1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <petscblaslapack.h> 4 5 extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat); 7 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 8 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 9 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 10 extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 11 extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 12 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec); 13 14 #undef __FUNCT__ 15 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 16 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 17 { 18 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 19 PetscErrorCode ierr; 20 PetscInt i,*idxb = 0; 21 PetscScalar *va,*vb; 22 Vec vtmp; 23 24 PetscFunctionBegin; 25 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 26 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 27 if (idx) { 28 for (i=0; i<A->rmap->n; i++) { 29 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 30 } 31 } 32 33 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 34 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 35 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 36 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 37 38 for (i=0; i<A->rmap->n; i++) { 39 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 40 va[i] = vb[i]; 41 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 42 } 43 } 44 45 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 46 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 47 ierr = PetscFree(idxb);CHKERRQ(ierr); 48 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 49 PetscFunctionReturn(0); 50 } 51 52 #undef __FUNCT__ 53 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 54 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 55 { 56 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 57 PetscErrorCode ierr; 58 59 PetscFunctionBegin; 60 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 61 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 62 PetscFunctionReturn(0); 63 } 64 65 #undef __FUNCT__ 66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 67 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 68 { 69 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 70 PetscErrorCode ierr; 71 72 PetscFunctionBegin; 73 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 74 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 75 PetscFunctionReturn(0); 76 } 77 78 /* 79 Local utility routine that creates a mapping from the global column 80 number to the local number in the off-diagonal part of the local 81 storage of the matrix. This is done in a non scalable way since the 82 length of colmap equals the global matrix length. 83 */ 84 #undef __FUNCT__ 85 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 86 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 87 { 88 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 89 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 90 PetscErrorCode ierr; 91 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 92 93 PetscFunctionBegin; 94 #if defined(PETSC_USE_CTABLE) 95 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 96 for (i=0; i<nbs; i++) { 97 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 98 } 99 #else 100 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 101 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 102 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 104 #endif 105 PetscFunctionReturn(0); 106 } 107 108 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 109 { \ 110 \ 111 brow = row/bs; \ 112 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 113 rmax = aimax[brow]; nrow = ailen[brow]; \ 114 bcol = col/bs; \ 115 ridx = row % bs; cidx = col % bs; \ 116 low = 0; high = nrow; \ 117 while (high-low > 3) { \ 118 t = (low+high)/2; \ 119 if (rp[t] > bcol) high = t; \ 120 else low = t; \ 121 } \ 122 for (_i=low; _i<high; _i++) { \ 123 if (rp[_i] > bcol) break; \ 124 if (rp[_i] == bcol) { \ 125 bap = ap + bs2*_i + bs*cidx + ridx; \ 126 if (addv == ADD_VALUES) *bap += value; \ 127 else *bap = value; \ 128 goto a_noinsert; \ 129 } \ 130 } \ 131 if (a->nonew == 1) goto a_noinsert; \ 132 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 133 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 134 N = nrow++ - 1; \ 135 /* shift up all the later entries in this row */ \ 136 for (ii=N; ii>=_i; ii--) { \ 137 rp[ii+1] = rp[ii]; \ 138 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 139 } \ 140 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 141 rp[_i] = bcol; \ 142 ap[bs2*_i + bs*cidx + ridx] = value; \ 143 a_noinsert:; \ 144 ailen[brow] = nrow; \ 145 } 146 147 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 148 { \ 149 brow = row/bs; \ 150 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 151 rmax = bimax[brow]; nrow = bilen[brow]; \ 152 bcol = col/bs; \ 153 ridx = row % bs; cidx = col % bs; \ 154 low = 0; high = nrow; \ 155 while (high-low > 3) { \ 156 t = (low+high)/2; \ 157 if (rp[t] > bcol) high = t; \ 158 else low = t; \ 159 } \ 160 for (_i=low; _i<high; _i++) { \ 161 if (rp[_i] > bcol) break; \ 162 if (rp[_i] == bcol) { \ 163 bap = ap + bs2*_i + bs*cidx + ridx; \ 164 if (addv == ADD_VALUES) *bap += value; \ 165 else *bap = value; \ 166 goto b_noinsert; \ 167 } \ 168 } \ 169 if (b->nonew == 1) goto b_noinsert; \ 170 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 171 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 172 N = nrow++ - 1; \ 173 /* shift up all the later entries in this row */ \ 174 for (ii=N; ii>=_i; ii--) { \ 175 rp[ii+1] = rp[ii]; \ 176 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 177 } \ 178 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 179 rp[_i] = bcol; \ 180 ap[bs2*_i + bs*cidx + ridx] = value; \ 181 b_noinsert:; \ 182 bilen[brow] = nrow; \ 183 } 184 185 #undef __FUNCT__ 186 #define __FUNCT__ "MatSetValues_MPIBAIJ" 187 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 188 { 189 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 190 MatScalar value; 191 PetscBool roworiented = baij->roworiented; 192 PetscErrorCode ierr; 193 PetscInt i,j,row,col; 194 PetscInt rstart_orig=mat->rmap->rstart; 195 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 196 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 197 198 /* Some Variables required in the macro */ 199 Mat A = baij->A; 200 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 201 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 202 MatScalar *aa =a->a; 203 204 Mat B = baij->B; 205 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 206 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 207 MatScalar *ba =b->a; 208 209 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 210 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 211 MatScalar *ap,*bap; 212 213 PetscFunctionBegin; 214 if (v) PetscValidScalarPointer(v,6); 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 = PetscMalloc(bs2*sizeof(MatScalar),&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 if (v) PetscValidScalarPointer(v,6); 398 for (i=0; i<m; i++) { 399 #if defined(PETSC_USE_DEBUG) 400 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 401 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); 402 #endif 403 row = im[i]; 404 if (row >= rstart_orig && row < rend_orig) { 405 for (j=0; j<n; j++) { 406 col = in[j]; 407 if (roworiented) value = v[i*n+j]; 408 else value = v[i+j*m]; 409 /* Look up PetscInto the Hash Table */ 410 key = (row/bs)*Nbs+(col/bs)+1; 411 h1 = HASH(size,key,tmp); 412 413 414 idx = h1; 415 #if defined(PETSC_USE_DEBUG) 416 insert_ct++; 417 total_ct++; 418 if (HT[idx] != key) { 419 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 420 if (idx == size) { 421 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 422 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 423 } 424 } 425 #else 426 if (HT[idx] != key) { 427 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 428 if (idx == size) { 429 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 430 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 431 } 432 } 433 #endif 434 /* A HASH table entry is found, so insert the values at the correct address */ 435 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 436 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 437 } 438 } else if (!baij->donotstash) { 439 if (roworiented) { 440 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 441 } else { 442 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 443 } 444 } 445 } 446 #if defined(PETSC_USE_DEBUG) 447 baij->ht_total_ct = total_ct; 448 baij->ht_insert_ct = insert_ct; 449 #endif 450 PetscFunctionReturn(0); 451 } 452 453 #undef __FUNCT__ 454 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 455 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 456 { 457 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 458 PetscBool roworiented = baij->roworiented; 459 PetscErrorCode ierr; 460 PetscInt i,j,ii,jj,row,col; 461 PetscInt rstart=baij->rstartbs; 462 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 463 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 464 PetscReal tmp; 465 MatScalar **HD = baij->hd,*baij_a; 466 const PetscScalar *v_t,*value; 467 #if defined(PETSC_USE_DEBUG) 468 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 469 #endif 470 471 PetscFunctionBegin; 472 if (roworiented) stepval = (n-1)*bs; 473 else stepval = (m-1)*bs; 474 475 for (i=0; i<m; i++) { 476 #if defined(PETSC_USE_DEBUG) 477 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 478 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); 479 #endif 480 row = im[i]; 481 v_t = v + i*nbs2; 482 if (row >= rstart && row < rend) { 483 for (j=0; j<n; j++) { 484 col = in[j]; 485 486 /* Look up into the Hash Table */ 487 key = row*Nbs+col+1; 488 h1 = HASH(size,key,tmp); 489 490 idx = h1; 491 #if defined(PETSC_USE_DEBUG) 492 total_ct++; 493 insert_ct++; 494 if (HT[idx] != key) { 495 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 496 if (idx == size) { 497 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 498 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 499 } 500 } 501 #else 502 if (HT[idx] != key) { 503 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 504 if (idx == size) { 505 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 506 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 507 } 508 } 509 #endif 510 baij_a = HD[idx]; 511 if (roworiented) { 512 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 513 /* value = v + (i*(stepval+bs)+j)*bs; */ 514 value = v_t; 515 v_t += bs; 516 if (addv == ADD_VALUES) { 517 for (ii=0; ii<bs; ii++,value+=stepval) { 518 for (jj=ii; jj<bs2; jj+=bs) { 519 baij_a[jj] += *value++; 520 } 521 } 522 } else { 523 for (ii=0; ii<bs; ii++,value+=stepval) { 524 for (jj=ii; jj<bs2; jj+=bs) { 525 baij_a[jj] = *value++; 526 } 527 } 528 } 529 } else { 530 value = v + j*(stepval+bs)*bs + i*bs; 531 if (addv == ADD_VALUES) { 532 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 533 for (jj=0; jj<bs; jj++) { 534 baij_a[jj] += *value++; 535 } 536 } 537 } else { 538 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 539 for (jj=0; jj<bs; jj++) { 540 baij_a[jj] = *value++; 541 } 542 } 543 } 544 } 545 } 546 } else { 547 if (!baij->donotstash) { 548 if (roworiented) { 549 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 550 } else { 551 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 552 } 553 } 554 } 555 } 556 #if defined(PETSC_USE_DEBUG) 557 baij->ht_total_ct = total_ct; 558 baij->ht_insert_ct = insert_ct; 559 #endif 560 PetscFunctionReturn(0); 561 } 562 563 #undef __FUNCT__ 564 #define __FUNCT__ "MatGetValues_MPIBAIJ" 565 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 566 { 567 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 568 PetscErrorCode ierr; 569 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 570 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 571 572 PetscFunctionBegin; 573 for (i=0; i<m; i++) { 574 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 575 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); 576 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 577 row = idxm[i] - bsrstart; 578 for (j=0; j<n; j++) { 579 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 580 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); 581 if (idxn[j] >= bscstart && idxn[j] < bscend) { 582 col = idxn[j] - bscstart; 583 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 584 } else { 585 if (!baij->colmap) { 586 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 587 } 588 #if defined(PETSC_USE_CTABLE) 589 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 590 data--; 591 #else 592 data = baij->colmap[idxn[j]/bs]-1; 593 #endif 594 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 595 else { 596 col = data + idxn[j]%bs; 597 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 598 } 599 } 600 } 601 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 602 } 603 PetscFunctionReturn(0); 604 } 605 606 #undef __FUNCT__ 607 #define __FUNCT__ "MatNorm_MPIBAIJ" 608 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 609 { 610 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 611 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 612 PetscErrorCode ierr; 613 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 