 865 ierr = PetscFree(baij);CHKERRQ(ierr); 866 867 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 868 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 869 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 870 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 871 PetscFunctionReturn(0); 872 } 873 874 #undef __FUNCT__ 875 #define __FUNCT__ "MatMult_MPISBAIJ" 876 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 877 { 878 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 879 PetscErrorCode ierr; 880 PetscInt nt,mbs=a->mbs,bs=A->bs; 881 PetscScalar *x,*from,zero=0.0; 882 883 PetscFunctionBegin; 884 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 885 if (nt != A->n) { 886 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 887 } 888 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 889 if (nt != A->m) { 890 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 891 } 892 893 /* diagonal part */ 894 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 895 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 896 897 /* subdiagonal part */ 898 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 899 900 /* copy x into the vec slvec0 */ 901 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 902 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 903 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 904 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 905 906 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 907 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 908 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 909 910 /* supperdiagonal part */ 911 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 912 913 PetscFunctionReturn(0); 914 } 915 916 #undef __FUNCT__ 917 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 918 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 919 { 920 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 921 PetscErrorCode ierr; 922 PetscInt nt; 923 924 PetscFunctionBegin; 925 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 926 if (nt != A->n) { 927 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 928 } 929 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 930 if (nt != A->m) { 931 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 932 } 933 934 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 935 /* do diagonal part */ 936 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 937 /* do supperdiagonal part */ 938 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 939 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 940 /* do subdiagonal part */ 941 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 942 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 943 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 944 945 PetscFunctionReturn(0); 946 } 947 948 #undef __FUNCT__ 949 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 950 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 951 { 952 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 953 PetscErrorCode ierr; 954 PetscInt mbs=a->mbs,bs=A->bs; 955 PetscScalar *x,*from,zero=0.0; 956 957 PetscFunctionBegin; 958 /* 959 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 960 PetscSynchronizedFlush(A->comm); 961 */ 962 /* diagonal part */ 963 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 964 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 965 966 /* subdiagonal part */ 967 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 968 969 /* copy x into the vec slvec0 */ 970 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 971 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 972 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 973 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 974 975 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 976 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 977 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 978 979 /* supperdiagonal part */ 980 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 981 982 PetscFunctionReturn(0); 983 } 984 985 #undef __FUNCT__ 986 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 987 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 988 { 989 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 990 PetscErrorCode ierr; 991 992 PetscFunctionBegin; 993 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 994 /* do diagonal part */ 995 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 996 /* do supperdiagonal part */ 997 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 998 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 999 1000 /* do subdiagonal part */ 1001 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1002 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1003 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1004 1005 PetscFunctionReturn(0); 1006 } 1007 1008 #undef __FUNCT__ 1009 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1010 PetscErrorCode MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1011 { 1012 PetscErrorCode ierr; 1013 1014 PetscFunctionBegin; 1015 ierr = MatMult(A,xx,yy);CHKERRQ(ierr); 1016 PetscFunctionReturn(0); 1017 } 1018 1019 #undef __FUNCT__ 1020 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1021 PetscErrorCode MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1022 { 1023 PetscErrorCode ierr; 1024 1025 PetscFunctionBegin; 1026 ierr = MatMultAdd(A,xx,yy,zz);CHKERRQ(ierr); 1027 PetscFunctionReturn(0); 1028 } 1029 1030 /* 1031 This only works correctly for square matrices where the subblock A->A is the 1032 diagonal block 1033 */ 1034 #undef __FUNCT__ 1035 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1036 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1037 { 1038 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1039 PetscErrorCode ierr; 1040 1041 PetscFunctionBegin; 1042 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1043 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1044 PetscFunctionReturn(0); 1045 } 1046 1047 #undef __FUNCT__ 1048 #define __FUNCT__ "MatScale_MPISBAIJ" 1049 PetscErrorCode MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1050 { 1051 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1052 PetscErrorCode ierr; 1053 1054 PetscFunctionBegin; 1055 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1056 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 #undef __FUNCT__ 1061 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1062 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1063 { 1064 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1065 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1066 PetscErrorCode ierr; 1067 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1068 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1069 