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++) {if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;} 29 } 30 31 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 32 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 33 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 34 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 35 36 for (i=0; i<A->rmap->n; i++){ 37 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {va[i] = vb[i]; if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);} 38 } 39 40 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 41 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 42 ierr = PetscFree(idxb);CHKERRQ(ierr); 43 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 44 PetscFunctionReturn(0); 45 } 46 47 EXTERN_C_BEGIN 48 #undef __FUNCT__ 49 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 50 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 51 { 52 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 53 PetscErrorCode ierr; 54 55 PetscFunctionBegin; 56 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 57 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 58 PetscFunctionReturn(0); 59 } 60 EXTERN_C_END 61 62 EXTERN_C_BEGIN 63 #undef __FUNCT__ 64 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 65 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 66 { 67 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 68 PetscErrorCode ierr; 69 70 PetscFunctionBegin; 71 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 72 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 73 PetscFunctionReturn(0); 74 } 75 EXTERN_C_END 76 77 /* 78 Local utility routine that creates a mapping from the global column 79 number to the local number in the off-diagonal part of the local 80 storage of the matrix. This is done in a non scalable way since the 81 length of colmap equals the global matrix length. 82 */ 83 #undef __FUNCT__ 84 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 85 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 86 { 87 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 88 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 89 PetscErrorCode ierr; 90 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 91 92 PetscFunctionBegin; 93 #if defined (PETSC_USE_CTABLE) 94 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 95 for (i=0; i<nbs; i++){ 96 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 97 } 98 #else 99 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 100 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 101 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 102 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 103 #endif 104 PetscFunctionReturn(0); 105 } 106 107 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 108 { \ 109 \ 110 brow = row/bs; \ 111 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 112 rmax = aimax[brow]; nrow = ailen[brow]; \ 113 bcol = col/bs; \ 114 ridx = row % bs; cidx = col % bs; \ 115 low = 0; high = nrow; \ 116 while (high-low > 3) { \ 117 t = (low+high)/2; \ 118 if (rp[t] > bcol) high = t; \ 119 else low = t; \ 120 } \ 121 for (_i=low; _i<high; _i++) { \ 122 if (rp[_i] > bcol) break; \ 123 if (rp[_i] == bcol) { \ 124 bap = ap + bs2*_i + bs*cidx + ridx; \ 125 if (addv == ADD_VALUES) *bap += value; \ 126 else *bap = value; \ 127 goto a_noinsert; \ 128 } \ 129 } \ 130 if (a->nonew == 1) goto a_noinsert; \ 131 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 132 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 133 N = nrow++ - 1; \ 134 /* shift up all the later entries in this row */ \ 135 for (ii=N; ii>=_i; ii--) { \ 136 rp[ii+1] = rp[ii]; \ 137 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 138 } \ 139 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 140 rp[_i] = bcol; \ 141 ap[bs2*_i + bs*cidx + ridx] = value; \ 142 a_noinsert:; \ 143 ailen[brow] = nrow; \ 144 } 145 146 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 147 { \ 148 brow = row/bs; \ 149 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 150 rmax = bimax[brow]; nrow = bilen[brow]; \ 151 bcol = col/bs; \ 152 ridx = row % bs; cidx = col % bs; \ 153 low = 0; high = nrow; \ 154 while (high-low > 3) { \ 155 t = (low+high)/2; \ 156 if (rp[t] > bcol) high = t; \ 157 else low = t; \ 158 } \ 159 for (_i=low; _i<high; _i++) { \ 160 if (rp[_i] > bcol) break; \ 161 if (rp[_i] == bcol) { \ 162 bap = ap + bs2*_i + bs*cidx + ridx; \ 163 if (addv == ADD_VALUES) *bap += value; \ 164 else *bap = value; \ 165 goto b_noinsert; \ 166 } \ 167 } \ 168 if (b->nonew == 1) goto b_noinsert; \ 169 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 170 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 171 CHKMEMQ;\ 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]; else value = v[i+j*m]; 226 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 227 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 228 } else if (in[j] < 0) continue; 229 #if defined(PETSC_USE_DEBUG) 230 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); 231 #endif 232 else { 233 if (mat->was_assembled) { 234 if (!baij->colmap) { 235 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 236 } 237 #if defined (PETSC_USE_CTABLE) 238 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 239 col = col - 1; 240 #else 241 col = baij->colmap[in[j]/bs] - 1; 242 #endif 243 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 244 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 245 col = in[j]; 246 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 247 B = baij->B; 248 b = (Mat_SeqBAIJ*)(B)->data; 249 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 250 ba=b->a; 251 } else col += in[j]%bs; 252 } else col = in[j]; 253 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 254 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 255 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 256 } 257 } 258 } else { 259 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]); 260 if (!baij->donotstash) { 261 mat->assembled = PETSC_FALSE; 262 if (roworiented) { 263 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 264 } else { 265 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 266 } 267 } 268 } 269 } 270 PetscFunctionReturn(0); 271 } 272 273 #undef __FUNCT__ 274 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 275 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 276 { 277 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 278 const PetscScalar *value; 279 MatScalar *barray=baij->barray; 280 PetscBool roworiented = baij->roworiented; 281 PetscErrorCode ierr; 282 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 283 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 284 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 285 286 PetscFunctionBegin; 287 if(!barray) { 288 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 289 baij->barray = barray; 290 } 291 292 if (roworiented) { 293 stepval = (n-1)*bs; 294 } else { 295 stepval = (m-1)*bs; 296 } 297 for (i=0; i<m; i++) { 298 if (im[i] < 0) continue; 299 #if defined(PETSC_USE_DEBUG) 300 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); 301 #endif 302 if (im[i] >= rstart && im[i] < rend) { 303 row = im[i] - rstart; 304 for (j=0; j<n; j++) { 305 /* If NumCol = 1 then a copy is not required */ 306 if ((roworiented) && (n == 1)) { 307 barray = (MatScalar*)v + i*bs2; 308 } else if((!roworiented) && (m == 1)) { 309 barray = (MatScalar*)v + j*bs2; 310 } else { /* Here a copy is required */ 311 if (roworiented) { 312 value = v + (i*(stepval+bs) + j)*bs; 313 } else { 314 value = v + (j*(stepval+bs) + i)*bs; 315 } 316 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 317 for (jj=0; jj<bs; jj++) { 318 barray[jj] = value[jj]; 319 } 320 barray += bs; 321 } 322 barray -= bs2; 323 } 324 325 if (in[j] >= cstart && in[j] < cend){ 326 col = in[j] - cstart; 327 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 328 } 329 else if (in[j] < 0) continue; 330 #if defined(PETSC_USE_DEBUG) 331 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); 332 #endif 333 else { 334 if (mat->was_assembled) { 335 if (!baij->colmap) { 336 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 337 } 338 339 #if defined(PETSC_USE_DEBUG) 340 #if defined (PETSC_USE_CTABLE) 341 { PetscInt data; 342 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 343 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 344 } 345 #else 346 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 347 #endif 348 #endif 349 #if defined (PETSC_USE_CTABLE) 350 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 351 col = (col - 1)/bs; 352 #else 353 col = (baij->colmap[in[j]] - 1)/bs; 354 #endif 355 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 356 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 357 col = in[j]; 358 } 359 } 360 else col = in[j]; 361 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 362 } 363 } 364 } else { 365 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]); 366 if (!baij->donotstash) { 367 if (roworiented) { 368 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 369 } else { 370 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 371 } 372 } 373 } 374 } 375 PetscFunctionReturn(0); 376 } 377 378 #define HASH_KEY 0.6180339887 