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