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1070 1071 PetscFunctionBegin; 1072 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1073 mat->getrowactive = PETSC_TRUE; 1074 1075 if (!mat->rowvalues && (idx || v)) { 1076 /* 1077 allocate enough space to hold information from the longest row. 1078 */ 1079 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1080 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1081 PetscInt max = 1,mbs = mat->mbs,tmp; 1082 for (i=0; i<mbs; i++) { 1083 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1084 if (max < tmp) { max = tmp; } 1085 } 1086 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1087 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1088 } 1089 1090 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1091 lrow = row - brstart; /* local row index */ 1092 1093 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1094 if (!v) {pvA = 0; pvB = 0;} 1095 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1096 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1097 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1098 nztot = nzA + nzB; 1099 1100 cmap = mat->garray; 1101 if (v || idx) { 1102 if (nztot) { 1103 /* Sort by increasing column numbers, assuming A and B already sorted */ 1104 PetscInt imark = -1; 1105 if (v) { 1106 *v = v_p = mat->rowvalues; 1107 for (i=0; i<nzB; i++) { 1108 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1109 else break; 1110 } 1111 imark = i; 1112 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1113 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1114 } 1115 if (idx) { 1116 *idx = idx_p = mat->rowindices; 1117 if (imark > -1) { 1118 for (i=0; i<imark; i++) { 1119 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1120 } 1121 } else { 1122 for (i=0; i<nzB; i++) { 1123 if (cmap[cworkB[i]/bs] < cstart) 1124 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1125 else break; 1126 } 1127 imark = i; 1128 } 1129 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1130 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1131 } 1132 } else { 1133 if (idx) *idx = 0; 1134 if (v) *v = 0; 1135 } 1136 } 1137 *nz = nztot; 1138 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1139 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1145 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1146 { 1147 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1148 1149 PetscFunctionBegin; 1150 if (baij->getrowactive == PETSC_FALSE) { 1151 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1152 } 1153 baij->getrowactive = PETSC_FALSE; 1154 PetscFunctionReturn(0); 1155 } 1156 1157 #undef __FUNCT__ 1158 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1159 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1160 { 1161 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1162 PetscErrorCode ierr; 1163 1164 PetscFunctionBegin; 1165 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1166 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1167 PetscFunctionReturn(0); 1168 } 1169 1170 #undef __FUNCT__ 1171 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1172 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1173 { 1174 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1175 Mat A = a->A,B = a->B; 1176 PetscErrorCode ierr; 1177 PetscReal isend[5],irecv[5]; 1178 1179 PetscFunctionBegin; 1180 info->block_size = (PetscReal)matin->bs; 1181 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1182 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1183 isend[3] = info->memory; isend[4] = info->mallocs; 1184 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1185 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1186 isend[3] += info->memory; isend[4] += info->mallocs; 1187 if (flag == MAT_LOCAL) { 1188 info->nz_used = isend[0]; 1189 info->nz_allocated = isend[1]; 1190 info->nz_unneeded = isend[2]; 1191 info->memory = isend[3]; 1192 info->mallocs = isend[4]; 1193 } else if (flag == MAT_GLOBAL_MAX) { 1194 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1195 info->nz_used = irecv[0]; 1196 info->nz_allocated = irecv[1]; 1197 info->nz_unneeded = irecv[2]; 1198 info->memory = irecv[3]; 1199 info->mallocs = irecv[4]; 1200 } else if (flag == MAT_GLOBAL_SUM) { 1201 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1202 info->nz_used = irecv[0]; 1203 info->nz_allocated = irecv[1]; 1204 info->nz_unneeded = irecv[2]; 1205 info->memory = irecv[3]; 1206 info->mallocs = irecv[4]; 1207 } else { 1208 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1209 } 1210 info->rows_global = (PetscReal)A->M; 1211 info->columns_global = (PetscReal)A->N; 1212 info->rows_local = (PetscReal)A->m; 1213 info->columns_local = (PetscReal)A->N; 1214 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1215 info->fill_ratio_needed = 0; 1216 info->factor_mallocs = 0; 1217 PetscFunctionReturn(0); 1218 } 1219 1220 #undef __FUNCT__ 1221 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1222 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op) 1223 { 1224 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1225 PetscErrorCode ierr; 1226 1227 PetscFunctionBegin; 1228 switch (op) { 1229 case MAT_NO_NEW_NONZERO_LOCATIONS: 1230 case MAT_YES_NEW_NONZERO_LOCATIONS: 1231 case MAT_COLUMNS_UNSORTED: 1232 case MAT_COLUMNS_SORTED: 1233 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1234 case MAT_KEEP_ZEROED_ROWS: 1235 case MAT_NEW_NONZERO_LOCATION_ERR: 1236 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1237 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1238 break; 1239 case MAT_ROW_ORIENTED: 1240 a->roworiented = PETSC_TRUE; 1241 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1242 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1243 break; 1244 case MAT_ROWS_SORTED: 1245 case MAT_ROWS_UNSORTED: 1246 case MAT_YES_NEW_DIAGONALS: 1247 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1248 break; 1249 case MAT_COLUMN_ORIENTED: 1250 a->roworiented = PETSC_FALSE; 1251 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1252 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1253 break; 1254 case MAT_IGNORE_OFF_PROC_ENTRIES: 1255 a->donotstash = PETSC_TRUE; 1256 break; 1257 case MAT_NO_NEW_DIAGONALS: 1258 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1259 case MAT_USE_HASH_TABLE: 1260 a->ht_flag = PETSC_TRUE; 1261 break; 1262 case MAT_NOT_SYMMETRIC: 1263 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1264 case MAT_HERMITIAN: 1265 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1266 case MAT_SYMMETRIC: 1267 case MAT_STRUCTURALLY_SYMMETRIC: 1268 case MAT_NOT_HERMITIAN: 1269 case MAT_SYMMETRY_ETERNAL: 1270 case MAT_NOT_SYMMETRY_ETERNAL: 1271 break; 1272 default: 1273 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1274 } 1275 PetscFunctionReturn(0); 1276 } 1277 1278 #undef __FUNCT__ 1279 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1280 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,Mat *B) 1281 { 1282 PetscErrorCode ierr; 1283 PetscFunctionBegin; 1284 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1285 PetscFunctionReturn(0); 1286 } 1287 1288 #undef __FUNCT__ 1289 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1290 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1291 { 1292 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1293 Mat a = baij->A,b = baij->B; 1294 PetscErrorCode ierr; 1295 PetscInt s1,s2,s3; 1296 1297 PetscFunctionBegin; 1298 if (ll != rr) { 1299 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1300 } 1301 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1302 if (rr) { 1303 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1304 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1305 /* Overlap communication with computation. */ 1306 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1307 /*} if (ll) { */ 1308 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1309 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1310 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1311 /* } */ 1312 /* scale the diagonal block */ 1313 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1314 1315 /* if (rr) { */ 1316 /* Do a scatter end and then right scale the off-diagonal block */ 1317 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1318 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1319 } 1320 1321 PetscFunctionReturn(0); 1322 } 1323 1324 #undef __FUNCT__ 1325 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1326 PetscErrorCode MatPrintHelp_MPISBAIJ(Mat A) 1327 { 1328 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1329 MPI_Comm comm = A->comm; 1330 static PetscTruth called = PETSC_FALSE; 1331 PetscErrorCode ierr; 1332 1333 PetscFunctionBegin; 1334 if (!a->rank) { 1335 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1336 } 1337 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1338 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1339 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1340 PetscFunctionReturn(0); 1341 } 1342 1343 #undef __FUNCT__ 1344 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1345 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1346 { 1347 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1348 PetscErrorCode ierr; 1349 1350 PetscFunctionBegin; 1351 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1352 PetscFunctionReturn(0); 1353 } 1354 1355 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1356 1357 #undef __FUNCT__ 1358 #define __FUNCT__ "MatEqual_MPISBAIJ" 1359 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1360 { 1361 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1362 Mat a,b,c,d; 1363 PetscTruth flg; 1364 PetscErrorCode ierr; 1365 1366 PetscFunctionBegin; 1367 a = matA->A; b = matA->B; 1368 c = matB->A; d = matB->B; 1369 1370 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1371 if (flg == PETSC_TRUE) { 1372 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1373 } 1374 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1375 PetscFunctionReturn(0); 1376 } 1377 1378 #undef __FUNCT__ 1379 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1380 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1381 { 1382 PetscErrorCode ierr; 1383 1384 PetscFunctionBegin; 1385 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1386 PetscFunctionReturn(0); 1387 } 1388 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1391 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1392 { 1393 PetscErrorCode ierr; 1394 PetscInt i; 1395 PetscTruth flg; 1396 1397 PetscFunctionBegin; 1398 for (i=0; i<n; i++) { 1399 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1400 if (!flg) { 1401 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1402 } 1403 } 1404 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1405 PetscFunctionReturn(0); 1406 } 1407 1408 1409 /* -------------------------------------------------------------------*/ 1410 static struct _MatOps MatOps_Values = { 1411 MatSetValues_MPISBAIJ, 1412 MatGetRow_MPISBAIJ, 1413 MatRestoreRow_MPISBAIJ, 1414 MatMult_MPISBAIJ, 1415 /* 4*/ MatMultAdd_MPISBAIJ, 1416 MatMultTranspose_MPISBAIJ, 1417 MatMultTransposeAdd_MPISBAIJ, 1418 0, 1419 0, 1420 0, 1421 /*10*/ 0, 1422 0, 1423 0, 1424 MatRelax_MPISBAIJ, 1425 MatTranspose_MPISBAIJ, 1426 /*15*/ MatGetInfo_MPISBAIJ, 1427 MatEqual_MPISBAIJ, 1428 MatGetDiagonal_MPISBAIJ, 1429 MatDiagonalScale_MPISBAIJ, 1430 MatNorm_MPISBAIJ, 1431 /*20*/ MatAssemblyBegin_MPISBAIJ, 1432 MatAssemblyEnd_MPISBAIJ, 1433 0, 1434 MatSetOption_MPISBAIJ, 1435 MatZeroEntries_MPISBAIJ, 1436 /*25*/ 0, 1437 0, 1438 0, 1439 0, 1440 0, 1441 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1442 0, 1443 0, 1444 0, 1445 0, 1446 /*35*/ MatDuplicate_MPISBAIJ, 1447 0, 1448 0, 1449 0, 1450 0, 1451 /*40*/ 0, 1452 MatGetSubMatrices_MPISBAIJ, 1453 MatIncreaseOverlap_MPISBAIJ, 1454 MatGetValues_MPISBAIJ, 1455 0, 1456 /*45*/ MatPrintHelp_MPISBAIJ, 1457 MatScale_MPISBAIJ, 1458 0, 1459 0, 1460 0, 1461 /*50*/ 0, 1462 0, 1463 0, 1464 0, 1465 0, 1466 /*55*/ 0, 1467 0, 1468 MatSetUnfactored_MPISBAIJ, 1469 0, 1470 MatSetValuesBlocked_MPISBAIJ, 1471 /*60*/ 0, 1472 0, 1473 0, 1474 MatGetPetscMaps_Petsc, 1475 0, 1476 /*65*/ 0, 1477 0, 1478 0, 1479 0, 1480 0, 1481 /*70*/ MatGetRowMax_MPISBAIJ, 1482 0, 1483 0, 1484 0, 1485 0, 1486 /*75*/ 0, 1487 0, 1488 0, 1489 0, 1490 0, 1491 /*80*/ 0, 1492 0, 1493 0, 1494 0, 1495 MatLoad_MPISBAIJ, 1496 /*85*/ 0, 1497 0, 1498 0, 1499 0, 1500 0, 1501 /*90*/ 0, 1502 0, 1503 0, 1504 0, 1505 0, 1506 /*95*/ 0, 1507 0, 1508 0, 1509 0}; 1510 1511 1512 EXTERN_C_BEGIN 1513 #undef __FUNCT__ 1514 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1515 PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1516 { 1517 PetscFunctionBegin; 1518 *a = ((Mat_MPISBAIJ *)A->data)->A; 1519 *iscopy = PETSC_FALSE; 1520 PetscFunctionReturn(0); 1521 } 1522 EXTERN_C_END 1523 1524 EXTERN_C_BEGIN 1525 #undef __FUNCT__ 1526 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1527 PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1528 { 1529 Mat_MPISBAIJ *b; 1530 PetscErrorCode ierr; 1531 PetscInt i,mbs,Mbs; 1532 1533 PetscFunctionBegin; 1534 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1535 1536 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1537 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1538 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1539 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1540 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1541 if (d_nnz) { 1542 for (i=0; i<B->m/bs; i++) { 1543 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]); 1544 } 1545 } 1546 if (o_nnz) { 1547 for (i=0; i<B->m/bs; i++) { 