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 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2004 } else { 2005 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2006 } 2007 PetscFunctionReturn(0); 2008 } 2009 2010 #undef __FUNCT__ 2011 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2012 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2013 { 2014 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2015 PetscErrorCode ierr; 2016 2017 PetscFunctionBegin; 2018 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2019 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2020 PetscFunctionReturn(0); 2021 } 2022 2023 #undef __FUNCT__ 2024 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2025 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2026 { 2027 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2028 PetscErrorCode ierr; 2029 2030 PetscFunctionBegin; 2031 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2032 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2033 PetscFunctionReturn(0); 2034 } 2035 2036 #undef __FUNCT__ 2037 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2038 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2039 { 2040 PetscErrorCode ierr; 2041 IS iscol_local; 2042 PetscInt csize; 2043 2044 PetscFunctionBegin; 2045 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2046 if (call == MAT_REUSE_MATRIX) { 2047 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2048 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2049 } else { 2050 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2051 } 2052 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2053 if (call == MAT_INITIAL_MATRIX) { 2054 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2055 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2056 } 2057 PetscFunctionReturn(0); 2058 } 2059 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2060 #undef __FUNCT__ 2061 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2062 /* 2063 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2064 in local and then by concatenating the local matrices the end result. 2065 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2066 */ 2067 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2068 { 2069 PetscErrorCode ierr; 2070 PetscMPIInt rank,size; 2071 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2072 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2073 Mat M,Mreuse; 2074 MatScalar *vwork,*aa; 2075 MPI_Comm comm; 2076 IS isrow_new, iscol_new; 2077 PetscBool idflag,allrows, allcols; 2078 Mat_SeqBAIJ *aij; 2079 2080 PetscFunctionBegin; 2081 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2082 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2083 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2084 /* The compression and expansion should be avoided. Doesn't point 2085 out errors, might change the indices, hence buggey */ 2086 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2087 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2088 2089 /* Check for special case: each processor gets entire matrix columns */ 2090 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2091 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2092 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2093 else allcols = PETSC_FALSE; 2094 2095 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2096 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2097 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2098 else allrows = PETSC_FALSE; 2099 2100 if (call == MAT_REUSE_MATRIX) { 2101 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2102 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2103 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2104 } else { 2105 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2106 } 2107 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2108 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2109 /* 2110 m - number of local rows 2111 n - number of columns (same on all processors) 2112 rstart - first row in new global matrix generated 2113 */ 2114 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2115 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2116 m = m/bs; 2117 n = n/bs; 2118 2119 if (call == MAT_INITIAL_MATRIX) { 2120 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2121 ii = aij->i; 2122 jj = aij->j; 2123 2124 /* 2125 Determine the number of non-zeros in the diagonal and off-diagonal 2126 portions of the matrix in order to do correct preallocation 2127 */ 2128 2129 /* first get start and end of "diagonal" columns */ 2130 if (csize == PETSC_DECIDE) { 2131 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2132 if (mglobal == n*bs) { /* square matrix */ 2133 nlocal = m; 2134 } else { 2135 nlocal = n/size + ((n % size) > rank); 2136 } 2137 } else { 2138 nlocal = csize/bs; 2139 } 2140 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2141 rstart = rend - nlocal; 2142 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); 2143 2144 /* next, compute all the lengths */ 2145 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2146 for (i=0; i<m; i++) { 2147 jend = ii[i+1] - ii[i]; 2148 olen = 0; 2149 dlen = 0; 2150 for (j=0; j<jend; j++) { 2151 if (*jj < rstart || *jj >= rend) olen++; 2152 else dlen++; 2153 jj++; 2154 } 2155 olens[i] = olen; 2156 dlens[i] = dlen; 2157 } 2158 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2159 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2160 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2161 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2162 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2163 } else { 2164 PetscInt ml,nl; 2165 2166 M = *newmat; 2167 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2168 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2169 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2170 /* 2171 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2172 rather than the slower MatSetValues(). 2173 */ 2174 M->was_assembled = PETSC_TRUE; 2175 M->assembled = PETSC_FALSE; 2176 } 2177 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2178 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2179 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2180 ii = aij->i; 2181 jj = aij->j; 2182 aa = aij->a; 2183 for (i=0; i<m; i++) { 2184 row = rstart/bs + i; 2185 nz = ii[i+1] - ii[i]; 2186 cwork = jj; jj += nz; 2187 vwork = aa; aa += nz*bs*bs; 2188 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2189 } 2190 2191 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2192 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2193 *newmat = M; 2194 2195 /* save submatrix used in processor for next request */ 2196 if (call == MAT_INITIAL_MATRIX) { 2197 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2198 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2199 } 2200 PetscFunctionReturn(0); 2201 } 2202 2203 #undef __FUNCT__ 2204 #define __FUNCT__ "MatPermute_MPIBAIJ" 2205 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2206 { 2207 MPI_Comm comm,pcomm; 2208 PetscInt clocal_size,nrows; 2209 const PetscInt *rows; 2210 PetscMPIInt size; 2211 IS crowp,lcolp; 2212 PetscErrorCode ierr; 2213 2214 PetscFunctionBegin; 2215 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2216 /* make a collective version of 'rowp' */ 2217 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2218 if (pcomm==comm) { 2219 crowp = rowp; 2220 } else { 2221 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2222 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2223 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2224 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2225 } 2226 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2227 /* make a local version of 'colp' */ 2228 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2229 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2230 if (size==1) { 2231 lcolp = colp; 2232 } else { 2233 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2234 } 2235 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2236 /* now we just get the submatrix */ 2237 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2238 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2239 /* clean up */ 2240 if (pcomm!