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 default: 1356 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1357 } 1358 PetscFunctionReturn(0); 1359 } 1360 1361 #undef __FUNCT__ 1362 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1363 int MatTranspose_MPISBAIJ(Mat A,Mat *B) 1364 { 1365 int ierr; 1366 PetscFunctionBegin; 1367 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1368 PetscFunctionReturn(0); 1369 } 1370 1371 #undef __FUNCT__ 1372 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1373 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1374 { 1375 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1376 Mat a = baij->A,b = baij->B; 1377 int ierr,s1,s2,s3; 1378 1379 PetscFunctionBegin; 1380 if (ll != rr) { 1381 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1382 } 1383 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1384 if (rr) { 1385 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1386 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1387 /* Overlap communication with computation. */ 1388 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1389 /*} if (ll) { */ 1390 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1391 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1392 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1393 /* } */ 1394 /* scale the diagonal block */ 1395 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1396 1397 /* if (rr) { */ 1398 /* Do a scatter end and then right scale the off-diagonal block */ 1399 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1400 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1401 } 1402 1403 PetscFunctionReturn(0); 1404 } 1405 1406 #undef __FUNCT__ 1407 #define __FUNCT__ "MatZeroRows_MPISBAIJ" 1408 int MatZeroRows_MPISBAIJ(Mat A,IS is,const PetscScalar *diag) 1409 { 1410 PetscFunctionBegin; 1411 SETERRQ(PETSC_ERR_SUP,"No support for this function yet"); 1412 } 1413 1414 #undef __FUNCT__ 1415 #define __FUNCT__ "MatPrintHelp_MPISBAIJ" 1416 int MatPrintHelp_MPISBAIJ(Mat A) 1417 { 1418 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1419 MPI_Comm comm = A->comm; 1420 static int called = 0; 1421 int ierr; 1422 1423 PetscFunctionBegin; 1424 if (!a->rank) { 1425 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1426 } 1427 if (called) {PetscFunctionReturn(0);} else called = 1; 1428 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1429 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1430 PetscFunctionReturn(0); 1431 } 1432 1433 #undef __FUNCT__ 1434 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1435 int MatSetUnfactored_MPISBAIJ(Mat A) 1436 { 1437 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1438 int ierr; 1439 1440 PetscFunctionBegin; 1441 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1442 PetscFunctionReturn(0); 1443 } 1444 1445 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1446 1447 #undef __FUNCT__ 1448 #define __FUNCT__ "MatEqual_MPISBAIJ" 1449 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1450 { 1451 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1452 Mat a,b,c,d; 1453 PetscTruth flg; 1454 int ierr; 1455 1456 PetscFunctionBegin; 1457 a = matA->A; b = matA->B; 1458 c = matB->A; d = matB->B; 1459 1460 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1461 if (flg == PETSC_TRUE) { 1462 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1463 } 1464 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1465 PetscFunctionReturn(0); 1466 } 1467 1468 #undef __FUNCT__ 1469 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1470 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1471 { 1472 int ierr; 1473 1474 PetscFunctionBegin; 1475 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1476 PetscFunctionReturn(0); 1477 } 1478 /* -------------------------------------------------------------------*/ 1479 static struct _MatOps MatOps_Values = { 1480 MatSetValues_MPISBAIJ, 1481 MatGetRow_MPISBAIJ, 1482 MatRestoreRow_MPISBAIJ, 1483 MatMult_MPISBAIJ, 1484 /* 4*/ MatMultAdd_MPISBAIJ, 1485 MatMultTranspose_MPISBAIJ, 1486 MatMultTransposeAdd_MPISBAIJ, 1487 0, 1488 0, 1489 0, 1490 /*10*/ 0, 1491 0, 1492 0, 1493 MatRelax_MPISBAIJ, 1494 MatTranspose_MPISBAIJ, 1495 /*15*/ MatGetInfo_MPISBAIJ, 1496 MatEqual_MPISBAIJ, 1497 MatGetDiagonal_MPISBAIJ, 1498 MatDiagonalScale_MPISBAIJ, 1499 MatNorm_MPISBAIJ, 1500 /*20*/ MatAssemblyBegin_MPISBAIJ, 1501 MatAssemblyEnd_MPISBAIJ, 1502 0, 1503 MatSetOption_MPISBAIJ, 1504 MatZeroEntries_MPISBAIJ, 1505 /*25*/ MatZeroRows_MPISBAIJ, 1506 0, 1507 0, 1508 0, 1509 0, 1510 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1511 0, 1512 0, 1513 0, 1514 0, 1515 /*35*/ MatDuplicate_MPISBAIJ, 1516 0, 1517 0, 1518 0, 1519 0, 1520 /*40*/ 0, 1521 0, 1522 0, 1523 MatGetValues_MPISBAIJ, 1524 0, 1525 /*45*/ MatPrintHelp_MPISBAIJ, 1526 MatScale_MPISBAIJ, 1527 0, 1528 0, 1529 0, 1530 /*50*/ MatGetBlockSize_MPISBAIJ, 1531 0, 1532 0, 1533 0, 1534 0, 1535 /*55*/ 0, 1536 0, 1537 MatSetUnfactored_MPISBAIJ, 1538 0, 