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 PetscSF sf; 1728 PetscInt *lrows; 1729 PetscSFNode *rrows; 1730 PetscInt r, p = 0, len = 0; 1731 PetscErrorCode ierr; 1732 1733 PetscFunctionBegin; 1734 /* Create SF where leaves are input rows and roots are owned rows */ 1735 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1736 for (r = 0; r < n; ++r) lrows[r] = -1; 1737 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 1738 for (r = 0; r < N; ++r) { 1739 const PetscInt idx = rows[r]; 1740 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1741 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1742 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1743 } 1744 if (A->nooffproczerorows) { 1745 if (p != l->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,l->rank); 1746 lrows[len++] = idx - owners[p]; 1747 } else { 1748 rrows[r].rank = p; 1749 rrows[r].index = rows[r] - owners[p]; 1750 } 1751 } 1752 if (!A->nooffproczerorows) { 1753 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1754 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1755 /* Collect flags for rows to be zeroed */ 1756 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1757 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1758 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1759 /* Compress and put in row numbers */ 1760 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1761 } 1762 /* fix right hand side if needed */ 1763 if (x && b) { 1764 const PetscScalar *xx; 1765 PetscScalar *bb; 1766 1767 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1768 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1769 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1770 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1771 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1772 } 1773 1774 /* actually zap the local rows */ 1775 /* 1776 Zero the required rows. If the "diagonal block" of the matrix 1777 is square and the user wishes to set the diagonal we use separate 1778 code so that MatSetValues() is not called for each diagonal allocating 1779 new memory, thus calling lots of mallocs and slowing things down. 1780 1781 */ 1782 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1783 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1784 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1785 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1786 } else if (diag != 0.0) { 1787 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1788 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\ 1789 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1790 for (r = 0; r < len; ++r) { 1791 const PetscInt row = lrows[r] + A->rmap->rstart; 1792 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 } else { 1797 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1798 } 1799 ierr = PetscFree(lrows);CHKERRQ(ierr); 1800 1801 /* only change matrix nonzero state if pattern was allowed to be changed */ 1802 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1803 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1804 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1805 } 1806 PetscFunctionReturn(0); 1807 } 1808 1809 #undef __FUNCT__ 1810 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1811 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1812 { 1813 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1814 PetscErrorCode ierr; 1815 PetscMPIInt size = l->size,n = A->rmap->n,lastidx = -1; 1816 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1817 PetscInt *lrows,*owners = A->rmap->range; 1818 PetscSFNode *rrows; 1819 PetscSF sf; 1820 const PetscScalar *xx; 1821 PetscScalar *bb,*mask; 1822 Vec xmask,lmask; 1823 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1824 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1825 PetscScalar *aa; 1826 #if defined(PETSC_DEBUG) 1827 PetscBool found = PETSC_FALSE; 1828 #endif 1829 1830 PetscFunctionBegin; 1831 /* Create SF where leaves are input rows and roots are owned rows */ 1832 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1833 for (r = 0; r < n; ++r) lrows[r] = -1; 1834 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1835 for (r = 0; r < N; ++r) { 1836 const PetscInt idx = rows[r]; 1837 PetscBool found = PETSC_FALSE; 1838 /* Trick for efficient searching for sorted rows */ 1839 if (lastidx > idx) p = 0; 1840 lastidx = idx; 1841 for (; p < size; ++p) { 1842 if (idx >= owners[p] && idx < owners[p+1]) { 1843 rrows[r].rank = p; 1844 rrows[r].index = rows[r] - owners[p]; 1845 found = PETSC_TRUE; 1846 break; 1847 } 1848 } 1849 if (!found) SETERRQ1(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %d not found in matrix distribution", idx); 1850 } 1851 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1852 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1853 /* Collect flags for rows to be zeroed */ 1854 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1855 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1856 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1857 /* Compress and put in row numbers */ 1858 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1859 /* zero diagonal part of matrix */ 1860 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1861 /* handle off diagonal part of matrix */ 1862 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1863 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1864 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1865 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1866 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1867 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1868 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1869 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1870 if (x) { 1871 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1872 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1873 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1874 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1875 } 1876 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1877 /* remove zeroed rows of off diagonal matrix */ 1878 for (i = 0; i < len; ++i) { 1879 row = lrows[i]; 1880 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1881 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1882 for (k = 0; k < count; ++k) { 1883 aa[0] = 0.0; 1884 aa += bs; 1885 } 1886 } 1887 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1888 for (i = 0; i < l->B->rmap->N; ++i) { 1889 row = i/bs; 1890 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1891 for (k = 0; k < bs; ++k) { 1892 col = bs*baij->j[j] + k; 1893 if (PetscAbsScalar(mask[col])) { 1894 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1895 if (b) bb[i] -= aa[0]*xx[col]; 1896 aa[0] = 0.0; 1897 } 1898 } 1899 } 1900 } 1901 if (x) { 1902 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1903 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1904 } 1905 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1906 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1907 ierr = PetscFree(lrows);CHKERRQ(ierr); 1908 1909 /* only change matrix nonzero state if pattern was allowed to be changed */ 1910 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1911 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1912 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1919 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1920 { 1921 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1922 PetscErrorCode ierr; 1923 1924 PetscFunctionBegin; 1925 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1926 PetscFunctionReturn(0); 1927 } 1928 1929 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1930 1931 #undef __FUNCT__ 1932 #define __FUNCT__ "MatEqual_MPIBAIJ" 1933 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1934 { 1935 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1936 Mat a,b,c,d; 1937 PetscBool flg; 1938 PetscErrorCode ierr; 1939 1940 PetscFunctionBegin; 1941 a = matA->A; b = matA->B; 1942 c = matB->A; d = matB->B; 1943 1944 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1945 if (flg) { 1946 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1947 } 1948 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1949 PetscFunctionReturn(0); 1950 } 1951 1952 #undef __FUNCT__ 1953 #define __FUNCT__ "MatCopy_MPIBAIJ" 1954 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1955 { 1956 PetscErrorCode ierr; 1957 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1958 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1959 1960 PetscFunctionBegin; 1961 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1962 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1963 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1964 } else { 1965 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1966 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1967 } 1968 PetscFunctionReturn(0); 1969 } 1970 1971 #undef __FUNCT__ 1972 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1973 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1974 { 1975 PetscErrorCode ierr; 1976 1977 PetscFunctionBegin; 1978 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1979 