379 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 380 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 381 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 382 #undef __FUNCT__ 383 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 384 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 385 { 386 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 387 PetscBool roworiented = baij->roworiented; 388 PetscErrorCode ierr; 389 PetscInt i,j,row,col; 390 PetscInt rstart_orig=mat->rmap->rstart; 391 PetscInt rend_orig=mat->rmap->rend,Nbs=baij->Nbs; 392 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 393 PetscReal tmp; 394 MatScalar **HD = baij->hd,value; 395 #if defined(PETSC_USE_DEBUG) 396 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 397 #endif 398 399 PetscFunctionBegin; 400 if (v) PetscValidScalarPointer(v,6); 401 for (i=0; i<m; i++) { 402 #if defined(PETSC_USE_DEBUG) 403 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 404 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); 405 #endif 406 row = im[i]; 407 if (row >= rstart_orig && row < rend_orig) { 408 for (j=0; j<n; j++) { 409 col = in[j]; 410 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 411 /* Look up PetscInto the Hash Table */ 412 key = (row/bs)*Nbs+(col/bs)+1; 413 h1 = HASH(size,key,tmp); 414 415 416 idx = h1; 417 #if defined(PETSC_USE_DEBUG) 418 insert_ct++; 419 total_ct++; 420 if (HT[idx] != key) { 421 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 422 if (idx == size) { 423 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 424 if (idx == h1) { 425 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 426 } 427 } 428 } 429 #else 430 if (HT[idx] != key) { 431 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 432 if (idx == size) { 433 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 434 if (idx == h1) { 435 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 436 } 437 } 438 } 439 #endif 440 /* A HASH table entry is found, so insert the values at the correct address */ 441 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 442 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 443 } 444 } else { 445 if (!baij->donotstash) { 446 if (roworiented) { 447 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 448 } else { 449 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 450 } 451 } 452 } 453 } 454 #if defined(PETSC_USE_DEBUG) 455 baij->ht_total_ct = total_ct; 456 baij->ht_insert_ct = insert_ct; 457 #endif 458 PetscFunctionReturn(0); 459 } 460 461 #undef __FUNCT__ 462 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 463 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 464 { 465 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 466 PetscBool roworiented = baij->roworiented; 467 PetscErrorCode ierr; 468 PetscInt i,j,ii,jj,row,col; 469 PetscInt rstart=baij->rstartbs; 470 PetscInt rend=mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 471 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 472 PetscReal tmp; 473 MatScalar **HD = baij->hd,*baij_a; 474 const PetscScalar *v_t,*value; 475 #if defined(PETSC_USE_DEBUG) 476 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 477 #endif 478 479 PetscFunctionBegin; 480 481 if (roworiented) { 482 stepval = (n-1)*bs; 483 } else { 484 stepval = (m-1)*bs; 485 } 486 for (i=0; i<m; i++) { 487 #if defined(PETSC_USE_DEBUG) 488 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 489 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); 490 #endif 491 row = im[i]; 492 v_t = v + i*nbs2; 493 if (row >= rstart && row < rend) { 494 for (j=0; j<n; j++) { 495 col = in[j]; 496 497 /* Look up into the Hash Table */ 498 key = row*Nbs+col+1; 499 h1 = HASH(size,key,tmp); 500 501 idx = h1; 502 #if defined(PETSC_USE_DEBUG) 503 total_ct++; 504 insert_ct++; 505 if (HT[idx] != key) { 506 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 507 if (idx == size) { 508 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 509 if (idx == h1) { 510 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 511 } 512 } 513 } 514 #else 515 if (HT[idx] != key) { 516 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 517 if (idx == size) { 518 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 519 if (idx == h1) { 520 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 521 } 522 } 523 } 524 #endif 525 baij_a = HD[idx]; 526 if (roworiented) { 527 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 528 /* value = v + (i*(stepval+bs)+j)*bs; */ 529 value = v_t; 530 v_t += bs; 531 if (addv == ADD_VALUES) { 532 for (ii=0; ii<bs; ii++,value+=stepval) { 533 for (jj=ii; jj<bs2; jj+=bs) { 534 baij_a[jj] += *value++; 535 } 536 } 537 } else { 538 for (ii=0; ii<bs; ii++,value+=stepval) { 539 for (jj=ii; jj<bs2; jj+=bs) { 540 baij_a[jj] = *value++; 541 } 542 } 543 } 544 } else { 545 value = v + j*(stepval+bs)*bs + i*bs; 546 if (addv == ADD_VALUES) { 547 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 548 for (jj=0; jj<bs; jj++) { 549 baij_a[jj] += *value++; 550 } 551 } 552 } else { 553 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 554 for (jj=0; jj<bs; jj++) { 555 baij_a[jj] = *value++; 556 } 557 } 558 } 559 } 560 } 561 } else { 562 if (!baij->donotstash) { 563 if (roworiented) { 564 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 565 } else { 566 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 567 } 568 } 569 } 570 } 571 #if defined(PETSC_USE_DEBUG) 572 baij->ht_total_ct = total_ct; 573 baij->ht_insert_ct = insert_ct; 574 #endif 575 PetscFunctionReturn(0); 576 } 577 578 #undef __FUNCT__ 579 #define __FUNCT__ "MatGetValues_MPIBAIJ" 580 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 581 { 582 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 583 PetscErrorCode ierr; 584 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 585 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 586 587 PetscFunctionBegin; 588 for (i=0; i<m; i++) { 589 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 590 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); 591 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 592 row = idxm[i] - bsrstart; 593 for (j=0; j<n; j++) { 594 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 595 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); 596 if (idxn[j] >= bscstart && idxn[j] < bscend){ 597 col = idxn[j] - bscstart; 598 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 599 } else { 600 if (!baij->colmap) { 601 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 602 } 603 #if defined (PETSC_USE_CTABLE) 604 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 605 data --; 606 #else 607 data = baij->colmap[idxn[j]/bs]-1; 608 #endif 609 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 610 else { 611 col = data + idxn[j]%bs; 612 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 613 } 614 } 615 } 616 } else { 617 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 618 } 619 } 620 PetscFunctionReturn(0); 621 } 622 623 #undef __FUNCT__ 624 #define __FUNCT__ "MatNorm_MPIBAIJ" 625 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 626 { 627 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 628 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 629 PetscErrorCode ierr; 630 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 631 PetscReal sum = 0.0; 632 MatScalar *v; 633 634 PetscFunctionBegin; 635 if (baij->size == 1) { 636 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 637 } else { 638 if (type == NORM_FROBENIUS) { 639 v = amat->a; 640 nz = amat->nz*bs2; 641 for (i=0; i<nz; i++) { 642 #if defined(PETSC_USE_COMPLEX) 643 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 644 #else 645 sum += (*v)*(*v); v++; 646 #endif 647 } 648 v = bmat->a; 649 nz = bmat->nz*bs2; 650 for (i=0; i<nz; i++) { 651 #if defined(PETSC_USE_COMPLEX) 652 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 653 #else 654 sum += (*v)*(*v); v++; 655 #endif 656 } 657 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 658 *nrm = PetscSqrtReal(*nrm); 659 } else if (type == NORM_1) { /* max column sum */ 660 PetscReal *tmp,*tmp2; 661 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 662 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);CHKERRQ(ierr); 663 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 664 v = amat->a; jj = amat->j; 665 for (i=0; i<amat->nz; i++) { 666 for (j=0; j<bs; j++){ 667 col = bs*(cstart + *jj) + j; /* column index */ 668 for (row=0; row<bs; row++){ 669 tmp[col] += PetscAbsScalar(*v); v++; 670 } 671 } 672 jj++; 673 } 674 v = bmat->a; jj = bmat->j; 675 for (i=0; i<bmat->nz; i++) { 676 for (j=0; j<bs; j++){ 677 col = bs*garray[*jj] + j; 678 for (row=0; row<bs; row++){ 679 tmp[col] += PetscAbsScalar(*v); v++; 680 } 681 } 682 jj++; 683 } 684 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 685 *nrm = 0.0; 686 for (j=0; j<mat->cmap->N; j++) { 687 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 688 } 689 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 690 } else if (type == NORM_INFINITY) { /* max row sum */ 691 PetscReal *sums; 692 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr); 693 sum = 0.0; 694 for (j=0; j<amat->mbs; j++) { 695 for (row=0; row<bs; row++) sums[row] = 0.0; 696 v = amat->a + bs2*amat->i[j]; 697 nz = amat->i[j+1]-amat->i[j]; 698 for (i=0; i<nz; i++) { 699 for (col=0; col<bs; col++){ 700 for (row=0; row<bs; row++){ 701 sums[row] += PetscAbsScalar(*v); v++; 702 } 703 } 704 } 705 v = bmat->a + bs2*bmat->i[j]; 706 nz = bmat->i[j+1]-bmat->i[j]; 707 for (i=0; i<nz; i++) { 708 for (col=0; col<bs; col++){ 709 for (row=0; row<bs; row++){ 710 sums[row] += PetscAbsScalar(*v); v++; 711 } 712 } 713 } 714 for (row=0; row<bs; row++){ 715 if (sums[row] > sum) sum = sums[row]; 716 } 717 } 718 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 719 ierr = PetscFree(sums);CHKERRQ(ierr); 720 } else SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"No support for this norm yet"); 721 } 722 PetscFunctionReturn(0); 723 } 724 725 /* 726 Creates the hash table, and sets the table 727 This table is created only once. 728 If new entried need to be added to the matrix 729 then the hash table has to be destroyed and 730 recreated. 