1539 MatSetValuesBlocked_MPISBAIJ, 1540 /*60*/ 0, 1541 0, 1542 0, 1543 MatGetPetscMaps_Petsc, 1544 0, 1545 /*65*/ 0, 1546 0, 1547 0, 1548 0, 1549 0, 1550 /*70*/ MatGetRowMax_MPISBAIJ, 1551 0, 1552 0, 1553 0, 1554 0, 1555 /*75*/ 0, 1556 0, 1557 0, 1558 0, 1559 0, 1560 /*80*/ 0, 1561 0, 1562 0, 1563 0, 1564 0, 1565 /*85*/ MatLoad_MPISBAIJ 1566 }; 1567 1568 1569 EXTERN_C_BEGIN 1570 #undef __FUNCT__ 1571 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1572 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1573 { 1574 PetscFunctionBegin; 1575 *a = ((Mat_MPISBAIJ *)A->data)->A; 1576 *iscopy = PETSC_FALSE; 1577 PetscFunctionReturn(0); 1578 } 1579 EXTERN_C_END 1580 1581 EXTERN_C_BEGIN 1582 #undef __FUNCT__ 1583 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1584 int MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1585 { 1586 Mat_MPISBAIJ *b; 1587 int ierr,i,mbs,Mbs; 1588 1589 PetscFunctionBegin; 1590 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1591 1592 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1593 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1594 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1595 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 1596 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 1597 if (d_nnz) { 1598 for (i=0; i<B->m/bs; i++) { 1599 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]); 1600 } 1601 } 1602 if (o_nnz) { 1603 for (i=0; i<B->m/bs; i++) { 1604 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]); 1605 } 1606 } 1607 B->preallocated = PETSC_TRUE; 1608 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1609 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1610 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1611 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1612 1613 b = (Mat_MPISBAIJ*)B->data; 1614 mbs = B->m/bs; 1615 Mbs = B->M/bs; 1616 if (mbs*bs != B->m) { 1617 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1618 } 1619 1620 b->bs = bs; 1621 b->bs2 = bs*bs; 1622 b->mbs = mbs; 1623 b->nbs = mbs; 1624 b->Mbs = Mbs; 1625 b->Nbs = Mbs; 1626 1627 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1628 b->rowners[0] = 0; 1629 for (i=2; i<=b->size; i++) { 1630 b->rowners[i] += b->rowners[i-1]; 1631 } 1632 b->rstart = b->rowners[b->rank]; 1633 b->rend = b->rowners[b->rank+1]; 1634 b->cstart = b->rstart; 1635 b->cend = b->rend; 1636 for (i=0; i<=b->size; i++) { 1637 b->rowners_bs[i] = b->rowners[i]*bs; 1638 } 1639 b->rstart_bs = b-> rstart*bs; 1640 b->rend_bs = b->rend*bs; 1641 1642 b->cstart_bs = b->cstart*bs; 1643 b->cend_bs = b->cend*bs; 1644 1645 1646 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1647 PetscLogObjectParent(B,b->A); 1648 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1649 PetscLogObjectParent(B,b->B); 1650 1651 /* build cache for off array entries formed */ 1652 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1653 1654 PetscFunctionReturn(0); 1655 } 1656 EXTERN_C_END 1657 1658 /*MC 1659 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1660 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1661 1662 Options Database Keys: 1663 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1664 1665 Level: beginner 1666 1667 .seealso: MatCreateMPISBAIJ 1668 M*/ 1669 1670 EXTERN_C_BEGIN 1671 #undef __FUNCT__ 1672 #define __FUNCT__ "MatCreate_MPISBAIJ" 1673 int MatCreate_MPISBAIJ(Mat B) 1674 { 1675 Mat_MPISBAIJ *b; 1676 int ierr; 1677 PetscTruth flg; 1678 1679 PetscFunctionBegin; 1680 1681 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1682 B->data = (void*)b; 1683 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1684 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1685 1686 B->ops->destroy = MatDestroy_MPISBAIJ; 1687 B->ops->view = MatView_MPISBAIJ; 1688 B->mapping = 0; 1689 B->factor = 0; 1690 B->assembled = PETSC_FALSE; 1691 1692 B->insertmode = NOT_SET_VALUES; 1693 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1694 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1695 1696 /* build local table of row and column ownerships */ 1697 ierr = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1698 b->cowners = b->rowners + b->size + 2; 1699 b->rowners_bs = b->cowners + b->size + 2; 1700 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1701 1702 /* build cache for off array entries formed */ 1703 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1704 b->donotstash = PETSC_FALSE; 1705 b->colmap = PETSC_NULL; 1706 b->garray = PETSC_NULL; 1707 b->roworiented = PETSC_TRUE; 1708 1709 #if defined(PETSC_USE_MAT_SINGLE) 1710 /* stuff for MatSetValues_XXX in single precision */ 1711 b->setvalueslen = 0; 1712 b->setvaluescopy = PETSC_NULL; 1713 #endif 1714 1715 /* stuff used in block assembly */ 1716 b->barray = 0; 1717 1718 /* stuff used for matrix vector multiply */ 1719 b->lvec = 0; 1720 b->Mvctx = 0; 1721 b->slvec0 = 0; 1722 b->slvec0b = 0; 1723 b->slvec1 = 0; 1724 b->slvec1a = 0; 1725 b->slvec1b = 0; 1726 b->sMvctx = 0; 1727 1728 /* stuff for MatGetRow() */ 1729 b->rowindices = 0; 1730 b->rowvalues = 0; 1731 b->getrowactive = PETSC_FALSE; 1732 1733 /* hash table stuff */ 1734 b->ht = 0; 1735 b->hd = 0; 1736 b->ht_size = 0; 1737 b->ht_flag = PETSC_FALSE; 1738 b->ht_fact = 0; 1739 b->ht_total_ct = 0; 1740 b->ht_insert_ct = 0; 1741 1742 ierr = PetscOptionsHasName(B->prefix,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1743 if (flg) { 1744 PetscReal fact = 1.39; 1745 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1746 ierr = PetscOptionsGetReal(B->prefix,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1747 if (fact <= 1.0) fact = 1.39; 1748 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1749 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1750 } 1751 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1752 "MatStoreValues_MPISBAIJ", 1753 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1754 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1755 "MatRetrieveValues_MPISBAIJ", 1756 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1757 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1758 "MatGetDiagonalBlock_MPISBAIJ", 1759 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1760 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1761 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1762 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1763 PetscFunctionReturn(0); 1764 } 1765 EXTERN_C_END 1766 1767 /*MC 1768 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1769 1770 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1771 and MATMPISBAIJ otherwise. 1772 1773 Options Database Keys: 1774 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1775 1776 Level: beginner 1777 1778 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1779 M*/ 1780 1781 EXTERN_C_BEGIN 1782 #undef __FUNCT__ 1783 #define __FUNCT__ "MatCreate_SBAIJ" 1784 int MatCreate_SBAIJ(Mat A) { 1785 int ierr,size; 1786 1787 PetscFunctionBegin; 1788 ierr = PetscObjectChangeTypeName((PetscObject)A,MATSBAIJ);CHKERRQ(ierr); 1789 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 1790 if (size == 1) { 1791 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1792 } else { 1793 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1794 } 1795 PetscFunctionReturn(0); 1796 } 1797 EXTERN_C_END 1798 1799 #undef __FUNCT__ 1800 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1801 /*@C 1802 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1803 the user should preallocate the matrix storage by setting the parameters 1804 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1805 performance can be increased by more than a factor of 50. 1806 1807 Collective on Mat 1808 1809 Input Parameters: 1810 + A - the matrix 1811 . bs - size of blockk 1812 . d_nz - number of block nonzeros per block row in diagonal portion of local 1813 submatrix (same for all local rows) 1814 . d_nnz - array containing the number of block nonzeros in the various block rows 1815 in the upper triangular and diagonal part of the in diagonal portion of the local 1816 (possibly different for each block row) or PETSC_NULL. You must leave room 1817 for the diagonal entry even if it is zero. 1818 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1819 submatrix (same for all local rows). 1820 - o_nnz - array containing the number of nonzeros in the various block rows of the 1821 off-diagonal portion of the local submatrix (possibly different for 1822 each block row) or PETSC_NULL. 1823 1824 1825 Options Database Keys: 1826 . -mat_no_unroll - uses code that does not unroll the loops in the 1827 block calculations (much slower) 1828 . -mat_block_size - size of the blocks to use 1829 1830 Notes: 1831 1832 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1833 than it must be used on all processors that share the object for that argument. 1834 1835 Storage Information: 1836 For a square global matrix we define each processor's diagonal portion 1837 to be its local rows and the corresponding columns (a square submatrix); 1838 each processor's off-diagonal portion encompasses the remainder of the 1839 local matrix (a rectangular submatrix). 1840 1841 The user can specify preallocated storage for the diagonal part of 1842 the local submatrix with either d_nz or d_nnz (not both). Set 1843 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1844 memory allocation. Likewise, specify preallocated storage for the 1845 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1846 1847 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1848 the figure below we depict these three local rows and all columns (0-11). 