1 /*$Id: mpisbaij.c,v 1.61 2001/08/10 03:31:37 bsmith Exp $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "mpisbaij.h" 5 #include "src/mat/impls/sbaij/seq/sbaij.h" 6 7 extern int MatSetUpMultiply_MPISBAIJ(Mat); 8 extern int MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 extern int DisAssemble_MPISBAIJ(Mat); 10 extern int MatIncreaseOverlap_MPISBAIJ(Mat,int,IS[],int); 11 extern int MatGetValues_SeqSBAIJ(Mat,int,const int[],int,const int[],PetscScalar []); 12 extern int MatGetValues_SeqBAIJ(Mat,int,const int[],int,const int[],PetscScalar []); 13 extern int MatSetValues_SeqSBAIJ(Mat,int,const int [],int,const int [],const PetscScalar [],InsertMode); 14 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,const int[],int,const int[],const PetscScalar[],InsertMode); 15 extern int MatSetValuesBlocked_SeqBAIJ(Mat,int,const int[],int,const int[],const PetscScalar[],InsertMode); 16 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,PetscScalar**); 17 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,PetscScalar**); 18 extern int MatPrintHelp_SeqSBAIJ(Mat); 19 extern int MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 20 extern int MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 21 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 22 extern int MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,int,int,Vec); 23 24 /* UGLY, ugly, ugly 25 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 26 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 27 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 28 converts the entries into single precision and then calls ..._MatScalar() to put them 29 into the single precision data structures. 30 */ 31 #if defined(PETSC_USE_MAT_SINGLE) 32 extern int MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,int,const int[],int,const int[],const MatScalar[],InsertMode); 33 extern int MatSetValues_MPISBAIJ_MatScalar(Mat,int,const int[],int,const int[],const MatScalar[],InsertMode); 34 extern int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,int,const int[],int,const int[],const MatScalar[],InsertMode); 35 extern int MatSetValues_MPISBAIJ_HT_MatScalar(Mat,int,const int[],int,const int[],const MatScalar[],InsertMode); 36 extern int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,int,const int[],int,const int[],const MatScalar[],InsertMode); 37 #else 38 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 39 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 40 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 41 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 42 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 43 #endif 44 45 EXTERN_C_BEGIN 46 #undef __FUNCT__ 47 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 48 int MatStoreValues_MPISBAIJ(Mat mat) 49 { 50 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 51 int ierr; 52 53 PetscFunctionBegin; 54 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 55 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 56 PetscFunctionReturn(0); 57 } 58 EXTERN_C_END 59 60 EXTERN_C_BEGIN 61 #undef __FUNCT__ 62 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 63 int MatRetrieveValues_MPISBAIJ(Mat mat) 64 { 65 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 66 int ierr; 67 68 PetscFunctionBegin; 69 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 70 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 71 PetscFunctionReturn(0); 72 } 73 EXTERN_C_END 74 75 76 #define CHUNKSIZE 10 77 78 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 79 { \ 80 \ 81 brow = row/bs; \ 82 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 83 rmax = aimax[brow]; nrow = ailen[brow]; \ 84 bcol = col/bs; \ 85 ridx = row % bs; cidx = col % bs; \ 86 low = 0; high = nrow; \ 87 while (high-low > 3) { \ 88 t = (low+high)/2; \ 89 if (rp[t] > bcol) high = t; \ 90 else low = t; \ 91 } \ 92 for (_i=low; _i<high; _i++) { \ 93 if (rp[_i] > bcol) break; \ 94 if (rp[_i] == bcol) { \ 95 bap = ap + bs2*_i + bs*cidx + ridx; \ 96 if (addv == ADD_VALUES) *bap += value; \ 97 else *bap = value; \ 98 goto a_noinsert; \ 99 } \ 100 } \ 101 if (a->nonew == 1) goto a_noinsert; \ 102 else if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) into matrix", row, col); \ 103 if (nrow >= rmax) { \ 104 /* there is no extra room in row, therefore enlarge */ \ 105 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 106 MatScalar *new_a; \ 107 \ 108 if (a->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); \ 109 \ 110 /* malloc new storage space */ \ 111 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 112 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 113 new_j = (int*)(new_a + bs2*new_nz); \ 114 new_i = new_j + new_nz; \ 115 \ 116 /* copy over old data into new slots */ \ 117 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 118 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 119 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 120 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 121 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 122 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 123 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 124 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 125 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 126 /* free up old matrix storage */ \ 127 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 128 if (!a->singlemalloc) { \ 129 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 130 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 131 } \ 132 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 133 a->singlemalloc = PETSC_TRUE; \ 134 \ 135 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 136 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 137 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 138 a->maxnz += bs2*CHUNKSIZE; \ 139 a->reallocs++; \ 140 a->nz++; \ 141 } \ 142 N = nrow++ - 1; \ 143 /* shift up all the later entries in this row */ \ 144 for (ii=N; ii>=_i; ii--) { \ 145 rp[ii+1] = rp[ii]; \ 146 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 147 } \ 148 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 149 rp[_i] = bcol; \ 150 ap[bs2*_i + bs*cidx + ridx] = value; \ 151 a_noinsert:; \ 152 ailen[brow] = nrow; \ 153 } 154 #ifndef MatSetValues_SeqBAIJ_B_Private 155 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 156 { \ 157 brow = row/bs; \ 158 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 159 rmax = bimax[brow]; nrow = bilen[brow]; \ 160 bcol = col/bs; \ 161 ridx = row % bs; cidx = col % bs; \ 162 low = 0; high = nrow; \ 163 while (high-low > 3) { \ 164 t = (low+high)/2; \ 165 if (rp[t] > bcol) high = t; \ 166 else low = t; \ 167 } \ 168 for (_i=low; _i<high; _i++) { \ 169 if (rp[_i] > bcol) break; \ 170 if (rp[_i] == bcol) { \ 171 bap = ap + bs2*_i + bs*cidx + ridx; \ 172 if (addv == ADD_VALUES) *bap += value; \ 173 else *bap = value; \ 174 goto b_noinsert; \ 175 } \ 176 } \ 177 if (b->nonew == 1) goto b_noinsert; \ 178 else if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) into matrix", row, col); \ 179 if (nrow >= rmax) { \ 180 /* there is no extra room in row, therefore enlarge */ \ 181 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 182 MatScalar *new_a; \ 183 \ 184 if (b->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); \ 185 \ 186 /* malloc new storage space */ \ 187 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 188 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 189 new_j = (int*)(new_a + bs2*new_nz); \ 190 new_i = new_j + new_nz; \ 191 \ 192 /* copy over old data into new slots */ \ 193 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 194 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 195 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 196 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 197 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 198 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 199 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 200 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 201 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 202 /* free up old matrix storage */ \ 203 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 204 if (!b->singlemalloc) { \ 205 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 206 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 207 } \ 208 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 209 b->singlemalloc = PETSC_TRUE; \ 210 \ 211 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 212 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 213 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 214 b->maxnz += bs2*CHUNKSIZE; \ 215 b->reallocs++; \ 216 b->nz++; \ 217 } \ 218 N = nrow++ - 1; \ 219 /* shift up all the later entries in this row */ \ 220 for (ii=N; ii>=_i; ii--) { \ 221 rp[ii+1] = rp[ii]; \ 222 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 223 } \ 224 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 225 rp[_i] = bcol; \ 226 ap[bs2*_i + bs*cidx + ridx] = value; \ 227 b_noinsert:; \ 228 bilen[brow] = nrow; \ 229 } 230 #endif 231 232 #if defined(PETSC_USE_MAT_SINGLE) 233 #undef __FUNCT__ 234 #define __FUNCT__ "MatSetValues_MPISBAIJ" 235 int MatSetValues_MPISBAIJ(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 236 { 237 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 238 int ierr,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 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 259 { 260 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 261 int ierr,i,N = m*n*b->bs2; 262 MatScalar *vsingle; 263 264 PetscFunctionBegin; 265 if (N > b->setvalueslen) { 266 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 267 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 268 b->setvalueslen = N; 269 } 270 vsingle = b->setvaluescopy; 271 for (i=0; i<N; i++) { 272 vsingle[i] = v[i]; 273 } 274 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 275 PetscFunctionReturn(0); 276 } 277 278 #undef __FUNCT__ 279 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT" 280 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 281 { 282 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 283 int ierr,i,N = m*n; 284 MatScalar *vsingle; 285 286 PetscFunctionBegin; 287 SETERRQ(1,"Function not yet written for SBAIJ format"); 288 /* PetscFunctionReturn(0); */ 289 } 290 291 #undef __FUNCT__ 292 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT" 293 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 294 { 295 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 296 int ierr,i,N = m*n*b->bs2; 297 MatScalar *vsingle; 298 299 PetscFunctionBegin; 300 SETERRQ(1,"Function not yet written for SBAIJ format"); 301 /* PetscFunctionReturn(0); */ 302 } 303 #endif 304 305 /* Only add/insert a(i,j) with i<=j (blocks). 306 Any a(i,j) with i>j input by user is ingored. 