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 "src/vec/vecimpl.h" 5 #include "mpisbaij.h" 6 #include "src/mat/impls/sbaij/seq/sbaij.h" 7 8 extern int MatSetUpMultiply_MPISBAIJ(Mat); 9 extern int MatSetUpMultiply_MPISBAIJ_2comm(Mat); 10 extern int DisAssemble_MPISBAIJ(Mat); 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 Local utility routine that creates a mapping from the global column 77 number to the local number in the off-diagonal part of the local 78 storage of the matrix. This is done in a non scable way since the 79 length of colmap equals the global matrix length. 80 */ 81 #undef __FUNCT__ 82 #define __FUNCT__ "CreateColmap_MPISBAIJ_Private" 83 static int CreateColmap_MPISBAIJ_Private(Mat mat) 84 { 85 PetscFunctionBegin; 86 SETERRQ(1,"Function not yet written for SBAIJ format"); 87 /* PetscFunctionReturn(0); */ 88 } 89 90 #define CHUNKSIZE 10 91 92 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 93 { \ 94 \ 95 brow = row/bs; \ 96 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 97 rmax = aimax[brow]; nrow = ailen[brow]; \ 98 bcol = col/bs; \ 99 ridx = row % bs; cidx = col % bs; \ 100 low = 0; high = nrow; \ 101 while (high-low > 3) { \ 102 t = (low+high)/2; \ 103 if (rp[t] > bcol) high = t; \ 104 else low = t; \ 105 } \ 106 for (_i=low; _i<high; _i++) { \ 107 if (rp[_i] > bcol) break; \ 108 if (rp[_i] == bcol) { \ 109 bap = ap + bs2*_i + bs*cidx + ridx; \ 110 if (addv == ADD_VALUES) *bap += value; \ 111 else *bap = value; \ 112 goto a_noinsert; \ 113 } \ 114 } \ 115 if (a->nonew == 1) goto a_noinsert; \ 116 else if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) into matrix", row, col); \ 117 if (nrow >= rmax) { \ 118 /* there is no extra room in row, therefore enlarge */ \ 119 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 120 MatScalar *new_a; \ 121 \ 122 if (a->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); \ 123 \ 124 /* malloc new storage space */ \ 125 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 126 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 127 new_j = (int*)(new_a + bs2*new_nz); \ 128 new_i = new_j + new_nz; \ 129 \ 130 /* copy over old data into new slots */ \ 131 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 132 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 133 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 134 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 135 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 136 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 137 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \ 138 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 139 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 140 /* free up old matrix storage */ \ 141 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 142 if (!a->singlemalloc) { \ 143 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 144 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 145 } \ 146 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 147 a->singlemalloc = PETSC_TRUE; \ 148 \ 149 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 150 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 151 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 152 a->s_maxnz += bs2*CHUNKSIZE; \ 153 a->reallocs++; \ 154 a->s_nz++; \ 155 } \ 156 N = nrow++ - 1; \ 157 /* shift up all the later entries in this row */ \ 158 for (ii=N; ii>=_i; ii--) { \ 159 rp[ii+1] = rp[ii]; \ 160 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 161 } \ 162 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 163 rp[_i] = bcol; \ 164 ap[bs2*_i + bs*cidx + ridx] = value; \ 165 a_noinsert:; \ 166 ailen[brow] = nrow; \ 167 } 168 #ifndef MatSetValues_SeqBAIJ_B_Private 169 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 170 { \ 171 brow = row/bs; \ 172 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 173 rmax = bimax[brow]; nrow = bilen[brow]; \ 174 bcol = col/bs; \ 175 ridx = row % bs; cidx = col % bs; \ 176 low = 0; high = nrow; \ 177 while (high-low > 3) { \ 178 t = (low+high)/2; \ 179 if (rp[t] > bcol) high = t; \ 180 else low = t; \ 181 } \ 182 for (_i=low; _i<high; _i++) { \ 183 if (rp[_i] > bcol) break; \ 184 if (rp[_i] == bcol) { \ 185 bap = ap + bs2*_i + bs*cidx + ridx; \ 186 if (addv == ADD_VALUES) *bap += value; \ 187 else *bap = value; \ 188 goto b_noinsert; \ 189 } \ 190 } \ 191 if (b->nonew == 1) goto b_noinsert; \ 192 else if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) into matrix", row, col); \ 193 if (nrow >= rmax) { \ 194 /* there is no extra room in row, therefore enlarge */ \ 195 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 196 MatScalar *new_a; \ 197 \ 198 if (b->nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); \ 199 \ 200 /* malloc new storage space */ \ 201 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 202 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 203 new_j = (int*)(new_a + bs2*new_nz); \ 204 new_i = new_j + new_nz; \ 205 \ 206 /* copy over old data into new slots */ \ 207 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 208 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 209 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 210 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 211 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 212 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 213 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 214 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 215 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 216 /* free up old matrix storage */ \ 217 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 218 if (!b->singlemalloc) { \ 219 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 220 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 221 } \ 222 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 223 b->singlemalloc = PETSC_TRUE; \ 224 \ 225 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 226 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 227 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 228 b->maxnz += bs2*CHUNKSIZE; \ 229 b->reallocs++; \ 230 b->nz++; \ 231 } \ 232 N = nrow++ - 1; \ 233 /* shift up all the later entries in this row */ \ 234 for (ii=N; ii>=_i; ii--) { \ 235 rp[ii+1] = rp[ii]; \ 236 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 237 } \ 238 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 239 rp[_i] = bcol; \ 240 ap[bs2*_i + bs*cidx + ridx] = value; \ 241 b_noinsert:; \ 242 bilen[brow] = nrow; \ 243 } 244 #endif 245 246 #if defined(PETSC_USE_MAT_SINGLE) 247 #undef __FUNCT__ 248 #define __FUNCT__ "MatSetValues_MPISBAIJ" 249 int MatSetValues_MPISBAIJ(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 250 { 251 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 252 int ierr,i,N = m*n; 253 MatScalar *vsingle; 254 255 PetscFunctionBegin; 256 if (N > b->setvalueslen) { 257 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 258 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 259 b->setvalueslen = N; 260 } 261 vsingle = b->setvaluescopy; 262 263 for (i=0; i<N; i++) { 264 vsingle[i] = v[i]; 265 } 266 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 267 PetscFunctionReturn(0); 268 } 269 270 #undef __FUNCT__ 271 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 272 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 273 { 274 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 275 int ierr,i,N = m*n*b->bs2; 276 MatScalar *vsingle; 277 278 PetscFunctionBegin; 279 if (N > b->setvalueslen) { 280 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 281 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 282 b->setvalueslen = N; 283 } 284 vsingle = b->setvaluescopy; 285 for (i=0; i<N; i++) { 286 vsingle[i] = v[i]; 287 } 288 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 289 PetscFunctionReturn(0); 290 } 291 292 #undef __FUNCT__ 293 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT" 294 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 295 { 296 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 297 int ierr,i,N = m*n; 298 MatScalar *vsingle; 299 300 PetscFunctionBegin; 301 SETERRQ(1,"Function not yet written for SBAIJ format"); 302 /* PetscFunctionReturn(0); */ 303 } 304 305 #undef __FUNCT__ 306 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT" 307 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv) 308 { 309 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 310 int ierr,i,N = m*n*b->bs2; 311 MatScalar *vsingle; 312 313 PetscFunctionBegin; 314 SETERRQ(1,"Function not yet written for SBAIJ format"); 315 /* PetscFunctionReturn(0); */ 316 } 317 #endif 318 319 /* Only add/insert a(i,j) with i<=j (blocks). 320 Any a(i,j) with i>j input by user is ingored. 321 */ 322 #undef __FUNCT__ 323 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 324 int MatSetValues_MPISBAIJ_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 325 { 326 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 327 MatScalar value; 328 PetscTruth roworiented = baij->roworiented; 329 int ierr,i,j,row,col; 330 int rstart_orig=baij->rstart_bs; 331 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 332 int cend_orig=baij->cend_bs,bs=baij->bs; 333 334 /* Some Variables required in the macro */ 335 Mat A = baij->A; 336 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 337 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 338 MatScalar *aa=a->a; 339 340 Mat B = baij->B; 341 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 342 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 343 MatScalar *ba=b->a; 344 345 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 346 int low,high,t,ridx,cidx,bs2=a->bs2; 347 MatScalar *ap,*bap; 348 349 /* for stash */ 350 int n_loc, *in_loc=0; 351 MatScalar *v_loc=0; 352 353 PetscFunctionBegin; 354 355 if(!baij->donotstash){ 356 ierr = PetscMalloc(n*sizeof(int),&in_loc);CHKERRQ(ierr); 357 ierr = PetscMalloc(n*sizeof(MatScalar),&v_loc);CHKERRQ(ierr); 358 } 359 360 for (i=0; i<m; i++) { 361 if (im[i] < 0) continue; 362 #if defined(PETSC_USE_BOPT_g) 363 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",im[i],mat->M-1); 364 #endif 365 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 366 row = im[i] - rstart_orig; /* local row index */ 367 for (j=0; j<n; j++) { 368 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 