731 */ 732 #undef __FUNCT__ 733 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 734 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 735 { 736 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 737 Mat A = baij->A,B=baij->B; 738 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 739 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 740 PetscErrorCode ierr; 741 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 742 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 743 PetscInt *HT,key; 744 MatScalar **HD; 745 PetscReal tmp; 746 #if defined(PETSC_USE_INFO) 747 PetscInt ct=0,max=0; 748 #endif 749 750 PetscFunctionBegin; 751 if (baij->ht) PetscFunctionReturn(0); 752 753 baij->ht_size = (PetscInt)(factor*nz); 754 ht_size = baij->ht_size; 755 756 /* Allocate Memory for Hash Table */ 757 ierr = PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);CHKERRQ(ierr); 758 ierr = PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));CHKERRQ(ierr); 759 ierr = PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));CHKERRQ(ierr); 760 HD = baij->hd; 761 HT = baij->ht; 762 763 /* Loop Over A */ 764 for (i=0; i<a->mbs; i++) { 765 for (j=ai[i]; j<ai[i+1]; j++) { 766 row = i+rstart; 767 col = aj[j]+cstart; 768 769 key = row*Nbs + col + 1; 770 h1 = HASH(ht_size,key,tmp); 771 for (k=0; k<ht_size; k++){ 772 if (!HT[(h1+k)%ht_size]) { 773 HT[(h1+k)%ht_size] = key; 774 HD[(h1+k)%ht_size] = a->a + j*bs2; 775 break; 776 #if defined(PETSC_USE_INFO) 777 } else { 778 ct++; 779 #endif 780 } 781 } 782 #if defined(PETSC_USE_INFO) 783 if (k> max) max = k; 784 #endif 785 } 786 } 787 /* Loop Over B */ 788 for (i=0; i<b->mbs; i++) { 789 for (j=bi[i]; j<bi[i+1]; j++) { 790 row = i+rstart; 791 col = garray[bj[j]]; 792 key = row*Nbs + col + 1; 793 h1 = HASH(ht_size,key,tmp); 794 for (k=0; k<ht_size; k++){ 795 if (!HT[(h1+k)%ht_size]) { 796 HT[(h1+k)%ht_size] = key; 797 HD[(h1+k)%ht_size] = b->a + j*bs2; 798 break; 799 #if defined(PETSC_USE_INFO) 800 } else { 801 ct++; 802 #endif 803 } 804 } 805 #if defined(PETSC_USE_INFO) 806 if (k> max) max = k; 807 #endif 808 } 809 } 810 811 /* Print Summary */ 812 #if defined(PETSC_USE_INFO) 813 for (i=0,j=0; i<ht_size; i++) { 814 if (HT[i]) {j++;} 815 } 816 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 817 #endif 818 PetscFunctionReturn(0); 819 } 820 821 #undef __FUNCT__ 822 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 823 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 824 { 825 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 826 PetscErrorCode ierr; 827 PetscInt nstash,reallocs; 828 InsertMode addv; 829 830 PetscFunctionBegin; 831 if (baij->donotstash || mat->nooffprocentries) { 832 PetscFunctionReturn(0); 833 } 834 835 /* make sure all processors are either in INSERTMODE or ADDMODE */ 836 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 837 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 838 mat->insertmode = addv; /* in case this processor had no cache */ 839 840 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 841 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 842 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 843 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 844 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 845 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 846 PetscFunctionReturn(0); 847 } 848 849 #undef __FUNCT__ 850 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 851 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 852 { 853 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 854 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data; 855 PetscErrorCode ierr; 856 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 857 PetscInt *row,*col; 858 PetscBool r1,r2,r3,other_disassembled; 859 MatScalar *val; 860 InsertMode addv = mat->insertmode; 861 PetscMPIInt n; 862 863 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 864 PetscFunctionBegin; 865 if (!baij->donotstash && !mat->nooffprocentries) { 866 while (1) { 867 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 868 if (!flg) break; 869 870 for (i=0; i<n;) { 871 /* Now identify the consecutive vals belonging to the same row */ 872 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 873 if (j < n) ncols = j-i; 874 else ncols = n-i; 875 /* Now assemble all these values with a single function call */ 876 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 877 i = j; 878 } 879 } 880 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 881 /* Now process the block-stash. Since the values are stashed column-oriented, 882 set the roworiented flag to column oriented, and after MatSetValues() 883 restore the original flags */ 884 r1 = baij->roworiented; 885 r2 = a->roworiented; 886 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 887 baij->roworiented = PETSC_FALSE; 888 a->roworiented = PETSC_FALSE; 889 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 890 while (1) { 891 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 892 if (!flg) break; 893 894 for (i=0; i<n;) { 895 /* Now identify the consecutive vals belonging to the same row */ 896 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 897 if (j < n) ncols = j-i; 898 else ncols = n-i; 899 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 900 i = j; 901 } 902 } 903 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 904 baij->roworiented = r1; 905 a->roworiented = r2; 906 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 907 } 908 909 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 910 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 911 912 /* determine if any processor has disassembled, if so we must 913 also disassemble ourselfs, in order that we may reassemble. */ 914 /* 915 if nonzero structure of submatrix B cannot change then we know that 916 no processor disassembled thus we can skip this stuff 917 */ 918 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 919 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 920 if (mat->was_assembled && !other_disassembled) { 921 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 922 } 923 } 924 925 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 926 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 927 } 928 ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 929 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 930 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 931 932 #if defined(PETSC_USE_INFO) 933 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 934 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 935 baij->ht_total_ct = 0; 936 baij->ht_insert_ct = 0; 937 } 938 #endif 939 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 940 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 941 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 942 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 943 } 944 945 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 946 baij->rowvalues = 0; 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 952 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 953 { 954 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 955 PetscErrorCode ierr; 956 PetscMPIInt size = baij->size,rank = baij->rank; 957 PetscInt bs = mat->rmap->bs; 958 PetscBool iascii,isdraw; 959 PetscViewer sviewer; 960 PetscViewerFormat format; 961 962 PetscFunctionBegin; 963 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 964 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 965 if (iascii) { 966 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 967 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 968 MatInfo info; 969 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 970 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 971 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 972 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 973 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 974 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 975 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 976 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 977 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 978 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 979 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 980 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 