307 */ 308 #undef __FUNCT__ 309 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 310 int MatSetValues_MPISBAIJ_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 311 { 312 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 313 MatScalar value; 314 PetscTruth roworiented = baij->roworiented; 315 int ierr,i,j,row,col; 316 int rstart_orig=baij->rstart_bs; 317 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 318 int cend_orig=baij->cend_bs,bs=baij->bs; 319 320 /* Some Variables required in the macro */ 321 Mat A = baij->A; 322 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 323 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 324 MatScalar *aa=a->a; 325 326 Mat B = baij->B; 327 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 328 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 329 MatScalar *ba=b->a; 330 331 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 332 int low,high,t,ridx,cidx,bs2=a->bs2; 333 MatScalar *ap,*bap; 334 335 /* for stash */ 336 int n_loc, *in_loc=0; 337 MatScalar *v_loc=0; 338 339 PetscFunctionBegin; 340 341 if(!baij->donotstash){ 342 ierr = PetscMalloc(n*sizeof(int),&in_loc);CHKERRQ(ierr); 343 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 344 } 345 346 for (i=0; i<m; i++) { 347 if (im[i] < 0) continue; 348 #if defined(PETSC_USE_BOPT_g) 349 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",im[i],mat->M-1); 350 #endif 351 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 352 row = im[i] - rstart_orig; /* local row index */ 353 for (j=0; j<n; j++) { 354 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 355 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 356 col = in[j] - cstart_orig; /* local col index */ 357 brow = row/bs; bcol = col/bs; 358 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 359 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 360 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 361 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 362 } else if (in[j] < 0) continue; 363 #if defined(PETSC_USE_BOPT_g) 364 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[j],mat->N-1);} 365 #endif 366 else { /* off-diag entry (B) */ 367 if (mat->was_assembled) { 368 if (!baij->colmap) { 369 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 370 } 371 #if defined (PETSC_USE_CTABLE) 372 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 373 col = col - 1; 374 #else 375 col = baij->colmap[in[j]/bs] - 1; 376 #endif 377 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 378 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 379 col = in[j]; 380 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 381 B = baij->B; 382 b = (Mat_SeqBAIJ*)(B)->data; 383 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 384 ba=b->a; 385 } else col += in[j]%bs; 386 } else col = in[j]; 387 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 388 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 389 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 390 } 391 } 392 } else { /* off processor entry */ 393 if (!baij->donotstash) { 394 n_loc = 0; 395 for (j=0; j<n; j++){ 396 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 397 in_loc[n_loc] = in[j]; 398 if (roworiented) { 399 v_loc[n_loc] = v[i*n+j]; 400 } else { 401 v_loc[n_loc] = v[j*m+i]; 402 } 403 n_loc++; 404 } 405 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 406 } 407 } 408 } 409 410 if(!baij->donotstash){ 411 ierr = PetscFree(in_loc);CHKERRQ(ierr); 412 ierr = PetscFree(v_loc);CHKERRQ(ierr); 413 } 414 PetscFunctionReturn(0); 415 } 416 417 #undef __FUNCT__ 418 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 419 int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 420 { 421 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 422 const MatScalar *value; 423 MatScalar *barray=baij->barray; 424 PetscTruth roworiented = baij->roworiented; 425 int ierr,i,j,ii,jj,row,col,rstart=baij->rstart; 426 int rend=baij->rend,cstart=baij->cstart,stepval; 427 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 428 429 PetscFunctionBegin; 430 if(!barray) { 431 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 432 baij->barray = barray; 433 } 434 435 if (roworiented) { 436 stepval = (n-1)*bs; 437 } else { 438 stepval = (m-1)*bs; 439 } 440 for (i=0; i<m; i++) { 441 if (im[i] < 0) continue; 442 #if defined(PETSC_USE_BOPT_g) 443 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %d max %d",im[i],baij->Mbs-1); 444 #endif 445 if (im[i] >= rstart && im[i] < rend) { 446 row = im[i] - rstart; 447 for (j=0; j<n; j++) { 448 /* If NumCol = 1 then a copy is not required */ 449 if ((roworiented) && (n == 1)) { 450 barray = (MatScalar*) v + i*bs2; 451 } else if((!roworiented) && (m == 1)) { 452 barray = (MatScalar*) v + j*bs2; 453 } else { /* Here a copy is required */ 454 if (roworiented) { 455 value = v + i*(stepval+bs)*bs + j*bs; 456 } else { 457 value = v + j*(stepval+bs)*bs + i*bs; 458 } 459 for (ii=0; ii<bs; ii++,value+=stepval) { 460 for (jj=0; jj<bs; jj++) { 461 *barray++ = *value++; 462 } 463 } 464 barray -=bs2; 465 } 466 467 if (in[j] >= cstart && in[j] < cend){ 468 col = in[j] - cstart; 469 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 470 } 471 else if (in[j] < 0) continue; 472 #if defined(PETSC_USE_BOPT_g) 473 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %d max %d",in[j],baij->Nbs-1);} 474 #endif 475 else { 476 if (mat->was_assembled) { 477 if (!baij->colmap) { 478 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 479 } 480 481 #if defined(PETSC_USE_BOPT_g) 482 #if defined (PETSC_USE_CTABLE) 483 { int data; 484 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 485 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 486 } 487 #else 488 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 489 #endif 490 #endif 491 #if defined (PETSC_USE_CTABLE) 492 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 493 col = (col - 1)/bs; 494 #else 495 col = (baij->colmap[in[j]] - 1)/bs; 496 #endif 497 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 498 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 499 col = in[j]; 500 } 501 } 502 else col = in[j]; 503 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 504 } 505 } 506 } else { 507 if (!baij->donotstash) { 508 if (roworiented) { 509 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 510 } else { 511 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 512 } 513 } 514 } 515 } 516 PetscFunctionReturn(0); 517 } 518 519 #define HASH_KEY 0.6180339887 520 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 521 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 522 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 523 #undef __FUNCT__ 524 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT_MatScalar" 525 int MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 526 { 527 PetscFunctionBegin; 528 SETERRQ(1,"Function not yet written for SBAIJ format"); 529 /* PetscFunctionReturn(0); */ 530 } 531 532 #undef __FUNCT__ 533 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 534 int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 535 { 536 PetscFunctionBegin; 537 SETERRQ(1,"Function not yet written for SBAIJ format"); 538 /* PetscFunctionReturn(0); */ 539 } 540 541 #undef __FUNCT__ 542 #define __FUNCT__ "MatGetValues_MPISBAIJ" 543 int MatGetValues_MPISBAIJ(Mat mat,int m,const int idxm[],int n,const int idxn[],PetscScalar v[]) 544 { 545 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 546 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 547 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 548 549 PetscFunctionBegin; 550 for (i=0; i<m; i++) { 551 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %d",idxm[i]); 552 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",idxm[i],mat->M-1); 553 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 554 row = idxm[i] - bsrstart; 555 for (j=0; j<n; j++) { 556 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %d",idxn[j]); 557 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",idxn[j],mat->N-1); 558 if (idxn[j] >= bscstart && idxn[j] < bscend){ 559 col = idxn[j] - bscstart; 560 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 561 } else { 562 if (!baij->colmap) { 563 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 564 } 565 #if defined (PETSC_USE_CTABLE) 566 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 567 data --; 568 #else 569 data = baij->colmap[idxn[j]/bs]-1; 570 #endif 571 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 572 else { 573 col = data + idxn[j]%bs; 574 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 575 } 576 } 577 } 578 } else { 579 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 580 } 581 } 582 PetscFunctionReturn(0); 583 } 584 585 #undef __FUNCT__ 586 #define __FUNCT__ "MatNorm_MPISBAIJ" 587 int MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 588 { 589 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 590 /* Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ*)baij->A->data; */ 591 /* Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ*)baij->B->data; */ 592 int ierr; 593 PetscReal sum[2],*lnorm2; 594 595 PetscFunctionBegin; 596 if (baij->size == 1) { 597 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 598 } else { 599 if (type == NORM_FROBENIUS) { 600 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 601 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 602 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 603 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 604 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 605 /* 606 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 607 PetscSynchronizedPrintf(mat->comm,"[%d], lnorm2=%g, %g\n",rank,lnorm2[0],lnorm2[1]); 608 */ 609 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 610 /* 611 PetscSynchronizedPrintf(mat->comm,"[%d], sum=%g, %g\n",rank,sum[0],sum[1]); 612 PetscSynchronizedFlush(mat->comm); */ 613 614 *norm = sqrt(sum[0] + 2*sum[1]); 615 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 616 } else { 617 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 618 } 619 } 620 PetscFunctionReturn(0); 621 } 622 623 /* 624 Creates the hash table, and sets the table 625 This table is created only once. 626 If new entried need to be added to the matrix 627 then the hash table has to be destroyed and 628 recreated. 