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 if (!rank) { 1134 ierr = MatCreate(mat->comm,M,N,M,N,&A);CHKERRQ(ierr); 1135 } else { 1136 ierr = MatCreate(mat->comm,0,0,M,N,&A);CHKERRQ(ierr); 1137 } 1138 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1139 ierr = MatMPIBAIJSetPreallocation(A,mat->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1140 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1141 1142 /* copy over the A part */ 1143 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1144 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1145 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1146 1147 for (i=0; i<mbs; i++) { 1148 rvals[0] = bs*(baij->rstart + i); 1149 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1150 for (j=ai[i]; j<ai[i+1]; j++) { 1151 col = (baij->cstart+aj[j])*bs; 1152 for (k=0; k<bs; k++) { 1153 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1154 col++; a += bs; 1155 } 1156 } 1157 } 1158 /* copy over the B part */ 1159 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1160 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1161 for (i=0; i<mbs; i++) { 1162 rvals[0] = bs*(baij->rstart + i); 1163 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1164 for (j=ai[i]; j<ai[i+1]; j++) { 1165 col = baij->garray[aj[j]]*bs; 1166 for (k=0; k<bs; k++) { 1167 ierr = MatSetValues_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1168 col++; a += bs; 1169 } 1170 } 1171 } 1172 ierr = PetscFree(rvals);CHKERRQ(ierr); 1173 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1174 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1175 /* 1176 Everyone has to call to draw the matrix since the graphics waits are 1177 synchronized across all processors that share the PetscDraw object 1178 */ 1179 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1180 if (!rank) { 1181 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 1182 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1183 } 1184 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1185 ierr = MatDestroy(A);CHKERRQ(ierr); 1186 } 1187 PetscFunctionReturn(0); 1188 } 1189 1190 #undef __FUNCT__ 1191 #define __FUNCT__ "MatView_MPIBAIJ" 1192 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1193 { 1194 PetscErrorCode ierr; 1195 PetscTruth iascii,isdraw,issocket,isbinary; 1196 1197 PetscFunctionBegin; 1198 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1199 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1200 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1201 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1202 if (iascii || isdraw || issocket || isbinary) { 1203 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1204 } else { 1205 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1206 } 1207 PetscFunctionReturn(0); 1208 } 1209 1210 #undef __FUNCT__ 1211 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1212 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1213 { 1214 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1215 PetscErrorCode ierr; 1216 1217 PetscFunctionBegin; 1218 #if defined(PETSC_USE_LOG) 1219 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->M,mat->N); 1220 #endif 1221 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1222 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1223 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 1224 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1225 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1226 #if defined (PETSC_USE_CTABLE) 1227 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 1228 #else 1229 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 1230 #endif 1231 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 1232 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1233 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1234 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 1235 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 1236 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 1237 #if defined(PETSC_USE_MAT_SINGLE) 1238 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 1239 #endif 1240 ierr = PetscFree(baij);CHKERRQ(ierr); 1241 1242 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1243 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1244 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1245 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1246 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1247 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1248 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1249 PetscFunctionReturn(0); 1250 } 1251 1252 #undef __FUNCT__ 1253 #define __FUNCT__ "MatMult_MPIBAIJ" 1254 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1255 { 1256 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1257 PetscErrorCode ierr; 1258 PetscInt nt; 1259 1260 PetscFunctionBegin; 1261 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1262 if (nt != A->n) { 1263 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1264 } 1265 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1266 if (nt != A->m) { 1267 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1268 } 1269 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1270 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1271 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1272 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1273 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1274 PetscFunctionReturn(0); 1275 } 1276 1277 #undef __FUNCT__ 1278 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1279 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1280 { 1281 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1282 PetscErrorCode ierr; 1283 1284 PetscFunctionBegin; 1285 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1286 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1287 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1288 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1289 PetscFunctionReturn(0); 1290 } 1291 1292 #undef __FUNCT__ 1293 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1294 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1295 { 1296 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1297 PetscErrorCode ierr; 1298 PetscTruth merged; 1299 1300 PetscFunctionBegin; 1301 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1302 /* do nondiagonal part */ 1303 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1304 if (!merged) { 1305 /* send it on its way */ 1306 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1307 /* do local part */ 1308 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1309 /* receive remote parts: note this assumes the values are not actually */ 1310 /* inserted in yy until the next line */ 1311 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1312 } else { 1313 /* do local part */ 1314 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1315 /* send it on its way */ 1316 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1317 /* values actually were received in the Begin() but we need to call this nop */ 1318 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1319 } 1320 PetscFunctionReturn(0); 1321 } 1322 1323 #undef __FUNCT__ 1324 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1325 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1326 { 1327 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1328 PetscErrorCode ierr; 1329 1330 PetscFunctionBegin; 1331 /* do nondiagonal part */ 1332 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1333 /* send it on its way */ 1334 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1335 /* do