614 PetscReal sum = 0.0; 615 MatScalar *v; 616 617 PetscFunctionBegin; 618 if (baij->size == 1) { 619 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 620 } else { 621 if (type == NORM_FROBENIUS) { 622 v = amat->a; 623 nz = amat->nz*bs2; 624 for (i=0; i<nz; i++) { 625 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 626 } 627 v = bmat->a; 628 nz = bmat->nz*bs2; 629 for (i=0; i<nz; i++) { 630 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 631 } 632 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 633 *nrm = PetscSqrtReal(*nrm); 634 } else if (type == NORM_1) { /* max column sum */ 635 PetscReal *tmp,*tmp2; 636 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 637 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);CHKERRQ(ierr); 638 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 639 v = amat->a; jj = amat->j; 640 for (i=0; i<amat->nz; i++) { 641 for (j=0; j<bs; j++) { 642 col = bs*(cstart + *jj) + j; /* column index */ 643 for (row=0; row<bs; row++) { 644 tmp[col] += PetscAbsScalar(*v); v++; 645 } 646 } 647 jj++; 648 } 649 v = bmat->a; jj = bmat->j; 650 for (i=0; i<bmat->nz; i++) { 651 for (j=0; j<bs; j++) { 652 col = bs*garray[*jj] + j; 653 for (row=0; row<bs; row++) { 654 tmp[col] += PetscAbsScalar(*v); v++; 655 } 656 } 657 jj++; 658 } 659 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 660 *nrm = 0.0; 661 for (j=0; j<mat->cmap->N; j++) { 662 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 663 } 664 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 665 } else if (type == NORM_INFINITY) { /* max row sum */ 666 PetscReal *sums; 667 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr); 668 sum = 0.0; 669 for (j=0; j<amat->mbs; j++) { 670 for (row=0; row<bs; row++) sums[row] = 0.0; 671 v = amat->a + bs2*amat->i[j]; 672 nz = amat->i[j+1]-amat->i[j]; 673 for (i=0; i<nz; i++) { 674 for (col=0; col<bs; col++) { 675 for (row=0; row<bs; row++) { 676 sums[row] += PetscAbsScalar(*v); v++; 677 } 678 } 679 } 680 v = bmat->a + bs2*bmat->i[j]; 681 nz = bmat->i[j+1]-bmat->i[j]; 682 for (i=0; i<nz; i++) { 683 for (col=0; col<bs; col++) { 684 for (row=0; row<bs; row++) { 685 sums[row] += PetscAbsScalar(*v); v++; 686 } 687 } 688 } 689 for (row=0; row<bs; row++) { 690 if (sums[row] > sum) sum = sums[row]; 691 } 692 } 693 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 694 ierr = PetscFree(sums);CHKERRQ(ierr); 695 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 696 } 697 PetscFunctionReturn(0); 698 } 699 700 /* 701 Creates the hash table, and sets the table 702 This table is created only once. 703 If new entried need to be added to the matrix 704 then the hash table has to be destroyed and 705 recreated. 706 */ 707 #undef __FUNCT__ 708 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 709 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 710 { 711 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 712 Mat A = baij->A,B=baij->B; 713 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 714 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 715 PetscErrorCode ierr; 716 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 717 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 718 PetscInt *HT,key; 719 MatScalar **HD; 720 PetscReal tmp; 721 #if defined(PETSC_USE_INFO) 722 PetscInt ct=0,max=0; 723 #endif 724 725 PetscFunctionBegin; 726 if (baij->ht) PetscFunctionReturn(0); 727 728 baij->ht_size = (PetscInt)(factor*nz); 729 ht_size = baij->ht_size; 730 731 /* Allocate Memory for Hash Table */ 732 ierr = PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);CHKERRQ(ierr); 733 ierr = PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));CHKERRQ(ierr); 734 ierr = PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));CHKERRQ(ierr); 735 HD = baij->hd; 736 HT = baij->ht; 737 738 /* Loop Over A */ 739 for (i=0; i<a->mbs; i++) { 740 for (j=ai[i]; j<ai[i+1]; j++) { 741 row = i+rstart; 742 col = aj[j]+cstart; 743 744 key = row*Nbs + col + 1; 745 h1 = HASH(ht_size,key,tmp); 746 for (k=0; k<ht_size; k++) { 747 if (!HT[(h1+k)%ht_size]) { 748 HT[(h1+k)%ht_size] = key; 749 HD[(h1+k)%ht_size] = a->a + j*bs2; 750 break; 751 #if defined(PETSC_USE_INFO) 752 } else { 753 ct++; 754 #endif 755 } 756 } 757 #if defined(PETSC_USE_INFO) 758 if (k> max) max = k; 759 #endif 760 } 761 } 762 /* Loop Over B */ 763 for (i=0; i<b->mbs; i++) { 764 for (j=bi[i]; j<bi[i+1]; j++) { 765 row = i+rstart; 766 col = garray[bj[j]]; 767 key = row*Nbs + col + 1; 768 h1 = HASH(ht_size,key,tmp); 769 for (k=0; k<ht_size; k++) { 770 if (!HT[(h1+k)%ht_size]) { 771 HT[(h1+k)%ht_size] = key; 772 HD[(h1+k)%ht_size] = b->a + j*bs2; 773 break; 774 #if defined(PETSC_USE_INFO) 775 } else { 776 ct++; 777 #endif 778 } 779 } 780 #if defined(PETSC_USE_INFO) 781 if (k> max) max = k; 782 #endif 783 } 784 } 785 786 /* Print Summary */ 787 #if defined(PETSC_USE_INFO) 788 for (i=0,j=0; i<ht_size; i++) { 789 if (HT[i]) j++; 790 } 791 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 792 #endif 793 PetscFunctionReturn(0); 794 } 795 796 #undef __FUNCT__ 797 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 798 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 799 { 800 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 801 PetscErrorCode ierr; 802 PetscInt nstash,reallocs; 803 InsertMode addv; 804 805 PetscFunctionBegin; 806 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 807 808 /* make sure all processors are either in INSERTMODE or ADDMODE */ 809 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 810 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 811 mat->insertmode = addv; /* in case this processor had no cache */ 812 813 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 814 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 815 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 816 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 817 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 818 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 819 PetscFunctionReturn(0); 820 } 821 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 824 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 825 { 826 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 827 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 828 PetscErrorCode ierr; 829 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 830 PetscInt *row,*col; 831 PetscBool r1,r2,r3,other_disassembled; 832 MatScalar *val; 833 InsertMode addv = mat->insertmode; 834 PetscMPIInt n; 835 836 PetscFunctionBegin; 837 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 838 if (!baij->donotstash && !mat->nooffprocentries) { 839 while (1) { 840 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 841 if (!flg) break; 842 843 for (i=0; i<n;) { 844 /* Now identify the consecutive vals belonging to the same row */ 845 for (j=i,rstart=row[j]; j<n; j++) { 846 if (row[j] != rstart) break; 847 } 848 if (j < n) ncols = j-i; 849 else ncols = n-i; 850 /* Now assemble all these values with a single function call */ 851 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 852 i = j; 853 } 854 } 855 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 856 /* Now process the block-stash. Since the values are stashed column-oriented, 857 set the roworiented flag to column oriented, and after MatSetValues() 858 restore the original flags */ 859 r1 = baij->roworiented; 860 r2 = a->roworiented; 861 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 862 863 baij->roworiented = PETSC_FALSE; 864 a->roworiented = PETSC_FALSE; 865 866 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 867 while (1) { 868 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 869 if (!flg) break; 870 871 for (i=0; i<n;) { 872 /* Now identify the consecutive vals belonging to the same row */ 873 for (j=i,rstart=row[j]; j<n; j++) { 874 if (row[j] != rstart) break; 875 } 876 if (j < n) ncols = j-i; 877 else ncols = n-i; 878 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 879 i = j; 880 } 881 } 882 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 883 884 baij->roworiented = r1; 885 a->roworiented = r2; 886 887 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 888 } 889 890 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 891 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 892 893 /* determine if any processor has disassembled, if so we must 894 also disassemble ourselfs, in order that we may reassemble. */ 895 /* 896 if nonzero structure of submatrix B cannot change then we know that 897 no processor disassembled thus we can skip this stuff 898 */ 899 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 900 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 901 if (mat->was_assembled && !other_disassembled) { 902 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 903 } 904 } 905 906 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 907 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 908 } 909 ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 910 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 911 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 912 913 #if defined(PETSC_USE_INFO) 914 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 915 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 916 917 baij->ht_total_ct = 0; 918 baij->ht_insert_ct = 0; 919 } 920 #endif 921 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 922 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 923 924 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 925 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 926 } 927 928 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 929 930 baij->rowvalues = 0; 931 PetscFunctionReturn(0); 932 } 933 934 #include <petscdraw.h> 935 #undef __FUNCT__ 936 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 937 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 938 { 939 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 940 PetscErrorCode ierr; 941 PetscMPIInt size = baij->size,rank = baij->rank; 942 PetscInt bs = mat->rmap->bs; 943 PetscBool iascii,isdraw; 944 PetscViewer sviewer; 945 PetscViewerFormat format; 946 947 PetscFunctionBegin; 948 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 949 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 950 if (iascii) { 951 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 952 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 953 MatInfo info; 954 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 955 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 956 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 957 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 958 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 959 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 960 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 961 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 962 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 963 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 964 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 965 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 966 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 967 PetscFunctionReturn(0); 968 } else if (format == PETSC_VIEWER_ASCII_INFO) { 969 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 970 PetscFunctionReturn(0); 971 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 972 PetscFunctionReturn(0); 973 } 974 } 975 976 if (isdraw) { 977 PetscDraw draw; 978 PetscBool isnull; 979 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 980 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 981 } 982 983 if (size == 1) { 984 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 985 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 986 } else { 987 /* assemble the entire matrix onto first processor. */ 988 Mat A; 989 Mat_SeqBAIJ *Aloc; 990 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 991 MatScalar *a; 992 993 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 994 /* Perhaps this should be the type of mat? */ 995 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 996 if (!rank) { 997 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 998 } else { 999 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1000 } 1001 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1002 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1003 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1004 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1005 1006 /* copy over the A part */ 1007 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1008 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1009 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1010 1011 for (i=0; i<mbs; i++) { 1012 rvals[0] = bs*(baij->rstartbs + i); 1013 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1014 for (j=ai[i]; j<ai[i+1]; j++) { 1015 col = (baij->cstartbs+aj[j])*bs; 1016 for (k=0; k<bs; k++) { 1017 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1018 col++; a += bs; 1019 } 1020 } 1021 } 1022 /* copy over the B part */ 1023 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1024 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1025 for (i=0; i<mbs; i++) { 1026 rvals[0] = bs*(baij->rstartbs + i); 1027 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1028 for (j=ai[i]; j<ai[i+1]; j++) { 