PetscFunctionReturn(0); 1980 } 1981 1982 #undef __FUNCT__ 1983 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 1984 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1985 { 1986 PetscErrorCode ierr; 1987 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1988 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1989 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1990 1991 PetscFunctionBegin; 1992 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1993 PetscFunctionReturn(0); 1994 } 1995 1996 #undef __FUNCT__ 1997 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1998 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1999 { 2000 PetscErrorCode ierr; 2001 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 2002 PetscBLASInt bnz,one=1; 2003 Mat_SeqBAIJ *x,*y; 2004 2005 PetscFunctionBegin; 2006 if (str == SAME_NONZERO_PATTERN) { 2007 PetscScalar alpha = a; 2008 x = (Mat_SeqBAIJ*)xx->A->data; 2009 y = (Mat_SeqBAIJ*)yy->A->data; 2010 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2011 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2012 x = (Mat_SeqBAIJ*)xx->B->data; 2013 y = (Mat_SeqBAIJ*)yy->B->data; 2014 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2015 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2016 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2017 } else { 2018 Mat B; 2019 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2020 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2021 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2022 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2023 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2024 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2025 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2026 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2027 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2028 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2029 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2030 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2031 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2032 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2033 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2034 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2035 } 2036 PetscFunctionReturn(0); 2037 } 2038 2039 #undef __FUNCT__ 2040 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2041 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2042 { 2043 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2044 PetscErrorCode ierr; 2045 2046 PetscFunctionBegin; 2047 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2048 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2049 PetscFunctionReturn(0); 2050 } 2051 2052 #undef __FUNCT__ 2053 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2054 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2055 { 2056 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2057 PetscErrorCode ierr; 2058 2059 PetscFunctionBegin; 2060 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2061 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2062 PetscFunctionReturn(0); 2063 } 2064 2065 #undef __FUNCT__ 2066 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2067 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2068 { 2069 PetscErrorCode ierr; 2070 IS iscol_local; 2071 PetscInt csize; 2072 2073 PetscFunctionBegin; 2074 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2075 if (call == MAT_REUSE_MATRIX) { 2076 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2077 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2078 } else { 2079 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2080 } 2081 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2082 if (call == MAT_INITIAL_MATRIX) { 2083 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2084 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2085 } 2086 PetscFunctionReturn(0); 2087 } 2088 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2089 #undef __FUNCT__ 2090 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2091 /* 2092 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2093 in local and then by concatenating the local matrices the end result. 2094 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2095 */ 2096 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2097 { 2098 PetscErrorCode ierr; 2099 PetscMPIInt rank,size; 2100 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2101 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2102 Mat M,Mreuse; 2103 MatScalar *vwork,*aa; 2104 MPI_Comm comm; 2105 IS isrow_new, iscol_new; 2106 PetscBool idflag,allrows, allcols; 2107 Mat_SeqBAIJ *aij; 2108 2109 PetscFunctionBegin; 2110 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2111 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2112 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2113 /* The compression and expansion should be avoided. Doesn't point 2114 out errors, might change the indices, hence buggey */ 2115 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2116 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2117 2118 /* Check for special case: each processor gets entire matrix columns */ 2119 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2120 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2121 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2122 else allcols = PETSC_FALSE; 2123 2124 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2125 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2126 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2127 else allrows = PETSC_FALSE; 2128 2129 if (call == MAT_REUSE_MATRIX) { 2130 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2131 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2132 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2133 } else { 2134 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2135 } 2136 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2137 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2138 /* 2139 m - number of local rows 2140 n - number of columns (same on all processors) 2141 rstart - first row in new global matrix generated 2142 */ 2143 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2144 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2145 m = m/bs; 2146 n = n/bs; 2147 2148 if (call == MAT_INITIAL_MATRIX) { 2149 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2150 ii = aij->i; 2151 jj = aij->j; 2152 2153 /* 2154 Determine the number of non-zeros in the diagonal and off-diagonal 2155 portions of the matrix in order to do correct preallocation 2156 */ 2157 2158 /* first get start and end of "diagonal" columns */ 2159 if (csize == PETSC_DECIDE) { 2160 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2161 if (mglobal == n*bs) { /* square matrix */ 2162 nlocal = m; 2163 } else { 2164 nlocal = n/size + ((n % size) > rank); 2165 } 2166 } else { 2167 nlocal = csize/bs; 2168 } 2169 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2170 rstart = rend - nlocal; 2171 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); 2172 2173 /* next, compute all the lengths */ 2174 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2175 for (i=0; i<m; i++) { 2176 jend = ii[i+1] - ii[i]; 2177 olen = 0; 2178 dlen = 0; 2179 for (j=0; j<jend; j++) { 2180 if (*jj < rstart || *jj >= rend) olen++; 2181 else dlen++; 2182 jj++; 2183 } 2184 olens[i] = olen; 2185 dlens[i] = dlen; 2186 } 2187 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2188 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2189 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2190 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2191 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2192 } else { 2193 PetscInt ml,nl; 2194 2195 M = *newmat; 2196 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2197 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2198 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2199 /* 2200 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2201 rather than the slower MatSetValues(). 