local part */ 1336 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1337 /* receive remote parts: note this assumes the values are not actually */ 1338 /* inserted in yy until the next line, which is true for my implementation*/ 1339 /* but is not perhaps always true. */ 1340 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1341 PetscFunctionReturn(0); 1342 } 1343 1344 /* 1345 This only works correctly for square matrices where the subblock A->A is the 1346 diagonal block 1347 */ 1348 #undef __FUNCT__ 1349 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1350 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1351 { 1352 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1353 PetscErrorCode ierr; 1354 1355 PetscFunctionBegin; 1356 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1357 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1358 PetscFunctionReturn(0); 1359 } 1360 1361 #undef __FUNCT__ 1362 #define __FUNCT__ "MatScale_MPIBAIJ" 1363 PetscErrorCode MatScale_MPIBAIJ(const PetscScalar *aa,Mat A) 1364 { 1365 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1366 PetscErrorCode ierr; 1367 1368 PetscFunctionBegin; 1369 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 1370 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 1371 PetscFunctionReturn(0); 1372 } 1373 1374 #undef __FUNCT__ 1375 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1376 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1377 { 1378 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1379 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1380 PetscErrorCode ierr; 1381 PetscInt bs = matin->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1382 PetscInt nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 1383 PetscInt *cmap,*idx_p,cstart = mat->cstart; 1384 1385 PetscFunctionBegin; 1386 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1387 mat->getrowactive = PETSC_TRUE; 1388 1389 if (!mat->rowvalues && (idx || v)) { 1390 /* 1391 allocate enough space to hold information from the longest row. 1392 */ 1393 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1394 PetscInt max = 1,mbs = mat->mbs,tmp; 1395 for (i=0; i<mbs; i++) { 1396 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1397 if (max < tmp) { max = tmp; } 1398 } 1399 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1400 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1401 } 1402 1403 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1404 lrow = row - brstart; 1405 1406 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1407 if (!v) {pvA = 0; pvB = 0;} 1408 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1409 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1410 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1411 nztot = nzA + nzB; 1412 1413 cmap = mat->garray; 1414 if (v || idx) { 1415 if (nztot) { 1416 /* Sort by increasing column numbers, assuming A and B already sorted */ 1417 PetscInt imark = -1; 1418 if (v) { 1419 *v = v_p = mat->rowvalues; 1420 for (i=0; i<nzB; i++) { 1421 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1422 else break; 1423 } 1424 imark = i; 1425 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1426 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1427 } 1428 if (idx) { 1429 *idx = idx_p = mat->rowindices; 1430 if (imark > -1) { 1431 for (i=0; i<imark; i++) { 1432 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1433 } 1434 } else { 1435 for (i=0; i<nzB; i++) { 1436 if (cmap[cworkB[i]/bs] < cstart) 1437 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1438 else break; 1439 } 1440 imark = i; 1441 } 1442 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1443 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1444 } 1445 } else { 1446 if (idx) *idx = 0; 1447 if (v) *v = 0; 1448 } 1449 } 1450 *nz = nztot; 1451 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1452 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1453 PetscFunctionReturn(0); 1454 } 1455 1456 #undef __FUNCT__ 1457 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1458 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1459 { 1460 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1461 1462 PetscFunctionBegin; 1463 if (!baij->getrowactive) { 1464 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1465 } 1466 baij->getrowactive = PETSC_FALSE; 1467 PetscFunctionReturn(0); 1468 } 1469 1470 #undef __FUNCT__ 1471 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1472 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1473 { 1474 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1475 PetscErrorCode ierr; 1476 1477 PetscFunctionBegin; 1478 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1479 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1480 PetscFunctionReturn(0); 1481 } 1482 1483 #undef __FUNCT__ 1484 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1485 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1486 { 1487 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1488 Mat A = a->A,B = a->B; 1489 PetscErrorCode ierr; 1490 PetscReal isend[5],irecv[5]; 1491 1492 PetscFunctionBegin; 1493 info->block_size = (PetscReal)matin->bs; 1494 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1495 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1496 isend[3] = info->memory; isend[4] = info->mallocs; 1497 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1498 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1499 isend[3] += info->memory; isend[4] += info->mallocs; 1500 if (flag == MAT_LOCAL) { 1501 info->nz_used = isend[0]; 1502 info->nz_allocated = isend[1]; 1503 info->nz_unneeded = isend[2]; 1504 info->memory = isend[3]; 1505 info->mallocs = isend[4]; 1506 } else if (flag == MAT_GLOBAL_MAX) { 1507 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1508 info->nz_used = irecv[0]; 1509 info->nz_allocated = irecv[1]; 1510 info->nz_unneeded = irecv[2]; 1511 info->memory = irecv[3]; 1512 info->mallocs = irecv[4]; 1513 } else if (flag == MAT_GLOBAL_SUM) { 1514 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1515 info->nz_used = irecv[0]; 1516 info->nz_allocated = irecv[1]; 1517 info->nz_unneeded = irecv[2]; 1518 info->memory = irecv[3]; 1519 info->mallocs = irecv[4]; 1520 } else { 1521 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1522 } 1523 info->rows_global = (PetscReal)A->M; 1524 info->columns_global = (PetscReal)A->N; 1525 info->rows_local = (PetscReal)A->m; 1526 info->columns_local = (PetscReal)A->N; 1527 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1528 info->fill_ratio_needed = 0; 1529 info->factor_mallocs = 0; 1530 PetscFunctionReturn(0); 1531 } 1532 1533 #undef __FUNCT__ 1534 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1535 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op) 1536 { 1537 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1538 PetscErrorCode ierr; 1539 1540 PetscFunctionBegin; 1541 switch (op) { 1542 case MAT_NO_NEW_NONZERO_LOCATIONS: 1543 case MAT_YES_NEW_NONZERO_LOCATIONS: 1544 case MAT_COLUMNS_UNSORTED: 1545 case MAT_COLUMNS_SORTED: 1546 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1547 case MAT_KEEP_ZEROED_ROWS: 1548 case MAT_NEW_NONZERO_LOCATION_ERR: 1549 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1550 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1551 break; 1552 case MAT_ROW_ORIENTED: 1553 a->roworiented = PETSC_TRUE; 1554 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1555 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1556 break; 1557 case MAT_ROWS_SORTED: 1558 case MAT_ROWS_UNSORTED: 1559 case MAT_YES_NEW_DIAGONALS: 1560 ierr = PetscLogInfo((A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"));CHKERRQ(ierr); 1561 break; 1562 case MAT_COLUMN_ORIENTED: 1563 a->roworiented = PETSC_FALSE; 1564 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1565 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1566 break; 1567 case MAT_IGNORE_OFF_PROC_ENTRIES: 1568 a->donotstash = PETSC_TRUE; 1569 break; 1570 case MAT_NO_NEW_DIAGONALS: 1571 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1572 case MAT_USE_HASH_TABLE: 1573 a->ht_flag = PETSC_TRUE; 1574 break; 1575 case MAT_SYMMETRIC: 1576 case MAT_STRUCTURALLY_SYMMETRIC: 1577 case MAT_HERMITIAN: 1578 case MAT_SYMMETRY_ETERNAL: 1579 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1580 break; 1581 case MAT_NOT_SYMMETRIC: 1582 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 1583 case MAT_NOT_HERMITIAN: 1584 case MAT_NOT_SYMMETRY_ETERNAL: 1585 break; 1586 default: 1587 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1588 } 1589 PetscFunctionReturn(0); 1590 } 1591 1592 #undef __FUNCT__ 1593 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1594 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1595 { 1596 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1597 Mat_SeqBAIJ *Aloc; 1598 Mat B; 1599 PetscErrorCode ierr; 1600 PetscInt M=A->M,N=A->N,*ai,*aj,i,*rvals,j,k,col; 1601 PetscInt bs=A->bs,mbs=baij->mbs; 1602 MatScalar *a; 1603 1604 PetscFunctionBegin; 1605 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1606 ierr = MatCreate(A->comm,A->n,A->m,N,M,&B);CHKERRQ(ierr); 1607 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 1608 ierr = MatMPIBAIJSetPreallocation(B,A->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1609 1610 /* copy over the A part */ 1611 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1612 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1613 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1614 1615 for (i=0; i<mbs; i++) { 1616 rvals[0] = bs*(baij->rstart + i); 1617 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1618 for (j=ai[i]; j<ai[i+1]; j++) { 1619 col = (baij->cstart+aj[j])*bs; 1620 for (k=0; k<bs; k++) { 1621 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1622 col++; a += bs; 1623 } 1624 } 1625 } 1626 /* copy over the B part */ 1627 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1628 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1629 for (i=0; i<mbs; i++) { 1630 rvals[0] = bs*(baij->rstart + i); 1631 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1632 for (j=ai[i]; j<ai[i+1]; j++) { 1633 col = baij->garray[aj[j]]*bs; 1634 for (k=0; k<bs; k++) { 1635 ierr = MatSetValues_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1636 col++; a += bs; 1637 } 1638 } 1639 } 1640 ierr = PetscFree(rvals);CHKERRQ(ierr); 1641 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1642 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1643 1644 if (matout) { 1645 *matout = B; 1646 } else { 1647 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1648 } 1649 PetscFunctionReturn(0); 1650 } 1651 1652 #undef __FUNCT__ 1653 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1654 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1655 { 1656 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1657 Mat a = baij->A,b = baij->B; 1658 PetscErrorCode ierr; 1659 PetscInt s1,s2,s3; 1660 1661 PetscFunctionBegin; 1662 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1663 if (rr) { 1664 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1665 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1666 /* Overlap communication with computation. */ 1667 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1668 } 1669 if (ll) { 1670 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1671 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1672 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1673 } 1674 /* scale the diagonal block */ 1675 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1676 1677 if (rr) { 1678 /* Do a scatter end and then right scale the off-diagonal block */ 1679 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1680 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1681 } 1682 1683 PetscFunctionReturn(0); 1684 } 1685 1686 #undef __FUNCT__ 1687 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1688 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,IS is,const PetscScalar *diag) 1689 { 1690 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1691 PetscErrorCode ierr; 1692 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1693 PetscInt i,N,*rows,*owners = l->rowners; 1694 PetscInt *nprocs,j,idx,nsends,row; 1695 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1696 PetscInt *rvalues,tag = A->tag,count,base,slen,*source,lastidx = -1; 1697 PetscInt *lens,*lrows,*values,bs=A->bs,rstart_bs=l->rstart_bs; 1698 MPI_Comm comm = A->comm; 1699 MPI_Request *send_waits,*recv_waits; 1700 MPI_Status recv_status,*send_status; 1701 IS istmp; 1702 #if defined(PETSC_DEBUG) 1703 PetscTruth found = PETSC_FALSE; 1704 #endif 1705 1706 PetscFunctionBegin; 1707 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 1708 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1709 1710 /* first count number of contributors to each processor */ 1711 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1712 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1713 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1714 j = 0; 1715 for (i=0; i<N; i++) { 1716 if (lastidx > (idx = rows[i])) j = 0; 1717 lastidx = idx; 1718 for (; j<size; j++) { 1719 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1720 nprocs[2*j]++; 1721 nprocs[2*j+1] = 1; 1722 owner[i] = j; 1723 #if defined(PETSC_DEBUG) 1724 found = PETSC_TRUE; 1725 #endif 1726 break; 1727 } 1728 } 1729 #if defined(PETSC_DEBUG) 1730 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1731 found = PETSC_FALSE; 1732 #endif 1733 } 1734 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1735 1736 /* inform other processors of number of messages and max length*/ 1737 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1738 1739 /* post receives: */ 1740 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1741 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1742 for (i=0; i<nrecvs; i++) { 1743 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1744 } 1745 1746 /* do sends: 1747 1) starts[i] gives the starting index in svalues for stuff going to 1748 the ith processor 1749 */ 1750 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1751 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1752 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1753 starts[0] = 0; 1754 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1755 for (i=0; i<N; i++) { 1756 svalues[starts[owner[i]]++] = rows[i]; 1757 } 1758 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1759 1760 starts[0] = 0; 1761 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1762 count = 0; 1763 for (i=0; i<size; i++) { 1764 if (nprocs[2*i+1]) { 1765 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1766 } 1767 } 1768 ierr = PetscFree(starts);CHKERRQ(ierr); 1769 1770 base = owners[rank]*bs; 1771 1772 /* wait on receives */ 1773 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1774 source = lens + nrecvs; 1775 count = nrecvs; slen = 0; 1776 while (count) { 1777 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1778 /* unpack receives into our local space */ 1779 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1780 source[imdex] = recv_status.MPI_SOURCE; 1781 lens[imdex] = n; 1782 slen += n; 1783 count--; 1784 } 1785 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1786 1787 /* move the data into