629 */ 630 #undef __FUNCT__ 631 #define __FUNCT__ "MatCreateHashTable_MPISBAIJ_Private" 632 int MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 633 { 634 PetscFunctionBegin; 635 SETERRQ(1,"Function not yet written for SBAIJ format"); 636 /* PetscFunctionReturn(0); */ 637 } 638 639 #undef __FUNCT__ 640 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 641 int MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 642 { 643 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 644 int ierr,nstash,reallocs; 645 InsertMode addv; 646 647 PetscFunctionBegin; 648 if (baij->donotstash) { 649 PetscFunctionReturn(0); 650 } 651 652 /* make sure all processors are either in INSERTMODE or ADDMODE */ 653 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 654 if (addv == (ADD_VALUES|INSERT_VALUES)) { 655 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 656 } 657 mat->insertmode = addv; /* in case this processor had no cache */ 658 659 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 660 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 661 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 662 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 663 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 664 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 665 PetscFunctionReturn(0); 666 } 667 668 #undef __FUNCT__ 669 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 670 int MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 671 { 672 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 673 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 674 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 675 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 676 int *row,*col,other_disassembled; 677 PetscTruth r1,r2,r3; 678 MatScalar *val; 679 InsertMode addv = mat->insertmode; 680 681 PetscFunctionBegin; 682 683 if (!baij->donotstash) { 684 while (1) { 685 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 686 /* 687 PetscSynchronizedPrintf(mat->comm,"[%d]: in AssemblyEnd, stash, flg=%d\n",rank,flg); 688 PetscSynchronizedFlush(mat->comm); 689 */ 690 if (!flg) break; 691 692 for (i=0; i<n;) { 693 /* Now identify the consecutive vals belonging to the same row */ 694 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 695 if (j < n) ncols = j-i; 696 else ncols = n-i; 697 /* Now assemble all these values with a single function call */ 698 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 699 i = j; 700 } 701 } 702 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 703 /* Now process the block-stash. Since the values are stashed column-oriented, 704 set the roworiented flag to column oriented, and after MatSetValues() 705 restore the original flags */ 706 r1 = baij->roworiented; 707 r2 = a->roworiented; 708 r3 = b->roworiented; 709 baij->roworiented = PETSC_FALSE; 710 a->roworiented = PETSC_FALSE; 711 b->roworiented = PETSC_FALSE; 712 while (1) { 713 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 714 if (!flg) break; 715 716 for (i=0; i<n;) { 717 /* Now identify the consecutive vals belonging to the same row */ 718 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 719 if (j < n) ncols = j-i; 720 else ncols = n-i; 721 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 722 i = j; 723 } 724 } 725 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 726 baij->roworiented = r1; 727 a->roworiented = r2; 728 b->roworiented = r3; 729 } 730 731 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 732 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 733 734 /* determine if any processor has disassembled, if so we must 735 also disassemble ourselfs, in order that we may reassemble. */ 736 /* 737 if nonzero structure of submatrix B cannot change then we know that 738 no processor disassembled thus we can skip this stuff 739 */ 740 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 741 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 742 if (mat->was_assembled && !other_disassembled) { 743 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 744 } 745 } 746 747 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 748 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 749 } 750 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 751 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 752 753 #if defined(PETSC_USE_BOPT_g) 754 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 755 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 756 baij->ht_total_ct = 0; 757 baij->ht_insert_ct = 0; 758 } 759 #endif 760 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 761 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 762 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 763 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 764 } 765 766 if (baij->rowvalues) { 767 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 768 baij->rowvalues = 0; 769 } 770 771 PetscFunctionReturn(0); 772 } 773 774 #undef __FUNCT__ 775 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 776 static int MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 777 { 778 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 779 int ierr,bs = baij->bs,size = baij->size,rank = baij->rank; 780 PetscTruth isascii,isdraw; 781 PetscViewer sviewer; 782 PetscViewerFormat format; 783 784 PetscFunctionBegin; 785 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 786 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 787 if (isascii) { 788 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 789 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 790 MatInfo info; 791 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 792 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 793 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 794 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 795 baij->bs,(int)info.memory);CHKERRQ(ierr); 796 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 797 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 798 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 799 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 800 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 801 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 802 PetscFunctionReturn(0); 803 } else if (format == PETSC_VIEWER_ASCII_INFO) { 804 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 805 PetscFunctionReturn(0); 806 } 807 } 808 809 if (isdraw) { 810 PetscDraw draw; 811 PetscTruth isnull; 812 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 813 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 814 } 815 816 if (size == 1) { 817 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 818 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 819 } else { 820 /* assemble the entire matrix onto first processor. */ 821 Mat A; 822 Mat_SeqSBAIJ *Aloc; 823 Mat_SeqBAIJ *Bloc; 824 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 825 MatScalar *a; 826 827 /* Should this be the same type as mat? */ 828 if (!rank) { 829 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 830 } else { 831 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 832 } 833 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 834 ierr = MatMPISBAIJSetPreallocation(A,baij->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 835 PetscLogObjectParent(mat,A); 836 837 /* copy over the A part */ 838 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 839 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 840 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 841 842 for (i=0; i<mbs; i++) { 843 rvals[0] = bs*(baij->rstart + i); 844 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 845 for (j=ai[i]; j<ai[i+1]; j++) { 846 col = (baij->cstart+aj[j])*bs; 847 for (k=0; k<bs; k++) { 848 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 849 col++; a += bs; 850 } 851 } 852 } 853 /* copy over the B part */ 854 Bloc = (Mat_SeqBAIJ*)baij->B->data; 855 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 856 for (i=0; i<mbs; i++) { 857 rvals[0] = bs*(baij->rstart + i); 858 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 859 for (j=ai[i]; j<ai[i+1]; j++) { 860 col = baij->garray[aj[j]]*bs; 861 for (k=0; k<bs; k++) { 862 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 863 col++; a += bs; 864 } 865 } 866 } 867 ierr = PetscFree(rvals);CHKERRQ(ierr); 868 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 869 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 870 /* 871 Everyone has to call to draw the matrix since the graphics waits are 872 synchronized across all processors that share the PetscDraw object 873 */ 874 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 875 if (!rank) { 876 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 877 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 878 } 879 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 880 ierr = MatDestroy(A);CHKERRQ(ierr); 881 } 882 PetscFunctionReturn(0); 883 } 884 885 #undef __FUNCT__ 886 #define __FUNCT__ "MatView_MPISBAIJ" 887 int MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 888 { 889 int ierr; 890 PetscTruth isascii,isdraw,issocket,isbinary; 891 892 PetscFunctionBegin; 893 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 894 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 895 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 896 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 897 if (isascii || isdraw || issocket || isbinary) { 898 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 899 } else { 900 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 901 } 902 PetscFunctionReturn(0); 903 } 904 905 #undef __FUNCT__ 906 #define __FUNCT__ "MatDestroy_MPISBAIJ" 907 int MatDestroy_MPISBAIJ(Mat mat) 908 { 909 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 910 int ierr; 911 912 PetscFunctionBegin; 913 #if defined(PETSC_USE_LOG) 914 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 915 #endif 916 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 917 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 918 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 919 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 920 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 921 #if defined (PETSC_USE_CTABLE) 922 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 923 #else 924 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 925 #endif 926 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 927 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 928 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 929 if (baij->slvec0) { 930 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 931 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 932 } 933 if (baij->slvec1) { 934 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 935 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 936 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 937 } 938 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 939 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 940 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 941 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 942 #if defined(PETSC_USE_MAT_SINGLE) 943 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 944 #endif 945 ierr = PetscFree(baij);CHKERRQ(ierr); 946 PetscFunctionReturn(0); 947 } 948 949 #undef __FUNCT__ 950 #define __FUNCT__ "MatMult_MPISBAIJ" 951 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 952 { 953 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 954 int ierr,nt,mbs=a->mbs,bs=a->bs; 955 PetscScalar *x,*from,zero=0.0; 956 957 PetscFunctionBegin; 