1849 1850 .vb 1851 0 1 2 3 4 5 6 7 8 9 10 11 1852 ------------------- 1853 row 3 | o o o d d d o o o o o o 1854 row 4 | o o o d d d o o o o o o 1855 row 5 | o o o d d d o o o o o o 1856 ------------------- 1857 .ve 1858 1859 Thus, any entries in the d locations are stored in the d (diagonal) 1860 submatrix, and any entries in the o locations are stored in the 1861 o (off-diagonal) submatrix. Note that the d matrix is stored in 1862 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1863 1864 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1865 plus the diagonal part of the d matrix, 1866 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1867 In general, for PDE problems in which most nonzeros are near the diagonal, 1868 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1869 or you will get TERRIBLE performance; see the users' manual chapter on 1870 matrices. 1871 1872 Level: intermediate 1873 1874 .keywords: matrix, block, aij, compressed row, sparse, parallel 1875 1876 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1877 @*/ 1878 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,const int d_nnz[],int o_nz,const int o_nnz[]) 1879 { 1880 int ierr,(*f)(Mat,int,int,const int[],int,const int[]); 1881 1882 PetscFunctionBegin; 1883 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1884 if (f) { 1885 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1886 } 1887 PetscFunctionReturn(0); 1888 } 1889 1890 #undef __FUNCT__ 1891 #define __FUNCT__ "MatCreateMPISBAIJ" 1892 /*@C 1893 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1894 (block compressed row). For good matrix assembly performance 1895 the user should preallocate the matrix storage by setting the parameters 1896 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1897 performance can be increased by more than a factor of 50. 1898 1899 Collective on MPI_Comm 1900 1901 Input Parameters: 1902 + comm - MPI communicator 1903 . bs - size of blockk 1904 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1905 This value should be the same as the local size used in creating the 1906 y vector for the matrix-vector product y = Ax. 1907 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1908 This value should be the same as the local size used in creating the 1909 x vector for the matrix-vector product y = Ax. 1910 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1911 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1912 . d_nz - number of block nonzeros per block row in diagonal portion of local 1913 submatrix (same for all local rows) 1914 . d_nnz - array containing the number of block nonzeros in the various block rows 1915 in the upper triangular portion of the in diagonal portion of the local 1916 (possibly different for each block block row) or PETSC_NULL. 1917 You must leave room for the diagonal entry even if it is zero. 1918 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1919 submatrix (same for all local rows). 1920 - o_nnz - array containing the number of nonzeros in the various block rows of the 1921 off-diagonal portion of the local submatrix (possibly different for 1922 each block row) or PETSC_NULL. 1923 1924 Output Parameter: 1925 . A - the matrix 1926 1927 Options Database Keys: 1928 . -mat_no_unroll - uses code that does not unroll the loops in the 1929 block calculations (much slower) 1930 . -mat_block_size - size of the blocks to use 1931 . -mat_mpi - use the parallel matrix data structures even on one processor 1932 (defaults to using SeqBAIJ format on one processor) 1933 1934 Notes: 1935 The user MUST specify either the local or global matrix dimensions 1936 (possibly both). 1937 1938 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1939 than it must be used on all processors that share the object for that argument. 1940 1941 Storage Information: 1942 For a square global matrix we define each processor's diagonal portion 1943 to be its local rows and the corresponding columns (a square submatrix); 1944 each processor's off-diagonal portion encompasses the remainder of the 1945 local matrix (a rectangular submatrix). 1946 1947 The user can specify preallocated storage for the diagonal part of 1948 the local submatrix with either d_nz or d_nnz (not both). Set 1949 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1950 memory allocation. Likewise, specify preallocated storage for the 1951 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1952 1953 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1954 the figure below we depict these three local rows and all columns (0-11). 1955 1956 .vb 1957 0 1 2 3 4 5 6 7 8 9 10 11 1958 ------------------- 1959 row 3 | o o o d d d o o o o o o 1960 row 4 | o o o d d d o o o o o o 1961 row 5 | o o o d d d o o o o o o 1962 ------------------- 1963 .ve 1964 1965 Thus, any entries in the d locations are stored in the d (diagonal) 1966 submatrix, and any entries in the o locations are stored in the 1967 o (off-diagonal) submatrix. Note that the d matrix is stored in 1968 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1969 1970 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1971 plus the diagonal part of the d matrix, 1972 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1973 In general, for PDE problems in which most nonzeros are near the diagonal, 1974 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1975 or you will get TERRIBLE performance; see the users' manual chapter on 1976 matrices. 