the send scatter */ 1788 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1789 count = 0; 1790 for (i=0; i<nrecvs; i++) { 1791 values = rvalues + i*nmax; 1792 for (j=0; j<lens[i]; j++) { 1793 lrows[count++] = values[j] - base; 1794 } 1795 } 1796 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1797 ierr = PetscFree(lens);CHKERRQ(ierr); 1798 ierr = PetscFree(owner);CHKERRQ(ierr); 1799 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1800 1801 /* actually zap the local rows */ 1802 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1803 ierr = PetscLogObjectParent(A,istmp);CHKERRQ(ierr); 1804 1805 /* 1806 Zero the required rows. If the "diagonal block" of the matrix 1807 is square and the user wishes to set the diagonal we use seperate 1808 code so that MatSetValues() is not called for each diagonal allocating 1809 new memory, thus calling lots of mallocs and slowing things down. 1810 1811 Contributed by: Mathew Knepley 1812 */ 1813 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1814 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1815 if (diag && (l->A->M == l->A->N)) { 1816 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1817 } else if (diag) { 1818 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1819 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1820 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1821 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1822 } 1823 for (i=0; i<slen; i++) { 1824 row = lrows[i] + rstart_bs; 1825 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1826 } 1827 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1828 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1829 } else { 1830 ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1831 } 1832 1833 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1834 ierr = PetscFree(lrows);CHKERRQ(ierr); 1835 1836 /* wait on sends */ 1837 if (nsends) { 1838 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1839 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1840 ierr = PetscFree(send_status);CHKERRQ(ierr); 1841 } 1842 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1843 ierr = PetscFree(svalues);CHKERRQ(ierr); 1844 1845 PetscFunctionReturn(0); 1846 } 1847 1848 #undef __FUNCT__ 1849 #define __FUNCT__ "MatPrintHelp_MPIBAIJ" 1850 PetscErrorCode MatPrintHelp_MPIBAIJ(Mat A) 1851 { 1852 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1853 MPI_Comm comm = A->comm; 1854 static PetscTruth called = PETSC_FALSE; 1855 PetscErrorCode ierr; 1856 1857 PetscFunctionBegin; 1858 if (!a->rank) { 1859 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1860 } 1861 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1862 ierr = (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1863 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1864 PetscFunctionReturn(0); 1865 } 1866 1867 #undef __FUNCT__ 1868 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1869 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1870 { 1871 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1872 PetscErrorCode ierr; 1873 1874 PetscFunctionBegin; 1875 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1876 PetscFunctionReturn(0); 1877 } 1878 1879 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1880 1881 #undef __FUNCT__ 1882 #define __FUNCT__ "MatEqual_MPIBAIJ" 1883 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1884 { 1885 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1886 Mat a,b,c,d; 1887 PetscTruth flg; 1888 PetscErrorCode ierr; 1889 1890 PetscFunctionBegin; 1891 a = matA->A; b = matA->B; 1892 c = matB->A; d = matB->B; 1893 1894 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1895 if (flg) { 1896 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1897 } 1898 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1899 PetscFunctionReturn(0); 1900 } 1901 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1905 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1906 { 1907 PetscErrorCode ierr; 1908 1909 PetscFunctionBegin; 1910 ierr = MatMPIBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1911 PetscFunctionReturn(0); 1912 } 1913 1914 /* -------------------------------------------------------------------*/ 1915 static struct _MatOps MatOps_Values = { 1916 MatSetValues_MPIBAIJ, 1917 MatGetRow_MPIBAIJ, 1918 MatRestoreRow_MPIBAIJ, 1919 MatMult_MPIBAIJ, 1920 /* 4*/ MatMultAdd_MPIBAIJ, 1921 MatMultTranspose_MPIBAIJ, 1922 MatMultTransposeAdd_MPIBAIJ, 1923 0, 1924 0, 1925 0, 1926 /*10*/ 0, 1927 0, 1928 0, 1929 0, 1930 MatTranspose_MPIBAIJ, 1931 /*15*/ MatGetInfo_MPIBAIJ, 1932 MatEqual_MPIBAIJ, 1933 MatGetDiagonal_MPIBAIJ, 1934 MatDiagonalScale_MPIBAIJ, 1935 MatNorm_MPIBAIJ, 1936 /*20*/ MatAssemblyBegin_MPIBAIJ, 1937 MatAssemblyEnd_MPIBAIJ, 1938 0, 1939 MatSetOption_MPIBAIJ, 1940 MatZeroEntries_MPIBAIJ, 1941 /*25*/ MatZeroRows_MPIBAIJ, 1942 0, 1943 0, 1944 0, 1945 0, 1946 /*30*/ MatSetUpPreallocation_MPIBAIJ, 1947 0, 1948 0, 1949 0, 1950 0, 1951 /*35*/ MatDuplicate_MPIBAIJ, 1952 0, 1953 0, 1954 0, 1955 0, 1956 /*40*/ 0, 1957 MatGetSubMatrices_MPIBAIJ, 1958 MatIncreaseOverlap_MPIBAIJ, 1959 MatGetValues_MPIBAIJ, 1960 0, 1961 /*45*/ MatPrintHelp_MPIBAIJ, 1962 MatScale_MPIBAIJ, 1963 0, 1964 0, 1965 0, 1966 /*50*/ 0, 1967 0, 1968 0, 1969 0, 1970 0, 1971 /*55*/ 0, 1972 0, 1973 MatSetUnfactored_MPIBAIJ, 1974 0, 1975 MatSetValuesBlocked_MPIBAIJ, 1976 /*60*/ 0, 1977 MatDestroy_MPIBAIJ, 1978 MatView_MPIBAIJ, 1979 MatGetPetscMaps_Petsc, 1980 0, 1981 /*65*/ 0, 1982 0, 1983 0, 1984 0, 1985 0, 1986 /*70*/ MatGetRowMax_MPIBAIJ, 1987 0, 1988 0, 1989 0, 1990 0, 1991 /*75*/ 0, 1992 0, 1993 0, 1994 0, 1995 0, 1996 /*80*/ 0, 1997 0, 1998 0, 1999 0, 2000 MatLoad_MPIBAIJ, 2001 /*85*/ 0, 2002 0, 2003 0, 2004 0, 2005 0, 2006 /*90*/ 0, 2007 0, 2008 0, 2009 0, 2010 0, 2011 /*95*/ 0, 2012 0, 2013 0, 2014 0}; 2015 2016 2017 EXTERN_C_BEGIN 2018 #undef __FUNCT__ 2019 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2020 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 2021 { 2022 PetscFunctionBegin; 2023 *a = ((Mat_MPIBAIJ *)A->data)->A; 2024 *iscopy = PETSC_FALSE; 2025 PetscFunctionReturn(0); 2026 } 2027 EXTERN_C_END 2028 2029 EXTERN_C_BEGIN 2030 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat,const MatType,MatReuse,Mat*); 2031 EXTERN_C_END 2032 2033 #undef __FUNCT__ 2034 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2035 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt I[],const PetscInt J[],const PetscScalar v[]) 2036 { 2037 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 2038 PetscInt m = B->m/bs,cstart = b->cstart, cend = b->cend,j,nnz,i,d; 2039 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart = b->rstart,ii; 2040 const PetscInt *JJ; 2041 PetscScalar *values; 2042 PetscErrorCode ierr; 2043 2044 PetscFunctionBegin; 2045 #if defined(PETSC_OPT_g) 2046 if (I[0]) SETERRQ1(PETSC_ERR_ARG_RANGE,"I[0] must be 0 it is %D",I[0]); 2047 #endif 2048 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2049 o_nnz = d_nnz + m; 2050 2051 for (i=0; i<m; i++) { 2052 nnz = I[i+1]- I[i]; 2053 JJ = J + I[i]; 2054 nnz_max = PetscMax(nnz_max,nnz); 2055 #if defined(PETSC_OPT_g) 2056 if (nnz < 0) SETERRQ1(PETSC_ERR_ARG_RANGE,"Local row %D has a negative %D number of columns",i,nnz); 2057 #endif 2058 for (j=0; j<nnz; j++) { 2059 if (*JJ >= cstart) break; 2060 JJ++; 2061 } 2062 d = 0; 2063 for (; j<nnz; j++) { 2064 if (*JJ++ >= cend) break; 2065 d++; 2066 } 2067 d_nnz[i] = d; 2068 o_nnz[i] = nnz - d; 2069 } 2070 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2071 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2072 2073 if (v) values = (PetscScalar*)v; 2074 else { 2075 ierr = PetscMalloc(bs*bs*(nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2076 ierr = PetscMemzero(values,bs*bs*nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2077 } 2078 2079 ierr = MatSetOption(B,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2080 for (i=0; i<m; i++) { 2081 ii = i + rstart; 2082 nnz = I[i+1]- I[i]; 2083 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&ii,nnz,J+I[i],values,INSERT_VALUES);CHKERRQ(ierr); 2084 } 2085 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2086 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2087 ierr = MatSetOption(B,MAT_COLUMNS_UNSORTED);CHKERRQ(ierr); 2088 2089 if (!v) { 2090 ierr = PetscFree(values);CHKERRQ(ierr); 2091 } 2092 PetscFunctionReturn(0); 2093 } 2094 2095 #undef __FUNCT__ 2096 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2097 /*@C 2098 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2099 (the default parallel PETSc format). 