2202 */ 2203 M->was_assembled = PETSC_TRUE; 2204 M->assembled = PETSC_FALSE; 2205 } 2206 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2207 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2208 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2209 ii = aij->i; 2210 jj = aij->j; 2211 aa = aij->a; 2212 for (i=0; i<m; i++) { 2213 row = rstart/bs + i; 2214 nz = ii[i+1] - ii[i]; 2215 cwork = jj; jj += nz; 2216 vwork = aa; aa += nz*bs*bs; 2217 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2218 } 2219 2220 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2221 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2222 *newmat = M; 2223 2224 /* save submatrix used in processor for next request */ 2225 if (call == MAT_INITIAL_MATRIX) { 2226 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2227 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2228 } 2229 PetscFunctionReturn(0); 2230 } 2231 2232 #undef __FUNCT__ 2233 #define __FUNCT__ "MatPermute_MPIBAIJ" 2234 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2235 { 2236 MPI_Comm comm,pcomm; 2237 PetscInt clocal_size,nrows; 2238 const PetscInt *rows; 2239 PetscMPIInt size; 2240 IS crowp,lcolp; 2241 PetscErrorCode ierr; 2242 2243 PetscFunctionBegin; 2244 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2245 /* make a collective version of 'rowp' */ 2246 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2247 if (pcomm==comm) { 2248 crowp = rowp; 2249 } else { 2250 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2251 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2252 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2253 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2254 } 2255 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2256 /* make a local version of 'colp' */ 2257 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2258 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2259 if (size==1) { 2260 lcolp = colp; 2261 } else { 2262 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2263 } 2264 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2265 /* now we just get the submatrix */ 2266 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2267 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2268 /* clean up */ 2269 if (pcomm!=comm) { 2270 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2271 } 2272 if (size>1) { 2273 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2274 } 2275 PetscFunctionReturn(0); 2276 } 2277 2278 #undef __FUNCT__ 2279 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2280 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2281 { 2282 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2283 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2284 2285 PetscFunctionBegin; 2286 if (nghosts) *nghosts = B->nbs; 2287 if (ghosts) *ghosts = baij->garray; 2288 PetscFunctionReturn(0); 2289 } 2290 2291 #undef __FUNCT__ 2292 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2293 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2294 { 2295 Mat B; 2296 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2297 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2298 Mat_SeqAIJ *b; 2299 PetscErrorCode ierr; 2300 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2301 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2302 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2303 2304 PetscFunctionBegin; 2305 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2306 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2307 2308 /* ---------------------------------------------------------------- 2309 Tell every processor the number of nonzeros per row 2310 */ 2311 ierr = PetscMalloc1((A->rmap->N/bs),&lens);CHKERRQ(ierr); 2312 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2313 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]; 2314 } 2315 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2316 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2317 displs = recvcounts + size; 2318 for (i=0; i<size; i++) { 2319 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2320 displs[i] = A->rmap->range[i]/bs; 2321 } 2322 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2323 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2324 #else 2325 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2326 #endif 2327 /* --------------------------------------------------------------- 2328 Create the sequential matrix of the same type as the local block diagonal 2329 */ 2330 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2331 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2332 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2333 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2334 b = (Mat_SeqAIJ*)B->data; 2335 2336 /*-------------------------------------------------------------------- 2337 Copy my part of matrix column indices over 2338 */ 2339 sendcount = ad->nz + bd->nz; 2340 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2341 a_jsendbuf = ad->j; 2342 b_jsendbuf = bd->j; 2343 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2344 cnt = 0; 2345 for (i=0; i<n; i++) { 2346 2347 /* put in lower diagonal portion */ 2348 m = bd->i[i+1] - bd->i[i]; 2349 while (m > 0) { 2350 /* is it above diagonal (in bd (compressed) numbering) */ 2351 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2352 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2353 m--; 2354 } 2355 2356 /* put in diagonal portion */ 2357 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2358 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2359 } 2360 2361 /* put in upper diagonal portion */ 2362 while (m-- > 0) { 2363 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2364 } 2365 } 2366 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2367 2368 /*-------------------------------------------------------------------- 2369 Gather all column indices to all processors 2370 */ 2371 for (i=0; i<size; i++) { 2372 recvcounts[i] = 0; 2373 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2374 recvcounts[i] += lens[j]; 2375 } 2376 } 2377 displs[0] = 0; 2378 for (i=1; i<size; i++) { 2379 displs[i] = displs[i-1] + recvcounts[i-1]; 2380 } 2381 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2382 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2383 #else 2384 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2385 #endif 2386 /*-------------------------------------------------------------------- 2387 Assemble the matrix into useable form (note numerical values not yet set) 2388 */ 2389 /* set the b->ilen (length of each row) values */ 2390 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2391 /* set the b->i indices */ 2392 b->i[0] = 0; 2393 for (i=1; i<=A->rmap->N/bs; i++) { 2394 b->i[i] = b->i[i-1] + lens[i-1]; 2395 } 2396 ierr = PetscFree(lens);CHKERRQ(ierr); 2397 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2398 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2399 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2400 2401 if (A->symmetric) { 2402 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2403 } else if (A->hermitian) { 2404 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2405 } else if (A->structurally_symmetric) { 2406 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2407 } 2408 *newmat = B; 2409 PetscFunctionReturn(0); 2410 } 2411 2412 #undef __FUNCT__ 2413 #define __FUNCT__ "MatSOR_MPIBAIJ" 2414 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2415 { 2416 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2417 PetscErrorCode ierr; 2418 Vec bb1 = 0; 2419 2420 PetscFunctionBegin; 2421 if (flag == SOR_APPLY_UPPER) { 2422 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2423 PetscFunctionReturn(0); 2424 } 2425 2426 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2427 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2428 } 2429 2430 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2431 if (flag & SOR_ZERO_INITIAL_GUESS) { 2432 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2433 its--; 2434 } 2435 2436 while (its--) { 2437 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2438 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2439 2440 /* update rhs: bb1 = bb - B*x */ 2441 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2442 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2443 2444 /* local sweep */ 2445 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2446 } 2447 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2448 if (flag & SOR_ZERO_INITIAL_GUESS) { 2449 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2450 its--; 2451 } 2452 while (its--) { 2453 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2454 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2455 2456 /* update rhs: bb1 = bb - B*x */ 2457 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2458 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2459 2460 /* local sweep */ 2461 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2462 } 2463 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2464 if (flag & SOR_ZERO_INITIAL_GUESS) { 2465 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2466 its--; 2467 } 2468 while (its--) { 2469 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2470 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2471 2472 /* update rhs: bb1 = bb - B*x */ 2473 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2474 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2475 2476 /* local sweep */ 2477 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2478 } 2479 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2480 2481 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2482 PetscFunctionReturn(0); 2483 } 2484 2485 #undef __FUNCT__ 2486 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2487 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2488 { 2489 PetscErrorCode ierr; 2490 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2491 PetscInt N,i,*garray = aij->garray; 2492 PetscInt ib,jb,bs = A->rmap->bs; 2493 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2494 MatScalar *a_val = a_aij->a; 2495 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2496 