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 const char *matname; 993 994 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 995 /* Perhaps this should be the type of mat? */ 996 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 997 if (!rank) { 998 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 999 } else { 1000 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1001 } 1002 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1003 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1004 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1005 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1006 1007 /* copy over the A part */ 1008 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1009 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1010 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1011 1012 for (i=0; i<mbs; i++) { 1013 rvals[0] = bs*(baij->rstartbs + i); 1014 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1015 for (j=ai[i]; j<ai[i+1]; j++) { 1016 col = (baij->cstartbs+aj[j])*bs; 1017 for (k=0; k<bs; k++) { 1018 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1019 col++; a += bs; 1020 } 1021 } 1022 } 1023 /* copy over the B part */ 1024 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1025 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1026 for (i=0; i<mbs; i++) { 1027 rvals[0] = bs*(baij->rstartbs + i); 1028 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1029 for (j=ai[i]; j<ai[i+1]; j++) { 1030 col = baij->garray[aj[j]]*bs; 1031 for (k=0; k<bs; k++) { 1032 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1033 col++; a += bs; 1034 } 1035 } 1036 } 1037 ierr = PetscFree(rvals);CHKERRQ(ierr); 1038 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1039 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1040 /* 1041 Everyone has to call to draw the matrix since the graphics waits are 1042 synchronized across all processors that share the PetscDraw object 1043 */ 1044 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1045 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1046 if (!rank) { 1047 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1048 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1049 } 1050 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1051 ierr = MatDestroy(&A);CHKERRQ(ierr); 1052 } 1053 PetscFunctionReturn(0); 1054 } 1055 1056 #undef __FUNCT__ 1057 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1058 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1059 { 1060 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1061 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1062 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1063 PetscErrorCode ierr; 1064 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1065 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1066 int fd; 1067 PetscScalar *column_values; 1068 FILE *file; 1069 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1070 PetscInt message_count,flowcontrolcount; 1071 1072 PetscFunctionBegin; 1073 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1074 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1075 nz = bs2*(A->nz + B->nz); 1076 rlen = mat->rmap->n; 1077 if (!rank) { 1078 header[0] = MAT_FILE_CLASSID; 1079 header[1] = mat->rmap->N; 1080 header[2] = mat->cmap->N; 1081 1082 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1083 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1084 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1085 /* get largest number of rows any processor has */ 1086 range = mat->rmap->range; 1087 for (i=1; i<size; i++) { 1088 rlen = PetscMax(rlen,range[i+1] - range[i]); 1089 } 1090 } else { 1091 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1092 } 1093 1094 ierr = PetscMalloc1((rlen/bs),&crow_lens);CHKERRQ(ierr); 1095 /* compute lengths of each row */ 1096 for (i=0; i<a->mbs; i++) { 1097 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1098 } 1099 /* store the row lengths to the file */ 1100 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1101 if (!rank) { 1102 MPI_Status status; 1103 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1104 rlen = (range[1] - range[0])/bs; 1105 for (i=0; i<rlen; i++) { 1106 for (j=0; j<bs; j++) { 1107 row_lens[i*bs+j] = bs*crow_lens[i]; 1108 } 1109 } 1110 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1111 for (i=1; i<size; i++) { 1112 rlen = (range[i+1] - range[i])/bs; 1113 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1114 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1115 for (k=0; k<rlen; k++) { 1116 for (j=0; j<bs; j++) { 1117 row_lens[k*bs+j] = bs*crow_lens[k]; 1118 } 1119 } 1120 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1121 } 1122 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1123 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1124 } else { 1125 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1126 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1127 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1128 } 1129 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1130 1131 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1132 information needed to make it for each row from a block row. This does require more communication but still not more than 1133 the communication needed for the nonzero values */ 1134 nzmax = nz; /* space a largest processor needs */ 1135 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1136 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1137 cnt = 0; 1138 for (i=0; i<a->mbs; i++) { 1139 pcnt = cnt; 1140 for (j=B->i[i]; j<B->i[i+1]; j++) { 1141 if ((col = garray[B->j[j]]) > cstart) break; 1142 for (l=0; l<bs; l++) { 1143 column_indices[cnt++] = bs*col+l; 1144 } 1145 } 1146 for (k=A->i[i]; k<A->i[i+1]; k++) { 1147 for (l=0; l<bs; l++) { 1148 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1149 } 1150 } 1151 for (; j<B->i[i+1]; j++) { 1152 for (l=0; l<bs; l++) { 1153 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1154 } 1155 } 1156 len = cnt - pcnt; 1157 for (k=1; k<bs; k++) { 1158 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1159 cnt += len; 1160 } 1161 } 1162 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1163 1164 /* store the columns to the file */ 1165 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1166 if (!rank) { 1167 MPI_Status status; 1168 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1169 for (i=1; i<size; i++) { 1170 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1171 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1172 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1173 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1174 } 1175 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1176 } else { 1177 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1178 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1179 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1180 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1181 } 1182 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1183 1184 /* load up the numerical values */ 1185 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1186 cnt = 0; 1187 for (i=0; i<a->mbs; i++) { 1188 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1189 for (j=B->i[i]; j<B->i[i+1]; j++) { 1190 if (garray[B->j[j]] > cstart) break; 1191 for (l=0; l<bs; l++) { 1192 for (ll=0; ll<bs; ll++) { 1193 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1194 } 1195 } 1196 cnt += bs; 1197 } 1198 for (k=A->i[i]; k<A->i[i+1]; k++) { 1199 for (l=0; l<bs; l++) { 1200 for (ll=0; ll<bs; ll++) { 1201 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1202 } 1203 } 1204 cnt += bs; 1205 } 1206 for (; j<B->i[i+1]; j++) { 1207 for (l=0; l<bs; l++) { 1208 for (ll=0; ll<bs; ll++) { 1209 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1210 } 1211 } 1212 cnt += bs; 1213 } 1214 cnt += (bs-1)*rlen; 1215 } 1216 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1217 1218 /* store the column values to the file */ 1219 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1220 if (!rank) { 1221 MPI_Status status; 1222 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1223 for (i=1; i<size; i++) { 1224 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1225 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1226 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1227 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1228 } 1229 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1230 } else { 1231 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1232 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1233 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1234 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1235 } 1236 ierr = PetscFree(column_values);CHKERRQ(ierr); 1237 1238 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1239 if (file) { 1240 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1241 } 1242 PetscFunctionReturn(0); 1243 } 1244 1245 #undef __FUNCT__ 1246 #define __FUNCT__ "MatView_MPIBAIJ" 1247 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1248 { 1249 PetscErrorCode ierr; 1250 PetscBool iascii,isdraw,issocket,isbinary; 1251 1252 PetscFunctionBegin; 1253 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1254 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1255 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1256 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1257 if (iascii || isdraw || issocket) { 1258 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1259 } else if (isbinary) { 1260 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1261 } 1262 PetscFunctionReturn(0); 1263 } 1264 1265 #undef __FUNCT__ 1266 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1267 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1268 { 1269 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1270 PetscErrorCode ierr; 1271 1272 PetscFunctionBegin; 1273 #if defined(PETSC_USE_LOG) 1274 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1275 #endif 1276 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1277 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1278 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1279 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1280 #if defined(PETSC_USE_CTABLE) 1281 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1282 #else 1283 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1284 #endif 1285 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1286 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1287 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1288 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1289 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1290 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1291 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1292 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1293 1294 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatMult_MPIBAIJ" 1309 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1310 { 1311 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1312 PetscErrorCode ierr; 1313 PetscInt nt; 1314 1315 PetscFunctionBegin; 1316 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1317 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1318 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1319 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1320 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1321 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1322 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1323 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1324 PetscFunctionReturn(0); 1325 } 1326 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1329 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1330 { 1331 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1332 PetscErrorCode ierr; 1333 1334 PetscFunctionBegin; 1335 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1336 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1337 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1338 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1339 PetscFunctionReturn(0); 1340 } 1341 1342 #undef __FUNCT__ 1343 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1344 