369 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 370 col = in[j] - cstart_orig; /* local col index */ 371 brow = row/bs; bcol = col/bs; 372 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 373 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 374 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 375 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 376 } else if (in[j] < 0) continue; 377 #if defined(PETSC_USE_BOPT_g) 378 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[j],mat->N-1);} 379 #endif 380 else { /* off-diag entry (B) */ 381 if (mat->was_assembled) { 382 if (!baij->colmap) { 383 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 384 } 385 #if defined (PETSC_USE_CTABLE) 386 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 387 col = col - 1; 388 #else 389 col = baij->colmap[in[j]/bs] - 1; 390 #endif 391 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 392 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 393 col = in[j]; 394 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 395 B = baij->B; 396 b = (Mat_SeqBAIJ*)(B)->data; 397 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 398 ba=b->a; 399 } else col += in[j]%bs; 400 } else col = in[j]; 401 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 402 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 403 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 404 } 405 } 406 } else { /* off processor entry */ 407 if (!baij->donotstash) { 408 n_loc = 0; 409 for (j=0; j<n; j++){ 410 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 411 in_loc[n_loc] = in[j]; 412 if (roworiented) { 413 v_loc[n_loc] = v[i*n+j]; 414 } else { 415 v_loc[n_loc] = v[j*m+i]; 416 } 417 n_loc++; 418 } 419 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 420 } 421 } 422 } 423 424 if(!baij->donotstash){ 425 ierr = PetscFree(in_loc);CHKERRQ(ierr); 426 ierr = PetscFree(v_loc);CHKERRQ(ierr); 427 } 428 PetscFunctionReturn(0); 429 } 430 431 #undef __FUNCT__ 432 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_MatScalar" 433 int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 434 { 435 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 436 const MatScalar *value; 437 MatScalar *barray=baij->barray; 438 PetscTruth roworiented = baij->roworiented; 439 int ierr,i,j,ii,jj,row,col,rstart=baij->rstart; 440 int rend=baij->rend,cstart=baij->cstart,stepval; 441 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 442 443 PetscFunctionBegin; 444 if(!barray) { 445 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 446 baij->barray = barray; 447 } 448 449 if (roworiented) { 450 stepval = (n-1)*bs; 451 } else { 452 stepval = (m-1)*bs; 453 } 454 for (i=0; i<m; i++) { 455 if (im[i] < 0) continue; 456 #if defined(PETSC_USE_BOPT_g) 457 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %d max %d",im[i],baij->Mbs-1); 458 #endif 459 if (im[i] >= rstart && im[i] < rend) { 460 row = im[i] - rstart; 461 for (j=0; j<n; j++) { 462 /* If NumCol = 1 then a copy is not required */ 463 if ((roworiented) && (n == 1)) { 464 barray = (MatScalar*) v + i*bs2; 465 } else if((!roworiented) && (m == 1)) { 466 barray = (MatScalar*) v + j*bs2; 467 } else { /* Here a copy is required */ 468 if (roworiented) { 469 value = v + i*(stepval+bs)*bs + j*bs; 470 } else { 471 value = v + j*(stepval+bs)*bs + i*bs; 472 } 473 for (ii=0; ii<bs; ii++,value+=stepval) { 474 for (jj=0; jj<bs; jj++) { 475 *barray++ = *value++; 476 } 477 } 478 barray -=bs2; 479 } 480 481 if (in[j] >= cstart && in[j] < cend){ 482 col = in[j] - cstart; 483 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 484 } 485 else if (in[j] < 0) continue; 486 #if defined(PETSC_USE_BOPT_g) 487 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %d max %d",in[j],baij->Nbs-1);} 488 #endif 489 else { 490 if (mat->was_assembled) { 491 if (!baij->colmap) { 492 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 493 } 494 495 #if defined(PETSC_USE_BOPT_g) 496 #if defined (PETSC_USE_CTABLE) 497 { int data; 498 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 499 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 500 } 501 #else 502 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 503 #endif 504 #endif 505 #if defined (PETSC_USE_CTABLE) 506 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 507 col = (col - 1)/bs; 508 #else 509 col = (baij->colmap[in[j]] - 1)/bs; 510 #endif 511 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 512 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 513 col = in[j]; 514 } 515 } 516 else col = in[j]; 517 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 518 } 519 } 520 } else { 521 if (!baij->donotstash) { 522 if (roworiented) { 523 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 524 } else { 525 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 526 } 527 } 528 } 529 } 530 PetscFunctionReturn(0); 531 } 532 533 #define HASH_KEY 0.6180339887 534 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 535 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 536 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 537 #undef __FUNCT__ 538 #define __FUNCT__ "MatSetValues_MPISBAIJ_HT_MatScalar" 539 int MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 540 { 541 PetscFunctionBegin; 542 SETERRQ(1,"Function not yet written for SBAIJ format"); 543 /* PetscFunctionReturn(0); */ 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 548 int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,int m,const int im[],int n,const int in[],const MatScalar v[],InsertMode addv) 549 { 550 PetscFunctionBegin; 551 SETERRQ(1,"Function not yet written for SBAIJ format"); 552 /* PetscFunctionReturn(0); */ 553 } 554 555 #undef __FUNCT__ 556 #define __FUNCT__ "MatGetValues_MPISBAIJ" 557 int MatGetValues_MPISBAIJ(Mat mat,int m,const int idxm[],int n,const int idxn[],PetscScalar v[]) 558 { 559 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 560 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 561 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 562 563 PetscFunctionBegin; 564 for (i=0; i<m; i++) { 565 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %d",idxm[i]); 566 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",idxm[i],mat->M-1); 567 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 568 row = idxm[i] - bsrstart; 569 for (j=0; j<n; j++) { 570 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %d",idxn[j]); 571 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",idxn[j],mat->N-1); 572 if (idxn[j] >= bscstart && idxn[j] < bscend){ 573 col = idxn[j] - bscstart; 574 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 575 } else { 576 if (!baij->colmap) { 577 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 578 } 579 #if defined (PETSC_USE_CTABLE) 580 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 581 data --; 582 #else 583 data = baij->colmap[idxn[j]/bs]-1; 584 #endif 585 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 586 else { 587 col = data + idxn[j]%bs; 588 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 589 } 590 } 591 } 592 } else { 593 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 594 } 595 } 596 PetscFunctionReturn(0); 597 } 598 599 #undef __FUNCT__ 600 #define __FUNCT__ "MatNorm_MPISBAIJ" 601 int MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 602 { 603 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 604 /* Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ*)baij->A->data; */ 605 /* Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ*)baij->B->data; */ 606 int ierr; 607 PetscReal sum[2],*lnorm2; 608 609 PetscFunctionBegin; 610 if (baij->size == 1) { 611 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 612 } else { 613 if (type == NORM_FROBENIUS) { 614 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 615 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 616 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 617 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 618 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 619 /* 620 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 621 PetscSynchronizedPrintf(mat->comm,"[%d], lnorm2=%g, %g\n",rank,lnorm2[0],lnorm2[1]); 622 */ 623 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 624 /* 625 PetscSynchronizedPrintf(mat->comm,"[%d], sum=%g, %g\n",rank,sum[0],sum[1]); 626 PetscSynchronizedFlush(mat->comm); */ 627 628 *norm = sqrt(sum[0] + 2*sum[1]); 629 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 630 } else { 631 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 632 } 633 } 634 PetscFunctionReturn(0); 635 } 636 637 /* 638 Creates the hash table, and sets the table 639 This table is created only once. 640 If new entried need to be added to the matrix 641 then the hash table has to be destroyed and 642 recreated. 643 */ 644 #undef __FUNCT__ 645 #define __FUNCT__ "MatCreateHashTable_MPISBAIJ_Private" 646 int MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 647 { 648 PetscFunctionBegin; 649 SETERRQ(1,"Function not yet written for SBAIJ format"); 650 /* PetscFunctionReturn(0); */ 651 } 652 653 #undef __FUNCT__ 654 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 655 int MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 656 { 657 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 658 int ierr,nstash,reallocs; 659 InsertMode addv; 660 661 PetscFunctionBegin; 662 if (baij->donotstash) { 663 PetscFunctionReturn(0); 664 } 665 666 /* make sure all processors are either in INSERTMODE or ADDMODE */ 667 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 668 if (addv == (ADD_VALUES|INSERT_VALUES)) { 669 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 670 } 671 mat->insertmode = addv; /* in case this processor had no cache */ 672 673 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 674 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 675 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 676 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 677 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 678 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 679 PetscFunctionReturn(0); 680 } 681 682 #undef __FUNCT__ 683 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 684 int MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 685 { 686 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 687 