981 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 982 PetscFunctionReturn(0); 983 } else if (format == PETSC_VIEWER_ASCII_INFO) { 984 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 985 PetscFunctionReturn(0); 986 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 987 PetscFunctionReturn(0); 988 } 989 } 990 991 if (isdraw) { 992 PetscDraw draw; 993 PetscBool isnull; 994 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 995 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 996 } 997 998 if (size == 1) { 999 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1000 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1001 } else { 1002 /* assemble the entire matrix onto first processor. */ 1003 Mat A; 1004 Mat_SeqBAIJ *Aloc; 1005 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1006 MatScalar *a; 1007 1008 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1009 /* Perhaps this should be the type of mat? */ 1010 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1011 if (!rank) { 1012 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1013 } else { 1014 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1015 } 1016 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1017 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1018 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1019 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1020 1021 /* copy over the A part */ 1022 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1023 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1024 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1025 1026 for (i=0; i<mbs; i++) { 1027 rvals[0] = bs*(baij->rstartbs + i); 1028 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1029 for (j=ai[i]; j<ai[i+1]; j++) { 1030 col = (baij->cstartbs+aj[j])*bs; 1031 for (k=0; k<bs; k++) { 1032 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1033 col++; a += bs; 1034 } 1035 } 1036 } 1037 /* copy over the B part */ 1038 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1039 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1040 for (i=0; i<mbs; i++) { 1041 rvals[0] = bs*(baij->rstartbs + i); 1042 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1043 for (j=ai[i]; j<ai[i+1]; j++) { 1044 col = baij->garray[aj[j]]*bs; 1045 for (k=0; k<bs; k++) { 1046 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1047 col++; a += bs; 1048 } 1049 } 1050 } 1051 ierr = PetscFree(rvals);CHKERRQ(ierr); 1052 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1053 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1054 /* 1055 Everyone has to call to draw the matrix since the graphics waits are 1056 synchronized across all processors that share the PetscDraw object 1057 */ 1058 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1059 if (!rank) { 1060 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1061 /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/ 1062 PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ); 1063 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1064 } 1065 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1066 ierr = MatDestroy(&A);CHKERRQ(ierr); 1067 } 1068 PetscFunctionReturn(0); 1069 } 1070 1071 #undef __FUNCT__ 1072 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1073 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1074 { 1075 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1076 Mat_SeqBAIJ* A = (Mat_SeqBAIJ*)a->A->data; 1077 Mat_SeqBAIJ* B = (Mat_SeqBAIJ*)a->B->data; 1078 PetscErrorCode ierr; 1079 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1080 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1081 int fd; 1082 PetscScalar *column_values; 1083 FILE *file; 1084 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1085 PetscInt message_count,flowcontrolcount; 1086 1087 PetscFunctionBegin; 1088 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1089 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 1090 nz = bs2*(A->nz + B->nz); 1091 rlen = mat->rmap->n; 1092 if (!rank) { 1093 header[0] = MAT_FILE_CLASSID; 1094 header[1] = mat->rmap->N; 1095 header[2] = mat->cmap->N; 1096 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1097 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1098 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1099 /* get largest number of rows any processor has */ 1100 range = mat->rmap->range; 1101 for (i=1; i<size; i++) { 1102 rlen = PetscMax(rlen,range[i+1] - range[i]); 1103 } 1104 } else { 1105 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1106 } 1107 1108 ierr = PetscMalloc((rlen/bs)*sizeof(PetscInt),&crow_lens);CHKERRQ(ierr); 1109 /* compute lengths of each row */ 1110 for (i=0; i<a->mbs; i++) { 1111 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1112 } 1113 /* store the row lengths to the file */ 1114 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1115 if (!rank) { 1116 MPI_Status status; 1117 ierr = PetscMalloc(rlen*sizeof(PetscInt),&row_lens);CHKERRQ(ierr); 1118 rlen = (range[1] - range[0])/bs; 1119 for (i=0; i<rlen; i++) { 1120 for (j=0; j<bs; j++) { 1121 row_lens[i*bs+j] = bs*crow_lens[i]; 1122 } 1123 } 1124 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1125 for (i=1; i<size; i++) { 1126 rlen = (range[i+1] - range[i])/bs; 1127 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1128 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1129 for (k=0; k<rlen; k++) { 1130 for (j=0; j<bs; j++) { 1131 row_lens[k*bs+j] = bs*crow_lens[k]; 1132 } 1133 } 1134 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1135 } 1136 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1137 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1138 } else { 1139 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1140 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1141 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1142 } 1143 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1144 1145 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1146 information needed to make it for each row from a block row. This does require more communication but still not more than 1147 the communication needed for the nonzero values */ 1148 nzmax = nz; /* space a largest processor needs */ 1149 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1150 ierr = PetscMalloc(nzmax*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1151 cnt = 0; 1152 for (i=0; i<a->mbs; i++) { 1153 pcnt = cnt; 1154 for (j=B->i[i]; j<B->i[i+1]; j++) { 1155 if ( (col = garray[B->j[j]]) > cstart) break; 1156 for (l=0; l<bs; l++) { 1157 column_indices[cnt++] = bs*col+l; 1158 } 1159 } 1160 for (k=A->i[i]; k<A->i[i+1]; k++) { 1161 for (l=0; l<bs; l++) { 1162 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1163 } 1164 } 1165 for (; j<B->i[i+1]; j++) { 1166 for (l=0; l<bs; l++) { 1167 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1168 } 1169 } 1170 len = cnt - pcnt; 1171 for (k=1; k<bs; k++) { 1172 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1173 cnt += len; 1174 } 1175 } 1176 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1177 1178 /* store the columns to the file */ 1179 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1180 if (!rank) { 1181 MPI_Status status; 1182 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1183 for (i=1; i<size; i++) { 1184 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1185 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1186 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1187 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1188 } 1189 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1190 } else { 1191 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1192 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1193 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1194 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1195 } 1196 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1197 1198 /* load up the numerical values */ 1199 ierr = PetscMalloc(nzmax*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1200 cnt = 0; 1201 for (i=0; i<a->mbs; i++) { 1202 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1203 for (j=B->i[i]; j<B->i[i+1]; j++) { 1204 if ( garray[B->j[j]] > cstart) break; 1205 for (l=0; l<bs; l++) { 1206 for (ll=0; ll<bs; ll++) { 1207 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1208 } 1209 } 1210 cnt += bs; 1211 } 1212 for (k=A->i[i]; k<A->i[i+1]; k++) { 1213 for (l=0; l<bs; l++) { 1214 for (ll=0; ll<bs; ll++) { 1215 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1216 } 1217 } 1218 cnt += bs; 1219 } 1220 for (; j<B->i[i+1]; j++) { 1221 for (l=0; l<bs; l++) { 1222 for (ll=0; ll<bs; ll++) { 1223 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1224 } 1225 } 1226 cnt += bs; 1227 } 1228 cnt += (bs-1)*rlen; 1229 } 1230 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1231 1232 /* store the column values to the file */ 1233 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1234 if (!rank) { 1235 MPI_Status status; 1236 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1237 for (i=1; i<size; i++) { 1238 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1239 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1240 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1241 