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1345 { 1346 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1347 PetscErrorCode ierr; 1348 PetscBool merged; 1349 1350 PetscFunctionBegin; 1351 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1352 /* do nondiagonal part */ 1353 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1354 if (!merged) { 1355 /* send it on its way */ 1356 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1357 /* do local part */ 1358 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1359 /* receive remote parts: note this assumes the values are not actually */ 1360 /* inserted in yy until the next line */ 1361 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1362 } else { 1363 /* do local part */ 1364 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1365 /* send it on its way */ 1366 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1367 /* values actually were received in the Begin() but we need to call this nop */ 1368 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1369 } 1370 PetscFunctionReturn(0); 1371 } 1372 1373 #undef __FUNCT__ 1374 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1375 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1376 { 1377 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1378 PetscErrorCode ierr; 1379 1380 PetscFunctionBegin; 1381 /* do nondiagonal part */ 1382 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1383 /* send it on its way */ 1384 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1385 /* do local part */ 1386 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1387 /* receive remote parts: note this assumes the values are not actually */ 1388 /* inserted in yy until the next line, which is true for my implementation*/ 1389 /* but is not perhaps always true. */ 1390 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /* 1395 This only works correctly for square matrices where the subblock A->A is the 1396 diagonal block 1397 */ 1398 #undef __FUNCT__ 1399 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1400 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1401 { 1402 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1403 PetscErrorCode ierr; 1404 1405 PetscFunctionBegin; 1406 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1407 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1408 PetscFunctionReturn(0); 1409 } 1410 1411 #undef __FUNCT__ 1412 #define __FUNCT__ "MatScale_MPIBAIJ" 1413 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1414 { 1415 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1416 PetscErrorCode ierr; 1417 1418 PetscFunctionBegin; 1419 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1420 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1421 PetscFunctionReturn(0); 1422 } 1423 1424 #undef __FUNCT__ 1425 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1426 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1427 { 1428 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1429 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1430 PetscErrorCode ierr; 1431 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1432 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1433 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1434 1435 PetscFunctionBegin; 1436 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1437 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1438 mat->getrowactive = PETSC_TRUE; 1439 1440 if (!mat->rowvalues && (idx || v)) { 1441 /* 1442 allocate enough space to hold information from the longest row. 1443 */ 1444 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1445 PetscInt max = 1,mbs = mat->mbs,tmp; 1446 for (i=0; i<mbs; i++) { 1447 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1448 if (max < tmp) max = tmp; 1449 } 1450 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1451 } 1452 lrow = row - brstart; 1453 1454 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1455 if (!v) {pvA = 0; pvB = 0;} 1456 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1457 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1458 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1459 nztot = nzA + nzB; 1460 1461 cmap = mat->garray; 1462 if (v || idx) { 1463 if (nztot) { 1464 /* Sort by increasing column numbers, assuming A and B already sorted */ 1465 PetscInt imark = -1; 1466 if (v) { 1467 *v = v_p = mat->rowvalues; 1468 for (i=0; i<nzB; i++) { 1469 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1470 else break; 1471 } 1472 imark = i; 1473 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1474 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1475 } 1476 if (idx) { 1477 *idx = idx_p = mat->rowindices; 1478 if (imark > -1) { 1479 for (i=0; i<imark; i++) { 1480 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1481 } 1482 } else { 1483 for (i=0; i<nzB; i++) { 1484 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1485 else break; 1486 } 1487 imark = i; 1488 } 1489 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1490 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1491 } 1492 } else { 1493 if (idx) *idx = 0; 1494 if (v) *v = 0; 1495 } 1496 } 1497 *nz = nztot; 1498 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1499 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1500 PetscFunctionReturn(0); 1501 } 1502 1503 #undef __FUNCT__ 1504 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1505 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1506 { 1507 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1508 1509 PetscFunctionBegin; 1510 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1511 baij->getrowactive = PETSC_FALSE; 1512 PetscFunctionReturn(0); 1513 } 1514 1515 #undef __FUNCT__ 1516 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1517 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1518 { 1519 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1520 PetscErrorCode ierr; 1521 1522 PetscFunctionBegin; 1523 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1524 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1525 PetscFunctionReturn(0); 1526 } 1527 1528 #undef __FUNCT__ 1529 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1530 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1531 { 1532 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1533 Mat A = a->A,B = a->B; 1534 PetscErrorCode ierr; 1535 PetscReal isend[5],irecv[5]; 1536 1537 PetscFunctionBegin; 1538 info->block_size = (PetscReal)matin->rmap->bs; 1539 1540 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1541 1542 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1543 isend[3] = info->memory; isend[4] = info->mallocs; 1544 1545 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1546 1547 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1548 isend[3] += info->memory; isend[4] += info->mallocs; 1549 1550 if (flag == MAT_LOCAL) { 1551 info->nz_used = isend[0]; 1552 info->nz_allocated = isend[1]; 1553 info->nz_unneeded = isend[2]; 1554 info->memory = isend[3]; 1555 info->mallocs = isend[4]; 1556 } else if (flag == MAT_GLOBAL_MAX) { 1557 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1558 1559 info->nz_used = irecv[0]; 1560 info->nz_allocated = irecv[1]; 1561 info->nz_unneeded = irecv[2]; 1562 info->memory = irecv[3]; 1563 info->mallocs = irecv[4]; 1564 } else if (flag == MAT_GLOBAL_SUM) { 1565 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1566 1567 info->nz_used = irecv[0]; 1568 info->nz_allocated = irecv[1]; 1569 info->nz_unneeded = irecv[2]; 1570 info->memory = irecv[3]; 1571 info->mallocs = irecv[4]; 1572 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1573 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1574 info->fill_ratio_needed = 0; 1575 info->factor_mallocs = 0; 1576 PetscFunctionReturn(0); 1577 } 1578 1579 #undef __FUNCT__ 1580 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1581 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1582 { 1583 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1584 PetscErrorCode ierr; 1585 1586 PetscFunctionBegin; 1587 switch (op) { 1588 case MAT_NEW_NONZERO_LOCATIONS: 1589 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1590 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1591 case MAT_KEEP_NONZERO_PATTERN: 1592 case MAT_NEW_NONZERO_LOCATION_ERR: 1593 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1594 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1595 break; 1596 case MAT_ROW_ORIENTED: 1597 a->roworiented = flg; 1598 1599 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1600 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1601 break; 1602 case MAT_NEW_DIAGONALS: 1603 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1604 break; 1605 case MAT_IGNORE_OFF_PROC_ENTRIES: 1606 a->donotstash = flg; 1607 break; 1608 case MAT_USE_HASH_TABLE: 1609 a->ht_flag = flg; 1610 break; 1611 case MAT_SYMMETRIC: 1612 case MAT_STRUCTURALLY_SYMMETRIC: 1613 case MAT_HERMITIAN: 1614 case MAT_SYMMETRY_ETERNAL: 1615 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1616 break; 1617 default: 1618 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1619 } 1620 PetscFunctionReturn(0); 1621 } 1622 1623 #undef __FUNCT__ 1624 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1625 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1626 { 1627 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1628 Mat_SeqBAIJ *Aloc; 1629 Mat B; 1630 PetscErrorCode ierr; 1631 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1632 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1633 MatScalar *a; 1634 1635 PetscFunctionBegin; 1636 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1637 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1638 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1639 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1640 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1641 /* Do not know preallocation information, but must set block size */ 1642 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1643 } else { 1644 B = *matout; 1645 } 1646 1647 /* copy over the A part */ 1648 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1649 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1650 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1651 1652 for (i=0; i<mbs; i++) { 1653 rvals[0] = bs*(baij->rstartbs + i); 1654 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1655 for (j=ai[i]; j<ai[i+1]; j++) { 1656 col = (baij->cstartbs+aj[j])*bs; 1657 for (k=0; k<bs; k++) { 1658 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1659 1660 col++; a += bs; 1661 } 1662 } 1663 } 1664 /* copy over the B part */ 1665 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1666 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1667 for (i=0; i<mbs; i++) { 1668 rvals[0] = bs*(baij->rstartbs + i); 1669 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1670 for (j=ai[i]; j<ai[i+1]; j++) { 1671 col = baij->garray[aj[j]]*bs; 1672 for (k=0; k<bs; k++) { 1673 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1674 col++; 1675 a += bs; 1676 } 1677 } 1678 } 1679 ierr = PetscFree(rvals);CHKERRQ(ierr); 1680 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1681 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1682 1683 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1684 else { 1685 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1686 } 1687 PetscFunctionReturn(0); 1688 } 1689 1690 #undef __FUNCT__ 1691 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1692 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1693 { 1694 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1695 Mat a = baij->A,b = baij->B; 1696 PetscErrorCode ierr; 1697 PetscInt s1,s2,s3; 1698 1699 PetscFunctionBegin; 1700 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1701 if (rr) { 1702 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1703 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1704 /* Overlap communication with computation. */ 1705 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1706 } 1707 if (ll) { 1708 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1709 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1710 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1711 } 1712 /* scale the diagonal block */ 1713 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1714 1715 if (rr) { 1716 /* Do a scatter end and then right scale the off-diagonal block */ 1717 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1718 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1719 } 1720 PetscFunctionReturn(0); 1721 } 1722 1723 #undef __FUNCT__ 1724 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1725 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1726 { 1727 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1728 PetscInt *owners = A->rmap->range; 1729 PetscInt n = A->rmap->n; 1730 PetscSF sf; 1731 PetscInt *lrows; 1732 PetscSFNode *rrows; 1733 PetscInt r, p = 0, len = 0; 1734 PetscErrorCode ierr; 1735 1736 PetscFunctionBegin; 1737 /* Create SF where leaves are input rows and roots are owned rows */ 1738 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1739 for (r = 0; r < n; ++r) lrows[r] = -1; 1740 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 1741 for (r = 0; r < N; ++r) { 1742 const PetscInt idx = rows[r]; 1743 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); 1744 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1745 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1746 } 1747 if (A->nooffproczerorows) { 1748 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); 1749 lrows[len++] = idx - owners[p]; 1750 } else { 1751 rrows[r].rank = p; 1752 rrows[r].index = rows[r] - owners[p]; 1753 } 1754 } 1755 if (!A->nooffproczerorows) { 1756 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1757 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1758 /* Collect flags for rows to be zeroed */ 1759 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1760 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1761 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1762 /* Compress and put in row numbers */ 1763 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1764 } 1765 /* fix right hand side if needed */ 1766 if (x && b) { 1767 const PetscScalar *xx; 1768 PetscScalar *bb; 1769 1770 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1771 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1772 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1773 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1774 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1775 } 1776 1777 /* actually zap the local rows */ 1778 /* 1779 Zero the required rows. If the "diagonal block" of the matrix 1780 is square and the user wishes to set the diagonal we use separate 1781 code so that MatSetValues() is not called for each diagonal allocating 1782 new memory, thus calling lots of mallocs and slowing things down. 1783 1784 */ 1785 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1786 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1787 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1788 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1789 } else if (diag != 0.0) { 1790 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1791 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\ 1792 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1793 for (r = 0; r < len; ++r) { 1794 const PetscInt row = lrows[r] + A->rmap->rstart; 1795 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1796 } 1797 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1798 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1799 } else { 1800 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1801 } 1802 ierr = PetscFree(lrows);CHKERRQ(ierr); 1803 1804 /* only change matrix nonzero state if pattern was allowed to be changed */ 1805 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1806 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1807 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1808 } 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1814 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1815 { 1816 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1817 PetscErrorCode ierr; 1818 PetscMPIInt n = A->rmap->n; 1819 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1820 PetscInt *lrows,*owners = A->rmap->range; 1821 PetscSFNode *rrows; 1822 PetscSF sf; 1823 const PetscScalar *xx; 1824 PetscScalar *bb,*mask; 1825 Vec xmask,lmask; 1826 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1827 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1828 PetscScalar *aa; 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 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); 1838 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1839 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1840 } 1841 rrows[r].rank = p; 1842 rrows[r].index = rows[r] - owners[p]; 1843 } 1844 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1845 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1846 /* Collect flags for rows to be zeroed */ 1847 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1848 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1849 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1850 /* Compress and put in row numbers */ 1851 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1852 /* zero diagonal part of matrix */ 1853 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1854 /* handle off diagonal part of matrix */ 1855 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1856 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1857 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1858 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1859 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1860 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1861 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1862 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1863 if (x) { 1864 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1865 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1866 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1867 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1868 } 1869 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1870 /* remove zeroed rows of off diagonal matrix */ 1871 for (i = 0; i < len; ++i) { 1872 row = lrows[i]; 1873 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1874 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1875 for (k = 0; k < count; ++k) { 1876 aa[0] = 0.0; 1877 aa += bs; 1878 } 1879 } 1880 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1881 for (i = 0; i < l->B->rmap->N; ++i) { 1882 row = i/bs; 1883 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1884 for (k = 0; k < bs; ++k) { 1885 col = bs*baij->j[j] + k; 1886 if (PetscAbsScalar(mask[col])) { 1887 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1888 if (b) bb[i] -= aa[0]*xx[col]; 1889 aa[0] = 0.0; 1890 } 1891 } 1892 } 1893 } 1894 if (x) { 1895 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1896 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1897 } 1898 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1899 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1900 ierr = PetscFree(lrows);CHKERRQ(ierr); 1901 1902 /* only change matrix nonzero state if pattern was allowed to be changed */ 1903 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1904 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1905 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1906 } 1907 PetscFunctionReturn(0); 1908 } 1909 1910 #undef __FUNCT__ 1911 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1912 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1913 { 1914 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1915 PetscErrorCode ierr; 1916 1917 PetscFunctionBegin; 1918 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1919 PetscFunctionReturn(0); 1920 } 1921 1922 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1923 1924 #undef __FUNCT__ 1925 #define __FUNCT__ "MatEqual_MPIBAIJ" 1926 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1927 { 1928 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1929 Mat a,b,c,d; 1930 PetscBool flg; 1931 PetscErrorCode ierr; 1932 1933 PetscFunctionBegin; 1934 a = matA->A; b = matA->B; 1935 c = matB->A; d = matB->B; 1936 1937 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1938 if (flg) { 1939 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1940 } 1941 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1942 PetscFunctionReturn(0); 1943 } 1944 1945 #undef __FUNCT__ 1946 #define __FUNCT__ "MatCopy_MPIBAIJ" 1947 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1948 { 1949 PetscErrorCode ierr; 1950 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1951 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1952 1953 PetscFunctionBegin; 1954 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1955 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1956 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1957 } else { 1958 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1959 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1960 } 1961 PetscFunctionReturn(0); 1962 } 1963 1964 #undef __FUNCT__ 1965 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1966 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1967 { 1968 PetscErrorCode ierr; 1969 1970 PetscFunctionBegin; 1971 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1972 PetscFunctionReturn(0); 1973 } 1974 1975 #undef __FUNCT__ 1976 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 1977 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1978 { 1979 PetscErrorCode ierr; 1980 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1981 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1982 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1983 1984 PetscFunctionBegin; 1985 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1986 PetscFunctionReturn(0); 1987 } 1988 1989 #undef __FUNCT__ 1990 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1991 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1992 { 1993 PetscErrorCode ierr; 1994 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1995 PetscBLASInt bnz,one=1; 1996 Mat_SeqBAIJ *x,*y; 1997 1998 PetscFunctionBegin; 1999 if (str == SAME_NONZERO_PATTERN) { 2000 PetscScalar alpha = a; 2001 x = (Mat_SeqBAIJ*)xx->A->data; 2002 y = (Mat_SeqBAIJ*)yy->A->data; 2003 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2004 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2005 x = (Mat_SeqBAIJ*)xx->B->data; 2006 y = (Mat_SeqBAIJ*)yy->B->data; 2007 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2008 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2009 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2010 } else { 2011 Mat B; 2012 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2013 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2014 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2015 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2016 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2017 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2018 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2019 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2020 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2021 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2022 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2023 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2024 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2025 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2026 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2027 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2028 } 2029 PetscFunctionReturn(0); 2030 } 2031 2032 #undef __FUNCT__ 2033 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2034 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2035 { 2036 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2037 PetscErrorCode ierr; 2038 2039 PetscFunctionBegin; 2040 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2041 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2042 PetscFunctionReturn(0); 2043 } 2044 2045 #undef __FUNCT__ 2046 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2047 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2048 { 2049 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2050 PetscErrorCode ierr; 2051 2052 PetscFunctionBegin; 2053 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2054 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2055 PetscFunctionReturn(0); 2056 } 2057 2058 #undef __FUNCT__ 2059 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2060 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2061 { 2062 PetscErrorCode ierr; 2063 IS iscol_local; 2064 PetscInt csize; 2065 2066 PetscFunctionBegin; 2067 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2068 if (call == MAT_REUSE_MATRIX) { 2069 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2070 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2071 } else { 2072 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2073 } 2074 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2075 if (call == MAT_INITIAL_MATRIX) { 2076 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2077 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2078 } 2079 PetscFunctionReturn(0); 2080 } 2081 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2082 #undef __FUNCT__ 2083 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2084 /* 2085 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2086 in local and then by concatenating the local matrices the end result. 