1029 col = baij->garray[aj[j]]*bs; 1030 for (k=0; k<bs; k++) { 1031 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1032 col++; a += bs; 1033 } 1034 } 1035 } 1036 ierr = PetscFree(rvals);CHKERRQ(ierr); 1037 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1038 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1039 /* 1040 Everyone has to call to draw the matrix since the graphics waits are 1041 synchronized across all processors that share the PetscDraw object 1042 */ 1043 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1044 if (!rank) { 1045 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1046 /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/ 1047 PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ); 1048 ierr = MatView(((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 = PetscMalloc((rlen/bs)*sizeof(PetscInt),&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 = PetscMalloc(rlen*sizeof(PetscInt),&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 = PetscMalloc(nzmax*sizeof(PetscInt),&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 = PetscMalloc(nzmax*sizeof(PetscScalar),&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,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&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 = PetscMalloc(bs*sizeof(PetscInt),&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 PetscErrorCode ierr; 1729 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1730 PetscInt i,*owners = A->rmap->range; 1731 PetscInt *nprocs,j,idx,nsends,row; 1732 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1733 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1734 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1735 MPI_Comm comm; 1736 MPI_Request *send_waits,*recv_waits; 1737 MPI_Status recv_status,*send_status; 1738 const PetscScalar *xx; 1739 PetscScalar *bb; 1740 #if defined(PETSC_DEBUG) 1741 PetscBool found = PETSC_FALSE; 1742 #endif 1743 1744 PetscFunctionBegin; 1745 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1746 /* first count number of contributors to each processor */ 1747 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1748 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1749 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1750 j = 0; 1751 for (i=0; i<N; i++) { 1752 if (lastidx > (idx = rows[i])) j = 0; 1753 lastidx = idx; 1754 for (; j<size; j++) { 1755 if (idx >= owners[j] && idx < owners[j+1]) { 1756 nprocs[2*j]++; 1757 nprocs[2*j+1] = 1; 1758 owner[i] = j; 1759 #if defined(PETSC_DEBUG) 1760 found = PETSC_TRUE; 1761 #endif 1762 break; 1763 } 1764 } 1765 #if defined(PETSC_DEBUG) 1766 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1767 found = PETSC_FALSE; 1768 #endif 1769 } 1770 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 1771 1772 if (A->nooffproczerorows) { 1773 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 1774 nrecvs = nsends; 1775 nmax = N; 1776 } else { 1777 /* inform other processors of number of messages and max length*/ 1778 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1779 } 1780 1781 /* post receives: */ 1782 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1783 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1784 for (i=0; i<nrecvs; i++) { 1785 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1786 } 1787 1788 /* do sends: 1789 1) starts[i] gives the starting index in svalues for stuff going to 1790 the ith processor 1791 */ 1792 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1793 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1794 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1795 starts[0] = 0; 1796 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 1797 for (i=0; i<N; i++) { 1798 svalues[starts[owner[i]]++] = rows[i]; 1799 } 1800 1801 starts[0] = 0; 1802 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 1803 count = 0; 1804 for (i=0; i<size; i++) { 1805 if (nprocs[2*i+1]) { 1806 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1807 } 1808 } 1809 ierr = PetscFree(starts);CHKERRQ(ierr); 1810 1811 base = owners[rank]; 1812 1813 /* wait on receives */ 1814 ierr = PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);CHKERRQ(ierr); 1815 count = nrecvs; 1816 slen = 0; 1817 while (count) { 1818 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1819 /* unpack receives into our local space */ 1820 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1821 1822 source[imdex] = recv_status.MPI_SOURCE; 1823 lens[imdex] = n; 1824 slen += n; 1825 count--; 1826 } 1827 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1828 1829 /* move the data into the send scatter */ 1830 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1831 count = 0; 1832 for (i=0; i<nrecvs; i++) { 1833 values = rvalues + i*nmax; 1834 for (j=0; j<lens[i]; j++) { 1835 lrows[count++] = values[j] - base; 1836 } 1837 } 1838 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1839 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1840 ierr = PetscFree(owner);CHKERRQ(ierr); 1841 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1842 1843 /* fix right hand side if needed */ 1844 if (x && b) { 1845 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1846 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1847 for (i=0; i<slen; i++) { 1848 bb[lrows[i]] = diag*xx[lrows[i]]; 1849 } 1850 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1851 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1852 } 1853 1854 /* actually zap the local rows */ 1855 /* 1856 Zero the required rows. If the "diagonal block" of the matrix 1857 is square and the user wishes to set the diagonal we use separate 1858 code so that MatSetValues() is not called for each diagonal allocating 1859 new memory, thus calling lots of mallocs and slowing things down. 1860 1861 */ 1862 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1863 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1864 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1865 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 1866 } else if (diag != 0.0) { 1867 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1868 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\ 1869 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1870 for (i=0; i<slen; i++) { 1871 row = lrows[i] + rstart_bs; 1872 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1873 } 1874 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1875 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1876 } else { 1877 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1878 } 1879 1880 ierr = PetscFree(lrows);CHKERRQ(ierr); 1881 1882 /* wait on sends */ 1883 if (nsends) { 1884 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1885 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1886 ierr = PetscFree(send_status);CHKERRQ(ierr); 1887 } 1888 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1889 ierr = PetscFree(svalues);CHKERRQ(ierr); 1890 PetscFunctionReturn(0); 1891 } 1892 1893 #undef __FUNCT__ 1894 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1895 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1896 { 1897 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1898 PetscErrorCode ierr; 1899 1900 PetscFunctionBegin; 1901 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1902 PetscFunctionReturn(0); 1903 } 1904 1905 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1906 1907 #undef __FUNCT__ 1908 #define __FUNCT__ "MatEqual_MPIBAIJ" 1909 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1910 { 1911 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1912 Mat a,b,c,d; 1913 PetscBool flg; 1914 PetscErrorCode ierr; 1915 1916 PetscFunctionBegin; 1917 a = matA->A; b = matA->B; 1918 c = matB->A; d = matB->B; 1919 1920 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1921 if (flg) { 1922 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1923 } 1924 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1925 PetscFunctionReturn(0); 1926 } 1927 1928 #undef __FUNCT__ 1929 #define __FUNCT__ "MatCopy_MPIBAIJ" 1930 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1931 { 1932 PetscErrorCode ierr; 1933 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1934 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1935 1936 PetscFunctionBegin; 1937 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1938 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1939 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1940 } else { 1941 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1942 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1943 } 1944 PetscFunctionReturn(0); 1945 } 1946 1947 #undef __FUNCT__ 1948 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1949 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1950 { 1951 PetscErrorCode ierr; 1952 1953 PetscFunctionBegin; 1954 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1955 PetscFunctionReturn(0); 1956 } 1957 1958 #undef __FUNCT__ 1959 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1960 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1961 { 1962 PetscErrorCode ierr; 1963 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1964 PetscBLASInt bnz,one=1; 1965 Mat_SeqBAIJ *x,*y; 1966 1967 PetscFunctionBegin; 1968 if (str == SAME_NONZERO_PATTERN) { 1969 PetscScalar alpha = a; 1970 x = (Mat_SeqBAIJ*)xx->A->data; 1971 y = (Mat_SeqBAIJ*)yy->A->data; 1972 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 1973 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1974 x = (Mat_SeqBAIJ*)xx->B->data; 1975 y = (Mat_SeqBAIJ*)yy->B->data; 1976 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 1977 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1978 } else { 1979 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1980 } 1981 PetscFunctionReturn(0); 1982 } 1983 1984 #undef __FUNCT__ 1985 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1986 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1987 { 1988 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1989 PetscErrorCode ierr; 1990 1991 PetscFunctionBegin; 1992 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1993 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1999 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2000 { 2001 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2002 PetscErrorCode ierr; 2003 2004 PetscFunctionBegin; 2005 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2006 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2007 PetscFunctionReturn(0); 2008 } 2009 2010 #undef __FUNCT__ 2011 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2012 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2013 { 2014 PetscErrorCode ierr; 2015 IS iscol_local; 2016 PetscInt csize; 2017 2018 PetscFunctionBegin; 2019 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2020 if (call == MAT_REUSE_MATRIX) { 2021 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2022 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2023 } else { 2024 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2025 } 2026 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2027 if (call == MAT_INITIAL_MATRIX) { 2028 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2029 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2030 } 2031 PetscFunctionReturn(0); 2032 } 2033 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2034 #undef __FUNCT__ 2035 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2036 /* 2037 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2038 in local and then by concatenating the local matrices the end result. 