1548 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]); 1549 } 1550 } 1551 B->preallocated = PETSC_TRUE; 1552 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1553 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1554 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1555 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1556 1557 b = (Mat_MPISBAIJ*)B->data; 1558 mbs = B->m/bs; 1559 Mbs = B->M/bs; 1560 if (mbs*bs != B->m) { 1561 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->m,bs); 1562 } 1563 1564 B->bs = bs; 1565 b->bs2 = bs*bs; 1566 b->mbs = mbs; 1567 b->nbs = mbs; 1568 b->Mbs = Mbs; 1569 b->Nbs = Mbs; 1570 1571 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 1572 b->rowners[0] = 0; 1573 for (i=2; i<=b->size; i++) { 1574 b->rowners[i] += b->rowners[i-1]; 1575 } 1576 b->rstart = b->rowners[b->rank]; 1577 b->rend = b->rowners[b->rank+1]; 1578 b->cstart = b->rstart; 1579 b->cend = b->rend; 1580 for (i=0; i<=b->size; i++) { 1581 b->rowners_bs[i] = b->rowners[i]*bs; 1582 } 1583 b->rstart_bs = b-> rstart*bs; 1584 b->rend_bs = b->rend*bs; 1585 1586 b->cstart_bs = b->cstart*bs; 1587 b->cend_bs = b->cend*bs; 1588 1589 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1590 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1591 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1592 PetscLogObjectParent(B,b->A); 1593 1594 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1595 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1596 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1597 PetscLogObjectParent(B,b->B); 1598 1599 /* build cache for off array entries formed */ 1600 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1601 1602 PetscFunctionReturn(0); 1603 } 1604 EXTERN_C_END 1605 1606 /*MC 1607 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1608 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1609 1610 Options Database Keys: 1611 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1612 1613 Level: beginner 1614 1615 .seealso: MatCreateMPISBAIJ 1616 M*/ 1617 1618 EXTERN_C_BEGIN 1619 #undef __FUNCT__ 1620 #define __FUNCT__ "MatCreate_MPISBAIJ" 1621 PetscErrorCode MatCreate_MPISBAIJ(Mat B) 1622 { 1623 Mat_MPISBAIJ *b; 1624 PetscErrorCode ierr; 1625 PetscTruth flg; 1626 1627 PetscFunctionBegin; 1628 1629 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1630 B->data = (void*)b; 1631 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1632 1633 B->ops->destroy = MatDestroy_MPISBAIJ; 1634 B->ops->view = MatView_MPISBAIJ; 1635 B->mapping = 0; 1636 B->factor = 0; 1637 B->assembled = PETSC_FALSE; 1638 1639 B->insertmode = NOT_SET_VALUES; 1640 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1641 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1642 1643 /* build local table of row and column ownerships */ 1644 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 1645 b->cowners = b->rowners + b->size + 2; 1646 b->rowners_bs = b->cowners + b->size + 2; 1647 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1648 1649 /* build cache for off array entries formed */ 1650 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1651 b->donotstash = PETSC_FALSE; 1652 b->colmap = PETSC_NULL; 1653 b->garray = PETSC_NULL; 1654 b->roworiented = PETSC_TRUE; 1655 1656 #if defined(PETSC_USE_MAT_SINGLE) 1657 /* stuff for MatSetValues_XXX in single precision */ 1658 b->setvalueslen = 0; 1659 b->setvaluescopy = PETSC_NULL; 1660 #endif 1661 1662 /* stuff used in block assembly */ 1663 b->barray = 0; 1664 1665 /* stuff used for matrix vector multiply */ 1666 b->lvec = 0; 1667 b->Mvctx = 0; 1668 b->slvec0 = 0; 1669 b->slvec0b = 0; 1670 b->slvec1 = 0; 1671 b->slvec1a = 0; 1672 b->slvec1b = 0; 1673 b->sMvctx = 0; 1674 1675 /* stuff for MatGetRow() */ 1676 b->rowindices = 0; 1677 b->rowvalues = 0; 1678 b->getrowactive = PETSC_FALSE; 1679 1680 /* hash table stuff */ 1681 b->ht = 0; 1682 b->hd = 0; 1683 b->ht_size = 0; 1684 b->ht_flag = PETSC_FALSE; 1685 b->ht_fact = 0; 1686 b->ht_total_ct = 0; 1687 b->ht_insert_ct = 0; 1688 1689 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1690 if (flg) { 1691 PetscReal fact = 1.39; 1692 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1693 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1694 if (fact <= 1.0) fact = 1.39; 1695 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1696 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1697 } 1698 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1699 "MatStoreValues_MPISBAIJ", 1700 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1701 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1702 "MatRetrieveValues_MPISBAIJ", 1703 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1704 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1705 "MatGetDiagonalBlock_MPISBAIJ", 1706 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1707 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1708 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1709 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1710 B->symmetric = PETSC_TRUE; 1711 B->structurally_symmetric = PETSC_TRUE; 1712 B->symmetric_set = PETSC_TRUE; 1713 B->structurally_symmetric_set = PETSC_TRUE; 1714 PetscFunctionReturn(0); 1715 } 1716 EXTERN_C_END 1717 1718 /*MC 1719 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1720 1721 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1722 and MATMPISBAIJ otherwise. 1723 1724 Options Database Keys: 1725 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1726 1727 Level: beginner 1728 1729 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1730 M*/ 1731 1732 EXTERN_C_BEGIN 1733 #undef __FUNCT__ 1734 #define __FUNCT__ "MatCreate_SBAIJ" 1735 PetscErrorCode MatCreate_SBAIJ(Mat A) 1736 { 1737 PetscErrorCode ierr; 1738 PetscMPIInt size; 1739 1740 PetscFunctionBegin; 1741 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1742 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1743 if (size == 1) { 1744 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1745 } else { 1746 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1747 } 1748 PetscFunctionReturn(0); 1749 } 1750 EXTERN_C_END 1751 1752 #undef __FUNCT__ 1753 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1754 /*@C 1755 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1756 the user should preallocate the matrix storage by setting the parameters 1757 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1758 performance can be increased by more than a factor of 50. 