2087 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2088 */ 2089 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2090 { 2091 PetscErrorCode ierr; 2092 PetscMPIInt rank,size; 2093 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2094 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2095 Mat M,Mreuse; 2096 MatScalar *vwork,*aa; 2097 MPI_Comm comm; 2098 IS isrow_new, iscol_new; 2099 PetscBool idflag,allrows, allcols; 2100 Mat_SeqBAIJ *aij; 2101 2102 PetscFunctionBegin; 2103 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2104 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2105 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2106 /* The compression and expansion should be avoided. Doesn't point 2107 out errors, might change the indices, hence buggey */ 2108 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2109 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2110 2111 /* Check for special case: each processor gets entire matrix columns */ 2112 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2113 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2114 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2115 else allcols = PETSC_FALSE; 2116 2117 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2118 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2119 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2120 else allrows = PETSC_FALSE; 2121 2122 if (call == MAT_REUSE_MATRIX) { 2123 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2124 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2125 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2126 } else { 2127 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2128 } 2129 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2130 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2131 /* 2132 m - number of local rows 2133 n - number of columns (same on all processors) 2134 rstart - first row in new global matrix generated 2135 */ 2136 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2137 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2138 m = m/bs; 2139 n = n/bs; 2140 2141 if (call == MAT_INITIAL_MATRIX) { 2142 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2143 ii = aij->i; 2144 jj = aij->j; 2145 2146 /* 2147 Determine the number of non-zeros in the diagonal and off-diagonal 2148 portions of the matrix in order to do correct preallocation 2149 */ 2150 2151 /* first get start and end of "diagonal" columns */ 2152 if (csize == PETSC_DECIDE) { 2153 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2154 if (mglobal == n*bs) { /* square matrix */ 2155 nlocal = m; 2156 } else { 2157 nlocal = n/size + ((n % size) > rank); 2158 } 2159 } else { 2160 nlocal = csize/bs; 2161 } 2162 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2163 rstart = rend - nlocal; 2164 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); 2165 2166 /* next, compute all the lengths */ 2167 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2168 for (i=0; i<m; i++) { 2169 jend = ii[i+1] - ii[i]; 2170 olen = 0; 2171 dlen = 0; 2172 for (j=0; j<jend; j++) { 2173 if (*jj < rstart || *jj >= rend) olen++; 2174 else dlen++; 2175 jj++; 2176 } 2177 olens[i] = olen; 2178 dlens[i] = dlen; 2179 } 2180 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2181 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2182 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2183 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2184 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2185 } else { 2186 PetscInt ml,nl; 2187 2188 M = *newmat; 2189 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2190 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2191 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2192 /* 2193 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2194 rather than the slower MatSetValues(). 2195 */ 2196 M->was_assembled = PETSC_TRUE; 2197 M->assembled = PETSC_FALSE; 2198 } 2199 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2200 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2201 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2202 ii = aij->i; 2203 jj = aij->j; 2204 aa = aij->a; 2205 for (i=0; i<m; i++) { 2206 row = rstart/bs + i; 2207 nz = ii[i+1] - ii[i]; 2208 cwork = jj; jj += nz; 2209 vwork = aa; aa += nz*bs*bs; 2210 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2211 } 2212 2213 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2214 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2215 *newmat = M; 2216 2217 /* save submatrix used in processor for next request */ 2218 if (call == MAT_INITIAL_MATRIX) { 2219 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2220 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2221 } 2222 PetscFunctionReturn(0); 2223 } 2224 2225 #undef __FUNCT__ 2226 #define __FUNCT__ "MatPermute_MPIBAIJ" 2227 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2228 { 2229 MPI_Comm comm,pcomm; 2230 PetscInt clocal_size,nrows; 2231 const PetscInt *rows; 2232 PetscMPIInt size; 2233 IS crowp,lcolp; 2234 PetscErrorCode ierr; 2235 2236 PetscFunctionBegin; 2237 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2238 /* make a collective version of 'rowp' */ 2239 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2240 if (pcomm==comm) { 2241 crowp = rowp; 2242 } else { 2243 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2244 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2245 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2246 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2247 } 2248 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2249 /* make a local version of 'colp' */ 2250 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2251 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2252 if (size==1) { 2253 lcolp = colp; 2254 } else { 2255 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2256 } 2257 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2258 /* now we just get the submatrix */ 2259 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2260 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2261 /* clean up */ 2262 if (pcomm!=comm) { 2263 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2264 } 2265 if (size>1) { 2266 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2267 } 2268 PetscFunctionReturn(0); 2269 } 2270 2271 #undef __FUNCT__ 2272 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2273 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2274 { 2275 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2276 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2277 2278 PetscFunctionBegin; 2279 if (nghosts) *nghosts = B->nbs; 2280 if (ghosts) *ghosts = baij->garray; 2281 PetscFunctionReturn(0); 2282 } 2283 2284 #undef __FUNCT__ 2285 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2286 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2287 { 2288 Mat B; 2289 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2290 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2291 Mat_SeqAIJ *b; 2292 PetscErrorCode ierr; 2293 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2294 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2295 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2296 2297 PetscFunctionBegin; 2298 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2299 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2300 2301 /* ---------------------------------------------------------------- 2302 Tell every processor the number of nonzeros per row 2303 */ 2304 ierr = PetscMalloc1((A->rmap->N/bs),&lens);CHKERRQ(ierr); 2305 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2306 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]; 2307 } 2308 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2309 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2310 displs = recvcounts + size; 2311 for (i=0; i<size; i++) { 2312 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2313 displs[i] = A->rmap->range[i]/bs; 2314 } 2315 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2316 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2317 #else 2318 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2319 #endif 2320 /* --------------------------------------------------------------- 2321 Create the sequential matrix of the same type as the local block diagonal 2322 */ 2323 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2324 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2325 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2326 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2327 b = (Mat_SeqAIJ*)B->data; 2328 2329 /*-------------------------------------------------------------------- 2330 Copy my part of matrix column indices over 2331 */ 2332 sendcount = ad->nz + bd->nz; 2333 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2334 a_jsendbuf = ad->j; 2335 b_jsendbuf = bd->j; 2336 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2337 cnt = 0; 2338 for (i=0; i<n; i++) { 2339 2340 /* put in lower diagonal portion */ 2341 m = bd->i[i+1] - bd->i[i]; 2342 while (m > 0) { 2343 /* is it above diagonal (in bd (compressed) numbering) */ 2344 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2345 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2346 m--; 2347 } 2348 2349 /* put in diagonal portion */ 2350 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2351 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2352 } 2353 2354 /* put in upper diagonal portion */ 2355 while (m-- > 0) { 2356 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2357 } 2358 } 2359 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2360 2361 /*-------------------------------------------------------------------- 2362 Gather all column indices to all processors 2363 */ 2364 for (i=0; i<size; i++) { 2365 recvcounts[i] = 0; 2366 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2367 recvcounts[i] += lens[j]; 2368 } 2369 } 2370 displs[0] = 0; 2371 for (i=1; i<size; i++) { 2372 displs[i] = displs[i-1] + recvcounts[i-1]; 2373 } 2374 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2375 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2376 #else 2377 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2378 #endif 2379 /*-------------------------------------------------------------------- 2380 Assemble the matrix into useable form (note numerical values not yet set) 2381 */ 2382 /* set the b->ilen (length of each row) values */ 2383 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2384 /* set the b->i indices */ 2385 b->i[0] = 0; 2386 for (i=1; i<=A->rmap->N/bs; i++) { 2387 b->i[i] = b->i[i-1] + lens[i-1]; 2388 } 2389 ierr = PetscFree(lens);CHKERRQ(ierr); 2390 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2391 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2392 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2393 2394 if (A->symmetric) { 2395 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2396 } else if (A->hermitian) { 2397 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2398 } else if (A->structurally_symmetric) { 2399 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2400 } 2401 *newmat = B; 2402 PetscFunctionReturn(0); 2403 } 2404 2405 #undef __FUNCT__ 2406 #define __FUNCT__ "MatSOR_MPIBAIJ" 2407 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2408 { 2409 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2410 PetscErrorCode ierr; 2411 Vec bb1 = 0; 2412 2413 PetscFunctionBegin; 2414 if (flag == SOR_APPLY_UPPER) { 2415 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2416 PetscFunctionReturn(0); 2417 } 2418 2419 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2420 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2421 } 2422 2423 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2424 if (flag & SOR_ZERO_INITIAL_GUESS) { 2425 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2426 its--; 2427 } 2428 2429 while (its--) { 2430 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2431 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2432 2433 /* update rhs: bb1 = bb - B*x */ 2434 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2435 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2436 2437 /* local sweep */ 2438 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2439 } 2440 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2441 if (flag & SOR_ZERO_INITIAL_GUESS) { 2442 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2443 its--; 2444 } 2445 while (its--) { 2446 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2447 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2448 2449 /* update rhs: bb1 = bb - B*x */ 2450 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2451 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2452 2453 /* local sweep */ 2454 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2455 } 2456 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2457 if (flag & SOR_ZERO_INITIAL_GUESS) { 2458 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2459 its--; 2460 } 2461 while (its--) { 2462 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2463 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2464 2465 /* update rhs: bb1 = bb - B*x */ 2466 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2467 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2468 2469 /* local sweep */ 2470 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2471 } 2472 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2473 2474 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2475 PetscFunctionReturn(0); 2476 } 2477 2478 #undef __FUNCT__ 2479 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2480 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2481 { 2482 PetscErrorCode ierr; 2483 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2484 PetscInt N,i,*garray = aij->garray; 2485 PetscInt ib,jb,bs = A->rmap->bs; 2486 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2487 MatScalar *a_val = a_aij->a; 2488 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2489 MatScalar *b_val = b_aij->a; 2490 PetscReal *work; 2491 2492 PetscFunctionBegin; 2493 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2494 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2495 if (type == NORM_2) { 2496 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2497 for (jb=0; jb<bs; jb++) { 2498 for (ib=0; ib<bs; ib++) { 2499 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2500 a_val++; 2501 } 2502 } 2503 } 2504 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2505 for (jb=0; jb<bs; jb++) { 2506 for (ib=0; ib<bs; ib++) { 2507 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2508 b_val++; 2509 } 2510 } 2511 } 2512 } else if (type == NORM_1) { 2513 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2514 for (jb=0; jb<bs; jb++) { 2515 for (ib=0; ib<bs; ib++) { 2516 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2517 a_val++; 2518 } 2519 } 2520 } 2521 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2522 for (jb=0; jb<bs; jb++) { 2523 for (ib=0; ib<bs; ib++) { 2524 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2525 b_val++; 2526 } 2527 } 2528 } 2529 } else if (type == NORM_INFINITY) { 2530 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2531 for (jb=0; jb<bs; jb++) { 2532 for (ib=0; ib<bs; ib++) { 2533 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2534 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2535 a_val++; 2536 } 2537 } 2538 } 2539 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2540 for (jb=0; jb<bs; jb++) { 2541 for (ib=0; ib<bs; ib++) { 2542 int col = garray[b_aij->j[i]] * bs + jb; 2543 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2544 b_val++; 2545 } 2546 } 2547 } 2548 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2549 if (type == NORM_INFINITY) { 2550 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2551 } else { 2552 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2553 } 2554 ierr = PetscFree(work);CHKERRQ(ierr); 2555 if (type == NORM_2) { 2556 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2557 } 2558 PetscFunctionReturn(0); 2559 } 2560 2561 #undef __FUNCT__ 2562 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2563 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2564 { 2565 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2566 PetscErrorCode ierr; 2567 2568 PetscFunctionBegin; 2569 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2570 PetscFunctionReturn(0); 2571 } 2572 2573 2574 /* -------------------------------------------------------------------*/ 2575 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2576 MatGetRow_MPIBAIJ, 2577 MatRestoreRow_MPIBAIJ, 2578 MatMult_MPIBAIJ, 2579 /* 4*/ MatMultAdd_MPIBAIJ, 2580 MatMultTranspose_MPIBAIJ, 2581 MatMultTransposeAdd_MPIBAIJ, 2582 0, 2583 0, 2584 0, 2585 /*10*/ 0, 2586 0, 2587 0, 2588 MatSOR_MPIBAIJ, 2589 MatTranspose_MPIBAIJ, 2590 /*15*/ MatGetInfo_MPIBAIJ, 2591 MatEqual_MPIBAIJ, 2592 MatGetDiagonal_MPIBAIJ, 2593 MatDiagonalScale_MPIBAIJ, 2594 MatNorm_MPIBAIJ, 2595 /*20*/ MatAssemblyBegin_MPIBAIJ, 2596 MatAssemblyEnd_MPIBAIJ, 2597 MatSetOption_MPIBAIJ, 2598 MatZeroEntries_MPIBAIJ, 2599 /*24*/ MatZeroRows_MPIBAIJ, 2600 0, 2601 0, 2602 0, 2603 0, 2604 /*29*/ MatSetUp_MPIBAIJ, 2605 0, 2606 0, 2607 0, 2608 0, 2609 /*34*/ MatDuplicate_MPIBAIJ, 2610 0, 2611 0, 2612 0, 2613 0, 2614 /*39*/ MatAXPY_MPIBAIJ, 2615 MatGetSubMatrices_MPIBAIJ, 2616 MatIncreaseOverlap_MPIBAIJ, 2617 MatGetValues_MPIBAIJ, 2618 MatCopy_MPIBAIJ, 2619 /*44*/ 0, 2620 MatScale_MPIBAIJ, 2621 0, 2622 0, 2623 MatZeroRowsColumns_MPIBAIJ, 2624 /*49*/ 0, 2625 0, 2626 0, 2627 0, 2628 0, 2629 /*54*/ MatFDColoringCreate_MPIXAIJ, 2630 0, 2631 MatSetUnfactored_MPIBAIJ, 2632 MatPermute_MPIBAIJ, 2633 MatSetValuesBlocked_MPIBAIJ, 2634 /*59*/ MatGetSubMatrix_MPIBAIJ, 2635 MatDestroy_MPIBAIJ, 2636 MatView_MPIBAIJ, 2637 0, 2638 0, 2639 /*64*/ 0, 2640 0, 2641 0, 2642 0, 2643 0, 2644 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2645 0, 2646 0, 2647 0, 2648 0, 2649 /*74*/ 0, 2650 MatFDColoringApply_BAIJ, 2651 0, 2652 0, 2653 0, 2654 /*79*/ 0, 2655 0, 2656 0, 2657 0, 2658 MatLoad_MPIBAIJ, 2659 /*84*/ 0, 2660 0, 2661 0, 2662 0, 2663 0, 2664 /*89*/ 0, 2665 0, 2666 0, 2667 0, 2668 0, 2669 /*94*/ 0, 2670 0, 2671 0, 2672 0, 2673 0, 2674 /*99*/ 0, 2675 0, 2676 0, 2677 0, 2678 0, 2679 /*104*/0, 2680 MatRealPart_MPIBAIJ, 2681 MatImaginaryPart_MPIBAIJ, 2682 0, 2683 0, 2684 /*109*/0, 2685 0, 2686 0, 2687 0, 2688 0, 2689 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2690 0, 2691 MatGetGhosts_MPIBAIJ, 2692 0, 2693 0, 2694 /*119*/0, 2695 0, 2696 0, 2697 0, 2698 MatGetMultiProcBlock_MPIBAIJ, 2699 /*124*/0, 2700 MatGetColumnNorms_MPIBAIJ, 2701 MatInvertBlockDiagonal_MPIBAIJ, 2702 0, 2703 0, 2704 /*129*/ 0, 2705 0, 2706 0, 2707 0, 2708 0, 2709 /*134*/ 0, 2710 0, 2711 0, 2712 0, 2713 0, 2714 /*139*/ 0, 2715 0, 2716 0, 2717 MatFDColoringSetUp_MPIXAIJ 2718 }; 2719 2720 #undef __FUNCT__ 2721 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2722 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2723 { 2724 PetscFunctionBegin; 2725 *a = ((Mat_MPIBAIJ*)A->data)->A; 2726 PetscFunctionReturn(0); 2727 } 2728 2729 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2730 2731 #undef __FUNCT__ 2732 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2733 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2734 { 2735 PetscInt m,rstart,cstart,cend; 2736 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2737 const PetscInt *JJ =0; 2738 PetscScalar *values=0; 2739 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2740 PetscErrorCode ierr; 2741 2742 PetscFunctionBegin; 2743 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2744 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2745 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2746 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2747 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2748 m = B->rmap->n/bs; 2749 rstart = B->rmap->rstart/bs; 2750 cstart = B->cmap->rstart/bs; 2751 cend = B->cmap->rend/bs; 2752 2753 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2754 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2755 for (i=0; i<m; i++) { 2756 nz = ii[i+1] - ii[i]; 2757 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2758 nz_max = PetscMax(nz_max,nz); 2759 JJ = jj + ii[i]; 2760 for (j=0; j<nz; j++) { 2761 if (*JJ >= cstart) break; 2762 JJ++; 2763 } 2764 d = 0; 2765 for (; j<nz; j++) { 2766 if (*JJ++ >= cend) break; 2767 d++; 2768 } 2769 d_nnz[i] = d; 2770 o_nnz[i] = nz - d; 2771 } 2772 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2773 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2774 2775 values = (PetscScalar*)V; 2776 if (!values) { 2777 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2778 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2779 } 2780 for (i=0; i<m; i++) { 2781 PetscInt row = i + rstart; 2782 PetscInt ncols = ii[i+1] - ii[i]; 2783 const PetscInt *icols = jj + ii[i]; 2784 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2785 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2786 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2787 } else { /* block ordering does not match so we can only insert one block at a time. */ 2788 PetscInt j; 2789 for (j=0; j<ncols; j++) { 2790 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2791 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2792 } 2793 } 2794 } 2795 2796 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2797 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2798 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2799 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2800 PetscFunctionReturn(0); 2801 } 2802 2803 #undef __FUNCT__ 2804 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2805 /*@C 2806 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2807 (the default parallel PETSc format). 2808 2809 Collective on MPI_Comm 2810 2811 Input Parameters: 2812 + B - the matrix 2813 . bs - the block size 2814 . i - the indices into j for the start of each local row (starts with zero) 2815 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2816 - v - optional values in the matrix 2817 2818 Level: developer 2819 2820 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2821 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2822 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2823 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2824 block column and the second index is over columns within a block. 