958 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 959 if (nt != A->n) { 960 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 961 } 962 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 963 if (nt != A->m) { 964 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 965 } 966 967 /* diagonal part */ 968 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 969 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 970 971 /* subdiagonal part */ 972 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 973 974 /* copy x into the vec slvec0 */ 975 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 976 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 977 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 978 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 979 980 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 981 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 982 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 983 984 /* supperdiagonal part */ 985 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 986 987 PetscFunctionReturn(0); 988 } 989 990 #undef __FUNCT__ 991 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 992 int MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 993 { 994 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 995 int ierr,nt; 996 997 PetscFunctionBegin; 998 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 999 if (nt != A->n) { 1000 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1001 } 1002 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1003 if (nt != A->m) { 1004 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1005 } 1006 1007 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1008 /* do diagonal part */ 1009 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1010 /* do supperdiagonal part */ 1011 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1012 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1013 /* do subdiagonal part */ 1014 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1015 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1016 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1017 1018 PetscFunctionReturn(0); 1019 } 1020 1021 #undef __FUNCT__ 1022 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 1023 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1024 { 1025 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1026 int ierr,mbs=a->mbs,bs=a->bs; 1027 PetscScalar *x,*from,zero=0.0; 1028 1029 PetscFunctionBegin; 1030 /* 1031 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 1032 PetscSynchronizedFlush(A->comm); 1033 */ 1034 /* diagonal part */ 1035 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 1036 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 1037 1038 /* subdiagonal part */ 1039 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 1040 1041 /* copy x into the vec slvec0 */ 1042 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 1043 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1044 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1045 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1046 1047 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1048 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1049 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1050 1051 /* supperdiagonal part */ 1052 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 1053 1054 PetscFunctionReturn(0); 1055 } 1056 1057 #undef __FUNCT__ 1058 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 1059 int MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 1060 { 1061 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1062 int ierr; 1063 1064 PetscFunctionBegin; 1065 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1066 /* do diagonal part */ 1067 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1068 /* do supperdiagonal part */ 1069 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1070 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1071 1072 /* do subdiagonal part */ 1073 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1074 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1075 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1076 1077 PetscFunctionReturn(0); 1078 } 1079 1080 #undef __FUNCT__ 1081 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1082 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1083 { 1084 int ierr; 1085 1086 PetscFunctionBegin; 1087 ierr = MatMult(A,xx,yy);CHKERRQ(ierr); 1088 PetscFunctionReturn(0); 1089 } 1090 1091 #undef __FUNCT__ 1092 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1093 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1094 { 1095 int ierr; 1096 1097 PetscFunctionBegin; 1098 ierr = MatMultAdd(A,xx,yy,zz);CHKERRQ(ierr); 1099 PetscFunctionReturn(0); 1100 } 1101 1102 /* 1103 This only works correctly for square matrices where the subblock A->A is the 1104 diagonal block 1105 */ 1106 #undef __FUNCT__ 1107 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1108 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1109 { 1110 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1111 int ierr; 1112 1113 PetscFunctionBegin; 1114 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1115 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 #undef __FUNCT__ 1120 #define __FUNCT__ "MatScale_MPISBAIJ" 1121 int MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1122 { 1123 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1124 int ierr; 1125 1126 PetscFunctionBegin; 1127 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1128 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1129 PetscFunctionReturn(0); 1130 } 1131 1132 #undef __FUNCT__ 1133 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1134 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 1135 { 1136 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1137 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1138 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 1139 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1140 int *cmap,*idx_p,cstart = mat->cstart; 1141 1142 PetscFunctionBegin; 1143 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1144 mat->getrowactive = PETSC_TRUE; 1145 1146 if (!mat->rowvalues && (idx || v)) { 1147 /* 1148 allocate enough space to hold information from the longest row. 1149 */ 1150 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1151 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1152 int max = 1,mbs = mat->mbs,tmp; 1153 for (i=0; i<mbs; i++) { 1154 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1155 if (max < tmp) { max = tmp; } 1156 } 1157 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1158 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 1159 } 1160 1161 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1162 lrow = row - brstart; /* local row index */ 1163 1164 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1165 if (!v) {pvA = 0; pvB = 0;} 1166 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1167 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1168 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1169 nztot = nzA + nzB; 1170 1171 cmap = mat->garray; 1172 if (v || idx) { 1173 if (nztot) { 1174 /* Sort by increasing column numbers, assuming A and B already sorted */ 1175 int imark = -1; 1176 if (v) { 1177 *v = v_p = mat->rowvalues; 1178 for (i=0; i<nzB; i++) { 1179 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1180 else break; 1181 } 1182 imark = i; 1183 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1184 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1185 } 1186 if (idx) { 1187 *idx = idx_p = mat->rowindices; 1188 if (imark > -1) { 1189 for (i=0; i<imark; i++) { 1190 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1191 } 1192 } else { 1193 for (i=0; i<nzB; i++) { 1194 if (cmap[cworkB[i]/bs] < cstart) 1195 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1196 else break; 1197 } 1198 imark = i; 1199 } 1200 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1201 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1202 } 1203 } else { 1204 if (idx) *idx = 0; 1205 if (v) *v = 0; 1206 } 1207 } 1208 *nz = nztot; 1209 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1210 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1211 PetscFunctionReturn(0); 1212 } 1213 1214 #undef __FUNCT__ 1215 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1216 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1217 { 1218 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1219 1220 PetscFunctionBegin; 1221 if (baij->getrowactive == PETSC_FALSE) { 1222 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1223 } 1224 baij->getrowactive = PETSC_FALSE; 1225 PetscFunctionReturn(0); 1226 } 1227 1228 #undef __FUNCT__ 1229 #define __FUNCT__ "MatGetBlockSize_MPISBAIJ" 1230 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1231 { 1232 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1233 1234 PetscFunctionBegin; 1235 *bs = baij->bs; 1236 PetscFunctionReturn(0); 1237 } 1238 1239 #undef __FUNCT__ 1240 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1241 int MatZeroEntries_MPISBAIJ(Mat A) 1242 { 1243 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1244 int ierr; 1245 1246 PetscFunctionBegin; 1247 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1248 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1249 PetscFunctionReturn(0); 1250 } 1251 1252 #undef __FUNCT__ 1253 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1254 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1255 { 1256 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1257 Mat A = a->A,B = a->B; 1258 int ierr; 1259 PetscReal isend[5],irecv[5]; 1260 1261 PetscFunctionBegin; 1262 info->block_size = (PetscReal)a->bs; 1263 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1264 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1265 isend[3] = info->memory; isend[4] = info->mallocs; 1266 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1267 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1268 isend[3] += info->memory; isend[4] += info->mallocs; 1269 if (flag == MAT_LOCAL) { 1270 info->nz_used = isend[0]; 1271 info->nz_allocated = isend[1]; 1272 info->nz_unneeded = isend[2]; 1273 info->memory = isend[3]; 1274 info->mallocs = isend[4]; 1275 } else if (flag == MAT_GLOBAL_MAX) { 1276 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1277 info->nz_used = irecv[0]; 1278 info->nz_allocated = irecv[1]; 1279 info->nz_unneeded = irecv[2]; 1280 info->memory = irecv[3]; 1281 info->mallocs = irecv[4]; 1282 } else if (flag == MAT_GLOBAL_SUM) { 1283 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1284 info->nz_used = irecv[0]; 1285 info->nz_allocated = irecv[1]; 1286 info->nz_unneeded = irecv[2]; 1287 info->memory = irecv[3]; 1288 info->mallocs = irecv[4]; 1289 } else { 1290 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1291 } 1292 