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 688 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 689 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 690 int *row,*col,other_disassembled; 691 PetscTruth r1,r2,r3; 692 MatScalar *val; 693 InsertMode addv = mat->insertmode; 694 695 PetscFunctionBegin; 696 697 if (!baij->donotstash) { 698 while (1) { 699 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 700 /* 701 PetscSynchronizedPrintf(mat->comm,"[%d]: in AssemblyEnd, stash, flg=%d\n",rank,flg); 702 PetscSynchronizedFlush(mat->comm); 703 */ 704 if (!flg) break; 705 706 for (i=0; i<n;) { 707 /* Now identify the consecutive vals belonging to the same row */ 708 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 709 if (j < n) ncols = j-i; 710 else ncols = n-i; 711 /* Now assemble all these values with a single function call */ 712 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 713 i = j; 714 } 715 } 716 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 717 /* Now process the block-stash. Since the values are stashed column-oriented, 718 set the roworiented flag to column oriented, and after MatSetValues() 719 restore the original flags */ 720 r1 = baij->roworiented; 721 r2 = a->roworiented; 722 r3 = b->roworiented; 723 baij->roworiented = PETSC_FALSE; 724 a->roworiented = PETSC_FALSE; 725 b->roworiented = PETSC_FALSE; 726 while (1) { 727 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 728 if (!flg) break; 729 730 for (i=0; i<n;) { 731 /* Now identify the consecutive vals belonging to the same row */ 732 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 733 if (j < n) ncols = j-i; 734 else ncols = n-i; 735 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 736 i = j; 737 } 738 } 739 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 740 baij->roworiented = r1; 741 a->roworiented = r2; 742 b->roworiented = r3; 743 } 744 745 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 746 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 747 748 /* determine if any processor has disassembled, if so we must 749 also disassemble ourselfs, in order that we may reassemble. */ 750 /* 751 if nonzero structure of submatrix B cannot change then we know that 752 no processor disassembled thus we can skip this stuff 753 */ 754 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 755 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 756 if (mat->was_assembled && !other_disassembled) { 757 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 758 } 759 } 760 761 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 762 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 763 } 764 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 765 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 766 767 #if defined(PETSC_USE_BOPT_g) 768 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 769 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct); 770 baij->ht_total_ct = 0; 771 baij->ht_insert_ct = 0; 772 } 773 #endif 774 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 775 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 776 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 777 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 778 } 779 780 if (baij->rowvalues) { 781 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 782 baij->rowvalues = 0; 783 } 784 785 PetscFunctionReturn(0); 786 } 787 788 #undef __FUNCT__ 789 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 790 static int MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 791 { 792 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 793 int ierr,bs = baij->bs,size = baij->size,rank = baij->rank; 794 PetscTruth isascii,isdraw; 795 PetscViewer sviewer; 796 PetscViewerFormat format; 797 798 PetscFunctionBegin; 799 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 800 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 801 if (isascii) { 802 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 803 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 804 MatInfo info; 805 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 806 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 807 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 808 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 809 baij->bs,(int)info.memory);CHKERRQ(ierr); 810 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 811 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 812 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 813 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 814 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 815 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 816 PetscFunctionReturn(0); 817 } else if (format == PETSC_VIEWER_ASCII_INFO) { 818 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 819 PetscFunctionReturn(0); 820 } 821 } 822 823 if (isdraw) { 824 PetscDraw draw; 825 PetscTruth isnull; 826 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 827 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 828 } 829 830 if (size == 1) { 831 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 832 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 833 } else { 834 /* assemble the entire matrix onto first processor. */ 835 Mat A; 836 Mat_SeqSBAIJ *Aloc; 837 Mat_SeqBAIJ *Bloc; 838 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 839 MatScalar *a; 840 841 if (!rank) { 842 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 843 } else { 844 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 845 } 846 PetscLogObjectParent(mat,A); 847 848 /* copy over the A part */ 849 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 850 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 851 ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr); 852 853 for (i=0; i<mbs; i++) { 854 rvals[0] = bs*(baij->rstart + i); 855 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 856 for (j=ai[i]; j<ai[i+1]; j++) { 857 col = (baij->cstart+aj[j])*bs; 858 for (k=0; k<bs; k++) { 859 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 860 col++; a += bs; 861 } 862 } 863 } 864 /* copy over the B part */ 865 Bloc = (Mat_SeqBAIJ*)baij->B->data; 866 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 867 for (i=0; i<mbs; i++) { 868 rvals[0] = bs*(baij->rstart + i); 869 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 870 for (j=ai[i]; j<ai[i+1]; j++) { 871 col = baij->garray[aj[j]]*bs; 872 for (k=0; k<bs; k++) { 873 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 874 col++; a += bs; 875 } 876 } 877 } 878 ierr = PetscFree(rvals);CHKERRQ(ierr); 879 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 880 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 881 /* 882 Everyone has to call to draw the matrix since the graphics waits are 883 synchronized across all processors that share the PetscDraw object 884 */ 885 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 886 if (!rank) { 887 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 888 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 889 } 890 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 891 ierr = MatDestroy(A);CHKERRQ(ierr); 892 } 893 PetscFunctionReturn(0); 894 } 895 896 #undef __FUNCT__ 897 #define __FUNCT__ "MatView_MPISBAIJ" 898 int MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 899 { 900 int ierr; 901 PetscTruth isascii,isdraw,issocket,isbinary; 902 903 PetscFunctionBegin; 904 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 905 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 906 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 907 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 908 if (isascii || isdraw || issocket || isbinary) { 909 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 910 } else { 911 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 912 } 913 PetscFunctionReturn(0); 914 } 915 916 #undef __FUNCT__ 917 #define __FUNCT__ "MatDestroy_MPISBAIJ" 918 int MatDestroy_MPISBAIJ(Mat mat) 919 { 920 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 921 int ierr; 922 923 PetscFunctionBegin; 924 #if defined(PETSC_USE_LOG) 925 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 926 #endif 927 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 928 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 929 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 930 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 931 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 932 #if defined (PETSC_USE_CTABLE) 933 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 934 #else 935 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 936 #endif 937 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 938 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 939 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 940 if (baij->slvec0) { 941 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 942 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 943 } 944 if (baij->slvec1) { 945 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 946 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 947 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 948 } 949 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 950 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 951 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 952 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 953 #if defined(PETSC_USE_MAT_SINGLE) 954 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 955 #endif 956 ierr = PetscFree(baij);CHKERRQ(ierr); 957 PetscFunctionReturn(0); 958 } 959 960 #undef __FUNCT__ 961 #define __FUNCT__ "MatMult_MPISBAIJ" 962 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 963 { 964 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 965 int ierr,nt,mbs=a->mbs,bs=a->bs; 966 PetscScalar *x,*from,zero=0.0; 967 968 PetscFunctionBegin; 969 /* 970 PetscSynchronizedPrintf(A->comm," _1comm is called ...