1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 5 EXTERN PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 EXTERN PetscErrorCode DisAssemble_MPIBAIJ(Mat); 7 EXTERN PetscErrorCode MatIncreaseOverlap_MPIBAIJ(Mat,PetscInt,IS[],PetscInt); 8 EXTERN PetscErrorCode MatGetSubMatrices_MPIBAIJ(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]); 9 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 10 EXTERN PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 11 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 12 EXTERN PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 13 EXTERN PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 14 EXTERN PetscErrorCode MatPrintHelp_SeqBAIJ(Mat); 15 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,const PetscScalar*); 16 17 /* UGLY, ugly, ugly 18 When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 19 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 20 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 21 converts the entries into single precision and then calls ..._MatScalar() to put them 22 into the single precision data structures. 23 */ 24 #if defined(PETSC_USE_MAT_SINGLE) 25 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ_MatScalar(Mat,PetscInt,const PetscInt*,PetscInt,const PetscInt*,const MatScalar*,InsertMode); 26 EXTERN PetscErrorCode MatSetValues_MPIBAIJ_MatScalar(Mat,PetscInt,const PetscInt*,PetscInt,const PetscInt*,const MatScalar*,InsertMode); 27 EXTERN PetscErrorCode MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat,PetscInt,const PetscInt*,PetscInt,const PetscInt*,const MatScalar*,InsertMode); 28 EXTERN PetscErrorCode MatSetValues_MPIBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt*,PetscInt,const PetscInt*,const MatScalar*,InsertMode); 29 EXTERN PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt*,PetscInt,const PetscInt*,const MatScalar*,InsertMode); 30 #else 31 #define MatSetValuesBlocked_SeqBAIJ_MatScalar MatSetValuesBlocked_SeqBAIJ 32 #define MatSetValues_MPIBAIJ_MatScalar MatSetValues_MPIBAIJ 33 #define MatSetValuesBlocked_MPIBAIJ_MatScalar MatSetValuesBlocked_MPIBAIJ 34 #define MatSetValues_MPIBAIJ_HT_MatScalar MatSetValues_MPIBAIJ_HT 35 #define MatSetValuesBlocked_MPIBAIJ_HT_MatScalar MatSetValuesBlocked_MPIBAIJ_HT 36 #endif 37 38 #undef __FUNCT__ 39 #define __FUNCT__ "MatGetRowMax_MPIBAIJ" 40 PetscErrorCode MatGetRowMax_MPIBAIJ(Mat A,Vec v) 41 { 42 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 43 PetscErrorCode ierr; 44 PetscInt i; 45 PetscScalar *va,*vb; 46 Vec vtmp; 47 48 PetscFunctionBegin; 49 50 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 51 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 52 53 ierr = VecCreateSeq(PETSC_COMM_SELF,A->m,&vtmp);CHKERRQ(ierr); 54 ierr = MatGetRowMax(a->B,vtmp);CHKERRQ(ierr); 55 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 56 57 for (i=0; i<A->m; i++){ 58 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) va[i] = vb[i]; 59 } 60 61 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 62 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 63 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 64 65 PetscFunctionReturn(0); 66 } 67 68 EXTERN_C_BEGIN 69 #undef __FUNCT__ 70 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 71 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIBAIJ(Mat mat) 72 { 73 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 74 PetscErrorCode ierr; 75 76 PetscFunctionBegin; 77 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 78 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 79 PetscFunctionReturn(0); 80 } 81 EXTERN_C_END 82 83 EXTERN_C_BEGIN 84 #undef __FUNCT__ 85 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 86 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIBAIJ(Mat mat) 87 { 88 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 89 PetscErrorCode ierr; 90 91 PetscFunctionBegin; 92 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 93 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 94 PetscFunctionReturn(0); 95 } 96 EXTERN_C_END 97 98 /* 99 Local utility routine that creates a mapping from the global column 100 number to the local number in the off-diagonal part of the local 101 storage of the matrix. This is done in a non scable way since the 102 length of colmap equals the global matrix length. 103 */ 104 #undef __FUNCT__ 105 #define __FUNCT__ "CreateColmap_MPIBAIJ_Private" 106 PetscErrorCode CreateColmap_MPIBAIJ_Private(Mat mat) 107 { 108 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 109 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 110 PetscErrorCode ierr; 111 PetscInt nbs = B->nbs,i,bs=mat->bs; 112 113 PetscFunctionBegin; 114 #if defined (PETSC_USE_CTABLE) 115 ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr); 116 for (i=0; i<nbs; i++){ 117 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr); 118 } 119 #else 120 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 121 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 122 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 123 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 124 #endif 125 PetscFunctionReturn(0); 126 } 127 128 #define CHUNKSIZE 10 129 130 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 131 { \ 132 \ 133 brow = row/bs; \ 134 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 135 rmax = aimax[brow]; nrow = ailen[brow]; \ 136 bcol = col/bs; \ 137 ridx = row % bs; cidx = col % bs; \ 138 low = 0; high = nrow; \ 139 while (high-low > 3) { \ 140 t = (low+high)/2; \ 141 if (rp[t] > bcol) high = t; \ 142 else low = t; \ 143 } \ 144 for (_i=low; _i<high; _i++) { \ 145 if (rp[_i] > bcol) break; \ 146 if (rp[_i] == bcol) { \ 147 bap = ap + bs2*_i + bs*cidx + ridx; \ 148 if (addv == ADD_VALUES) *bap += value; \ 149 else *bap = value; \ 150 goto a_noinsert; \ 151 } \ 152 } \ 153 if (a->nonew == 1) goto a_noinsert; \ 154 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 155 MatSeqXAIJReallocateAIJ(a,bs2,nrow,brow,bcol,rmax,aa,ai,aj,a->mbs,rp,ap,aimax,a->nonew); \ 156 N = nrow++ - 1; \ 157 /* shift up all the later entries in this row */ \ 158 for (ii=N; ii>=_i; ii--) { \ 159 rp[ii+1] = rp[ii]; \ 160 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 161 } \ 162 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 163 rp[_i] = bcol; \ 164 ap[bs2*_i + bs*cidx + ridx] = value; \ 165 a_noinsert:; \ 166 ailen[brow] = nrow; \ 167 } 168 169 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 170 { \ 171 brow = row/bs; \ 172 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 173 rmax = bimax[brow]; nrow = bilen[brow]; \ 174 bcol = col/bs; \ 175 ridx = row % bs; cidx = col % bs; \ 176 low = 0; high = nrow; \ 177 while (high-low > 3) { \ 178 t = (low+high)/2; \ 179 if (rp[t] > bcol) high = t; \ 180 else low = t; \ 181 } \ 182 for (_i=low; _i<high; _i++) { \ 183 if (rp[_i] > bcol) break; \ 184 if (rp[_i] == bcol) { \ 185 bap = ap + bs2*_i + bs*cidx + ridx; \ 186 if (addv == ADD_VALUES) *bap += value; \ 187 else *bap = value; \ 188 goto b_noinsert; \ 189 } \ 190 } \ 191 if (b->nonew == 1) goto b_noinsert; \ 192 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 193 MatSeqXAIJReallocateAIJ(b,bs2,nrow,brow,bcol,rmax,ba,bi,bj,b->mbs,rp,ap,bimax,b->nonew); \ 194 CHKMEMQ;\ 195 N = nrow++ - 1; \ 196 /* shift up all the later entries in this row */ \ 197 for (ii=N; ii>=_i; ii--) { \ 198 rp[ii+1] = rp[ii]; \ 199 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 200 } \ 201 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 202 rp[_i] = bcol; \ 203 ap[bs2*_i + bs*cidx + ridx] = value; \ 204 b_noinsert:; \ 205 bilen[brow] = nrow; \ 206 } 207 208 #if defined(PETSC_USE_MAT_SINGLE) 209 #undef __FUNCT__ 210 #define __FUNCT__ "MatSetValues_MPIBAIJ" 211 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 212 { 213 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 214 PetscErrorCode ierr; 215 PetscInt i,N = m*n; 216 MatScalar *vsingle; 217 218 PetscFunctionBegin; 219 if (N > b->setvalueslen) { 220 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 221 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 222 b->setvalueslen = N; 223 } 224 vsingle = b->setvaluescopy; 225 226 for (i=0; i<N; i++) { 227 vsingle[i] = v[i]; 228 } 229 ierr = MatSetValues_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 230 PetscFunctionReturn(0); 231 } 232 233 #undef __FUNCT__ 234 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 235 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 236 { 237 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 238 PetscErrorCode ierr; 239 PetscInt i,N = m*n*b->bs2; 240 MatScalar *vsingle; 241 242 PetscFunctionBegin; 243 if (N > b->setvalueslen) { 244 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 245 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 246 b->setvalueslen = N; 247 } 248 vsingle = b->setvaluescopy; 249 for (i=0; i<N; i++) { 250 vsingle[i] = v[i]; 251 } 252 ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 258 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 259 { 260 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 261 PetscErrorCode ierr; 262 PetscInt i,N = m*n; 263 MatScalar *vsingle; 264 265 PetscFunctionBegin; 266 if (N > b->setvalueslen) { 267 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 268 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 269 b->setvalueslen = N; 270 } 271 vsingle = b->setvaluescopy; 272 for (i=0; i<N; i++) { 273 vsingle[i] = v[i]; 274 } 275 ierr = MatSetValues_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 276 PetscFunctionReturn(0); 277 } 278 279 #undef __FUNCT__ 280 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 281 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 282 { 283 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 284 PetscErrorCode ierr; 285 PetscInt i,N = m*n*b->bs2; 286 MatScalar *vsingle; 287 288 PetscFunctionBegin; 289 if (N > b->setvalueslen) { 290 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 291 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 292 b->setvalueslen = N; 293 } 294 vsingle = b->setvaluescopy; 295 for (i=0; i<N; i++) { 296 vsingle[i] = v[i]; 297 } 298 ierr = MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 299 PetscFunctionReturn(0); 300 } 301 #endif 302 303 #undef __FUNCT__ 304 #define __FUNCT__ "MatSetValues_MPIBAIJ_MatScalar" 305 PetscErrorCode MatSetValues_MPIBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 306 { 307 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 308 MatScalar value; 309 PetscTruth roworiented = baij->roworiented; 310 PetscErrorCode ierr; 311 PetscInt i,j,row,col; 312 PetscInt rstart_orig=baij->rstart_bs; 313 PetscInt rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 314 PetscInt cend_orig=baij->cend_bs,bs=mat->bs; 315 316 /* Some Variables required in the macro */ 317 Mat A = baij->A; 318 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 319 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 320 MatScalar *aa=a->a; 321 322 Mat B = baij->B; 323 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 324 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 325 MatScalar *ba=b->a; 326 327 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 328 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 329 MatScalar *ap,*bap; 330 331 PetscFunctionBegin; 332 for (i=0; i<m; i++) { 333 if (im[i] < 0) continue; 334 #if defined(PETSC_USE_DEBUG) 335 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->M-1); 336 #endif 337 if (im[i] >= rstart_orig && im[i] < rend_orig) { 338 row = im[i] - rstart_orig; 339 for (j=0; j<n; j++) { 340 if (in[j] >= cstart_orig && in[j] < cend_orig){ 341 col = in[j] - cstart_orig; 342 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 343 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 344 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 345 } else if (in[j] < 0) continue; 346 #if defined(PETSC_USE_DEBUG) 347 else if (in[j] >= mat->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[i],mat->N-1);} 348 #endif 349 else { 350 if (mat->was_assembled) { 351 if (!baij->colmap) { 352 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 353 } 354 #if defined (PETSC_USE_CTABLE) 355 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 356 col = col - 1; 357 #else 358 col = baij->colmap[in[j]/bs] - 1; 359 #endif 360 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 361 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 362 col = in[j]; 363 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 364 B = baij->B; 365 b = (Mat_SeqBAIJ*)(B)->data; 366 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 367 ba=b->a; 368 } else col += in[j]%bs; 369 } else col = in[j]; 370 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 371 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 372 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 373 } 374 } 375 } else { 376 if (!baij->donotstash) { 377 if (roworiented) { 378 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 379 } else { 380 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 381 } 382 } 383 } 384 } 385 PetscFunctionReturn(0); 386 } 387 388 #undef __FUNCT__ 389 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_MatScalar" 390 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 391 { 392 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 393 const MatScalar *value; 394 MatScalar *barray=baij->barray; 395 PetscTruth roworiented = baij->roworiented; 396 PetscErrorCode ierr; 397 PetscInt i,j,ii,jj,row,col,rstart=baij->rstart; 398 PetscInt rend=baij->rend,cstart=baij->cstart,stepval; 399 PetscInt cend=baij->cend,bs=mat->bs,bs2=baij->bs2; 400 401 PetscFunctionBegin; 402 if(!barray) { 403 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 404 baij->barray = barray; 405 } 406 407 if (roworiented) { 408 stepval = (n-1)*bs; 409 } else { 410 stepval = (m-1)*bs; 411 } 412 for (i=0; i<m; i++) { 413 if (im[i] < 0) continue; 414 #if defined(PETSC_USE_DEBUG) 415 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 416 #endif 417 if (im[i] >= rstart && im[i] < rend) { 418 row = im[i] - rstart; 419 for (j=0; j<n; j++) { 420 /* If NumCol = 1 then a copy is not required */ 421 if ((roworiented) && (n == 1)) { 422 barray = (MatScalar*)v + i*bs2; 423 } else if((!roworiented) && (m == 1)) { 424 barray = (MatScalar*)v + j*bs2; 425 } else { /* Here a copy is required */ 426 if (roworiented) { 427 value = v + i*(stepval+bs)*bs + j*bs; 428 } else { 429 value = v + j*(stepval+bs)*bs + i*bs; 430 } 431 for (ii=0; ii<bs; ii++,value+=stepval) { 432 for (jj=0; jj<bs; jj++) { 433 *barray++ = *value++; 434 } 435 } 436 barray -=bs2; 437 } 438 439 if (in[j] >= cstart && in[j] < cend){ 440 col = in[j] - cstart; 441 ierr = MatSetValuesBlocked_SeqBAIJ_MatScalar(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 442 } 443 else if (in[j] < 0) continue; 444 #if defined(PETSC_USE_DEBUG) 445 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 446 #endif 447 else { 448 if (mat->was_assembled) { 449 if (!baij->colmap) { 450 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 451 } 452 453 #if defined(PETSC_USE_DEBUG) 454 #if defined (PETSC_USE_CTABLE) 455 { PetscInt data; 456 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 457 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 458 } 459 #else 460 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 461 #endif 462 #endif 463 #if defined (PETSC_USE_CTABLE) 464 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 465 col = (col - 1)/bs; 466 #else 467 col = (baij->colmap[in[j]] - 1)/bs; 468 #endif 469 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 470 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 471 col = in[j]; 472 } 473 } 474 else col = in[j]; 475 ierr = MatSetValuesBlocked_SeqBAIJ_MatScalar(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 476 } 477 } 478 } else { 479 if (!baij->donotstash) { 480 if (roworiented) { 481 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 482 } else { 483 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 484 } 485 } 486 } 487 } 488 PetscFunctionReturn(0); 489 } 490 491 #define HASH_KEY 0.6180339887 492 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 493 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 494 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 495 #undef __FUNCT__ 496 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT_MatScalar" 497 PetscErrorCode MatSetValues_MPIBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 498 { 499 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 500 PetscTruth roworiented = baij->roworiented; 501 PetscErrorCode ierr; 502 PetscInt i,j,row,col; 503 PetscInt rstart_orig=baij->rstart_bs; 504 PetscInt rend_orig=baij->rend_bs,Nbs=baij->Nbs; 505 PetscInt h1,key,size=baij->ht_size,bs=mat->bs,*HT=baij->ht,idx; 506 PetscReal tmp; 507 MatScalar **HD = baij->hd,value; 508 #if defined(PETSC_USE_DEBUG) 509 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 510 #endif 511 512 PetscFunctionBegin; 513 514 for (i=0; i<m; i++) { 515 #if defined(PETSC_USE_DEBUG) 516 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 517 if (im[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->M-1); 518 #endif 519 row = im[i]; 520 if (row >= rstart_orig && row < rend_orig) { 521 for (j=0; j<n; j++) { 522 col = in[j]; 523 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 524 /* Look up PetscInto the Hash Table */ 525 key = (row/bs)*Nbs+(col/bs)+1; 526 h1 = HASH(size,key,tmp); 527 528 529 idx = h1; 530 #if defined(PETSC_USE_DEBUG) 531 insert_ct++; 532 total_ct++; 533 if (HT[idx] != key) { 534 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 535 if (idx == size) { 536 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 537 if (idx == h1) { 538 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 539 } 540 } 541 } 542 #else 543 if (HT[idx] != key) { 544 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 545 if (idx == size) { 546 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 547 if (idx == h1) { 548 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 549 } 550 } 551 } 552 #endif 553 /* A HASH table entry is found, so insert the values at the correct address */ 554 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 555 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 556 } 557 } else { 558 if (!baij->donotstash) { 559 if (roworiented) { 560 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 561 } else { 562 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 563 } 564 } 565 } 566 } 567 #if defined(PETSC_USE_DEBUG) 568 baij->ht_total_ct = total_ct; 569 baij->ht_insert_ct = insert_ct; 570 #endif 571 PetscFunctionReturn(0); 572 } 573 574 #undef __FUNCT__ 575 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT_MatScalar" 576 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 577 { 578 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 579 PetscTruth roworiented = baij->roworiented; 580 PetscErrorCode ierr; 581 PetscInt i,j,ii,jj,row,col; 582 PetscInt rstart=baij->rstart ; 583 PetscInt rend=baij->rend,stepval,bs=mat->bs,bs2=baij->bs2; 584 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 585 PetscReal tmp; 586 MatScalar **HD = baij->hd,*baij_a; 587 const MatScalar *v_t,*value; 588 #if defined(PETSC_USE_DEBUG) 589 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 590 #endif 591 592 PetscFunctionBegin; 593 594 if (roworiented) { 595 stepval = (n-1)*bs; 596 } else { 597 stepval = (m-1)*bs; 598 } 599 for (i=0; i<m; i++) { 600 #if defined(PETSC_USE_DEBUG) 601 if (im[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 602 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 603 #endif 604 row = im[i]; 605 v_t = v + i*bs2; 606 if (row >= rstart && row < rend) { 607 for (j=0; j<n; j++) { 608 col = in[j]; 609 610 /* Look up into the Hash Table */ 611 key = row*Nbs+col+1; 612 h1 = HASH(size,key,tmp); 613 614 idx = h1; 615 #if defined(PETSC_USE_DEBUG) 616 total_ct++; 617 insert_ct++; 618 if (HT[idx] != key) { 619 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 620 if (idx == size) { 621 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 622 if (idx == h1) { 623 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 624 } 625 } 626 } 627 #else 628 if (HT[idx] != key) { 629 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 630 if (idx == size) { 631 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 632 if (idx == h1) { 633 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 634 } 635 } 636 } 637 #endif 638 baij_a = HD[idx]; 639 if (roworiented) { 640 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 641 /* value = v + (i*(stepval+bs)+j)*bs; */ 642 value = v_t; 643 v_t += bs; 644 if (addv == ADD_VALUES) { 645 for (ii=0; ii<bs; ii++,value+=stepval) { 646 for (jj=ii; jj<bs2; jj+=bs) { 647 baij_a[jj] += *value++; 648 } 649 } 650 } else { 651 for (ii=0; ii<bs; ii++,value+=stepval) { 652 for (jj=ii; jj<bs2; jj+=bs) { 653 baij_a[jj] = *value++; 654 } 655 } 656 } 657 } else { 658 value = v + j*(stepval+bs)*bs + i*bs; 659 if (addv == ADD_VALUES) { 660 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 661 for (jj=0; jj<bs; jj++) { 662 baij_a[jj] += *value++; 663 } 664 } 665 } else { 666 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 667 for (jj=0; jj<bs; jj++) { 668 baij_a[jj] = *value++; 669 } 670 } 671 } 672 } 673 } 674 } else { 675 if (!baij->donotstash) { 676 if (roworiented) { 677 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 678 } else { 679 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 680 } 681 } 682 } 683 } 684 #if defined(PETSC_USE_DEBUG) 685 baij->ht_total_ct = total_ct; 686 baij->ht_insert_ct = insert_ct; 687 #endif 688 PetscFunctionReturn(0); 689 } 690 691 #undef __FUNCT__ 692 #define __FUNCT__ "MatGetValues_MPIBAIJ" 693 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 694 { 695 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 696 PetscErrorCode ierr; 697 PetscInt bs=mat->bs,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 698 PetscInt bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 699 700 PetscFunctionBegin; 701 for (i=0; i<m; i++) { 702 if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); 703 if (idxm[i] >= mat->M) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->M-1); 704 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 705 row = idxm[i] - bsrstart; 706 for (j=0; j<n; j++) { 707 if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); 708 if (idxn[j] >= mat->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->N-1); 709 if (idxn[j] >= bscstart && idxn[j] < bscend){ 710 col = idxn[j] - bscstart; 711 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 712 } else { 713 if (!baij->colmap) { 714 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 715 } 716 #if defined (PETSC_USE_CTABLE) 717 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 718 data --; 719 #else 720 data = baij->colmap[idxn[j]/bs]-1; 721 #endif 722 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 723 else { 724 col = data + idxn[j]%bs; 725 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 726 } 727 } 728 } 729 } else { 730 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 731 } 732 } 733 PetscFunctionReturn(0); 734 } 735 736 #undef __FUNCT__ 737 #define __FUNCT__ "MatNorm_MPIBAIJ" 738 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 739 { 740 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 741 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 742 PetscErrorCode ierr; 743 PetscInt i,j,bs2=baij->bs2,bs=baij->A->bs,nz,row,col; 744 PetscReal sum = 0.0; 745 MatScalar *v; 746 747 PetscFunctionBegin; 748 if (baij->size == 1) { 749 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 750 } else { 751 if (type == NORM_FROBENIUS) { 752 v = amat->a; 753 nz = amat->nz*bs2; 754 for (i=0; i<nz; i++) { 755 #if defined(PETSC_USE_COMPLEX) 756 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 757 #else 758 sum += (*v)*(*v); v++; 759 #endif 760 } 761 v = bmat->a; 762 nz = bmat->nz*bs2; 763 for (i=0; i<nz; i++) { 764 #if defined(PETSC_USE_COMPLEX) 765 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 766 #else 767 sum += (*v)*(*v); v++; 768 #endif 769 } 770 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 771 *nrm = sqrt(*nrm); 772 } else if (type == NORM_1) { /* max column sum */ 773 PetscReal *tmp,*tmp2; 774 PetscInt *jj,*garray=baij->garray,cstart=baij->cstart; 775 ierr = PetscMalloc((2*mat->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 776 tmp2 = tmp + mat->N; 777 ierr = PetscMemzero(tmp,mat->N*sizeof(PetscReal));CHKERRQ(ierr); 778 v = amat->a; jj = amat->j; 779 for (i=0; i<amat->nz; i++) { 780 for (j=0; j<bs; j++){ 781 col = bs*(cstart + *jj) + j; /* column index */ 782 for (row=0; row<bs; row++){ 783 tmp[col] += PetscAbsScalar(*v); v++; 784 } 785 } 786 jj++; 787 } 788 v = bmat->a; jj = bmat->j; 789 for (i=0; i<bmat->nz; i++) { 790 for (j=0; j<bs; j++){ 791 col = bs*garray[*jj] + j; 792 for (row=0; row<bs; row++){ 793 tmp[col] += PetscAbsScalar(*v); v++; 794 } 795 } 796 jj++; 797 } 798 ierr = MPI_Allreduce(tmp,tmp2,mat->N,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 799 *nrm = 0.0; 800 for (j=0; j<mat->N; j++) { 801 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 802 } 803 ierr = PetscFree(tmp);CHKERRQ(ierr); 804 } else if (type == NORM_INFINITY) { /* max row sum */ 805 PetscReal *sums; 806 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr) 807 sum = 0.0; 808 for (j=0; j<amat->mbs; j++) { 809 for (row=0; row<bs; row++) sums[row] = 0.0; 810 v = amat->a + bs2*amat->i[j]; 811 nz = amat->i[j+1]-amat->i[j]; 812 for (i=0; i<nz; i++) { 813 for (col=0; col<bs; col++){ 814 for (row=0; row<bs; row++){ 815 sums[row] += PetscAbsScalar(*v); v++; 816 } 817 } 818 } 819 v = bmat->a + bs2*bmat->i[j]; 820 nz = bmat->i[j+1]-bmat->i[j]; 821 for (i=0; i<nz; i++) { 822 for (col=0; col<bs; col++){ 823 for (row=0; row<bs; row++){ 824 sums[row] += PetscAbsScalar(*v); v++; 825 } 826 } 827 } 828 for (row=0; row<bs; row++){ 829 if (sums[row] > sum) sum = sums[row]; 830 } 831 } 832 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_MAX,mat->comm);CHKERRQ(ierr); 833 ierr = PetscFree(sums);CHKERRQ(ierr); 834 } else { 835 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 836 } 837 } 838 PetscFunctionReturn(0); 839 } 840 841 /* 842 Creates the hash table, and sets the table 843 This table is created only once. 844 If new entried need to be added to the matrix 845 then the hash table has to be destroyed and 846 recreated. 847 */ 848 #undef __FUNCT__ 849 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 850 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 851 { 852 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 853 Mat A = baij->A,B=baij->B; 854 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 855 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 856 PetscErrorCode ierr; 857 PetscInt size,bs2=baij->bs2,rstart=baij->rstart; 858 PetscInt cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs; 859 PetscInt *HT,key; 860 MatScalar **HD; 861 PetscReal tmp; 862 #if defined(PETSC_USE_DEBUG) 863 PetscInt ct=0,max=0; 864 #endif 865 866 PetscFunctionBegin; 867 baij->ht_size=(PetscInt)(factor*nz); 868 size = baij->ht_size; 869 870 if (baij->ht) { 871 PetscFunctionReturn(0); 872 } 873 874 /* Allocate Memory for Hash Table */ 875 ierr = PetscMalloc((size)*(sizeof(PetscInt)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr); 876 baij->ht = (PetscInt*)(baij->hd + size); 877 HD = baij->hd; 878 HT = baij->ht; 879 880 881 ierr = PetscMemzero(HD,size*(sizeof(PetscInt)+sizeof(PetscScalar*)));CHKERRQ(ierr); 882 883 884 /* Loop Over A */ 885 for (i=0; i<a->mbs; i++) { 886 for (j=ai[i]; j<ai[i+1]; j++) { 887 row = i+rstart; 888 col = aj[j]+cstart; 889 890 key = row*Nbs + col + 1; 891 h1 = HASH(size,key,tmp); 892 for (k=0; k<size; k++){ 893 if (!HT[(h1+k)%size]) { 894 HT[(h1+k)%size] = key; 895 HD[(h1+k)%size] = a->a + j*bs2; 896 break; 897 #if defined(PETSC_USE_DEBUG) 898 } else { 899 ct++; 900 #endif 901 } 902 } 903 #if defined(PETSC_USE_DEBUG) 904 if (k> max) max = k; 905 #endif 906 } 907 } 908 /* Loop Over B */ 909 for (i=0; i<b->mbs; i++) { 910 for (j=bi[i]; j<bi[i+1]; j++) { 911 row = i+rstart; 912 col = garray[bj[j]]; 913 key = row*Nbs + col + 1; 914 h1 = HASH(size,key,tmp); 915 for (k=0; k<size; k++){ 916 if (!HT[(h1+k)%size]) { 917 HT[(h1+k)%size] = key; 918 HD[(h1+k)%size] = b->a + j*bs2; 919 break; 920 #if defined(PETSC_USE_DEBUG) 921 } else { 922 ct++; 923 #endif 924 } 925 } 926 #if defined(PETSC_USE_DEBUG) 927 if (k> max) max = k; 928 #endif 929 } 930 } 931 932 /* Print Summary */ 933 #if defined(PETSC_USE_DEBUG) 934 for (i=0,j=0; i<size; i++) { 935 if (HT[i]) {j++;} 936 } 937 ierr = PetscLogInfo((0,"MatCreateHashTable_MPIBAIJ_Private: Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max));CHKERRQ(ierr); 938 #endif 939 PetscFunctionReturn(0); 940 } 941 942 #undef __FUNCT__ 943 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 944 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 945 { 946 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 947 PetscErrorCode ierr; 948 PetscInt nstash,reallocs; 949 InsertMode addv; 950 951 PetscFunctionBegin; 952 if (baij->donotstash) { 953 PetscFunctionReturn(0); 954 } 955 956 /* make sure all processors are either in INSERTMODE or ADDMODE */ 957 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 958 if (addv == (ADD_VALUES|INSERT_VALUES)) { 959 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 960 } 961 mat->insertmode = addv; /* in case this processor had no cache */ 962 963 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 964 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 965 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 966 ierr = PetscLogInfo((0,"MatAssemblyBegin_MPIBAIJ:Stash has %D entries,uses %D mallocs.\n",nstash,reallocs));CHKERRQ(ierr); 967 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 968 ierr = PetscLogInfo((0,"MatAssemblyBegin_MPIBAIJ:Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs));CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } 971 972 #undef __FUNCT__ 973 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 974 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 975 { 976 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 977 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data,*b=(Mat_SeqBAIJ*)baij->B->data; 978 PetscErrorCode ierr; 979 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 980 PetscInt *row,*col,other_disassembled; 981 PetscTruth r1,r2,r3; 982 MatScalar *val; 983 InsertMode addv = mat->insertmode; 984 PetscMPIInt n; 985 986 PetscFunctionBegin; 987 if (!baij->donotstash) { 988 while (1) { 989 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 990 if (!flg) break; 991 992 for (i=0; i<n;) { 993 /* Now identify the consecutive vals belonging to the same row */ 994 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 995 if (j < n) ncols = j-i; 996 else ncols = n-i; 997 /* Now assemble all these values with a single function call */ 998 ierr = MatSetValues_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 999 i = j; 1000 } 1001 } 1002 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 1003 /* Now process the block-stash. Since the values are stashed column-oriented, 1004 set the roworiented flag to column oriented, and after MatSetValues() 1005 restore the original flags */ 1006 r1 = baij->roworiented; 1007 r2 = a->roworiented; 1008 r3 = b->roworiented; 1009 baij->roworiented = PETSC_FALSE; 1010 a->roworiented = PETSC_FALSE; 1011 b->roworiented = PETSC_FALSE; 1012 while (1) { 1013 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 1014 if (!flg) break; 1015 1016 for (i=0; i<n;) { 1017 /* Now identify the consecutive vals belonging to the same row */ 1018 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 1019 if (j < n) ncols = j-i; 1020 else ncols = n-i; 1021 ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 1022 i = j; 1023 } 1024 } 1025 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 1026 baij->roworiented = r1; 1027 a->roworiented = r2; 1028 b->roworiented = r3; 1029 } 1030 1031 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 1032 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 1033 1034 /* determine if any processor has disassembled, if so we must 1035 also disassemble ourselfs, in order that we may reassemble. */ 1036 /* 1037 if nonzero structure of submatrix B cannot change then we know that 1038 no processor disassembled thus we can skip this stuff 1039 */ 1040 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 1041 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 1042 if (mat->was_assembled && !other_disassembled) { 1043 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 1044 } 1045 } 1046 1047 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 1048 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 1049 } 1050 b->compressedrow.use = PETSC_TRUE; 1051 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 1052 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 1053 1054 #if defined(PETSC_USE_DEBUG) 1055 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 1056 ierr = PetscLogInfo((0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct));CHKERRQ(ierr); 1057 baij->ht_total_ct = 0; 1058 baij->ht_insert_ct = 0; 1059 } 1060 #endif 1061 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 1062 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 1063 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 1064 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 1065 } 1066 1067 if (baij->rowvalues) { 1068 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1069 baij->rowvalues = 0; 1070 } 1071 PetscFunctionReturn(0); 1072 } 1073 1074 #undef __FUNCT__ 1075 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 1076 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1077 { 1078 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1079 PetscErrorCode ierr; 1080 PetscMPIInt size = baij->size,rank = baij->rank; 1081 PetscInt bs = mat->bs; 1082 PetscTruth iascii,isdraw; 1083 PetscViewer sviewer; 1084 PetscViewerFormat format; 1085 1086 PetscFunctionBegin; 1087 /* printf(" MatView_MPIBAIJ_ASCIIorDraworSocket is called ...\n"); */ 1088 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1089 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1090 if (iascii) { 1091 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1092 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1093 MatInfo info; 1094 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 1095 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1096 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 1097 rank,mat->m,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 1098 mat->bs,(PetscInt)info.memory);CHKERRQ(ierr); 1099 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1100 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 1101 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1102 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 1103 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1104 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 1105 PetscFunctionReturn(0); 1106 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1107 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1108 PetscFunctionReturn(0); 1109 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1110 PetscFunctionReturn(0); 1111 } 1112 } 1113 1114 if (isdraw) { 1115 PetscDraw draw; 1116 PetscTruth isnull; 1117 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1118 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1119 } 1120 1121 if (size == 1) { 1122 ierr = PetscObjectSetName((PetscObject)baij->A,mat->name);CHKERRQ(ierr); 1123 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1124 } else { 1125 /* assemble the entire matrix onto first processor. */ 1126 Mat A; 1127 Mat_SeqBAIJ *Aloc; 1128 PetscInt M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1129 MatScalar *a; 1130 1131 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1132 /* Perhaps this should be the type of mat? */ 1133 ierr = MatCreate(mat->comm,&A);CHKERRQ(ierr); 1134 if (!rank) { 1135 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1136 } else { 1137 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1138 } 1139 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1140 ierr = MatMPIBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1141 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1142 1143 /* copy over