=comm) { 2241 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2242 } 2243 if (size>1) { 2244 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2245 } 2246 PetscFunctionReturn(0); 2247 } 2248 2249 #undef __FUNCT__ 2250 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2251 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2252 { 2253 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2254 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2255 2256 PetscFunctionBegin; 2257 if (nghosts) *nghosts = B->nbs; 2258 if (ghosts) *ghosts = baij->garray; 2259 PetscFunctionReturn(0); 2260 } 2261 2262 #undef __FUNCT__ 2263 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2264 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2265 { 2266 Mat B; 2267 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2268 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2269 Mat_SeqAIJ *b; 2270 PetscErrorCode ierr; 2271 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2272 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2273 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2274 2275 PetscFunctionBegin; 2276 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2277 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2278 2279 /* ---------------------------------------------------------------- 2280 Tell every processor the number of nonzeros per row 2281 */ 2282 ierr = PetscMalloc1((A->rmap->N/bs),&lens);CHKERRQ(ierr); 2283 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2284 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]; 2285 } 2286 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2287 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2288 displs = recvcounts + size; 2289 for (i=0; i<size; i++) { 2290 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2291 displs[i] = A->rmap->range[i]/bs; 2292 } 2293 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2294 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2295 #else 2296 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2297 #endif 2298 /* --------------------------------------------------------------- 2299 Create the sequential matrix of the same type as the local block diagonal 2300 */ 2301 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2302 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2303 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2304 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2305 b = (Mat_SeqAIJ*)B->data; 2306 2307 /*-------------------------------------------------------------------- 2308 Copy my part of matrix column indices over 2309 */ 2310 sendcount = ad->nz + bd->nz; 2311 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2312 a_jsendbuf = ad->j; 2313 b_jsendbuf = bd->j; 2314 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2315 cnt = 0; 2316 for (i=0; i<n; i++) { 2317 2318 /* put in lower diagonal portion */ 2319 m = bd->i[i+1] - bd->i[i]; 2320 while (m > 0) { 2321 /* is it above diagonal (in bd (compressed) numbering) */ 2322 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2323 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2324 m--; 2325 } 2326 2327 /* put in diagonal portion */ 2328 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2329 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2330 } 2331 2332 /* put in upper diagonal portion */ 2333 while (m-- > 0) { 2334 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2335 } 2336 } 2337 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2338 2339 /*-------------------------------------------------------------------- 2340 Gather all column indices to all processors 2341 */ 2342 for (i=0; i<size; i++) { 2343 recvcounts[i] = 0; 2344 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2345 recvcounts[i] += lens[j]; 2346 } 2347 } 2348 displs[0] = 0; 2349 for (i=1; i<size; i++) { 2350 displs[i] = displs[i-1] + recvcounts[i-1]; 2351 } 2352 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2353 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2354 #else 2355 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2356 #endif 2357 /*-------------------------------------------------------------------- 2358 Assemble the matrix into useable form (note numerical values not yet set) 2359 */ 2360 /* set the b->ilen (length of each row) values */ 2361 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2362 /* set the b->i indices */ 2363 b->i[0] = 0; 2364 for (i=1; i<=A->rmap->N/bs; i++) { 2365 b->i[i] = b->i[i-1] + lens[i-1]; 2366 } 2367 ierr = PetscFree(lens);CHKERRQ(ierr); 2368 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2369 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2370 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2371 2372 if (A->symmetric) { 2373 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2374 } else if (A->hermitian) { 2375 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2376 } else if (A->structurally_symmetric) { 2377 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2378 } 2379 *newmat = B; 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatSOR_MPIBAIJ" 2385 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2386 { 2387 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2388 PetscErrorCode ierr; 2389 Vec bb1 = 0; 2390 2391 PetscFunctionBegin; 2392 if (flag == SOR_APPLY_UPPER) { 2393 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2394 PetscFunctionReturn(0); 2395 } 2396 2397 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2398 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2399 } 2400 2401 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2402 if (flag & SOR_ZERO_INITIAL_GUESS) { 2403 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2404 its--; 2405 } 2406 2407 while (its--) { 2408 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2409 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2410 2411 /* update rhs: bb1 = bb - B*x */ 2412 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2413 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2414 2415 /* local sweep */ 2416 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2417 } 2418 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2419 if (flag & SOR_ZERO_INITIAL_GUESS) { 2420 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2421 its--; 2422 } 2423 while (its--) { 2424 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2425 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2426 2427 /* update rhs: bb1 = bb - B*x */ 2428 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2429 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2430 2431 /* local sweep */ 2432 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2433 } 2434 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2435 if (flag & SOR_ZERO_INITIAL_GUESS) { 2436 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2437 its--; 2438 } 2439 while (its--) { 2440 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2441 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2442 2443 /* update rhs: bb1 = bb - B*x */ 2444 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2445 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2446 2447 /* local sweep */ 2448 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2449 } 2450 