1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 #if defined(PETSC_HAVE_HYPRE) 8 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 9 #endif 10 11 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 12 { 13 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 14 PetscErrorCode ierr; 15 PetscInt i,*idxb = 0; 16 PetscScalar *va,*vb; 17 Vec vtmp; 18 19 PetscFunctionBegin; 20 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 21 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 22 if (idx) { 23 for (i=0; i<A->rmap->n; i++) { 24 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 25 } 26 } 27 28 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 29 if (idx) {ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr);} 30 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 31 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 32 33 for (i=0; i<A->rmap->n; i++) { 34 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 35 va[i] = vb[i]; 36 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 37 } 38 } 39 40 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 41 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 42 ierr = PetscFree(idxb);CHKERRQ(ierr); 43 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 44 PetscFunctionReturn(0); 45 } 46 47 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 48 { 49 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 58 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 59 { 60 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 61 PetscErrorCode ierr; 62 63 PetscFunctionBegin; 64 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 65 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 66 PetscFunctionReturn(0); 67 } 68 69 /* 70 Local utility routine that creates a mapping from the global column 71 number to the local number in the off-diagonal part of the local 72 storage of the matrix. This is done in a non scalable way since the 73 length of colmap equals the global matrix length. 74 */ 75 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 76 { 77 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 78 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 79 PetscErrorCode ierr; 80 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 81 82 PetscFunctionBegin; 83 #if defined(PETSC_USE_CTABLE) 84 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 85 for (i=0; i<nbs; i++) { 86 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 87 } 88 #else 89 ierr = PetscCalloc1(baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 90 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 91 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 92 #endif 93 PetscFunctionReturn(0); 94 } 95 96 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol) \ 97 { \ 98 brow = row/bs; \ 99 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 100 rmax = aimax[brow]; nrow = ailen[brow]; \ 101 bcol = col/bs; \ 102 ridx = row % bs; cidx = col % bs; \ 103 low = 0; high = nrow; \ 104 while (high-low > 3) { \ 105 t = (low+high)/2; \ 106 if (rp[t] > bcol) high = t; \ 107 else low = t; \ 108 } \ 109 for (_i=low; _i<high; _i++) { \ 110 if (rp[_i] > bcol) break; \ 111 if (rp[_i] == bcol) { \ 112 bap = ap + bs2*_i + bs*cidx + ridx; \ 113 if (addv == ADD_VALUES) *bap += value; \ 114 else *bap = value; \ 115 goto a_noinsert; \ 116 } \ 117 } \ 118 if (a->nonew == 1) goto a_noinsert; \ 119 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 120 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 121 N = nrow++ - 1; \ 122 /* shift up all the later entries in this row */ \ 123 ierr = PetscArraymove(rp+_i+1,rp+_i,N-_i+1);CHKERRQ(ierr);\ 124 ierr = PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1));CHKERRQ(ierr); \ 125 ierr = PetscArrayzero(ap+bs2*_i,bs2);CHKERRQ(ierr); \ 126 rp[_i] = bcol; \ 127 ap[bs2*_i + bs*cidx + ridx] = value; \ 128 a_noinsert:; \ 129 ailen[brow] = nrow; \ 130 } 131 132 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol) \ 133 { \ 134 brow = row/bs; \ 135 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 136 rmax = bimax[brow]; nrow = bilen[brow]; \ 137 bcol = col/bs; \ 138 ridx = row % bs; cidx = col % bs; \ 139 low = 0; high = nrow; \ 140 while (high-low > 3) { \ 141 t = (low+high)/2; \ 142 if (rp[t] > bcol) high = t; \ 143 else low = t; \ 144 } \ 145 for (_i=low; _i<high; _i++) { \ 146 if (rp[_i] > bcol) break; \ 147 if (rp[_i] == bcol) { \ 148 bap = ap + bs2*_i + bs*cidx + ridx; \ 149 if (addv == ADD_VALUES) *bap += value; \ 150 else *bap = value; \ 151 goto b_noinsert; \ 152 } \ 153 } \ 154 if (b->nonew == 1) goto b_noinsert; \ 155 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 156 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 157 N = nrow++ - 1; \ 158 /* shift up all the later entries in this row */ \ 159 ierr = PetscArraymove(rp+_i+1,rp+_i,N-_i+1);CHKERRQ(ierr);\ 160 ierr = PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1));CHKERRQ(ierr);\ 161 ierr = PetscArrayzero(ap+bs2*_i,bs2);CHKERRQ(ierr); \ 162 rp[_i] = bcol; \ 163 ap[bs2*_i + bs*cidx + ridx] = value; \ 164 b_noinsert:; \ 165 bilen[brow] = nrow; \ 166 } 167 168 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 169 { 170 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 171 MatScalar value; 172 PetscBool roworiented = baij->roworiented; 173 PetscErrorCode ierr; 174 PetscInt i,j,row,col; 175 PetscInt rstart_orig=mat->rmap->rstart; 176 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 177 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 178 179 /* Some Variables required in the macro */ 180 Mat A = baij->A; 181 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 182 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 183 MatScalar *aa =a->a; 184 185 Mat B = baij->B; 186 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 187 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 188 MatScalar *ba =b->a; 189 190 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 191 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 192 MatScalar *ap,*bap; 193 194 PetscFunctionBegin; 195 for (i=0; i<m; i++) { 196 if (im[i] < 0) continue; 197 #if defined(PETSC_USE_DEBUG) 198 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 199 #endif 200 if (im[i] >= rstart_orig && im[i] < rend_orig) { 201 row = im[i] - rstart_orig; 202 for (j=0; j<n; j++) { 203 if (in[j] >= cstart_orig && in[j] < cend_orig) { 204 col = in[j] - cstart_orig; 205 if (roworiented) value = v[i*n+j]; 206 else value = v[i+j*m]; 207 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]); 208 } else if (in[j] < 0) continue; 209 #if defined(PETSC_USE_DEBUG) 210 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 211 #endif 212 else { 213 if (mat->was_assembled) { 214 if (!baij->colmap) { 215 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 216 } 217 #if defined(PETSC_USE_CTABLE) 218 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 219 col = col - 1; 220 #else 221 col = baij->colmap[in[j]/bs] - 1; 222 #endif 223 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 224 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 225 col = in[j]; 226 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 227 B = baij->B; 228 b = (Mat_SeqBAIJ*)(B)->data; 229 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 230 ba =b->a; 231 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 232 else col += in[j]%bs; 233 } else col = in[j]; 234 if (roworiented) value = v[i*n+j]; 235 else value = v[i+j*m]; 236 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]); 237 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 238 } 239 } 240 } else { 241 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 242 if (!baij->donotstash) { 243 mat->assembled = PETSC_FALSE; 244 if (roworiented) { 245 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 246 } else { 247 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 248 } 249 } 250 } 251 } 252 PetscFunctionReturn(0); 253 } 254 255 PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol) 256 { 257 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 258 PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N; 259 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 260 PetscErrorCode ierr; 261 PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs; 262 PetscBool roworiented=a->roworiented; 263 const PetscScalar *value = v; 264 MatScalar *ap,*aa = a->a,*bap; 265 266 PetscFunctionBegin; 267 rp = aj + ai[row]; 268 ap = aa + bs2*ai[row]; 269 rmax = imax[row]; 270 nrow = ailen[row]; 271 value = v; 272 low = 0; 273 high = nrow; 274 while (high-low > 7) { 275 t = (low+high)/2; 276 if (rp[t] > col) high = t; 277 else low = t; 278 } 279 for (i=low; i<high; i++) { 280 if (rp[i] > col) break; 281 if (rp[i] == col) { 282 bap = ap + bs2*i; 283 if (roworiented) { 284 if (is == ADD_VALUES) { 285 for (ii=0; ii<bs; ii++) { 286 for (jj=ii; jj<bs2; jj+=bs) { 287 bap[jj] += *value++; 288 } 289 } 290 } else { 291 for (ii=0; ii<bs; ii++) { 292 for (jj=ii; jj<bs2; jj+=bs) { 293 bap[jj] = *value++; 294 } 295 } 296 } 297 } else { 298 if (is == ADD_VALUES) { 299 for (ii=0; ii<bs; ii++,value+=bs) { 300 for (jj=0; jj<bs; jj++) { 301 bap[jj] += value[jj]; 302 } 303 bap += bs; 304 } 305 } else { 306 for (ii=0; ii<bs; ii++,value+=bs) { 307 for (jj=0; jj<bs; jj++) { 308 bap[jj] = value[jj]; 309 } 310 bap += bs; 311 } 312 } 313 } 314 goto noinsert2; 315 } 316 } 317 if (nonew == 1) goto noinsert2; 318 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol); 319 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 320 N = nrow++ - 1; high++; 321 /* shift up all the later entries in this row */ 322 ierr = PetscArraymove(rp+i+1,rp+i,N-i+1);CHKERRQ(ierr); 323 ierr = PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));CHKERRQ(ierr); 324 rp[i] = col; 325 bap = ap + bs2*i; 326 if (roworiented) { 327 for (ii=0; ii<bs; ii++) { 328 for (jj=ii; jj<bs2; jj+=bs) { 329 bap[jj] = *value++; 330 } 331 } 332 } else { 333 for (ii=0; ii<bs; ii++) { 334 for (jj=0; jj<bs; jj++) { 335 *bap++ = *value++; 336 } 337 } 338 } 339 noinsert2:; 340 ailen[row] = nrow; 341 PetscFunctionReturn(0); 342 } 343 344 /* 345 This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed 346 by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine 347 */ 348 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 349 { 350 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 351 const PetscScalar *value; 352 MatScalar *barray = baij->barray; 353 PetscBool roworiented = baij->roworiented; 354 PetscErrorCode ierr; 355 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 356 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 357 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 358 359 PetscFunctionBegin; 360 if (!barray) { 361 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 362 baij->barray = barray; 363 } 364 365 if (roworiented) stepval = (n-1)*bs; 366 else stepval = (m-1)*bs; 367 368 for (i=0; i<m; i++) { 369 if (im[i] < 0) continue; 370 #if defined(PETSC_USE_DEBUG) 371 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1); 372 #endif 373 if (im[i] >= rstart && im[i] < rend) { 374 row = im[i] - rstart; 375 for (j=0; j<n; j++) { 376 /* If NumCol = 1 then a copy is not required */ 377 if ((roworiented) && (n == 1)) { 378 barray = (MatScalar*)v + i*bs2; 379 } else if ((!roworiented) && (m == 1)) { 380 barray = (MatScalar*)v + j*bs2; 381 } else { /* Here a copy is required */ 382 if (roworiented) { 383 value = v + (i*(stepval+bs) + j)*bs; 384 } else { 385 value = v + (j*(stepval+bs) + i)*bs; 386 } 387 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 388 for (jj=0; jj<bs; jj++) barray[jj] = value[jj]; 389 barray += bs; 390 } 391 barray -= bs2; 392 } 393 394 if (in[j] >= cstart && in[j] < cend) { 395 col = in[j] - cstart; 396 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 397 } else if (in[j] < 0) continue; 398 #if defined(PETSC_USE_DEBUG) 399 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1); 400 #endif 401 else { 402 if (mat->was_assembled) { 403 if (!baij->colmap) { 404 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 405 } 406 407 #if defined(PETSC_USE_DEBUG) 408 #if defined(PETSC_USE_CTABLE) 409 { PetscInt data; 410 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 411 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 412 } 413 #else 414 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 415 #endif 416 #endif 417 #if defined(PETSC_USE_CTABLE) 418 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 419 col = (col - 1)/bs; 420 #else 421 col = (baij->colmap[in[j]] - 1)/bs; 422 #endif 423 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 424 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 425 col = in[j]; 426 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked indexed nonzero block (%D, %D) into matrix",im[i],in[j]); 427 } else col = in[j]; 428 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 429 } 430 } 431 } else { 432 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 433 if (!baij->donotstash) { 434 if (roworiented) { 435 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 436 } else { 437 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 438 } 439 } 440 } 441 } 442 PetscFunctionReturn(0); 443 } 444 445 #define HASH_KEY 0.6180339887 446 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 447 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 448 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 449 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 450 { 451 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 452 PetscBool roworiented = baij->roworiented; 453 PetscErrorCode ierr; 454 PetscInt i,j,row,col; 455 PetscInt rstart_orig=mat->rmap->rstart; 456 PetscInt rend_orig =mat->rmap->rend,Nbs=baij->Nbs; 457 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 458 PetscReal tmp; 459 MatScalar **HD = baij->hd,value; 460 #if defined(PETSC_USE_DEBUG) 461 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 462 #endif 463 464 PetscFunctionBegin; 465 for (i=0; i<m; i++) { 466 #if defined(PETSC_USE_DEBUG) 467 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 468 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 469 #endif 470 row = im[i]; 471 if (row >= rstart_orig && row < rend_orig) { 472 for (j=0; j<n; j++) { 473 col = in[j]; 474 if (roworiented) value = v[i*n+j]; 475 else value = v[i+j*m]; 476 /* Look up PetscInto the Hash Table */ 477 key = (row/bs)*Nbs+(col/bs)+1; 478 h1 = HASH(size,key,tmp); 479 480 481 idx = h1; 482 #if defined(PETSC_USE_DEBUG) 483 insert_ct++; 484 total_ct++; 485 if (HT[idx] != key) { 486 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 487 if (idx == size) { 488 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 489 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 490 } 491 } 492 #else 493 if (HT[idx] != key) { 494 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 495 if (idx == size) { 496 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 497 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 498 } 499 } 500 #endif 501 /* A HASH table entry is found, so insert the values at the correct address */ 502 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 503 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 504 } 505 } else if (!baij->donotstash) { 506 if (roworiented) { 507 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 508 } else { 509 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 510 } 511 } 512 } 513 #if defined(PETSC_USE_DEBUG) 514 baij->ht_total_ct += total_ct; 515 baij->ht_insert_ct += insert_ct; 516 #endif 517 PetscFunctionReturn(0); 518 } 519 520 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 521 { 522 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 523 PetscBool roworiented = baij->roworiented; 524 PetscErrorCode ierr; 525 PetscInt i,j,ii,jj,row,col; 526 PetscInt rstart=baij->rstartbs; 527 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 528 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 529 PetscReal tmp; 530 MatScalar **HD = baij->hd,*baij_a; 531 const PetscScalar *v_t,*value; 532 #if defined(PETSC_USE_DEBUG) 533 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 534 #endif 535 536 PetscFunctionBegin; 537 if (roworiented) stepval = (n-1)*bs; 538 else stepval = (m-1)*bs; 539 540 for (i=0; i<m; i++) { 541 #if defined(PETSC_USE_DEBUG) 542 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 543 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 