1977 1978 Level: intermediate 1979 1980 .keywords: matrix, block, aij, compressed row, sparse, parallel 1981 1982 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1983 @*/ 1984 1985 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) 1986 { 1987 int ierr,size; 1988 1989 PetscFunctionBegin; 1990 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1991 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1992 if (size > 1) { 1993 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1994 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1995 } else { 1996 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1997 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1998 } 1999 PetscFunctionReturn(0); 2000 } 2001 2002 2003 #undef __FUNCT__ 2004 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 2005 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2006 { 2007 Mat mat; 2008 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 2009 int ierr,len=0; 2010 2011 PetscFunctionBegin; 2012 *newmat = 0; 2013 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2014 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 2015 mat->preallocated = PETSC_TRUE; 2016 a = (Mat_MPISBAIJ*)mat->data; 2017 a->bs = oldmat->bs; 2018 a->bs2 = oldmat->bs2; 2019 a->mbs = oldmat->mbs; 2020 a->nbs = oldmat->nbs; 2021 a->Mbs = oldmat->Mbs; 2022 a->Nbs = oldmat->Nbs; 2023 2024 a->rstart = oldmat->rstart; 2025 a->rend = oldmat->rend; 2026 a->cstart = oldmat->cstart; 2027 a->cend = oldmat->cend; 2028 a->size = oldmat->size; 2029 a->rank = oldmat->rank; 2030 a->donotstash = oldmat->donotstash; 2031 a->roworiented = oldmat->roworiented; 2032 a->rowindices = 0; 2033 a->rowvalues = 0; 2034 a->getrowactive = PETSC_FALSE; 2035 a->barray = 0; 2036 a->rstart_bs = oldmat->rstart_bs; 2037 a->rend_bs = oldmat->rend_bs; 2038 a->cstart_bs = oldmat->cstart_bs; 2039 a->cend_bs = oldmat->cend_bs; 2040 2041 /* hash table stuff */ 2042 a->ht = 0; 2043 a->hd = 0; 2044 a->ht_size = 0; 2045 a->ht_flag = oldmat->ht_flag; 2046 a->ht_fact = oldmat->ht_fact; 2047 a->ht_total_ct = 0; 2048 a->ht_insert_ct = 0; 2049 2050 ierr = PetscMalloc(3*(a->size+2)*sizeof(int),&a->rowners);CHKERRQ(ierr); 2051 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 2052 a->cowners = a->rowners + a->size + 2; 2053 a->rowners_bs = a->cowners + a->size + 2; 2054 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 2055 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2056 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 2057 if (oldmat->colmap) { 2058 #if defined (PETSC_USE_CTABLE) 2059 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2060 #else 2061 ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr); 2062 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2063 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 2064 #endif 2065 } else a->colmap = 0; 2066 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2067 ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr); 2068 PetscLogObjectMemory(mat,len*sizeof(int)); 2069 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 2070 } else a->garray = 0; 2071 2072 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2073 PetscLogObjectParent(mat,a->lvec); 2074 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2075 2076 PetscLogObjectParent(mat,a->Mvctx); 2077 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2078 PetscLogObjectParent(mat,a->A); 2079 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2080 PetscLogObjectParent(mat,a->B); 2081 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 2082 *newmat = mat; 2083 PetscFunctionReturn(0); 2084 } 2085 2086 #include "petscsys.h" 2087 2088 #undef __FUNCT__ 2089 #define __FUNCT__ "MatLoad_MPISBAIJ" 2090 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 2091 { 2092 Mat A; 2093 int i,nz,ierr,j,rstart,rend,fd; 2094 PetscScalar *vals,*buf; 2095 MPI_Comm comm = ((PetscObject)viewer)->comm; 2096 MPI_Status status; 2097 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2098 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 2099 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2100 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2101 int dcount,kmax,k,nzcount,tmp; 2102 2103 PetscFunctionBegin; 2104 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2105 2106 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2107 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2108 if (!rank) { 2109 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2110 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2111 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2112 if (header[3] < 0) { 2113 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2114 } 2115 } 2116 2117 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2118 M = header[1]; N = header[2]; 2119 2120 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2121 