2100 2101 Collective on MPI_Comm 2102 2103 Input Parameters: 2104 + A - the matrix 2105 . i - the indices into j for the start of each local row (starts with zero) 2106 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2107 - v - optional values in the matrix 2108 2109 Level: developer 2110 2111 .keywords: matrix, aij, compressed row, sparse, parallel 2112 2113 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2114 @*/ 2115 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2116 { 2117 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2118 2119 PetscFunctionBegin; 2120 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2121 if (f) { 2122 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2123 } 2124 PetscFunctionReturn(0); 2125 } 2126 2127 EXTERN_C_BEGIN 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2130 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2131 { 2132 Mat_MPIBAIJ *b; 2133 PetscErrorCode ierr; 2134 PetscInt i; 2135 2136 PetscFunctionBegin; 2137 B->preallocated = PETSC_TRUE; 2138 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2139 2140 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2141 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2142 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2143 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2144 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2145 if (d_nnz) { 2146 for (i=0; i<B->m/bs; i++) { 2147 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]); 2148 } 2149 } 2150 if (o_nnz) { 2151 for (i=0; i<B->m/bs; i++) { 2152 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]); 2153 } 2154 } 2155 2156 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 2157 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 2158 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 2159 ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 2160 2161 b = (Mat_MPIBAIJ*)B->data; 2162 B->bs = bs; 2163 b->bs2 = bs*bs; 2164 b->mbs = B->m/bs; 2165 b->nbs = B->n/bs; 2166 b->Mbs = B->M/bs; 2167 b->Nbs = B->N/bs; 2168 2169 ierr = MPI_Allgather(&b->mbs,1,MPIU_INT,b->rowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 2170 b->rowners[0] = 0; 2171 for (i=2; i<=b->size; i++) { 2172 b->rowners[i] += b->rowners[i-1]; 2173 } 2174 b->rstart = b->rowners[b->rank]; 2175 b->rend = b->rowners[b->rank+1]; 2176 2177 ierr = MPI_Allgather(&b->nbs,1,MPIU_INT,b->cowners+1,1,MPIU_INT,B->comm);CHKERRQ(ierr); 2178 b->cowners[0] = 0; 2179 for (i=2; i<=b->size; i++) { 2180 b->cowners[i] += b->cowners[i-1]; 2181 } 2182 b->cstart = b->cowners[b->rank]; 2183 b->cend = b->cowners[b->rank+1]; 2184 2185 for (i=0; i<=b->size; i++) { 2186 b->rowners_bs[i] = b->rowners[i]*bs; 2187 } 2188 b->rstart_bs = b->rstart*bs; 2189 b->rend_bs = b->rend*bs; 2190 b->cstart_bs = b->cstart*bs; 2191 b->cend_bs = b->cend*bs; 2192 2193 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->n,B->m,B->n,&b->A);CHKERRQ(ierr); 2194 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2195 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2196 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2197 ierr = MatCreate(PETSC_COMM_SELF,B->m,B->N,B->m,B->N,&b->B);CHKERRQ(ierr); 2198 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2199 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2200 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2201 2202 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 2203 2204 PetscFunctionReturn(0); 2205 } 2206 EXTERN_C_END 2207 2208 EXTERN_C_BEGIN 2209 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2210 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2211 EXTERN_C_END 2212 2213 /*MC 2214 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2215 2216 Options Database Keys: 2217 . -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2218 2219 Level: beginner 2220 2221 .seealso: MatCreateMPIBAIJ 2222 M*/ 2223 2224 EXTERN_C_BEGIN 2225 #undef __FUNCT__ 2226 #define __FUNCT__ "MatCreate_MPIBAIJ" 2227 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2228 { 2229 Mat_MPIBAIJ *b; 2230 PetscErrorCode ierr; 2231 PetscTruth flg; 2232 2233 PetscFunctionBegin; 2234 ierr = PetscNew(Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2235 B->data = (void*)b; 2236 2237 2238 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2239 B->mapping = 0; 2240 B->factor = 0; 2241 B->assembled = PETSC_FALSE; 2242 2243 B->insertmode = NOT_SET_VALUES; 2244 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 2245 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 2246 2247 /* build local table of row and column ownerships */ 2248 ierr = PetscMalloc(3*(b->size+2)*sizeof(PetscInt),&b->rowners);CHKERRQ(ierr); 2249 ierr = PetscLogObjectMemory(B,3*(b->size+2)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ));CHKERRQ(ierr); 2250 b->cowners = b->rowners + b->size + 2; 2251 b->rowners_bs = b->cowners + b->size + 2; 2252 2253 /* build cache for off array entries formed */ 2254 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 2255 b->donotstash = PETSC_FALSE; 2256 b->colmap = PETSC_NULL; 2257 b->garray = PETSC_NULL; 2258 b->roworiented = PETSC_TRUE; 2259 2260 #if defined(PETSC_USE_MAT_SINGLE) 2261 /* stuff for MatSetValues_XXX in single precision */ 2262 b->setvalueslen = 0; 2263 b->setvaluescopy = PETSC_NULL; 2264 #endif 2265 2266 /* stuff used in block assembly */ 2267 b->barray = 0; 2268 2269 /* stuff used for matrix vector multiply */ 2270 b->lvec = 0; 2271 b->Mvctx = 0; 2272 2273 /* stuff for MatGetRow() */ 2274 b->rowindices = 0; 2275 b->rowvalues = 0; 2276 b->getrowactive = PETSC_FALSE; 2277 2278 /* hash table stuff */ 2279 b->ht = 0; 2280 b->hd = 0; 2281 b->ht_size = 0; 2282 b->ht_flag = PETSC_FALSE; 2283 b->ht_fact = 0; 2284 b->ht_total_ct = 0; 2285 b->ht_insert_ct = 0; 2286 2287 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 2288 if (flg) { 2289 PetscReal fact = 1.39; 2290 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 2291 ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 2292 if (fact <= 1.0) fact = 1.39; 2293 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2294 ierr = PetscLogInfo((0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact));CHKERRQ(ierr); 2295 } 2296 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2297 "MatStoreValues_MPIBAIJ", 2298 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2299 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2300 "MatRetrieveValues_MPIBAIJ", 2301 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2302 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2303 "MatGetDiagonalBlock_MPIBAIJ", 2304 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2305 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2306 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2307 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2308 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2309 "MatMPIBAIJSetPreallocationCSR_MPIAIJ", 2310 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2311 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2312 "MatDiagonalScaleLocal_MPIBAIJ", 2313 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2314 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2315 "MatSetHashTableFactor_MPIBAIJ", 2316 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2317 PetscFunctionReturn(0); 2318 } 2319 EXTERN_C_END 2320 2321 /*MC 2322 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2323 2324 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2325 and MATMPIBAIJ otherwise. 