MatScalar *b_val = b_aij->a; 2497 PetscReal *work; 2498 2499 PetscFunctionBegin; 2500 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2501 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2502 if (type == NORM_2) { 2503 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2504 for (jb=0; jb<bs; jb++) { 2505 for (ib=0; ib<bs; ib++) { 2506 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2507 a_val++; 2508 } 2509 } 2510 } 2511 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2512 for (jb=0; jb<bs; jb++) { 2513 for (ib=0; ib<bs; ib++) { 2514 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2515 b_val++; 2516 } 2517 } 2518 } 2519 } else if (type == NORM_1) { 2520 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2521 for (jb=0; jb<bs; jb++) { 2522 for (ib=0; ib<bs; ib++) { 2523 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2524 a_val++; 2525 } 2526 } 2527 } 2528 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2529 for (jb=0; jb<bs; jb++) { 2530 for (ib=0; ib<bs; ib++) { 2531 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2532 b_val++; 2533 } 2534 } 2535 } 2536 } else if (type == NORM_INFINITY) { 2537 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2538 for (jb=0; jb<bs; jb++) { 2539 for (ib=0; ib<bs; ib++) { 2540 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2541 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2542 a_val++; 2543 } 2544 } 2545 } 2546 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2547 for (jb=0; jb<bs; jb++) { 2548 for (ib=0; ib<bs; ib++) { 2549 int col = garray[b_aij->j[i]] * bs + jb; 2550 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2551 b_val++; 2552 } 2553 } 2554 } 2555 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2556 if (type == NORM_INFINITY) { 2557 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2558 } else { 2559 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2560 } 2561 ierr = PetscFree(work);CHKERRQ(ierr); 2562 if (type == NORM_2) { 2563 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2564 } 2565 PetscFunctionReturn(0); 2566 } 2567 2568 #undef __FUNCT__ 2569 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2570 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2571 { 2572 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2573 PetscErrorCode ierr; 2574 2575 PetscFunctionBegin; 2576 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2577 PetscFunctionReturn(0); 2578 } 2579 2580 2581 /* -------------------------------------------------------------------*/ 2582 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2583 MatGetRow_MPIBAIJ, 2584 MatRestoreRow_MPIBAIJ, 2585 MatMult_MPIBAIJ, 2586 /* 4*/ MatMultAdd_MPIBAIJ, 2587 MatMultTranspose_MPIBAIJ, 2588 MatMultTransposeAdd_MPIBAIJ, 2589 0, 2590 0, 2591 0, 2592 /*10*/ 0, 2593 0, 2594 0, 2595 MatSOR_MPIBAIJ, 2596 MatTranspose_MPIBAIJ, 2597 /*15*/ MatGetInfo_MPIBAIJ, 2598 MatEqual_MPIBAIJ, 2599 MatGetDiagonal_MPIBAIJ, 2600 MatDiagonalScale_MPIBAIJ, 2601 MatNorm_MPIBAIJ, 2602 /*20*/ MatAssemblyBegin_MPIBAIJ, 2603 MatAssemblyEnd_MPIBAIJ, 2604 MatSetOption_MPIBAIJ, 2605 MatZeroEntries_MPIBAIJ, 2606 /*24*/ MatZeroRows_MPIBAIJ, 2607 0, 2608 0, 2609 0, 2610 0, 2611 /*29*/ MatSetUp_MPIBAIJ, 2612 0, 2613 0, 2614 0, 2615 0, 2616 /*34*/ MatDuplicate_MPIBAIJ, 2617 0, 2618 0, 2619 0, 2620 0, 2621 /*39*/ MatAXPY_MPIBAIJ, 2622 MatGetSubMatrices_MPIBAIJ, 2623 MatIncreaseOverlap_MPIBAIJ, 2624 MatGetValues_MPIBAIJ, 2625 MatCopy_MPIBAIJ, 2626 /*44*/ 0, 2627 MatScale_MPIBAIJ, 2628 0, 2629 0, 2630 MatZeroRowsColumns_MPIBAIJ, 2631 /*49*/ 0, 2632 0, 2633 0, 2634 0, 2635 0, 2636 /*54*/ MatFDColoringCreate_MPIXAIJ, 2637 0, 2638 MatSetUnfactored_MPIBAIJ, 2639 MatPermute_MPIBAIJ, 2640 MatSetValuesBlocked_MPIBAIJ, 2641 /*59*/ MatGetSubMatrix_MPIBAIJ, 2642 MatDestroy_MPIBAIJ, 2643 MatView_MPIBAIJ, 2644 0, 2645 0, 2646 /*64*/ 0, 2647 0, 2648 0, 2649 0, 2650 0, 2651 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2652 0, 2653 0, 2654 0, 2655 0, 2656 /*74*/ 0, 2657 MatFDColoringApply_BAIJ, 2658 0, 2659 0, 2660 0, 2661 /*79*/ 0, 2662 0, 2663 0, 2664 0, 2665 MatLoad_MPIBAIJ, 2666 /*84*/ 0, 2667 0, 2668 0, 2669 0, 2670 0, 2671 /*89*/ 0, 2672 0, 2673 0, 2674 0, 2675 0, 2676 /*94*/ 0, 2677 0, 2678 0, 2679 0, 2680 0, 2681 /*99*/ 0, 2682 0, 2683 0, 2684 0, 2685 0, 2686 /*104*/0, 2687 MatRealPart_MPIBAIJ, 2688 MatImaginaryPart_MPIBAIJ, 2689 0, 2690 0, 2691 /*109*/0, 2692 0, 2693 0, 2694 0, 2695 0, 2696 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2697 0, 2698 MatGetGhosts_MPIBAIJ, 2699 0, 2700 0, 2701 /*119*/0, 2702 0, 2703 0, 2704 0, 2705 MatGetMultiProcBlock_MPIBAIJ, 2706 /*124*/0, 2707 MatGetColumnNorms_MPIBAIJ, 2708 MatInvertBlockDiagonal_MPIBAIJ, 2709 0, 2710 0, 2711 /*129*/ 0, 2712 0, 2713 0, 2714 0, 2715 0, 2716 /*134*/ 0, 2717 0, 2718 0, 2719 0, 2720 0, 2721 /*139*/ 0, 2722 0, 2723 0, 2724 MatFDColoringSetUp_MPIXAIJ 2725 }; 2726 2727 #undef __FUNCT__ 2728 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2729 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2730 { 2731 PetscFunctionBegin; 2732 *a = ((Mat_MPIBAIJ*)A->data)->A; 2733 PetscFunctionReturn(0); 2734 } 2735 2736 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2737 2738 #undef __FUNCT__ 2739 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2740 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2741 { 2742 PetscInt m,rstart,cstart,cend; 2743 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2744 const PetscInt *JJ =0; 2745 PetscScalar *values=0; 2746 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2747 PetscErrorCode ierr; 2748 2749 PetscFunctionBegin; 2750 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2751 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2752 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2753 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2754 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2755 m = B->rmap->n/bs; 2756 rstart = B->rmap->rstart/bs; 2757 cstart = B->cmap->rstart/bs; 2758 cend = B->cmap->rend/bs; 2759 2760 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2761 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2762 for (i=0; i<m; i++) { 2763 nz = ii[i+1] - ii[i]; 2764 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2765 nz_max = PetscMax(nz_max,nz); 2766 JJ = jj + ii[i]; 2767 for (j=0; j<nz; j++) { 2768 if (*JJ >= cstart) break; 2769 JJ++; 2770 } 2771 d = 0; 2772 for (; j<nz; j++) { 2773 if (*JJ++ >= cend) break; 2774 d++; 2775 } 2776 d_nnz[i] = d; 2777 o_nnz[i] = nz - d; 2778 } 2779 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2780 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2781 2782 values = (PetscScalar*)V; 2783 if (!values) { 2784 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2785 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2786 } 2787 for (i=0; i<m; i++) { 2788 PetscInt row = i + rstart; 2789 PetscInt ncols = ii[i+1] - ii[i]; 2790 const PetscInt *icols = jj + ii[i]; 2791 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2792 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2793 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2794 } else { /* block ordering does not match so we can only insert one block at a time. */ 2795 PetscInt j; 2796 for (j=0; j<ncols; j++) { 2797 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2798 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2799 } 2800 } 2801 } 2802 2803 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2804 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2805 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2806 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2807 PetscFunctionReturn(0); 2808 } 2809 2810 #undef __FUNCT__ 2811 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2812 /*@C 2813 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2814 (the default parallel PETSc format). 2815 2816 Collective on MPI_Comm 2817 2818 Input Parameters: 2819 + B - the matrix 2820 . bs - the block size 2821 . i - the indices into j for the start of each local row (starts with zero) 2822 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2823 - v - optional values in the matrix 2824 2825 Level: developer 2826 2827 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2828 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2829 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2830 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2831 block column and the second index is over columns within a block. 