2122 /* 2123 This code adds extra rows to make sure the number of rows is 2124 divisible by the blocksize 2125 */ 2126 Mbs = M/bs; 2127 extra_rows = bs - M + bs*(Mbs); 2128 if (extra_rows == bs) extra_rows = 0; 2129 else Mbs++; 2130 if (extra_rows &&!rank) { 2131 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2132 } 2133 2134 /* determine ownership of all rows */ 2135 mbs = Mbs/size + ((Mbs % size) > rank); 2136 m = mbs*bs; 2137 ierr = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 2138 browners = rowners + size + 1; 2139 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2140 rowners[0] = 0; 2141 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2142 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2143 rstart = rowners[rank]; 2144 rend = rowners[rank+1]; 2145 2146 /* distribute row lengths to all processors */ 2147 ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr); 2148 if (!rank) { 2149 ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); 2150 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2151 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2152 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 2153 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2154 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2155 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2156 } else { 2157 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2158 } 2159 2160 if (!rank) { /* procs[0] */ 2161 /* calculate the number of nonzeros on each processor */ 2162 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 2163 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2164 for (i=0; i<size; i++) { 2165 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2166 procsnz[i] += rowlengths[j]; 2167 } 2168 } 2169 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2170 2171 /* determine max buffer needed and allocate it */ 2172 maxnz = 0; 2173 for (i=0; i<size; i++) { 2174 maxnz = PetscMax(maxnz,procsnz[i]); 2175 } 2176 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 2177 2178 /* read in my part of the matrix column indices */ 2179 nz = procsnz[0]; 2180 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2181 mycols = ibuf; 2182 if (size == 1) nz -= extra_rows; 2183 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2184 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2185 2186 /* read in every ones (except the last) and ship off */ 2187 for (i=1; i<size-1; i++) { 2188 nz = procsnz[i]; 2189 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2190 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2191 } 2192 /* read in the stuff for the last proc */ 2193 if (size != 1) { 2194 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2195 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2196 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2197 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2198 } 2199 ierr = PetscFree(cols);CHKERRQ(ierr); 2200 } else { /* procs[i], i>0 */ 2201 /* determine buffer space needed for message */ 2202 nz = 0; 2203 for (i=0; i<m; i++) { 2204 nz += locrowlens[i]; 2205 } 2206 ierr = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr); 2207 mycols = ibuf; 2208 /* receive message of column indices*/ 2209 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2210 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2211 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2212 } 2213 2214 /* loop over local rows, determining number of off diagonal entries */ 2215 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2216 odlens = dlens + (rend-rstart); 2217 ierr = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr); 2218 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2219 masked1 = mask + Mbs; 2220 masked2 = masked1 + Mbs; 2221 rowcount = 0; nzcount = 0; 2222 for (i=0; i<mbs; i++) { 2223 dcount = 0; 2224 odcount = 0; 2225 for (j=0; j<bs; j++) { 2226 kmax = locrowlens[rowcount]; 2227 for (k=0; k<kmax; k++) { 2228 tmp = mycols[nzcount++]/bs; /* block col. index */ 2229 if (!mask[tmp]) { 2230 mask[tmp] = 1; 2231 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2232 else masked1[dcount++] = tmp; /* entry in diag portion */ 2233 } 2234 } 2235 rowcount++; 2236 } 2237 2238 dlens[i] = dcount; /* d_nzz[i] */ 2239 odlens[i] = odcount; /* o_nzz[i] */ 2240 2241 /* zero out the mask elements we set */ 2242 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2243 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2244 } 2245 2246 /* create our matrix */ 2247 ierr = MatCreate(comm,m,m,PETSC_DETERMINE,PETSC_DETERMINE,&A);CHKERRQ(ierr); 2248 ierr = MatSetType(A,type);CHKERRQ(ierr); 2249 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2250 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2251 2252 if (!rank) { 2253 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2254 /* read in my part of the matrix numerical values */ 2255 nz = procsnz[0]; 2256 vals = buf; 2257 mycols = ibuf; 2258 if (size == 1) nz -= extra_rows; 