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2451 2452 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2458 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2459 { 2460 PetscErrorCode ierr; 2461 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2462 PetscInt N,i,*garray = aij->garray; 2463 PetscInt ib,jb,bs = A->rmap->bs; 2464 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2465 MatScalar *a_val = a_aij->a; 2466 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2467 MatScalar *b_val = b_aij->a; 2468 PetscReal *work; 2469 2470 PetscFunctionBegin; 2471 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2472 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2473 if (type == NORM_2) { 2474 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2475 for (jb=0; jb<bs; jb++) { 2476 for (ib=0; ib<bs; ib++) { 2477 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2478 a_val++; 2479 } 2480 } 2481 } 2482 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2483 for (jb=0; jb<bs; jb++) { 2484 for (ib=0; ib<bs; ib++) { 2485 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2486 b_val++; 2487 } 2488 } 2489 } 2490 } else if (type == NORM_1) { 2491 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2492 for (jb=0; jb<bs; jb++) { 2493 for (ib=0; ib<bs; ib++) { 2494 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2495 a_val++; 2496 } 2497 } 2498 } 2499 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2500 for (jb=0; jb<bs; jb++) { 2501 for (ib=0; ib<bs; ib++) { 2502 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2503 b_val++; 2504 } 2505 } 2506 } 2507 } else if (type == NORM_INFINITY) { 2508 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2509 for (jb=0; jb<bs; jb++) { 2510 for (ib=0; ib<bs; ib++) { 2511 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2512 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2513 a_val++; 2514 } 2515 } 2516 } 2517 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2518 for (jb=0; jb<bs; jb++) { 2519 for (ib=0; ib<bs; ib++) { 2520 int col = garray[b_aij->j[i]] * bs + jb; 2521 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2522 b_val++; 2523 } 2524 } 2525 } 2526 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2527 if (type == NORM_INFINITY) { 2528 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2529 } else { 2530 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2531 } 2532 ierr = PetscFree(work);CHKERRQ(ierr); 2533 if (type == NORM_2) { 2534 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2535 } 2536 PetscFunctionReturn(0); 2537 } 2538 2539 #undef __FUNCT__ 2540 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2541 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2542 { 2543 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2544 PetscErrorCode ierr; 2545 2546 PetscFunctionBegin; 2547 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2548 PetscFunctionReturn(0); 2549 } 2550 2551 2552 /* -------------------------------------------------------------------*/ 2553 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2554 MatGetRow_MPIBAIJ, 2555 MatRestoreRow_MPIBAIJ, 2556 MatMult_MPIBAIJ, 2557 /* 4*/ MatMultAdd_MPIBAIJ, 2558 MatMultTranspose_MPIBAIJ, 2559 MatMultTransposeAdd_MPIBAIJ, 2560 0, 2561 0, 2562 0, 2563 /*10*/ 0, 2564 0, 2565 0, 2566 MatSOR_MPIBAIJ, 2567 MatTranspose_MPIBAIJ, 2568 /*15*/ MatGetInfo_MPIBAIJ, 2569 MatEqual_MPIBAIJ, 2570 MatGetDiagonal_MPIBAIJ, 2571 MatDiagonalScale_MPIBAIJ, 2572 MatNorm_MPIBAIJ, 2573 /*20*/ MatAssemblyBegin_MPIBAIJ, 2574 MatAssemblyEnd_MPIBAIJ, 2575 MatSetOption_MPIBAIJ, 2576 MatZeroEntries_MPIBAIJ, 2577 /*24*/ MatZeroRows_MPIBAIJ, 2578 0, 2579 0, 2580 0, 2581 0, 2582 /*29*/ MatSetUp_MPIBAIJ, 2583 0, 2584 0, 2585 0, 2586 0, 2587 /*34*/ MatDuplicate_MPIBAIJ, 2588 0, 2589 0, 2590 0, 2591 0, 2592 /*39*/ MatAXPY_MPIBAIJ, 2593 MatGetSubMatrices_MPIBAIJ, 2594 MatIncreaseOverlap_MPIBAIJ, 2595 MatGetValues_MPIBAIJ, 2596 MatCopy_MPIBAIJ, 2597 /*44*/ 0, 2598 MatScale_MPIBAIJ, 2599 0, 2600 0, 2601 MatZeroRowsColumns_MPIBAIJ, 2602 /*49*/ 0, 2603 0, 2604 0, 2605 0, 2606 0, 2607 /*54*/ MatFDColoringCreate_MPIXAIJ, 2608 0, 2609 MatSetUnfactored_MPIBAIJ, 2610 MatPermute_MPIBAIJ, 2611 MatSetValuesBlocked_MPIBAIJ, 2612 /*59*/ MatGetSubMatrix_MPIBAIJ, 2613 MatDestroy_MPIBAIJ, 2614 MatView_MPIBAIJ, 2615 0, 2616 0, 2617 /*64*/ 0, 2618 0, 2619 0, 2620 0, 2621 0, 2622 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2623 0, 2624 0, 2625 0, 2626 0, 2627 /*74*/ 0, 2628 MatFDColoringApply_BAIJ, 2629 0, 2630 0, 2631 0, 2632 /*79*/ 0, 2633 0, 2634 0, 2635 0, 2636 MatLoad_MPIBAIJ, 2637 /*84*/ 0, 2638 0, 2639 0, 2640 0, 2641 0, 2642 /*89*/ 0, 2643 0, 2644 0, 2645 0, 2646 0, 2647 /*94*/ 0, 2648 0, 2649 0, 2650 0, 2651 0, 2652 /*99*/ 0, 2653 0, 2654 0, 2655 0, 2656 0, 2657 /*104*/0, 2658 MatRealPart_MPIBAIJ, 2659 MatImaginaryPart_MPIBAIJ, 2660 0, 2661 0, 2662 /*109*/0, 2663 0, 2664 0, 2665 0, 2666 0, 2667 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2668 0, 2669 MatGetGhosts_MPIBAIJ, 2670 0, 2671 0, 2672 /*119*/0, 2673 0, 2674 0, 2675 0, 2676 MatGetMultiProcBlock_MPIBAIJ, 2677 /*124*/0, 2678 MatGetColumnNorms_MPIBAIJ, 2679 MatInvertBlockDiagonal_MPIBAIJ, 2680 0, 2681 0, 2682 /*129*/ 0, 2683 0, 2684 0, 2685 0, 2686 0, 2687 /*134*/ 0, 2688 0, 2689 0, 2690 0, 2691 0, 2692 /*139*/ 0, 2693 0, 2694 0, 2695 MatFDColoringSetUp_MPIXAIJ 2696 }; 2697 2698 #undef __FUNCT__ 2699 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2700 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2701 { 2702 PetscFunctionBegin; 2703 *a = ((Mat_MPIBAIJ*)A->data)->A; 2704 PetscFunctionReturn(0); 2705 } 2706 2707 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2708 2709 #undef __FUNCT__ 2710 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2711 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2712 { 2713 PetscInt m,rstart,cstart,cend; 2714 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2715 const PetscInt *JJ =0; 2716 PetscScalar *values=0; 2717 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2718 PetscErrorCode ierr; 2719 2720 PetscFunctionBegin; 2721 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2722 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2723 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2724 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2725 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2726 m = B->rmap->n/bs; 2727 rstart = B->rmap->rstart/bs; 2728 cstart = B->cmap->rstart/bs; 2729 cend = B->cmap->rend/bs; 2730 2731 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2732 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2733 for (i=0; i<m; i++) { 2734 nz = ii[i+1] - ii[i]; 2735 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2736 nz_max = PetscMax(nz_max,nz); 2737 JJ = jj + ii[i]; 2738 for (j=0; j<nz; j++) { 2739 if (*JJ >= cstart) break; 2740 JJ++; 2741 } 2742 d = 0; 2743 for (; j<nz; j++) { 2744 if (*JJ++ >= cend) break; 2745 d++; 2746 } 2747 d_nnz[i] = d; 2748 o_nnz[i] = nz - d; 2749 } 2750 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2751 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2752 2753 values = (PetscScalar*)V; 2754 if (!values) { 2755 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2756 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2757 } 2758 for (i=0; i<m; i++) { 2759 PetscInt row = i + rstart; 2760 PetscInt ncols = ii[i+1] - ii[i]; 2761 const PetscInt *icols = jj + ii[i]; 2762 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2763 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2764 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2765 } else { /* block ordering does not match so we can only insert one block at a time. */ 2766 PetscInt j; 2767 for (j=0; j<ncols; j++) { 2768 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2769 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2770 } 2771 } 2772 } 2773 2774 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2775 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2776 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2777 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2778 PetscFunctionReturn(0); 2779 } 2780 2781 #undef __FUNCT__ 2782 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2783 /*@C 2784 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2785 (the default parallel PETSc format). 