544 #endif 545 row = im[i]; 546 v_t = v + i*nbs2; 547 if (row >= rstart && row < rend) { 548 for (j=0; j<n; j++) { 549 col = in[j]; 550 551 /* Look up into the Hash Table */ 552 key = row*Nbs+col+1; 553 h1 = HASH(size,key,tmp); 554 555 idx = h1; 556 #if defined(PETSC_USE_DEBUG) 557 total_ct++; 558 insert_ct++; 559 if (HT[idx] != key) { 560 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 561 if (idx == size) { 562 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 563 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 564 } 565 } 566 #else 567 if (HT[idx] != key) { 568 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 569 if (idx == size) { 570 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 571 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 572 } 573 } 574 #endif 575 baij_a = HD[idx]; 576 if (roworiented) { 577 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 578 /* value = v + (i*(stepval+bs)+j)*bs; */ 579 value = v_t; 580 v_t += bs; 581 if (addv == ADD_VALUES) { 582 for (ii=0; ii<bs; ii++,value+=stepval) { 583 for (jj=ii; jj<bs2; jj+=bs) { 584 baij_a[jj] += *value++; 585 } 586 } 587 } else { 588 for (ii=0; ii<bs; ii++,value+=stepval) { 589 for (jj=ii; jj<bs2; jj+=bs) { 590 baij_a[jj] = *value++; 591 } 592 } 593 } 594 } else { 595 value = v + j*(stepval+bs)*bs + i*bs; 596 if (addv == ADD_VALUES) { 597 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 598 for (jj=0; jj<bs; jj++) { 599 baij_a[jj] += *value++; 600 } 601 } 602 } else { 603 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 604 for (jj=0; jj<bs; jj++) { 605 baij_a[jj] = *value++; 606 } 607 } 608 } 609 } 610 } 611 } else { 612 if (!baij->donotstash) { 613 if (roworiented) { 614 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 615 } else { 616 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 617 } 618 } 619 } 620 } 621 #if defined(PETSC_USE_DEBUG) 622 baij->ht_total_ct += total_ct; 623 baij->ht_insert_ct += insert_ct; 624 #endif 625 PetscFunctionReturn(0); 626 } 627 628 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 629 { 630 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 631 PetscErrorCode ierr; 632 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 633 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 634 635 PetscFunctionBegin; 636 for (i=0; i<m; i++) { 637 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 638 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 639 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 640 row = idxm[i] - bsrstart; 641 for (j=0; j<n; j++) { 642 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 643 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 644 if (idxn[j] >= bscstart && idxn[j] < bscend) { 645 col = idxn[j] - bscstart; 646 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 647 } else { 648 if (!baij->colmap) { 649 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 650 } 651 #if defined(PETSC_USE_CTABLE) 652 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 653 data--; 654 #else 655 data = baij->colmap[idxn[j]/bs]-1; 656 #endif 657 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 658 else { 659 col = data + idxn[j]%bs; 660 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 661 } 662 } 663 } 664 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 665 } 666 PetscFunctionReturn(0); 667 } 668 669 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 670 { 671 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 672 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 673 PetscErrorCode ierr; 674 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 675 PetscReal sum = 0.0; 676 MatScalar *v; 677 678 PetscFunctionBegin; 679 if (baij->size == 1) { 680 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 681 } else { 682 if (type == NORM_FROBENIUS) { 683 v = amat->a; 684 nz = amat->nz*bs2; 685 for (i=0; i<nz; i++) { 686 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 687 } 688 v = bmat->a; 689 nz = bmat->nz*bs2; 690 for (i=0; i<nz; i++) { 691 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 692 } 693 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 694 *nrm = PetscSqrtReal(*nrm); 695 } else if (type == NORM_1) { /* max column sum */ 696 PetscReal *tmp,*tmp2; 697 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 698 ierr = PetscCalloc1(mat->cmap->N,&tmp);CHKERRQ(ierr); 699 ierr = PetscMalloc1(mat->cmap->N,&tmp2);CHKERRQ(ierr); 700 v = amat->a; jj = amat->j; 701 for (i=0; i<amat->nz; i++) { 702 for (j=0; j<bs; j++) { 703 col = bs*(cstart + *jj) + j; /* column index */ 704 for (row=0; row<bs; row++) { 705 tmp[col] += PetscAbsScalar(*v); v++; 706 } 707 } 708 jj++; 709 } 710 v = bmat->a; jj = bmat->j; 711 for (i=0; i<bmat->nz; i++) { 712 for (j=0; j<bs; j++) { 713 col = bs*garray[*jj] + j; 714 for (row=0; row<bs; row++) { 715 tmp[col] += PetscAbsScalar(*v); v++; 716 } 717 } 718 jj++; 719 } 720 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 721 *nrm = 0.0; 722 for (j=0; j<mat->cmap->N; j++) { 723 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 724 } 725 ierr = PetscFree(tmp);CHKERRQ(ierr); 726 ierr = PetscFree(tmp2);CHKERRQ(ierr); 727 } else if (type == NORM_INFINITY) { /* max row sum */ 728 PetscReal *sums; 729 ierr = PetscMalloc1(bs,&sums);CHKERRQ(ierr); 730 sum = 0.0; 731 for (j=0; j<amat->mbs; j++) { 732 for (row=0; row<bs; row++) sums[row] = 0.0; 733 v = amat->a + bs2*amat->i[j]; 734 nz = amat->i[j+1]-amat->i[j]; 735 for (i=0; i<nz; i++) { 736 for (col=0; col<bs; col++) { 737 for (row=0; row<bs; row++) { 738 sums[row] += PetscAbsScalar(*v); v++; 739 } 740 } 741 } 742 v = bmat->a + bs2*bmat->i[j]; 743 nz = bmat->i[j+1]-bmat->i[j]; 744 for (i=0; i<nz; i++) { 745 for (col=0; col<bs; col++) { 746 for (row=0; row<bs; row++) { 747 sums[row] += PetscAbsScalar(*v); v++; 748 } 749 } 750 } 751 for (row=0; row<bs; row++) { 752 if (sums[row] > sum) sum = sums[row]; 753 } 754 } 755 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 756 ierr = PetscFree(sums);CHKERRQ(ierr); 757 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 758 } 759 PetscFunctionReturn(0); 760 } 761 762 /* 763 Creates the hash table, and sets the table 764 This table is created only once. 765 If new entried need to be added to the matrix 766 then the hash table has to be destroyed and 767 recreated. 768 */ 769 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 770 { 771 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 772 Mat A = baij->A,B=baij->B; 773 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 774 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 775 PetscErrorCode ierr; 776 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 777 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 778 PetscInt *HT,key; 779 MatScalar **HD; 780 PetscReal tmp; 781 #if defined(PETSC_USE_INFO) 782 PetscInt ct=0,max=0; 783 #endif 784 785 PetscFunctionBegin; 786 if (baij->ht) PetscFunctionReturn(0); 787 788 baij->ht_size = (PetscInt)(factor*nz); 789 ht_size = baij->ht_size; 790 791 /* Allocate Memory for Hash Table */ 792 ierr = PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);CHKERRQ(ierr); 793 HD = baij->hd; 794 HT = baij->ht; 795 796 /* Loop Over A */ 797 for (i=0; i<a->mbs; i++) { 798 for (j=ai[i]; j<ai[i+1]; j++) { 799 row = i+rstart; 800 col = aj[j]+cstart; 801 802 key = row*Nbs + col + 1; 803 h1 = HASH(ht_size,key,tmp); 804 for (k=0; k<ht_size; k++) { 805 if (!HT[(h1+k)%ht_size]) { 806 HT[(h1+k)%ht_size] = key; 807 HD[(h1+k)%ht_size] = a->a + j*bs2; 808 break; 809 #if defined(PETSC_USE_INFO) 810 } else { 811 ct++; 812 #endif 813 } 814 } 815 #if defined(PETSC_USE_INFO) 816 if (k> max) max = k; 817 #endif 818 } 819 } 820 /* Loop Over B */ 821 for (i=0; i<b->mbs; i++) { 822 for (j=bi[i]; j<bi[i+1]; j++) { 823 row = i+rstart; 824 col = garray[bj[j]]; 825 key = row*Nbs + col + 1; 826 h1 = HASH(ht_size,key,tmp); 827 for (k=0; k<ht_size; k++) { 828 if (!HT[(h1+k)%ht_size]) { 829 HT[(h1+k)%ht_size] = key; 830 HD[(h1+k)%ht_size] = b->a + j*bs2; 831 break; 832 #if defined(PETSC_USE_INFO) 833 } else { 834 ct++; 835 #endif 836 } 837 } 838 #if defined(PETSC_USE_INFO) 839 if (k> max) max = k; 840 #endif 841 } 842 } 843 844 /* Print Summary */ 845 #if defined(PETSC_USE_INFO) 846 for (i=0,j=0; i<ht_size; i++) { 847 if (HT[i]) j++; 848 } 849 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 850 #endif 851 PetscFunctionReturn(0); 852 } 853 854 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 855 { 856 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 857 PetscErrorCode ierr; 858 PetscInt nstash,reallocs; 859 860 PetscFunctionBegin; 861 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 862 863 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 864 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 865 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 866 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 867 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 868 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 869 PetscFunctionReturn(0); 870 } 871 872 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 873 { 874 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 875 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 876 PetscErrorCode ierr; 877 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 878 PetscInt *row,*col; 879 PetscBool r1,r2,r3,other_disassembled; 880 MatScalar *val; 881 PetscMPIInt n; 882 883 PetscFunctionBegin; 884 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 885 if (!baij->donotstash && !mat->nooffprocentries) { 886 while (1) { 887 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 888 if (!flg) break; 889 890 for (i=0; i<n;) { 891 /* Now identify the consecutive vals belonging to the same row */ 892 for (j=i,rstart=row[j]; j<n; j++) { 893 if (row[j] != rstart) break; 894 } 895 if (j < n) ncols = j-i; 896 else ncols = n-i; 897 /* Now assemble all these values with a single function call */ 898 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 899 i = j; 900 } 901 } 902 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 903 /* Now process the block-stash. Since the values are stashed column-oriented, 904 set the roworiented flag to column oriented, and after MatSetValues() 905 restore the original flags */ 906 r1 = baij->roworiented; 907 r2 = a->roworiented; 908 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 909 910 baij->roworiented = PETSC_FALSE; 911 a->roworiented = PETSC_FALSE; 912 913 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 914 while (1) { 915 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 916 if (!flg) break; 917 918 for (i=0; i<n;) { 919 /* Now identify the consecutive vals belonging to the same row */ 920 for (j=i,rstart=row[j]; j<n; j++) { 921 if (row[j] != rstart) break; 922 } 923 if (j < n) ncols = j-i; 924 else ncols = n-i; 925 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);CHKERRQ(ierr); 926 i = j; 927 } 928 } 929 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 930 931 baij->roworiented = r1; 932 a->roworiented = r2; 933 934 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 935 } 936 937 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 938 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 939 940 /* determine if any processor has disassembled, if so we must 941 also disassemble ourselfs, in order that we may reassemble. */ 942 /* 943 if nonzero structure of submatrix B cannot change then we know that 944 no processor disassembled thus we can skip this stuff 945 */ 946 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 947 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 948 if (mat->was_assembled && !other_disassembled) { 949 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 950 } 951 } 952 953 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 954 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 955 } 956 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 957 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 958 959 #if defined(PETSC_USE_INFO) 960 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 961 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",(double)((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 962 963 baij->ht_total_ct = 0; 964 baij->ht_insert_ct = 0; 965 } 966 #endif 967 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 968 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 969 970 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 971 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 972 } 973 974 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 975 976 baij->rowvalues = 0; 977 978 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 979 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 980 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 981 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 982 } 983 PetscFunctionReturn(0); 984 } 985 986 extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer); 987 #include <petscdraw.h> 988 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 989 { 990 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 991 PetscErrorCode ierr; 992 PetscMPIInt rank = baij->rank; 993 PetscInt bs = mat->rmap->bs; 994 PetscBool iascii,isdraw; 995 PetscViewer sviewer; 996 PetscViewerFormat format; 997 998 PetscFunctionBegin; 999 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1000 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1001 if (iascii) { 1002 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1003 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1004 MatInfo info; 1005 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1006 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1007 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1008 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %g\n", 1009 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);CHKERRQ(ierr); 1010 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1011 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1012 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1013 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1014 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1015 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1016 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1017 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 1018 PetscFunctionReturn(0); 1019 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1020 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1021 PetscFunctionReturn(0); 1022 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1023 PetscFunctionReturn(0); 1024 } 1025 } 1026 1027 if (isdraw) { 1028 PetscDraw draw; 1029 PetscBool isnull; 1030 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1031 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1032 if (isnull) PetscFunctionReturn(0); 1033 } 1034 1035 { 1036 /* assemble the entire matrix onto first processor. */ 1037 Mat A; 1038 Mat_SeqBAIJ *Aloc; 1039 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1040 MatScalar *a; 1041 const char *matname; 1042 1043 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1044 /* Perhaps this should be the type of mat? */ 1045 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1046 if (!rank) { 1047 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1048 } else { 1049 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1050 } 1051 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1052 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1053 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1054 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1055 1056 /* copy over the A part */ 1057 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1058 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1059 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1060 1061 for (i=0; i<mbs; i++) { 1062 rvals[0] = bs*(baij->rstartbs + i); 1063 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1064 for (j=ai[i]; j<ai[i+1]; j++) { 1065 col = (baij->cstartbs+aj[j])*bs; 1066 for (k=0; k<bs; k++) { 1067 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1068 col++; a += bs; 1069 } 1070 } 1071 } 1072 /* copy over the B part */ 1073 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1074 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1075 for (i=0; i<mbs; i++) { 1076 rvals[0] = bs*(baij->rstartbs + i); 1077 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1078 