2259 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2260 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2261 2262 /* insert into matrix */ 2263 jj = rstart*bs; 2264 for (i=0; i<m; i++) { 2265 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2266 mycols += locrowlens[i]; 2267 vals += locrowlens[i]; 2268 jj++; 2269 } 2270 2271 /* read in other processors (except the last one) and ship out */ 2272 for (i=1; i<size-1; i++) { 2273 nz = procsnz[i]; 2274 vals = buf; 2275 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2276 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2277 } 2278 /* the last proc */ 2279 if (size != 1){ 2280 nz = procsnz[i] - extra_rows; 2281 vals = buf; 2282 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2283 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2284 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2285 } 2286 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2287 2288 } else { 2289 /* receive numeric values */ 2290 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2291 2292 /* receive message of values*/ 2293 vals = buf; 2294 mycols = ibuf; 2295 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2296 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2297 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2298 2299 /* insert into matrix */ 2300 jj = rstart*bs; 2301 for (i=0; i<m; i++) { 2302 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2303 mycols += locrowlens[i]; 2304 vals += locrowlens[i]; 2305 jj++; 2306 } 2307 } 2308 2309 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2310 ierr = PetscFree(buf);CHKERRQ(ierr); 2311 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2312 ierr = PetscFree(rowners);CHKERRQ(ierr); 2313 ierr = PetscFree(dlens);CHKERRQ(ierr); 2314 ierr = PetscFree(mask);CHKERRQ(ierr); 2315 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2316 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2317 *newmat = A; 2318 PetscFunctionReturn(0); 2319 } 2320 2321 #undef __FUNCT__ 2322 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2323 /*@ 2324 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2325 2326 Input Parameters: 2327 . mat - the matrix 2328 . fact - factor 2329 2330 Collective on Mat 2331 2332 Level: advanced 2333 2334 Notes: 2335 This can also be set by the command line option: -mat_use_hash_table fact 2336 2337 .keywords: matrix, hashtable, factor, HT 2338 2339 .seealso: MatSetOption() 2340 @*/ 2341 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2342 { 2343 PetscFunctionBegin; 2344 SETERRQ(1,"Function not yet written for SBAIJ format"); 2345 /* PetscFunctionReturn(0); */ 2346 } 2347 2348 #undef __FUNCT__ 2349 #define __FUNCT__ "MatGetRowMax_MPISBAIJ" 2350 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2351 { 2352 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2353 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2354 PetscReal atmp; 2355 PetscReal *work,*svalues,*rvalues; 2356 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2357 int rank,size,*rowners_bs,dest,count,source; 2358 PetscScalar *va; 2359 MatScalar *ba; 2360 MPI_Status stat; 2361 2362 PetscFunctionBegin; 2363 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2364 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2365 2366 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2367 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2368 2369 bs = a->bs; 2370 mbs = a->mbs; 2371 Mbs = a->Mbs; 2372 ba = b->a; 2373 bi = b->i; 2374 bj = b->j; 2375 /* 2376 PetscSynchronizedPrintf(A->comm,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2377 PetscSynchronizedFlush(A->comm); 2378 */ 2379 2380 /* find ownerships */ 2381 rowners_bs = a->rowners_bs; 2382 /* 2383 if (!rank){ 2384 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2385 } 2386 */ 2387 2388 /* each proc creates an array to be distributed */ 2389 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2390 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2391 2392 /* row_max for B */ 2393 if (rank != size-1){ 2394 for (i=0; i<mbs; i++) { 2395 ncols = bi[1] - bi[0]; bi++; 2396 brow = bs*i; 2397 for (j=0; j<ncols; j++){ 2398 bcol = bs*(*bj); 2399 for (kcol=0; kcol<bs; kcol++){ 2400 col = bcol + kcol; /* local col index */ 2401 col += rowners_bs[rank+1]; /* global col index */ 2402 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2403 for (krow=0; krow<bs; krow++){ 2404 atmp = PetscAbsScalar(*ba); ba++; 2405 row = brow + krow; /* local row index */ 2406 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2407 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2408 if (work[col] < atmp) work[col] = atmp; 2409 } 2410 } 2411 bj++; 2412 } 2413 } 2414 /* 2415 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2416 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2417 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2418 */ 2419 2420 /* send values to its owners */ 2421 for (dest=rank+1; dest<size; dest++){ 2422 