2832 2833 .keywords: matrix, aij, compressed row, sparse, parallel 2834 2835 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2836 @*/ 2837 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2838 { 2839 PetscErrorCode ierr; 2840 2841 PetscFunctionBegin; 2842 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2843 PetscValidType(B,1); 2844 PetscValidLogicalCollectiveInt(B,bs,2); 2845 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2846 PetscFunctionReturn(0); 2847 } 2848 2849 #undef __FUNCT__ 2850 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2851 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2852 { 2853 Mat_MPIBAIJ *b; 2854 PetscErrorCode ierr; 2855 PetscInt i; 2856 2857 PetscFunctionBegin; 2858 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2859 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2860 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2861 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2862 2863 if (d_nnz) { 2864 for (i=0; i<B->rmap->n/bs; i++) { 2865 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]); 2866 } 2867 } 2868 if (o_nnz) { 2869 for (i=0; i<B->rmap->n/bs; i++) { 2870 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]); 2871 } 2872 } 2873 2874 b = (Mat_MPIBAIJ*)B->data; 2875 b->bs2 = bs*bs; 2876 b->mbs = B->rmap->n/bs; 2877 b->nbs = B->cmap->n/bs; 2878 b->Mbs = B->rmap->N/bs; 2879 b->Nbs = B->cmap->N/bs; 2880 2881 for (i=0; i<=b->size; i++) { 2882 b->rangebs[i] = B->rmap->range[i]/bs; 2883 } 2884 b->rstartbs = B->rmap->rstart/bs; 2885 b->rendbs = B->rmap->rend/bs; 2886 b->cstartbs = B->cmap->rstart/bs; 2887 b->cendbs = B->cmap->rend/bs; 2888 2889 if (!B->preallocated) { 2890 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2891 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2892 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2893 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2894 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2895 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2896 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2897 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2898 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2899 } 2900 2901 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2902 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2903 B->preallocated = PETSC_TRUE; 2904 PetscFunctionReturn(0); 2905 } 2906 2907 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2908 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2909 2910 #undef __FUNCT__ 2911 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2912 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2913 { 2914 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2915 PetscErrorCode ierr; 2916 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2917 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2918 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2919 2920 PetscFunctionBegin; 2921 ierr = PetscMalloc1((M+1),&ii);CHKERRQ(ierr); 2922 ii[0] = 0; 2923 for (i=0; i<M; i++) { 2924 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]); 2925 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]); 2926 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2927 /* remove one from count of matrix has diagonal */ 2928 for (j=id[i]; j<id[i+1]; j++) { 2929 if (jd[j] == i) {ii[i+1]--;break;} 2930 } 2931 } 2932 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2933 cnt = 0; 2934 for (i=0; i<M; i++) { 2935 for (j=io[i]; j<io[i+1]; j++) { 2936 if (garray[jo[j]] > rstart) break; 2937 jj[cnt++] = garray[jo[j]]; 2938 } 2939 for (k=id[i]; k<id[i+1]; k++) { 2940 if (jd[k] != i) { 2941 jj[cnt++] = rstart + jd[k]; 2942 } 2943 } 2944 for (; j<io[i+1]; j++) { 2945 jj[cnt++] = garray[jo[j]]; 2946 } 2947 } 2948 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2949 PetscFunctionReturn(0); 2950 } 2951 2952 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2953 2954 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2955 2956 #undef __FUNCT__ 2957 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2958 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2959 { 2960 PetscErrorCode ierr; 2961 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2962 Mat B; 2963 Mat_MPIAIJ *b; 2964 2965 PetscFunctionBegin; 2966 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2967 2968 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2969 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2970 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2971 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2972 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2973 b = (Mat_MPIAIJ*) B->data; 2974 2975 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2976 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2977 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2978 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2979 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2980 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2981 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2982 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2983 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2984 if (reuse == MAT_REUSE_MATRIX) { 2985 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2986 } else { 2987 *newmat = B; 2988 } 2989 PetscFunctionReturn(0); 2990 } 2991 2992 #if defined(PETSC_HAVE_MUMPS) 2993 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2994 #endif 2995 2996 /*MC 2997 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2998 2999 Options Database Keys: 3000 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3001 . -mat_block_size <bs> - set the blocksize used to store the matrix 3002 - -mat_use_hash_table <fact> 3003 3004 Level: beginner 3005 3006 .seealso: MatCreateMPIBAIJ 3007 M*/ 3008 3009 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3010 3011 #undef __FUNCT__ 3012 #define __FUNCT__ "MatCreate_MPIBAIJ" 3013 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3014 { 3015 Mat_MPIBAIJ *b; 3016 PetscErrorCode ierr; 3017 PetscBool flg; 3018 3019 PetscFunctionBegin; 3020 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3021 B->data = (void*)b; 3022 3023 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3024 B->assembled = PETSC_FALSE; 3025 3026 B->insertmode = NOT_SET_VALUES; 3027 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3028 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3029 3030 /* build local table of row and column ownerships */ 3031 ierr = PetscMalloc1((b->size+1),&b->rangebs);CHKERRQ(ierr); 3032 3033 /* build cache for off array entries formed */ 3034 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3035 3036 b->donotstash = PETSC_FALSE; 3037 b->colmap = NULL; 3038 b->garray = NULL; 3039 b->roworiented = PETSC_TRUE; 3040 3041 /* stuff used in block assembly */ 3042 b->barray = 0; 3043 3044 /* stuff used for matrix vector multiply */ 3045 b->lvec = 0; 3046 b->Mvctx = 0; 3047 3048 /* stuff for MatGetRow() */ 3049 b->rowindices = 0; 3050 b->rowvalues = 0; 3051 b->getrowactive = PETSC_FALSE; 3052 3053 /* hash table stuff */ 3054 b->ht = 0; 3055 b->hd = 0; 3056 b->ht_size = 0; 3057 b->ht_flag = PETSC_FALSE; 3058 b->ht_fact = 0; 3059 b->ht_total_ct = 0; 3060 b->ht_insert_ct = 0; 3061 3062 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3063 b->ijonly = PETSC_FALSE; 3064 3065 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3066 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3067 if (flg) { 3068 PetscReal fact = 1.39; 3069 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3070 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3071 if (fact <= 1.0) fact = 1.39; 3072 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3073 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3074 } 3075 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3076 3077 #if defined(PETSC_HAVE_MUMPS) 3078 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3079 #endif 3080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3086 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3091 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3092 PetscFunctionReturn(0); 3093 } 3094 3095 /*MC 3096 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3097 3098 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3099 and MATMPIBAIJ otherwise. 3100 3101 Options Database Keys: 3102 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3103 3104 Level: beginner 3105 3106 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3107 M*/ 3108 3109 #undef __FUNCT__ 3110 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3111 /*@C 3112 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3113 (block compressed row). For good matrix assembly performance 3114 the user should preallocate the matrix storage by setting the parameters 3115 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3116 performance can be increased by more than a factor of 50. 3117 3118 Collective on Mat 3119 3120 Input Parameters: 3121 + B - the matrix 3122 . bs - size of block 3123 . d_nz - number of block nonzeros per block row in diagonal portion of local 3124 submatrix (same for all local rows) 3125 . d_nnz - array containing the number of block nonzeros in the various block rows 3126 of the in diagonal portion of the local (possibly different for each block 3127 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3128 set it even if it is zero. 3129 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3130 submatrix (same for all local rows). 3131 - o_nnz - array containing the number of nonzeros in the various block rows of the 3132 off-diagonal portion of the local submatrix (possibly different for 3133 each block row) or NULL. 3134 3135 If the *_nnz parameter is given then the *_nz parameter is ignored 3136 3137 Options Database Keys: 3138 + -mat_block_size - size of the blocks to use 3139 - -mat_use_hash_table <fact> 3140 3141 Notes: 3142 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3143 than it must be used on all processors that share the object for that argument. 