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1242 } 1243 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1244 } else { 1245 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1246 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1247 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1248 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1249 } 1250 ierr = PetscFree(column_values);CHKERRQ(ierr); 1251 1252 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1253 if (file) { 1254 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1255 } 1256 PetscFunctionReturn(0); 1257 } 1258 1259 #undef __FUNCT__ 1260 #define __FUNCT__ "MatView_MPIBAIJ" 1261 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1262 { 1263 PetscErrorCode ierr; 1264 PetscBool iascii,isdraw,issocket,isbinary; 1265 1266 PetscFunctionBegin; 1267 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1268 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1269 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1270 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1271 if (iascii || isdraw || issocket) { 1272 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1273 } else if (isbinary) { 1274 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1275 } else { 1276 SETERRQ1(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1277 } 1278 PetscFunctionReturn(0); 1279 } 1280 1281 #undef __FUNCT__ 1282 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1283 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1284 { 1285 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1286 PetscErrorCode ierr; 1287 1288 PetscFunctionBegin; 1289 #if defined(PETSC_USE_LOG) 1290 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1291 #endif 1292 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1293 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1294 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1295 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1296 #if defined (PETSC_USE_CTABLE) 1297 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1298 #else 1299 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1300 #endif 1301 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1302 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1303 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1304 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1305 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1306 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1307 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1308 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1309 1310 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1311 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1312 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1313 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1314 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1315 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1316 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1317 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1318 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C","",PETSC_NULL);CHKERRQ(ierr); 1319 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C","",PETSC_NULL);CHKERRQ(ierr); 1320 PetscFunctionReturn(0); 1321 } 1322 1323 #undef __FUNCT__ 1324 #define __FUNCT__ "MatMult_MPIBAIJ" 1325 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1326 { 1327 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1328 PetscErrorCode ierr; 1329 PetscInt nt; 1330 1331 PetscFunctionBegin; 1332 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1333 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1334 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1335 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1336 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1337 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1338 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1339 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1340 PetscFunctionReturn(0); 1341 } 1342 1343 #undef __FUNCT__ 1344 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1345 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1346 { 1347 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1348 PetscErrorCode ierr; 1349 1350 PetscFunctionBegin; 1351 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1352 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1353 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1354 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1355 PetscFunctionReturn(0); 1356 } 1357 1358 #undef __FUNCT__ 1359 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1360 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1361 { 1362 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1363 PetscErrorCode ierr; 1364 PetscBool merged; 1365 1366 PetscFunctionBegin; 1367 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1368 /* do nondiagonal part */ 1369 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1370 if (!merged) { 1371 /* send it on its way */ 1372 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1373 /* do local part */ 1374 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1375 /* receive remote parts: note this assumes the values are not actually */ 1376 /* inserted in yy until the next line */ 1377 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1378 } else { 1379 /* do local part */ 1380 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1381 /* send it on its way */ 1382 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1383 /* values actually were received in the Begin() but we need to call this nop */ 1384 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1385 } 1386 PetscFunctionReturn(0); 1387 } 1388 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1391 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1392 { 1393 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1394 PetscErrorCode ierr; 1395 1396 PetscFunctionBegin; 1397 /* do nondiagonal part */ 1398 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1399 /* send it on its way */ 1400 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1401 /* do local part */ 1402 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1403 /* receive remote parts: note this assumes the values are not actually */ 1404 /* inserted in yy until the next line, which is true for my implementation*/ 1405 /* but is not perhaps always true. */ 1406 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1407 PetscFunctionReturn(0); 1408 } 1409 1410 /* 1411 This only works correctly for square matrices where the subblock A->A is the 1412 diagonal block 1413 */ 1414 #undef __FUNCT__ 1415 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1416 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1417 { 1418 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1419 PetscErrorCode ierr; 1420 1421 PetscFunctionBegin; 1422 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1423 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1424 PetscFunctionReturn(0); 1425 } 1426 1427 #undef __FUNCT__ 1428 #define __FUNCT__ "MatScale_MPIBAIJ" 1429 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1430 { 1431 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1432 PetscErrorCode ierr; 1433 1434 PetscFunctionBegin; 1435 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1436 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1437 PetscFunctionReturn(0); 1438 } 1439 1440 #undef __FUNCT__ 1441 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1442 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1443 { 1444 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1445 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1446 PetscErrorCode ierr; 1447 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1448 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1449 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1450 1451 PetscFunctionBegin; 1452 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1453 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1454 mat->getrowactive = PETSC_TRUE; 1455 1456 if (!mat->rowvalues && (idx || v)) { 1457 /* 1458 allocate enough space to hold information from the longest row. 1459 */ 1460 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1461 PetscInt max = 1,mbs = mat->mbs,tmp; 1462 for (i=0; i<mbs; i++) { 1463 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1464 if (max < tmp) { max = tmp; } 1465 } 1466 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1467 } 1468 lrow = row - brstart; 1469 1470 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1471 if (!v) {pvA = 0; pvB = 0;} 1472 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1473 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1474 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1475 nztot = nzA + nzB; 1476 1477 cmap = mat->garray; 1478 if (v || idx) { 1479 if (nztot) { 1480 /* Sort by increasing column numbers, assuming A and B already sorted */ 1481 PetscInt imark = -1; 1482 if (v) { 1483 *v = v_p = mat->rowvalues; 1484 for (i=0; i<nzB; i++) { 1485 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1486 else break; 1487 } 1488 imark = i; 1489 