2825 2826 .keywords: matrix, aij, compressed row, sparse, parallel 2827 2828 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2829 @*/ 2830 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2831 { 2832 PetscErrorCode ierr; 2833 2834 PetscFunctionBegin; 2835 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2836 PetscValidType(B,1); 2837 PetscValidLogicalCollectiveInt(B,bs,2); 2838 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2839 PetscFunctionReturn(0); 2840 } 2841 2842 #undef __FUNCT__ 2843 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2844 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2845 { 2846 Mat_MPIBAIJ *b; 2847 PetscErrorCode ierr; 2848 PetscInt i; 2849 2850 PetscFunctionBegin; 2851 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2852 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2853 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2854 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2855 2856 if (d_nnz) { 2857 for (i=0; i<B->rmap->n/bs; i++) { 2858 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]); 2859 } 2860 } 2861 if (o_nnz) { 2862 for (i=0; i<B->rmap->n/bs; i++) { 2863 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]); 2864 } 2865 } 2866 2867 b = (Mat_MPIBAIJ*)B->data; 2868 b->bs2 = bs*bs; 2869 b->mbs = B->rmap->n/bs; 2870 b->nbs = B->cmap->n/bs; 2871 b->Mbs = B->rmap->N/bs; 2872 b->Nbs = B->cmap->N/bs; 2873 2874 for (i=0; i<=b->size; i++) { 2875 b->rangebs[i] = B->rmap->range[i]/bs; 2876 } 2877 b->rstartbs = B->rmap->rstart/bs; 2878 b->rendbs = B->rmap->rend/bs; 2879 b->cstartbs = B->cmap->rstart/bs; 2880 b->cendbs = B->cmap->rend/bs; 2881 2882 if (!B->preallocated) { 2883 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2884 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2885 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2886 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2887 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2888 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2889 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2890 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2891 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2892 } 2893 2894 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2895 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2896 B->preallocated = PETSC_TRUE; 2897 PetscFunctionReturn(0); 2898 } 2899 2900 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2901 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2902 2903 #undef __FUNCT__ 2904 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2905 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2906 { 2907 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2908 PetscErrorCode ierr; 2909 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2910 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2911 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2912 2913 PetscFunctionBegin; 2914 ierr = PetscMalloc1((M+1),&ii);CHKERRQ(ierr); 2915 ii[0] = 0; 2916 for (i=0; i<M; i++) { 2917 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]); 2918 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]); 2919 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2920 /* remove one from count of matrix has diagonal */ 2921 for (j=id[i]; j<id[i+1]; j++) { 2922 if (jd[j] == i) {ii[i+1]--;break;} 2923 } 2924 } 2925 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2926 cnt = 0; 2927 for (i=0; i<M; i++) { 2928 for (j=io[i]; j<io[i+1]; j++) { 2929 if (garray[jo[j]] > rstart) break; 2930 jj[cnt++] = garray[jo[j]]; 2931 } 2932 for (k=id[i]; k<id[i+1]; k++) { 2933 if (jd[k] != i) { 2934 jj[cnt++] = rstart + jd[k]; 2935 } 2936 } 2937 for (; j<io[i+1]; j++) { 2938 jj[cnt++] = garray[jo[j]]; 2939 } 2940 } 2941 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2942 PetscFunctionReturn(0); 2943 } 2944 2945 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2946 2947 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2948 2949 #undef __FUNCT__ 2950 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2951 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2952 { 2953 PetscErrorCode ierr; 2954 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2955 Mat B; 2956 Mat_MPIAIJ *b; 2957 2958 PetscFunctionBegin; 2959 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2960 2961 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2962 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2963 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2964 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2965 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2966 b = (Mat_MPIAIJ*) B->data; 2967 2968 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2969 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2970 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2971 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2972 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2973 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2974 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2975 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2976 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2977 if (reuse == MAT_REUSE_MATRIX) { 2978 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2979 } else { 2980 *newmat = B; 2981 } 2982 PetscFunctionReturn(0); 2983 } 2984 2985 #if defined(PETSC_HAVE_MUMPS) 2986 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2987 #endif 2988 2989 /*MC 2990 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2991 2992 Options Database Keys: 2993 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2994 . -mat_block_size <bs> - set the blocksize used to store the matrix 2995 - -mat_use_hash_table <fact> 2996 2997 Level: beginner 2998 2999 .seealso: MatCreateMPIBAIJ 3000 M*/ 3001 3002 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3003 3004 #undef __FUNCT__ 3005 #define __FUNCT__ "MatCreate_MPIBAIJ" 3006 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3007 { 3008 Mat_MPIBAIJ *b; 3009 PetscErrorCode ierr; 3010 PetscBool flg; 3011 3012 PetscFunctionBegin; 3013 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3014 B->data = (void*)b; 3015 3016 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3017 B->assembled = PETSC_FALSE; 3018 3019 B->insertmode = NOT_SET_VALUES; 3020 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3021 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3022 3023 /* build local table of row and column ownerships */ 3024 ierr = PetscMalloc1((b->size+1),&b->rangebs);CHKERRQ(ierr); 3025 3026 /* build cache for off array entries formed */ 3027 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3028 3029 b->donotstash = PETSC_FALSE; 3030 b->colmap = NULL; 3031 b->garray = NULL; 3032 b->roworiented = PETSC_TRUE; 3033 3034 /* stuff used in block assembly */ 3035 b->barray = 0; 3036 3037 /* stuff used for matrix vector multiply */ 3038 b->lvec = 0; 3039 b->Mvctx = 0; 3040 3041 /* stuff for MatGetRow() */ 3042 b->rowindices = 0; 3043 b->rowvalues = 0; 3044 b->getrowactive = PETSC_FALSE; 3045 3046 /* hash table stuff */ 3047 b->ht = 0; 3048 b->hd = 0; 3049 b->ht_size = 0; 3050 b->ht_flag = PETSC_FALSE; 3051 b->ht_fact = 0; 3052 b->ht_total_ct = 0; 3053 b->ht_insert_ct = 0; 3054 3055 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3056 b->ijonly = PETSC_FALSE; 3057 3058 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3059 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3060 if (flg) { 3061 PetscReal fact = 1.39; 3062 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3063 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3064 if (fact <= 1.0) fact = 1.39; 3065 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3066 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3067 } 3068 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3069 3070 #if defined(PETSC_HAVE_MUMPS) 3071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3072 #endif 3073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3074 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3076 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3077 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3078 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3079 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3084 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3085 PetscFunctionReturn(0); 3086 } 3087 3088 /*MC 3089 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3090 3091 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3092 and MATMPIBAIJ otherwise. 3093 3094 Options Database Keys: 3095 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3096 3097 Level: beginner 3098 3099 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3100 M*/ 3101 3102 #undef __FUNCT__ 3103 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3104 /*@C 3105 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3106 (block compressed row). For good matrix assembly performance 3107 the user should preallocate the matrix storage by setting the parameters 3108 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3109 performance can be increased by more than a factor of 50. 3110 3111 Collective on Mat 3112 3113 Input Parameters: 3114 + B - the matrix 3115 . bs - size of block 3116 . d_nz - number of block nonzeros per block row in diagonal portion of local 3117 submatrix (same for all local rows) 3118 . d_nnz - array containing the number of block nonzeros in the various block rows 3119 of the in diagonal portion of the local (possibly different for each block 3120 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3121 set it even if it is zero. 3122 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3123 submatrix (same for all local rows). 3124 - o_nnz - array containing the number of nonzeros in the various block rows of the 3125 off-diagonal portion of the local submatrix (possibly different for 3126 each block row) or NULL. 3127 3128 If the *_nnz parameter is given then the *_nz parameter is ignored 3129 3130 Options Database Keys: 3131 + -mat_block_size - size of the blocks to use 3132 - -mat_use_hash_table <fact> 3133 3134 Notes: 3135 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3136 than it must be used on all processors that share the object for that argument. 3137 3138 Storage Information: 3139 For a square global matrix we define each processor's diagonal portion 3140 to be its local rows and the corresponding columns (a square submatrix); 3141 each processor's off-diagonal portion encompasses the remainder of the 3142 local matrix (a rectangular submatrix). 3143 3144 The user can specify preallocated storage for the diagonal part of 3145 the local submatrix with either d_nz or d_nnz (not both). Set 3146 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3147 memory allocation. Likewise, specify preallocated storage for the 3148 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3149 3150 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3151 the figure below we depict these three local rows and all columns (0-11). 3152 3153 .vb 3154 0 1 2 3 4 5 6 7 8 9 10 11 3155 -------------------------- 3156 row 3 |o o o d d d o o o o o o 3157 row 4 |o o o d d d o o o o o o 3158 row 5 |o o o d d d o o o o o o 3159 -------------------------- 3160 .ve 3161 3162 Thus, any entries in the d locations are stored in the d (diagonal) 3163 submatrix, and any entries in the o locations are stored in the 3164 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3165 stored simply in the MATSEQBAIJ format for compressed row storage. 3166 3167 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3168 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3169 In general, for PDE problems in which most nonzeros are near the diagonal, 3170 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3171 or you will get TERRIBLE performance; see the users' manual chapter on 3172 matrices. 3173 3174 You can call MatGetInfo() to get information on how effective the preallocation was; 3175 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3176 You can also run with the option -info and look for messages with the string 3177 malloc in them to see if additional memory allocation was needed. 3178 3179 Level: intermediate 3180 3181 .keywords: matrix, block, aij, compressed row, sparse, parallel 3182 3183 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3184 @*/ 3185 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3186 { 3187 PetscErrorCode ierr; 3188 3189 PetscFunctionBegin; 3190 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3191 PetscValidType(B,1); 3192 PetscValidLogicalCollectiveInt(B,bs,2); 3193 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); 3194 PetscFunctionReturn(0); 3195 } 3196 3197 #undef __FUNCT__ 3198 #define __FUNCT__ "MatCreateBAIJ" 3199 /*@C 3200 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3201 (block compressed row). For good matrix assembly performance 3202 the user should preallocate the matrix storage by setting the parameters 3203 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3204 performance can be increased by more than a factor of 50. 