2786 2787 Collective on MPI_Comm 2788 2789 Input Parameters: 2790 + A - the matrix 2791 . bs - the block size 2792 . i - the indices into j for the start of each local row (starts with zero) 2793 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2794 - v - optional values in the matrix 2795 2796 Level: developer 2797 2798 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2799 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2800 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2801 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2802 block column and the second index is over columns within a block. 2803 2804 .keywords: matrix, aij, compressed row, sparse, parallel 2805 2806 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2807 @*/ 2808 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2809 { 2810 PetscErrorCode ierr; 2811 2812 PetscFunctionBegin; 2813 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2814 PetscValidType(B,1); 2815 PetscValidLogicalCollectiveInt(B,bs,2); 2816 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2817 PetscFunctionReturn(0); 2818 } 2819 2820 #undef __FUNCT__ 2821 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2822 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2823 { 2824 Mat_MPIBAIJ *b; 2825 PetscErrorCode ierr; 2826 PetscInt i; 2827 2828 PetscFunctionBegin; 2829 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2830 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2831 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2832 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2833 2834 if (d_nnz) { 2835 for (i=0; i<B->rmap->n/bs; i++) { 2836 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]); 2837 } 2838 } 2839 if (o_nnz) { 2840 for (i=0; i<B->rmap->n/bs; i++) { 2841 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]); 2842 } 2843 } 2844 2845 b = (Mat_MPIBAIJ*)B->data; 2846 b->bs2 = bs*bs; 2847 b->mbs = B->rmap->n/bs; 2848 b->nbs = B->cmap->n/bs; 2849 b->Mbs = B->rmap->N/bs; 2850 b->Nbs = B->cmap->N/bs; 2851 2852 for (i=0; i<=b->size; i++) { 2853 b->rangebs[i] = B->rmap->range[i]/bs; 2854 } 2855 b->rstartbs = B->rmap->rstart/bs; 2856 b->rendbs = B->rmap->rend/bs; 2857 b->cstartbs = B->cmap->rstart/bs; 2858 b->cendbs = B->cmap->rend/bs; 2859 2860 if (!B->preallocated) { 2861 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2862 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2863 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2864 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2865 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2866 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2867 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2868 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2869 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2870 } 2871 2872 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2873 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2874 B->preallocated = PETSC_TRUE; 2875 PetscFunctionReturn(0); 2876 } 2877 2878 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2879 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2880 2881 #undef __FUNCT__ 2882 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2883 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2884 { 2885 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2886 PetscErrorCode ierr; 2887 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2888 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2889 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2890 2891 PetscFunctionBegin; 2892 ierr = PetscMalloc1((M+1),&ii);CHKERRQ(ierr); 2893 ii[0] = 0; 2894 for (i=0; i<M; i++) { 2895 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]); 2896 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]); 2897 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2898 /* remove one from count of matrix has diagonal */ 2899 for (j=id[i]; j<id[i+1]; j++) { 2900 if (jd[j] == i) {ii[i+1]--;break;} 2901 } 2902 } 2903 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2904 cnt = 0; 2905 for (i=0; i<M; i++) { 2906 for (j=io[i]; j<io[i+1]; j++) { 2907 if (garray[jo[j]] > rstart) break; 2908 jj[cnt++] = garray[jo[j]]; 2909 } 2910 for (k=id[i]; k<id[i+1]; k++) { 2911 if (jd[k] != i) { 2912 jj[cnt++] = rstart + jd[k]; 2913 } 2914 } 2915 for (; j<io[i+1]; j++) { 2916 jj[cnt++] = garray[jo[j]]; 2917 } 2918 } 2919 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2920 PetscFunctionReturn(0); 2921 } 2922 2923 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2924 2925 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2926 2927 #undef __FUNCT__ 2928 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2929 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2930 { 2931 PetscErrorCode ierr; 2932 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2933 Mat B; 2934 Mat_MPIAIJ *b; 2935 2936 PetscFunctionBegin; 2937 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2938 2939 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2940 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2941 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2942 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2943 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2944 b = (Mat_MPIAIJ*) B->data; 2945 2946 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2947 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2948 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2949 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2950 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2951 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2952 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2953 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2954 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2955 if (reuse == MAT_REUSE_MATRIX) { 2956 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2957 } else { 2958 *newmat = B; 2959 } 2960 PetscFunctionReturn(0); 2961 } 2962 2963 #if defined(PETSC_HAVE_MUMPS) 2964 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2965 #endif 2966 2967 /*MC 2968 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2969 2970 Options Database Keys: 2971 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2972 . -mat_block_size <bs> - set the blocksize used to store the matrix 2973 - -mat_use_hash_table <fact> 2974 2975 Level: beginner 2976 2977 .seealso: MatCreateMPIBAIJ 2978 M*/ 2979 2980 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 2981 2982 #undef __FUNCT__ 2983 #define __FUNCT__ "MatCreate_MPIBAIJ" 2984 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 2985 { 2986 Mat_MPIBAIJ *b; 2987 PetscErrorCode ierr; 2988 PetscBool flg; 2989 2990 PetscFunctionBegin; 2991 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2992 B->data = (void*)b; 2993 2994 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2995 B->assembled = PETSC_FALSE; 2996 2997 B->insertmode = NOT_SET_VALUES; 2998 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 2999 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3000 3001 /* build local table of row and column ownerships */ 3002 ierr = PetscMalloc1((b->size+1),&b->rangebs);CHKERRQ(ierr); 3003 3004 /* build cache for off array entries