for (j=ai[i]; j<ai[i+1]; j++) { 1079 col = baij->garray[aj[j]]*bs; 1080 for (k=0; k<bs; k++) { 1081 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1082 col++; a += bs; 1083 } 1084 } 1085 } 1086 ierr = PetscFree(rvals);CHKERRQ(ierr); 1087 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1088 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1089 /* 1090 Everyone has to call to draw the matrix since the graphics waits are 1091 synchronized across all processors that share the PetscDraw object 1092 */ 1093 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1094 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1095 if (!rank) { 1096 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1097 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1098 } 1099 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1100 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1101 ierr = MatDestroy(&A);CHKERRQ(ierr); 1102 } 1103 PetscFunctionReturn(0); 1104 } 1105 1106 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1107 { 1108 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1109 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1110 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1111 PetscErrorCode ierr; 1112 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1113 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1114 int fd; 1115 PetscScalar *column_values; 1116 FILE *file; 1117 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1118 PetscInt message_count,flowcontrolcount; 1119 1120 PetscFunctionBegin; 1121 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1122 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1123 nz = bs2*(A->nz + B->nz); 1124 rlen = mat->rmap->n; 1125 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1126 if (!rank) { 1127 header[0] = MAT_FILE_CLASSID; 1128 header[1] = mat->rmap->N; 1129 header[2] = mat->cmap->N; 1130 1131 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1132 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1133 /* get largest number of rows any processor has */ 1134 range = mat->rmap->range; 1135 for (i=1; i<size; i++) { 1136 rlen = PetscMax(rlen,range[i+1] - range[i]); 1137 } 1138 } else { 1139 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1140 } 1141 1142 ierr = PetscMalloc1(rlen/bs,&crow_lens);CHKERRQ(ierr); 1143 /* compute lengths of each row */ 1144 for (i=0; i<a->mbs; i++) { 1145 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1146 } 1147 /* store the row lengths to the file */ 1148 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1149 if (!rank) { 1150 MPI_Status status; 1151 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1152 rlen = (range[1] - range[0])/bs; 1153 for (i=0; i<rlen; i++) { 1154 for (j=0; j<bs; j++) { 1155 row_lens[i*bs+j] = bs*crow_lens[i]; 1156 } 1157 } 1158 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1159 for (i=1; i<size; i++) { 1160 rlen = (range[i+1] - range[i])/bs; 1161 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1162 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1163 for (k=0; k<rlen; k++) { 1164 for (j=0; j<bs; j++) { 1165 row_lens[k*bs+j] = bs*crow_lens[k]; 1166 } 1167 } 1168 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1169 } 1170 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1171 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1172 } else { 1173 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1174 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1175 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1176 } 1177 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1178 1179 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1180 information needed to make it for each row from a block row. This does require more communication but still not more than 1181 the communication needed for the nonzero values */ 1182 nzmax = nz; /* space a largest processor needs */ 1183 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1184 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1185 cnt = 0; 1186 for (i=0; i<a->mbs; i++) { 1187 pcnt = cnt; 1188 for (j=B->i[i]; j<B->i[i+1]; j++) { 1189 if ((col = garray[B->j[j]]) > cstart) break; 1190 for (l=0; l<bs; l++) { 1191 column_indices[cnt++] = bs*col+l; 1192 } 1193 } 1194 for (k=A->i[i]; k<A->i[i+1]; k++) { 1195 for (l=0; l<bs; l++) { 1196 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1197 } 1198 } 1199 for (; j<B->i[i+1]; j++) { 1200 for (l=0; l<bs; l++) { 1201 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1202 } 1203 } 1204 len = cnt - pcnt; 1205 for (k=1; k<bs; k++) { 1206 ierr = PetscArraycpy(&column_indices[cnt],&column_indices[pcnt],len);CHKERRQ(ierr); 1207 cnt += len; 1208 } 1209 } 1210 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1211 1212 /* store the columns to the file */ 1213 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1214 if (!rank) { 1215 MPI_Status status; 1216 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1217 for (i=1; i<size; i++) { 1218 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1219 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1220 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1221 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1222 } 1223 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1224 } else { 1225 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1226 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1227 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1228 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1229 } 1230 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1231 1232 /* load up the numerical values */ 1233 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1234 cnt = 0; 1235 for (i=0; i<a->mbs; i++) { 1236 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1237 for (j=B->i[i]; j<B->i[i+1]; j++) { 1238 if (garray[B->j[j]] > cstart) break; 1239 for (l=0; l<bs; l++) { 1240 for (ll=0; ll<bs; ll++) { 1241 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1242 } 1243 } 1244 cnt += bs; 1245 } 1246 for (k=A->i[i]; k<A->i[i+1]; k++) { 1247 for (l=0; l<bs; l++) { 1248 for (ll=0; ll<bs; ll++) { 1249 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1250 } 1251 } 1252 cnt += bs; 1253 } 1254 for (; j<B->i[i+1]; j++) { 1255 for (l=0; l<bs; l++) { 1256 for (ll=0; ll<bs; ll++) { 1257 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1258 } 1259 } 1260 cnt += bs; 1261 } 1262 cnt += (bs-1)*rlen; 1263 } 1264 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1265 1266 /* store the column values to the file */ 1267 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1268 if (!rank) { 1269 MPI_Status status; 1270 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1271 for (i=1; i<size; i++) { 1272 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1273 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1274 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1275 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1276 } 1277 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1278 } else { 1279 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1280 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1281 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1282 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1283 } 1284 ierr = PetscFree(column_values);CHKERRQ(ierr); 1285 1286 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1287 if (file) { 1288 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1289 } 1290 PetscFunctionReturn(0); 1291 } 1292 1293 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1294 { 1295 PetscErrorCode ierr; 1296 PetscBool iascii,isdraw,issocket,isbinary; 1297 1298 PetscFunctionBegin; 1299 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1300 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1301 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1302 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1303 if (iascii || isdraw || issocket) { 1304 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1305 } else if (isbinary) { 1306 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1307 } 1308 PetscFunctionReturn(0); 1309 } 1310 1311 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1312 { 1313 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1314 PetscErrorCode ierr; 1315 1316 PetscFunctionBegin; 1317 #if defined(PETSC_USE_LOG) 1318 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1319 #endif 1320 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1321 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1322 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1323 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1324 #if defined(PETSC_USE_CTABLE) 1325 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1326 #else 1327 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1328 #endif 1329 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1330 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1331 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1332 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1333 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1334 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1335 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1336 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1337 1338 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1339 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1340 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1341 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1342 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1343 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1344 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1345 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1346 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1347 #if defined(PETSC_HAVE_HYPRE) 1348 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_hypre_C",NULL);CHKERRQ(ierr); 1349 #endif 1350 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_is_C",NULL);CHKERRQ(ierr); 1351 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_is_mpibaij_C",NULL);CHKERRQ(ierr); 1352 PetscFunctionReturn(0); 1353 } 1354 1355 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1356 { 1357 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1358 PetscErrorCode ierr; 1359 PetscInt nt; 1360 1361 PetscFunctionBegin; 1362 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1363 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1364 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1365 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1366 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1367 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1368 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1369 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1370 PetscFunctionReturn(0); 1371 } 1372 1373 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1374 { 1375 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1376 PetscErrorCode ierr; 1377 1378 PetscFunctionBegin; 1379 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1380 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1381 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1382 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1383 PetscFunctionReturn(0); 1384 } 1385 1386 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1387 { 1388 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1389 PetscErrorCode ierr; 1390 1391 PetscFunctionBegin; 1392 /* do nondiagonal part */ 1393 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1394 /* do local part */ 1395 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1396 /* add partial results together */ 1397 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1398 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1399 PetscFunctionReturn(0); 1400 } 1401 1402 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1403 { 1404 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1405 PetscErrorCode ierr; 1406 1407 PetscFunctionBegin; 1408 /* do nondiagonal part */ 1409 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1410 /* do local part */ 1411 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1412 /* add partial results together */ 1413 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1414 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1415 PetscFunctionReturn(0); 1416 } 1417 1418 /* 1419 This only works correctly for square matrices where the subblock A->A is the 1420 diagonal block 1421 */ 1422 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1423 { 1424 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1425 PetscErrorCode ierr; 1426 1427 PetscFunctionBegin; 1428 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1429 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1430 PetscFunctionReturn(0); 1431 } 1432 1433 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1434 { 1435 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1436 PetscErrorCode ierr; 1437 1438 PetscFunctionBegin; 1439 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1440 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1441 PetscFunctionReturn(0); 1442 } 1443 1444 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1445 { 1446 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1447 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1448 PetscErrorCode ierr; 1449 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1450 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1451 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1452 1453 PetscFunctionBegin; 1454 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1455 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1456 mat->getrowactive = PETSC_TRUE; 1457 1458 if (!mat->rowvalues && (idx || v)) { 1459 /* 1460 allocate enough space to hold information from the longest row. 1461 */ 1462 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1463 PetscInt max = 1,mbs = mat->mbs,tmp; 1464 for (i=0; i<mbs; i++) { 1465 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1466 if (max < tmp) max = tmp; 1467 } 1468 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1469 } 1470 lrow = row - brstart; 1471 1472 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1473 if (!v) {pvA = 0; pvB = 0;} 1474 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1475 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1476 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1477 nztot = nzA + nzB; 1478 1479 cmap = mat->garray; 1480 if (v || idx) { 1481 if (nztot) { 1482 /* Sort by increasing column numbers, assuming A and B already sorted */ 1483 PetscInt imark = -1; 1484 if (v) { 1485 *v = v_p = mat->rowvalues; 1486 for (i=0; i<nzB; i++) { 1487 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1488 else break; 1489 } 1490 imark = i; 1491 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1492 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1493 } 1494 if (idx) { 1495 *idx = idx_p = mat->rowindices; 1496 if (imark > -1) { 1497 for (i=0; i<imark; i++) { 1498 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1499 } 1500 } else { 1501 for (i=0; i<nzB; i++) { 1502 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1503 else break; 1504 } 1505 imark = i; 1506 } 1507 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1508 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1509 } 1510 } else { 1511 if (idx) *idx = 0; 1512 if (v) *v = 0; 1513 } 1514 } 1515 *nz = nztot; 1516 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1517 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1518 PetscFunctionReturn(0); 1519 } 1520 1521 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1522 { 1523 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1524 1525 PetscFunctionBegin; 1526 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1527 baij->getrowactive = PETSC_FALSE; 1528 PetscFunctionReturn(0); 1529 } 1530 1531 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1532 { 1533 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1534 PetscErrorCode ierr; 1535 1536 PetscFunctionBegin; 1537 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1538 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1539 PetscFunctionReturn(0); 1540 } 1541 1542 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1543 { 1544 