1759 1760 Collective on Mat 1761 1762 Input Parameters: 1763 + A - the matrix 1764 . bs - size of blockk 1765 . d_nz - number of block nonzeros per block row in diagonal portion of local 1766 submatrix (same for all local rows) 1767 . d_nnz - array containing the number of block nonzeros in the various block rows 1768 in the upper triangular and diagonal part of the in diagonal portion of the local 1769 (possibly different for each block row) or PETSC_NULL. You must leave room 1770 for the diagonal entry even if it is zero. 1771 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1772 submatrix (same for all local rows). 1773 - o_nnz - array containing the number of nonzeros in the various block rows of the 1774 off-diagonal portion of the local submatrix (possibly different for 1775 each block row) or PETSC_NULL. 1776 1777 1778 Options Database Keys: 1779 . -mat_no_unroll - uses code that does not unroll the loops in the 1780 block calculations (much slower) 1781 . -mat_block_size - size of the blocks to use 1782 1783 Notes: 1784 1785 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1786 than it must be used on all processors that share the object for that argument. 1787 1788 If the *_nnz parameter is given then the *_nz parameter is ignored 1789 1790 Storage Information: 1791 For a square global matrix we define each processor's diagonal portion 1792 to be its local rows and the corresponding columns (a square submatrix); 1793 each processor's off-diagonal portion encompasses the remainder of the 1794 local matrix (a rectangular submatrix). 1795 1796 The user can specify preallocated storage for the diagonal part of 1797 the local submatrix with either d_nz or d_nnz (not both). Set 1798 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1799 memory allocation. Likewise, specify preallocated storage for the 1800 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1801 1802 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1803 the figure below we depict these three local rows and all columns (0-11). 1804 1805 .vb 1806 0 1 2 3 4 5 6 7 8 9 10 11 1807 ------------------- 1808 row 3 | o o o d d d o o o o o o 1809 row 4 | o o o d d d o o o o o o 1810 row 5 | o o o d d d o o o o o o 1811 ------------------- 1812 .ve 1813 1814 Thus, any entries in the d locations are stored in the d (diagonal) 1815 submatrix, and any entries in the o locations are stored in the 1816 o (off-diagonal) submatrix. Note that the d matrix is stored in 1817 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1818 1819 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1820 plus the diagonal part of the d matrix, 1821 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1822 In general, for PDE problems in which most nonzeros are near the diagonal, 1823 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1824 or you will get TERRIBLE performance; see the users' manual chapter on 1825 matrices. 1826 1827 Level: intermediate 1828 1829 .keywords: matrix, block, aij, compressed row, sparse, parallel 1830 1831 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1832 @*/ 1833 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1834 { 1835 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1836 1837 PetscFunctionBegin; 1838 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1839 if (f) { 1840 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1841 } 1842 PetscFunctionReturn(0); 1843 } 1844 1845 #undef __FUNCT__ 1846 #define __FUNCT__ "MatCreateMPISBAIJ" 1847 /*@C 1848 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1849 (block compressed row). For good matrix assembly performance 1850 the user should preallocate the matrix storage by setting the parameters 1851 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1852 performance can be increased by more than a factor of 50. 1853 1854 Collective on MPI_Comm 1855 1856 Input Parameters: 1857 + comm - MPI communicator 1858 . bs - size of blockk 1859 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1860 This value should be the same as the local size used in creating the 1861 y vector for the matrix-vector product y = Ax. 1862 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1863 This value should be the same as the local size used in creating the 1864 x vector for the matrix-vector product y = Ax. 1865 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1866 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1867 . d_nz - number of block nonzeros per block row in diagonal portion of local 1868 submatrix (same for all local rows) 1869 . d_nnz - array containing the number of block nonzeros in the various block rows 1870 in the upper triangular portion of the in diagonal portion of the local 1871 (possibly different for each block block row) or PETSC_NULL. 1872 You must leave room for the diagonal entry even if it is zero. 1873 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1874 submatrix (same for all local rows). 1875 - o_nnz - array containing the number of nonzeros in the various block rows of the 1876 off-diagonal portion of the local submatrix (possibly different for 1877 each block row) or PETSC_NULL. 1878 1879 Output Parameter: 1880 . A - the matrix 1881 1882 Options Database Keys: 1883 . -mat_no_unroll - uses code that does not unroll the loops in the 1884 block calculations (much slower) 1885 . -mat_block_size - size of the blocks to use 1886 . -mat_mpi - use the parallel matrix data structures even on one processor 1887 (defaults to using SeqBAIJ format on one processor) 1888 1889 Notes: 1890 The user MUST specify either the local or global matrix dimensions 1891 (possibly both). 1892 1893 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1894 than it must be used on all processors that share the object for that argument. 1895 1896 If the *_nnz parameter is given then the *_nz parameter is ignored 1897 1898 Storage Information: 1899 For a square global matrix we define each processor's diagonal portion 1900 to be its local rows and the corresponding columns (a square submatrix); 1901 each processor's off-diagonal portion encompasses the remainder of the 1902 local matrix (a rectangular submatrix). 1903 1904 The user can specify preallocated storage for the diagonal part of 1905 the local submatrix with either d_nz or d_nnz (not both). Set 1906 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1907 memory allocation. Likewise, specify preallocated storage for the 1908 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1909 1910 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1911 the figure below we depict these three local rows and all columns (0-11). 1912 1913 .vb 1914 0 1 2 3 4 5 6 7 8 9 10 11 1915 ------------------- 1916 row 3 | o o o d d d o o o o o o 1917 row 4 | o o o d d d o o o o o o 1918 row 5 | o o o d d d o o o o o o 1919 ------------------- 1920 .ve 1921 1922 Thus, any entries in the d locations are stored in the d (diagonal) 1923 submatrix, and any entries in the o locations are stored in the 1924 o (off-diagonal) submatrix. Note that the d matrix is stored in 1925 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1926 1927 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1928 plus the diagonal part of the d matrix, 1929 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1930 In general, for PDE problems in which most nonzeros are near the diagonal, 1931 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1932 or you will get TERRIBLE performance; see the users' manual chapter on 1933 matrices. 