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1490 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1491 } 1492 if (idx) { 1493 *idx = idx_p = mat->rowindices; 1494 if (imark > -1) { 1495 for (i=0; i<imark; i++) { 1496 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1497 } 1498 } else { 1499 for (i=0; i<nzB; i++) { 1500 if (cmap[cworkB[i]/bs] < cstart) 1501 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1502 else break; 1503 } 1504 imark = i; 1505 } 1506 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1507 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1508 } 1509 } else { 1510 if (idx) *idx = 0; 1511 if (v) *v = 0; 1512 } 1513 } 1514 *nz = nztot; 1515 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1516 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1517 PetscFunctionReturn(0); 1518 } 1519 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1522 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1523 { 1524 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1525 1526 PetscFunctionBegin; 1527 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1528 baij->getrowactive = PETSC_FALSE; 1529 PetscFunctionReturn(0); 1530 } 1531 1532 #undef __FUNCT__ 1533 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1534 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1535 { 1536 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1537 PetscErrorCode ierr; 1538 1539 PetscFunctionBegin; 1540 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1541 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1542 PetscFunctionReturn(0); 1543 } 1544 1545 #undef __FUNCT__ 1546 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1547 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1548 { 1549 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1550 Mat A = a->A,B = a->B; 1551 PetscErrorCode ierr; 1552 PetscReal isend[5],irecv[5]; 1553 1554 PetscFunctionBegin; 1555 info->block_size = (PetscReal)matin->rmap->bs; 1556 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1557 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1558 isend[3] = info->memory; isend[4] = info->mallocs; 1559 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1560 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1561 isend[3] += info->memory; isend[4] += info->mallocs; 1562 if (flag == MAT_LOCAL) { 1563 info->nz_used = isend[0]; 1564 info->nz_allocated = isend[1]; 1565 info->nz_unneeded = isend[2]; 1566 info->memory = isend[3]; 1567 info->mallocs = isend[4]; 1568 } else if (flag == MAT_GLOBAL_MAX) { 1569 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1570 info->nz_used = irecv[0]; 1571 info->nz_allocated = irecv[1]; 1572 info->nz_unneeded = irecv[2]; 1573 info->memory = irecv[3]; 1574 info->mallocs = irecv[4]; 1575 } else if (flag == MAT_GLOBAL_SUM) { 1576 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1577 info->nz_used = irecv[0]; 1578 info->nz_allocated = irecv[1]; 1579 info->nz_unneeded = irecv[2]; 1580 info->memory = irecv[3]; 1581 info->mallocs = irecv[4]; 1582 } else { 1583 SETERRQ1(((PetscObject)matin)->comm,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1584 } 1585 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1586 info->fill_ratio_needed = 0; 1587 info->factor_mallocs = 0; 1588 PetscFunctionReturn(0); 1589 } 1590 1591 #undef __FUNCT__ 1592 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1593 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1594 { 1595 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1596 PetscErrorCode ierr; 1597 1598 PetscFunctionBegin; 1599 switch (op) { 1600 case MAT_NEW_NONZERO_LOCATIONS: 1601 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1602 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1603 case MAT_KEEP_NONZERO_PATTERN: 1604 case MAT_NEW_NONZERO_LOCATION_ERR: 1605 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1606 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1607 break; 1608 case MAT_ROW_ORIENTED: 1609 a->roworiented = flg; 1610 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1611 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1612 break; 1613 case MAT_NEW_DIAGONALS: 1614 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1615 break; 1616 case MAT_IGNORE_OFF_PROC_ENTRIES: 1617 a->donotstash = flg; 1618 break; 1619 case MAT_USE_HASH_TABLE: 1620 a->ht_flag = flg; 1621 break; 1622 case MAT_SYMMETRIC: 1623 case MAT_STRUCTURALLY_SYMMETRIC: 1624 case MAT_HERMITIAN: 1625 case MAT_SYMMETRY_ETERNAL: 1626 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1627 break; 1628 default: 1629 SETERRQ1(((PetscObject)A)->comm,PETSC_ERR_SUP,"unknown option %d",op); 1630 } 1631 PetscFunctionReturn(0); 1632 } 1633 1634 #undef __FUNCT__ 1635 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1636 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1637 { 1638 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1639 Mat_SeqBAIJ *Aloc; 1640 Mat B; 1641 PetscErrorCode ierr; 1642 PetscInt M=A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1643 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1644 MatScalar *a; 1645 1646 PetscFunctionBegin; 1647 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1648 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1649 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1650 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1651 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1652 /* Do not know preallocation information, but must set block size */ 1653 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,PETSC_NULL,PETSC_DECIDE,PETSC_NULL);CHKERRQ(ierr); 1654 } else { 1655 B = *matout; 1656 } 1657 1658 /* copy over the A part */ 1659 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1660 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1661 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1662 1663 for (i=0; i<mbs; i++) { 1664 rvals[0] = bs*(baij->rstartbs + i); 1665 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1666 for (j=ai[i]; j<ai[i+1]; j++) { 1667 col = (baij->cstartbs+aj[j])*bs; 1668 for (k=0; k<bs; k++) { 1669 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1670 col++; a += bs; 1671 } 1672 } 1673 } 1674 /* copy over the B part */ 1675 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1676 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1677 for (i=0; i<mbs; i++) { 1678 rvals[0] = bs*(baij->rstartbs + i); 1679 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1680 for (j=ai[i]; j<ai[i+1]; j++) { 1681 col = baij->garray[aj[j]]*bs; 1682 for (k=0; k<bs; k++) { 1683 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1684 col++; a += bs; 1685 } 1686 } 1687 } 1688 ierr = PetscFree(rvals);CHKERRQ(ierr); 1689 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1690 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1691 1692 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1693 *matout = B; 1694 } else { 1695 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1696 } 1697 PetscFunctionReturn(0); 1698 } 1699 1700 #undef __FUNCT__ 1701 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1702 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1703 { 1704 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1705 Mat a = baij->A,b = baij->B; 1706 PetscErrorCode ierr; 1707 PetscInt s1,s2,s3; 1708 1709 PetscFunctionBegin; 1710 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1711 if (rr) { 1712 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1713 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1714 /* Overlap communication with computation. */ 1715 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1716 } 1717 if (ll) { 1718 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1719 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1720 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1721 } 1722 /* scale the diagonal block */ 1723 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1724 1725 if (rr) { 1726 /* Do a scatter end and then right scale the off-diagonal block */ 1727 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1728 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1729 } 1730 1731 PetscFunctionReturn(0); 1732 } 1733 1734 #undef __FUNCT__ 1735 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1736 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1737 { 1738 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1739 PetscErrorCode ierr; 1740 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1741 PetscInt i,*owners = A->rmap->range; 1742 PetscInt *nprocs,j,idx,nsends,row; 1743 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1744 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1745 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1746 MPI_Comm comm = ((PetscObject)A)->comm; 1747 MPI_Request *send_waits,*recv_waits; 1748 MPI_Status recv_status,*send_status; 1749 const PetscScalar *xx; 1750 PetscScalar *bb; 1751 #if defined(PETSC_DEBUG) 1752 PetscBool found = PETSC_FALSE; 1753 #endif 1754 1755 PetscFunctionBegin; 1756 /* first count number of contributors to each processor */ 1757 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1758 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1759 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1760 