info->rows_global = (PetscReal)A->M; 1293 info->columns_global = (PetscReal)A->N; 1294 info->rows_local = (PetscReal)A->m; 1295 info->columns_local = (PetscReal)A->N; 1296 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1297 info->fill_ratio_needed = 0; 1298 info->factor_mallocs = 0; 1299 PetscFunctionReturn(0); 1300 } 1301 1302 #undef __FUNCT__ 1303 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1304 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1305 { 1306 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1307 int ierr; 1308 1309 PetscFunctionBegin; 1310 switch (op) { 1311 case MAT_NO_NEW_NONZERO_LOCATIONS: 1312 case MAT_YES_NEW_NONZERO_LOCATIONS: 1313 case MAT_COLUMNS_UNSORTED: 1314 case MAT_COLUMNS_SORTED: 1315 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1316 case MAT_KEEP_ZEROED_ROWS: 1317 case MAT_NEW_NONZERO_LOCATION_ERR: 1318 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1319 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1320 break; 1321 case MAT_ROW_ORIENTED: 1322 a->roworiented = PETSC_TRUE; 1323 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1324 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1325 break; 1326 case MAT_ROWS_SORTED: 1327 case MAT_ROWS_UNSORTED: 1328 case MAT_YES_NEW_DIAGONALS: 1329 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1330 break; 1331 case MAT_COLUMN_ORIENTED: 1332 a->roworiented = PETSC_FALSE; 1333 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1334 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1335 break; 1336 case MAT_IGNORE_OFF_PROC_ENTRIES: 1337 a->donotstash = PETSC_TRUE; 1338 break; 1339 case MAT_NO_NEW_DIAGONALS: 1340 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1341 case MAT_USE_HASH_TABLE: 1342 a->ht_flag = PETSC_TRUE; 1343 break; 1344 case MAT_NOT_SYMMETRIC: 1345 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1346 case MAT_HERMITIAN: 1347 SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1348 case MAT_SYMMETRIC: 1349 case MAT_STRUCTURALLY_SYMMETRIC: 1350 case MAT_NOT_HERMITIAN: 1351 case MAT_SYMMETRY_ETERNAL: 1352 case MAT_NOT_SYMMETRY_ETERNAL: 1353 break; 1354 default: 1355 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1356 } 1357 PetscFunctionReturn(0); 1358 } 1359 1360 #undef __FUNCT__ 1361 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1362 int MatTranspose_MPISBAIJ(Mat A,Mat *B) 1363 { 1364 int ierr; 1365 PetscFunctionBegin; 1366 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1367 PetscFunctionReturn(0); 1368 } 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1372 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1373 { 1374 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1375 Mat a = baij->A,b = baij->B; 1376 int ierr,s1,s2,s3; 1377 1378 PetscFunctionBegin; 1379 if (ll != rr) { 1380 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1381 } 1382 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1383 if (rr) { 1384 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1385 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1386 /* Overlap communication with computation. */ 1387 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1388 /*} if (ll) { */ 1389 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1390 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1391 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1392 /* } */ 1393 /* scale the diagonal block */ 1394 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1395 1396 /* if (rr) { */ 1397 /* Do a scatter end and then right scale the off-diagonal block */ 1398 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1399 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1400 } 1401 1402 PetscFunctionReturn(0); 1403 } 1404 1405 #undef __FUNCT__ 1406 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1407 int MatZeroRows_MPISBAIJ(Mat A,IS is,const PetscScalar *diag) 1408 { 1409 PetscFunctionBegin; 1410 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1411 } 1412 1413 #undef __FUNCT__ 1414 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1415 int MatPrintHelp_MPISBAIJ(Mat A) 1416 { 1417 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1418 MPI_Comm comm = A->comm; 1419 static int called = 0; 1420 int ierr; 1421 1422 PetscFunctionBegin; 1423 if (!a->rank) { 1424 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1425 } 1426 if (called) {PetscFunctionReturn(0);} else called = 1; 1427 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1428 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1429 PetscFunctionReturn(0); 1430 } 1431 1432 #undef __FUNCT__ 1433 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1434 int MatSetUnfactored_MPISBAIJ(Mat A) 1435 { 1436 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1437 int ierr; 1438 1439 PetscFunctionBegin; 1440 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1441 PetscFunctionReturn(0); 1442 } 1443 1444 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1445 1446 #undef __FUNCT__ 1447 #define __FUNCT__ "MatEqual_MPISBAIJ" 1448 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1449 { 1450 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1451 Mat a,b,c,d; 1452 PetscTruth flg; 1453 int ierr; 1454 1455 PetscFunctionBegin; 1456 a = matA->A; b = matA->B; 1457 c = matB->A; d = matB->B; 1458 1459 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1460 if (flg == PETSC_TRUE) { 1461 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1462 } 1463 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1464 PetscFunctionReturn(0); 1465 } 1466 1467 #undef __FUNCT__ 1468 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1469 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1470 { 1471 int ierr; 1472 1473 PetscFunctionBegin; 1474 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1475 PetscFunctionReturn(0); 1476 } 1477 1478 #undef __FUNCT__ 1479 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1480 int MatGetSubMatrices_MPISBAIJ(Mat A,int n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1481 { 1482 int i,ierr; 1483 PetscTruth flg; 1484 1485 for (i=0; i<n; i++) { 1486 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1487 if (!flg) { 1488 SETERRQ(1,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1489 } 1490 } 1491 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1492 PetscFunctionReturn(0); 1493 } 1494 1495 1496 /* -------------------------------------------------------------------*/ 1497 static struct _MatOps MatOps_Values = { 1498 MatSetValues_MPISBAIJ, 1499 MatGetRow_MPISBAIJ, 1500 MatRestoreRow_MPISBAIJ, 1501 MatMult_MPISBAIJ, 1502 /* 4*/ MatMultAdd_MPISBAIJ, 1503 MatMultTranspose_MPISBAIJ, 1504 MatMultTransposeAdd_MPISBAIJ, 1505 0, 1506 0, 1507 0, 1508 /*10*/ 0, 1509 0, 1510 0, 1511 MatRelax_MPISBAIJ, 1512 MatTranspose_MPISBAIJ, 1513 /*15*/ MatGetInfo_MPISBAIJ, 1514 MatEqual_MPISBAIJ, 1515 MatGetDiagonal_MPISBAIJ, 1516 MatDiagonalScale_MPISBAIJ, 1517 MatNorm_MPISBAIJ, 1518 /*20*/ MatAssemblyBegin_MPISBAIJ, 1519 MatAssemblyEnd_MPISBAIJ, 1520 0, 1521 MatSetOption_MPISBAIJ, 1522 MatZeroEntries_MPISBAIJ, 1523 /*25*/ MatZeroRows_MPISBAIJ, 1524 0, 1525 0, 1526 0, 1527 0, 1528 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1529 0, 1530 0, 1531 0, 1532 0, 1533 /*35*/ MatDuplicate_MPISBAIJ, 1534 0, 1535 0, 1536 0, 1537 0, 1538 /*40*/ 0, 1539 MatGetSubMatrices_MPISBAIJ, 1540 MatIncreaseOverlap_MPISBAIJ, 1541 MatGetValues_MPISBAIJ, 1542 0, 1543 /*45*/ MatPrintHelp_MPISBAIJ, 1544 MatScale_MPISBAIJ, 1545 0, 1546 0, 1547 0, 1548 /*50*/ MatGetBlockSize_MPISBAIJ, 1549 0, 1550 0, 1551 0, 1552 0, 1553 /*55*/ 0, 1554 0, 1555 MatSetUnfactored_MPISBAIJ, 1556 0, 1557 MatSetValuesBlocked_MPISBAIJ, 1558 /*60*/ 0, 1559 0, 1560 0, 1561 MatGetPetscMaps_Petsc, 1562 0, 1563 /*65*/ 0, 1564 0, 1565 0, 1566 0, 1567 0, 1568 /*70*/ MatGetRowMax_MPISBAIJ, 1569 0, 1570 0, 1571 0, 1572 0, 1573 /*75*/ 0, 1574 0, 1575 0, 1576 0, 1577 0, 1578 /*80*/ 0, 1579 0, 1580 0, 1581 0, 1582 /*85*/ MatLoad_MPISBAIJ 1583 }; 1584 1585 1586 EXTERN_C_BEGIN 1587 #undef __FUNCT__ 1588 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1589 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1590 { 1591 PetscFunctionBegin; 1592 *a = ((Mat_MPISBAIJ *)A->data)->A; 1593 *iscopy = PETSC_FALSE; 1594 PetscFunctionReturn(0); 1595 } 1596 EXTERN_C_END 1597 1598 EXTERN_C_BEGIN 1599 #undef __FUNCT__ 1600 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1601 int MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1602 { 1603 Mat_MPISBAIJ *b; 1604 int ierr,i,mbs,Mbs; 1605 1606 PetscFunctionBegin; 1607 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1608 1609 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1610 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1611 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1612 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1613 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1614 if (d_nnz) { 1615 for (i=0; i<B->m/bs; i++) { 1616 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]); 1617 } 1618 } 1619 if (o_nnz) { 1620 for (i=0; i<B->m/bs; i++) { 1621 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]); 1622 } 1623 } 1624 B->preallocated = PETSC_TRUE; 1625 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1626 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1627 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1628 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1629 1630 b = (Mat_MPISBAIJ*)B->data; 1631 mbs = B->m/bs; 1632 Mbs = B->M/bs; 1633 if (mbs*bs != B->m) { 1634 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1635 } 1636 1637 b->bs = bs; 1638 b->bs2 = bs*bs; 1639 b->mbs = mbs; 1640 b->nbs = mbs; 1641 b->Mbs = Mbs; 1642 b->Nbs = Mbs; 1643 1644 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1645 b->rowners[0] = 0; 1646 for (i=2; i<=b->size; i++) { 1647 b->rowners[i] += b->rowners[i-1]; 1648 } 1649 b->rstart = b->rowners[b->rank]; 1650 b->rend = b->rowners[b->rank+1]; 1651 b->cstart = b->rstart; 1652 b->cend = b->rend; 1653 for (i=0; i<=b->size; i++) { 1654 b->rowners_bs[i] = b->rowners[i]*bs; 1655 } 1656 b->rstart_bs = b-> rstart*bs; 1657 b->rend_bs = b->rend*bs; 1658 1659 b->cstart_bs = b->cstart*bs; 1660 b->cend_bs = b->cend*bs; 1661 1662 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->m,B->m,B->m,&b->A);CHKERRQ(ierr); 1663 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1664 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1665 PetscLogObjectParent(B,b->A); 1666 1667 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->M,B->m,B->M,&b->B);CHKERRQ(ierr); 1668 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1669 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1670 PetscLogObjectParent(B,b->B); 1671 1672 /* build cache for off array entries formed */ 1673 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1674 1675 PetscFunctionReturn(0); 1676 } 1677 EXTERN_C_END 1678 1679 /*MC 1680 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1681 