1934 1935 Level: intermediate 1936 1937 .keywords: matrix, block, aij, compressed row, sparse, parallel 1938 1939 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1940 @*/ 1941 1942 PetscErrorCode 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) 1943 { 1944 PetscErrorCode ierr; 1945 PetscMPIInt size; 1946 1947 PetscFunctionBegin; 1948 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1949 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1950 if (size > 1) { 1951 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1952 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1953 } else { 1954 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1955 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1956 } 1957 PetscFunctionReturn(0); 1958 } 1959 1960 1961 #undef __FUNCT__ 1962 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1963 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1964 { 1965 Mat mat; 1966 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1967 PetscErrorCode ierr; 1968 PetscInt len=0,nt,bs=matin->bs,mbs=oldmat->mbs; 1969 PetscScalar *array; 1970 1971 PetscFunctionBegin; 1972 *newmat = 0; 1973 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1974 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 1975 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1976 1977 mat->factor = matin->factor; 1978 mat->preallocated = PETSC_TRUE; 1979 mat->assembled = PETSC_TRUE; 1980 mat->insertmode = NOT_SET_VALUES; 1981 1982 a = (Mat_MPISBAIJ*)mat->data; 1983 mat->bs = matin->bs; 1984 a->bs2 = oldmat->bs2; 1985 a->mbs = oldmat->mbs; 1986 a->nbs = oldmat->nbs; 1987 a->Mbs = oldmat->Mbs; 1988 a->Nbs = oldmat->Nbs; 1989 1990 a->rstart = oldmat->rstart; 1991 a->rend = oldmat->rend; 1992 a->cstart = oldmat->cstart; 1993 a->cend = oldmat->cend; 1994 a->size = oldmat->size; 1995 a->rank = oldmat->rank; 1996 a->donotstash = oldmat->donotstash; 1997 a->roworiented = oldmat->roworiented; 1998 a->rowindices = 0; 1999 a->rowvalues = 0; 2000 a->getrowactive = PETSC_FALSE; 2001 a->barray = 0; 2002 a->rstart_bs = oldmat->rstart_bs; 2003 a->rend_bs = oldmat->rend_bs; 2004 a->cstart_bs = oldmat->cstart_bs; 2005 a->cend_bs = oldmat->cend_bs; 2006 2007 /* hash table stuff */ 2008 a->ht = 0; 2009 a->hd = 0; 2010 a->ht_size = 0; 2011 a->ht_flag = oldmat->ht_flag; 2012 a->ht_fact = oldmat->ht_fact; 2013 a->ht_total_ct = 0; 2014 a->ht_insert_ct = 0; 2015 2016 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2017 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2018 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2019 if (oldmat->colmap) { 2020 #if defined (PETSC_USE_CTABLE) 2021 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2022 #else 2023 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2024 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt)); 2025 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2026 #endif 2027 } else a->colmap = 0; 2028 2029 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2030 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2031 PetscLogObjectMemory(mat,len*sizeof(PetscInt)); 2032 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2033 } else a->garray = 0; 2034 2035 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2036 PetscLogObjectParent(mat,a->lvec); 2037 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2038 PetscLogObjectParent(mat,a->Mvctx); 2039 2040 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2041 PetscLogObjectParent(mat,a->slvec0); 2042 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2043 PetscLogObjectParent(mat,a->slvec1); 2044 2045 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2046 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2047 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2048 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2049 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2050 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2051 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2052 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2053 PetscLogObjectParent(mat,a->slvec0); 2054 PetscLogObjectParent(mat,a->slvec1); 2055 PetscLogObjectParent(mat,a->slvec0b); 2056 PetscLogObjectParent(mat,a->slvec1a); 2057 PetscLogObjectParent(mat,a->slvec1b); 2058 2059 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2060 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2061 a->sMvctx = oldmat->sMvctx; 2062 PetscLogObjectParent(mat,a->sMvctx); 2063 2064 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2065 PetscLogObjectParent(mat,a->A); 2066 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2067 PetscLogObjectParent(mat,a->B); 2068 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2069 *newmat = mat; 2070 PetscFunctionReturn(0); 2071 } 2072 2073 #include "petscsys.h" 2074 2075 #undef __FUNCT__ 2076 #define __FUNCT__ "MatLoad_MPISBAIJ" 2077 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2078 { 2079 Mat A; 2080 PetscErrorCode ierr; 2081 PetscInt i,nz,j,rstart,rend; 2082 PetscScalar *vals,*buf; 2083 MPI_Comm comm = ((PetscObject)viewer)->comm; 2084 MPI_Status status; 2085 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners; 2086 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2087 PetscInt *locrowlens,*procsnz = 0,jj,*mycols,*ibuf; 2088 PetscInt bs=1,Mbs,mbs,extra_rows; 2089 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2090 PetscInt dcount,kmax,k,nzcount,tmp; 2091 int fd; 2092 2093 PetscFunctionBegin; 2094 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2095 2096 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2097 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2098 if (!rank) { 2099 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2100 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2101 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2102 if (header[3] < 0) { 2103 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2104 } 2105 } 2106 2107 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2108 M = header[1]; N = header[2]; 2109 2110 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2111 2112 /* 2113 This code adds extra rows to make sure the number of rows is 2114 divisible by the blocksize 2115 */ 2116 Mbs = M/bs; 2117 extra_rows = bs - M + bs*(Mbs); 2118 if (extra_rows == bs) extra_rows = 0; 2119 else Mbs++; 2120 if (extra_rows &&!rank) { 2121 