2039 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2040 */ 2041 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2042 { 2043 PetscErrorCode ierr; 2044 PetscMPIInt rank,size; 2045 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2046 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2047 Mat M,Mreuse; 2048 MatScalar *vwork,*aa; 2049 MPI_Comm comm; 2050 IS isrow_new, iscol_new; 2051 PetscBool idflag,allrows, allcols; 2052 Mat_SeqBAIJ *aij; 2053 2054 PetscFunctionBegin; 2055 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2056 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2057 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2058 /* The compression and expansion should be avoided. Doesn't point 2059 out errors, might change the indices, hence buggey */ 2060 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2061 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2062 2063 /* Check for special case: each processor gets entire matrix columns */ 2064 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2065 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2066 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2067 else allcols = PETSC_FALSE; 2068 2069 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2070 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2071 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2072 else allrows = PETSC_FALSE; 2073 2074 if (call == MAT_REUSE_MATRIX) { 2075 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2076 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2077 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2078 } else { 2079 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2080 } 2081 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2082 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2083 /* 2084 m - number of local rows 2085 n - number of columns (same on all processors) 2086 rstart - first row in new global matrix generated 2087 */ 2088 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2089 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2090 m = m/bs; 2091 n = n/bs; 2092 2093 if (call == MAT_INITIAL_MATRIX) { 2094 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2095 ii = aij->i; 2096 jj = aij->j; 2097 2098 /* 2099 Determine the number of non-zeros in the diagonal and off-diagonal 2100 portions of the matrix in order to do correct preallocation 2101 */ 2102 2103 /* first get start and end of "diagonal" columns */ 2104 if (csize == PETSC_DECIDE) { 2105 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2106 if (mglobal == n*bs) { /* square matrix */ 2107 nlocal = m; 2108 } else { 2109 nlocal = n/size + ((n % size) > rank); 2110 } 2111 } else { 2112 nlocal = csize/bs; 2113 } 2114 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2115 rstart = rend - nlocal; 2116 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); 2117 2118 /* next, compute all the lengths */ 2119 ierr = PetscMalloc2(m+1,PetscInt,&dlens,m+1,PetscInt,&olens);CHKERRQ(ierr); 2120 for (i=0; i<m; i++) { 2121 jend = ii[i+1] - ii[i]; 2122 olen = 0; 2123 dlen = 0; 2124 for (j=0; j<jend; j++) { 2125 if (*jj < rstart || *jj >= rend) olen++; 2126 else dlen++; 2127 jj++; 2128 } 2129 olens[i] = olen; 2130 dlens[i] = dlen; 2131 } 2132 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2133 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2134 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2135 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2136 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2137 } else { 2138 PetscInt ml,nl; 2139 2140 M = *newmat; 2141 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2142 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2143 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2144 /* 2145 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2146 rather than the slower MatSetValues(). 2147 */ 2148 M->was_assembled = PETSC_TRUE; 2149 M->assembled = PETSC_FALSE; 2150 } 2151 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2152 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2153 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2154 ii = aij->i; 2155 jj = aij->j; 2156 aa = aij->a; 2157 for (i=0; i<m; i++) { 2158 row = rstart/bs + i; 2159 nz = ii[i+1] - ii[i]; 2160 cwork = jj; jj += nz; 2161 vwork = aa; aa += nz*bs*bs; 2162 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2163 } 2164 2165 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2166 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2167 *newmat = M; 2168 2169 /* save submatrix used in processor for next request */ 2170 if (call == MAT_INITIAL_MATRIX) { 2171 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2172 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2173 } 2174 PetscFunctionReturn(0); 2175 } 2176 2177 #undef __FUNCT__ 2178 #define __FUNCT__ "MatPermute_MPIBAIJ" 2179 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2180 { 2181 MPI_Comm comm,pcomm; 2182 PetscInt first,rlocal_size,clocal_size,nrows; 2183 const PetscInt *rows; 2184 PetscMPIInt size; 2185 IS crowp,growp,irowp,lrowp,lcolp; 2186 PetscErrorCode ierr; 2187 2188 PetscFunctionBegin; 2189 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2190 /* make a collective version of 'rowp' */ 2191 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2192 if (pcomm==comm) { 2193 crowp = rowp; 2194 } else { 2195 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2196 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2197 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2198 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2199 } 2200 /* collect the global row permutation and invert it */ 2201 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 2202 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 2203 if (pcomm!=comm) { 2204 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2205 } 2206 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2207 ierr = ISDestroy(&growp);CHKERRQ(ierr); 2208 /* get the local target indices */ 2209 ierr = MatGetOwnershipRange(A,&first,NULL);CHKERRQ(ierr); 2210 ierr = MatGetLocalSize(A,&rlocal_size,&clocal_size);CHKERRQ(ierr); 2211 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 2212 ierr = ISCreateGeneral(MPI_COMM_SELF,rlocal_size,rows+first,PETSC_COPY_VALUES,&lrowp);CHKERRQ(ierr); 2213 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 2214 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2215 /* the column permutation is so much easier; 2216 make a local version of 'colp' and invert it */ 2217 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2218 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2219 if (size==1) { 2220 lcolp = colp; 2221 } else { 2222 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2223 } 2224 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2225 /* now we just get the submatrix */ 2226 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2227 if (size>1) { 2228 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2229 } 2230 /* clean up */ 2231 ierr = ISDestroy(&lrowp);CHKERRQ(ierr); 2232 PetscFunctionReturn(0); 2233 } 2234 2235 #undef __FUNCT__ 2236 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2237 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2238 { 2239 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2240 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2241 2242 PetscFunctionBegin; 2243 if (nghosts) *nghosts = B->nbs; 2244 if (ghosts) *ghosts = baij->garray; 2245 PetscFunctionReturn(0); 2246 } 2247 2248 extern PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat); 2249 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 2250 #undef __FUNCT__ 2251 #define __FUNCT__ "MatFDColoringCreate_MPIBAIJ" 2252 /* 2253 This routine is almost identical to MatFDColoringCreate_MPIAIJ()! 2254 */ 2255 PetscErrorCode MatFDColoringCreate_MPIBAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 2256 { 2257 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2258 PetscErrorCode ierr; 2259 PetscMPIInt size,*ncolsonproc,*disp,nn; 2260 PetscInt bs,i,n,nrows,j,k,m,ncols,col; 2261 const PetscInt *is,*rows = 0,*A_ci,*A_cj,*B_ci,*B_cj,*ltog; 2262 PetscInt nis = iscoloring->n,nctot,*cols; 2263 PetscInt *rowhit,M,cstart,cend,colb; 2264 PetscInt *columnsforrow,l; 2265 IS *isa; 2266 PetscBool done,flg; 2267 ISLocalToGlobalMapping map = mat->cmap->bmapping; 2268 PetscInt ctype=c->ctype; 2269 PetscBool new_impl=PETSC_FALSE; 2270 2271 PetscFunctionBegin; 2272 ierr = PetscOptionsName("-new","using new impls","",&new_impl);CHKERRQ(ierr); 2273 if (new_impl){ 2274 ierr = MatFDColoringCreate_MPIAIJ(mat,iscoloring,c);CHKERRQ(ierr); 2275 PetscFunctionReturn(0); 2276 } 2277 if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMappingBlock"); 2278 2279 if (map) {ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr);} 2280 else ltog = NULL; 2281 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 2282 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2283 2284 M = mat->rmap->n/bs; 2285 cstart = mat->cmap->rstart/bs; 2286 cend = mat->cmap->rend/bs; 2287 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 2288 c->N = mat->cmap->N/bs; 2289 c->m = mat->rmap->n/bs; 2290 c->rstart = mat->rmap->rstart/bs; 2291 2292 c->ncolors = nis; 2293 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr); 2294 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr); 2295 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr); 2296 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr); 2297 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr); 2298 ierr = PetscLogObjectMemory((PetscObject)c,5*nis*sizeof(PetscInt));CHKERRQ(ierr); 2299 2300 /* Allow access to data structures of local part of matrix */ 2301 if (!baij->colmap) { 2302 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2303 } 2304 ierr = MatGetColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 2305 ierr = MatGetColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 2306 2307 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr); 2308 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr); 2309 2310 for (i=0; i<nis; i++) { 2311 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 2312 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 2313 2314 c->ncolumns[i] = n; 2315 if (n) { 2316 ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr); 2317 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 2318 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 2319 } else { 2320 c->columns[i] = 0; 2321 } 2322 2323 if (ctype == IS_COLORING_GLOBAL) { 2324 /* Determine the total (parallel) number of columns of this color */ 2325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 2326 ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr); 2327 2328 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 2329 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2330 nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j]; 2331 if (!nctot) { 2332 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 2333 } 2334 2335 disp[0] = 0; 2336 for (j=1; j<size; j++) { 2337 disp[j] = disp[j-1] + ncolsonproc[j-1]; 2338 } 2339 2340 /* Get complete list of columns for color on each processor */ 2341 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2342 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2343 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 2344 } else if (ctype == IS_COLORING_GHOSTED) { 2345 /* Determine local number of columns of this color on this process, including ghost points */ 2346 nctot = n; 2347 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2348 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 2349 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 2350 2351 /* 2352 Mark all rows affect by these columns 2353 */ 2354 /* Temporary option to allow for debugging/testing */ 2355 flg = PETSC_FALSE; 2356 ierr = PetscOptionsGetBool(NULL,"-matfdcoloring_slow",&flg,NULL);CHKERRQ(ierr); 2357 if (!flg) { /*-----------------------------------------------------------------------------*/ 2358 /* crude, fast version */ 2359 ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr); 2360 /* loop over columns*/ 2361 for (j=0; j<nctot; j++) { 2362 if (ctype == IS_COLORING_GHOSTED) { 2363 col = ltog[cols[j]]; 2364 } else { 2365 col = cols[j]; 2366 } 2367 if (col >= cstart && col < cend) { 2368 /* column is in diagonal block of matrix */ 2369 rows = A_cj + A_ci[col-cstart]; 2370 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2371 } else { 2372 #if defined(PETSC_USE_CTABLE) 2373 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2374 colb--; 2375 #else 2376 colb = baij->colmap[col] - 1; 2377 #endif 2378 if (colb == -1) { 2379 m = 0; 2380 } else { 2381 colb = colb/bs; 2382 rows = B_cj + B_ci[colb]; 2383 m = B_ci[colb+1] - B_ci[colb]; 2384 } 2385 } 2386 /* loop over columns marking them in rowhit */ 2387 for (k=0; k<m; k++) { 2388 rowhit[*rows++] = col + 1; 2389 } 2390 } 2391 2392 /* count the number of hits */ 2393 nrows = 0; 2394 for (j=0; j<M; j++) { 2395 if (rowhit[j]) nrows++; 2396 } 2397 c->nrows[i] = nrows; 2398 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2399 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2400 ierr = PetscLogObjectMemory((PetscObject)c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2401 nrows = 0; 2402 for (j=0; j<M; j++) { 2403 if (rowhit[j]) { 2404 c->rows[i][nrows] = j; 2405 c->columnsforrow[i][nrows] = rowhit[j] - 1; 2406 nrows++; 2407 } 2408 } 2409 } else { /*-------------------------------------------------------------------------------*/ 2410 /* slow version, using rowhit as a linked list */ 2411 PetscInt currentcol,fm,mfm; 2412 rowhit[M] = M; 2413 nrows = 0; 2414 /* loop over columns*/ 2415 for (j=0; j<nctot; j++) { 2416 if (ctype == IS_COLORING_GHOSTED) { 2417 col = ltog[cols[j]]; 2418 } else { 2419 col = cols[j]; 2420 } 2421 if (col >= cstart && col < cend) { 2422 /* column is in diagonal block of matrix */ 2423 rows = A_cj + A_ci[col-cstart]; 2424 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2425 } else { 2426 #if defined(PETSC_USE_CTABLE) 2427 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2428 colb--; 2429 #else 2430 colb = baij->colmap[col] - 1; 2431 #endif 2432 if (colb == -1) { 2433 m = 0; 2434 } else { 2435 colb = colb/bs; 2436 rows = B_cj + B_ci[colb]; 2437 m = B_ci[colb+1] - B_ci[colb]; 2438 } 2439 } 2440 2441 /* loop over columns marking them in rowhit */ 2442 fm = M; /* fm points to first entry in linked list */ 2443 for (k=0; k<m; k++) { 2444 currentcol = *rows++; 2445 /* is it already in the list? */ 2446 do { 2447 mfm = fm; 2448 fm = rowhit[fm]; 2449 } while (fm < currentcol); 2450 /* not in list so add it */ 2451 if (fm != currentcol) { 2452 nrows++; 2453 columnsforrow[currentcol] = col; 2454 /* next three lines insert new entry into linked list */ 2455 rowhit[mfm] = currentcol; 2456 rowhit[currentcol] = fm; 2457 fm = currentcol; 2458 /* fm points to present position in list since we know the columns are sorted */ 2459 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected"); 2460 } 2461 } 2462 c->nrows[i] = nrows; 2463 