2326 2327 Options Database Keys: 2328 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2329 2330 Level: beginner 2331 2332 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2333 M*/ 2334 2335 EXTERN_C_BEGIN 2336 #undef __FUNCT__ 2337 #define __FUNCT__ "MatCreate_BAIJ" 2338 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2339 { 2340 PetscErrorCode ierr; 2341 PetscMPIInt size; 2342 2343 PetscFunctionBegin; 2344 ierr = PetscObjectChangeTypeName((PetscObject)A,MATBAIJ);CHKERRQ(ierr); 2345 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 2346 if (size == 1) { 2347 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2348 } else { 2349 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2350 } 2351 PetscFunctionReturn(0); 2352 } 2353 EXTERN_C_END 2354 2355 #undef __FUNCT__ 2356 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2357 /*@C 2358 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2359 (block compressed row). For good matrix assembly performance 2360 the user should preallocate the matrix storage by setting the parameters 2361 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2362 performance can be increased by more than a factor of 50. 2363 2364 Collective on Mat 2365 2366 Input Parameters: 2367 + A - the matrix 2368 . bs - size of blockk 2369 . d_nz - number of block nonzeros per block row in diagonal portion of local 2370 submatrix (same for all local rows) 2371 . d_nnz - array containing the number of block nonzeros in the various block rows 2372 of the in diagonal portion of the local (possibly different for each block 2373 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2374 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2375 submatrix (same for all local rows). 2376 - o_nnz - array containing the number of nonzeros in the various block rows of the 2377 off-diagonal portion of the local submatrix (possibly different for 2378 each block row) or PETSC_NULL. 2379 2380 If the *_nnz parameter is given then the *_nz parameter is ignored 2381 2382 Options Database Keys: 2383 . -mat_no_unroll - uses code that does not unroll the loops in the 2384 block calculations (much slower) 2385 . -mat_block_size - size of the blocks to use 2386 2387 Notes: 2388 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2389 than it must be used on all processors that share the object for that argument. 2390 2391 Storage Information: 2392 For a square global matrix we define each processor's diagonal portion 2393 to be its local rows and the corresponding columns (a square submatrix); 2394 each processor's off-diagonal portion encompasses the remainder of the 2395 local matrix (a rectangular submatrix). 2396 2397 The user can specify preallocated storage for the diagonal part of 2398 the local submatrix with either d_nz or d_nnz (not both). Set 2399 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2400 memory allocation. Likewise, specify preallocated storage for the 2401 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2402 2403 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2404 the figure below we depict these three local rows and all columns (0-11). 2405 2406 .vb 2407 0 1 2 3 4 5 6 7 8 9 10 11 2408 ------------------- 2409 row 3 | o o o d d d o o o o o o 2410 row 4 | o o o d d d o o o o o o 2411 row 5 | o o o d d d o o o o o o 2412 ------------------- 2413 .ve 2414 2415 Thus, any entries in the d locations are stored in the d (diagonal) 2416 submatrix, and any entries in the o locations are stored in the 2417 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2418 stored simply in the MATSEQBAIJ format for compressed row storage. 2419 2420 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2421 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2422 In general, for PDE problems in which most nonzeros are near the diagonal, 2423 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2424 or you will get TERRIBLE performance; see the users' manual chapter on 2425 matrices. 2426 2427 Level: intermediate 2428 2429 .keywords: matrix, block, aij, compressed row, sparse, parallel 2430 2431 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2432 @*/ 2433 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2434 { 2435 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2436 2437 PetscFunctionBegin; 2438 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2439 if (f) { 2440 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2441 } 2442 PetscFunctionReturn(0); 2443 } 2444 2445 #undef __FUNCT__ 2446 #define __FUNCT__ "MatCreateMPIBAIJ" 2447 /*@C 2448 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2449 (block compressed row). For good matrix assembly performance 2450 the user should preallocate the matrix storage by setting the parameters 2451 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2452 performance can be increased by more than a factor of 50. 2453 2454 Collective on MPI_Comm 2455 2456 Input Parameters: 2457 + comm - MPI communicator 2458 . bs - size of blockk 2459 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2460 This value should be the same as the local size used in creating the 2461 y vector for the matrix-vector product y = Ax. 2462 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2463 This value should be the same as the local size used in creating the 2464 x vector for the matrix-vector product y = Ax. 2465 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2466 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2467 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2468 submatrix (same for all local rows) 2469 . d_nnz - array containing the number of nonzero blocks in the various block rows 2470 of the in diagonal portion of the local (possibly different for each block 2471 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2472 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2473 submatrix (same for all local rows). 2474 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2475 off-diagonal portion of the local submatrix (possibly different for 2476 each block row) or PETSC_NULL. 2477 2478 Output Parameter: 2479 . A - the matrix 2480 2481 Options Database Keys: 2482 . -mat_no_unroll - uses code that does not unroll the loops in the 2483 block calculations (much slower) 2484 . -mat_block_size - size of the blocks to use 2485 2486 Notes: 2487 If the *_nnz parameter is given then the *_nz parameter is ignored 2488 2489 A nonzero block is any block that as 1 or more nonzeros in it 2490 2491 The user MUST specify either the local or global matrix dimensions 2492 (possibly both). 2493 2494 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2495 than it must be used on all processors that share the object for that argument. 2496 2497 Storage Information: 2498 For a square global matrix we define each processor's diagonal portion 2499 to be its local rows and the corresponding columns (a square submatrix); 2500 each processor's off-diagonal portion encompasses the remainder of the 2501 local matrix (a rectangular submatrix). 