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2122 } 2123 2124 /* determine ownership of all rows */ 2125 mbs = Mbs/size + ((Mbs % size) > rank); 2126 m = mbs*bs; 2127 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2128 browners = rowners + size + 1; 2129 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2130 rowners[0] = 0; 2131 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2132 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2133 rstart = rowners[rank]; 2134 rend = rowners[rank+1]; 2135 2136 /* distribute row lengths to all processors */ 2137 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2138 if (!rank) { 2139 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2140 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2141 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2142 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2143 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2144 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2145 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2146 } else { 2147 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2148 } 2149 2150 if (!rank) { /* procs[0] */ 2151 /* calculate the number of nonzeros on each processor */ 2152 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2153 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2154 for (i=0; i<size; i++) { 2155 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2156 procsnz[i] += rowlengths[j]; 2157 } 2158 } 2159 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2160 2161 /* determine max buffer needed and allocate it */ 2162 maxnz = 0; 2163 for (i=0; i<size; i++) { 2164 maxnz = PetscMax(maxnz,procsnz[i]); 2165 } 2166 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2167 2168 /* read in my part of the matrix column indices */ 2169 nz = procsnz[0]; 2170 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2171 mycols = ibuf; 2172 if (size == 1) nz -= extra_rows; 2173 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2174 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2175 2176 /* read in every ones (except the last) and ship off */ 2177 for (i=1; i<size-1; i++) { 2178 nz = procsnz[i]; 2179 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2180 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2181 } 2182 /* read in the stuff for the last proc */ 2183 if (size != 1) { 2184 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2185 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2186 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2187 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2188 } 2189 ierr = PetscFree(cols);CHKERRQ(ierr); 2190 } else { /* procs[i], i>0 */ 2191 /* determine buffer space needed for message */ 2192 nz = 0; 2193 for (i=0; i<m; i++) { 2194 nz += locrowlens[i]; 2195 } 2196 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2197 mycols = ibuf; 2198 /* receive message of column indices*/ 2199 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2200 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2201 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2202 } 2203 2204 /* loop over local rows, determining number of off diagonal entries */ 2205 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2206 odlens = dlens + (rend-rstart); 2207 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2208 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2209 masked1 = mask + Mbs; 2210 masked2 = masked1 + Mbs; 2211 rowcount = 0; nzcount = 0; 2212 for (i=0; i<mbs; i++) { 2213 dcount = 0; 2214 odcount = 0; 2215 for (j=0; j<bs; j++) { 2216 kmax = locrowlens[rowcount]; 2217 for (k=0; k<kmax; k++) { 2218 tmp = mycols[nzcount++]/bs; /* block col. index */ 2219 if (!mask[tmp]) { 2220 mask[tmp] = 1; 2221 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2222 else masked1[dcount++] = tmp; /* entry in diag portion */ 2223 } 2224 } 2225 rowcount++; 2226 } 2227 2228 dlens[i] = dcount; /* d_nzz[i] */ 2229 odlens[i] = odcount; /* o_nzz[i] */ 2230 2231 /* zero out the mask elements we set */ 2232 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2233 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2234 } 2235 2236 /* create our matrix */ 2237 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2238 ierr = MatSetType(A,type);CHKERRQ(ierr); 2239 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2240 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2241 2242 if (!rank) { 2243 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2244 /* read in my part of the matrix numerical values */ 2245 nz = procsnz[0]; 2246 vals = buf; 2247 mycols = ibuf; 2248 if (size == 1) nz -= extra_rows; 2249 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2250 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2251 2252 /* insert into matrix */ 2253 jj = rstart*bs; 2254 for (i=0; i<m; i++) { 2255 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2256 mycols += locrowlens[i]; 2257 vals += locrowlens[i]; 2258 jj++; 2259 } 2260 2261 /* read in other processors (except the last one) and ship out */ 2262 for (i=1; i<size-1; i++) { 2263 nz = procsnz[i]; 2264 vals = buf; 2265 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2266 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2267 } 2268 /* the last proc */ 2269 if (size != 1){ 2270 nz = procsnz[i] - extra_rows; 2271 vals = buf; 2272 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2273 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2274 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2275 } 2276 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2277 2278 } else { 2279 /* receive numeric values */ 2280 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2281 2282 /* receive message of values*/ 2283 vals = buf; 2284 mycols = ibuf; 2285 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2286 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2287 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2288 2289 /* insert into matrix */ 2290 jj = rstart*bs; 2291 for (i=0; i<m; i++) { 2292 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2293 mycols += locrowlens[i]; 2294 vals += locrowlens[i]; 2295 jj++; 2296 } 2297 } 2298 2299 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2300 ierr = PetscFree(buf);CHKERRQ(ierr); 2301 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2302 ierr = PetscFree(rowners);CHKERRQ(ierr); 2303 ierr = PetscFree(dlens);CHKERRQ(ierr); 2304 ierr = PetscFree(mask);CHKERRQ(ierr); 2305 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2306 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2307 *newmat = A; 2308 PetscFunctionReturn(0); 2309 } 2310 2311 #undef __FUNCT__ 2312 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2313 /*XXXXX@ 2314 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2315 