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1545 Mat A = a->A,B = a->B; 1546 PetscErrorCode ierr; 1547 PetscReal isend[5],irecv[5]; 1548 1549 PetscFunctionBegin; 1550 info->block_size = (PetscReal)matin->rmap->bs; 1551 1552 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1553 1554 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1555 isend[3] = info->memory; isend[4] = info->mallocs; 1556 1557 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1558 1559 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1560 isend[3] += info->memory; isend[4] += info->mallocs; 1561 1562 if (flag == MAT_LOCAL) { 1563 info->nz_used = isend[0]; 1564 info->nz_allocated = isend[1]; 1565 info->nz_unneeded = isend[2]; 1566 info->memory = isend[3]; 1567 info->mallocs = isend[4]; 1568 } else if (flag == MAT_GLOBAL_MAX) { 1569 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1570 1571 info->nz_used = irecv[0]; 1572 info->nz_allocated = irecv[1]; 1573 info->nz_unneeded = irecv[2]; 1574 info->memory = irecv[3]; 1575 info->mallocs = irecv[4]; 1576 } else if (flag == MAT_GLOBAL_SUM) { 1577 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1578 1579 info->nz_used = irecv[0]; 1580 info->nz_allocated = irecv[1]; 1581 info->nz_unneeded = irecv[2]; 1582 info->memory = irecv[3]; 1583 info->mallocs = irecv[4]; 1584 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1585 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1586 info->fill_ratio_needed = 0; 1587 info->factor_mallocs = 0; 1588 PetscFunctionReturn(0); 1589 } 1590 1591 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1592 { 1593 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1594 PetscErrorCode ierr; 1595 1596 PetscFunctionBegin; 1597 switch (op) { 1598 case MAT_NEW_NONZERO_LOCATIONS: 1599 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1600 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1601 case MAT_KEEP_NONZERO_PATTERN: 1602 case MAT_NEW_NONZERO_LOCATION_ERR: 1603 MatCheckPreallocated(A,1); 1604 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1605 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1606 break; 1607 case MAT_ROW_ORIENTED: 1608 MatCheckPreallocated(A,1); 1609 a->roworiented = flg; 1610 1611 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1612 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1613 break; 1614 case MAT_NEW_DIAGONALS: 1615 case MAT_SORTED_FULL: 1616 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1617 break; 1618 case MAT_IGNORE_OFF_PROC_ENTRIES: 1619 a->donotstash = flg; 1620 break; 1621 case MAT_USE_HASH_TABLE: 1622 a->ht_flag = flg; 1623 a->ht_fact = 1.39; 1624 break; 1625 case MAT_SYMMETRIC: 1626 case MAT_STRUCTURALLY_SYMMETRIC: 1627 case MAT_HERMITIAN: 1628 case MAT_SUBMAT_SINGLEIS: 1629 case MAT_SYMMETRY_ETERNAL: 1630 MatCheckPreallocated(A,1); 1631 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1632 break; 1633 default: 1634 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1635 } 1636 PetscFunctionReturn(0); 1637 } 1638 1639 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1640 { 1641 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1642 Mat_SeqBAIJ *Aloc; 1643 Mat B; 1644 PetscErrorCode ierr; 1645 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1646 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1647 MatScalar *a; 1648 1649 PetscFunctionBegin; 1650 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 1651 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1652 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1653 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1654 /* Do not know preallocation information, but must set block size */ 1655 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1656 } else { 1657 B = *matout; 1658 } 1659 1660 /* copy over the A part */ 1661 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1662 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1663 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1664 1665 for (i=0; i<mbs; i++) { 1666 rvals[0] = bs*(baij->rstartbs + i); 1667 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1668 for (j=ai[i]; j<ai[i+1]; j++) { 1669 col = (baij->cstartbs+aj[j])*bs; 1670 for (k=0; k<bs; k++) { 1671 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1672 1673 col++; a += bs; 1674 } 1675 } 1676 } 1677 /* copy over the B part */ 1678 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1679 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1680 for (i=0; i<mbs; i++) { 1681 rvals[0] = bs*(baij->rstartbs + i); 1682 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1683 for (j=ai[i]; j<ai[i+1]; j++) { 1684 col = baij->garray[aj[j]]*bs; 1685 for (k=0; k<bs; k++) { 1686 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1687 col++; 1688 a += bs; 1689 } 1690 } 1691 } 1692 ierr = PetscFree(rvals);CHKERRQ(ierr); 1693 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1694 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1695 1696 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) *matout = B; 1697 else { 1698 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1699 } 1700 PetscFunctionReturn(0); 1701 } 1702 1703 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1704 { 1705 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1706 Mat a = baij->A,b = baij->B; 1707 PetscErrorCode ierr; 1708 PetscInt s1,s2,s3; 1709 1710 PetscFunctionBegin; 1711 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1712 if (rr) { 1713 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1714 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1715 /* Overlap communication with computation. */ 1716 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1717 } 1718 if (ll) { 1719 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1720 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1721 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1722 } 1723 /* scale the diagonal block */ 1724 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1725 1726 if (rr) { 1727 /* Do a scatter end and then right scale the off-diagonal block */ 1728 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1729 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1730 } 1731 PetscFunctionReturn(0); 1732 } 1733 1734 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1735 { 1736 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1737 PetscInt *lrows; 1738 PetscInt r, len; 1739 PetscBool cong; 1740 PetscErrorCode ierr; 1741 1742 PetscFunctionBegin; 1743 /* get locally owned rows */ 1744 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 1745 /* fix right hand side if needed */ 1746 if (x && b) { 1747 const PetscScalar *xx; 1748 PetscScalar *bb; 1749 1750 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1751 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1752 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1753 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1754 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1755 } 1756 1757 /* actually zap the local rows */ 1758 /* 1759 Zero the required rows. If the "diagonal block" of the matrix 1760 is square and the user wishes to set the diagonal we use separate 1761 code so that MatSetValues() is not called for each diagonal allocating 1762 new memory, thus calling lots of mallocs and slowing things down. 1763 1764 */ 1765 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1766 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1767 ierr = MatHasCongruentLayouts(A,&cong);CHKERRQ(ierr); 1768 if ((diag != 0.0) && cong) { 1769 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1770 } else if (diag != 0.0) { 1771 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1772 if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1773 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1774 for (r = 0; r < len; ++r) { 1775 const PetscInt row = lrows[r] + A->rmap->rstart; 1776 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1777 } 1778 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1779 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1780 } else { 1781 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1782 } 1783 ierr = PetscFree(lrows);CHKERRQ(ierr); 1784 1785 /* only change matrix nonzero state if pattern was allowed to be changed */ 1786 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1787 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1788 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1789 } 1790 PetscFunctionReturn(0); 1791 } 1792 1793 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1794 { 1795 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1796 PetscErrorCode ierr; 1797 PetscMPIInt n = A->rmap->n; 1798 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1799 PetscInt *lrows,*owners = A->rmap->range; 1800 PetscSFNode *rrows; 1801 PetscSF sf; 1802 const PetscScalar *xx; 1803 PetscScalar *bb,*mask; 1804 Vec xmask,lmask; 1805 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1806 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1807 PetscScalar *aa; 1808 1809 PetscFunctionBegin; 1810 /* Create SF where leaves are input rows and roots are owned rows */ 1811 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1812 for (r = 0; r < n; ++r) lrows[r] = -1; 1813 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1814 for (r = 0; r < N; ++r) { 1815 const PetscInt idx = rows[r]; 1816 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1817 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1818 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1819 } 1820 rrows[r].rank = p; 1821 rrows[r].index = rows[r] - owners[p]; 1822 } 1823 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1824 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1825 /* Collect flags for rows to be zeroed */ 1826 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1827 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1828 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1829 /* Compress and put in row numbers */ 1830 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1831 /* zero diagonal part of matrix */ 1832 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1833 /* handle off diagonal part of matrix */ 1834 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 1835 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1836 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1837 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1838 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1839 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1840 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1841 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1842 if (x) { 1843 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1844 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1845 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1846 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1847 } 1848 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1849 /* remove zeroed rows of off diagonal matrix */ 1850 for (i = 0; i < len; ++i) { 1851 row = lrows[i]; 1852 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1853 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1854 for (k = 0; k < count; ++k) { 1855 aa[0] = 0.0; 1856 aa += bs; 1857 } 1858 } 1859 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1860 for (i = 0; i < l->B->rmap->N; ++i) { 1861 row = i/bs; 1862 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1863 for (k = 0; k < bs; ++k) { 1864 col = bs*baij->j[j] + k; 1865 if (PetscAbsScalar(mask[col])) { 1866 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1867 if (x) bb[i] -= aa[0]*xx[col]; 1868 aa[0] = 0.0; 1869 } 1870 } 1871 } 1872 } 1873 if (x) { 1874 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1875 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1876 } 1877 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1878 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1879 ierr = PetscFree(lrows);CHKERRQ(ierr); 1880 1881 /* only change matrix nonzero state if pattern was allowed to be changed */ 1882 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1883 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1884 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1885 } 1886 PetscFunctionReturn(0); 1887 } 1888 1889 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1890 { 1891 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1892 PetscErrorCode ierr; 1893 1894 PetscFunctionBegin; 1895 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1896 PetscFunctionReturn(0); 1897 } 1898 1899 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1900 1901 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1902 { 1903 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1904 Mat a,b,c,d; 1905 PetscBool flg; 1906 PetscErrorCode ierr; 1907 1908 PetscFunctionBegin; 1909 a = matA->A; b = matA->B; 1910 c = matB->A; d = matB->B; 1911 1912 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1913 if (flg) { 1914 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1915 } 1916 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1917 PetscFunctionReturn(0); 1918 } 1919 1920 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1921 { 1922 PetscErrorCode ierr; 1923 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1924 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1925 1926 PetscFunctionBegin; 1927 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1928 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1929 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1930 } else { 1931 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1932 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1933 } 1934 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 1935 PetscFunctionReturn(0); 1936 } 1937 1938 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1939 { 1940 PetscErrorCode ierr; 1941 1942 PetscFunctionBegin; 1943 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1944 PetscFunctionReturn(0); 1945 } 1946 1947 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1948 { 1949 PetscErrorCode ierr; 1950 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1951 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1952 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1953 1954 PetscFunctionBegin; 1955 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1956 PetscFunctionReturn(0); 1957 } 1958 1959 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1960 { 1961 PetscErrorCode ierr; 1962 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1963 PetscBLASInt bnz,one=1; 1964 Mat_SeqBAIJ *x,*y; 1965 PetscInt bs2 = Y->rmap->bs*Y->rmap->bs; 1966 1967 PetscFunctionBegin; 1968 if (str == SAME_NONZERO_PATTERN) { 1969 PetscScalar alpha = a; 1970 x = (Mat_SeqBAIJ*)xx->A->data; 1971 y = (Mat_SeqBAIJ*)yy->A->data; 1972 ierr = PetscBLASIntCast(x->nz*bs2,&bnz);CHKERRQ(ierr); 1973 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1974 x = (Mat_SeqBAIJ*)xx->B->data; 1975 y = (Mat_SeqBAIJ*)yy->B->data; 1976 ierr = PetscBLASIntCast(x->nz*bs2,&bnz);CHKERRQ(ierr); 1977 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1978 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 1979 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 1980 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1981 } else { 1982 Mat B; 1983 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 1984 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 1985 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 1986 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 1987 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 1988 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 1989 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 1990 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 1991 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 1992 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 1993 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 1994 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 1995 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 1996 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 1997 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 1998 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 1999 } 2000 PetscFunctionReturn(0); 2001 } 2002 2003 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2004 { 2005 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2006 PetscErrorCode ierr; 2007 2008 PetscFunctionBegin; 2009 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2010 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2011 PetscFunctionReturn(0); 2012 } 2013 2014 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2015 { 2016 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2017 PetscErrorCode ierr; 2018 2019 PetscFunctionBegin; 2020 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2021 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2022 PetscFunctionReturn(0); 2023 } 2024 2025 PetscErrorCode MatCreateSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2026 { 2027 PetscErrorCode ierr; 2028 IS iscol_local; 2029 PetscInt csize; 2030 2031 PetscFunctionBegin; 2032 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2033 if (call == MAT_REUSE_MATRIX) { 2034 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2035 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2036 } else { 2037 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2038 } 2039 ierr = MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2040 if (call == MAT_INITIAL_MATRIX) { 2041 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2042 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2043 } 2044 PetscFunctionReturn(0); 2045 } 2046 2047 /* 2048 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2049 in local and then by concatenating the local matrices the end result. 