3205 3206 Collective on MPI_Comm 3207 3208 Input Parameters: 3209 + comm - MPI communicator 3210 . bs - size of blockk 3211 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3212 This value should be the same as the local size used in creating the 3213 y vector for the matrix-vector product y = Ax. 3214 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3215 This value should be the same as the local size used in creating the 3216 x vector for the matrix-vector product y = Ax. 3217 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3218 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3219 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3220 submatrix (same for all local rows) 3221 . d_nnz - array containing the number of nonzero blocks in the various block rows 3222 of the in diagonal portion of the local (possibly different for each block 3223 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3224 and set it even if it is zero. 3225 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3226 submatrix (same for all local rows). 3227 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3228 off-diagonal portion of the local submatrix (possibly different for 3229 each block row) or NULL. 3230 3231 Output Parameter: 3232 . A - the matrix 3233 3234 Options Database Keys: 3235 + -mat_block_size - size of the blocks to use 3236 - -mat_use_hash_table <fact> 3237 3238 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3239 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3240 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3241 3242 Notes: 3243 If the *_nnz parameter is given then the *_nz parameter is ignored 3244 3245 A nonzero block is any block that as 1 or more nonzeros in it 3246 3247 The user MUST specify either the local or global matrix dimensions 3248 (possibly both). 3249 3250 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3251 than it must be used on all processors that share the object for that argument. 3252 3253 Storage Information: 3254 For a square global matrix we define each processor's diagonal portion 3255 to be its local rows and the corresponding columns (a square submatrix); 3256 each processor's off-diagonal portion encompasses the remainder of the 3257 local matrix (a rectangular submatrix). 3258 3259 The user can specify preallocated storage for the diagonal part of 3260 the local submatrix with either d_nz or d_nnz (not both). Set 3261 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3262 memory allocation. Likewise, specify preallocated storage for the 3263 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3264 3265 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3266 the figure below we depict these three local rows and all columns (0-11). 3267 3268 .vb 3269 0 1 2 3 4 5 6 7 8 9 10 11 3270 -------------------------- 3271 row 3 |o o o d d d o o o o o o 3272 row 4 |o o o d d d o o o o o o 3273 row 5 |o o o d d d o o o o o o 3274 -------------------------- 3275 .ve 3276 3277 Thus, any entries in the d locations are stored in the d (diagonal) 3278 submatrix, and any entries in the o locations are stored in the 3279 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3280 stored simply in the MATSEQBAIJ format for compressed row storage. 3281 3282 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3283 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3284 In general, for PDE problems in which most nonzeros are near the diagonal, 3285 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3286 or you will get TERRIBLE performance; see the users' manual chapter on 3287 matrices. 3288 3289 Level: intermediate 3290 3291 .keywords: matrix, block, aij, compressed row, sparse, parallel 3292 3293 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3294 @*/ 3295 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) 3296 { 3297 PetscErrorCode ierr; 3298 PetscMPIInt size; 3299 3300 PetscFunctionBegin; 3301 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3302 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3303 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3304 if (size > 1) { 3305 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3306 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3307 } else { 3308 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3309 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3310 } 3311 PetscFunctionReturn(0); 3312 } 3313 3314 #undef __FUNCT__ 3315 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3316 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3317 { 3318 Mat mat; 3319 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3320 PetscErrorCode ierr; 3321 PetscInt len=0; 3322 3323 PetscFunctionBegin; 3324 *newmat = 0; 3325 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3326 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3327 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3328 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3329 3330 mat->factortype = matin->factortype; 3331 mat->preallocated = PETSC_TRUE; 3332 mat->assembled = PETSC_TRUE; 3333 mat->insertmode = NOT_SET_VALUES; 3334 3335 a = (Mat_MPIBAIJ*)mat->data; 3336 mat->rmap->bs = matin->rmap->bs; 3337 a->bs2 = oldmat->bs2; 3338 a->mbs = oldmat->mbs; 3339 a->nbs = oldmat->nbs; 3340 a->Mbs = oldmat->Mbs; 3341 a->Nbs = oldmat->Nbs; 3342 3343 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3344 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3345 3346 a->size = oldmat->size; 3347 a->rank = oldmat->rank; 3348 a->donotstash = oldmat->donotstash; 3349 a->roworiented = oldmat->roworiented; 3350 a->rowindices = 0; 3351 a->rowvalues = 0; 3352 a->getrowactive = PETSC_FALSE; 3353 a->barray = 0; 3354 a->rstartbs = oldmat->rstartbs; 3355 a->rendbs = oldmat->rendbs; 3356 a->cstartbs = oldmat->cstartbs; 3357 a->cendbs = oldmat->cendbs; 3358 3359 /* hash table stuff */ 3360 a->ht = 0; 3361 a->hd = 0; 3362 a->ht_size = 0; 3363 a->ht_flag = oldmat->ht_flag; 3364 a->ht_fact = oldmat->ht_fact; 3365 a->ht_total_ct = 0; 3366 a->ht_insert_ct = 0; 3367 3368 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3369 if (oldmat->colmap) { 3370 #if defined(PETSC_USE_CTABLE) 3371 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3372 #else 3373 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 3374 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3375 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3376 #endif 3377 } else a->colmap = 0; 3378 3379 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3380 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3381 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3382 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3383 } else a->garray = 0; 3384 3385 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3386 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3387 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3388 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3389 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3390 3391 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3392 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3393 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3394 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3395 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3396 *newmat = mat; 3397 PetscFunctionReturn(0); 3398 } 3399 3400 #undef __FUNCT__ 3401 #define __FUNCT__ "MatLoad_MPIBAIJ" 3402 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3403 { 3404 PetscErrorCode ierr; 3405 int fd; 3406 PetscInt i,nz,j,rstart,rend; 3407 PetscScalar *vals,*buf; 3408 MPI_Comm comm; 3409 MPI_Status status; 3410 PetscMPIInt rank,size,maxnz; 3411 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3412 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3413 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3414 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3415 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3416 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3417 3418 PetscFunctionBegin; 3419 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3420 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3421 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3422 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3423 if (bs < 0) bs = 1; 3424 3425 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3426 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3427 if (!rank) { 3428 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3429 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3430 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3431 } 3432 3433 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3434 3435 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3436 M = header[1]; N = header[2]; 3437 3438 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3439 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3440 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3441 3442 /* If global sizes are set, check if they are consistent with that given in the file */ 3443 if (sizesset) { 3444 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3445 } 3446 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); 3447 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); 3448 3449 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3450 3451 /* 3452 This code adds extra rows to make sure the number of rows is 3453 divisible by the blocksize 3454 */ 3455 Mbs = M/bs; 3456 extra_rows = bs - M + bs*Mbs; 3457 if (extra_rows == bs) extra_rows = 0; 3458 else Mbs++; 3459 if (extra_rows && !rank) { 3460 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3461 } 3462 3463 /* determine ownership of all rows */ 3464 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3465 mbs = Mbs/size + ((Mbs % size) > rank); 3466 m = mbs*bs; 3467 } else { /* User set */ 3468 m = newmat->rmap->n; 3469 mbs = m/bs; 3470 } 3471 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3472 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3473 3474 /* process 0 needs enough room for process with most rows */ 3475 if (!rank) { 3476 mmax = rowners[1]; 3477 for (i=2; i<=size; i++) { 3478 mmax = PetscMax(mmax,rowners[i]); 3479 } 3480 mmax*=bs; 3481 } else mmax = -1; /* unused, but compiler warns anyway */ 3482 3483 rowners[0] = 0; 3484 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3485 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3486 rstart = rowners[rank]; 3487 rend = rowners[rank+1]; 3488 3489 /* distribute row lengths to all processors */ 3490 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3491 if (!rank) { 3492 mend = m; 3493 if (size == 1) mend = mend - extra_rows; 3494 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3495 for (j=mend; j<m; j++) locrowlens[j] = 1; 3496 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3497 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3498 for (j=0; j<m; j++) { 3499 procsnz[0] += locrowlens[j]; 3500 } 3501 for (i=1; i<size; i++) { 3502 mend = browners[i+1] - browners[i]; 3503 if (i == size-1) mend = mend - extra_rows; 3504 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3505 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3506 /* calculate the number of nonzeros on each processor */ 3507 for (j=0; j<browners[i+1]-browners[i]; j++) { 3508 procsnz[i] += rowlengths[j]; 3509 } 3510 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3511 } 3512 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3513 } else { 3514 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3515 } 3516 3517 if (!rank) { 3518 /* determine max buffer needed and allocate it */ 3519 maxnz = procsnz[0]; 3520 for (i=1; i<size; i++) { 3521 maxnz = PetscMax(maxnz,procsnz[i]); 3522 } 3523 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3524 3525 /* read in my part of the matrix column indices */ 3526 nz = procsnz[0]; 3527 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3528 mycols = ibuf; 3529 if (size == 1) nz -= extra_rows; 3530 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3531 if (size == 1) { 3532 