\n"); 971 PetscSynchronizedFlush(A->comm); 972 */ 973 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 974 if (nt != A->n) { 975 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 976 } 977 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 978 if (nt != A->m) { 979 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 980 } 981 982 /* diagonal part */ 983 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 984 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 985 986 /* subdiagonal part */ 987 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 988 989 /* copy x into the vec slvec0 */ 990 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 991 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 992 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 993 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 994 995 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 996 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 997 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 998 999 /* supperdiagonal part */ 1000 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 1001 1002 PetscFunctionReturn(0); 1003 } 1004 1005 #undef __FUNCT__ 1006 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 1007 int MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 1008 { 1009 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1010 int ierr,nt; 1011 1012 PetscFunctionBegin; 1013 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1014 if (nt != A->n) { 1015 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1016 } 1017 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1018 if (nt != A->m) { 1019 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1020 } 1021 1022 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1023 /* do diagonal part */ 1024 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1025 /* do supperdiagonal part */ 1026 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1027 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1028 /* do subdiagonal part */ 1029 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1030 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1031 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1032 1033 PetscFunctionReturn(0); 1034 } 1035 1036 #undef __FUNCT__ 1037 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 1038 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1039 { 1040 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1041 int ierr,mbs=a->mbs,bs=a->bs; 1042 PetscScalar *x,*from,zero=0.0; 1043 1044 PetscFunctionBegin; 1045 /* 1046 PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n"); 1047 PetscSynchronizedFlush(A->comm); 1048 */ 1049 /* diagonal part */ 1050 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 1051 ierr = VecSet(&zero,a->slvec1b);CHKERRQ(ierr); 1052 1053 /* subdiagonal part */ 1054 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 1055 1056 /* copy x into the vec slvec0 */ 1057 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 1058 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1059 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1060 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 1061 1062 ierr = VecScatterBegin(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1063 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1064 ierr = VecScatterEnd(a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD,a->sMvctx);CHKERRQ(ierr); 1065 1066 /* supperdiagonal part */ 1067 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 1068 1069 PetscFunctionReturn(0); 1070 } 1071 1072 #undef __FUNCT__ 1073 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 1074 int MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 1075 { 1076 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1077 int ierr; 1078 1079 PetscFunctionBegin; 1080 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1081 /* do diagonal part */ 1082 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1083 /* do supperdiagonal part */ 1084 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1085 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1086 1087 /* do subdiagonal part */ 1088 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1089 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1090 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1091 1092 PetscFunctionReturn(0); 1093 } 1094 1095 #undef __FUNCT__ 1096 #define __FUNCT__ "MatMultTranspose_MPISBAIJ" 1097 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 1098 { 1099 PetscFunctionBegin; 1100 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 1101 /* PetscFunctionReturn(0); */ 1102 } 1103 1104 #undef __FUNCT__ 1105 #define __FUNCT__ "MatMultTransposeAdd_MPISBAIJ" 1106 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1107 { 1108 PetscFunctionBegin; 1109 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 1110 /* PetscFunctionReturn(0); */ 1111 } 1112 1113 /* 1114 This only works correctly for square matrices where the subblock A->A is the 1115 diagonal block 1116 */ 1117 #undef __FUNCT__ 1118 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 1119 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 1120 { 1121 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1122 int ierr; 1123 1124 PetscFunctionBegin; 1125 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1126 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatScale_MPISBAIJ" 1132 int MatScale_MPISBAIJ(const PetscScalar *aa,Mat A) 1133 { 1134 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1135 int ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1139 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatGetRow_MPISBAIJ" 1145 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 1146 { 1147 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 1148 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1149 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 1150 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1151 int *cmap,*idx_p,cstart = mat->cstart; 1152 1153 PetscFunctionBegin; 1154 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1155 mat->getrowactive = PETSC_TRUE; 1156 1157 if (!mat->rowvalues && (idx || v)) { 1158 /* 1159 allocate enough space to hold information from the longest row. 1160 */ 1161 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 1162 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 1163 int max = 1,mbs = mat->mbs,tmp; 1164 for (i=0; i<mbs; i++) { 1165 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 1166 if (max < tmp) { max = tmp; } 1167 } 1168 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1169 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 1170 } 1171 1172 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1173 lrow = row - brstart; /* local row index */ 1174 1175 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1176 if (!v) {pvA = 0; pvB = 0;} 1177 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1178 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1179 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1180 nztot = nzA + nzB; 1181 1182 cmap = mat->garray; 1183 if (v || idx) { 1184 if (nztot) { 1185 /* Sort by increasing column numbers, assuming A and B already sorted */ 1186 int imark = -1; 1187 if (v) { 1188 *v = v_p = mat->rowvalues; 1189 for (i=0; i<nzB; i++) { 1190 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1191 else break; 1192 } 1193 imark = i; 1194 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1195 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1196 } 1197 if (idx) { 1198 *idx = idx_p = mat->rowindices; 1199 if (imark > -1) { 1200 for (i=0; i<imark; i++) { 1201 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1202 } 1203 } else { 1204 for (i=0; i<nzB; i++) { 1205 if (cmap[cworkB[i]/bs] < cstart) 1206 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1207 else break; 1208 } 1209 imark = i; 1210 } 1211 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1212 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1213 } 1214 } else { 1215 if (idx) *idx = 0; 1216 if (v) *v = 0; 1217 } 1218 } 1219 *nz = nztot; 1220 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1221 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1222 PetscFunctionReturn(0); 1223 } 1224 1225 #undef __FUNCT__ 1226 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1227 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1228 { 1229 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1230 1231 PetscFunctionBegin; 1232 if (baij->getrowactive == PETSC_FALSE) { 1233 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1234 } 1235 baij->getrowactive = PETSC_FALSE; 1236 PetscFunctionReturn(0); 1237 } 1238 1239 #undef __FUNCT__ 1240 #define __FUNCT__ "MatGetBlockSize_MPISBAIJ" 1241 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1242 { 1243 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1244 1245 PetscFunctionBegin; 1246 *bs = baij->bs; 1247 PetscFunctionReturn(0); 1248 } 1249 1250 #undef __FUNCT__ 1251 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1252 int MatZeroEntries_MPISBAIJ(Mat A) 1253 { 1254 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1255 int ierr; 1256 1257 PetscFunctionBegin; 1258 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1259 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1260 PetscFunctionReturn(0); 1261 } 1262 1263 #undef __FUNCT__ 1264 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1265 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1266 { 1267 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1268 Mat A = a->A,B = a->B; 1269 int ierr; 1270 PetscReal isend[5],irecv[5]; 1271 1272 PetscFunctionBegin; 1273 info->block_size = (PetscReal)a->bs; 1274 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1275 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1276 isend[3] = info->memory; isend[4] = info->mallocs; 1277 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1278 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1279 isend[3] += info->memory; isend[4] += info->mallocs; 1280 if (flag == MAT_LOCAL) { 1281 info->nz_used = isend[0]; 1282 info->nz_allocated = isend[1]; 1283 info->nz_unneeded = isend[2]; 1284 info->memory = isend[3]; 1285 info->mallocs = isend[4]; 1286 } else if (flag == MAT_GLOBAL_MAX) { 1287 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1288 info->nz_used = irecv[0]; 1289 info->nz_allocated = irecv[1]; 1290 info->nz_unneeded = irecv[2]; 1291 info->memory = irecv[3]; 1292 info->mallocs = irecv[4]; 1293 } else if (flag == MAT_GLOBAL_SUM) { 1294 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1295 info->nz_used = irecv[0]; 1296 info->nz_allocated = irecv[1]; 1297 info->nz_unneeded = irecv[2]; 1298 info->memory = irecv[3]; 1299 info->mallocs = irecv[4]; 1300 } else { 1301 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1302 } 1303 info->rows_global = (PetscReal)A->M; 1304 info->columns_global = (PetscReal)A->N; 1305 info->rows_local = (PetscReal)A->m; 1306 info->columns_local = (PetscReal)A->N; 1307 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1308 info->fill_ratio_needed = 0; 1309 info->factor_mallocs = 0; 1310 PetscFunctionReturn(0); 1311 } 1312 1313 #undef __FUNCT__ 1314 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1315 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1316 { 1317 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1318 int ierr; 1319 1320 PetscFunctionBegin; 1321 switch (op) { 1322 case MAT_NO_NEW_NONZERO_LOCATIONS: 1323 case MAT_YES_NEW_NONZERO_LOCATIONS: 1324 case MAT_COLUMNS_UNSORTED: 1325 case MAT_COLUMNS_SORTED: 1326 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1327 case MAT_KEEP_ZEROED_ROWS: 1328 case MAT_NEW_NONZERO_LOCATION_ERR: 1329 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1330 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1331 break; 1332 case MAT_ROW_ORIENTED: 1333 a->roworiented = PETSC_TRUE; 1334 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1335 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1336 break; 1337 case MAT_ROWS_SORTED: 1338 case MAT_ROWS_UNSORTED: 1339 case MAT_YES_NEW_DIAGONALS: 1340 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1341 break; 1342 case MAT_COLUMN_ORIENTED: 1343 a->roworiented = PETSC_FALSE; 1344 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1345 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1346 break; 1347 case MAT_IGNORE_OFF_PROC_ENTRIES: 1348 a->donotstash = PETSC_TRUE; 1349 break; 1350 case MAT_NO_NEW_DIAGONALS: 1351 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1352 case MAT_USE_HASH_TABLE: 1353 a->ht_flag = PETSC_TRUE; 1354 break; 1355 case MAT_SYMMETRIC: 1356 case MAT_STRUCTURALLY_SYMMETRIC: 1357 break; 1358 default: 1359 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1360 } 1361 PetscFunctionReturn(0); 1362 } 1363 1364 #undef __FUNCT__ 1365 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1366 int MatTranspose_MPISBAIJ(Mat A,Mat *B) 1367 { 1368 int ierr; 1369 PetscFunctionBegin; 1370 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1371 PetscFunctionReturn(0); 1372 } 1373 1374 #undef __FUNCT__ 1375 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1376 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1377 { 1378 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1379 Mat a = baij->A,b = baij->B; 1380 int ierr,s1,s2,s3; 1381 1382 PetscFunctionBegin; 1383 if (ll != rr) { 1384 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1385 } 1386 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1387 if (rr) { 1388 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1389 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1390 /* Overlap communication with computation. */ 1391 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1392 /*} if (ll) { */ 1393 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1394 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1395 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1396 /* } */ 1397 /* scale the diagonal block */ 1398 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1399 1400 /* if (rr) { */ 1401 /* Do a scatter end and then right scale the off-diagonal block */ 1402 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1403 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1404 } 1405 1406 PetscFunctionReturn(0); 1407 } 1408 1409 #undef __FUNCT__ 1410 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1411 int MatZeroRows_MPISBAIJ(Mat A,IS is,const PetscScalar *diag) 1412 { 1413 PetscFunctionBegin; 1414 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1415 } 1416 1417 #undef __FUNCT__ 1418 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1419 int MatPrintHelp_MPISBAIJ(Mat A) 1420 { 1421 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1422 MPI_Comm comm = A->comm; 1423 static int called = 0; 1424 int ierr; 1425 1426 PetscFunctionBegin; 1427 if (!a->rank) { 1428 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1429 } 1430 if (called) {PetscFunctionReturn(0);} else called = 1; 1431 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1432 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1433 PetscFunctionReturn(0); 1434 } 1435 1436 #undef __FUNCT__ 1437 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1438 int MatSetUnfactored_MPISBAIJ(Mat A) 1439 { 1440 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1441 int ierr; 1442 1443 PetscFunctionBegin; 1444 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1445 PetscFunctionReturn(0); 1446 } 1447 1448 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1449 1450 #undef __FUNCT__ 1451 #define __FUNCT__ "MatEqual_MPISBAIJ" 1452 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1453 { 1454 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1455 Mat a,b,c,d; 1456 PetscTruth flg; 1457 int ierr; 1458 1459 PetscFunctionBegin; 1460 a = matA->A; b = matA->B; 1461 c = matB->A; d = matB->B; 1462 1463 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1464 if (flg == PETSC_TRUE) { 1465 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1466 } 1467 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1468 PetscFunctionReturn(0); 1469 } 1470 1471 #undef __FUNCT__ 1472 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1473 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1474 { 1475 int ierr; 1476 1477 PetscFunctionBegin; 1478 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1479 PetscFunctionReturn(0); 1480 } 1481 /* -------------------------------------------------------------------*/ 1482 static struct _MatOps MatOps_Values = { 1483 MatSetValues_MPISBAIJ, 1484 MatGetRow_MPISBAIJ, 1485 MatRestoreRow_MPISBAIJ, 1486 MatMult_MPISBAIJ, 1487 /* 4*/ MatMultAdd_MPISBAIJ, 1488 MatMultTranspose_MPISBAIJ, 1489 MatMultTransposeAdd_MPISBAIJ, 1490 0, 1491 0, 1492 0, 1493 /*10*/ 0, 1494 0, 1495 0, 1496 MatRelax_MPISBAIJ, 1497 MatTranspose_MPISBAIJ, 1498 /*15*/ MatGetInfo_MPISBAIJ, 1499 MatEqual_MPISBAIJ, 1500 MatGetDiagonal_MPISBAIJ, 1501 MatDiagonalScale_MPISBAIJ, 1502 MatNorm_MPISBAIJ, 1503 /*20*/ MatAssemblyBegin_MPISBAIJ, 1504 MatAssemblyEnd_MPISBAIJ, 1505 0, 1506 MatSetOption_MPISBAIJ, 1507 MatZeroEntries_MPISBAIJ, 1508 /*25*/ MatZeroRows_MPISBAIJ, 1509 0, 1510 0, 1511 0, 1512 0, 1513 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1514 0, 1515 0, 1516 0, 1517 0, 1518 /*35*/ MatDuplicate_MPISBAIJ, 1519 0, 1520 0, 1521 0, 1522 0, 1523 /*40*/ 0, 1524 0, 1525 0, 1526 MatGetValues_MPISBAIJ, 1527 0, 1528 /*45*/ MatPrintHelp_MPISBAIJ, 1529 MatScale_MPISBAIJ, 1530 0, 1531 0, 1532 0, 1533 /*50*/ MatGetBlockSize_MPISBAIJ, 1534 0, 1535 0, 1536 0, 1537 0, 1538 /*55*/ 0, 1539 0, 1540 MatSetUnfactored_MPISBAIJ, 1541 0, 1542 MatSetValuesBlocked_MPISBAIJ, 1543 /*60*/ 0, 1544 0, 1545 0, 1546 MatGetPetscMaps_Petsc, 1547 0, 1548 /*65*/ 0, 1549 0, 1550 0, 1551 0, 1552 0, 1553 /*70*/ MatGetRowMax_MPISBAIJ, 1554 0, 1555 0, 1556 0, 1557 0, 1558 /*75*/ 0, 1559 0, 1560 0, 1561 0, 1562 0, 1563 /*80*/ 0, 1564 0, 1565 0, 1566 0, 1567 0, 1568 /*85*/ MatLoad_MPISBAIJ 1569 }; 1570 1571 1572 EXTERN_C_BEGIN 1573 #undef __FUNCT__ 1574 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1575 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1576 { 1577 PetscFunctionBegin; 1578 *a = ((Mat_MPISBAIJ *)A->data)->A; 1579 *iscopy = PETSC_FALSE; 1580 PetscFunctionReturn(0); 1581 } 1582 EXTERN_C_END 1583 1584 EXTERN_C_BEGIN 1585 #undef __FUNCT__ 1586 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1587 int MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1588 { 1589 Mat_MPISBAIJ *b; 1590 int ierr,i,mbs,Mbs; 1591 1592 PetscFunctionBegin; 1593 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1594 1595 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1596 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1597 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1598 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1599 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1600 if (d_nnz) { 1601 for (i=0; i<B->m/bs; i++) { 1602 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]); 1603 } 1604 } 1605 if (o_nnz) { 1606 for (i=0; i<B->m/bs; i++) { 1607 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]); 1608 } 1609 } 1610 B->preallocated = PETSC_TRUE; 1611 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1612 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1613 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1614 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1615 1616 b = (Mat_MPISBAIJ*)B->data; 1617 mbs = B->m/bs; 1618 Mbs = B->M/bs; 1619 if (mbs*bs != B->m) { 1620 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1621 } 1622 1623 b->bs = bs; 1624 b->bs2 = bs*bs; 1625 b->mbs = mbs; 1626 b->nbs = mbs; 1627 b->Mbs = Mbs; 1628 b->Nbs = Mbs; 1629 1630 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1631 b->rowners[0] = 0; 1632 for (i=2; i<=b->size; i++) { 1633 b->rowners[i] += b->rowners[i-1]; 1634 } 1635 b->rstart = b->rowners[b->rank]; 1636 b->rend = b->rowners[b->rank+1]; 1637 b->cstart = b->rstart; 1638 b->cend = b->rend; 1639 for (i=0; i<=b->size; i++) { 1640 b->rowners_bs[i] = b->rowners[i]*bs; 1641 } 1642 b->rstart_bs = b-> rstart*bs; 1643 b->rend_bs = b->rend*bs; 1644 1645 b->cstart_bs = b->cstart*bs; 1646 b->cend_bs = b->cend*bs; 1647 1648 1649 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1650 PetscLogObjectParent(B,b->A); 1651 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1652 PetscLogObjectParent(B,b->B); 1653 1654 /* build cache for off array entries formed */ 1655 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1656 1657 PetscFunctionReturn(0); 1658 } 1659 EXTERN_C_END 1660 1661 /*MC 1662 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1663 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1664 1665 Options Database Keys: 1666 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1667 1668 Level: beginner 1669 1670 .seealso: MatCreateMPISBAIJ 1671 M*/ 1672 1673 EXTERN_C_BEGIN 1674 #undef __FUNCT__ 1675 #define __FUNCT__ "MatCreate_MPISBAIJ" 1676 int MatCreate_MPISBAIJ(Mat B) 1677 { 1678 Mat_MPISBAIJ *b; 1679 int ierr; 1680 PetscTruth flg; 1681 1682 