3144 3145 Storage Information: 3146 For a square global matrix we define each processor's diagonal portion 3147 to be its local rows and the corresponding columns (a square submatrix); 3148 each processor's off-diagonal portion encompasses the remainder of the 3149 local matrix (a rectangular submatrix). 3150 3151 The user can specify preallocated storage for the diagonal part of 3152 the local submatrix with either d_nz or d_nnz (not both). Set 3153 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3154 memory allocation. Likewise, specify preallocated storage for the 3155 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3156 3157 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3158 the figure below we depict these three local rows and all columns (0-11). 3159 3160 .vb 3161 0 1 2 3 4 5 6 7 8 9 10 11 3162 -------------------------- 3163 row 3 |o o o d d d o o o o o o 3164 row 4 |o o o d d d o o o o o o 3165 row 5 |o o o d d d o o o o o o 3166 -------------------------- 3167 .ve 3168 3169 Thus, any entries in the d locations are stored in the d (diagonal) 3170 submatrix, and any entries in the o locations are stored in the 3171 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3172 stored simply in the MATSEQBAIJ format for compressed row storage. 3173 3174 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3175 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3176 In general, for PDE problems in which most nonzeros are near the diagonal, 3177 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3178 or you will get TERRIBLE performance; see the users' manual chapter on 3179 matrices. 3180 3181 You can call MatGetInfo() to get information on how effective the preallocation was; 3182 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3183 You can also run with the option -info and look for messages with the string 3184 malloc in them to see if additional memory allocation was needed. 3185 3186 Level: intermediate 3187 3188 .keywords: matrix, block, aij, compressed row, sparse, parallel 3189 3190 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3191 @*/ 3192 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3193 { 3194 PetscErrorCode ierr; 3195 3196 PetscFunctionBegin; 3197 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3198 PetscValidType(B,1); 3199 PetscValidLogicalCollectiveInt(B,bs,2); 3200 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); 3201 PetscFunctionReturn(0); 3202 } 3203 3204 #undef __FUNCT__ 3205 #define __FUNCT__ "MatCreateBAIJ" 3206 /*@C 3207 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3208 (block compressed row). For good matrix assembly performance 3209 the user should preallocate the matrix storage by setting the parameters 3210 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3211 performance can be increased by more than a factor of 50. 3212 3213 Collective on MPI_Comm 3214 3215 Input Parameters: 3216 + comm - MPI communicator 3217 . bs - size of blockk 3218 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3219 This value should be the same as the local size used in creating the 3220 y vector for the matrix-vector product y = Ax. 3221 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3222 This value should be the same as the local size used in creating the 3223 x vector for the matrix-vector product y = Ax. 3224 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3225 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3226 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3227 submatrix (same for all local rows) 3228 . d_nnz - array containing the number of nonzero blocks in the various block rows 3229 of the in diagonal portion of the local (possibly different for each block 3230 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3231 and set it even if it is zero. 3232 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3233 submatrix (same for all local rows). 3234 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3235 off-diagonal portion of the local submatrix (possibly different for 3236 each block row) or NULL. 3237 3238 Output Parameter: 3239 . A - the matrix 3240 3241 Options Database Keys: 3242 + -mat_block_size - size of the blocks to use 3243 - -mat_use_hash_table <fact> 3244 3245 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3246 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3247 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3248 3249 Notes: 3250 If the *_nnz parameter is given then the *_nz parameter is ignored 3251 3252 A nonzero block is any block that as 1 or more nonzeros in it 3253 3254 The user MUST specify either the local or global matrix dimensions 3255 (possibly both). 3256 3257 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3258 than it must be used on all processors that share the object for that argument. 3259 3260 Storage Information: 3261 For a square global matrix we define each processor's diagonal portion 3262 to be its local rows and the corresponding columns (a square submatrix); 3263 each processor's off-diagonal portion encompasses the remainder of the 3264 local matrix (a rectangular submatrix). 3265 3266 The user can specify preallocated storage for the diagonal part of 3267 the local submatrix with either d_nz or d_nnz (not both). Set 3268 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3269 memory allocation. Likewise, specify preallocated storage for the 3270 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3271 3272 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3273 the figure below we depict these three local rows and all columns (0-11). 3274 3275 .vb 3276 0 1 2 3 4 5 6 7 8 9 10 11 3277 -------------------------- 3278 row 3 |o o o d d d o o o o o o 3279 row 4 |o o o d d d o o o o o o 3280 row 5 |o o o d d d o o o o o o 3281 -------------------------- 3282 .ve 3283 3284 Thus, any entries in the d locations are stored in the d (diagonal) 3285 submatrix, and any entries in the o locations are stored in the 3286 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3287 stored simply in the MATSEQBAIJ format for compressed row storage. 3288 3289 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3290 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3291 In general, for PDE problems in which most nonzeros are near the diagonal, 3292 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3293 or you will get TERRIBLE performance; see the users' manual chapter on 3294 matrices. 3295 3296 Level: intermediate 3297 3298 .keywords: matrix, block, aij, compressed row, sparse, parallel 3299 3300 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3301 @*/ 3302 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) 3303 { 3304 PetscErrorCode ierr; 3305 PetscMPIInt size; 3306 3307 PetscFunctionBegin; 3308 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3309 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3310 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3311 if (size > 1) { 3312 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3313 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3314 } else { 3315 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3316 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3317 } 3318 PetscFunctionReturn(0); 3319 } 3320 3321 #undef __FUNCT__ 3322 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3323 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3324 { 3325 Mat mat; 3326 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3327 PetscErrorCode ierr; 3328 PetscInt len=0; 3329 3330 PetscFunctionBegin; 3331 *newmat = 0; 3332 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3333 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3334 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3335 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3336 3337 mat->factortype = matin->factortype; 3338 mat->preallocated = PETSC_TRUE; 3339 mat->assembled = PETSC_TRUE; 3340 mat->insertmode = NOT_SET_VALUES; 3341 3342 a = (Mat_MPIBAIJ*)mat->data; 3343 mat->rmap->bs = matin->rmap->bs; 3344 a->bs2 = oldmat->bs2; 3345 a->mbs = oldmat->mbs; 3346 a->nbs = oldmat->nbs; 3347 a->Mbs = oldmat->Mbs; 3348 a->Nbs = oldmat->Nbs; 3349 3350 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3351 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3352 3353 a->size = oldmat->size; 3354 a->rank = oldmat->rank; 3355 a->donotstash = oldmat->donotstash; 3356 a->roworiented = oldmat->roworiented; 3357 a->rowindices = 0; 3358 a->rowvalues = 0; 3359 a->getrowactive = PETSC_FALSE; 3360 a->barray = 0; 3361 a->rstartbs = oldmat->rstartbs; 3362 a->rendbs = oldmat->rendbs; 3363 a->cstartbs = oldmat->cstartbs; 3364 a->cendbs = oldmat->cendbs; 3365 3366 /* hash table stuff */ 3367 a->ht = 0; 3368 a->hd = 0; 3369 a->ht_size = 0; 3370 a->ht_flag = oldmat->ht_flag; 3371 a->ht_fact = oldmat->ht_fact; 3372 a->ht_total_ct = 0; 3373 a->ht_insert_ct = 0; 3374 3375 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3376 if (oldmat->colmap) { 3377 #if defined(PETSC_USE_CTABLE) 3378 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3379 #else 3380 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 3381 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3382 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3383 #endif 3384 } else a->colmap = 0; 3385 3386 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3387 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3388 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3389 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3390 } else a->garray = 0; 3391 3392 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3393 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3394 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3395 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3396 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3397 3398 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3399 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3400 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3401 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3402 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3403 *newmat = mat; 3404 PetscFunctionReturn(0); 3405 } 3406 3407 #undef __FUNCT__ 3408 #define __FUNCT__ "MatLoad_MPIBAIJ" 3409 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3410 { 3411 PetscErrorCode ierr; 3412 int fd; 3413 PetscInt i,nz,j,rstart,rend; 3414 PetscScalar *vals,*buf; 3415 MPI_Comm comm; 3416 MPI_Status status; 3417 PetscMPIInt rank,size,maxnz; 3418 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3419 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3420 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3421 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3422 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3423 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3424 3425 PetscFunctionBegin; 3426 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3427 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3428 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3429 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3430 3431 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3432 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3433 if (!rank) { 3434 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3435 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3436 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3437 } 3438 3439 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3440 3441 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3442 M = header[1]; N = header[2]; 3443 3444 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3445 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3446 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3447 3448 /* If global sizes are set, check if they are consistent with that given in the file */ 3449 if (sizesset) { 3450 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3451 } 3452 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); 3453 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); 3454 3455 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3456 3457 /* 3458 This code adds extra rows to make sure the number of rows is 3459 divisible by the blocksize 3460 */ 3461 Mbs = M/bs; 3462 extra_rows = bs - M + bs*Mbs; 3463 if (extra_rows == bs) extra_rows = 0; 3464 else Mbs++; 3465 if (extra_rows && !rank) { 3466 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3467 } 3468 3469 /* determine ownership of all rows */ 3470 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3471 mbs = Mbs/size + ((Mbs % size) > rank); 3472 m = mbs*bs; 3473 } else { /* User set */ 3474 m = newmat->rmap->n; 3475 mbs = m/bs; 3476 } 3477 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3478 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3479 3480 /* process 0 needs enough room for process with most rows */ 3481 if (!rank) { 3482 mmax = rowners[1]; 3483 for (i=2; i<=size; i++) { 3484 mmax = PetscMax(mmax,rowners[i]); 3485 } 3486 mmax*=bs; 3487 } else mmax = -1; /* unused, but compiler warns anyway */ 3488 3489 rowners[0] = 0; 3490 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3491 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3492 rstart = rowners[rank]; 3493 rend = rowners[rank+1]; 3494 3495 /* distribute row lengths to all processors */ 3496 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3497 if (!rank) { 3498 mend = m; 3499 if (size == 1) mend = mend - extra_rows; 3500 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3501 for (j=mend; j<m; j++) locrowlens[j] = 1; 3502 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3503 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3504 for (j=0; j<m; j++) { 3505 procsnz[0] += locrowlens[j]; 3506 } 3507 for (i=1; i<size; i++) { 3508 mend = browners[i+1] - browners[i]; 3509 if (i == size-1) mend = mend - extra_rows; 3510 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3511 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3512 /* calculate the number of nonzeros on each processor */ 3513 for (j=0; j<browners[i+1]-browners[i]; j++) { 3514 procsnz[i] += rowlengths[j]; 3515 } 3516 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3517 } 3518 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3519 } else { 3520 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3521 } 3522 3523 if (!rank) { 3524 /* determine max buffer needed and allocate it */ 3525 maxnz = procsnz[0]; 3526 for (i=1; i<size; i++) { 3527 maxnz = PetscMax(maxnz,procsnz[i]); 3528 } 3529 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3530 3531 /* read in my part of the matrix column indices */ 3532 nz = procsnz[0]; 3533 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3534 mycols = ibuf; 3535 if (size == 1) nz -= extra_rows; 3536 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3537 if (size == 1) { 3538 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3539 } 3540 3541 /* read in every ones (except the last) and ship off */ 3542 for (i=1; i<size-1; i++) { 3543 nz = procsnz[i]; 3544 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3545 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3546 } 3547 /* read in the stuff for the last proc */ 3548 if (size != 1) { 3549 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3550 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3551 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3552 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3553 } 3554 ierr = PetscFree(cols);CHKERRQ(ierr); 3555 } else { 3556 /* determine buffer space needed for message */ 3557 nz = 0; 3558 for (i=0; i<m; i++) { 3559 nz += locrowlens[i]; 3560 } 3561 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3562 mycols = ibuf; 3563 /* receive message of column indices*/ 3564 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3565 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3566 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3567 } 3568 3569 /* loop over local rows, determining number of off diagonal entries */ 3570 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3571 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3572 rowcount = 0; nzcount = 0; 3573 for (i=0; i<mbs; i++) { 3574 dcount = 0; 3575 odcount = 0; 3576 for (j=0; j<bs; j++) { 3577 kmax = locrowlens[rowcount]; 3578 for (k=0; k<kmax; k++) { 3579 tmp = mycols[nzcount++]/bs; 3580 if (!mask[tmp]) { 3581 mask[tmp] = 1; 3582 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3583 else masked1[dcount++] = tmp; 3584 } 3585 } 3586 rowcount++; 3587 } 3588 3589 dlens[i] = dcount; 3590 odlens[i] = odcount; 3591 3592 /* zero out the mask elements we set */ 3593 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3594 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3595 } 3596 3597 3598 if (!sizesset) { 3599 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3600 } 3601 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3602 3603 if (!rank) { 3604 ierr = PetscMalloc1((maxnz+1),&buf);CHKERRQ(ierr); 3605 /* read in my part of the matrix numerical values */ 3606 nz = procsnz[0]; 3607 vals = buf; 3608 mycols = ibuf; 3609 if (size == 1) nz -= extra_rows; 3610 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3611 if (size == 1) { 3612 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3613 } 3614 3615 /* insert into matrix */ 3616 jj = rstart*bs; 3617 for (i=0; i<m; i++) { 3618 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3619 mycols += locrowlens[i]; 3620 vals += locrowlens[i]; 3621 jj++; 3622 } 3623 /* read in other processors (except the last one) and ship out */ 3624 for (i=1; i<size-1; i++) { 3625 nz = procsnz[i]; 3626 vals = buf; 3627 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3628 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3629 } 3630 /* the last proc */ 3631 if (size != 1) { 3632 nz = procsnz[i] - extra_rows; 3633 vals = buf; 3634 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3635 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3636 