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2464 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2465 ierr = PetscLogObjectMemory((PetscObject)c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2466 /* now store the linked list of rows into c->rows[i] */ 2467 nrows = 0; 2468 fm = rowhit[M]; 2469 do { 2470 c->rows[i][nrows] = fm; 2471 c->columnsforrow[i][nrows++] = columnsforrow[fm]; 2472 fm = rowhit[fm]; 2473 } while (fm < M); 2474 } /* ---------------------------------------------------------------------------------------*/ 2475 ierr = PetscFree(cols);CHKERRQ(ierr); 2476 } 2477 2478 /* Optimize by adding the vscale, and scaleforrow[][] fields */ 2479 /* 2480 vscale will contain the "diagonal" on processor scalings followed by the off processor 2481 */ 2482 if (ctype == IS_COLORING_GLOBAL) { 2483 PetscInt *garray; 2484 ierr = PetscMalloc(baij->B->cmap->n*sizeof(PetscInt),&garray);CHKERRQ(ierr); 2485 for (i=0; i<baij->B->cmap->n/bs; i++) { 2486 for (j=0; j<bs; j++) { 2487 garray[i*bs+j] = bs*baij->garray[i]+j; 2488 } 2489 } 2490 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),baij->A->rmap->n,PETSC_DETERMINE,baij->B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 2491 ierr = PetscFree(garray);CHKERRQ(ierr); 2492 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2493 for (k=0; k<c->ncolors; k++) { 2494 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2495 for (l=0; l<c->nrows[k]; l++) { 2496 col = c->columnsforrow[k][l]; 2497 if (col >= cstart && col < cend) { 2498 /* column is in diagonal block of matrix */ 2499 colb = col - cstart; 2500 } else { 2501 /* column is in "off-processor" part */ 2502 #if defined(PETSC_USE_CTABLE) 2503 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2504 colb--; 2505 #else 2506 colb = baij->colmap[col] - 1; 2507 #endif 2508 colb = colb/bs; 2509 colb += cend - cstart; 2510 } 2511 c->vscaleforrow[k][l] = colb; 2512 } 2513 } 2514 } else if (ctype == IS_COLORING_GHOSTED) { 2515 /* Get gtol mapping */ 2516 PetscInt N = mat->cmap->N,nlocal,*gtol; 2517 ierr = PetscMalloc((N+1)*sizeof(PetscInt),>ol);CHKERRQ(ierr); 2518 for (i=0; i<N; i++) gtol[i] = -1; 2519 ierr = ISLocalToGlobalMappingGetSize(map,&nlocal);CHKERRQ(ierr); 2520 for (i=0; i<nlocal; i++) gtol[ltog[i]] = i; 2521 2522 c->vscale = 0; /* will be created in MatFDColoringApply() */ 2523 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2524 for (k=0; k<c->ncolors; k++) { 2525 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2526 for (l=0; l<c->nrows[k]; l++) { 2527 col = c->columnsforrow[k][l]; /* global column index */ 2528 2529 c->vscaleforrow[k][l] = gtol[col]; /* local column index */ 2530 } 2531 } 2532 ierr = PetscFree(gtol);CHKERRQ(ierr); 2533 } 2534 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 2535 2536 ierr = PetscFree(rowhit);CHKERRQ(ierr); 2537 ierr = PetscFree(columnsforrow);CHKERRQ(ierr); 2538 ierr = MatRestoreColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 2539 ierr = MatRestoreColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 2540 if (map) {ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr);} 2541 PetscFunctionReturn(0); 2542 } 2543 2544 #undef __FUNCT__ 2545 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2546 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2547 { 2548 Mat B; 2549 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2550 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2551 Mat_SeqAIJ *b; 2552 PetscErrorCode ierr; 2553 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2554 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2555 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2556 2557 PetscFunctionBegin; 2558 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2559 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2560 2561 /* ---------------------------------------------------------------- 2562 Tell every processor the number of nonzeros per row 2563 */ 2564 ierr = PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2565 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2566 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]; 2567 } 2568 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2569 ierr = PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);CHKERRQ(ierr); 2570 displs = recvcounts + size; 2571 for (i=0; i<size; i++) { 2572 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2573 displs[i] = A->rmap->range[i]/bs; 2574 } 2575 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2576 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2577 #else 2578 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2579 #endif 2580 /* --------------------------------------------------------------- 2581 Create the sequential matrix of the same type as the local block diagonal 2582 */ 2583 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2584 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2585 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2586 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2587 b = (Mat_SeqAIJ*)B->data; 2588 2589 /*-------------------------------------------------------------------- 2590 Copy my part of matrix column indices over 2591 */ 2592 sendcount = ad->nz + bd->nz; 2593 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2594 a_jsendbuf = ad->j; 2595 b_jsendbuf = bd->j; 2596 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2597 cnt = 0; 2598 for (i=0; i<n; i++) { 2599 2600 /* put in lower diagonal portion */ 2601 m = bd->i[i+1] - bd->i[i]; 2602 while (m > 0) { 2603 /* is it above diagonal (in bd (compressed) numbering) */ 2604 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2605 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2606 m--; 2607 } 2608 2609 /* put in diagonal portion */ 2610 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2611 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2612 } 2613 2614 /* put in upper diagonal portion */ 2615 while (m-- > 0) { 2616 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2617 } 2618 } 2619 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2620 2621 /*-------------------------------------------------------------------- 2622 Gather all column indices to all processors 2623 */ 2624 for (i=0; i<size; i++) { 2625 recvcounts[i] = 0; 2626 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2627 recvcounts[i] += lens[j]; 2628 } 2629 } 2630 displs[0] = 0; 2631 for (i=1; i<size; i++) { 2632 displs[i] = displs[i-1] + recvcounts[i-1]; 2633 } 2634 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2635 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2636 #else 2637 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2638 #endif 2639 /*-------------------------------------------------------------------- 2640 Assemble the matrix into useable form (note numerical values not yet set) 2641 */ 2642 /* set the b->ilen (length of each row) values */ 2643 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2644 /* set the b->i indices */ 2645 b->i[0] = 0; 2646 for (i=1; i<=A->rmap->N/bs; i++) { 2647 b->i[i] = b->i[i-1] + lens[i-1]; 2648 } 2649 ierr = PetscFree(lens);CHKERRQ(ierr); 2650 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2651 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2652 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2653 2654 if (A->symmetric) { 2655 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2656 } else if (A->hermitian) { 2657 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2658 } else if (A->structurally_symmetric) { 2659 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2660 } 2661 *newmat = B; 2662 PetscFunctionReturn(0); 2663 } 2664 2665 #undef __FUNCT__ 2666 #define __FUNCT__ "MatSOR_MPIBAIJ" 2667 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2668 { 2669 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2670 PetscErrorCode ierr; 2671 Vec bb1 = 0; 2672 2673 PetscFunctionBegin; 2674 if (flag == SOR_APPLY_UPPER) { 2675 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2676 PetscFunctionReturn(0); 2677 } 2678 2679 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2680 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2681 } 2682 2683 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2684 if (flag & SOR_ZERO_INITIAL_GUESS) { 2685 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2686 its--; 2687 } 2688 2689 while (its--) { 2690 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2691 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2692 2693 /* update rhs: bb1 = bb - B*x */ 2694 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2695 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2696 2697 /* local sweep */ 2698 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2699 } 2700 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2701 if (flag & SOR_ZERO_INITIAL_GUESS) { 2702 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2703 its--; 2704 } 2705 while (its--) { 2706 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2707 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2708 2709 /* update rhs: bb1 = bb - B*x */ 2710 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2711 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2712 2713 /* local sweep */ 2714 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2715 } 2716 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2717 if (flag & SOR_ZERO_INITIAL_GUESS) { 2718 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2719 its--; 2720 } 2721 while (its--) { 2722 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2723 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2724 2725 /* update rhs: bb1 = bb - B*x */ 2726 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2727 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2728 2729 /* local sweep */ 2730 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2731 } 2732 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2733 2734 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2735 PetscFunctionReturn(0); 2736 } 2737 2738 extern PetscErrorCode MatFDColoringApply_BAIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2739 2740 #undef __FUNCT__ 2741 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2742 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2743 { 2744 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2745 PetscErrorCode ierr; 2746 2747 PetscFunctionBegin; 2748 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2749 PetscFunctionReturn(0); 2750 } 2751 2752 2753 /* -------------------------------------------------------------------*/ 2754 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2755 MatGetRow_MPIBAIJ, 2756 MatRestoreRow_MPIBAIJ, 2757 MatMult_MPIBAIJ, 2758 /* 4*/ MatMultAdd_MPIBAIJ, 2759 MatMultTranspose_MPIBAIJ, 2760 MatMultTransposeAdd_MPIBAIJ, 2761 0, 2762 0, 2763 0, 2764 /*10*/ 0, 2765 0, 2766 0, 2767 MatSOR_MPIBAIJ, 2768 MatTranspose_MPIBAIJ, 2769 /*15*/ MatGetInfo_MPIBAIJ, 2770 MatEqual_MPIBAIJ, 2771 MatGetDiagonal_MPIBAIJ, 2772 MatDiagonalScale_MPIBAIJ, 2773 MatNorm_MPIBAIJ, 2774 /*20*/ MatAssemblyBegin_MPIBAIJ, 2775 MatAssemblyEnd_MPIBAIJ, 2776 MatSetOption_MPIBAIJ, 2777 MatZeroEntries_MPIBAIJ, 2778 /*24*/ MatZeroRows_MPIBAIJ, 2779 0, 2780 0, 2781 0, 2782 0, 2783 /*29*/ MatSetUp_MPIBAIJ, 2784 0, 2785 0, 2786 0, 2787 0, 2788 /*34*/ MatDuplicate_MPIBAIJ, 2789 0, 2790 0, 2791 0, 2792 0, 2793 /*39*/ MatAXPY_MPIBAIJ, 2794 MatGetSubMatrices_MPIBAIJ, 2795 MatIncreaseOverlap_MPIBAIJ, 2796 MatGetValues_MPIBAIJ, 2797 MatCopy_MPIBAIJ, 2798 /*44*/ 0, 2799 MatScale_MPIBAIJ, 2800 0, 2801 0, 2802 0, 2803 /*49*/ 0, 2804 0, 2805 0, 2806 0, 2807 0, 2808 /*54*/ MatFDColoringCreate_MPIBAIJ, 2809 0, 2810 MatSetUnfactored_MPIBAIJ, 2811 MatPermute_MPIBAIJ, 2812 MatSetValuesBlocked_MPIBAIJ, 2813 /*59*/ MatGetSubMatrix_MPIBAIJ, 2814 MatDestroy_MPIBAIJ, 2815 MatView_MPIBAIJ, 2816 0, 2817 0, 2818 /*64*/ 0, 2819 0, 2820 0, 2821 0, 2822 0, 2823 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2824 0, 2825 0, 2826 0, 2827 0, 2828 /*74*/ 0, 2829 MatFDColoringApply_BAIJ, 2830 0, 2831 0, 2832 0, 2833 /*79*/ 0, 2834 0, 2835 0, 2836 0, 2837 MatLoad_MPIBAIJ, 2838 /*84*/ 0, 2839 0, 2840 0, 2841 0, 2842 0, 2843 /*89*/ 0, 2844 0, 2845 0, 2846 0, 2847 0, 2848 /*94*/ 0, 2849 0, 2850 0, 2851 0, 2852 0, 2853 /*99*/ 0, 2854 0, 2855 0, 2856 0, 2857 0, 2858 /*104*/0, 2859 MatRealPart_MPIBAIJ, 2860 MatImaginaryPart_MPIBAIJ, 2861 0, 2862 0, 2863 /*109*/0, 2864 0, 2865 0, 2866 0, 2867 0, 2868 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2869 0, 2870 MatGetGhosts_MPIBAIJ, 2871 0, 2872 0, 2873 /*119*/0, 2874 0, 2875 0, 2876 0, 2877 MatGetMultiProcBlock_MPIBAIJ, 2878 /*124*/0, 2879 0, 2880 MatInvertBlockDiagonal_MPIBAIJ, 2881 0, 2882 0, 2883 /*129*/ 0, 2884 0, 2885 0, 2886 0, 2887 0, 2888 /*134*/ 0, 2889 0, 2890 0, 2891 0, 2892 0, 2893 /*139*/ 0, 2894 0 2895 }; 2896 2897 #undef __FUNCT__ 2898 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2899 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2900 { 2901 PetscFunctionBegin; 2902 *a = ((Mat_MPIBAIJ*)A->data)->A; 2903 PetscFunctionReturn(0); 2904 } 2905 2906 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2907 2908 #undef __FUNCT__ 2909 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2910 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2911 { 2912 PetscInt m,rstart,cstart,cend; 2913 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2914 const