2316 Input Parameters: 2317 . mat - the matrix 2318 . fact - factor 2319 2320 Collective on Mat 2321 2322 Level: advanced 2323 2324 Notes: 2325 This can also be set by the command line option: -mat_use_hash_table fact 2326 2327 .keywords: matrix, hashtable, factor, HT 2328 2329 .seealso: MatSetOption() 2330 @XXXXX*/ 2331 2332 2333 #undef __FUNCT__ 2334 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2335 PetscErrorCode MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2336 { 2337 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2338 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2339 PetscReal atmp; 2340 PetscReal *work,*svalues,*rvalues; 2341 PetscErrorCode ierr; 2342 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2343 PetscMPIInt rank,size; 2344 PetscInt *rowners_bs,dest,count,source; 2345 PetscScalar *va; 2346 MatScalar *ba; 2347 MPI_Status stat; 2348 2349 PetscFunctionBegin; 2350 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2351 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2352 2353 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2354 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2355 2356 bs = A->bs; 2357 mbs = a->mbs; 2358 Mbs = a->Mbs; 2359 ba = b->a; 2360 bi = b->i; 2361 bj = b->j; 2362 2363 /* find ownerships */ 2364 rowners_bs = a->rowners_bs; 2365 2366 /* each proc creates an array to be distributed */ 2367 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2368 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2369 2370 /* row_max for B */ 2371 if (rank != size-1){ 2372 for (i=0; i<mbs; i++) { 2373 ncols = bi[1] - bi[0]; bi++; 2374 brow = bs*i; 2375 for (j=0; j<ncols; j++){ 2376 bcol = bs*(*bj); 2377 for (kcol=0; kcol<bs; kcol++){ 2378 col = bcol + kcol; /* local col index */ 2379 col += rowners_bs[rank+1]; /* global col index */ 2380 for (krow=0; krow<bs; krow++){ 2381 atmp = PetscAbsScalar(*ba); ba++; 2382 row = brow + krow; /* local row index */ 2383 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2384 if (work[col] < atmp) work[col] = atmp; 2385 } 2386 } 2387 bj++; 2388 } 2389 } 2390 2391 /* send values to its owners */ 2392 for (dest=rank+1; dest<size; dest++){ 2393 svalues = work + rowners_bs[dest]; 2394 count = rowners_bs[dest+1]-rowners_bs[dest]; 2395 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2396 } 2397 } 2398 2399 /* receive values */ 2400 if (rank){ 2401 rvalues = work; 2402 count = rowners_bs[rank+1]-rowners_bs[rank]; 2403 for (source=0; source<rank; source++){ 2404 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2405 /* process values */ 2406 for (i=0; i<count; i++){ 2407 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2408 } 2409 } 2410 } 2411 2412 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2413 ierr = PetscFree(work);CHKERRQ(ierr); 2414 PetscFunctionReturn(0); 2415 } 2416 2417 #undef __FUNCT__ 2418 #define __FUNCT__ "MatRelax_MPISBAIJ" 2419 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2420 { 2421 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2422 PetscErrorCode ierr; 2423 PetscInt mbs=mat->mbs,bs=matin->bs; 2424 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2425 Vec bb1; 2426 2427 PetscFunctionBegin; 2428 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2429 if (bs > 1) 2430 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2431 2432 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2433 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2434 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2435 its--; 2436 } 2437 2438 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2439 while (its--){ 2440 2441 /* lower triangular part: slvec0b = - B^T*xx */ 2442 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2443 2444 /* copy xx into slvec0a */ 2445 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2446 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2447 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2448 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2449 2450 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2451 2452 /* copy bb into slvec1a */ 2453 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2454 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2455 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2456 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2457 2458 /* set slvec1b = 0 */ 2459 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2460 2461 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2462 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2463 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2464 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2465 2466 /* upper triangular part: bb1 = bb1 - B*x */ 2467 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2468 2469 /* local diagonal sweep */ 2470 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2471 } 2472 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2473 } else { 2474 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2475 } 2476 PetscFunctionReturn(0); 2477 } 2478 2479 #undef __FUNCT__ 2480 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2481 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2482 { 2483 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2484 PetscErrorCode ierr; 2485 PetscScalar mone=-1.0; 2486 Vec lvec1,bb1; 2487 2488 PetscFunctionBegin; 2489 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2490 if (matin->bs > 1) 2491 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2492 2493 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2494 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2495 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2496 its--; 2497 } 2498 2499 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2500 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2501 while (its--){ 2502 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2503 2504 /* lower diagonal part: bb1 = bb - B^T*xx */ 2505 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2506 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2507 2508 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2509 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2510 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2511 2512 /* upper diagonal part: bb1 = bb1 - B*x */ 2513 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2514 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2515 2516 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2517 2518 /* diagonal sweep */ 2519 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2520 } 2521 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2522 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2523 } else { 2524 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2525 } 2526 PetscFunctionReturn(0); 2527 } 2528 2529