svalues = work + rowners_bs[dest]; 2423 count = rowners_bs[dest+1]-rowners_bs[dest]; 2424 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,A->comm);CHKERRQ(ierr); 2425 /* 2426 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]); 2427 PetscSynchronizedFlush(A->comm); 2428 */ 2429 } 2430 } 2431 2432 /* receive values */ 2433 if (rank){ 2434 rvalues = work; 2435 count = rowners_bs[rank+1]-rowners_bs[rank]; 2436 for (source=0; source<rank; source++){ 2437 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,A->comm,&stat);CHKERRQ(ierr); 2438 /* process values */ 2439 for (i=0; i<count; i++){ 2440 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2441 } 2442 /* 2443 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]); 2444 PetscSynchronizedFlush(A->comm); 2445 */ 2446 } 2447 } 2448 2449 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2450 ierr = PetscFree(work);CHKERRQ(ierr); 2451 PetscFunctionReturn(0); 2452 } 2453 2454 #undef __FUNCT__ 2455 #define __FUNCT__ "MatRelax_MPISBAIJ" 2456 int MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2457 { 2458 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2459 int ierr,mbs=mat->mbs,bs=mat->bs; 2460 PetscScalar mone=-1.0,*x,*b,*ptr,zero=0.0; 2461 Vec bb1; 2462 2463 PetscFunctionBegin; 2464 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2465 if (bs > 1) 2466 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2467 2468 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2469 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2470 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2471 its--; 2472 } 2473 2474 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2475 while (its--){ 2476 2477 /* lower triangular part: slvec0b = - B^T*xx */ 2478 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2479 2480 /* copy xx into slvec0a */ 2481 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2482 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2483 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2484 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2485 2486 ierr = VecScale(&mone,mat->slvec0);CHKERRQ(ierr); 2487 2488 /* copy bb into slvec1a */ 2489 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2490 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2491 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2492 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2493 2494 /* set slvec1b = 0 */ 2495 ierr = VecSet(&zero,mat->slvec1b);CHKERRQ(ierr); 2496 2497 ierr = VecScatterBegin(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2498 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2499 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2500 ierr = VecScatterEnd(mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD,mat->sMvctx);CHKERRQ(ierr); 2501 2502 /* upper triangular part: bb1 = bb1 - B*x */ 2503 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2504 2505 /* local diagonal sweep */ 2506 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2507 } 2508 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2509 } else { 2510 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2511 } 2512 PetscFunctionReturn(0); 2513 } 2514 2515 #undef __FUNCT__ 2516 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2517 int MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 2518 { 2519 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2520 int ierr; 2521 PetscScalar mone=-1.0; 2522 Vec lvec1,bb1; 2523 2524 PetscFunctionBegin; 2525 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 2526 if (mat->bs > 1) 2527 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2528 2529 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2530 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2531 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2532 its--; 2533 } 2534 2535 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2536 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2537 while (its--){ 2538 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2539 2540 /* lower diagonal part: bb1 = bb - B^T*xx */ 2541 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2542 ierr = VecScale(&mone,lvec1);CHKERRQ(ierr); 2543 2544 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 2545 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2546 ierr = VecScatterBegin(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2547 2548 /* upper diagonal part: bb1 = bb1 - B*x */ 2549 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 2550 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2551 2552 ierr = VecScatterEnd(lvec1,bb1,ADD_VALUES,SCATTER_REVERSE,mat->Mvctx);CHKERRQ(ierr); 2553 2554 /* diagonal sweep */ 2555 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2556 } 2557 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2558 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2559 } else { 2560 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2561 } 2562 PetscFunctionReturn(0); 2563 } 2564 2565