PetscInt *JJ =0; 2915 PetscScalar *values=0; 2916 PetscErrorCode ierr; 2917 2918 PetscFunctionBegin; 2919 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2920 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2921 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2922 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2923 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2924 m = B->rmap->n/bs; 2925 rstart = B->rmap->rstart/bs; 2926 cstart = B->cmap->rstart/bs; 2927 cend = B->cmap->rend/bs; 2928 2929 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2930 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 2931 for (i=0; i<m; i++) { 2932 nz = ii[i+1] - ii[i]; 2933 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2934 nz_max = PetscMax(nz_max,nz); 2935 JJ = jj + ii[i]; 2936 for (j=0; j<nz; j++) { 2937 if (*JJ >= cstart) break; 2938 JJ++; 2939 } 2940 d = 0; 2941 for (; j<nz; j++) { 2942 if (*JJ++ >= cend) break; 2943 d++; 2944 } 2945 d_nnz[i] = d; 2946 o_nnz[i] = nz - d; 2947 } 2948 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2949 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2950 2951 values = (PetscScalar*)V; 2952 if (!values) { 2953 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2954 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2955 } 2956 for (i=0; i<m; i++) { 2957 PetscInt row = i + rstart; 2958 PetscInt ncols = ii[i+1] - ii[i]; 2959 const PetscInt *icols = jj + ii[i]; 2960 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2961 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2962 } 2963 2964 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2965 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2966 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2967 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2968 PetscFunctionReturn(0); 2969 } 2970 2971 #undef __FUNCT__ 2972 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2973 /*@C 2974 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2975 (the default parallel PETSc format). 2976 2977 Collective on MPI_Comm 2978 2979 Input Parameters: 2980 + A - the matrix 2981 . bs - the block size 2982 . i - the indices into j for the start of each local row (starts with zero) 2983 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2984 - v - optional values in the matrix 2985 2986 Level: developer 2987 2988 .keywords: matrix, aij, compressed row, sparse, parallel 2989 2990 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2991 @*/ 2992 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2993 { 2994 PetscErrorCode ierr; 2995 2996 PetscFunctionBegin; 2997 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2998 PetscValidType(B,1); 2999 PetscValidLogicalCollectiveInt(B,bs,2); 3000 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 3001 PetscFunctionReturn(0); 3002 } 3003 3004 #undef __FUNCT__ 3005 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 3006 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 3007 { 3008 Mat_MPIBAIJ *b; 3009 PetscErrorCode ierr; 3010 PetscInt i; 3011 3012 PetscFunctionBegin; 3013 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 3014 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 3015 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3016 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3017 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 3018 3019 if (d_nnz) { 3020 for (i=0; i<B->rmap->n/bs; i++) { 3021 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]); 3022 } 3023 } 3024 if (o_nnz) { 3025 for (i=0; i<B->rmap->n/bs; i++) { 3026 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]); 3027 } 3028 } 3029 3030 b = (Mat_MPIBAIJ*)B->data; 3031 b->bs2 = bs*bs; 3032 b->mbs = B->rmap->n/bs; 3033 b->nbs = B->cmap->n/bs; 3034 b->Mbs = B->rmap->N/bs; 3035 b->Nbs = B->cmap->N/bs; 3036 3037 for (i=0; i<=b->size; i++) { 3038 b->rangebs[i] = B->rmap->range[i]/bs; 3039 } 3040 b->rstartbs = B->rmap->rstart/bs; 3041 b->rendbs = B->rmap->rend/bs; 3042 b->cstartbs = B->cmap->rstart/bs; 3043 b->cendbs = B->cmap->rend/bs; 3044 3045 if (!B->preallocated) { 3046 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3047 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3048 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 3049 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3050 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3051 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3052 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 3053 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3054 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 3055 } 3056 3057 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3058 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 3059 B->preallocated = PETSC_TRUE; 3060 PetscFunctionReturn(0); 3061 } 3062 3063 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 3064 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 3065 3066 #undef __FUNCT__ 3067 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 3068 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 3069 { 3070 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 3071 PetscErrorCode ierr; 3072 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 3073 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 3074 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 3075 3076 PetscFunctionBegin; 3077 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 3078 ii[0] = 0; 3079 for (i=0; i<M; i++) { 3080 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]); 3081 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]); 3082 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 3083 /* remove one from count of matrix has diagonal */ 3084 for (j=id[i]; j<id[i+1]; j++) { 3085 if (jd[j] == i) {ii[i+1]--;break;} 3086 } 3087 } 3088 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 3089 cnt = 0; 3090 for (i=0; i<M; i++) { 3091 for (j=io[i]; j<io[i+1]; j++) { 3092 if (garray[jo[j]] > rstart) break; 3093 jj[cnt++] = garray[jo[j]]; 3094 } 3095 for (k=id[i]; k<id[i+1]; k++) { 3096 if (jd[k] != i) { 3097 jj[cnt++] = rstart + jd[k]; 3098 } 3099 } 3100 for (; j<io[i+1]; j++) { 3101 jj[cnt++] = garray[jo[j]]; 3102 } 3103 } 3104 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 3105 PetscFunctionReturn(0); 3106 } 3107 3108 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3109 3110 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 3111 3112 #undef __FUNCT__ 3113 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 3114 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 3115 { 3116 PetscErrorCode ierr; 3117 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3118 Mat B; 3119 Mat_MPIAIJ *b; 3120 3121 PetscFunctionBegin; 3122 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 3123 3124 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 3125 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 3126 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 3127 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3128 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 3129 b = (Mat_MPIAIJ*) B->data; 3130 3131 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 3132 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3133 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 3134 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 3135 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 3136 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3137 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3138 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3139 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3140 if (reuse == MAT_REUSE_MATRIX) { 3141 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 3142 } else { 3143 *newmat = B; 3144 } 3145 PetscFunctionReturn(0); 3146 } 3147 3148 #if defined(PETSC_HAVE_MUMPS) 3149 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 3150 #endif 3151 3152 /*MC 3153 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 3154 3155 Options Database Keys: 3156 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3157 . -mat_block_size <bs> - set the blocksize used to store the matrix 3158 - -mat_use_hash_table <fact> 3159 3160 Level: beginner 3161 3162 .seealso: MatCreateMPIBAIJ 3163 M*/ 3164 3165 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3166 3167 #undef __FUNCT__ 3168 #define __FUNCT__ "MatCreate_MPIBAIJ" 3169 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3170 { 3171 Mat_MPIBAIJ *b; 3172 PetscErrorCode ierr; 3173 PetscBool flg; 3174 3175 PetscFunctionBegin; 3176 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 3177 B->data = (void*)b; 3178 3179 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3180 B->assembled = PETSC_FALSE; 3181 3182 B->insertmode = NOT_SET_VALUES; 3183 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3184 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3185 3186 /* build local table of row and column ownerships */ 3187 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 3188 3189 /* build cache for off array entries formed */ 3190 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3191 3192 b->donotstash = PETSC_FALSE; 3193 b->colmap = NULL; 3194 b->garray = NULL; 3195 b->roworiented = PETSC_TRUE; 3196 3197 /* stuff used in block assembly */ 3198 b->barray = 0; 3199 3200 /* stuff used for matrix vector multiply */ 3201 b->lvec = 0; 3202 b->Mvctx = 0; 3203 3204 /* stuff for MatGetRow() */ 3205 b->rowindices = 0; 3206 b->rowvalues = 0; 3207 b->getrowactive = PETSC_FALSE; 3208 3209 /* hash table stuff */ 3210 b->ht = 0; 3211 b->hd = 0; 3212 b->ht_size = 0; 3213 b->ht_flag = PETSC_FALSE; 3214 b->ht_fact = 0; 3215 b->ht_total_ct = 0; 3216 b->ht_insert_ct = 0; 3217 3218 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3219 b->ijonly = PETSC_FALSE; 3220 3221 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3222 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3223 if (flg) { 3224 PetscReal fact = 1.39; 3225 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3226 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3227 if (fact <= 1.0) fact = 1.39; 3228 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3229 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3230 } 3231 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3232 3233 #if defined(PETSC_HAVE_MUMPS) 3234 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3235 #endif 3236 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3237 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3238 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3239 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3240 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3241 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3242 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3243 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3244 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3245 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3246 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3247 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3248 PetscFunctionReturn(0); 3249 } 3250 3251 /*MC 3252 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3253 3254 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3255 and MATMPIBAIJ otherwise. 3256 3257 Options Database Keys: 3258 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3259 3260 Level: beginner 3261 3262 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3263 M*/ 3264 3265 #undef __FUNCT__ 3266 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3267 /*@C 3268 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3269 (block compressed row). For good matrix assembly performance 3270 the user should preallocate the matrix storage by setting the parameters 3271 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3272 performance can be increased by more than a factor of 50. 3273 3274 Collective on Mat 3275 3276 Input Parameters: 3277 + A - the matrix 3278 . bs - size of block 3279 . d_nz - number of block nonzeros per block row in diagonal portion of local 3280 submatrix (same for all local rows) 3281 . d_nnz - array containing the number of block nonzeros in the various block rows 3282 of the in diagonal portion of the local (possibly different for each block 3283 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3284 set it even if it is zero. 3285 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3286 submatrix (same for all local rows). 3287 - o_nnz - array containing the number of nonzeros in the various block rows of the 3288 off-diagonal portion of the local submatrix (possibly different for 3289 each block row) or NULL. 3290 3291 If the *_nnz parameter is given then the *_nz parameter is ignored 3292 3293 Options Database Keys: 3294 + -mat_block_size - size of the blocks to use 3295 - -mat_use_hash_table <fact> 3296 3297 Notes: 3298 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3299 than it must be used on all processors that share the object for that argument. 3300 3301 Storage Information: 3302 For a square global matrix we define each processor's diagonal portion 3303 to be its local rows and the corresponding columns (a square submatrix); 3304 each processor's off-diagonal portion encompasses the remainder of the 3305 local matrix (a rectangular submatrix). 