2050 Writing it directly would be much like MatCreateSubMatrices_MPIBAIJ(). 2051 This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency). 2052 */ 2053 PetscErrorCode MatCreateSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2054 { 2055 PetscErrorCode ierr; 2056 PetscMPIInt rank,size; 2057 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2058 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2059 Mat M,Mreuse; 2060 MatScalar *vwork,*aa; 2061 MPI_Comm comm; 2062 IS isrow_new, iscol_new; 2063 Mat_SeqBAIJ *aij; 2064 2065 PetscFunctionBegin; 2066 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2067 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2068 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2069 /* The compression and expansion should be avoided. Doesn't point 2070 out errors, might change the indices, hence buggey */ 2071 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2072 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2073 2074 if (call == MAT_REUSE_MATRIX) { 2075 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2076 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2077 ierr = MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&Mreuse);CHKERRQ(ierr); 2078 } else { 2079 ierr = MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&Mreuse);CHKERRQ(ierr); 2080 } 2081 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2082 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2083 /* 2084 m - number of local rows 2085 n - number of columns (same on all processors) 2086 rstart - first row in new global matrix generated 2087 */ 2088 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2089 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2090 m = m/bs; 2091 n = n/bs; 2092 2093 if (call == MAT_INITIAL_MATRIX) { 2094 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2095 ii = aij->i; 2096 jj = aij->j; 2097 2098 /* 2099 Determine the number of non-zeros in the diagonal and off-diagonal 2100 portions of the matrix in order to do correct preallocation 2101 */ 2102 2103 /* first get start and end of "diagonal" columns */ 2104 if (csize == PETSC_DECIDE) { 2105 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2106 if (mglobal == n*bs) { /* square matrix */ 2107 nlocal = m; 2108 } else { 2109 nlocal = n/size + ((n % size) > rank); 2110 } 2111 } else { 2112 nlocal = csize/bs; 2113 } 2114 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2115 rstart = rend - nlocal; 2116 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2117 2118 /* next, compute all the lengths */ 2119 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2120 for (i=0; i<m; i++) { 2121 jend = ii[i+1] - ii[i]; 2122 olen = 0; 2123 dlen = 0; 2124 for (j=0; j<jend; j++) { 2125 if (*jj < rstart || *jj >= rend) olen++; 2126 else dlen++; 2127 jj++; 2128 } 2129 olens[i] = olen; 2130 dlens[i] = dlen; 2131 } 2132 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2133 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2134 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2135 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2136 ierr = MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2137 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2138 } else { 2139 PetscInt ml,nl; 2140 2141 M = *newmat; 2142 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2143 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2144 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2145 /* 2146 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2147 rather than the slower MatSetValues(). 2148 */ 2149 M->was_assembled = PETSC_TRUE; 2150 M->assembled = PETSC_FALSE; 2151 } 2152 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2153 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2154 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2155 ii = aij->i; 2156 jj = aij->j; 2157 aa = aij->a; 2158 for (i=0; i<m; i++) { 2159 row = rstart/bs + i; 2160 nz = ii[i+1] - ii[i]; 2161 cwork = jj; jj += nz; 2162 vwork = aa; aa += nz*bs*bs; 2163 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2164 } 2165 2166 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2167 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2168 *newmat = M; 2169 2170 /* save submatrix used in processor for next request */ 2171 if (call == MAT_INITIAL_MATRIX) { 2172 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2173 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2174 } 2175 PetscFunctionReturn(0); 2176 } 2177 2178 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2179 { 2180 MPI_Comm comm,pcomm; 2181 PetscInt clocal_size,nrows; 2182 const PetscInt *rows; 2183 PetscMPIInt size; 2184 IS crowp,lcolp; 2185 PetscErrorCode ierr; 2186 2187 PetscFunctionBegin; 2188 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2189 /* make a collective version of 'rowp' */ 2190 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2191 if (pcomm==comm) { 2192 crowp = rowp; 2193 } else { 2194 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2195 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2196 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2197 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2198 } 2199 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2200 /* make a local version of 'colp' */ 2201 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2202 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2203 if (size==1) { 2204 lcolp = colp; 2205 } else { 2206 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2207 } 2208 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2209 /* now we just get the submatrix */ 2210 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2211 ierr = MatCreateSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2212 /* clean up */ 2213 if (pcomm!=comm) { 2214 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2215 } 2216 if (size>1) { 2217 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2218 } 2219 PetscFunctionReturn(0); 2220 } 2221 2222 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2223 { 2224 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2225 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2226 2227 PetscFunctionBegin; 2228 if (nghosts) *nghosts = B->nbs; 2229 if (ghosts) *ghosts = baij->garray; 2230 PetscFunctionReturn(0); 2231 } 2232 2233 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2234 { 2235 Mat B; 2236 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2237 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2238 Mat_SeqAIJ *b; 2239 PetscErrorCode ierr; 2240 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2241 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2242 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2243 2244 PetscFunctionBegin; 2245 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2246 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2247 2248 /* ---------------------------------------------------------------- 2249 Tell every processor the number of nonzeros per row 2250 */ 2251 ierr = PetscMalloc1(A->rmap->N/bs,&lens);CHKERRQ(ierr); 2252 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2253 lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs]; 2254 } 2255 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2256 displs = recvcounts + size; 2257 for (i=0; i<size; i++) { 2258 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2259 displs[i] = A->rmap->range[i]/bs; 2260 } 2261 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2262 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2263 #else 2264 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2265 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2266 #endif 2267 /* --------------------------------------------------------------- 2268 Create the sequential matrix of the same type as the local block diagonal 2269 */ 2270 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2271 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2272 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2273 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2274 b = (Mat_SeqAIJ*)B->data; 2275 2276 /*-------------------------------------------------------------------- 2277 Copy my part of matrix column indices over 2278 */ 2279 sendcount = ad->nz + bd->nz; 2280 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2281 a_jsendbuf = ad->j; 2282 b_jsendbuf = bd->j; 2283 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2284 cnt = 0; 2285 for (i=0; i<n; i++) { 2286 2287 /* put in lower diagonal portion */ 2288 m = bd->i[i+1] - bd->i[i]; 2289 while (m > 0) { 2290 /* is it above diagonal (in bd (compressed) numbering) */ 2291 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2292 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2293 m--; 2294 } 2295 2296 /* put in diagonal portion */ 2297 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2298 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2299 } 2300 2301 /* put in upper diagonal portion */ 2302 while (m-- > 0) { 2303 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2304 } 2305 } 2306 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2307 2308 /*-------------------------------------------------------------------- 2309 Gather all column indices to all processors 2310 */ 2311 for (i=0; i<size; i++) { 2312 recvcounts[i] = 0; 2313 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2314 recvcounts[i] += lens[j]; 2315 } 2316 } 2317 displs[0] = 0; 2318 for (i=1; i<size; i++) { 2319 displs[i] = displs[i-1] + recvcounts[i-1]; 2320 } 2321 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2322 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2323 #else 2324 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2325 #endif 2326 /*-------------------------------------------------------------------- 2327 Assemble the matrix into useable form (note numerical values not yet set) 2328 */ 2329 /* set the b->ilen (length of each row) values */ 2330 ierr = PetscArraycpy(b->ilen,lens,A->rmap->N/bs);CHKERRQ(ierr); 2331 /* set the b->i indices */ 2332 b->i[0] = 0; 2333 for (i=1; i<=A->rmap->N/bs; i++) { 2334 b->i[i] = b->i[i-1] + lens[i-1]; 2335 } 2336 ierr = PetscFree(lens);CHKERRQ(ierr); 2337 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2338 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2339 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2340 2341 if (A->symmetric) { 2342 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2343 } else if (A->hermitian) { 2344 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2345 } else if (A->structurally_symmetric) { 2346 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2347 } 2348 *newmat = B; 2349 PetscFunctionReturn(0); 2350 } 2351 2352 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2353 { 2354 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2355 PetscErrorCode ierr; 2356 Vec bb1 = 0; 2357 2358 PetscFunctionBegin; 2359 if (flag == SOR_APPLY_UPPER) { 2360 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2361 PetscFunctionReturn(0); 2362 } 2363 2364 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2365 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2366 } 2367 2368 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2369 if (flag & SOR_ZERO_INITIAL_GUESS) { 2370 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2371 its--; 2372 } 2373 2374 while (its--) { 2375 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2376 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2377 2378 /* update rhs: bb1 = bb - B*x */ 2379 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2380 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2381 2382 /* local sweep */ 2383 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2384 } 2385 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2386 if (flag & SOR_ZERO_INITIAL_GUESS) { 2387 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2388 its--; 2389 } 2390 while (its--) { 2391 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2392 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2393 2394 /* update rhs: bb1 = bb - B*x */ 2395 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2396 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2397 2398 /* local sweep */ 2399 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2400 } 2401 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2402 if (flag & SOR_ZERO_INITIAL_GUESS) { 2403 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2404 its--; 2405 } 2406 while (its--) { 2407 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2408 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2409 2410 /* update rhs: bb1 = bb - B*x */ 2411 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2412 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2413 2414 /* local sweep */ 2415 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2416 } 2417 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2418 2419 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2420 PetscFunctionReturn(0); 2421 } 2422 2423 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2424 { 2425 PetscErrorCode ierr; 2426 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2427 PetscInt N,i,*garray = aij->garray; 2428 PetscInt ib,jb,bs = A->rmap->bs; 2429 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2430 MatScalar *a_val = a_aij->a; 2431 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2432 MatScalar *b_val = b_aij->a; 2433 PetscReal *work; 2434 2435 PetscFunctionBegin; 2436 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2437 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2438 if (type == NORM_2) { 2439 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2440 for (jb=0; jb<bs; jb++) { 2441 for (ib=0; ib<bs; ib++) { 2442 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2443 a_val++; 2444 } 2445 } 2446 } 2447 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2448 for (jb=0; jb<bs; jb++) { 2449 for (ib=0; ib<bs; ib++) { 2450 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2451 b_val++; 2452 } 2453 } 2454 } 2455 } else if (type == NORM_1) { 2456 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2457 for (jb=0; jb<bs; jb++) { 2458 for (ib=0; ib<bs; ib++) { 2459 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2460 a_val++; 2461 } 2462 } 2463 } 2464 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2465 for (jb=0; jb<bs; jb++) { 2466 for (ib=0; ib<bs; ib++) { 2467 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2468 b_val++; 2469 } 2470 } 2471 } 2472 } else if (type == NORM_INFINITY) { 2473 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2474 for (jb=0; jb<bs; jb++) { 2475 for (ib=0; ib<bs; ib++) { 2476 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2477 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2478 a_val++; 2479 } 2480 } 2481 } 2482 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2483 for (jb=0; jb<bs; jb++) { 2484 for (ib=0; ib<bs; ib++) { 2485 int col = garray[b_aij->j[i]] * bs + jb; 2486 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2487 b_val++; 2488 } 2489 } 2490 } 2491 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2492 if (type == NORM_INFINITY) { 2493 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2494 } else { 2495 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2496 } 2497 ierr = PetscFree(work);CHKERRQ(ierr); 2498 if (type == NORM_2) { 2499 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2500 } 2501 PetscFunctionReturn(0); 2502 } 2503 2504 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2505 { 2506 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2507 PetscErrorCode ierr; 2508 2509 PetscFunctionBegin; 2510 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2511 A->factorerrortype = a->A->factorerrortype; 2512 A->factorerror_zeropivot_value = a->A->factorerror_zeropivot_value; 2513 A->factorerror_zeropivot_row = a->A->factorerror_zeropivot_row; 2514 PetscFunctionReturn(0); 2515 } 2516 2517 PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a) 2518 { 2519 PetscErrorCode ierr; 2520 Mat_MPIBAIJ *maij = (Mat_MPIBAIJ*)Y->data; 2521 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)maij->A->data; 2522 2523 PetscFunctionBegin; 2524 if (!Y->preallocated) { 2525 ierr = MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);CHKERRQ(ierr); 2526 } else if (!aij->nz) { 2527 PetscInt nonew = aij->nonew; 2528 ierr = MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);CHKERRQ(ierr); 2529 aij->nonew = nonew; 2530 } 2531 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2532 PetscFunctionReturn(0); 2533 } 2534 2535 PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool *missing,PetscInt *d) 2536 { 2537 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2538 PetscErrorCode ierr; 2539 2540 PetscFunctionBegin; 2541 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2542 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2543 if (d) { 2544 PetscInt rstart; 2545 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2546 *d += rstart/A->rmap->bs; 2547 2548 } 2549 PetscFunctionReturn(0); 2550 } 2551 2552 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2553 { 2554 PetscFunctionBegin; 2555 *a = ((Mat_MPIBAIJ*)A->data)->A; 2556 PetscFunctionReturn(0); 2557 } 2558 2559 /* -------------------------------------------------------------------*/ 2560 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2561 MatGetRow_MPIBAIJ, 2562 MatRestoreRow_MPIBAIJ, 2563 MatMult_MPIBAIJ, 2564 /* 4*/ MatMultAdd_MPIBAIJ, 2565 MatMultTranspose_MPIBAIJ, 2566 MatMultTransposeAdd_MPIBAIJ, 2567 0, 2568 0, 2569 0, 2570 /*10*/ 0, 2571 0, 2572 0, 2573 MatSOR_MPIBAIJ, 2574 MatTranspose_MPIBAIJ, 2575 /*15*/ MatGetInfo_MPIBAIJ, 2576 MatEqual_MPIBAIJ, 2577 MatGetDiagonal_MPIBAIJ, 2578 MatDiagonalScale_MPIBAIJ, 2579 MatNorm_MPIBAIJ, 2580 /*20*/ MatAssemblyBegin_MPIBAIJ, 2581 MatAssemblyEnd_MPIBAIJ, 2582 MatSetOption_MPIBAIJ, 2583 MatZeroEntries_MPIBAIJ, 2584 /*24*/ MatZeroRows_MPIBAIJ, 2585 0, 2586 0, 2587 0, 2588 0, 2589 /*29*/ MatSetUp_MPIBAIJ, 2590 0, 2591 0, 2592 MatGetDiagonalBlock_MPIBAIJ, 2593 0, 2594 /*34*/ MatDuplicate_MPIBAIJ, 2595 0, 2596 0, 2597 0, 2598 0, 2599 /*39*/ MatAXPY_MPIBAIJ, 2600 MatCreateSubMatrices_MPIBAIJ, 2601 MatIncreaseOverlap_MPIBAIJ, 2602 MatGetValues_MPIBAIJ, 2603 MatCopy_MPIBAIJ, 2604 /*44*/ 0, 2605 MatScale_MPIBAIJ, 2606 MatShift_MPIBAIJ, 2607 0, 2608 MatZeroRowsColumns_MPIBAIJ, 2609 /*49*/ 0, 2610 0, 2611 0, 2612 0, 2613 0, 2614 /*54*/ MatFDColoringCreate_MPIXAIJ, 2615 0, 2616 MatSetUnfactored_MPIBAIJ, 2617 MatPermute_MPIBAIJ, 2618 MatSetValuesBlocked_MPIBAIJ, 2619 /*59*/ MatCreateSubMatrix_MPIBAIJ, 2620 MatDestroy_MPIBAIJ, 2621 MatView_MPIBAIJ, 2622 0, 2623 0, 2624 /*64*/ 0, 2625 0, 2626 0, 2627 0, 2628 0, 2629 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2630 0, 2631 0, 2632 0, 2633 0, 2634 /*74*/ 0, 2635 MatFDColoringApply_BAIJ, 2636 0, 2637 0, 2638 0, 2639 /*79*/ 0, 2640 0, 2641 0, 2642 0, 2643 MatLoad_MPIBAIJ, 2644 /*84*/ 0, 2645 0, 2646 0, 2647 0, 2648 0, 2649 /*89*/ 0, 2650 0, 2651 0, 2652 0, 2653 0, 2654 /*94*/ 0, 2655 0, 2656 0, 2657 0, 2658 0, 2659 /*99*/ 0, 2660 0, 2661 0, 2662 0, 2663 0, 2664 /*104*/0, 2665 MatRealPart_MPIBAIJ, 2666 MatImaginaryPart_MPIBAIJ, 2667 0, 2668 0, 2669 /*109*/0, 2670 0, 2671 0, 2672 0, 2673 MatMissingDiagonal_MPIBAIJ, 2674 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2675 0, 2676 MatGetGhosts_MPIBAIJ, 2677 0, 2678 0, 2679 /*119*/0, 2680 0, 2681 0, 2682 0, 2683 MatGetMultiProcBlock_MPIBAIJ, 2684 /*124*/0, 2685 MatGetColumnNorms_MPIBAIJ, 2686 MatInvertBlockDiagonal_MPIBAIJ, 2687 0, 2688 0, 2689 /*129*/ 0, 2690 0, 2691 0, 2692 0, 2693 0, 2694 /*134*/ 0, 2695 0, 2696 0, 2697 0, 2698 0, 2699 /*139*/ MatSetBlockSizes_Default, 2700 0, 2701 0, 2702 MatFDColoringSetUp_MPIXAIJ, 2703 0, 2704 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ 2705 }; 2706 2707 2708 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 2709 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 2710 2711 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2712 { 2713 PetscInt m,rstart,cstart,cend; 2714 PetscInt i,j,dlen,olen,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2715 const PetscInt *JJ =0; 2716 PetscScalar *values=0; 2717 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2718 PetscErrorCode ierr; 2719 2720 PetscFunctionBegin; 2721 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2722 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2723 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2724 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2725 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2726 m = B->rmap->n/bs; 2727 rstart = B->rmap->rstart/bs; 2728 cstart = B->cmap->rstart/bs; 2729 cend = B->cmap->rend/bs; 2730 2731 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2732 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2733 for (i=0; i<m; i++) { 2734 nz = ii[i+1] - ii[i]; 2735 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2736 nz_max = PetscMax(nz_max,nz); 2737 dlen = 0; 2738 olen = 0; 2739 JJ = jj + ii[i]; 2740 for (j=0; j<nz; j++) { 2741 if (*JJ < cstart || *JJ >= cend) olen++; 2742 else dlen++; 2743 JJ++; 2744 } 2745 d_nnz[i] = dlen; 2746 o_nnz[i] = olen; 2747 } 2748 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2749 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2750 2751 values = (PetscScalar*)V; 2752 if (!values) { 2753 ierr = PetscCalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2754 } 2755 for (i=0; i<m; i++) { 2756 PetscInt row = i + rstart; 2757 PetscInt ncols = ii[i+1] - ii[i]; 2758 const PetscInt *icols = jj + ii[i]; 2759 if (bs == 1 || !roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2760 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2761 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2762 } else { /* block ordering does not match so we can only insert one block at a time. */ 2763 PetscInt j; 2764 for (j=0; j<ncols; j++) { 2765 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2766 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2767 } 2768 } 2769 } 2770 2771 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2772 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2773 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2774 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2775 PetscFunctionReturn(0); 2776 } 2777 2778 /*@C 2779 MatMPIBAIJSetPreallocationCSR - Creates a sparse parallel matrix in BAIJ format using the given nonzero structure and (optional) numerical values 2780 2781 Collective 2782 2783 Input Parameters: 2784 + B - the matrix 2785 . bs - the block size 2786 . i - the indices into j for the start of each local row (starts with zero) 2787 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2788 - v - optional values in the matrix 2789 2790 Level: advanced 2791 2792 Notes: 2793 The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2794 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2795 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2796 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2797 block column and the second index is over columns within a block. 2798 2799 Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries and usually the numerical values as well 2800 2801 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2802 @*/ 2803 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2804 { 2805 PetscErrorCode ierr; 2806 2807 PetscFunctionBegin; 2808 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2809 PetscValidType(B,1); 2810 PetscValidLogicalCollectiveInt(B,bs,2); 2811 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2812 PetscFunctionReturn(0); 2813 } 2814 2815 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2816 { 2817 Mat_MPIBAIJ *b; 2818 PetscErrorCode ierr; 2819 PetscInt i; 2820 PetscMPIInt size; 2821 2822 PetscFunctionBegin; 2823 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2824 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2825 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2826 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2827 2828 if (d_nnz) { 2829 for (i=0; i<B->rmap->n/bs; i++) { 2830 if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2831 } 2832 } 2833 if (o_nnz) { 2834 for (i=0; i<B->rmap->n/bs; i++) { 2835 if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2836 } 2837 } 2838 2839 b = (Mat_MPIBAIJ*)B->data; 2840 b->bs2 = bs*bs; 2841 b->mbs = B->rmap->n/bs; 2842 b->nbs = B->cmap->n/bs; 2843 b->Mbs = B->rmap->N/bs; 2844 b->Nbs = B->cmap->N/bs; 2845 2846 for (i=0; i<=b->size; i++) { 2847 b->rangebs[i] = B->rmap->range[i]/bs; 2848 } 2849 b->rstartbs = B->rmap->rstart/bs; 2850 b->rendbs = B->rmap->rend/bs; 2851 b->cstartbs = B->cmap->rstart/bs; 2852 b->cendbs = B->cmap->rend/bs; 2853 2854 #if defined(PETSC_USE_CTABLE) 2855 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2856 #else 2857 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2858 #endif 2859 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2860 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2861 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2862 2863 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2864 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2865 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2866 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2867 ierr = MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);CHKERRQ(ierr); 2868 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2869 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2870 2871 if (!B->preallocated) { 2872 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2873 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2874 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2875 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2876 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2877 } 2878 2879 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2880 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2881 B->preallocated = PETSC_TRUE; 2882 B->was_assembled = PETSC_FALSE; 2883 B->assembled = PETSC_FALSE; 2884 PetscFunctionReturn(0); 2885 } 2886 2887 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2888 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2889 2890 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2891 { 2892 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2893 PetscErrorCode ierr; 2894 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2895 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2896 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2897 2898 PetscFunctionBegin; 2899 ierr = PetscMalloc1(M+1,&ii);CHKERRQ(ierr); 2900 ii[0] = 0; 2901 for (i=0; i<M; i++) { 2902 if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]); 2903 if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]); 2904 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2905 /* remove one from count of matrix has diagonal */ 2906 for (j=id[i]; j<id[i+1]; j++) { 2907 if (jd[j] == i) {ii[i+1]--;break;} 2908 } 2909 } 2910 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2911 cnt = 0; 2912 for (i=0; i<M; i++) { 2913 for (j=io[i]; j<io[i+1]; j++) { 2914 if (garray[jo[j]] > rstart) break; 2915 jj[cnt++] = garray[jo[j]]; 2916 } 2917 for (k=id[i]; k<id[i+1]; k++) { 2918 if (jd[k] != i) { 2919 jj[cnt++] = rstart + jd[k]; 2920 } 2921 } 2922 for (; j<io[i+1]; j++) { 2923 jj[cnt++] = garray[jo[j]]; 2924 } 2925 } 2926 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2927 PetscFunctionReturn(0); 2928 } 2929 2930 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2931 2932 PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2933 2934 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2935 { 2936 PetscErrorCode ierr; 2937 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2938 Mat B; 2939 Mat_MPIAIJ *b; 2940 2941 PetscFunctionBegin; 2942 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2943 2944 if (reuse == MAT_REUSE_MATRIX) { 2945 B = *newmat; 2946 } else { 2947 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2948 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2949 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2950 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2951 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2952 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2953 } 2954 b = (Mat_MPIAIJ*) B->data; 2955 2956 if (reuse == MAT_REUSE_MATRIX) { 2957 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);CHKERRQ(ierr); 2958 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);CHKERRQ(ierr); 2959 } else { 2960 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2961 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2962 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2963 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2964 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2965 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2966 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2967 } 2968 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2969 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2970 2971 if (reuse == MAT_INPLACE_MATRIX) { 2972 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 2973 } else { 2974 *newmat = B; 2975 } 2976 PetscFunctionReturn(0); 2977 } 2978 2979 /*MC 2980 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2981 2982 Options Database Keys: 2983 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2984 . -mat_block_size <bs> - set the blocksize used to store the matrix 2985 - -mat_use_hash_table <fact> 2986 2987 Level: beginner 2988 2989 Notes: 2990 MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no 2991 space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored 2992 2993 .seealso: MatCreateMPIBAIJ 2994 M*/ 2995 2996 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 2997 PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*); 2998 2999 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3000 { 3001 Mat_MPIBAIJ *b; 3002 PetscErrorCode ierr; 3003 PetscBool flg = PETSC_FALSE; 3004 3005 PetscFunctionBegin; 3006 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3007 B->data = (void*)b; 3008 3009 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3010 B->assembled = PETSC_FALSE; 3011 3012 B->insertmode = NOT_SET_VALUES; 3013 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3014 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3015 3016 /* build local table of row and column ownerships */ 3017 ierr = PetscMalloc1(b->size+1,&b->rangebs);CHKERRQ(ierr); 3018 3019 /* build cache for off array entries formed */ 3020 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3021 3022 b->donotstash = PETSC_FALSE; 3023 b->colmap = NULL; 3024 b->garray = NULL; 3025 b->roworiented = PETSC_TRUE; 3026 3027 /* stuff used in block assembly */ 3028 b->barray = 0; 3029 3030 /* stuff used for matrix vector multiply */ 3031 b->lvec = 0; 3032 b->Mvctx = 0; 3033 3034 /* stuff for MatGetRow() */ 3035 b->rowindices = 0; 3036 b->rowvalues = 0; 3037 b->getrowactive = PETSC_FALSE; 3038 3039 /* hash table stuff */ 3040 b->ht = 0; 3041 b->hd = 0; 3042 b->ht_size = 0; 3043 b->ht_flag = PETSC_FALSE; 3044 b->ht_fact = 0; 3045 b->ht_total_ct = 0; 3046 b->ht_insert_ct = 0; 3047 3048 /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */ 3049 b->ijonly = PETSC_FALSE; 3050 3051 3052 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3053 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3054 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3055 #if defined(PETSC_HAVE_HYPRE) 3056 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 3057 #endif 3058 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3059 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3060 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3061 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3062 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3063 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3064 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_mpibaij_C",MatPtAP_IS_XAIJ);CHKERRQ(ierr); 3065 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 3066 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3067 3068 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3069 ierr = PetscOptionsName("-mat_use_hash_table","Use hash table to save time in constructing matrix","MatSetOption",&flg);CHKERRQ(ierr); 3070 if (flg) { 3071 PetscReal fact = 1.39; 3072 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3073 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3074 if (fact <= 1.0) fact = 1.39; 3075 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3076 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3077 } 3078 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3079 PetscFunctionReturn(0); 3080 } 3081 3082 /*MC 3083 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3084 3085 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3086 and MATMPIBAIJ otherwise. 