2502 2503 The user can specify preallocated storage for the diagonal part of 2504 the local submatrix with either d_nz or d_nnz (not both). Set 2505 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2506 memory allocation. Likewise, specify preallocated storage for the 2507 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2508 2509 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2510 the figure below we depict these three local rows and all columns (0-11). 2511 2512 .vb 2513 0 1 2 3 4 5 6 7 8 9 10 11 2514 ------------------- 2515 row 3 | o o o d d d o o o o o o 2516 row 4 | o o o d d d o o o o o o 2517 row 5 | o o o d d d o o o o o o 2518 ------------------- 2519 .ve 2520 2521 Thus, any entries in the d locations are stored in the d (diagonal) 2522 submatrix, and any entries in the o locations are stored in the 2523 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2524 stored simply in the MATSEQBAIJ format for compressed row storage. 2525 2526 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2527 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2528 In general, for PDE problems in which most nonzeros are near the diagonal, 2529 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2530 or you will get TERRIBLE performance; see the users' manual chapter on 2531 matrices. 2532 2533 Level: intermediate 2534 2535 .keywords: matrix, block, aij, compressed row, sparse, parallel 2536 2537 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2538 @*/ 2539 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) 2540 { 2541 PetscErrorCode ierr; 2542 PetscMPIInt size; 2543 2544 PetscFunctionBegin; 2545 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2546 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2547 if (size > 1) { 2548 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2549 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2550 } else { 2551 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2552 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2553 } 2554 PetscFunctionReturn(0); 2555 } 2556 2557 #undef __FUNCT__ 2558 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2559 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2560 { 2561 Mat mat; 2562 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2563 PetscErrorCode ierr; 2564 PetscInt len=0; 2565 2566 PetscFunctionBegin; 2567 *newmat = 0; 2568 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 2569 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2570 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2571 2572 mat->factor = matin->factor; 2573 mat->preallocated = PETSC_TRUE; 2574 mat->assembled = PETSC_TRUE; 2575 mat->insertmode = NOT_SET_VALUES; 2576 2577 a = (Mat_MPIBAIJ*)mat->data; 2578 mat->bs = matin->bs; 2579 a->bs2 = oldmat->bs2; 2580 a->mbs = oldmat->mbs; 2581 a->nbs = oldmat->nbs; 2582 a->Mbs = oldmat->Mbs; 2583 a->Nbs = oldmat->Nbs; 2584 2585 a->rstart = oldmat->rstart; 2586 a->rend = oldmat->rend; 2587 a->cstart = oldmat->cstart; 2588 a->cend = oldmat->cend; 2589 a->size = oldmat->size; 2590 a->rank = oldmat->rank; 2591 a->donotstash = oldmat->donotstash; 2592 a->roworiented = oldmat->roworiented; 2593 a->rowindices = 0; 2594 a->rowvalues = 0; 2595 a->getrowactive = PETSC_FALSE; 2596 a->barray = 0; 2597 a->rstart_bs = oldmat->rstart_bs; 2598 a->rend_bs = oldmat->rend_bs; 2599 a->cstart_bs = oldmat->cstart_bs; 2600 a->cend_bs = oldmat->cend_bs; 2601 2602 /* hash table stuff */ 2603 a->ht = 0; 2604 a->hd = 0; 2605 a->ht_size = 0; 2606 a->ht_flag = oldmat->ht_flag; 2607 a->ht_fact = oldmat->ht_fact; 2608 a->ht_total_ct = 0; 2609 a->ht_insert_ct = 0; 2610 2611 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2612 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2613 ierr = MatStashCreate_Private(matin->comm,matin->bs,&mat->bstash);CHKERRQ(ierr); 2614 if (oldmat->colmap) { 2615 #if defined (PETSC_USE_CTABLE) 2616 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2617 #else 2618 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2619 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2620 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2621 #endif 2622 } else a->colmap = 0; 2623 2624 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2625 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2626 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2627 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2628 } else a->garray = 0; 2629 2630 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2631 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2632 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2633 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2634 2635 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2636 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2637 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2638 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2639 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 2640 *newmat = mat; 2641 2642 PetscFunctionReturn(0); 2643 } 2644 2645 #include "petscsys.h" 2646 2647 #undef __FUNCT__ 2648 #define __FUNCT__ "MatLoad_MPIBAIJ" 2649 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer,const MatType type,Mat *newmat) 2650 { 2651 Mat A; 2652 PetscErrorCode ierr; 2653 int fd; 2654 PetscInt i,nz,j,rstart,rend; 2655 PetscScalar *vals,*buf; 2656 MPI_Comm comm = ((PetscObject)viewer)->comm; 2657 MPI_Status status; 2658 PetscMPIInt rank,size,maxnz; 2659 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2660 PetscInt *locrowlens,*procsnz = 0,*browners; 2661 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2662 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2663 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2664 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2665 2666 PetscFunctionBegin; 2667 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2668 2669 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2670 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2671 if (!rank) { 2672 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2673 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2674 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2675 } 2676 2677 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2678 M = header[1]; N = header[2]; 2679 2680 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2681 2682 /* 2683 This code adds extra rows to make sure the number of rows is 2684 divisible by the blocksize 2685 */ 2686 Mbs = M/bs; 2687 extra_rows = bs - M + bs*Mbs; 2688 if (extra_rows == bs) extra_rows = 0; 2689 else Mbs++; 2690 if (extra_rows && !rank) { 2691 ierr = PetscLogInfo((0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"));CHKERRQ(ierr); 2692 } 2693 2694 /* determine ownership of all rows */ 2695 mbs = Mbs/size + ((Mbs % size) > rank); 2696 m = mbs*bs; 2697 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2698 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2699 2700 /* process 0 needs enough room for process with most rows */ 2701 if (!rank) { 2702 mmax = rowners[1]; 2703 for (i=2; i<size; i++) { 2704 mmax = PetscMax(mmax,rowners[i]); 2705 } 2706 mmax*=bs; 2707 } else mmax = m; 2708 2709 rowners[0] = 0; 2710 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2711 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2712 rstart = rowners[rank]; 2713 rend = rowners[rank+1]; 2714 2715 /* distribute row lengths to all processors */ 2716 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2717 if (!rank) { 