3306 3307 The user can specify preallocated storage for the diagonal part of 3308 the local submatrix with either d_nz or d_nnz (not both). Set 3309 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3310 memory allocation. Likewise, specify preallocated storage for the 3311 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3312 3313 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3314 the figure below we depict these three local rows and all columns (0-11). 3315 3316 .vb 3317 0 1 2 3 4 5 6 7 8 9 10 11 3318 -------------------------- 3319 row 3 |o o o d d d o o o o o o 3320 row 4 |o o o d d d o o o o o o 3321 row 5 |o o o d d d o o o o o o 3322 -------------------------- 3323 .ve 3324 3325 Thus, any entries in the d locations are stored in the d (diagonal) 3326 submatrix, and any entries in the o locations are stored in the 3327 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3328 stored simply in the MATSEQBAIJ format for compressed row storage. 3329 3330 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3331 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3332 In general, for PDE problems in which most nonzeros are near the diagonal, 3333 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3334 or you will get TERRIBLE performance; see the users' manual chapter on 3335 matrices. 3336 3337 You can call MatGetInfo() to get information on how effective the preallocation was; 3338 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3339 You can also run with the option -info and look for messages with the string 3340 malloc in them to see if additional memory allocation was needed. 3341 3342 Level: intermediate 3343 3344 .keywords: matrix, block, aij, compressed row, sparse, parallel 3345 3346 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3347 @*/ 3348 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3349 { 3350 PetscErrorCode ierr; 3351 3352 PetscFunctionBegin; 3353 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3354 PetscValidType(B,1); 3355 PetscValidLogicalCollectiveInt(B,bs,2); 3356 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); 3357 PetscFunctionReturn(0); 3358 } 3359 3360 #undef __FUNCT__ 3361 #define __FUNCT__ "MatCreateBAIJ" 3362 /*@C 3363 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3364 (block compressed row). For good matrix assembly performance 3365 the user should preallocate the matrix storage by setting the parameters 3366 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3367 performance can be increased by more than a factor of 50. 3368 3369 Collective on MPI_Comm 3370 3371 Input Parameters: 3372 + comm - MPI communicator 3373 . bs - size of blockk 3374 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3375 This value should be the same as the local size used in creating the 3376 y vector for the matrix-vector product y = Ax. 3377 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3378 This value should be the same as the local size used in creating the 3379 x vector for the matrix-vector product y = Ax. 3380 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3381 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3382 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3383 submatrix (same for all local rows) 3384 . d_nnz - array containing the number of nonzero blocks in the various block rows 3385 of the in diagonal portion of the local (possibly different for each block 3386 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3387 and set it even if it is zero. 3388 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3389 submatrix (same for all local rows). 3390 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3391 off-diagonal portion of the local submatrix (possibly different for 3392 each block row) or NULL. 3393 3394 Output Parameter: 3395 . A - the matrix 3396 3397 Options Database Keys: 3398 + -mat_block_size - size of the blocks to use 3399 - -mat_use_hash_table <fact> 3400 3401 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3402 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3403 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3404 3405 Notes: 3406 If the *_nnz parameter is given then the *_nz parameter is ignored 3407 3408 A nonzero block is any block that as 1 or more nonzeros in it 3409 3410 The user MUST specify either the local or global matrix dimensions 3411 (possibly both). 3412 3413 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3414 than it must be used on all processors that share the object for that argument. 3415 3416 Storage Information: 3417 For a square global matrix we define each processor's diagonal portion 3418 to be its local rows and the corresponding columns (a square submatrix); 3419 each processor's off-diagonal portion encompasses the remainder of the 3420 local matrix (a rectangular submatrix). 3421 3422 The user can specify preallocated storage for the diagonal part of 3423 the local submatrix with either d_nz or d_nnz (not both). Set 3424 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3425 memory allocation. Likewise, specify preallocated storage for the 3426 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3427 3428 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3429 the figure below we depict these three local rows and all columns (0-11). 3430 3431 .vb 3432 0 1 2 3 4 5 6 7 8 9 10 11 3433 -------------------------- 3434 row 3 |o o o d d d o o o o o o 3435 row 4 |o o o d d d o o o o o o 3436 row 5 |o o o d d d o o o o o o 3437 -------------------------- 3438 .ve 3439 3440 Thus, any entries in the d locations are stored in the d (diagonal) 3441 submatrix, and any entries in the o locations are stored in the 3442 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3443 stored simply in the MATSEQBAIJ format for compressed row storage. 3444 3445 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3446 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3447 In general, for PDE problems in which most nonzeros are near the diagonal, 3448 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3449 or you will get TERRIBLE performance; see the users' manual chapter on 3450 matrices. 3451 3452 Level: intermediate 3453 3454 .keywords: matrix, block, aij, compressed row, sparse, parallel 3455 3456 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3457 @*/ 3458 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) 3459 { 3460 PetscErrorCode ierr; 3461 PetscMPIInt size; 3462 3463 PetscFunctionBegin; 3464 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3465 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3466 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3467 if (size > 1) { 3468 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3469 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3470 } else { 3471 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3472 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3473 } 3474 PetscFunctionReturn(0); 3475 } 3476 3477 #undef __FUNCT__ 3478 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3479 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3480 { 3481 Mat mat; 3482 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3483 PetscErrorCode ierr; 3484 PetscInt len=0; 3485 3486 PetscFunctionBegin; 3487 *newmat = 0; 3488 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3489 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3490 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3491 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3492 3493 mat->factortype = matin->factortype; 3494 mat->preallocated = PETSC_TRUE; 3495 mat->assembled = PETSC_TRUE; 3496 mat->insertmode = NOT_SET_VALUES; 3497 3498 a = (Mat_MPIBAIJ*)mat->data; 3499 mat->rmap->bs = matin->rmap->bs; 3500 a->bs2 = oldmat->bs2; 3501 a->mbs = oldmat->mbs; 3502 a->nbs = oldmat->nbs; 3503 a->Mbs = oldmat->Mbs; 3504 a->Nbs = oldmat->Nbs; 3505 3506 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3507 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3508 3509 a->size = oldmat->size; 3510 a->rank = oldmat->rank; 3511 a->donotstash = oldmat->donotstash; 3512 a->roworiented = oldmat->roworiented; 3513 a->rowindices = 0; 3514 a->rowvalues = 0; 3515 a->getrowactive = PETSC_FALSE; 3516 a->barray = 0; 3517 a->rstartbs = oldmat->rstartbs; 3518 a->rendbs = oldmat->rendbs; 3519 a->cstartbs = oldmat->cstartbs; 3520 a->cendbs = oldmat->cendbs; 3521 3522 /* hash table stuff */ 3523 a->ht = 0; 3524 a->hd = 0; 3525 a->ht_size = 0; 3526 a->ht_flag = oldmat->ht_flag; 3527 a->ht_fact = oldmat->ht_fact; 3528 a->ht_total_ct = 0; 3529 a->ht_insert_ct = 0; 3530 3531 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3532 if (oldmat->colmap) { 3533 #if defined(PETSC_USE_CTABLE) 3534 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3535 #else 3536 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3537 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3538 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3539 #endif 3540 } else a->colmap = 0; 3541 3542 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3543 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3544 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3545 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3546 } else a->garray = 0; 3547 3548 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3549 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3550 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3551 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3552 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3553 3554 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3555 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3556 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3557 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3558 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3559 *newmat = mat; 3560 PetscFunctionReturn(0); 3561 } 3562 3563 #undef __FUNCT__ 3564 #define __FUNCT__ "MatLoad_MPIBAIJ" 3565 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3566 { 3567 PetscErrorCode ierr; 3568 int fd; 3569 PetscInt i,nz,j,rstart,rend; 3570 PetscScalar *vals,*buf; 3571 MPI_Comm comm; 3572 MPI_Status status; 3573 PetscMPIInt rank,size,maxnz; 3574 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3575 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3576 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3577 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3578 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3579 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3580 3581 PetscFunctionBegin; 3582 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3583 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3584 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3585 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3586 3587 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3588 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3589 if (!rank) { 3590 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3591 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3592 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3593 } 3594 3595 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3596 3597 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3598 M = header[1]; N = header[2]; 3599 3600 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3601 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3602 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3603 3604 /* If global sizes are set, check if they are consistent with that given in the file */ 3605 if (sizesset) { 3606 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3607 } 3608 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); 3609 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); 3610 3611 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3612 3613 /* 3614 This code adds extra rows to make sure the number of rows is 3615 divisible by the blocksize 3616 */ 3617 Mbs = M/bs; 3618 extra_rows = bs - M + bs*Mbs; 3619 if (extra_rows == bs) extra_rows = 0; 3620 else Mbs++; 3621 if (extra_rows && !rank) { 3622 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3623 } 3624 3625 /* determine ownership of all rows */ 3626 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3627 mbs = Mbs/size + ((Mbs % size) > rank); 3628 m = mbs*bs; 3629 } else { /* User set */ 3630 m = newmat->rmap->n; 3631 mbs = m/bs; 3632 } 3633 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 3634 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3635 3636 /* process 0 needs enough room for process with most rows */ 3637 if (!rank) { 3638 mmax = rowners[1]; 3639 for (i=2; i<=size; i++) { 3640 mmax = PetscMax(mmax,rowners[i]); 3641 } 3642 mmax*=bs; 3643 } else mmax = -1; /* unused, but compiler warns anyway */ 3644 3645 rowners[0] = 0; 3646 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3647 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3648 rstart = rowners[rank]; 3649 rend = rowners[rank+1]; 3650 3651 /* distribute row lengths to all processors */ 3652 ierr = PetscMalloc(m*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 3653 if (!rank) { 3654 mend = m; 3655 if (size == 1) mend = mend - extra_rows; 3656 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3657 for (j=mend; j<m; j++) locrowlens[j] = 1; 3658 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3659 