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1682 1683 Options Database Keys: 1684 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1685 1686 Level: beginner 1687 1688 .seealso: MatCreateMPISBAIJ 1689 M*/ 1690 1691 EXTERN_C_BEGIN 1692 #undef __FUNCT__ 1693 #define __FUNCT__ "MatCreate_MPISBAIJ" 1694 int MatCreate_MPISBAIJ(Mat B) 1695 { 1696 Mat_MPISBAIJ *b; 1697 int ierr; 1698 PetscTruth flg; 1699 1700 PetscFunctionBegin; 1701 1702 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1703 B->data = (void*)b; 1704 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1705 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1706 1707 B->ops->destroy = MatDestroy_MPISBAIJ; 1708 B->ops->view = MatView_MPISBAIJ; 1709 B->mapping = 0; 1710 B->factor = 0; 1711 B->assembled = PETSC_FALSE; 1712 1713 B->insertmode = NOT_SET_VALUES; 1714 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1715 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1716 1717 /* build local table of row and column ownerships */ 1718 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1719 b->cowners = b->rowners + b->size + 2; 1720 b->rowners_bs = b->cowners + b->size + 2; 1721 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1722 1723 /* build cache for off array entries formed */ 1724 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1725 b->donotstash = PETSC_FALSE; 1726 b->colmap = PETSC_NULL; 1727 b->garray = PETSC_NULL; 1728 b->roworiented = PETSC_TRUE; 1729 1730 #if defined(PETSC_USE_MAT_SINGLE) 1731 /* stuff for MatSetValues_XXX in single precision */ 1732 b->setvalueslen = 0; 1733 b->setvaluescopy = PETSC_NULL; 1734 #endif 1735 1736 /* stuff used in block assembly */ 1737 b->barray = 0; 1738 1739 /* stuff used for matrix vector multiply */ 1740 b->lvec = 0; 1741 b->Mvctx = 0; 1742 b->slvec0 = 0; 1743 b->slvec0b = 0; 1744 b->slvec1 = 0; 1745 b->slvec1a = 0; 1746 b->slvec1b = 0; 1747 b->sMvctx = 0; 1748 1749 /* stuff for MatGetRow() */ 1750 b->rowindices = 0; 1751 b->rowvalues = 0; 1752 b->getrowactive = PETSC_FALSE; 1753 1754 /* hash table stuff */ 1755 b->ht = 0; 1756 b->hd = 0; 1757 b->ht_size = 0; 1758 b->ht_flag = PETSC_FALSE; 1759 b->ht_fact = 0; 1760 b->ht_total_ct = 0; 1761 b->ht_insert_ct = 0; 1762 1763 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1764 if (flg) { 1765 PetscReal fact = 1.39; 1766 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1767 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1768 if (fact <= 1.0) fact = 1.39; 1769 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1770 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1771 } 1772 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1773 "MatStoreValues_MPISBAIJ", 1774 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1775 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1776 "MatRetrieveValues_MPISBAIJ", 1777 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1778 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1779 "MatGetDiagonalBlock_MPISBAIJ", 1780 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1781 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1782 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1783 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1784 PetscFunctionReturn(0); 1785 } 1786 EXTERN_C_END 1787 1788 /*MC 1789 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1790 1791 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1792 and MATMPISBAIJ otherwise. 1793 1794 Options Database Keys: 1795 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1796 1797 Level: beginner 1798 1799 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1800 M*/ 1801 1802 EXTERN_C_BEGIN 1803 #undef __FUNCT__ 1804 #define __FUNCT__ "MatCreate_SBAIJ" 1805 int MatCreate_SBAIJ(Mat A) { 1806 int ierr,size; 1807 1808 PetscFunctionBegin; 1809 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1810 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1811 if (size == 1) { 1812 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1813 } else { 1814 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1815 } 1816 PetscFunctionReturn(0); 1817 } 1818 EXTERN_C_END 1819 1820 #undef __FUNCT__ 1821 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1822 /*@C 1823 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1824 the user should preallocate the matrix storage by setting the parameters 1825 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1826 performance can be increased by more than a factor of 50. 1827 1828 Collective on Mat 1829 1830 Input Parameters: 1831 + A - the matrix 1832 . bs - size of blockk 1833 . d_nz - number of block nonzeros per block row in diagonal portion of local 1834 submatrix (same for all local rows) 1835 . d_nnz - array containing the number of block nonzeros in the various block rows 1836 in the upper triangular and diagonal part of the in diagonal portion of the local 1837 (possibly different for each block row) or PETSC_NULL. You must leave room 1838 for the diagonal entry even if it is zero. 1839 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1840 submatrix (same for all local rows). 1841 - o_nnz - array containing the number of nonzeros in the various block rows of the 1842 off-diagonal portion of the local submatrix (possibly different for 1843 each block row) or PETSC_NULL. 1844 1845 1846 Options Database Keys: 1847 . -mat_no_unroll - uses code that does not unroll the loops in the 1848 block calculations (much slower) 1849 . -mat_block_size - size of the blocks to use 1850 1851 Notes: 1852 1853 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1854 than it must be used on all processors that share the object for that argument. 1855 1856 Storage Information: 1857 For a square global matrix we define each processor's diagonal portion 1858 to be its local rows and the corresponding columns (a square submatrix); 1859 each processor's off-diagonal portion encompasses the remainder of the 1860 local matrix (a rectangular submatrix). 1861 1862 The user can specify preallocated storage for the diagonal part of 1863 the local submatrix with either d_nz or d_nnz (not both). Set 1864 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1865 memory allocation. Likewise, specify preallocated storage for the 1866 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1867 1868 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1869 the figure below we depict these three local rows and all columns (0-11). 1870 1871 .vb 1872 0 1 2 3 4 5 6 7 8 9 10 11 1873 ------------------- 1874 row 3 | o o o d d d o o o o o o 1875 row 4 | o o o d d d o o o o o o 1876 row 5 | o o o d d d o o o o o o 1877 ------------------- 1878 .ve 1879 1880 Thus, any entries in the d locations are stored in the d (diagonal) 1881 submatrix, and any entries in the o locations are stored in the 1882 o (off-diagonal) submatrix. Note that the d matrix is stored in 1883 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1884 1885 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1886 plus the diagonal part of the d matrix, 1887 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1888 In general, for PDE problems in which most nonzeros are near the diagonal, 1889 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1890 or you will get TERRIBLE performance; see the users' manual chapter on 1891 matrices. 1892 1893 Level: intermediate 1894 1895 .keywords: matrix, block, aij, compressed row, sparse, parallel 1896 1897 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1898 @*/ 1899 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,const int d_nnz[],int o_nz,const int o_nnz[]) 1900 { 1901 int ierr,(*f)(Mat,int,int,const int[],int,const int[]); 1902 1903 PetscFunctionBegin; 1904 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1905 if (f) { 1906 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1907 } 1908 PetscFunctionReturn(0); 1909 } 1910 1911 #undef __FUNCT__ 1912 #define __FUNCT__ "MatCreateMPISBAIJ" 1913 /*@C 1914 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1915 (block compressed row). For good matrix assembly performance 1916 the user should preallocate the matrix storage by setting the parameters 1917 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1918 performance can be increased by more than a factor of 50. 1919 1920 Collective on MPI_Comm 1921 1922 Input Parameters: 1923 + comm - MPI communicator 1924 . bs - size of blockk 1925 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1926 This value should be the same as the local size used in creating the 1927 y vector for the matrix-vector product y = Ax. 1928 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1929 This value should be the same as the local size used in creating the 1930 x vector for the matrix-vector product y = Ax. 1931 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1932 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1933 . d_nz - number of block nonzeros per block row in diagonal portion of local 1934 submatrix (same for all local rows) 1935 . d_nnz - array containing the number of block nonzeros in the various block rows 1936 in the upper triangular portion of the in diagonal portion of the local 1937 (possibly different for each block block row) or PETSC_NULL. 1938 You must leave room for the diagonal entry even if it is zero. 1939 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1940 submatrix (same for all local rows). 1941 - o_nnz - array containing the number of nonzeros in the various block rows of the 1942 off-diagonal portion of the local submatrix (possibly different for 1943 each block row) or PETSC_NULL. 1944 1945 Output Parameter: 1946 . A - the matrix 1947 1948 Options Database Keys: 1949 . -mat_no_unroll - uses code that does not unroll the loops in the 1950 block calculations (much slower) 1951 . -mat_block_size - size of the blocks to use 1952 . -mat_mpi - use the parallel matrix data structures even on one processor 1953 (defaults to using SeqBAIJ format on one processor) 1954 1955 Notes: 1956 The user MUST specify either the local or global matrix dimensions 1957 (possibly both). 1958 1959 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1960 than it must be used on all processors that share the object for that argument. 1961 1962 Storage Information: 1963 For a square global matrix we define each processor's diagonal portion 1964 to be its local rows and the corresponding columns (a square submatrix); 1965 each processor's off-diagonal portion encompasses the remainder of the 1966 local matrix (a rectangular submatrix). 1967 1968 The user can specify preallocated storage for the diagonal part of 1969 the local submatrix with either d_nz or d_nnz (not both). Set 1970 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1971 memory allocation. Likewise, specify preallocated storage for the 1972 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1973 1974 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1975 the figure below we depict these three local rows and all columns (0-11). 