j = 0; 1761 for (i=0; i<N; i++) { 1762 if (lastidx > (idx = rows[i])) j = 0; 1763 lastidx = idx; 1764 for (; j<size; j++) { 1765 if (idx >= owners[j] && idx < owners[j+1]) { 1766 nprocs[2*j]++; 1767 nprocs[2*j+1] = 1; 1768 owner[i] = j; 1769 #if defined(PETSC_DEBUG) 1770 found = PETSC_TRUE; 1771 #endif 1772 break; 1773 } 1774 } 1775 #if defined(PETSC_DEBUG) 1776 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1777 found = PETSC_FALSE; 1778 #endif 1779 } 1780 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1781 1782 if (A->nooffproczerorows) { 1783 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"); 1784 nrecvs = nsends; 1785 nmax = N; 1786 } else { 1787 /* inform other processors of number of messages and max length*/ 1788 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1789 } 1790 1791 /* post receives: */ 1792 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1793 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1794 for (i=0; i<nrecvs; i++) { 1795 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1796 } 1797 1798 /* do sends: 1799 1) starts[i] gives the starting index in svalues for stuff going to 1800 the ith processor 1801 */ 1802 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1803 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1804 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1805 starts[0] = 0; 1806 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1807 for (i=0; i<N; i++) { 1808 svalues[starts[owner[i]]++] = rows[i]; 1809 } 1810 1811 starts[0] = 0; 1812 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1813 count = 0; 1814 for (i=0; i<size; i++) { 1815 if (nprocs[2*i+1]) { 1816 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1817 } 1818 } 1819 ierr = PetscFree(starts);CHKERRQ(ierr); 1820 1821 base = owners[rank]; 1822 1823 /* wait on receives */ 1824 ierr = PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);CHKERRQ(ierr); 1825 count = nrecvs; 1826 slen = 0; 1827 while (count) { 1828 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1829 /* unpack receives into our local space */ 1830 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1831 source[imdex] = recv_status.MPI_SOURCE; 1832 lens[imdex] = n; 1833 slen += n; 1834 count--; 1835 } 1836 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1837 1838 /* move the data into the send scatter */ 1839 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1840 count = 0; 1841 for (i=0; i<nrecvs; i++) { 1842 values = rvalues + i*nmax; 1843 for (j=0; j<lens[i]; j++) { 1844 lrows[count++] = values[j] - base; 1845 } 1846 } 1847 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1848 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1849 ierr = PetscFree(owner);CHKERRQ(ierr); 1850 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1851 1852 /* fix right hand side if needed */ 1853 if (x && b) { 1854 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1855 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1856 for (i=0; i<slen; i++) { 1857 bb[lrows[i]] = diag*xx[lrows[i]]; 1858 } 1859 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1860 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1861 } 1862 1863 /* actually zap the local rows */ 1864 /* 1865 Zero the required rows. If the "diagonal block" of the matrix 1866 is square and the user wishes to set the diagonal we use separate 1867 code so that MatSetValues() is not called for each diagonal allocating 1868 new memory, thus calling lots of mallocs and slowing things down. 1869 1870 */ 1871 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1872 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1873 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1874 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 1875 } else if (diag != 0.0) { 1876 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1877 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\ 1878 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1879 for (i=0; i<slen; i++) { 1880 row = lrows[i] + rstart_bs; 1881 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1882 } 1883 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1884 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1885 } else { 1886 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1887 } 1888 1889 ierr = PetscFree(lrows);CHKERRQ(ierr); 1890 1891 /* wait on sends */ 1892 if (nsends) { 1893 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1894 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1895 ierr = PetscFree(send_status);CHKERRQ(ierr); 1896 } 1897 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1898 ierr = PetscFree(svalues);CHKERRQ(ierr); 1899 1900 PetscFunctionReturn(0); 1901 } 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1905 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1906 { 1907 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1908 PetscErrorCode ierr; 1909 1910 PetscFunctionBegin; 1911 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatEqual_MPIBAIJ" 1919 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1920 { 1921 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1922 Mat a,b,c,d; 1923 PetscBool flg; 1924 PetscErrorCode ierr; 1925 1926 PetscFunctionBegin; 1927 a = matA->A; b = matA->B; 1928 c = matB->A; d = matB->B; 1929 1930 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1931 if (flg) { 1932 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1933 } 1934 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1935 PetscFunctionReturn(0); 1936 } 1937 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatCopy_MPIBAIJ" 1940 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1941 { 1942 PetscErrorCode ierr; 1943 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1944 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1945 1946 PetscFunctionBegin; 1947 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1948 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1949 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1950 } else { 1951 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1952 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1953 } 1954 PetscFunctionReturn(0); 1955 } 1956 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1959 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1960 { 1961 PetscErrorCode ierr; 1962 1963 PetscFunctionBegin; 1964 if (A->rmap->bs < 0) { 1965 ierr = PetscLayoutSetBlockSize(A->rmap,1);CHKERRQ(ierr); 1966 ierr = PetscLayoutSetBlockSize(A->cmap,1);CHKERRQ(ierr); 1967 } 1968 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1969 PetscFunctionReturn(0); 1970 } 1971 1972 #undef __FUNCT__ 1973 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1974 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1975 { 1976 PetscErrorCode ierr; 1977 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1978 PetscBLASInt bnz,one=1; 1979 Mat_SeqBAIJ *x,*y; 1980 1981 PetscFunctionBegin; 1982 if (str == SAME_NONZERO_PATTERN) { 1983 PetscScalar alpha = a; 1984 x = (Mat_SeqBAIJ *)xx->A->data; 1985 y = (Mat_SeqBAIJ *)yy->A->data; 1986 bnz = PetscBLASIntCast(x->nz); 1987 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1988 x = (Mat_SeqBAIJ *)xx->B->data; 1989 y = (Mat_SeqBAIJ *)yy->B->data; 1990 bnz = PetscBLASIntCast(x->nz); 1991 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1992 } else { 1993 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1994 } 1995 PetscFunctionReturn(0); 1996 } 1997 1998 #undef __FUNCT__ 1999 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2000 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2001 { 2002 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2003 PetscErrorCode ierr; 2004 2005 PetscFunctionBegin; 2006 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2007 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2008 PetscFunctionReturn(0); 2009 } 2010 2011 #undef __FUNCT__ 2012 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2013 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2014 { 2015 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2016 PetscErrorCode ierr; 2017 2018 PetscFunctionBegin; 2019 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2020 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2021 PetscFunctionReturn(0); 2022 } 2023 2024 #undef __FUNCT__ 2025 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2026 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2027 { 2028 PetscErrorCode ierr; 2029 IS iscol_local; 2030 PetscInt csize; 2031 2032 PetscFunctionBegin; 2033 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2034 if (call == MAT_REUSE_MATRIX) { 2035 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2036 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2037 } else { 2038 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2039 } 2040 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2041 if (call == MAT_INITIAL_MATRIX) { 2042 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2043 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2044 } 2045 PetscFunctionReturn(0); 2046 } 2047 2048 #undef __FUNCT__ 2049 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2050 /* 2051 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2052 in local and then by concatenating the local matrices the end result. 