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3660 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3661 for (j=0; j<m; j++) { 3662 procsnz[0] += locrowlens[j]; 3663 } 3664 for (i=1; i<size; i++) { 3665 mend = browners[i+1] - browners[i]; 3666 if (i == size-1) mend = mend - extra_rows; 3667 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3668 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3669 /* calculate the number of nonzeros on each processor */ 3670 for (j=0; j<browners[i+1]-browners[i]; j++) { 3671 procsnz[i] += rowlengths[j]; 3672 } 3673 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3674 } 3675 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3676 } else { 3677 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3678 } 3679 3680 if (!rank) { 3681 /* determine max buffer needed and allocate it */ 3682 maxnz = procsnz[0]; 3683 for (i=1; i<size; i++) { 3684 maxnz = PetscMax(maxnz,procsnz[i]); 3685 } 3686 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3687 3688 /* read in my part of the matrix column indices */ 3689 nz = procsnz[0]; 3690 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3691 mycols = ibuf; 3692 if (size == 1) nz -= extra_rows; 3693 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3694 if (size == 1) { 3695 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3696 } 3697 3698 /* read in every ones (except the last) and ship off */ 3699 for (i=1; i<size-1; i++) { 3700 nz = procsnz[i]; 3701 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3702 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3703 } 3704 /* read in the stuff for the last proc */ 3705 if (size != 1) { 3706 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3707 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3708 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3709 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3710 } 3711 ierr = PetscFree(cols);CHKERRQ(ierr); 3712 } else { 3713 /* determine buffer space needed for message */ 3714 nz = 0; 3715 for (i=0; i<m; i++) { 3716 nz += locrowlens[i]; 3717 } 3718 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3719 mycols = ibuf; 3720 /* receive message of column indices*/ 3721 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3722 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3723 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3724 } 3725 3726 /* loop over local rows, determining number of off diagonal entries */ 3727 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3728 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3729 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3730 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3731 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3732 rowcount = 0; nzcount = 0; 3733 for (i=0; i<mbs; i++) { 3734 dcount = 0; 3735 odcount = 0; 3736 for (j=0; j<bs; j++) { 3737 kmax = locrowlens[rowcount]; 3738 for (k=0; k<kmax; k++) { 3739 tmp = mycols[nzcount++]/bs; 3740 if (!mask[tmp]) { 3741 mask[tmp] = 1; 3742 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3743 else masked1[dcount++] = tmp; 3744 } 3745 } 3746 rowcount++; 3747 } 3748 3749 dlens[i] = dcount; 3750 odlens[i] = odcount; 3751 3752 /* zero out the mask elements we set */ 3753 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3754 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3755 } 3756 3757 3758 if (!sizesset) { 3759 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3760 } 3761 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3762 3763 if (!rank) { 3764 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3765 /* read in my part of the matrix numerical values */ 3766 nz = procsnz[0]; 3767 vals = buf; 3768 mycols = ibuf; 3769 if (size == 1) nz -= extra_rows; 3770 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3771 if (size == 1) { 3772 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3773 } 3774 3775 /* insert into matrix */ 3776 jj = rstart*bs; 3777 for (i=0; i<m; i++) { 3778 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3779 mycols += locrowlens[i]; 3780 vals += locrowlens[i]; 3781 jj++; 3782 } 3783 /* read in other processors (except the last one) and ship out */ 3784 for (i=1; i<size-1; i++) { 3785 nz = procsnz[i]; 3786 vals = buf; 3787 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3788 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3789 } 3790 /* the last proc */ 3791 if (size != 1) { 3792 nz = procsnz[i] - extra_rows; 3793 vals = buf; 3794 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3795 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3796 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3797 } 3798 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3799 } else { 3800 /* receive numeric values */ 3801 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3802 3803 /* receive message of values*/ 3804 vals = buf; 3805 mycols = ibuf; 3806 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3807 3808 /* insert into matrix */ 3809 jj = rstart*bs; 3810 for (i=0; i<m; i++) { 3811 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3812 mycols += locrowlens[i]; 3813 vals += locrowlens[i]; 3814 jj++; 3815 } 3816 } 3817 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3818 ierr = PetscFree(buf);CHKERRQ(ierr); 3819 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3820 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3821 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3822 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3823 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3824 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3825 PetscFunctionReturn(0); 3826 } 3827 3828 #undef __FUNCT__ 3829 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3830 /*@ 3831 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3832 3833 Input Parameters: 3834 . mat - the matrix 3835 . fact - factor 3836 3837 Not Collective, each process can use a different factor 3838 3839 Level: advanced 3840 3841 Notes: 3842 This can also be set by the command line option: -mat_use_hash_table <fact> 3843 3844 .keywords: matrix, hashtable, factor, HT 3845 3846 .seealso: MatSetOption() 3847 @*/ 3848 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3849 { 3850 PetscErrorCode ierr; 3851 3852 PetscFunctionBegin; 3853 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3854 PetscFunctionReturn(0); 3855 } 3856 3857 #undef __FUNCT__ 3858 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3859 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3860 { 3861 Mat_MPIBAIJ *baij; 3862 3863 PetscFunctionBegin; 3864 baij = (Mat_MPIBAIJ*)mat->data; 3865 baij->ht_fact = fact; 3866 PetscFunctionReturn(0); 3867 } 3868 3869 #undef __FUNCT__ 3870 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3871 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3872 { 3873 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3874 3875 PetscFunctionBegin; 3876 *Ad = a->A; 3877 *Ao = a->B; 3878 *colmap = a->garray; 3879 PetscFunctionReturn(0); 3880 } 3881 3882 /* 3883 Special version for direct calls from Fortran (to eliminate two function call overheads 3884 */ 3885 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3886 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3887 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3888 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3889 #endif 3890 3891 #undef __FUNCT__ 3892 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3893 /*@C 3894 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3895 3896 Collective on Mat 3897 3898 Input Parameters: 3899 + mat - the matrix 3900 . min - number of input rows 3901 . im - input rows 3902 . nin - number of input columns 3903 . in - input columns 3904 . v - numerical values input 3905 - addvin - INSERT_VALUES or ADD_VALUES 3906 3907 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3908 3909 Level: advanced 3910 3911 .seealso: MatSetValuesBlocked() 3912 @*/ 3913 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3914 { 3915 /* convert input arguments to C version */ 3916 Mat mat = *matin; 3917 PetscInt m = *min, n = *nin; 3918 InsertMode addv = *addvin; 3919 3920 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3921 const MatScalar *value; 3922 MatScalar *barray = baij->barray; 3923 PetscBool roworiented = baij->roworiented; 3924 PetscErrorCode ierr; 3925 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3926 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3927 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3928 3929 PetscFunctionBegin; 3930 /* tasks normally handled by MatSetValuesBlocked() */ 3931 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3932 #if defined(PETSC_USE_DEBUG) 3933 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3934 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3935 #endif 3936 if (mat->assembled) { 3937 mat->was_assembled = PETSC_TRUE; 3938 mat->assembled = PETSC_FALSE; 3939 } 3940 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3941 3942 3943 if (!barray) { 3944 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3945 baij->barray = barray; 3946 } 3947 3948 if (roworiented) stepval = (n-1)*bs; 3949 else stepval = (m-1)*bs; 3950 3951 for (i=0; i<m; i++) { 3952 if (im[i] < 0) continue; 3953 #if defined(PETSC_USE_DEBUG) 3954 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); 3955 #endif 3956 if (im[i] >= rstart && im[i] < rend) { 3957 row = im[i] - rstart; 3958 for (j=0; j<n; j++) { 3959 /* If NumCol = 1 then a copy is not required */ 3960 if ((roworiented) && (n == 1)) { 3961 barray = (MatScalar*)v + i*bs2; 3962 } else if ((!roworiented) && (m == 1)) { 3963 barray = (MatScalar*)v + j*bs2; 3964 } else { /* Here a copy is required */ 3965 if (roworiented) { 3966 value = v + i*(stepval+bs)*bs + j*bs; 3967 } else { 3968 value = v + j*(stepval+bs)*bs + i*bs; 3969 } 3970 for (ii=0; ii<bs; ii++,value+=stepval) { 3971 for (jj=0; jj<bs; jj++) { 3972 *barray++ = *value++; 3973 } 3974 } 3975 barray -=bs2; 3976 } 3977 3978 if (in[j] >= cstart && in[j] < cend) { 3979 col = in[j] - cstart; 3980 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3981 } else if (in[j] < 0) continue; 3982 #if defined(PETSC_USE_DEBUG) 3983 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); 3984 #endif 3985 else { 3986 if (mat->was_assembled) { 3987 if (!baij->colmap) { 3988 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3989 } 3990 3991 #if defined(PETSC_USE_DEBUG) 3992 #if defined(PETSC_USE_CTABLE) 3993 { PetscInt data; 3994 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3995 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3996 } 3997 #else 3998 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3999 #endif 4000 #endif 4001 #if defined(PETSC_USE_CTABLE) 4002 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4003 col = (col - 1)/bs; 4004 #else 4005 col = (baij->colmap[in[j]] - 1)/bs; 4006 #endif 4007 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 4008 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 4009 col = in[j]; 4010 } 4011 } else col = in[j]; 4012 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 4013 } 4014 } 4015 } else { 4016 if (!baij->donotstash) { 4017 if (roworiented) { 4018 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4019 } else { 4020 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4021 } 4022 } 4023 } 4024 } 4025 4026 /* task normally handled by MatSetValuesBlocked() */ 4027 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 4028 PetscFunctionReturn(0); 4029 } 4030 4031 #undef __FUNCT__ 4032 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 4033 /*@ 4034 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 4035 CSR format the local rows. 4036 4037 Collective on MPI_Comm 4038 4039 Input Parameters: 4040 + comm - MPI communicator 4041 . bs - the block size, only a block size of 1 is supported 4042 . m - number of local rows (Cannot be PETSC_DECIDE) 4043 . n - This value should be the same as the local size used in creating the 4044 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4045 calculated if N is given) For square matrices n is almost always m. 4046 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4047 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4048 . i - row indices 4049 . j - column indices 4050 - a - matrix values 4051 4052 Output Parameter: 4053 . mat - the matrix 4054 4055 Level: intermediate 4056 4057 Notes: 4058 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4059 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4060 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4061 4062 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4063 4064 .keywords: matrix, aij, compressed row, sparse, parallel 4065 4066 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4067 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4068 @*/ 4069 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) 4070 { 4071 PetscErrorCode ierr; 4072 4073 PetscFunctionBegin; 4074 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4075 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4076 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4077 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4078 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 4079 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 4080 PetscFunctionReturn(0); 4081 } 4082