the A part */ 1144 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1145 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1146 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1147 1148 for (i=0; i<mbs; i++) { 1149 rvals[0] = bs*(baij->rstart + i); 1150 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1151 for (j=ai[i]; j<ai[i+1]; j++) { 1152 col = (baij->cstart+aj[j])*bs; 1153 for (k=0; k<bs; k++) { 1154 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1155 col++; a += bs; 1156 } 1157 } 1158 } 1159 /* copy over the B part */ 1160 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1161 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1162 for (i=0; i<mbs; i++) { 1163 rvals[0] = bs*(baij->rstart + i); 1164 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1165 for (j=ai[i]; j<ai[i+1]; j++) { 1166 col = baij->garray[aj[j]]*bs; 1167 for (k=0; k<bs; k++) { 1168 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1169 col++; a += bs; 1170 } 1171 } 1172 } 1173 ierr = PetscFree(rvals);CHKERRQ(ierr); 1174 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1175 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1176 /* 1177 Everyone has to call to draw the matrix since the graphics waits are 1178 synchronized across all processors that share the PetscDraw object 1179 */ 1180 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1181 if (!rank) { 1182 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 1183 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1184 } 1185 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1186 ierr = MatDestroy(A);CHKERRQ(ierr); 1187 } 1188 PetscFunctionReturn(0); 1189 } 1190 1191 #undef __FUNCT__ 1192 #define __FUNCT__ "MatView_MPIBAIJ" 1193 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1194 { 1195 PetscErrorCode ierr; 1196 PetscTruth iascii,isdraw,issocket,isbinary; 1197 1198 PetscFunctionBegin; 1199 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1200 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1201 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1202 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1203 if (iascii || isdraw || issocket || isbinary) { 1204 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1205 } else { 1206 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1207 } 1208 PetscFunctionReturn(0); 1209 } 1210 1211 #undef __FUNCT__ 1212 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1213 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1214 { 1215 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1216 PetscErrorCode ierr; 1217 1218 PetscFunctionBegin; 1219 #if defined(PETSC_USE_LOG) 1220 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 1221 #endif 1222 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1223 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1224 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 1225 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1226 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1227 #if defined (PETSC_USE_CTABLE) 1228 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 1229 #else 1230 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 1231 #endif 1232 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 1233 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1234 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1235 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 1236 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 1237 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 1238 #if defined(PETSC_USE_MAT_SINGLE) 1239 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 1240 #endif 1241 ierr = PetscFree(baij);CHKERRQ(ierr); 1242 1243 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1244 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1245 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1246 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1247 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1248 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1249 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1250 PetscFunctionReturn(0); 1251 } 1252 1253 #undef __FUNCT__ 1254 #define __FUNCT__ "MatMult_MPIBAIJ" 1255 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1256 { 1257 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1258 PetscErrorCode ierr; 1259 PetscInt nt; 1260 1261 PetscFunctionBegin; 1262 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1263 if (nt != A->n) { 1264 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1265 } 1266 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1267 if (nt != A->m) { 1268 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1269 } 1270 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1271 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1272 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1273 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1274 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1275 PetscFunctionReturn(0); 1276 } 1277 1278 #undef __FUNCT__ 1279 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1280 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1281 { 1282 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1283 PetscErrorCode ierr; 1284 1285 PetscFunctionBegin; 1286 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1287 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1288 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1289 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1290 PetscFunctionReturn(0); 1291 } 1292 1293 #undef __FUNCT__ 1294 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1295 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1296 { 1297 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1298 PetscErrorCode ierr; 1299 PetscTruth merged; 1300 1301 PetscFunctionBegin; 1302 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1303 /* do nondiagonal part */ 1304 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1305 if (!merged) { 1306 /* send it on its way */ 1307 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1308 /* do local part */ 1309 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1310 /* receive remote parts: note this assumes the values are not actually */ 1311 /* inserted in yy until the next line */ 1312 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1313 } else { 1314 /* do local part */ 1315 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1316 /* send it on its way */ 1317 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1318 /* values actually were received in the Begin() but we need to call this nop */ 1319 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1320 } 1321 PetscFunctionReturn(0); 1322 } 1323 1324 #undef __FUNCT__ 1325 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1326 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1327 { 1328 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1329 PetscErrorCode ierr; 1330 1331 PetscFunctionBegin; 1332 /* do nondiagonal part */ 1333 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1334 /* send it on its way */ 1335 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1336 /* do local part */ 1337 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1338 /* receive remote parts: note this assumes the values are not actually */ 1339 /* inserted in yy until the next line, which is true for my implementation*/ 1340 /* but is not perhaps always true. */ 1341 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1342 PetscFunctionReturn(0); 1343 } 1344 1345 /* 1346 This only works correctly for square matrices where the subblock A->A is the 1347 diagonal block 1348 */ 1349 #undef __FUNCT__ 1350 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1351 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1352 { 1353 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1354 PetscErrorCode ierr; 1355 1356 PetscFunctionBegin; 1357 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1358 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1359 PetscFunctionReturn(0); 1360 } 1361 1362 #undef __FUNCT__ 1363 #define __FUNCT__ "MatScale_MPIBAIJ" 1364 PetscErrorCode MatScale_MPIBAIJ(const PetscScalar *aa,Mat A) 1365 { 1366 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1367 PetscErrorCode ierr; 1368 1369 PetscFunctionBegin; 1370 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1371 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1372 PetscFunctionReturn(0); 1373 } 1374 1375 #undef __FUNCT__ 1376 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1377 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1378 { 1379 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1380 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1381 PetscErrorCode ierr; 1382 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1383 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1384 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1385 1386 PetscFunctionBegin; 1387 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1388 mat->getrowactive = PETSC_TRUE; 1389 1390 if (!mat->rowvalues && (idx || v)) { 1391 /* 1392 allocate enough space to hold information from the longest row. 1393 */ 1394 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1395 PetscInt max = 1,mbs = mat->mbs,tmp; 1396 for (i=0; i<mbs; i++) { 1397 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1398 if (max < tmp) { max = tmp; } 1399 } 1400 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1401 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1402 } 1403 1404 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1405 lrow = row - brstart; 1406 1407 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1408 if (!v) {pvA = 0; pvB = 0;} 1409 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1410 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1411 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1412 nztot = nzA + nzB; 1413 1414 cmap = mat->garray; 1415 if (v || idx) { 1416 if (nztot) { 1417 /* Sort by increasing column numbers, assuming A and B already sorted */ 1418 PetscInt imark = -1; 1419 if (v) { 1420 *v = v_p = mat->rowvalues; 1421 for (i=0; i<nzB; i++) { 1422 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1423 else break; 1424 } 1425 imark = i; 1426 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1427 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1428 } 1429 if (idx) { 1430 *idx = idx_p = mat->rowindices; 1431 if (imark > -1) { 1432 for (i=0; i<imark; i++) { 1433 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1434 } 1435 } else { 1436 for (i=0; i<nzB; i++) { 1437 if (cmap[cworkB[i]/bs] < cstart) 1438 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1439 else break; 1440 } 1441 imark = i; 1442 } 1443 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1444 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1445 } 1446 } else { 1447 if (idx) *idx = 0; 1448 if (v) *v = 0; 1449 } 1450 } 1451 *nz = nztot; 1452 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1453 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1454 PetscFunctionReturn(0); 1455 } 1456 1457 #undef __FUNCT__ 1458 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1459 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1460 { 1461 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1462 1463 PetscFunctionBegin; 1464 if (!baij->getrowactive) { 1465 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1466 } 1467 baij->getrowactive = PETSC_FALSE; 1468 PetscFunctionReturn(0); 1469 } 1470 1471 #undef __FUNCT__ 1472 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1473 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1474 { 1475 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1476 PetscErrorCode ierr; 1477 1478 PetscFunctionBegin; 1479 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1480 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1481 PetscFunctionReturn(0); 1482 } 1483 1484 #undef __FUNCT__ 1485 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1486 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1487 { 1488 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1489 Mat A = a->A,B = a->B; 1490 PetscErrorCode ierr; 1491 PetscReal isend[5],irecv[5]; 1492 1493 PetscFunctionBegin; 1494 info->block_size = (PetscReal)matin->bs; 1495 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1496 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1497 isend[3] = info->memory; isend[4] = info->mallocs; 1498 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1499 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1500 isend[3] += info->memory; isend[4] += info->mallocs; 1501 if (flag == MAT_LOCAL) { 1502 info->nz_used = isend[0]; 1503 info->nz_allocated = isend[1]; 1504 info->nz_unneeded = isend[2]; 1505 info->memory = isend[3]; 1506 info->mallocs = isend[4]; 1507 } else if (flag == MAT_GLOBAL_MAX) { 1508 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1509 info->nz_used = irecv[0]; 1510 info->nz_allocated = irecv[1]; 1511 info->nz_unneeded = irecv[2]; 1512 info->memory = irecv[3]; 1513 info->mallocs = irecv[4]; 1514 } else if (flag == MAT_GLOBAL_SUM) { 1515 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1516 info->nz_used = irecv[0]; 1517 info->nz_allocated = irecv[1]; 1518 info->nz_unneeded = irecv[2]; 1519 info->memory = irecv[3]; 1520 info->mallocs = irecv[4]; 1521 } else { 1522 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1523 } 1524 info->rows_global = (PetscReal)A->M; 1525 info->columns_global = (PetscReal)A->N; 1526 info->rows_local = (PetscReal)A->m; 1527 info->columns_local = (PetscReal)A->N; 1528 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1529 info->fill_ratio_needed = 0; 1530 info->factor_mallocs = 0; 1531 PetscFunctionReturn(0); 1532 } 1533 1534 #undef __FUNCT__ 1535 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1536 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op) 1537 { 1538 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1539 PetscErrorCode ierr; 1540 1541 PetscFunctionBegin; 1542 switch (op) { 1543 case MAT_NO_NEW_NONZERO_LOCATIONS: 1544 case MAT_YES_NEW_NONZERO_LOCATIONS: 1545 case MAT_COLUMNS_UNSORTED: 1546 case MAT_COLUMNS_SORTED: 1547 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1548 case MAT_KEEP_ZEROED_ROWS: 1549 case MAT_NEW_NONZERO_LOCATION_ERR: 1550 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1551 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1552 break; 1553 case MAT_ROW_ORIENTED: 1554 a->roworiented = PETSC_TRUE; 1555 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1556 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1557 break; 1558 case MAT_ROWS_SORTED: 1559 case MAT_ROWS_UNSORTED: 1560 case MAT_YES_NEW_DIAGONALS: 1561 ierr = PetscLogInfo((A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"));CHKERRQ(ierr); 1562 break; 1563 case MAT_COLUMN_ORIENTED: 1564 a->roworiented = PETSC_FALSE; 1565 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1566 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1567 break; 1568 case MAT_IGNORE_OFF_PROC_ENTRIES: 1569 a->donotstash = PETSC_TRUE; 1570 break; 1571 case MAT_NO_NEW_DIAGONALS: 1572 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1573 case MAT_USE_HASH_TABLE: 1574 a->ht_flag = PETSC_TRUE; 1575 break; 1576 case MAT_SYMMETRIC: 1577 case MAT_STRUCTURALLY_SYMMETRIC: 1578 case MAT_HERMITIAN: 1579 case MAT_SYMMETRY_ETERNAL: 1580 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1581 break; 1582 case MAT_NOT_SYMMETRIC: 1583 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1584 case MAT_NOT_HERMITIAN: 1585 case MAT_NOT_SYMMETRY_ETERNAL: 1586 break; 1587 default: 1588 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1589 } 1590 PetscFunctionReturn(0); 1591 } 1592 1593 #undef __FUNCT__ 1594 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1595 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1596 { 1597 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1598 Mat_SeqBAIJ *Aloc; 1599 Mat B; 1600 PetscErrorCode ierr; 1601 PetscInt M=A->M,N=A->N,*ai,*aj,i,*rvals,j,k,col; 1602 PetscInt bs=A->bs,mbs=baij->mbs; 1603 MatScalar *a; 1604 1605 PetscFunctionBegin; 1606 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1607 ierr = MatCreate(A->comm,&B);CHKERRQ(ierr); 1608 ierr = MatSetSizes(B,A->n,A->m,N,M);CHKERRQ(ierr); 1609 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 1610 ierr = MatMPIBAIJSetPreallocation(B,A->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1611 1612 /* copy over the A part */ 1613 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1614 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1615 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1616 1617 for (i=0; i<mbs; i++) { 1618 rvals[0] = bs*(baij->rstart + i); 1619 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1620 for (j=ai[i]; j<ai[i+1]; j++) { 1621 col = (baij->cstart+aj[j])*bs; 1622 for (k=0; k<bs; k++) { 1623 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1624 col++; a += bs; 1625 } 1626 } 1627 } 1628 /* copy over the B part */ 1629 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1630 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1631 for (i=0; i<mbs; i++) { 1632 rvals[0] = bs*(baij->rstart + i); 1633 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1634 for (j=ai[i]; j<ai[i+1]; j++) { 1635 col = baij->garray[aj[j]]*bs; 1636 for (k=0; k<bs; k++) { 1637 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1638 col++; a += bs; 1639 } 1640 } 1641 } 1642 ierr = PetscFree(rvals);CHKERRQ(ierr); 1643 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1644 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1645 1646 if (matout) { 1647 *matout = B; 1648 } else { 1649 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1650 } 1651 PetscFunctionReturn(0); 1652 } 1653 1654 #undef __FUNCT__ 1655 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1656 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1657 { 1658 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1659 Mat a = baij->A,b = baij->B; 1660 PetscErrorCode ierr; 1661 PetscInt s1,s2,s3; 1662 1663 PetscFunctionBegin; 1664 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1665 if (rr) { 1666 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1667 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1668 /* Overlap communication with computation. */ 1669 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1670 } 1671 if (ll) { 1672 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1673 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1674 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1675 } 1676 /* scale the diagonal block */ 1677 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1678 1679 if (rr) { 1680 /* Do a scatter end and then right scale the off-diagonal block */ 1681 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1682 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1683 } 1684 1685 PetscFunctionReturn(0); 1686 } 1687 1688 #undef __FUNCT__ 1689 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1690 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,IS is,const PetscScalar *diag) 1691 { 1692 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1693 PetscErrorCode ierr; 1694 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1695 PetscInt i,N,*rows,*owners = l->rowners; 1696 PetscInt *nprocs,j,idx,nsends,row; 1697 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1698 PetscInt *rvalues,tag = A->tag,count,base,slen,*source,lastidx = -1; 1699 PetscInt *lens,*lrows,*values,bs=A->bs,rstart_bs=l->rstart_bs; 1700 MPI_Comm comm = A->comm; 1701 MPI_Request *send_waits,*recv_waits; 1702 MPI_Status recv_status,*send_status; 1703 IS istmp; 1704 #if defined(PETSC_DEBUG) 1705 PetscTruth found = PETSC_FALSE; 1706 #endif 1707 1708 PetscFunctionBegin; 1709 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 1710 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1711 1712 /* first count number of contributors to each processor */ 1713 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1714 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1715 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1716 j = 0; 1717 for (i=0; i<N; i++) { 1718 if (lastidx > (idx = rows[i])) j = 0; 1719 lastidx = idx; 1720 for (; j<size; j++) { 1721 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1722 nprocs[2*j]++; 1723 nprocs[2*j+1] = 1; 1724 owner[i] = j; 1725 #if defined(PETSC_DEBUG) 1726 found = PETSC_TRUE; 1727 #endif 1728 break; 1729 } 1730 } 1731 #if defined(PETSC_DEBUG) 1732 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1733 found = PETSC_FALSE; 1734 #endif 1735 } 1736 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1737 1738 /* inform other processors of number of messages and max length*/ 1739 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1740 1741 /* post receives: */ 1742 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1743 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1744 for (i=0; i<nrecvs; i++) { 1745 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1746 } 1747 1748 /* do sends: 1749 1) starts[i] gives the starting index in svalues for stuff going to 1750 the ith processor 1751 */ 1752 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1753 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1754 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1755 starts[0] = 0; 1756 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1757 for (i=0; i<N; i++) { 1758 svalues[starts[owner[i]]++] = rows[i]; 1759 } 1760 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1761 1762 starts[0] = 0; 1763 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1764 count = 0; 1765 for (i=0; i<size; i++) { 1766 if (nprocs[2*i+1]) { 1767 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1768 } 1769 } 1770 ierr = PetscFree(starts);CHKERRQ(ierr); 1771 1772 base = owners[rank]*bs; 1773 1774 /* wait on receives */ 1775 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1776 source = lens + nrecvs; 1777 count = nrecvs; slen = 0; 1778 while (count) { 1779 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1780 /* unpack receives into our local space */ 1781 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1782 source[imdex] = recv_status.MPI_SOURCE; 1783 lens[imdex] = n; 1784 slen += n; 1785 count--; 1786 } 1787 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1788 1789 /* move the data into the send scatter */ 1790 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1791 count = 0; 1792 for (i=0; i<nrecvs; i++) { 1793 values = rvalues + i*nmax; 1794 for (j=0; j<lens[i]; j++) { 1795 lrows[count++] = values[j] - base; 1796 } 1797 } 1798 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1799 ierr = PetscFree(lens);CHKERRQ(ierr); 1800 ierr = PetscFree(owner);CHKERRQ(ierr); 1801 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1802 1803 /* actually zap the local rows */ 1804 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1805 ierr = PetscLogObjectParent(A,istmp);CHKERRQ(ierr); 1806 1807 /* 1808 Zero the required rows. If the "diagonal block" of the matrix 1809 is square and the user wishes to set the diagonal we use seperate 1810 code so that MatSetValues() is not called for each diagonal allocating 1811 new memory, thus calling lots of mallocs and slowing things down. 1812 1813 Contributed by: Mathew Knepley 1814 */ 1815 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1816 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1817 if (diag && (l->A->M == l->A->N)) { 1818 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1819 } else if (diag) { 1820 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1821 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1822 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1823 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1824 } 1825 for (i=0; i<slen; i++) { 1826 row = lrows[i] + rstart_bs; 1827 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1828 } 1829 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1830 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1831 } else { 1832 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1833 } 1834 1835 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1836 ierr = PetscFree(lrows);CHKERRQ(ierr); 1837 1838 /* wait on sends */ 1839 if (nsends) { 1840 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1841 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1842 ierr = PetscFree(send_status);CHKERRQ(ierr); 1843 } 1844 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1845 ierr = PetscFree(svalues);CHKERRQ(ierr); 1846 1847 PetscFunctionReturn(0); 1848 } 1849 1850 #undef __FUNCT__ 1851 #define __FUNCT__ "MatPrintHelp_MPIBAIJ" 1852 PetscErrorCode MatPrintHelp_MPIBAIJ(Mat A) 1853 { 1854 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1855 MPI_Comm comm = A->comm; 1856 static PetscTruth called = PETSC_FALSE; 1857 PetscErrorCode ierr; 1858 1859 PetscFunctionBegin; 1860 if (!a->rank) { 1861 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1862 } 1863 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1864 ierr = (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1865 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1866 PetscFunctionReturn(0); 1867 } 1868 1869 #undef __FUNCT__ 1870 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1871 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1872 { 1873 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1874 PetscErrorCode ierr; 1875 1876 PetscFunctionBegin; 1877 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1878 PetscFunctionReturn(0); 1879 } 1880 1881 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1882 1883 #undef __FUNCT__ 1884 #define __FUNCT__ "MatEqual_MPIBAIJ" 1885 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1886 { 1887 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1888 Mat a,b,c,d; 1889 PetscTruth flg; 1890 PetscErrorCode ierr; 1891 1892 PetscFunctionBegin; 1893 a = matA->A; b = matA->B; 1894 c = matB->A; d = matB->B; 1895 1896 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1897 if (flg) { 1898 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1899 } 1900 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1901 PetscFunctionReturn(0); 1902 } 1903 1904 1905 #undef __FUNCT__ 1906 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1907 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1908 { 1909 PetscErrorCode ierr; 1910 1911 PetscFunctionBegin; 1912 ierr = MatMPIBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1913 PetscFunctionReturn(0); 1914 } 1915 1916 /* -------------------------------------------------------------------*/ 1917 static struct _MatOps MatOps_Values = { 1918 MatSetValues_MPIBAIJ, 1919 MatGetRow_MPIBAIJ, 1920 MatRestoreRow_MPIBAIJ, 1921 MatMult_MPIBAIJ, 1922 /* 4*/ MatMultAdd_MPIBAIJ, 1923 MatMultTranspose_MPIBAIJ, 1924 MatMultTransposeAdd_MPIBAIJ, 1925 0, 1926 0, 1927 0, 1928 /*10*/ 0, 1929 0, 1930 0, 1931 0, 1932 MatTranspose_MPIBAIJ, 1933 /*15*/ MatGetInfo_MPIBAIJ, 1934 MatEqual_MPIBAIJ, 1935 MatGetDiagonal_MPIBAIJ, 1936 MatDiagonalScale_MPIBAIJ, 1937 MatNorm_MPIBAIJ, 1938 /*20*/ MatAssemblyBegin_MPIBAIJ, 1939 MatAssemblyEnd_MPIBAIJ, 1940 0, 1941 MatSetOption_MPIBAIJ, 1942 MatZeroEntries_MPIBAIJ, 1943 /*25*/ MatZeroRows_MPIBAIJ, 1944 0, 1945 0, 1946 0, 1947 0, 1948 /*30*/ MatSetUpPreallocation_MPIBAIJ, 1949 0, 1950 0, 1951 0, 1952 0, 1953 /*35*/ MatDuplicate_MPIBAIJ, 1954 0, 1955 0, 1956 0, 1957 0, 1958 /*40*/ 0, 1959 MatGetSubMatrices_MPIBAIJ, 1960 MatIncreaseOverlap_MPIBAIJ, 1961 MatGetValues_MPIBAIJ, 1962 0, 1963 /*45*/ MatPrintHelp_MPIBAIJ, 1964 MatScale_MPIBAIJ, 1965 0, 1966 0, 1967 0, 1968 /*50*/ 0, 1969 0, 1970 0, 1971 0, 1972 0, 1973 /*55*/ 0, 1974 0, 1975 MatSetUnfactored_MPIBAIJ, 1976 0, 1977 MatSetValuesBlocked_MPIBAIJ, 1978 /*60*/ 0, 1979 MatDestroy_MPIBAIJ, 1980 MatView_MPIBAIJ, 1981 MatGetPetscMaps_Petsc, 1982 0, 1983 /*65*/ 0, 1984 0, 1985 0, 1986 0, 1987 0, 1988 /*70*/ MatGetRowMax_MPIBAIJ, 1989 0, 1990 0, 1991 0, 1992 0, 1993 /*75*/ 0, 1994 0, 1995 0, 1996 0, 1997 0, 1998 /*80*/ 0, 1999 0, 2000 0, 2001 0, 2002 MatLoad_MPIBAIJ, 2003 /*85*/ 0, 2004 0, 2005 0, 2006 0, 2007 0, 2008 /*90*/ 0, 2009 0, 2010 0, 2011 0, 2012 0, 2013 /*95*/ 0, 2014 0, 2015 0, 2016 0}; 2017 2018 2019 EXTERN_C_BEGIN 2020 #undef __FUNCT__ 2021 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2022 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 2023 { 2024 PetscFunctionBegin; 2025 *a = ((Mat_MPIBAIJ *)A->data)->A; 2026 *iscopy = PETSC_FALSE; 2027 PetscFunctionReturn(0); 2028 } 2029 EXTERN_C_END 2030 2031 EXTERN_C_BEGIN 2032 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2033 EXTERN_C_END 2034 2035 #undef __FUNCT__ 2036 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2037 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt I[],const PetscInt J[],const PetscScalar v[]) 2038 { 2039 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 2040 PetscInt m = B->m/bs,cstart = b->cstart, cend = b->cend,j,nnz,i,d; 2041 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart = b->rstart,ii; 2042 const PetscInt *JJ; 2043 PetscScalar *values; 2044 PetscErrorCode ierr; 2045 2046 PetscFunctionBegin; 2047 #if defined(PETSC_OPT_g) 2048 if (I[0]) SETERRQ1(PETSC_ERR_ARG_RANGE,"I[0] must be 0 it is %D",I[0]); 2049 #endif 2050 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2051 o_nnz = d_nnz + m; 2052 2053 for (i=0; i<m; i++) { 2054 nnz = I[i+1]- I[i]; 2055 JJ = J + I[i]; 2056 nnz_max = PetscMax(nnz_max,nnz); 2057 #if defined(PETSC_OPT_g) 2058 if (nnz < 0) SETERRQ1(PETSC_ERR_ARG_RANGE,"Local row %D has a negative %D number of columns",i,nnz); 2059 #endif 2060 for (j=0; j<nnz; j++) { 2061 if (*JJ >= cstart) break; 2062 JJ++; 2063 } 2064 d = 0; 2065 for (; j<nnz; j++) { 2066 if (*JJ++ >= cend) break; 2067 d++; 2068 } 2069 d_nnz[i] = d; 2070 o_nnz[i] = nnz - d; 2071 } 2072 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2073 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2074 2075 if (v) values = (PetscScalar*)v; 2076 else { 2077 ierr = PetscMalloc(bs*bs*(nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2078 ierr = PetscMemzero(values,bs*bs*nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2079 } 2080 2081 ierr = MatSetOption(B,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2082 for (i=0; i<m; i++) { 2083 ii = i + rstart; 2084 nnz = I[i+1]- I[i]; 2085 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&ii,nnz,J+I[i],values,INSERT_VALUES);CHKERRQ(ierr); 2086 } 2087 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2088 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2089 ierr = MatSetOption(B,MAT_COLUMNS_UNSORTED);CHKERRQ(ierr); 2090 2091 if (!v) { 2092 ierr = PetscFree(values);CHKERRQ(ierr); 2093 } 2094 PetscFunctionReturn(0); 2095 } 2096 2097 #undef __FUNCT__ 2098 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2099 /*@C 2100 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2101 (the default parallel PETSc format). 2102 2103 Collective on MPI_Comm 2104 2105 Input Parameters: 2106 + A - the matrix 2107 . i - the indices into j for the start of each local row (starts with zero) 2108 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2109 - v - optional values in the matrix 2110 2111 Level: developer 2112 2113 .keywords: matrix, aij, compressed row, sparse, parallel 2114 2115 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2116 @*/ 2117 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2118 { 2119 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2120 2121 PetscFunctionBegin; 2122 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2123 if (f) { 2124 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2125 } 2126 PetscFunctionReturn(0); 2127 } 2128 2129 EXTERN_C_BEGIN 2130 #undef __FUNCT__ 2131 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2132 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2133 { 2134 Mat_MPIBAIJ *b; 2135 PetscErrorCode ierr; 2136 PetscInt i; 2137 2138 PetscFunctionBegin; 2139 B->preallocated = PETSC_TRUE; 2140 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2141 2142 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2143 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2144 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2145 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2146 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2147 if (d_nnz) { 2148 for (i=0; i<B->m/bs; i++) { 2149 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2150 } 2151 } 2152 if (o_nnz) { 2153 for (i=0; i<B->m/bs; i++) { 2154 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2155 } 2156 } 2157 2158 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 2159 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 2160 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 2161 ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 2162 2163 b = (Mat_MPIBAIJ*)B->data; 2164 B->bs = bs; 2165 b->bs2 = bs*bs; 2166 b->mbs = B->m/bs; 2167 b->nbs = B->n/bs; 2168 b->Mbs = B->M/bs; 2169 b->Nbs = B->N/bs; 2170 2171 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 2172 b->rowners[0] = 0; 2173 for (i=2; i<=b->size; i++) { 2174 b->rowners[i] += b->rowners[i-1]; 2175 } 2176 b->rstart = b->rowners[b->rank]; 2177 b->rend = b->rowners[b->rank+1]; 2178 2179 ierr = MPI_Allgather(&b->nbs,1,MPIU_INT,b->cowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 2180 b->cowners[0] = 0; 2181 for (i=2; i<=b->size; i++) { 2182 b->cowners[i] += b->cowners[i-1]; 2183 } 2184 b->cstart = b->cowners[b->rank]; 2185 b->cend = b->cowners[b->rank+1]; 2186 2187 for (i=0; i<=b->size; i++) { 2188 b->rowners_bs[i] = b->rowners[i]*bs; 2189 } 2190 b->rstart_bs = b->rstart*bs; 2191 b->rend_bs = b->rend*bs; 2192 b->cstart_bs = b->cstart*bs; 2193 b->cend_bs = b->cend*bs; 2194 2195 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2196 ierr = MatSetSizes(b->A,B->m,B->n,B->m,B->n);CHKERRQ(ierr); 2197 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2198 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2199 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2200 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2201 ierr = MatSetSizes(b->B,B->m,B->N,B->m,B->N);CHKERRQ(ierr); 2202 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2203 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2204 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2205 2206 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 2207 2208 PetscFunctionReturn(0); 2209 } 2210 EXTERN_C_END 2211 2212 EXTERN_C_BEGIN 2213 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2214 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2215 EXTERN_C_END 2216 2217 /*MC 2218 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2219 2220 Options Database Keys: 2221 . -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2222 2223 Level: beginner 2224 2225 .seealso: MatCreateMPIBAIJ 2226 M*/ 2227 2228 EXTERN_C_BEGIN 2229 #undef __FUNCT__ 2230 #define __FUNCT__ "MatCreate_MPIBAIJ" 2231 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2232 { 2233 Mat_MPIBAIJ *b; 2234 PetscErrorCode ierr; 2235 PetscTruth flg; 2236 2237 PetscFunctionBegin; 2238 ierr = PetscNew(Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2239 B->data = (void*)b; 2240 2241 2242 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2243 B->mapping = 0; 2244 B->factor = 0; 2245 B->assembled = PETSC_FALSE; 2246 2247 B->insertmode = NOT_SET_VALUES; 2248 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 2249 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 2250 2251 /* build local table of row and column ownerships */ 2252 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 2253 ierr = PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ));CHKERRQ(ierr); 2254 b->cowners = b->rowners + b->size + 2; 2255 b->rowners_bs = b->cowners + b->size + 2; 2256 2257 /* build cache for off array entries formed */ 2258 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 2259 b->donotstash = PETSC_FALSE; 2260 b->colmap = PETSC_NULL; 2261 b->garray = PETSC_NULL; 2262 b->roworiented = PETSC_TRUE; 2263 2264 #if defined(PETSC_USE_MAT_SINGLE) 2265 /* stuff for MatSetValues_XXX in single precision */ 2266 b->setvalueslen = 0; 2267 b->setvaluescopy = PETSC_NULL; 2268 #endif 2269 2270 /* stuff used in block assembly */ 2271 b->barray = 0; 2272 2273 /* stuff used for matrix vector multiply */ 2274 b->lvec = 0; 2275 b->Mvctx = 0; 2276 2277 /* stuff for MatGetRow() */ 2278 