PetscFunctionBegin; 1683 1684 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1685 B->data = (void*)b; 1686 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1687 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1688 1689 B->ops->destroy = MatDestroy_MPISBAIJ; 1690 B->ops->view = MatView_MPISBAIJ; 1691 B->mapping = 0; 1692 B->factor = 0; 1693 B->assembled = PETSC_FALSE; 1694 1695 B->insertmode = NOT_SET_VALUES; 1696 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1697 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1698 1699 /* build local table of row and column ownerships */ 1700 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1701 b->cowners = b->rowners + b->size + 2; 1702 b->rowners_bs = b->cowners + b->size + 2; 1703 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1704 1705 /* build cache for off array entries formed */ 1706 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1707 b->donotstash = PETSC_FALSE; 1708 b->colmap = PETSC_NULL; 1709 b->garray = PETSC_NULL; 1710 b->roworiented = PETSC_TRUE; 1711 1712 #if defined(PETSC_USE_MAT_SINGLE) 1713 /* stuff for MatSetValues_XXX in single precision */ 1714 b->setvalueslen = 0; 1715 b->setvaluescopy = PETSC_NULL; 1716 #endif 1717 1718 /* stuff used in block assembly */ 1719 b->barray = 0; 1720 1721 /* stuff used for matrix vector multiply */ 1722 b->lvec = 0; 1723 b->Mvctx = 0; 1724 b->slvec0 = 0; 1725 b->slvec0b = 0; 1726 b->slvec1 = 0; 1727 b->slvec1a = 0; 1728 b->slvec1b = 0; 1729 b->sMvctx = 0; 1730 1731 /* stuff for MatGetRow() */ 1732 b->rowindices = 0; 1733 b->rowvalues = 0; 1734 b->getrowactive = PETSC_FALSE; 1735 1736 /* hash table stuff */ 1737 b->ht = 0; 1738 b->hd = 0; 1739 b->ht_size = 0; 1740 b->ht_flag = PETSC_FALSE; 1741 b->ht_fact = 0; 1742 b->ht_total_ct = 0; 1743 b->ht_insert_ct = 0; 1744 1745 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1746 if (flg) { 1747 PetscReal fact = 1.39; 1748 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1749 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1750 if (fact <= 1.0) fact = 1.39; 1751 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1752 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1753 } 1754 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1755 "MatStoreValues_MPISBAIJ", 1756 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1757 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1758 "MatRetrieveValues_MPISBAIJ", 1759 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1760 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1761 "MatGetDiagonalBlock_MPISBAIJ", 1762 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1763 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1764 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1765 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1766 PetscFunctionReturn(0); 1767 } 1768 EXTERN_C_END 1769 1770 /*MC 1771 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1772 1773 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1774 and MATMPISBAIJ otherwise. 1775 1776 Options Database Keys: 1777 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1778 1779 Level: beginner 1780 1781 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1782 M*/ 1783 1784 EXTERN_C_BEGIN 1785 #undef __FUNCT__ 1786 #define __FUNCT__ "MatCreate_SBAIJ" 1787 int MatCreate_SBAIJ(Mat A) { 1788 int ierr,size; 1789 1790 PetscFunctionBegin; 1791 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1792 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1793 if (size == 1) { 1794 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1795 } else { 1796 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1797 } 1798 PetscFunctionReturn(0); 1799 } 1800 EXTERN_C_END 1801 1802 #undef __FUNCT__ 1803 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1804 /*@C 1805 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1806 the user should preallocate the matrix storage by setting the parameters 1807 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1808 performance can be increased by more than a factor of 50. 1809 1810 Collective on Mat 1811 1812 Input Parameters: 1813 + A - the matrix 1814 . bs - size of blockk 1815 . d_nz - number of block nonzeros per block row in diagonal portion of local 1816 submatrix (same for all local rows) 1817 . d_nnz - array containing the number of block nonzeros in the various block rows 1818 in the upper triangular and diagonal part of the in diagonal portion of the local 1819 (possibly different for each block row) or PETSC_NULL. You must leave room 1820 for the diagonal entry even if it is zero. 1821 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1822 submatrix (same for all local rows). 1823 - o_nnz - array containing the number of nonzeros in the various block rows of the 1824 off-diagonal portion of the local submatrix (possibly different for 1825 each block row) or PETSC_NULL. 1826 1827 1828 Options Database Keys: 1829 . -mat_no_unroll - uses code that does not unroll the loops in the 1830 block calculations (much slower) 1831 . -mat_block_size - size of the blocks to use 1832 1833 Notes: 1834 1835 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1836 than it must be used on all processors that share the object for that argument. 1837 1838 Storage Information: 1839 For a square global matrix we define each processor's diagonal portion 1840 to be its local rows and the corresponding columns (a square submatrix); 1841 each processor's off-diagonal portion encompasses the remainder of the 1842 local matrix (a rectangular submatrix). 1843 1844 The user can specify preallocated storage for the diagonal part of 1845 the local submatrix with either d_nz or d_nnz (not both). Set 1846 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1847 memory allocation. Likewise, specify preallocated storage for the 1848 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1849 1850 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1851 the figure below we depict these three local rows and all columns (0-11). 1852 1853 .vb 1854 0 1 2 3 4 5 6 7 8 9 10 11 1855 ------------------- 1856 row 3 | o o o d d d o o o o o o 1857 row 4 | o o o d d d o o o o o o 1858 row 5 | o o o d d d o o o o o o 1859 ------------------- 1860 .ve 1861 1862 Thus, any entries in the d locations are stored in the d (diagonal) 1863 submatrix, and any entries in the o locations are stored in the 1864 o (off-diagonal) submatrix. Note that the d matrix is stored in 1865 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1866 1867 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1868 plus the diagonal part of the d matrix, 1869 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1870 In general, for PDE problems in which most nonzeros are near the diagonal, 1871 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1872 or you will get TERRIBLE performance; see the users' manual chapter on 1873 matrices. 1874 1875 Level: intermediate 1876 1877 .keywords: matrix, block, aij, compressed row, sparse, parallel 1878 1879 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1880 @*/ 1881 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,const int d_nnz[],int o_nz,const int o_nnz[]) 1882 { 1883 int ierr,(*f)(Mat,int,int,const int[],int,const int[]); 1884 1885 PetscFunctionBegin; 1886 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1887 if (f) { 1888 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1889 } 1890 PetscFunctionReturn(0); 1891 } 1892 1893 #undef __FUNCT__ 1894 #define __FUNCT__ "MatCreateMPISBAIJ" 1895 /*@C 1896 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1897 (block compressed row). For good matrix assembly performance 1898 the user should preallocate the matrix storage by setting the parameters 1899 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1900 performance can be increased by more than a factor of 50. 1901 1902 Collective on MPI_Comm 1903 1904 Input Parameters: 1905 + comm - MPI communicator 1906 . bs - size of blockk 1907 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1908 This value should be the same as the local size used in creating the 1909 y vector for the matrix-vector product y = Ax. 1910 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1911 This value should be the same as the local size used in creating the 1912 x vector for the matrix-vector product y = Ax. 1913 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1914 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1915 . d_nz - number of block nonzeros per block row in diagonal portion of local 1916 submatrix (same for all local rows) 1917 . d_nnz - array containing the number of block nonzeros in the various block rows 1918 in the upper triangular portion of the in diagonal portion of the local 1919 (possibly different for each block block row) or PETSC_NULL. 1920 You must leave room for the diagonal entry even if it is zero. 1921 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1922 submatrix (same for all local rows). 1923 - o_nnz - array containing the number of nonzeros in the various block rows of the 1924 off-diagonal portion of the local submatrix (possibly different for 1925 each block row) or PETSC_NULL. 1926 1927 Output Parameter: 1928 . A - the matrix 1929 1930 Options Database Keys: 1931 . -mat_no_unroll - uses code that does not unroll the loops in the 1932 block calculations (much slower) 1933 . -mat_block_size - size of the blocks to use 1934 . -mat_mpi - use the parallel matrix data structures even on one processor 1935 (defaults to using SeqBAIJ format on one processor) 1936 1937 Notes: 1938 The user MUST specify either the local or global matrix dimensions 1939 (possibly both). 1940 1941 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1942 than it must be used on all processors that share the object for that argument. 1943 1944 Storage Information: 1945 For a square global matrix we define each processor's diagonal portion 1946 to be its local rows and the corresponding columns (a square submatrix); 1947 each processor's off-diagonal portion encompasses the remainder of the 1948 local matrix (a rectangular submatrix). 