formed */ 3005 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3006 3007 b->donotstash = PETSC_FALSE; 3008 b->colmap = NULL; 3009 b->garray = NULL; 3010 b->roworiented = PETSC_TRUE; 3011 3012 /* stuff used in block assembly */ 3013 b->barray = 0; 3014 3015 /* stuff used for matrix vector multiply */ 3016 b->lvec = 0; 3017 b->Mvctx = 0; 3018 3019 /* stuff for MatGetRow() */ 3020 b->rowindices = 0; 3021 b->rowvalues = 0; 3022 b->getrowactive = PETSC_FALSE; 3023 3024 /* hash table stuff */ 3025 b->ht = 0; 3026 b->hd = 0; 3027 b->ht_size = 0; 3028 b->ht_flag = PETSC_FALSE; 3029 b->ht_fact = 0; 3030 b->ht_total_ct = 0; 3031 b->ht_insert_ct = 0; 3032 3033 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3034 b->ijonly = PETSC_FALSE; 3035 3036 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3037 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3038 if (flg) { 3039 PetscReal fact = 1.39; 3040 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3041 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3042 if (fact <= 1.0) fact = 1.39; 3043 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3044 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3045 } 3046 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3047 3048 #if defined(PETSC_HAVE_MUMPS) 3049 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3050 #endif 3051 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3052 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3053 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3054 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3055 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3056 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3057 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3058 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3059 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3060 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3061 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3062 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3063 PetscFunctionReturn(0); 3064 } 3065 3066 /*MC 3067 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3068 3069 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3070 and MATMPIBAIJ otherwise. 3071 3072 Options Database Keys: 3073 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3074 3075 Level: beginner 3076 3077 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3078 M*/ 3079 3080 #undef __FUNCT__ 3081 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3082 /*@C 3083 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3084 (block compressed row). For good matrix assembly performance 3085 the user should preallocate the matrix storage by setting the parameters 3086 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3087 performance can be increased by more than a factor of 50. 3088 3089 Collective on Mat 3090 3091 Input Parameters: 3092 + A - the matrix 3093 . bs - size of block 3094 . d_nz - number of block nonzeros per block row in diagonal portion of local 3095 submatrix (same for all local rows) 3096 . d_nnz - array containing the number of block nonzeros in the various block rows 3097 of the in diagonal portion of the local (possibly different for each block 3098 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3099 set it even if it is zero. 3100 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3101 submatrix (same for all local rows). 3102 - o_nnz - array containing the number of nonzeros in the various block rows of the 3103 off-diagonal portion of the local submatrix (possibly different for 3104 each block row) or NULL. 3105 3106 If the *_nnz parameter is given then the *_nz parameter is ignored 3107 3108 Options Database Keys: 3109 + -mat_block_size - size of the blocks to use 3110 - -mat_use_hash_table <fact> 3111 3112 Notes: 3113 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3114 than it must be used on all processors that share the object for that argument. 3115 3116 Storage Information: 3117 For a square global matrix we define each processor's diagonal portion 3118 to be its local rows and the corresponding columns (a square submatrix); 3119 each processor's off-diagonal portion encompasses the remainder of the 3120 local matrix (a rectangular submatrix). 3121 3122 The user can specify preallocated storage for the diagonal part of 3123 the local submatrix with either d_nz or d_nnz (not both). Set 3124 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3125 memory allocation. Likewise, specify preallocated storage for the 3126 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3127 3128 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3129 the figure below we depict these three local rows and all columns (0-11). 3130 3131 .vb 3132 0 1 2 3 4 5 6 7 8 9 10 11 3133 -------------------------- 3134 row 3 |o o o d d d o o o o o o 3135 row 4 |o o o d d d o o o o o o 3136 row 5 |o o o d d d o o o o o o 3137 -------------------------- 3138 .ve 3139 3140 Thus, any entries in the d locations are stored in the d (diagonal) 3141 submatrix, and any entries in the o locations are stored in the 3142 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3143 stored simply in the MATSEQBAIJ format for compressed row storage. 3144 3145 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3146 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3147 In general, for PDE problems in which most nonzeros are near the diagonal, 3148 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3149 or you will get TERRIBLE performance; see the users' manual chapter on 3150 matrices. 3151 3152 You can call MatGetInfo() to get information on how effective the preallocation was; 3153 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3154 You can also run with the option -info and look for messages with the string 3155 malloc in them to see if additional memory allocation was needed. 3156 3157 Level: intermediate 3158 3159 .keywords: matrix, block, aij, compressed row, sparse, parallel 3160 3161 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3162 @*/ 3163 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3164 { 3165 PetscErrorCode ierr; 3166 3167 PetscFunctionBegin; 3168 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3169 PetscValidType(B,1); 3170 PetscValidLogicalCollectiveInt(B,bs,2); 3171 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); 3172 PetscFunctionReturn(0); 3173 } 3174 3175 #undef __FUNCT__ 3176 #define __FUNCT__ "MatCreateBAIJ" 3177 /*@C 3178 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3179 (block compressed row). For good matrix assembly performance 3180 the user should preallocate the matrix storage by setting the parameters 3181 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3182 performance can be increased by more than a factor of 50. 3183 3184 Collective on MPI_Comm 3185 3186 Input Parameters: 3187 + comm - MPI communicator 3188 . bs - size of blockk 3189 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3190 This value should be the same as the local size used in creating the 3191 y vector for the matrix-vector product y = Ax. 3192 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3193 This value should be the same as the local size used in creating the 3194 x vector for the matrix-vector product y = Ax. 3195 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3196 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3197 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3198 submatrix (same for all local rows) 3199 . d_nnz - array containing the number of nonzero blocks in the various block rows 3200 of the in diagonal portion of the local (possibly different for each block 3201 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3202 and set it even if it is zero. 3203 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3204 submatrix (same for all local rows). 