2718 mend = m; 2719 if (size == 1) mend = mend - extra_rows; 2720 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2721 for (j=mend; j<m; j++) locrowlens[j] = 1; 2722 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2723 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2724 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2725 for (j=0; j<m; j++) { 2726 procsnz[0] += locrowlens[j]; 2727 } 2728 for (i=1; i<size; i++) { 2729 mend = browners[i+1] - browners[i]; 2730 if (i == size-1) mend = mend - extra_rows; 2731 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2732 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2733 /* calculate the number of nonzeros on each processor */ 2734 for (j=0; j<browners[i+1]-browners[i]; j++) { 2735 procsnz[i] += rowlengths[j]; 2736 } 2737 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2738 } 2739 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2740 } else { 2741 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2742 } 2743 2744 if (!rank) { 2745 /* determine max buffer needed and allocate it */ 2746 maxnz = procsnz[0]; 2747 for (i=1; i<size; i++) { 2748 maxnz = PetscMax(maxnz,procsnz[i]); 2749 } 2750 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2751 2752 /* read in my part of the matrix column indices */ 2753 nz = procsnz[0]; 2754 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2755 mycols = ibuf; 2756 if (size == 1) nz -= extra_rows; 2757 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2758 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2759 2760 /* read in every ones (except the last) and ship off */ 2761 for (i=1; i<size-1; i++) { 2762 nz = procsnz[i]; 2763 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2764 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2765 } 2766 /* read in the stuff for the last proc */ 2767 if (size != 1) { 2768 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2769 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2770 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2771 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2772 } 2773 ierr = PetscFree(cols);CHKERRQ(ierr); 2774 } else { 2775 /* determine buffer space needed for message */ 2776 nz = 0; 2777 for (i=0; i<m; i++) { 2778 nz += locrowlens[i]; 2779 } 2780 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2781 mycols = ibuf; 2782 /* receive message of column indices*/ 2783 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2784 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2785 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2786 } 2787 2788 /* loop over local rows, determining number of off diagonal entries */ 2789 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2790 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2791 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2792 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2793 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2794 rowcount = 0; nzcount = 0; 2795 for (i=0; i<mbs; i++) { 2796 dcount = 0; 2797 odcount = 0; 2798 for (j=0; j<bs; j++) { 2799 kmax = locrowlens[rowcount]; 2800 for (k=0; k<kmax; k++) { 2801 tmp = mycols[nzcount++]/bs; 2802 if (!mask[tmp]) { 2803 mask[tmp] = 1; 2804 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2805 else masked1[dcount++] = tmp; 2806 } 2807 } 2808 rowcount++; 2809 } 2810 2811 dlens[i] = dcount; 2812 odlens[i] = odcount; 2813 2814 /* zero out the mask elements we set */ 2815 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2816 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2817 } 2818 2819 /* create our matrix */ 2820 ierr = MatCreate(comm,m,m,M+extra_rows,N+extra_rows,&A);CHKERRQ(ierr); 2821 ierr = MatSetType(A,type);CHKERRQ(ierr) 2822 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2823 2824 /* Why doesn't this called using ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); */ 2825 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2826 2827 if (!rank) { 2828 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2829 /* read in my part of the matrix numerical values */ 2830 nz = procsnz[0]; 2831 vals = buf; 2832 mycols = ibuf; 2833 if (size == 1) nz -= extra_rows; 2834 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2835 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2836 2837 /* insert into matrix */ 2838 jj = rstart*bs; 2839 for (i=0; i<m; i++) { 2840 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2841 mycols += locrowlens[i]; 2842 vals += locrowlens[i]; 2843 jj++; 2844 } 2845 /* read in other processors (except the last one) and ship out */ 2846 for (i=1; i<size-1; i++) { 2847 nz = procsnz[i]; 2848 vals = buf; 2849 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2850 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2851 } 2852 /* the last proc */ 2853 if (size != 1){ 2854 nz = procsnz[i] - extra_rows; 2855 vals = buf; 2856 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2857 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2858 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2859 } 2860 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2861 } else { 2862 /* receive numeric values */ 2863 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2864 2865 /* receive message of values*/ 2866 vals = buf; 2867 mycols = ibuf; 2868 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2869 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2870 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2871 2872 /* insert into matrix */ 2873 jj = rstart*bs; 2874 for (i=0; i<m; i++) { 2875 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2876 mycols += locrowlens[i]; 2877 vals += locrowlens[i]; 2878 jj++; 2879 } 2880 } 2881 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2882 ierr = PetscFree(buf);CHKERRQ(ierr); 2883 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2884 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2885 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2886 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2887 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2888 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2889 2890 *newmat = A; 2891 PetscFunctionReturn(0); 2892 } 2893 2894 #undef __FUNCT__ 2895 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2896 /*@ 2897 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2898 2899 Input Parameters: 2900 . mat - the matrix 2901 . fact - factor 2902 2903 Collective on Mat 2904 2905 Level: advanced 2906 2907 Notes: 2908 This can also be set by the command line option: -mat_use_hash_table fact 2909 2910 .keywords: matrix, hashtable, factor, HT 2911 2912 .seealso: MatSetOption() 2913 @*/ 2914 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2915 { 2916 PetscErrorCode ierr,(*f)(Mat,PetscReal); 2917 2918 PetscFunctionBegin; 2919 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 2920 if (f) { 2921 ierr = (*f)(mat,fact);CHKERRQ(ierr); 2922 } 2923 PetscFunctionReturn(0); 2924 } 2925 2926 EXTERN_C_BEGIN 2927 #undef __FUNCT__ 2928 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 2929 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 2930 { 2931 Mat_MPIBAIJ *baij; 2932 2933 PetscFunctionBegin; 2934 baij = (Mat_MPIBAIJ*)mat->data; 2935 baij->ht_fact = fact; 2936 PetscFunctionReturn(0); 2937 } 2938 EXTERN_C_END 2939 2940 #undef __FUNCT__ 2941 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2942 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 2943 { 2944 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2945 PetscFunctionBegin; 2946 *Ad = a->A; 2947 *Ao = a->B; 2948 *colmap = a->garray; 2949 PetscFunctionReturn(0); 2950 } 2951