1949 1950 The user can specify preallocated storage for the diagonal part of 1951 the local submatrix with either d_nz or d_nnz (not both). Set 1952 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1953 memory allocation. Likewise, specify preallocated storage for the 1954 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1955 1956 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1957 the figure below we depict these three local rows and all columns (0-11). 1958 1959 .vb 1960 0 1 2 3 4 5 6 7 8 9 10 11 1961 ------------------- 1962 row 3 | o o o d d d o o o o o o 1963 row 4 | o o o d d d o o o o o o 1964 row 5 | o o o d d d o o o o o o 1965 ------------------- 1966 .ve 1967 1968 Thus, any entries in the d locations are stored in the d (diagonal) 1969 submatrix, and any entries in the o locations are stored in the 1970 o (off-diagonal) submatrix. Note that the d matrix is stored in 1971 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1972 1973 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1974 plus the diagonal part of the d matrix, 1975 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1976 In general, for PDE problems in which most nonzeros are near the diagonal, 1977 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1978 or you will get TERRIBLE performance; see the users' manual chapter on 1979 matrices. 1980 1981 Level: intermediate 1982 1983 .keywords: matrix, block, aij, compressed row, sparse, parallel 1984 1985 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1986 @*/ 1987 1988 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) 1989 { 1990 int ierr,size; 1991 1992 PetscFunctionBegin; 1993 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1994 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1995 if (size > 1) { 1996 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1997 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1998 } else { 1999 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 2000 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2001 } 2002 PetscFunctionReturn(0); 2003 } 2004 2005 2006 #undef __FUNCT__ 2007 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2008 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2009 { 2010 Mat mat; 2011 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2012 int ierr,len=0; 2013 2014 PetscFunctionBegin; 2015 *newmat = 0; 2016 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2017 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 2018 mat->preallocated = PETSC_TRUE; 2019 a = (Mat_MPISBAIJ*)mat->data; 2020 a->bs = oldmat->bs; 2021 a->bs2 = oldmat->bs2; 2022 a->mbs = oldmat->mbs; 2023 a->nbs = oldmat->nbs; 2024 a->Mbs = oldmat->Mbs; 2025 a->Nbs = oldmat->Nbs; 2026 2027 a->rstart = oldmat->rstart; 2028 a->rend = oldmat->rend; 2029 a->cstart = oldmat->cstart; 2030 a->cend = oldmat->cend; 2031 a->size = oldmat->size; 2032 a->rank = oldmat->rank; 2033 a->donotstash = oldmat->donotstash; 2034 a->roworiented = oldmat->roworiented; 2035 a->rowindices = 0; 2036 a->rowvalues = 0; 2037 a->getrowactive = PETSC_FALSE; 2038 a->barray = 0; 2039 a->rstart_bs = oldmat->rstart_bs; 2040 a->rend_bs = oldmat->rend_bs; 2041 a->cstart_bs = oldmat->cstart_bs; 2042 a->cend_bs = oldmat->cend_bs; 2043 2044 /* hash table stuff */ 2045 a->ht = 0; 2046 a->hd = 0; 2047 a->ht_size = 0; 2048 a->ht_flag = oldmat->ht_flag; 2049 a->ht_fact = oldmat->ht_fact; 2050 a->ht_total_ct = 0; 2051 a->ht_insert_ct = 0; 2052 2053 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 2054 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 2055 a->cowners = a->rowners + a->size + 2; 2056 a->rowners_bs = a->cowners + a->size + 2; 2057 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 2058 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2059 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 2060 if (oldmat->colmap) { 2061 #if defined (PETSC_USE_CTABLE) 2062 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2063 #else 2064 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 2065 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2066 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 2067 #endif 2068 } else a->colmap = 0; 2069 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2070 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2071 PetscLogObjectMemory(mat,len*sizeof(int)); 2072 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2073 } else a->garray = 0; 2074 2075 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2076 PetscLogObjectParent(mat,a->lvec); 2077 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2078 2079 PetscLogObjectParent(mat,a->Mvctx); 2080 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2081 PetscLogObjectParent(mat,a->A); 2082 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2083 PetscLogObjectParent(mat,a->B); 2084 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2085 *newmat = mat; 2086 PetscFunctionReturn(0); 2087 } 2088 2089 #include "petscsys.h" 2090 2091 #undef __FUNCT__ 2092 #define __FUNCT__ "MatLoad_MPISBAIJ" 2093 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 2094 { 2095 Mat A; 2096 int i,nz,ierr,j,rstart,rend,fd; 2097 PetscScalar *vals,*buf; 2098 MPI_Comm comm = ((PetscObject)viewer)->comm; 2099 MPI_Status status; 2100 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2101 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2102 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2103 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2104 int dcount,kmax,k,nzcount,tmp; 2105 2106 PetscFunctionBegin; 2107 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2108 2109 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2110 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2111 if (!rank) { 2112 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2113 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2114 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2115 if (header[3] < 0) { 2116 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2117 } 2118 } 2119 2120 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2121 M = header[1]; N = header[2]; 2122 2123 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2124 2125 /* 2126 This code adds extra rows to make sure the number of rows is 2127 divisible by the blocksize 2128 */ 2129 Mbs = M/bs; 2130 extra_rows = bs - M + bs*(Mbs); 2131 if (extra_rows == bs) extra_rows = 0; 2132 else Mbs++; 2133 if (extra_rows &&!rank) { 2134 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2135 } 2136 2137 /* determine ownership of all rows */ 2138 mbs = Mbs/size + ((Mbs % size) > rank); 2139 m = mbs*bs; 2140 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2141 browners = rowners + size + 1; 2142 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2143 rowners[0] = 0; 2144 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2145 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2146 rstart = rowners[rank]; 2147 rend = rowners[rank+1]; 2148 2149 /* distribute row lengths to all processors */ 2150 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2151 if (!rank) { 2152 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2153 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2154 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2155 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2156 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2157 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2158 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2159 } else { 2160 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2161 } 2162 2163 if (!rank) { /* procs[0] */ 2164 /* calculate the number of nonzeros on each processor */ 2165 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2166 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2167 for (i=0; i<size; i++) { 2168 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2169 procsnz[i] += rowlengths[j]; 2170 } 2171 } 2172 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2173 2174 /* determine max buffer needed and allocate it */ 2175 maxnz = 0; 2176 for (i=0; i<size; i++) { 2177 maxnz = PetscMax(maxnz,procsnz[i]); 2178 } 2179 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2180 2181 /* read in my part of the matrix column indices */ 2182 nz = procsnz[0]; 2183 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2184 mycols = ibuf; 2185 if (size == 1) nz -= extra_rows; 2186 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2187 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2188 2189 /* read in every ones (except the last) and ship off */ 2190 for (i=1; i<size-1; i++) { 2191 nz = procsnz[i]; 2192 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2193 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2194 } 2195 /* read in the stuff for the last proc */ 2196 if (size != 1) { 2197 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2198 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2199 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2200 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2201 } 2202 ierr = PetscFree(cols);CHKERRQ(ierr); 2203 } else { /* procs[i], i>0 */ 2204 /* determine buffer space needed for message */ 2205 nz = 0; 2206 for (i=0; i<m; i++) { 2207 nz += locrowlens[i]; 2208 } 2209 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2210 mycols = ibuf; 2211 /* receive message of column indices*/ 2212 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2213 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2214 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2215 } 2216 2217 /* loop over local rows, determining number of off diagonal entries */ 2218 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2219 odlens = dlens + (rend-rstart); 2220 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2221 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2222 masked1 = mask + Mbs; 2223 masked2 = masked1 + Mbs; 2224 rowcount = 0; nzcount = 0; 2225 for (i=0; i<mbs; i++) { 2226 dcount = 0; 2227 odcount = 0; 2228 for (j=0; j<bs; j++) { 2229 kmax = locrowlens[rowcount]; 2230 for (k=0; k<kmax; k++) { 2231 tmp = mycols[nzcount++]/bs; /* block col. index */ 2232 if (!mask[tmp]) { 2233 mask[tmp] = 1; 2234 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2235 else masked1[dcount++] = tmp; /* entry in diag portion */ 2236 } 2237 } 2238 rowcount++; 2239 } 2240 2241 dlens[i] = dcount; /* d_nzz[i] */ 2242 odlens[i] = odcount; /* o_nzz[i] */ 2243 2244 /* zero out the mask elements we set */ 2245 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2246 