3205 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3206 off-diagonal portion of the local submatrix (possibly different for 3207 each block row) or NULL. 3208 3209 Output Parameter: 3210 . A - the matrix 3211 3212 Options Database Keys: 3213 + -mat_block_size - size of the blocks to use 3214 - -mat_use_hash_table <fact> 3215 3216 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3217 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3218 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3219 3220 Notes: 3221 If the *_nnz parameter is given then the *_nz parameter is ignored 3222 3223 A nonzero block is any block that as 1 or more nonzeros in it 3224 3225 The user MUST specify either the local or global matrix dimensions 3226 (possibly both). 3227 3228 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3229 than it must be used on all processors that share the object for that argument. 3230 3231 Storage Information: 3232 For a square global matrix we define each processor's diagonal portion 3233 to be its local rows and the corresponding columns (a square submatrix); 3234 each processor's off-diagonal portion encompasses the remainder of the 3235 local matrix (a rectangular submatrix). 3236 3237 The user can specify preallocated storage for the diagonal part of 3238 the local submatrix with either d_nz or d_nnz (not both). Set 3239 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3240 memory allocation. Likewise, specify preallocated storage for the 3241 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3242 3243 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3244 the figure below we depict these three local rows and all columns (0-11). 3245 3246 .vb 3247 0 1 2 3 4 5 6 7 8 9 10 11 3248 -------------------------- 3249 row 3 |o o o d d d o o o o o o 3250 row 4 |o o o d d d o o o o o o 3251 row 5 |o o o d d d o o o o o o 3252 -------------------------- 3253 .ve 3254 3255 Thus, any entries in the d locations are stored in the d (diagonal) 3256 submatrix, and any entries in the o locations are stored in the 3257 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3258 stored simply in the MATSEQBAIJ format for compressed row storage. 3259 3260 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3261 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3262 In general, for PDE problems in which most nonzeros are near the diagonal, 3263 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3264 or you will get TERRIBLE performance; see the users' manual chapter on 3265 matrices. 3266 3267 Level: intermediate 3268 3269 .keywords: matrix, block, aij, compressed row, sparse, parallel 3270 3271 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3272 @*/ 3273 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) 3274 { 3275 PetscErrorCode ierr; 3276 PetscMPIInt size; 3277 3278 PetscFunctionBegin; 3279 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3280 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3281 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3282 if (size > 1) { 3283 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3284 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3285 } else { 3286 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3287 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3288 } 3289 PetscFunctionReturn(0); 3290 } 3291 3292 #undef __FUNCT__ 3293 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3294 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3295 { 3296 Mat mat; 3297 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3298 PetscErrorCode ierr; 3299 PetscInt len=0; 3300 3301 PetscFunctionBegin; 3302 *newmat = 0; 3303 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3304 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3305 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3306 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3307 3308 mat->factortype = matin->factortype; 3309 mat->preallocated = PETSC_TRUE; 3310 mat->assembled = PETSC_TRUE; 3311 mat->insertmode = NOT_SET_VALUES; 3312 3313 a = (Mat_MPIBAIJ*)mat->data; 3314 mat->rmap->bs = matin->rmap->bs; 3315 a->bs2 = oldmat->bs2; 3316 a->mbs = oldmat->mbs; 3317 a->nbs = oldmat->nbs; 3318 a->Mbs = oldmat->Mbs; 3319 a->Nbs = oldmat->Nbs; 3320 3321 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3322 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3323 3324 a->size = oldmat->size; 3325 a->rank = oldmat->rank; 3326 a->donotstash = oldmat->donotstash; 3327 a->roworiented = oldmat->roworiented; 3328 a->rowindices = 0; 3329 a->rowvalues = 0; 3330 a->getrowactive = PETSC_FALSE; 3331 a->barray = 0; 3332 a->rstartbs = oldmat->rstartbs; 3333 a->rendbs = oldmat->rendbs; 3334 a->cstartbs = oldmat->cstartbs; 3335 a->cendbs = oldmat->cendbs; 3336 3337 /* hash table stuff */ 3338 a->ht = 0; 3339 a->hd = 0; 3340 a->ht_size = 0; 3341 a->ht_flag = oldmat->ht_flag; 3342 a->ht_fact = oldmat->ht_fact; 3343 a->ht_total_ct = 0; 3344 a->ht_insert_ct = 0; 3345 3346 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3347 if (oldmat->colmap) { 3348 #if defined(PETSC_USE_CTABLE) 3349 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3350 #else 3351 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 3352 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3353 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3354 #endif 3355 } else a->colmap = 0; 3356 3357 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3358 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3359 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3360 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3361 } else a->garray = 0; 3362 3363 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3364 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3365 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3366 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3367 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3368 3369 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3370 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3371 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3372 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3373 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3374 *newmat = mat; 3375 PetscFunctionReturn(0); 3376 } 3377 3378 #undef __FUNCT__ 3379 #define __FUNCT__ "MatLoad_MPIBAIJ" 3380 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3381 { 3382 PetscErrorCode ierr; 3383 int fd; 3384 PetscInt i,nz,j,rstart,rend; 3385 PetscScalar *vals,*buf; 3386 MPI_Comm comm; 3387 MPI_Status status; 3388 PetscMPIInt rank,size,maxnz; 3389 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3390 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3391 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3392 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3393 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3394 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3395 3396 PetscFunctionBegin; 3397 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3398 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3399 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3400 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3401 3402 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3403 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3404 if (!rank) { 3405 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3406 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3407 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3408 } 3409 3410 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3411 3412 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3413 M = header[1]; N = header[2]; 3414 3415 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3416 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3417 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3418 3419 /* If global sizes are set, check if they are consistent with that given in the file */ 3420 if (sizesset) { 3421 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3422 } 3423 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); 3424 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); 3425 3426 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3427 3428 /* 3429 This code adds extra rows to make sure the number of rows is 3430 divisible by the blocksize 3431 */ 3432 Mbs = M/bs; 3433 extra_rows = bs - M + bs*Mbs; 3434 if (extra_rows == bs) extra_rows = 0; 3435 else Mbs++; 3436 if (extra_rows && !rank) { 3437 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3438 } 3439 3440 /* determine ownership of all rows */ 3441 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3442 mbs = Mbs/size + ((Mbs % size) > rank); 3443 m = mbs*bs; 3444 } else { /* User set */ 3445 m = newmat->rmap->n; 3446 mbs = m/bs; 3447 } 3448 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3449 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3450 3451 /* process 0 needs enough room for process with most rows */ 3452 if (!rank) { 3453 mmax = rowners[1]; 3454 for (i=2; i<=size; i++) { 3455 mmax = PetscMax(mmax,rowners[i]); 3456 } 3457 mmax*=bs; 3458 } else mmax = -1; /* unused, but compiler warns anyway */ 3459 3460 rowners[0] = 0; 3461 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3462 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3463 rstart = rowners[rank]; 3464 rend = rowners[rank+1]; 3465 3466 /* distribute row lengths to all processors */ 3467 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3468 if (!rank) { 3469 mend = m; 3470 if (size == 1) mend = mend - extra_rows; 3471 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3472 for (j=mend; j<m; j++) locrowlens[j] = 1; 3473 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3474 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3475 for (j=0; j<m; j++) { 3476 procsnz[0] += locrowlens[j]; 3477 } 3478 for (i=1; i<size; i++) { 3479 mend = browners[i+1] - browners[i]; 3480 if (i == size-1) mend = mend - extra_rows; 3481 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3482 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3483 /* calculate the number of nonzeros on each processor */ 3484 for (j=0; j<browners[i+1]-browners[i]; j++) { 3485 procsnz[i] += rowlengths[j]; 3486 } 3487 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3488 } 3489 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3490 } else { 3491 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3492 } 3493 3494 if (!rank) { 3495 /* determine max buffer needed and allocate it */ 3496 maxnz = procsnz[0]; 3497 for (i=1; i<size; i++) { 3498 maxnz = PetscMax(maxnz,procsnz[i]); 3499 } 3500 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3501 3502 /* read in my part of the matrix column indices */ 3503 nz = procsnz[0]; 3504 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3505 mycols = ibuf; 3506 if (size == 1) nz -= extra_rows; 3507 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3508 if (size == 1) { 3509 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3510 } 3511 3512 /* read in every ones (except the last) and ship off */ 3513 for (i=1; i<size-1; i++) { 3514 nz = procsnz[i]; 3515 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3516 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3517 } 3518 /* read in the stuff for the last proc */ 3519 if (size != 1) { 3520 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3521 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3522 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3523 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3524 } 3525 ierr = PetscFree(cols);CHKERRQ(ierr); 3526 } else { 3527 /* determine buffer space needed for message */ 3528 nz = 0; 3529 for (i=0; i<m; i++) { 3530 nz += locrowlens[i]; 3531 } 3532 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3533 mycols = ibuf; 3534 /* receive message of column indices*/ 3535 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3536 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3537 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3538 } 3539 3540 /* loop over local rows, determining number of off diagonal entries */ 3541 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3542 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3543 rowcount = 0; nzcount = 0; 3544 for (i=0; i<mbs; i++) { 3545 dcount = 0; 3546 odcount = 0; 3547 for (j=0; j<bs; j++) { 3548 kmax = locrowlens[rowcount]; 3549 for (k=0; k<kmax; k++) { 3550 tmp = mycols[nzcount++]/bs; 3551 if (!mask[tmp]) { 3552 mask[tmp] = 1; 3553 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3554 else masked1[dcount++] = tmp; 3555 } 3556 } 3557 rowcount++; 3558 } 3559 3560 dlens[i] = dcount; 3561 odlens[i] = odcount; 3562 3563 /* zero out the mask elements we set */ 3564 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3565 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3566 } 3567 3568 3569 if (!sizesset) { 3570 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3571 } 3572 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3573 3574 if (!rank) { 3575 ierr = PetscMalloc1((maxnz+1),&buf);CHKERRQ(ierr); 3576 /* read in my part of the matrix numerical values */ 3577 nz = procsnz[0]; 3578 vals = buf; 3579 mycols = ibuf; 3580 if (size == 1) nz -= extra_rows; 3581 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3582 if (size == 1) { 3583 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3584 } 3585 3586 /* insert into matrix */ 3587 jj = rstart*bs; 3588 for (i=0; i<m; i++) { 3589 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3590 mycols += locrowlens[i]; 3591 vals += locrowlens[i]; 3592 jj++; 3593 } 3594 /* read in other processors (except the last one) and ship out */ 3595 for (i=1; i<size-1; i++) { 3596 nz = procsnz[i]; 3597 vals = buf; 3598 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3599 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3600 } 3601 /* the last proc */ 3602 if (size != 1) { 3603 nz = procsnz[i] - extra_rows; 3604 vals = buf; 3605 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3606 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3607 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3608 } 3609 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3610 } else { 3611 /* receive numeric values */ 3612 ierr = PetscMalloc1((nz+1),&buf);CHKERRQ(ierr); 3613 3614 /* receive message of values*/ 3615 vals = buf; 3616 mycols = ibuf; 3617 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3618 3619 /* insert into matrix */ 3620 jj = rstart*bs; 3621 for (i=0; i<m; i++) { 3622 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3623 mycols += locrowlens[i]; 3624 vals += locrowlens[i]; 3625 jj++; 3626 } 3627 } 3628 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3629 ierr = PetscFree(buf);CHKERRQ(ierr); 3630 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3631 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3632 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3633 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3634 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3635 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3636 PetscFunctionReturn(0); 3637 } 3638 3639 #undef __FUNCT__ 3640 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3641 /*@ 3642 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3643 3644 Input Parameters: 3645 . mat - the matrix 3646 . fact - factor 3647 3648 Not Collective, each