1976 1977 .vb 1978 0 1 2 3 4 5 6 7 8 9 10 11 1979 ------------------- 1980 row 3 | o o o d d d o o o o o o 1981 row 4 | o o o d d d o o o o o o 1982 row 5 | o o o d d d o o o o o o 1983 ------------------- 1984 .ve 1985 1986 Thus, any entries in the d locations are stored in the d (diagonal) 1987 submatrix, and any entries in the o locations are stored in the 1988 o (off-diagonal) submatrix. Note that the d matrix is stored in 1989 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1990 1991 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1992 plus the diagonal part of the d matrix, 1993 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1994 In general, for PDE problems in which most nonzeros are near the diagonal, 1995 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1996 or you will get TERRIBLE performance; see the users' manual chapter on 1997 matrices. 1998 1999 Level: intermediate 2000 2001 .keywords: matrix, block, aij, compressed row, sparse, parallel 2002 2003 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2004 @*/ 2005 2006 int MatCreateMPISBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N,int d_nz,const int d_nnz[],int o_nz,const int o_nnz[],Mat *A) 2007 { 2008 int ierr,size; 2009 2010 PetscFunctionBegin; 2011 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2012 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2013 if (size > 1) { 2014 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 2015 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2016 } else { 2017 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2018 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2019 } 2020 PetscFunctionReturn(0); 2021 } 2022 2023 2024 #undef __FUNCT__ 2025 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2026 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2027 { 2028 Mat mat; 2029 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2030 int ierr,len=0,nt,bs=oldmat->bs,mbs=oldmat->mbs; 2031 PetscScalar *array; 2032 2033 PetscFunctionBegin; 2034 *newmat = 0; 2035 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2036 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2037 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2038 mat->factor = matin->factor; 2039 mat->preallocated = PETSC_TRUE; 2040 mat->assembled = PETSC_TRUE; 2041 mat->insertmode = NOT_SET_VALUES; 2042 2043 a = (Mat_MPISBAIJ*)mat->data; 2044 a->bs = oldmat->bs; 2045 a->bs2 = oldmat->bs2; 2046 a->mbs = oldmat->mbs; 2047 a->nbs = oldmat->nbs; 2048 a->Mbs = oldmat->Mbs; 2049 a->Nbs = oldmat->Nbs; 2050 2051 a->rstart = oldmat->rstart; 2052 a->rend = oldmat->rend; 2053 a->cstart = oldmat->cstart; 2054 a->cend = oldmat->cend; 2055 a->size = oldmat->size; 2056 a->rank = oldmat->rank; 2057 a->donotstash = oldmat->donotstash; 2058 a->roworiented = oldmat->roworiented; 2059 a->rowindices = 0; 2060 a->rowvalues = 0; 2061 a->getrowactive = PETSC_FALSE; 2062 a->barray = 0; 2063 a->rstart_bs = oldmat->rstart_bs; 2064 a->rend_bs = oldmat->rend_bs; 2065 a->cstart_bs = oldmat->cstart_bs; 2066 a->cend_bs = oldmat->cend_bs; 2067 2068 /* hash table stuff */ 2069 a->ht = 0; 2070 a->hd = 0; 2071 a->ht_size = 0; 2072 a->ht_flag = oldmat->ht_flag; 2073 a->ht_fact = oldmat->ht_fact; 2074 a->ht_total_ct = 0; 2075 a->ht_insert_ct = 0; 2076 2077 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 2078 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2079 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 2080 if (oldmat->colmap) { 2081 #if defined (PETSC_USE_CTABLE) 2082 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2083 #else 2084 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 2085 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2086 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 2087 #endif 2088 } else a->colmap = 0; 2089 2090 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2091 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2092 PetscLogObjectMemory(mat,len*sizeof(int)); 2093 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2094 } else a->garray = 0; 2095 2096 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2097 PetscLogObjectParent(mat,a->lvec); 2098 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2099 PetscLogObjectParent(mat,a->Mvctx); 2100 2101 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2102 PetscLogObjectParent(mat,a->slvec0); 2103 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2104 PetscLogObjectParent(mat,a->slvec1); 2105 2106 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2107 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2108 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2109 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2110 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2111 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2112 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2113 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2114 PetscLogObjectParent(mat,a->slvec0); 2115 PetscLogObjectParent(mat,a->slvec1); 2116 PetscLogObjectParent(mat,a->slvec0b); 2117 PetscLogObjectParent(mat,a->slvec1a); 2118 PetscLogObjectParent(mat,a->slvec1b); 2119 2120 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2121 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2122 a->sMvctx = oldmat->sMvctx; 2123 PetscLogObjectParent(mat,a->sMvctx); 2124 2125 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2126 PetscLogObjectParent(mat,a->A); 2127 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2128 PetscLogObjectParent(mat,a->B); 2129 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2130 *newmat = mat; 2131 PetscFunctionReturn(0); 2132 } 2133 2134 #include "petscsys.h" 2135 2136 #undef __FUNCT__ 2137 #define __FUNCT__ "MatLoad_MPISBAIJ" 2138 int MatLoad_MPISBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2139 { 2140 Mat A; 2141 int i,nz,ierr,j,rstart,rend,fd; 2142 PetscScalar *vals,*buf; 2143 MPI_Comm comm = ((PetscObject)viewer)->comm; 2144 MPI_Status status; 2145 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2146 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2147 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2148 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2149 int dcount,kmax,k,nzcount,tmp; 2150 2151 PetscFunctionBegin; 2152 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2153 2154 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2155 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2156 if (!rank) { 2157 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2158 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2159 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2160 if (header[3] < 0) { 2161 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2162 } 2163 } 2164 2165 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2166 M = header[1]; N = header[2]; 2167 2168 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2169 2170 /* 2171 This code adds extra rows to make sure the number of rows is 2172 divisible by the blocksize 2173 */ 2174 Mbs = M/bs; 2175 extra_rows = bs - M + bs*(Mbs); 2176 if (extra_rows == bs) extra_rows = 0; 2177 else Mbs++; 2178 if (extra_rows &&!rank) { 2179 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2180 } 2181 2182 /* determine ownership of all rows */ 2183 mbs = Mbs/size + ((Mbs % size) > rank); 2184 m = mbs*bs; 2185 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2186 browners = rowners + size + 1; 2187 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2188 rowners[0] = 0; 2189 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2190 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2191 rstart = rowners[rank]; 2192 rend = rowners[rank+1]; 2193 2194 /* distribute row lengths to all processors */ 2195 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2196 if (!rank) { 2197 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2198 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2199 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2200 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2201 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2202 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2203 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2204 } else { 2205 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2206 } 2207 2208 if (!rank) { /* procs[0] */ 2209 /* calculate the number of nonzeros on each processor */ 2210 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2211 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2212 for (i=0; i<size; i++) { 2213 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2214 procsnz[i] += rowlengths[j]; 2215 } 2216 } 2217 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2218 2219 /* determine max buffer needed and allocate it */ 2220 maxnz = 0; 2221 for (i=0; i<size; i++) { 2222 maxnz = PetscMax(maxnz,procsnz[i]); 2223 } 2224 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2225 2226 /* read in my part of the matrix column indices */ 2227 nz = procsnz[0]; 2228 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2229 mycols = ibuf; 2230 if (size == 1) nz -= extra_rows; 2231 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2232 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2233 2234 /* read in every ones (except the last) and ship off */ 2235 for (i=1; i<size-1; i++) { 2236 nz = procsnz[i]; 2237 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2238 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2239 } 2240 /* read in the stuff for the last proc */ 2241 if (size != 1) { 2242 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2243 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2244 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2245 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2246 } 2247 ierr = PetscFree(cols);CHKERRQ(ierr); 2248 } else { /* procs[i], i>0 */ 2249 /* determine buffer space needed for message */ 2250 nz = 0; 2251 for (i=0; i<m; i++) { 2252 nz += locrowlens[i]; 2253 } 2254 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2255 mycols = ibuf; 2256 /* receive message of column indices*/ 2257 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2258 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2259 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2260 } 2261 2262 /* loop over local rows, determining number of off diagonal entries */ 2263 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2264 odlens = dlens + (rend-rstart); 2265 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2266 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2267 masked1 = mask + Mbs; 2268 masked2 = masked1 + Mbs; 2269 rowcount = 0; nzcount = 0; 2270 for (i=0; i<mbs; i++) { 2271 dcount = 0; 2272 odcount = 0; 2273 for (j=0; j<bs; j++) { 2274 kmax = locrowlens[rowcount]; 2275 for (k=0; k<kmax; k++) { 2276 tmp = mycols[nzcount++]/bs; /* block