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2247 } 2248 2249 /* create our matrix */ 2250 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2251 ierr = MatSetType(A,type);CHKERRQ(ierr); 2252 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2253 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2254 2255 if (!rank) { 2256 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2257 /* read in my part of the matrix numerical values */ 2258 nz = procsnz[0]; 2259 vals = buf; 2260 mycols = ibuf; 2261 if (size == 1) nz -= extra_rows; 2262 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2263 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2264 2265 /* insert into matrix */ 2266 jj = rstart*bs; 2267 for (i=0; i<m; i++) { 2268 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2269 mycols += locrowlens[i]; 2270 vals += locrowlens[i]; 2271 jj++; 2272 } 2273 2274 /* read in other processors (except the last one) and ship out */ 2275 for (i=1; i<size-1; i++) { 2276 nz = procsnz[i]; 2277 vals = buf; 2278 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2279 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2280 } 2281 /* the last proc */ 2282 if (size != 1){ 2283 nz = procsnz[i] - extra_rows; 2284 vals = buf; 2285 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2286 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2287 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2288 } 2289 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2290 2291 } else { 2292 /* receive numeric values */ 2293 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2294 2295 /* receive message of values*/ 2296 vals = buf; 2297 mycols = ibuf; 2298 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2299 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2300 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2301 2302 /* insert into matrix */ 2303 jj = rstart*bs; 2304 for (i=0; i<m; i++) { 2305 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2306 mycols += locrowlens[i]; 2307 vals += locrowlens[i]; 2308 jj++; 2309 } 2310 } 2311 2312 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2313 ierr = PetscFree(buf);CHKERRQ(ierr); 2314 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2315 ierr = PetscFree(rowners);CHKERRQ(ierr); 2316 ierr = PetscFree(dlens);CHKERRQ(ierr); 2317 ierr = PetscFree(mask);CHKERRQ(ierr); 2318 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2319 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2320 *newmat = A; 2321 PetscFunctionReturn(0); 2322 } 2323 2324 #undef __FUNCT__ 2325 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2326 /*@ 2327 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2328 2329 Input Parameters: 2330 . mat - the matrix 2331 . fact - factor 2332 2333 Collective on Mat 2334 2335 Level: advanced 2336 2337 Notes: 2338 This can also be set by the command line option: -mat_use_hash_table fact 2339 2340 .keywords: matrix, hashtable, factor, HT 2341 2342 .seealso: MatSetOption() 2343 @*/ 2344 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2345 { 2346 PetscFunctionBegin; 2347 SETERRQ(1,"Function not yet written for SBAIJ format"); 2348 /* PetscFunctionReturn(0); */ 2349 } 2350 2351 #undef __FUNCT__ 2352 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2353 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2354 { 2355 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2356 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2357 PetscReal atmp; 2358 PetscReal *work,*svalues,*rvalues; 2359 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2360 int rank,size,*rowners_bs,dest,count,source; 2361 PetscScalar *va; 2362 MatScalar *ba; 2363 MPI_Status stat; 2364 2365 PetscFunctionBegin; 2366 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2367 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2368 2369 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2370 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2371 2372 bs = a->bs; 2373 mbs = a->mbs; 2374 Mbs = a->Mbs; 2375 ba = b->a; 2376 bi = b->i; 2377 bj = b->j; 2378 /* 2379 PetscSynchronizedPrintf(A->comm,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2380 PetscSynchronizedFlush(A->comm); 2381 */ 2382 2383 /* find ownerships */ 2384 rowners_bs = a->rowners_bs; 2385 /* 2386 if (!rank){ 2387 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2388 } 2389 */ 2390 2391 /* each proc creates an array to be distributed */ 2392 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2393 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2394 2395 /* row_max for B */ 2396 if (rank != size-1){ 2397 for (i=0; i<mbs; i++) { 2398 ncols = bi[1] - bi[0]; bi++; 2399 brow = bs*i; 2400 for (j=0; j<ncols; j++){ 2401 bcol = bs*(*bj); 2402 for (kcol=0; kcol<bs; kcol++){ 2403 col = bcol + kcol; /* local col index */ 2404 col += rowners_bs[rank+1]; /* global col index */ 2405 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2406 for (krow=0; krow<bs; krow++){ 2407 atmp = PetscAbsScalar(*ba); ba++; 2408 row = brow + krow; /* local row index */ 2409 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2410 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2411 if (work[col] < atmp) work[col] = atmp; 2412 } 2413 } 2414 bj++; 2415 } 2416 } 2417 /* 2418 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2419 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2420 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2421 */ 2422 2423 /* send values to its owners */ 2424 for (dest=rank+1; dest<size; dest++){ 2425 svalues = work + rowners_bs[dest]; 2426 count = rowners_bs[dest+1]-rowners_bs[dest]; 2427 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2428 /* 2429 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]); 2430 PetscSynchronizedFlush(A->comm); 2431 */ 2432 } 2433 } 2434 2435 /* receive values */ 2436 if (rank){ 2437 rvalues = work; 2438 count = rowners_bs[rank+1]-rowners_bs[rank]; 2439 for (source=0; source<rank; source++){ 2440 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2441 /* process values */ 2442 for (i=0; i<count; i++){ 2443 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2444 } 2445 /* 2446 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]); 2447 PetscSynchronizedFlush(A->comm); 2448 */ 2449 } 2450 } 2451 2452 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2453 ierr = PetscFree(work);CHKERRQ(ierr); 2454 PetscFunctionReturn(0); 2455 } 2456 2457 #undef __FUNCT__ 2458 #define __FUNCT__ "MatRelax_MPISBAIJ" 2459 int MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2460 { 2461 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2462 int ierr,mbs=mat->mbs,bs=mat->bs; 2463 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2464 Vec bb1; 2465 2466 PetscFunctionBegin; 2467 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2468 if (bs > 1) 2469 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2470 2471 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2472 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2473 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2474 its--; 2475 } 2476 2477 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2478 while (its--){ 2479 2480 /* lower triangular part: slvec0b = - B^T*xx */ 2481 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2482 2483 /* copy xx into slvec0a */ 2484 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2485 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2486 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2487 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2488 2489 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2490 2491 /* copy bb into slvec1a */ 2492 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2493 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2494 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2495 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2496 2497 /* set slvec1b = 0 */ 2498 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2499 2500 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2501 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2502 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2503 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2504 2505 /* upper triangular part: bb1 = bb1 - B*x */ 2506 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2507 2508 /* local diagonal sweep */ 2509 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2510 } 2511 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2512 } else { 2513 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2514 } 2515 PetscFunctionReturn(0); 2516 } 2517 2518 #undef __FUNCT__ 2519 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2520 int MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2521 { 2522 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2523 int ierr; 2524 PetscScalar mone=-1.0; 2525 Vec lvec1,bb1; 2526 2527 PetscFunctionBegin; 2528 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2529 if (mat->bs > 1) 2530 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2531 2532 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2533 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2534 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2535 its--; 2536 } 2537 2538 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2539 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2540 while (its--){ 2541 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2542 2543 /* lower diagonal part: bb1 = bb - B^T*xx */ 2544 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2545 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2546 2547 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2548 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2549 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2550 2551 /* upper diagonal part: bb1 = bb1 - B*x */ 2552 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2553 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2554 2555 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2556 2557 /* diagonal sweep */ 2558 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2559 } 2560 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2561 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2562 } else { 2563 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2564 } 2565 PetscFunctionReturn(0); 2566 } 2567 2568