b->rowindices = 0; 2279 b->rowvalues = 0; 2280 b->getrowactive = PETSC_FALSE; 2281 2282 /* hash table stuff */ 2283 b->ht = 0; 2284 b->hd = 0; 2285 b->ht_size = 0; 2286 b->ht_flag = PETSC_FALSE; 2287 b->ht_fact = 0; 2288 b->ht_total_ct = 0; 2289 b->ht_insert_ct = 0; 2290 2291 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 2292 if (flg) { 2293 PetscReal fact = 1.39; 2294 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 2295 ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 2296 if (fact <= 1.0) fact = 1.39; 2297 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2298 ierr = PetscLogInfo((0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact));CHKERRQ(ierr); 2299 } 2300 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2301 "MatStoreValues_MPIBAIJ", 2302 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2303 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2304 "MatRetrieveValues_MPIBAIJ", 2305 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2306 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2307 "MatGetDiagonalBlock_MPIBAIJ", 2308 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2309 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2310 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2311 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2312 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2313 "MatMPIBAIJSetPreallocationCSR_MPIAIJ", 2314 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2315 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2316 "MatDiagonalScaleLocal_MPIBAIJ", 2317 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2318 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2319 "MatSetHashTableFactor_MPIBAIJ", 2320 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2321 PetscFunctionReturn(0); 2322 } 2323 EXTERN_C_END 2324 2325 /*MC 2326 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2327 2328 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2329 and MATMPIBAIJ otherwise. 2330 2331 Options Database Keys: 2332 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2333 2334 Level: beginner 2335 2336 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2337 M*/ 2338 2339 EXTERN_C_BEGIN 2340 #undef __FUNCT__ 2341 #define __FUNCT__ "MatCreate_BAIJ" 2342 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2343 { 2344 PetscErrorCode ierr; 2345 PetscMPIInt size; 2346 2347 PetscFunctionBegin; 2348 ierr = PetscObjectChangeTypeName((PetscObject)A,MATBAIJ);CHKERRQ(ierr); 2349 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2350 if (size == 1) { 2351 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2352 } else { 2353 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2354 } 2355 PetscFunctionReturn(0); 2356 } 2357 EXTERN_C_END 2358 2359 #undef __FUNCT__ 2360 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2361 /*@C 2362 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2363 (block compressed row). For good matrix assembly performance 2364 the user should preallocate the matrix storage by setting the parameters 2365 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2366 performance can be increased by more than a factor of 50. 2367 2368 Collective on Mat 2369 2370 Input Parameters: 2371 + A - the matrix 2372 . bs - size of blockk 2373 . d_nz - number of block nonzeros per block row in diagonal portion of local 2374 submatrix (same for all local rows) 2375 . d_nnz - array containing the number of block nonzeros in the various block rows 2376 of the in diagonal portion of the local (possibly different for each block 2377 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2378 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2379 submatrix (same for all local rows). 2380 - o_nnz - array containing the number of nonzeros in the various block rows of the 2381 off-diagonal portion of the local submatrix (possibly different for 2382 each block row) or PETSC_NULL. 2383 2384 If the *_nnz parameter is given then the *_nz parameter is ignored 2385 2386 Options Database Keys: 2387 . -mat_no_unroll - uses code that does not unroll the loops in the 2388 block calculations (much slower) 2389 . -mat_block_size - size of the blocks to use 2390 2391 Notes: 2392 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2393 than it must be used on all processors that share the object for that argument. 2394 2395 Storage Information: 2396 For a square global matrix we define each processor's diagonal portion 2397 to be its local rows and the corresponding columns (a square submatrix); 2398 each processor's off-diagonal portion encompasses the remainder of the 2399 local matrix (a rectangular submatrix). 2400 2401 The user can specify preallocated storage for the diagonal part of 2402 the local submatrix with either d_nz or d_nnz (not both). Set 2403 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2404 memory allocation. Likewise, specify preallocated storage for the 2405 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2406 2407 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2408 the figure below we depict these three local rows and all columns (0-11). 2409 2410 .vb 2411 0 1 2 3 4 5 6 7 8 9 10 11 2412 ------------------- 2413 row 3 | o o o d d d o o o o o o 2414 row 4 | o o o d d d o o o o o o 2415 row 5 | o o o d d d o o o o o o 2416 ------------------- 2417 .ve 2418 2419 Thus, any entries in the d locations are stored in the d (diagonal) 2420 submatrix, and any entries in the o locations are stored in the 2421 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2422 stored simply in the MATSEQBAIJ format for compressed row storage. 2423 2424 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2425 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2426 In general, for PDE problems in which most nonzeros are near the diagonal, 2427 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2428 or you will get TERRIBLE performance; see the users' manual chapter on 2429 matrices. 2430 2431 Level: intermediate 2432 2433 .keywords: matrix, block, aij, compressed row, sparse, parallel 2434 2435 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2436 @*/ 2437 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2438 { 2439 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2440 2441 PetscFunctionBegin; 2442 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2443 if (f) { 2444 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2445 } 2446 PetscFunctionReturn(0); 2447 } 2448 2449 #undef __FUNCT__ 2450 #define __FUNCT__ "MatCreateMPIBAIJ" 2451 /*@C 2452 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2453 (block compressed row). For good matrix assembly performance 2454 the user should preallocate the matrix storage by setting the parameters 2455 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2456 performance can be increased by more than a factor of 50. 2457 2458 Collective on MPI_Comm 2459 2460 Input Parameters: 2461 + comm - MPI communicator 2462 . bs - size of blockk 2463 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2464 This value should be the same as the local size used in creating the 2465 y vector for the matrix-vector product y = Ax. 2466 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2467 This value should be the same as the local size used in creating the 2468 x vector for the matrix-vector product y = Ax. 2469 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2470 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2471 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2472 submatrix (same for all local rows) 2473 . d_nnz - array containing the number of nonzero blocks in the various block rows 2474 of the in diagonal portion of the local (possibly different for each block 2475 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2476 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2477 submatrix (same for all local rows). 2478 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2479 off-diagonal portion of the local submatrix (possibly different for 2480 each block row) or PETSC_NULL. 2481 2482 Output Parameter: 2483 . A - the matrix 2484 2485 Options Database Keys: 2486 . -mat_no_unroll - uses code that does not unroll the loops in the 2487 block calculations (much slower) 2488 . -mat_block_size - size of the blocks to use 2489 2490 Notes: 2491 If the *_nnz parameter is given then the *_nz parameter is ignored 2492 2493 A nonzero block is any block that as 1 or more nonzeros in it 2494 2495 The user MUST specify either the local or global matrix dimensions 2496 (possibly both). 2497 2498 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2499 than it must be used on all processors that share the object for that argument. 2500 2501 Storage Information: 2502 For a square global matrix we define each processor's diagonal portion 2503 to be its local rows and the corresponding columns (a square submatrix); 2504 each processor's off-diagonal portion encompasses the remainder of the 2505 local matrix (a rectangular submatrix). 2506 2507 The user can specify preallocated storage for the diagonal part of 2508 the local submatrix with either d_nz or d_nnz (not both). Set 2509 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2510 memory allocation. Likewise, specify preallocated storage for the 2511 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2512 2513 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2514 the figure below we depict these three local rows and all columns (0-11). 2515 2516 .vb 2517 0 1 2 3 4 5 6 7 8 9 10 11 2518 ------------------- 2519 row 3 | o o o d d d o o o o o o 2520 row 4 | o o o d d d o o o o o o 2521 row 5 | o o o d d d o o o o o o 2522 ------------------- 2523 .ve 2524 2525 Thus, any entries in the d locations are stored in the d (diagonal) 2526 submatrix, and any entries in the o locations are stored in the 2527 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2528 stored simply in the MATSEQBAIJ format for compressed row storage. 2529 2530 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2531 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2532 In general, for PDE problems in which most nonzeros are near the diagonal, 2533 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2534 or you will get TERRIBLE performance; see the users' manual chapter on 2535 matrices. 2536 2537 Level: intermediate 2538 2539 .keywords: matrix, block, aij, compressed row, sparse, parallel 2540 2541 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2542 @*/ 2543 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIBAIJ(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) 2544 { 2545 PetscErrorCode ierr; 2546 PetscMPIInt size; 2547 2548 PetscFunctionBegin; 2549 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2550 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2551 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2552 if (size > 1) { 2553 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2554 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2555 } else { 2556 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2557 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2558 } 2559 PetscFunctionReturn(0); 2560 } 2561 2562 #undef __FUNCT__ 2563 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2564 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2565 { 2566 Mat mat; 2567 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2568 PetscErrorCode ierr; 2569 PetscInt len=0; 2570 2571 PetscFunctionBegin; 2572 *newmat = 0; 2573 ierr = MatCreate(matin->comm,&mat);CHKERRQ(ierr); 2574 ierr = MatSetSizes(mat,matin->m,matin->n,matin->M,matin->N);CHKERRQ(ierr); 2575 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2576 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2577 2578 mat->factor = matin->factor; 2579 mat->preallocated = PETSC_TRUE; 2580 mat->assembled = PETSC_TRUE; 2581 mat->insertmode = NOT_SET_VALUES; 2582 2583 a = (Mat_MPIBAIJ*)mat->data; 2584 mat->bs = matin->bs; 2585 a->bs2 = oldmat->bs2; 2586 a->mbs = oldmat->mbs; 2587 a->nbs = oldmat->nbs; 2588 a->Mbs = oldmat->Mbs; 2589 a->Nbs = oldmat->Nbs; 2590 2591 a->rstart = oldmat->rstart; 2592 a->rend = oldmat->rend; 