3087 3088 Options Database Keys: 3089 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3090 3091 Level: beginner 3092 3093 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3094 M*/ 3095 3096 /*@C 3097 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3098 (block compressed row). For good matrix assembly performance 3099 the user should preallocate the matrix storage by setting the parameters 3100 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3101 performance can be increased by more than a factor of 50. 3102 3103 Collective on Mat 3104 3105 Input Parameters: 3106 + B - the matrix 3107 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3108 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3109 . d_nz - number of block nonzeros per block row in diagonal portion of local 3110 submatrix (same for all local rows) 3111 . d_nnz - array containing the number of block nonzeros in the various block rows 3112 of the in diagonal portion of the local (possibly different for each block 3113 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3114 set it even if it is zero. 3115 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3116 submatrix (same for all local rows). 3117 - o_nnz - array containing the number of nonzeros in the various block rows of the 3118 off-diagonal portion of the local submatrix (possibly different for 3119 each block row) or NULL. 3120 3121 If the *_nnz parameter is given then the *_nz parameter is ignored 3122 3123 Options Database Keys: 3124 + -mat_block_size - size of the blocks to use 3125 - -mat_use_hash_table <fact> 3126 3127 Notes: 3128 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3129 than it must be used on all processors that share the object for that argument. 3130 3131 Storage Information: 3132 For a square global matrix we define each processor's diagonal portion 3133 to be its local rows and the corresponding columns (a square submatrix); 3134 each processor's off-diagonal portion encompasses the remainder of the 3135 local matrix (a rectangular submatrix). 3136 3137 The user can specify preallocated storage for the diagonal part of 3138 the local submatrix with either d_nz or d_nnz (not both). Set 3139 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3140 memory allocation. Likewise, specify preallocated storage for the 3141 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3142 3143 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3144 the figure below we depict these three local rows and all columns (0-11). 3145 3146 .vb 3147 0 1 2 3 4 5 6 7 8 9 10 11 3148 -------------------------- 3149 row 3 |o o o d d d o o o o o o 3150 row 4 |o o o d d d o o o o o o 3151 row 5 |o o o d d d o o o o o o 3152 -------------------------- 3153 .ve 3154 3155 Thus, any entries in the d locations are stored in the d (diagonal) 3156 submatrix, and any entries in the o locations are stored in the 3157 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3158 stored simply in the MATSEQBAIJ format for compressed row storage. 3159 3160 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3161 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3162 In general, for PDE problems in which most nonzeros are near the diagonal, 3163 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3164 or you will get TERRIBLE performance; see the users' manual chapter on 3165 matrices. 3166 3167 You can call MatGetInfo() to get information on how effective the preallocation was; 3168 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3169 You can also run with the option -info and look for messages with the string 3170 malloc in them to see if additional memory allocation was needed. 3171 3172 Level: intermediate 3173 3174 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3175 @*/ 3176 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3177 { 3178 PetscErrorCode ierr; 3179 3180 PetscFunctionBegin; 3181 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3182 PetscValidType(B,1); 3183 PetscValidLogicalCollectiveInt(B,bs,2); 3184 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3185 PetscFunctionReturn(0); 3186 } 3187 3188 /*@C 3189 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3190 (block compressed row). For good matrix assembly performance 3191 the user should preallocate the matrix storage by setting the parameters 3192 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3193 performance can be increased by more than a factor of 50. 3194 3195 Collective 3196 3197 Input Parameters: 3198 + comm - MPI communicator 3199 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3200 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3201 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3202 This value should be the same as the local size used in creating the 3203 y vector for the matrix-vector product y = Ax. 3204 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3205 This value should be the same as the local size used in creating the 3206 x vector for the matrix-vector product y = Ax. 3207 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3208 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3209 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3210 submatrix (same for all local rows) 3211 . d_nnz - array containing the number of nonzero blocks in the various block rows 3212 of the in diagonal portion of the local (possibly different for each block 3213 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3214 and set it even if it is zero. 3215 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3216 submatrix (same for all local rows). 3217 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3218 off-diagonal portion of the local submatrix (possibly different for 3219 each block row) or NULL. 3220 3221 Output Parameter: 3222 . A - the matrix 3223 3224 Options Database Keys: 3225 + -mat_block_size - size of the blocks to use 3226 - -mat_use_hash_table <fact> 3227 3228 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3229 MatXXXXSetPreallocation() paradigm instead of this routine directly. 3230 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3231 3232 Notes: 3233 If the *_nnz parameter is given then the *_nz parameter is ignored 3234 3235 A nonzero block is any block that as 1 or more nonzeros in it 3236 3237 The user MUST specify either the local or global matrix dimensions 3238 (possibly both). 3239 3240 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3241 than it must be used on all processors that share the object for that argument. 3242 3243 Storage Information: 3244 For a square global matrix we define each processor's diagonal portion 3245 to be its local rows and the corresponding columns (a square submatrix); 3246 each processor's off-diagonal portion encompasses the remainder of the 3247 local matrix (a rectangular submatrix). 3248 3249 The user can specify preallocated storage for the diagonal part of 3250 the local submatrix with either d_nz or d_nnz (not both). Set 3251 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3252 memory allocation. Likewise, specify preallocated storage for the 3253 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3254 3255 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3256 the figure below we depict these three local rows and all columns (0-11). 3257 3258 .vb 3259 0 1 2 3 4 5 6 7 8 9 10 11 3260 -------------------------- 3261 row 3 |o o o d d d o o o o o o 3262 row 4 |o o o d d d o o o o o o 3263 row 5 |o o o d d d o o o o o o 3264 -------------------------- 3265 .ve 3266 3267 Thus, any entries in the d locations are stored in the d (diagonal) 3268 submatrix, and any entries in the o locations are stored in the 3269 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3270 stored simply in the MATSEQBAIJ format for compressed row storage. 3271 3272 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3273 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3274 In general, for PDE problems in which most nonzeros are near the diagonal, 3275 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3276 or you will get TERRIBLE performance; see the users' manual chapter on 3277 matrices. 3278 3279 Level: intermediate 3280 3281 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3282 @*/ 3283 PetscErrorCode MatCreateBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3284 { 3285 PetscErrorCode ierr; 3286 PetscMPIInt size; 3287 3288 PetscFunctionBegin; 3289 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3290 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3291 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3292 if (size > 1) { 3293 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3294 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3295 } else { 3296 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3297 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3298 } 3299 PetscFunctionReturn(0); 3300 } 3301 3302 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3303 { 3304 Mat mat; 3305 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3306 PetscErrorCode ierr; 3307 PetscInt len=0; 3308 3309 PetscFunctionBegin; 3310 *newmat = 0; 3311 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3312 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3313 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3314 3315 mat->factortype = matin->factortype; 3316 mat->preallocated = PETSC_TRUE; 3317 mat->assembled = PETSC_TRUE; 3318 mat->insertmode = NOT_SET_VALUES; 3319 3320 a = (Mat_MPIBAIJ*)mat->data; 3321 mat->rmap->bs = matin->rmap->bs; 3322 a->bs2 = oldmat->bs2; 3323 a->mbs = oldmat->mbs; 3324 a->nbs = oldmat->nbs; 3325 a->Mbs = oldmat->Mbs; 3326 a->Nbs = oldmat->Nbs; 3327 3328 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3329 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3330 3331 a->size = oldmat->size; 3332 a->rank = oldmat->rank; 3333 a->donotstash = oldmat->donotstash; 3334 a->roworiented = oldmat->roworiented; 3335 a->rowindices = 0; 3336 a->rowvalues = 0; 3337 a->getrowactive = PETSC_FALSE; 3338 a->barray = 0; 3339 a->rstartbs = oldmat->rstartbs; 3340 a->rendbs = oldmat->rendbs; 3341 a->cstartbs = oldmat->cstartbs; 3342 a->cendbs = oldmat->cendbs; 3343 3344 /* hash table stuff */ 3345 a->ht = 0; 3346 a->hd = 0; 3347 a->ht_size = 0; 3348 a->ht_flag = oldmat->ht_flag; 3349 a->ht_fact = oldmat->ht_fact; 3350 a->ht_total_ct = 0; 3351 a->ht_insert_ct = 0; 3352 3353 ierr = PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+1);CHKERRQ(ierr); 3354 if (oldmat->colmap) { 3355 #if defined(PETSC_USE_CTABLE) 3356 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3357 #else 3358 ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr); 3359 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3360 ierr = PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);CHKERRQ(ierr); 3361 #endif 3362 } else a->colmap = 0; 3363 3364 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3365 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3366 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3367 ierr = PetscArraycpy(a->garray,oldmat->garray,len);CHKERRQ(ierr); 3368 } else a->garray = 0; 3369 3370 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3371 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3372 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3373 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3374 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3375 3376 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3377 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3378 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3379 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3380 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3381 *newmat = mat; 3382 PetscFunctionReturn(0); 3383 } 3384 3385 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3386 { 3387 PetscErrorCode ierr; 3388 int fd; 3389 PetscInt i,nz,j,rstart,rend; 3390 PetscScalar *vals,*buf; 3391 MPI_Comm comm; 3392 MPI_Status status; 3393 PetscMPIInt rank,size,maxnz; 3394 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3395 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3396 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3397 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3398 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3399 PetscInt dcount,kmax,k,nzcount,tmp,mend; 3400 PetscBool isbinary; 3401 3402 PetscFunctionBegin; 3403 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 3404 if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name); 3405 3406 /* force binary viewer to load .info file if it has not yet done so */ 3407 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 3408 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3409 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3410 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3411 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3412 if (bs < 0) bs = 1; 3413 3414 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3415 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3416 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3417 if (!rank) { 3418 ierr = PetscBinaryRead(fd,(char*)header,4,NULL,PETSC_INT);CHKERRQ(ierr); 3419 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3420 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ"); 3421 } 3422 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3423 M = header[1]; N = header[2]; 3424 3425 /* If global sizes are set, check if they are consistent with that given in the file */ 3426 if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M); 3427 if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N); 3428 3429 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3430 3431 /* 3432 This code adds extra rows to make sure the number of rows is 3433 divisible by the blocksize 3434 */ 3435 Mbs = M/bs; 3436 extra_rows = bs - M + bs*Mbs; 3437 if (extra_rows == bs) extra_rows = 0; 3438 else Mbs++; 3439 if (extra_rows && !rank) { 3440 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3441 } 3442 3443 /* determine ownership of all rows */ 3444 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3445 mbs = Mbs/size + ((Mbs % size) > rank); 3446 m = mbs*bs; 3447 } else { /* User set */ 3448 m = newmat->rmap->n; 3449 mbs = m/bs; 3450 } 3451 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3452 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3453 3454 /* process 0 needs enough room for process with most rows */ 3455 if (!rank) { 3456 mmax = rowners[1]; 3457 for (i=2; i<=size; i++) { 3458 mmax = PetscMax(mmax,rowners[i]); 3459 } 3460 mmax*=bs; 3461 } else mmax = -1; /* unused, but compiler warns anyway */ 3462 3463 rowners[0] = 0; 3464 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3465 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3466 rstart = rowners[rank]; 3467 rend = rowners[rank+1]; 3468 3469 /* distribute row lengths to all processors */ 3470 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3471 if (!rank) { 3472 mend = m; 3473 if (size == 1) mend = mend - extra_rows; 3474 ierr = PetscBinaryRead(fd,locrowlens,mend,NULL,PETSC_INT);CHKERRQ(ierr); 3475 for (j=mend; j<m; j++) locrowlens[j] = 1; 3476 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3477 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 3478 procsnz[0] = 0; 3479 for (j=0; j<m; j++) { 3480 procsnz[0] += locrowlens[j]; 3481 } 3482 for (i=1; i<size; i++) { 3483 mend = browners[i+1] - browners[i]; 3484 if (i == size-1) mend = mend - extra_rows; 3485 ierr = PetscBinaryRead(fd,rowlengths,mend,NULL,PETSC_INT);CHKERRQ(ierr); 3486 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3487 /* calculate the number of nonzeros on each processor */ 3488 procsnz[i] = 0; 3489 for (j=0; j<browners[i+1]-browners[i]; j++) { 3490 procsnz[i] += rowlengths[j]; 3491 } 3492 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3493 } 3494 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3495 } else { 3496 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3497 } 3498 3499 if (!rank) { 3500 /* determine max buffer needed and allocate it */ 3501 maxnz = procsnz[0]; 3502 for (i=1; i<size; i++) { 3503 maxnz = PetscMax(maxnz,procsnz[i]); 3504 } 3505 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3506 3507 /* read in my part of the matrix column indices */ 3508 nz = procsnz[0]; 3509 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3510 mycols = ibuf; 3511 if (size == 1) nz -= extra_rows; 3512 ierr = PetscBinaryRead(fd,mycols,nz,NULL,PETSC_INT);CHKERRQ(ierr); 3513 if (size == 1) { 3514 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3515 } 3516 3517 /* read in every ones (except the last) and ship off */ 3518 for (i=1; i<size-1; i++) { 3519 nz = procsnz[i]; 3520 ierr = PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);CHKERRQ(ierr); 3521 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3522 } 3523 /* read in the stuff for the last proc */ 3524 if (size != 1) { 3525 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3526 ierr = PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);CHKERRQ(ierr); 3527 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3528 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3529 } 3530 ierr = PetscFree(cols);CHKERRQ(ierr); 3531 } else { 3532 /* determine buffer space needed for message */ 3533 nz = 0; 3534 for (i=0; i<m; i++) { 3535 nz += locrowlens[i]; 3536 } 3537 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3538 mycols = ibuf; 3539 /* receive message of column indices*/ 3540 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3541 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3542 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3543 } 3544 3545 /* loop over local rows, determining number of off diagonal entries */ 3546 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3547 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3548 rowcount = 0; nzcount = 0; 3549 for (i=0; i<mbs; i++) { 3550 dcount = 0; 3551 odcount = 0; 3552 for (j=0; j<bs; j++) { 3553 kmax = locrowlens[rowcount]; 3554 for (k=0; k<kmax; k++) { 3555 tmp = mycols[nzcount++]/bs; 3556 if (!mask[tmp]) { 3557 mask[tmp] = 1; 3558 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3559 else masked1[dcount++] = tmp; 3560 } 3561 } 3562 rowcount++; 3563 } 3564 3565 dlens[i] = dcount; 3566 odlens[i] = odcount; 3567 3568 /* zero out the mask elements we set */ 3569 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3570 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3571 } 3572 3573 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3574 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3575 3576 if (!rank) { 3577 ierr = PetscMalloc1(maxnz+1,&buf);CHKERRQ(ierr); 3578 /* read in my part of the matrix numerical values */ 3579 nz = procsnz[0]; 3580 vals = buf; 3581 mycols = ibuf; 3582 if (size == 1) nz -= extra_rows; 3583 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 3584 if (size == 1) { 3585 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3586 } 3587 3588 /* insert into matrix */ 3589 jj = rstart*bs; 3590 for (i=0; i<m; i++) { 3591 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3592 mycols += locrowlens[i]; 3593 vals += locrowlens[i]; 3594 jj++; 3595 } 3596 /* read in other processors (except the last one) and ship out */ 3597 for (i=1; i<size-1; i++) { 3598 nz = procsnz[i]; 3599 vals = buf; 3600 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 3601 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3602 } 3603 /* the last proc */ 3604 if (size != 1) { 3605 nz = procsnz[i] - extra_rows; 3606 vals = buf; 3607 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 3608 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3609 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3610 } 3611 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3612 } else { 3613 /* receive numeric values */ 3614 ierr = PetscMalloc1(nz+1,&buf);CHKERRQ(ierr); 3615 3616 /* receive message of values*/ 3617 vals = buf; 3618 mycols = ibuf; 3619 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3620 3621 /* insert into matrix */ 3622 jj = rstart*bs; 3623 for (i=0; i<m; i++) { 3624 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3625 mycols += locrowlens[i]; 3626 vals += locrowlens[i]; 3627 jj++; 3628 } 3629 } 3630 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3631 ierr = PetscFree(buf);CHKERRQ(ierr); 3632 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3633 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3634 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3635 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3636 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3637 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3638 PetscFunctionReturn(0); 3639 } 3640 3641 /*@ 3642 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3643 3644 Input Parameters: 3645 + mat - the matrix 3646 - fact - factor 3647 3648 Not Collective, each process can use a different factor 3649 3650 Level: advanced 3651 3652 Notes: 3653 This can also be set by the command line option: -mat_use_hash_table <fact> 3654 3655 .seealso: MatSetOption() 3656 @*/ 3657 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3658 { 3659 PetscErrorCode ierr; 3660 3661 PetscFunctionBegin; 3662 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3663 PetscFunctionReturn(0); 3664 } 3665 3666 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3667 { 3668 Mat_MPIBAIJ *baij; 3669 3670 PetscFunctionBegin; 3671 baij = (Mat_MPIBAIJ*)mat->data; 3672 baij->ht_fact = fact; 3673 PetscFunctionReturn(0); 3674 } 3675 3676 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3677 { 3678 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3679 PetscBool flg; 3680 PetscErrorCode ierr; 3681 3682 PetscFunctionBegin; 3683 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIBAIJ,&flg);CHKERRQ(ierr); 3684 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIBAIJ matrix as input"); 3685 if (Ad) *Ad = a->A; 3686 if (Ao) *Ao = a->B; 3687 if (colmap) *colmap = a->garray; 3688 PetscFunctionReturn(0); 3689 } 3690 3691 /* 3692 Special version for direct calls from Fortran (to eliminate two function call overheads 3693 */ 3694 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3695 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3696 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3697 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3698 #endif 3699 3700 /*@C 3701 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3702 3703 Collective on Mat 3704 3705 Input Parameters: 3706 + mat - the matrix 3707 . min - number of input rows 3708 . im - input rows 3709 . nin - number of input columns 3710 . in - input columns 3711 . v - numerical values input 3712 - addvin - INSERT_VALUES or ADD_VALUES 3713 3714 Notes: 3715 This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3716 3717 Level: advanced 3718 3719 .seealso: MatSetValuesBlocked() 3720 @*/ 3721 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3722 { 3723 /* convert input arguments to C version */ 3724 Mat mat = *matin; 3725 PetscInt m = *min, n = *nin; 3726 InsertMode addv = *addvin; 3727 3728 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3729 const MatScalar *value; 3730 MatScalar *barray = baij->barray; 3731 PetscBool roworiented = baij->roworiented; 3732 PetscErrorCode ierr; 3733 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3734 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3735 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3736 3737 PetscFunctionBegin; 3738 /* tasks normally handled by MatSetValuesBlocked() */ 3739 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3740 #if defined(PETSC_USE_DEBUG) 3741 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3742 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3743 #endif 3744 if (mat->assembled) { 3745 mat->was_assembled = PETSC_TRUE; 3746 mat->assembled = PETSC_FALSE; 3747 } 3748 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3749 3750 3751 if (!barray) { 3752 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3753 baij->barray = barray; 3754 } 3755 3756 if (roworiented) stepval = (n-1)*bs; 3757 else stepval = (m-1)*bs; 3758 3759 for (i=0; i<m; i++) { 3760 if (im[i] < 0) continue; 3761 #if defined(PETSC_USE_DEBUG) 3762 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 3763 #endif 3764 if (im[i] >= rstart && im[i] < rend) { 3765 row = im[i] - rstart; 3766 for (j=0; j<n; j++) { 3767 /* If NumCol = 1 then a copy is not required */ 3768 if ((roworiented) && (n == 1)) { 3769 barray = (MatScalar*)v + i*bs2; 3770 } else if ((!roworiented) && (m == 1)) { 3771 barray = (MatScalar*)v + j*bs2; 3772 } else { /* Here a copy is required */ 3773 if (roworiented) { 3774 value = v + i*(stepval+bs)*bs + j*bs; 3775 } else { 3776 value = v + j*(stepval+bs)*bs + i*bs; 3777 } 3778 for (ii=0; ii<bs; ii++,value+=stepval) { 3779 for (jj=0; jj<bs; jj++) { 3780 *barray++ = *value++; 3781 } 3782 } 3783 barray -=bs2; 3784 } 3785 3786 if (in[j] >= cstart && in[j] < cend) { 3787 col = in[j] - cstart; 3788 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3789 } else if (in[j] < 0) continue; 3790 #if defined(PETSC_USE_DEBUG) 3791 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 3792 #endif 3793 else { 3794 if (mat->was_assembled) { 3795 if (!baij->colmap) { 3796 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3797 } 3798 3799 #if defined(PETSC_USE_DEBUG) 3800 #if defined(PETSC_USE_CTABLE) 3801 { PetscInt data; 3802 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3803 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3804 } 3805 #else 3806 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3807 #endif 3808 #endif 3809 #if defined(PETSC_USE_CTABLE) 3810 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3811 col = (col - 1)/bs; 3812 #else 3813 col = (baij->colmap[in[j]] - 1)/bs; 3814 #endif 3815 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3816 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3817 col = in[j]; 3818 } 3819 } else col = in[j]; 3820 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3821 } 3822 } 3823 } else { 3824 if (!baij->donotstash) { 3825 if (roworiented) { 3826 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3827 } else { 3828 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3829 } 3830 } 3831 } 3832 } 3833 3834 /* task normally handled by MatSetValuesBlocked() */ 3835 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3836 PetscFunctionReturn(0); 3837 } 3838 3839 /*@ 3840 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard block 3841 CSR format the local rows. 3842 3843 Collective 3844 3845 Input Parameters: 3846 + comm - MPI communicator 3847 . bs - the block size, only a block size of 1 is supported 3848 . m - number of local rows (Cannot be PETSC_DECIDE) 3849 . n - This value should be the same as the local size used in creating the 3850 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3851 calculated if N is given) For square matrices n is almost always m. 3852 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3853 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3854 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that rowth block row of the matrix 3855 . j - column indices 3856 - a - matrix values 3857 3858 Output Parameter: 3859 . mat - the matrix 3860 3861 Level: intermediate 3862 3863 Notes: 3864 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3865 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3866 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3867 3868 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3869 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3870 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3871 with column-major ordering within blocks. 3872 3873 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3874 3875 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3876 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3877 @*/ 3878 PetscErrorCode MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3879 { 3880 PetscErrorCode ierr; 3881 3882 PetscFunctionBegin; 3883 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3884 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3885 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3886 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3887 ierr = MatSetType(*mat,MATMPIBAIJ);CHKERRQ(ierr); 3888 ierr = MatSetBlockSize(*mat,bs);CHKERRQ(ierr); 3889 ierr = MatSetUp(*mat);CHKERRQ(ierr); 3890 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3891 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3892 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3893 PetscFunctionReturn(0); 3894 } 3895 3896 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3897 { 3898 PetscErrorCode ierr; 3899 PetscInt m,N,i,rstart,nnz,Ii,bs,cbs; 3900 PetscInt *indx; 3901 PetscScalar *values; 3902 3903 PetscFunctionBegin; 3904 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3905 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3906 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inmat->data; 3907 PetscInt *dnz,*onz,mbs,Nbs,nbs; 3908 PetscInt *bindx,rmax=a->rmax,j; 3909 PetscMPIInt rank,size; 3910 3911 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3912 mbs = m/bs; Nbs = N/cbs; 3913 if (n == PETSC_DECIDE) { 3914 ierr = PetscSplitOwnershipBlock(comm,cbs,&n,&N); 3915 } 3916 nbs = n/cbs; 3917 3918 ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr); 3919 ierr = MatPreallocateInitialize(comm,mbs,nbs,dnz,onz);CHKERRQ(ierr); /* inline function, output __end and __rstart are used below */ 3920 3921 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3922 ierr = MPI_Comm_rank(comm,&size);CHKERRQ(ierr); 3923 if (rank == size-1) { 3924 /* Check sum(nbs) = Nbs */ 3925 if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs); 3926 } 3927 3928 rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */ 3929 for (i=0; i<mbs; i++) { 3930 ierr = MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */ 3931 nnz = nnz/bs; 3932 for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs; 3933 ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr); 3934 ierr = MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); 3935 } 3936 ierr = PetscFree(bindx);CHKERRQ(ierr); 3937 3938 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3939 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3940 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3941 ierr = MatSetType(*outmat,MATBAIJ);CHKERRQ(ierr); 3942 ierr = MatSeqBAIJSetPreallocation(*outmat,bs,0,dnz);CHKERRQ(ierr); 3943 ierr = MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr); 3944 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3945 } 3946 3947 /* numeric phase */ 3948 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3949 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3950 3951 for (i=0; i<m; i++) { 3952 ierr = MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3953 Ii = i + rstart; 3954 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3955 ierr = MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3956 } 3957 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3958 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3959 PetscFunctionReturn(0); 3960 } 3961