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3637 } 3638 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3639 } else { 3640 /* receive numeric values */ 3641 ierr = PetscMalloc1((nz+1),&buf);CHKERRQ(ierr); 3642 3643 /* receive message of values*/ 3644 vals = buf; 3645 mycols = ibuf; 3646 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3647 3648 /* insert into matrix */ 3649 jj = rstart*bs; 3650 for (i=0; i<m; i++) { 3651 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3652 mycols += locrowlens[i]; 3653 vals += locrowlens[i]; 3654 jj++; 3655 } 3656 } 3657 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3658 ierr = PetscFree(buf);CHKERRQ(ierr); 3659 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3660 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3661 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3662 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3663 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3664 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3665 PetscFunctionReturn(0); 3666 } 3667 3668 #undef __FUNCT__ 3669 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3670 /*@ 3671 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3672 3673 Input Parameters: 3674 . mat - the matrix 3675 . fact - factor 3676 3677 Not Collective, each process can use a different factor 3678 3679 Level: advanced 3680 3681 Notes: 3682 This can also be set by the command line option: -mat_use_hash_table <fact> 3683 3684 .keywords: matrix, hashtable, factor, HT 3685 3686 .seealso: MatSetOption() 3687 @*/ 3688 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3689 { 3690 PetscErrorCode ierr; 3691 3692 PetscFunctionBegin; 3693 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3694 PetscFunctionReturn(0); 3695 } 3696 3697 #undef __FUNCT__ 3698 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3699 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3700 { 3701 Mat_MPIBAIJ *baij; 3702 3703 PetscFunctionBegin; 3704 baij = (Mat_MPIBAIJ*)mat->data; 3705 baij->ht_fact = fact; 3706 PetscFunctionReturn(0); 3707 } 3708 3709 #undef __FUNCT__ 3710 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3711 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3712 { 3713 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3714 3715 PetscFunctionBegin; 3716 if (Ad) *Ad = a->A; 3717 if (Ao) *Ao = a->B; 3718 if (colmap) *colmap = a->garray; 3719 PetscFunctionReturn(0); 3720 } 3721 3722 /* 3723 Special version for direct calls from Fortran (to eliminate two function call overheads 3724 */ 3725 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3726 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3727 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3728 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3729 #endif 3730 3731 #undef __FUNCT__ 3732 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3733 /*@C 3734 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3735 3736 Collective on Mat 3737 3738 Input Parameters: 3739 + mat - the matrix 3740 . min - number of input rows 3741 . im - input rows 3742 . nin - number of input columns 3743 . in - input columns 3744 . v - numerical values input 3745 - addvin - INSERT_VALUES or ADD_VALUES 3746 3747 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3748 3749 Level: advanced 3750 3751 .seealso: MatSetValuesBlocked() 3752 @*/ 3753 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3754 { 3755 /* convert input arguments to C version */ 3756 Mat mat = *matin; 3757 PetscInt m = *min, n = *nin; 3758 InsertMode addv = *addvin; 3759 3760 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3761 const MatScalar *value; 3762 MatScalar *barray = baij->barray; 3763 PetscBool roworiented = baij->roworiented; 3764 PetscErrorCode ierr; 3765 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3766 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3767 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3768 3769 PetscFunctionBegin; 3770 /* tasks normally handled by MatSetValuesBlocked() */ 3771 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3772 #if defined(PETSC_USE_DEBUG) 3773 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3774 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3775 #endif 3776 if (mat->assembled) { 3777 mat->was_assembled = PETSC_TRUE; 3778 mat->assembled = PETSC_FALSE; 3779 } 3780 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3781 3782 3783 if (!barray) { 3784 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3785 baij->barray = barray; 3786 } 3787 3788 if (roworiented) stepval = (n-1)*bs; 3789 else stepval = (m-1)*bs; 3790 3791 for (i=0; i<m; i++) { 3792 if (im[i] < 0) continue; 3793 #if defined(PETSC_USE_DEBUG) 3794 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); 3795 #endif 3796 if (im[i] >= rstart && im[i] < rend) { 3797 row = im[i] - rstart; 3798 for (j=0; j<n; j++) { 3799 /* If NumCol = 1 then a copy is not required */ 3800 if ((roworiented) && (n == 1)) { 3801 barray = (MatScalar*)v + i*bs2; 3802 } else if ((!roworiented) && (m == 1)) { 3803 barray = (MatScalar*)v + j*bs2; 3804 } else { /* Here a copy is required */ 3805 if (roworiented) { 3806 value = v + i*(stepval+bs)*bs + j*bs; 3807 } else { 3808 value = v + j*(stepval+bs)*bs + i*bs; 3809 } 3810 for (ii=0; ii<bs; ii++,value+=stepval) { 3811 for (jj=0; jj<bs; jj++) { 3812 *barray++ = *value++; 3813 } 3814 } 3815 barray -=bs2; 3816 } 3817 3818 if (in[j] >= cstart && in[j] < cend) { 3819 col = in[j] - cstart; 3820 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3821 } else if (in[j] < 0) continue; 3822 #if defined(PETSC_USE_DEBUG) 3823 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); 3824 #endif 3825 else { 3826 if (mat->was_assembled) { 3827 if (!baij->colmap) { 3828 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3829 } 3830 3831 #if defined(PETSC_USE_DEBUG) 3832 #if defined(PETSC_USE_CTABLE) 3833 { PetscInt data; 3834 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3835 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3836 } 3837 #else 3838 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3839 #endif 3840 #endif 3841 #if defined(PETSC_USE_CTABLE) 3842 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3843 col = (col - 1)/bs; 3844 #else 3845 col = (baij->colmap[in[j]] - 1)/bs; 3846 #endif 3847 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3848 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3849 col = in[j]; 3850 } 3851 } else col = in[j]; 3852 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3853 } 3854 } 3855 } else { 3856 if (!baij->donotstash) { 3857 if (roworiented) { 3858 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3859 } else { 3860 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3861 } 3862 } 3863 } 3864 } 3865 3866 /* task normally handled by MatSetValuesBlocked() */ 3867 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3868 PetscFunctionReturn(0); 3869 } 3870 3871 #undef __FUNCT__ 3872 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3873 /*@ 3874 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3875 CSR format the local rows. 3876 3877 Collective on MPI_Comm 3878 3879 Input Parameters: 3880 + comm - MPI communicator 3881 . bs - the block size, only a block size of 1 is supported 3882 . m - number of local rows (Cannot be PETSC_DECIDE) 3883 . n - This value should be the same as the local size used in creating the 3884 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3885 calculated if N is given) For square matrices n is almost always m. 3886 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3887 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3888 . i - row indices 3889 . j - column indices 3890 - a - matrix values 3891 3892 Output Parameter: 3893 . mat - the matrix 3894 3895 Level: intermediate 3896 3897 Notes: 3898 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3899 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3900 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3901 3902 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3903 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3904 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3905 with column-major ordering within blocks. 3906 3907 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3908 3909 .keywords: matrix, aij, compressed row, sparse, parallel 3910 3911 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3912 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3913 @*/ 3914 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) 3915 { 3916 PetscErrorCode ierr; 3917 3918 PetscFunctionBegin; 3919 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3920 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3921 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3922 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3923 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3924 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3925 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3926 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3927 PetscFunctionReturn(0); 3928 } 3929