2593 a->cstart = oldmat->cstart; 2594 a->cend = oldmat->cend; 2595 a->size = oldmat->size; 2596 a->rank = oldmat->rank; 2597 a->donotstash = oldmat->donotstash; 2598 a->roworiented = oldmat->roworiented; 2599 a->rowindices = 0; 2600 a->rowvalues = 0; 2601 a->getrowactive = PETSC_FALSE; 2602 a->barray = 0; 2603 a->rstart_bs = oldmat->rstart_bs; 2604 a->rend_bs = oldmat->rend_bs; 2605 a->cstart_bs = oldmat->cstart_bs; 2606 a->cend_bs = oldmat->cend_bs; 2607 2608 /* hash table stuff */ 2609 a->ht = 0; 2610 a->hd = 0; 2611 a->ht_size = 0; 2612 a->ht_flag = oldmat->ht_flag; 2613 a->ht_fact = oldmat->ht_fact; 2614 a->ht_total_ct = 0; 2615 a->ht_insert_ct = 0; 2616 2617 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2618 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2619 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2620 if (oldmat->colmap) { 2621 #if defined (PETSC_USE_CTABLE) 2622 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2623 #else 2624 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2625 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2626 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2627 #endif 2628 } else a->colmap = 0; 2629 2630 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2631 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2632 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2633 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2634 } else a->garray = 0; 2635 2636 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2637 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2638 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2639 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2640 2641 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2642 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2643 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2644 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2645 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 2646 *newmat = mat; 2647 2648 PetscFunctionReturn(0); 2649 } 2650 2651 #include "petscsys.h" 2652 2653 #undef __FUNCT__ 2654 #define __FUNCT__ "MatLoad_MPIBAIJ" 2655 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2656 { 2657 Mat A; 2658 PetscErrorCode ierr; 2659 int fd; 2660 PetscInt i,nz,j,rstart,rend; 2661 PetscScalar *vals,*buf; 2662 MPI_Comm comm = ((PetscObject)viewer)->comm; 2663 MPI_Status status; 2664 PetscMPIInt rank,size,maxnz; 2665 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2666 PetscInt *locrowlens,*procsnz = 0,*browners; 2667 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2668 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2669 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2670 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2671 2672 PetscFunctionBegin; 2673 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2674 2675 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2676 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2677 if (!rank) { 2678 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2679 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2680 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2681 } 2682 2683 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2684 M = header[1]; N = header[2]; 2685 2686 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2687 2688 /* 2689 This code adds extra rows to make sure the number of rows is 2690 divisible by the blocksize 2691 */ 2692 Mbs = M/bs; 2693 extra_rows = bs - M + bs*Mbs; 2694 if (extra_rows == bs) extra_rows = 0; 2695 else Mbs++; 2696 if (extra_rows && !rank) { 2697 ierr = PetscLogInfo((0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"));CHKERRQ(ierr); 2698 } 2699 2700 /* determine ownership of all rows */ 2701 mbs = Mbs/size + ((Mbs % size) > rank); 2702 m = mbs*bs; 2703 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2704 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2705 2706 /* process 0 needs enough room for process with most rows */ 2707 if (!rank) { 2708 mmax = rowners[1]; 2709 for (i=2; i<size; i++) { 2710 mmax = PetscMax(mmax,rowners[i]); 2711 } 2712 mmax*=bs; 2713 } else mmax = m; 2714 2715 rowners[0] = 0; 2716 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2717 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2718 rstart = rowners[rank]; 2719 rend = rowners[rank+1]; 2720 2721 /* distribute row lengths to all processors */ 2722 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2723 if (!rank) { 2724 mend = m; 2725 if (size == 1) mend = mend - extra_rows; 2726 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2727 for (j=mend; j<m; j++) locrowlens[j] = 1; 2728 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2729 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2730 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2731 for (j=0; j<m; j++) { 2732 procsnz[0] += locrowlens[j]; 2733 } 2734 for (i=1; i<size; i++) { 2735 mend = browners[i+1] - browners[i]; 2736 if (i == size-1) mend = mend - extra_rows; 2737 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2738 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2739 /* calculate the number of nonzeros on each processor */ 2740 for (j=0; j<browners[i+1]-browners[i]; j++) { 2741 procsnz[i] += rowlengths[j]; 2742 } 2743 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2744 } 2745 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2746 } else { 2747 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2748 } 2749 2750 if (!rank) { 2751 /* determine max buffer needed and allocate it */ 2752 maxnz = procsnz[0]; 2753 for (i=1; i<size; i++) { 2754 maxnz = PetscMax(maxnz,procsnz[i]); 2755 } 2756 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2757 2758 /* read in my part of the matrix column indices */ 2759 nz = procsnz[0]; 2760 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2761 mycols = ibuf; 2762 if (size == 1) nz -= extra_rows; 2763 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2764 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2765 2766 /* read in every ones (except the last) and ship off */ 2767 for (i=1; i<size-1; i++) { 2768 nz = procsnz[i]; 2769 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2770 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2771 } 2772 /* read in the stuff for the last proc */ 2773 if (size != 1) { 2774 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2775 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2776 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2777 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2778 } 2779 ierr = PetscFree(cols);CHKERRQ(ierr); 2780 } else { 2781 /* determine buffer space needed for message */ 2782 nz = 0; 2783 for (i=0; i<m; i++) { 2784 nz += locrowlens[i]; 2785 } 2786 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2787 mycols = ibuf; 2788 /* receive message of column indices*/ 2789 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2790 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2791 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2792 } 2793 2794 /* loop over local rows, determining number of off diagonal entries */ 2795 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2796 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2797 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2798 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2799 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2800 rowcount = 0; nzcount = 0; 2801 for (i=0; i<mbs; i++) { 2802 dcount = 0; 2803 odcount = 0; 2804 for (j=0; j<bs; j++) { 2805 kmax = locrowlens[rowcount]; 2806 for (k=0; k<kmax; k++) { 2807 tmp = mycols[nzcount++]/bs; 2808 if (!mask[tmp]) { 2809 mask[tmp] = 1; 2810 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2811 else masked1[dcount++] = tmp; 2812 } 2813 } 2814 rowcount++; 2815 } 2816 2817 dlens[i] = dcount; 2818 odlens[i] = odcount; 2819 2820 /* zero out the mask elements we set */ 2821 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2822 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2823 } 2824 2825 /* create our matrix */ 2826 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2827 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2828 ierr = MatSetType(A,type);CHKERRQ(ierr) 2829 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2830 2831 /* Why doesn't this called using ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); */ 2832 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2833 2834 if (!rank) { 2835 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2836 /* read in my part of the matrix numerical values */ 2837 nz = procsnz[0]; 2838 vals = buf; 2839 mycols = ibuf; 2840 if (size == 1) nz -= extra_rows; 2841 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2842 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2843 2844 /* insert into matrix */ 2845 jj = rstart*bs; 2846 for (i=0; i<m; i++) { 2847 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2848 mycols += locrowlens[i]; 2849 vals += locrowlens[i]; 2850 jj++; 2851 } 2852 /* read in other processors (except the last one) and ship out */ 2853 for (i=1; i<size-1; i++) { 2854 nz = procsnz[i]; 2855 vals = buf; 2856 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2857 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2858 } 2859 /* the last proc */ 2860 if (size != 1){ 2861 nz = procsnz[i] - extra_rows; 2862 vals = buf; 2863 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2864 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2865 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2866 } 2867 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2868 } else { 2869 /* receive numeric values */ 2870 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2871 2872 /* receive message of values*/ 2873 vals = buf; 2874 mycols = ibuf; 2875 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2876 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2877 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2878 2879 /* insert into matrix */ 2880 jj = rstart*bs; 2881 for (i=0; i<m; i++) { 2882 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2883 mycols += locrowlens[i]; 2884 vals += locrowlens[i]; 2885 jj++; 2886 } 2887 } 2888 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2889 ierr = PetscFree(buf);CHKERRQ(ierr); 2890 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2891 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2892 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2893 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2894 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2895 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2896 2897 *newmat = A; 2898 PetscFunctionReturn(0); 2899 } 2900 2901 #undef __FUNCT__ 2902 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2903 /*@ 2904 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2905 2906 Input Parameters: 2907 . mat - the matrix 2908 . fact - factor 2909 2910 Collective on Mat 2911 2912 Level: advanced 2913 2914 Notes: 2915 This can also be set by the command line option: -mat_use_hash_table fact 2916 2917 .keywords: matrix, hashtable, factor, HT 2918 2919 .seealso: MatSetOption() 2920 @*/ 2921 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2922 { 2923 PetscErrorCode ierr,(*f)(Mat,PetscReal); 2924 2925 PetscFunctionBegin; 2926 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 2927 if (f) { 2928 ierr = (*f)(mat,fact);CHKERRQ(ierr); 2929 } 2930 PetscFunctionReturn(0); 2931 } 2932 2933 EXTERN_C_BEGIN 2934 #undef __FUNCT__ 2935 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 2936 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 2937 { 2938 Mat_MPIBAIJ *baij; 2939 2940 PetscFunctionBegin; 2941 baij = (Mat_MPIBAIJ*)mat->data; 2942 baij->ht_fact = fact; 2943 PetscFunctionReturn(0); 2944 } 2945 EXTERN_C_END 2946 2947 #undef __FUNCT__ 2948 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2949 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 2950 { 2951 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2952 PetscFunctionBegin; 2953 *Ad = a->A; 2954 *Ao = a->B; 2955 *colmap = a->garray; 2956 PetscFunctionReturn(0); 2957 } 2958