process can use a different factor 3649 3650 Level: advanced 3651 3652 Notes: 3653 This can also be set by the command line option: -mat_use_hash_table <fact> 3654 3655 .keywords: matrix, hashtable, factor, HT 3656 3657 .seealso: MatSetOption() 3658 @*/ 3659 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3660 { 3661 PetscErrorCode ierr; 3662 3663 PetscFunctionBegin; 3664 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3665 PetscFunctionReturn(0); 3666 } 3667 3668 #undef __FUNCT__ 3669 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3670 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3671 { 3672 Mat_MPIBAIJ *baij; 3673 3674 PetscFunctionBegin; 3675 baij = (Mat_MPIBAIJ*)mat->data; 3676 baij->ht_fact = fact; 3677 PetscFunctionReturn(0); 3678 } 3679 3680 #undef __FUNCT__ 3681 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3682 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3683 { 3684 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3685 3686 PetscFunctionBegin; 3687 *Ad = a->A; 3688 *Ao = a->B; 3689 *colmap = a->garray; 3690 PetscFunctionReturn(0); 3691 } 3692 3693 /* 3694 Special version for direct calls from Fortran (to eliminate two function call overheads 3695 */ 3696 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3697 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3698 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3699 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3700 #endif 3701 3702 #undef __FUNCT__ 3703 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3704 /*@C 3705 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3706 3707 Collective on Mat 3708 3709 Input Parameters: 3710 + mat - the matrix 3711 . min - number of input rows 3712 . im - input rows 3713 . nin - number of input columns 3714 . in - input columns 3715 . v - numerical values input 3716 - addvin - INSERT_VALUES or ADD_VALUES 3717 3718 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3719 3720 Level: advanced 3721 3722 .seealso: MatSetValuesBlocked() 3723 @*/ 3724 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3725 { 3726 /* convert input arguments to C version */ 3727 Mat mat = *matin; 3728 PetscInt m = *min, n = *nin; 3729 InsertMode addv = *addvin; 3730 3731 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3732 const MatScalar *value; 3733 MatScalar *barray = baij->barray; 3734 PetscBool roworiented = baij->roworiented; 3735 PetscErrorCode ierr; 3736 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3737 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3738 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3739 3740 PetscFunctionBegin; 3741 /* tasks normally handled by MatSetValuesBlocked() */ 3742 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3743 #if defined(PETSC_USE_DEBUG) 3744 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3745 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3746 #endif 3747 if (mat->assembled) { 3748 mat->was_assembled = PETSC_TRUE; 3749 mat->assembled = PETSC_FALSE; 3750 } 3751 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3752 3753 3754 if (!barray) { 3755 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3756 baij->barray = barray; 3757 } 3758 3759 if (roworiented) stepval = (n-1)*bs; 3760 else stepval = (m-1)*bs; 3761 3762 for (i=0; i<m; i++) { 3763 if (im[i] < 0) continue; 3764 #if defined(PETSC_USE_DEBUG) 3765 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); 3766 #endif 3767 if (im[i] >= rstart && im[i] < rend) { 3768 row = im[i] - rstart; 3769 for (j=0; j<n; j++) { 3770 /* If NumCol = 1 then a copy is not required */ 3771 if ((roworiented) && (n == 1)) { 3772 barray = (MatScalar*)v + i*bs2; 3773 } else if ((!roworiented) && (m == 1)) { 3774 barray = (MatScalar*)v + j*bs2; 3775 } else { /* Here a copy is required */ 3776 if (roworiented) { 3777 value = v + i*(stepval+bs)*bs + j*bs; 3778 } else { 3779 value = v + j*(stepval+bs)*bs + i*bs; 3780 } 3781 for (ii=0; ii<bs; ii++,value+=stepval) { 3782 for (jj=0; jj<bs; jj++) { 3783 *barray++ = *value++; 3784 } 3785 } 3786 barray -=bs2; 3787 } 3788 3789 if (in[j] >= cstart && in[j] < cend) { 3790 col = in[j] - cstart; 3791 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3792 } else if (in[j] < 0) continue; 3793 #if defined(PETSC_USE_DEBUG) 3794 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); 3795 #endif 3796 else { 3797 if (mat->was_assembled) { 3798 if (!baij->colmap) { 3799 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3800 } 3801 3802 #if defined(PETSC_USE_DEBUG) 3803 #if defined(PETSC_USE_CTABLE) 3804 { PetscInt data; 3805 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3806 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3807 } 3808 #else 3809 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3810 #endif 3811 #endif 3812 #if defined(PETSC_USE_CTABLE) 3813 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3814 col = (col - 1)/bs; 3815 #else 3816 col = (baij->colmap[in[j]] - 1)/bs; 3817 #endif 3818 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3819 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3820 col = in[j]; 3821 } 3822 } else col = in[j]; 3823 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3824 } 3825 } 3826 } else { 3827 if (!baij->donotstash) { 3828 if (roworiented) { 3829 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3830 } else { 3831 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3832 } 3833 } 3834 } 3835 } 3836 3837 /* task normally handled by MatSetValuesBlocked() */ 3838 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3839 PetscFunctionReturn(0); 3840 } 3841 3842 #undef __FUNCT__ 3843 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3844 /*@ 3845 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3846 CSR format the local rows. 3847 3848 Collective on MPI_Comm 3849 3850 Input Parameters: 3851 + comm - MPI communicator 3852 . bs - the block size, only a block size of 1 is supported 3853 . m - number of local rows (Cannot be PETSC_DECIDE) 3854 . n - This value should be the same as the local size used in creating the 3855 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3856 calculated if N is given) For square matrices n is almost always m. 3857 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3858 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3859 . i - row indices 3860 . j - column indices 3861 - a - matrix values 3862 3863 Output Parameter: 3864 . mat - the matrix 3865 3866 Level: intermediate 3867 3868 Notes: 3869 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3870 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3871 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3872 3873 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3874 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3875 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3876 with column-major ordering within blocks. 3877 3878 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3879 3880 .keywords: matrix, aij, compressed row, sparse, parallel 3881 3882 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3883 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3884 @*/ 3885 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) 3886 { 3887 PetscErrorCode ierr; 3888 3889 PetscFunctionBegin; 3890 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3891 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3892 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3893 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3894 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3895 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3896 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3897 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3898 PetscFunctionReturn(0); 3899 } 3900