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3533 } 3534 3535 /* read in every ones (except the last) and ship off */ 3536 for (i=1; i<size-1; i++) { 3537 nz = procsnz[i]; 3538 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3539 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3540 } 3541 /* read in the stuff for the last proc */ 3542 if (size != 1) { 3543 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3544 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3545 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3546 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3547 } 3548 ierr = PetscFree(cols);CHKERRQ(ierr); 3549 } else { 3550 /* determine buffer space needed for message */ 3551 nz = 0; 3552 for (i=0; i<m; i++) { 3553 nz += locrowlens[i]; 3554 } 3555 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3556 mycols = ibuf; 3557 /* receive message of column indices*/ 3558 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3559 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3560 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3561 } 3562 3563 /* loop over local rows, determining number of off diagonal entries */ 3564 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3565 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3566 rowcount = 0; nzcount = 0; 3567 for (i=0; i<mbs; i++) { 3568 dcount = 0; 3569 odcount = 0; 3570 for (j=0; j<bs; j++) { 3571 kmax = locrowlens[rowcount]; 3572 for (k=0; k<kmax; k++) { 3573 tmp = mycols[nzcount++]/bs; 3574 if (!mask[tmp]) { 3575 mask[tmp] = 1; 3576 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3577 else masked1[dcount++] = tmp; 3578 } 3579 } 3580 rowcount++; 3581 } 3582 3583 dlens[i] = dcount; 3584 odlens[i] = odcount; 3585 3586 /* zero out the mask elements we set */ 3587 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3588 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3589 } 3590 3591 3592 if (!sizesset) { 3593 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3594 } 3595 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3596 3597 if (!rank) { 3598 ierr = PetscMalloc1((maxnz+1),&buf);CHKERRQ(ierr); 3599 /* read in my part of the matrix numerical values */ 3600 nz = procsnz[0]; 3601 vals = buf; 3602 mycols = ibuf; 3603 if (size == 1) nz -= extra_rows; 3604 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3605 if (size == 1) { 3606 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3607 } 3608 3609 /* insert into matrix */ 3610 jj = rstart*bs; 3611 for (i=0; i<m; i++) { 3612 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3613 mycols += locrowlens[i]; 3614 vals += locrowlens[i]; 3615 jj++; 3616 } 3617 /* read in other processors (except the last one) and ship out */ 3618 for (i=1; i<size-1; i++) { 3619 nz = procsnz[i]; 3620 vals = buf; 3621 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3622 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3623 } 3624 /* the last proc */ 3625 if (size != 1) { 3626 nz = procsnz[i] - extra_rows; 3627 vals = buf; 3628 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3629 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3630 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3631 } 3632 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3633 } else { 3634 /* receive numeric values */ 3635 ierr = PetscMalloc1((nz+1),&buf);CHKERRQ(ierr); 3636 3637 /* receive message of values*/ 3638 vals = buf; 3639 mycols = ibuf; 3640 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3641 3642 /* insert into matrix */ 3643 jj = rstart*bs; 3644 for (i=0; i<m; i++) { 3645 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3646 mycols += locrowlens[i]; 3647 vals += locrowlens[i]; 3648 jj++; 3649 } 3650 } 3651 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3652 ierr = PetscFree(buf);CHKERRQ(ierr); 3653 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3654 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3655 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3656 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3657 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3658 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3659 PetscFunctionReturn(0); 3660 } 3661 3662 #undef __FUNCT__ 3663 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3664 /*@ 3665 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3666 3667 Input Parameters: 3668 . mat - the matrix 3669 . fact - factor 3670 3671 Not Collective, each process can use a different factor 3672 3673 Level: advanced 3674 3675 Notes: 3676 This can also be set by the command line option: -mat_use_hash_table <fact> 3677 3678 .keywords: matrix, hashtable, factor, HT 3679 3680 .seealso: MatSetOption() 3681 @*/ 3682 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3683 { 3684 PetscErrorCode ierr; 3685 3686 PetscFunctionBegin; 3687 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3688 PetscFunctionReturn(0); 3689 } 3690 3691 #undef __FUNCT__ 3692 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3693 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3694 { 3695 Mat_MPIBAIJ *baij; 3696 3697 PetscFunctionBegin; 3698 baij = (Mat_MPIBAIJ*)mat->data; 3699 baij->ht_fact = fact; 3700 PetscFunctionReturn(0); 3701 } 3702 3703 #undef __FUNCT__ 3704 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3705 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3706 { 3707 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3708 3709 PetscFunctionBegin; 3710 if (Ad) *Ad = a->A; 3711 if (Ao) *Ao = a->B; 3712 if (colmap) *colmap = a->garray; 3713 PetscFunctionReturn(0); 3714 } 3715 3716 /* 3717 Special version for direct calls from Fortran (to eliminate two function call overheads 3718 */ 3719 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3720 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3721 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3722 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3723 #endif 3724 3725 #undef __FUNCT__ 3726 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3727 /*@C 3728 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3729 3730 Collective on Mat 3731 3732 Input Parameters: 3733 + mat - the matrix 3734 . min - number of input rows 3735 . im - input rows 3736 . nin - number of input columns 3737 . in - input columns 3738 . v - numerical values input 3739 - addvin - INSERT_VALUES or ADD_VALUES 3740 3741 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3742 3743 Level: advanced 3744 3745 .seealso: MatSetValuesBlocked() 3746 @*/ 3747 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3748 { 3749 /* convert input arguments to C version */ 3750 Mat mat = *matin; 3751 PetscInt m = *min, n = *nin; 3752 InsertMode addv = *addvin; 3753 3754 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3755 const MatScalar *value; 3756 MatScalar *barray = baij->barray; 3757 PetscBool roworiented = baij->roworiented; 3758 PetscErrorCode ierr; 3759 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3760 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3761 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3762 3763 PetscFunctionBegin; 3764 /* tasks normally handled by MatSetValuesBlocked() */ 3765 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3766 #if defined(PETSC_USE_DEBUG) 3767 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3768 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3769 #endif 3770 if (mat->assembled) { 3771 mat->was_assembled = PETSC_TRUE; 3772 mat->assembled = PETSC_FALSE; 3773 } 3774 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3775 3776 3777 if (!barray) { 3778 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3779 baij->barray = barray; 3780 } 3781 3782 if (roworiented) stepval = (n-1)*bs; 3783 else stepval = (m-1)*bs; 3784 3785 for (i=0; i<m; i++) { 3786 if (im[i] < 0) continue; 3787 #if defined(PETSC_USE_DEBUG) 3788 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); 3789 #endif 3790 if (im[i] >= rstart && im[i] < rend) { 3791 row = im[i] - rstart; 3792 for (j=0; j<n; j++) { 3793 /* If NumCol = 1 then a copy is not required */ 3794 if ((roworiented) && (n == 1)) { 3795 barray = (MatScalar*)v + i*bs2; 3796 } else if ((!roworiented) && (m == 1)) { 3797 barray = (MatScalar*)v + j*bs2; 3798 } else { /* Here a copy is required */ 3799 if (roworiented) { 3800 value = v + i*(stepval+bs)*bs + j*bs; 3801 } else { 3802 value = v + j*(stepval+bs)*bs + i*bs; 3803 } 3804 for (ii=0; ii<bs; ii++,value+=stepval) { 3805 for (jj=0; jj<bs; jj++) { 3806 *barray++ = *value++; 3807 } 3808 } 3809 barray -=bs2; 3810 } 3811 3812 if (in[j] >= cstart && in[j] < cend) { 3813 col = in[j] - cstart; 3814 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3815 } else if (in[j] < 0) continue; 3816 #if defined(PETSC_USE_DEBUG) 3817 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); 3818 #endif 3819 else { 3820 if (mat->was_assembled) { 3821 if (!baij->colmap) { 3822 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3823 } 3824 3825 #if defined(PETSC_USE_DEBUG) 3826 #if defined(PETSC_USE_CTABLE) 3827 { PetscInt data; 3828 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3829 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3830 } 3831 #else 3832 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3833 #endif 3834 #endif 3835 #if defined(PETSC_USE_CTABLE) 3836 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3837 col = (col - 1)/bs; 3838 #else 3839 col = (baij->colmap[in[j]] - 1)/bs; 3840 #endif 3841 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3842 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3843 col = in[j]; 3844 } 3845 } else col = in[j]; 3846 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3847 } 3848 } 3849 } else { 3850 if (!baij->donotstash) { 3851 if (roworiented) { 3852 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3853 } else { 3854 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3855 } 3856 } 3857 } 3858 } 3859 3860 /* task normally handled by MatSetValuesBlocked() */ 3861 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3862 PetscFunctionReturn(0); 3863 } 3864 3865 #undef __FUNCT__ 3866 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3867 /*@ 3868 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3869 CSR format the local rows. 3870 3871 Collective on MPI_Comm 3872 3873 Input Parameters: 3874 + comm - MPI communicator 3875 . bs - the block size, only a block size of 1 is supported 3876 . m - number of local rows (Cannot be PETSC_DECIDE) 3877 . n - This value should be the same as the local size used in creating the 3878 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3879 calculated if N is given) For square matrices n is almost always m. 3880 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3881 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3882 . i - row indices 3883 . j - column indices 3884 - a - matrix values 3885 3886 Output Parameter: 3887 . mat - the matrix 3888 3889 Level: intermediate 3890 3891 Notes: 3892 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3893 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3894 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3895 3896 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3897 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3898 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3899 with column-major ordering within blocks. 3900 3901 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3902 3903 .keywords: matrix, aij, compressed row, sparse, parallel 3904 3905 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3906 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3907 @*/ 3908 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) 3909 { 3910 PetscErrorCode ierr; 3911 3912 PetscFunctionBegin; 3913 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3914 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3915 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3916 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3917 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3918 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3919 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3920 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3921 PetscFunctionReturn(0); 3922 } 3923