col. index */ 2277 if (!mask[tmp]) { 2278 mask[tmp] = 1; 2279 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2280 else masked1[dcount++] = tmp; /* entry in diag portion */ 2281 } 2282 } 2283 rowcount++; 2284 } 2285 2286 dlens[i] = dcount; /* d_nzz[i] */ 2287 odlens[i] = odcount; /* o_nzz[i] */ 2288 2289 /* zero out the mask elements we set */ 2290 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2291 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2292 } 2293 2294 /* create our matrix */ 2295 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2296 ierr = MatSetType(A,type);CHKERRQ(ierr); 2297 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2298 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2299 2300 if (!rank) { 2301 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2302 /* read in my part of the matrix numerical values */ 2303 nz = procsnz[0]; 2304 vals = buf; 2305 mycols = ibuf; 2306 if (size == 1) nz -= extra_rows; 2307 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2308 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2309 2310 /* insert into matrix */ 2311 jj = rstart*bs; 2312 for (i=0; i<m; i++) { 2313 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2314 mycols += locrowlens[i]; 2315 vals += locrowlens[i]; 2316 jj++; 2317 } 2318 2319 /* read in other processors (except the last one) and ship out */ 2320 for (i=1; i<size-1; i++) { 2321 nz = procsnz[i]; 2322 vals = buf; 2323 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2324 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2325 } 2326 /* the last proc */ 2327 if (size != 1){ 2328 nz = procsnz[i] - extra_rows; 2329 vals = buf; 2330 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2331 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2332 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2333 } 2334 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2335 2336 } else { 2337 /* receive numeric values */ 2338 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2339 2340 /* receive message of values*/ 2341 vals = buf; 2342 mycols = ibuf; 2343 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2344 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2345 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2346 2347 /* insert into matrix */ 2348 jj = rstart*bs; 2349 for (i=0; i<m; i++) { 2350 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2351 mycols += locrowlens[i]; 2352 vals += locrowlens[i]; 2353 jj++; 2354 } 2355 } 2356 2357 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2358 ierr = PetscFree(buf);CHKERRQ(ierr); 2359 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2360 ierr = PetscFree(rowners);CHKERRQ(ierr); 2361 ierr = PetscFree(dlens);CHKERRQ(ierr); 2362 ierr = PetscFree(mask);CHKERRQ(ierr); 2363 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2364 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2365 *newmat = A; 2366 PetscFunctionReturn(0); 2367 } 2368 2369 #undef __FUNCT__ 2370 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2371 /*@ 2372 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2373 2374 Input Parameters: 2375 . mat - the matrix 2376 . fact - factor 2377 2378 Collective on Mat 2379 2380 Level: advanced 2381 2382 Notes: 2383 This can also be set by the command line option: -mat_use_hash_table fact 2384 2385 .keywords: matrix, hashtable, factor, HT 2386 2387 .seealso: MatSetOption() 2388 @*/ 2389 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2390 { 2391 PetscFunctionBegin; 2392 SETERRQ(1,"Function not yet written for SBAIJ format"); 2393 /* PetscFunctionReturn(0); */ 2394 } 2395 2396 #undef __FUNCT__ 2397 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2398 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2399 { 2400 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2401 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2402 PetscReal atmp; 2403 PetscReal *work,*svalues,*rvalues; 2404 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2405 int rank,size,*rowners_bs,dest,count,source; 2406 PetscScalar *va; 2407 MatScalar *ba; 2408 MPI_Status stat; 2409 2410 PetscFunctionBegin; 2411 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2412 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2413 2414 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2415 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2416 2417 bs = a->bs; 2418 mbs = a->mbs; 2419 Mbs = a->Mbs; 2420 ba = b->a; 2421 bi = b->i; 2422 bj = b->j; 2423 /* 2424 PetscSynchronizedPrintf(A->comm,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2425 PetscSynchronizedFlush(A->comm); 2426 */ 2427 2428 /* find ownerships */ 2429 rowners_bs = a->rowners_bs; 2430 /* 2431 if (!rank){ 2432 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2433 } 2434 */ 2435 2436 /* each proc creates an array to be distributed */ 2437 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2438 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2439 2440 /* row_max for B */ 2441 if (rank != size-1){ 2442 for (i=0; i<mbs; i++) { 2443 ncols = bi[1] - bi[0]; bi++; 2444 brow = bs*i; 2445 for (j=0; j<ncols; j++){ 2446 bcol = bs*(*bj); 2447 for (kcol=0; kcol<bs; kcol++){ 2448 col = bcol + kcol; /* local col index */ 2449 col += rowners_bs[rank+1]; /* global col index */ 2450 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2451 for (krow=0; krow<bs; krow++){ 2452 atmp = PetscAbsScalar(*ba); ba++; 2453 row = brow + krow; /* local row index */ 2454 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2455 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2456 if (work[col] < atmp) work[col] = atmp; 2457 } 2458 } 2459 bj++; 2460 } 2461 } 2462 /* 2463 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2464 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2465 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2466 */ 2467 2468 /* send values to its owners */ 2469 for (dest=rank+1; dest<size; dest++){ 2470 svalues = work + rowners_bs[dest]; 2471 count = rowners_bs[dest+1]-rowners_bs[dest]; 2472 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2473 /* 2474 PetscSynchronizedPrintf(A->comm,"[%d] sends %d values to [%d]: %g, %g, %g, %g\n",rank,count,dest,svalues[0],svalues[1],svalues[2],svalues[3]); 2475 PetscSynchronizedFlush(A->comm); 2476 */ 2477 } 2478 } 2479 2480 /* receive values */ 2481 if (rank){ 2482 rvalues = work; 2483 count = rowners_bs[rank+1]-rowners_bs[rank]; 2484 for (source=0; source<rank; source++){ 2485 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2486 /* process values */ 2487 for (i=0; i<count; i++){ 2488 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2489 } 2490 /* 2491 PetscSynchronizedPrintf(A->comm,"[%d] received %d values from [%d]: %g, %g, %g, %g \n",rank,count,stat.MPI_SOURCE,rvalues[0],rvalues[1],rvalues[2],rvalues[3]); 2492 PetscSynchronizedFlush(A->comm); 2493 */ 2494 } 2495 } 2496 2497 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2498 ierr = PetscFree(work);CHKERRQ(ierr); 2499 PetscFunctionReturn(0); 2500 } 2501 2502 #undef __FUNCT__ 2503 #define __FUNCT__ "MatRelax_MPISBAIJ" 2504 int MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2505 { 2506 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2507 int ierr,mbs=mat->mbs,bs=mat->bs; 2508 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2509 Vec bb1; 2510 2511 PetscFunctionBegin; 2512 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2513 if (bs > 1) 2514 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2515 2516 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2517 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2518 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2519 its--; 2520 } 2521 2522 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2523 while (its--){ 2524 2525 /* lower triangular part: slvec0b = - B^T*xx */ 2526 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2527 2528 /* copy xx into slvec0a */ 2529 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2530 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2531 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2532 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2533 2534 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2535 2536 /* copy bb into slvec1a */ 2537 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2538 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2539 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2540 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2541 2542 /* set slvec1b = 0 */ 2543 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2544 2545 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2546 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2547 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2548 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2549 2550 /* upper triangular part: bb1 = bb1 - B*x */ 2551 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2552 2553 /* local diagonal sweep */ 2554 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2555 } 2556 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2557 } else { 2558 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2559 } 2560 PetscFunctionReturn(0); 2561 } 2562 2563 #undef __FUNCT__ 2564 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2565 int MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2566 { 2567 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2568 int ierr; 2569 PetscScalar mone=-1.0; 2570 Vec lvec1,bb1; 2571 2572 PetscFunctionBegin; 2573 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2574 if (mat->bs > 1) 2575 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2576 2577 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2578 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2579 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2580 its--; 2581 } 2582 2583 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2584 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2585 while (its--){ 2586 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2587 2588 /* lower diagonal part: bb1 = bb - B^T*xx */ 2589 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2590 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2591 2592 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2593 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2594 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2595 2596 /* upper diagonal part: bb1 = bb1 - B*x */ 2597 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2598 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2599 2600 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2601 2602 /* diagonal sweep */ 2603 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2604 } 2605 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2606 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2607 } else { 2608 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2609 } 2610 PetscFunctionReturn(0); 2611 } 2612 2613