2053 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2054 */ 2055 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2056 { 2057 PetscErrorCode ierr; 2058 PetscMPIInt rank,size; 2059 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2060 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2061 Mat *local,M,Mreuse; 2062 MatScalar *vwork,*aa; 2063 MPI_Comm comm = ((PetscObject)mat)->comm; 2064 Mat_SeqBAIJ *aij; 2065 2066 2067 PetscFunctionBegin; 2068 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2069 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2070 2071 if (call == MAT_REUSE_MATRIX) { 2072 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2073 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2074 local = &Mreuse; 2075 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2076 } else { 2077 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2078 Mreuse = *local; 2079 ierr = PetscFree(local);CHKERRQ(ierr); 2080 } 2081 2082 /* 2083 m - number of local rows 2084 n - number of columns (same on all processors) 2085 rstart - first row in new global matrix generated 2086 */ 2087 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2088 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2089 m = m/bs; 2090 n = n/bs; 2091 2092 if (call == MAT_INITIAL_MATRIX) { 2093 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2094 ii = aij->i; 2095 jj = aij->j; 2096 2097 /* 2098 Determine the number of non-zeros in the diagonal and off-diagonal 2099 portions of the matrix in order to do correct preallocation 2100 */ 2101 2102 /* first get start and end of "diagonal" columns */ 2103 if (csize == PETSC_DECIDE) { 2104 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2105 if (mglobal == n*bs) { /* square matrix */ 2106 nlocal = m; 2107 } else { 2108 nlocal = n/size + ((n % size) > rank); 2109 } 2110 } else { 2111 nlocal = csize/bs; 2112 } 2113 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2114 rstart = rend - nlocal; 2115 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); 2116 2117 /* next, compute all the lengths */ 2118 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2119 olens = dlens + m; 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 = PetscFree(dlens);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; 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 2175 PetscFunctionReturn(0); 2176 } 2177 2178 #undef __FUNCT__ 2179 #define __FUNCT__ "MatPermute_MPIBAIJ" 2180 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2181 { 2182 MPI_Comm comm,pcomm; 2183 PetscInt first,local_size,nrows; 2184 const PetscInt *rows; 2185 PetscMPIInt size; 2186 IS crowp,growp,irowp,lrowp,lcolp,icolp; 2187 PetscErrorCode ierr; 2188 2189 PetscFunctionBegin; 2190 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2191 /* make a collective version of 'rowp' */ 2192 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2193 if (pcomm==comm) { 2194 crowp = rowp; 2195 } else { 2196 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2197 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2198 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2199 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2200 } 2201 /* collect the global row permutation and invert it */ 2202 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 2203 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 2204 if (pcomm!=comm) { 2205 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2206 } 2207 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2208 /* get the local target indices */ 2209 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 2210 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL);CHKERRQ(ierr); 2211 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 2212 ierr = ISCreateGeneral(MPI_COMM_SELF,local_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 = ISGetSize(colp,&nrows);CHKERRQ(ierr); 2223 ierr = ISGetIndices(colp,&rows);CHKERRQ(ierr); 2224 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,PETSC_COPY_VALUES,&lcolp);CHKERRQ(ierr); 2225 } 2226 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2227 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2228 ierr = ISSetPermutation(icolp);CHKERRQ(ierr); 2229 if (size>1) { 2230 ierr = ISRestoreIndices(colp,&rows);CHKERRQ(ierr); 2231 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2232 } 2233 /* now we just get the submatrix */ 2234 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2235 /* clean up */ 2236 ierr = ISDestroy(&lrowp);CHKERRQ(ierr); 2237 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2238 PetscFunctionReturn(0); 2239 } 2240 2241 #undef __FUNCT__ 2242 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2243 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2244 { 2245 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2246 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2247 2248 PetscFunctionBegin; 2249 if (nghosts) { *nghosts = B->nbs;} 2250 if (ghosts) {*ghosts = baij->garray;} 2251 PetscFunctionReturn(0); 2252 } 2253 2254 extern PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat); 2255 2256 #undef __FUNCT__ 2257 #define __FUNCT__ "MatFDColoringCreate_MPIBAIJ" 2258 /* 2259 This routine is almost identical to MatFDColoringCreate_MPIBAIJ()! 2260 */ 2261 PetscErrorCode MatFDColoringCreate_MPIBAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 2262 { 2263 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2264 PetscErrorCode ierr; 2265 PetscMPIInt size,*ncolsonproc,*disp,nn; 2266 PetscInt bs,i,n,nrows,j,k,m,*rows = 0,*A_ci,*A_cj,ncols,col; 2267 const PetscInt *is; 2268 PetscInt nis = iscoloring->n,nctot,*cols,*B_ci,*B_cj; 2269 PetscInt *rowhit,M,cstart,cend,colb; 2270 PetscInt *columnsforrow,l; 2271 IS *isa; 2272 PetscBool done,flg; 2273 ISLocalToGlobalMapping map = mat->cmap->bmapping; 2274 PetscInt *ltog = (map ? map->indices : (PetscInt*) PETSC_NULL) ,ctype=c->ctype; 2275 2276 PetscFunctionBegin; 2277 if (!mat->assembled) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be assembled first; MatAssemblyBegin/End();"); 2278 if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMappingBlock"); 2279 2280 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 2281 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2282 M = mat->rmap->n/bs; 2283 cstart = mat->cmap->rstart/bs; 2284 cend = mat->cmap->rend/bs; 2285 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 2286 c->N = mat->cmap->N/bs; 2287 c->m = mat->rmap->n/bs; 2288 c->rstart = mat->rmap->rstart/bs; 2289 2290 c->ncolors = nis; 2291 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr); 2292 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr); 2293 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr); 2294 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr); 2295 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr); 2296 ierr = PetscLogObjectMemory(c,5*nis*sizeof(PetscInt));CHKERRQ(ierr); 2297 2298 /* Allow access to data structures of local part of matrix */ 2299 if (!baij->colmap) { 2300 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2301 } 2302 ierr = MatGetColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 2303 ierr = MatGetColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 2304 2305 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr); 2306 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr); 2307 2308 for (i=0; i<nis; i++) { 2309 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 2310 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 2311 c->ncolumns[i] = n; 2312 if (n) { 2313 ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr); 2314 ierr = PetscLogObjectMemory(c,n*sizeof(PetscInt));CHKERRQ(ierr); 2315 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 2316 } else { 2317 c->columns[i] = 0; 2318 } 2319 2320 if (ctype == IS_COLORING_GLOBAL){ 2321 /* Determine the total (parallel) number of columns of this color */ 2322 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 2323 ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr); 2324 2325 nn = PetscMPIIntCast(n); 2326 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,((PetscObject)mat)->comm);CHKERRQ(ierr); 2327 nctot = 0; for (j=0; j<size; j++) {nctot += ncolsonproc[j];} 2328 if (!nctot) { 2329 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 2330 } 2331 2332 disp[0] = 0; 2333 for (j=1; j<size; j++) { 2334 disp[j] = disp[j-1] + ncolsonproc[j-1]; 2335 } 2336 2337 /* Get complete list of columns for color on each processor */ 2338 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2339 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,((PetscObject)mat)->comm);CHKERRQ(ierr); 2340 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 2341 } else if (ctype == IS_COLORING_GHOSTED){ 2342 /* Determine local number of columns of this color on this process, including ghost points */ 2343 nctot = n; 2344 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2345 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 2346 } else { 2347 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 2348 } 2349 2350 /* 2351 Mark all rows affect by these columns 2352 */ 2353 /* Temporary option to allow for debugging/testing */ 2354 flg = PETSC_FALSE; 2355 ierr = PetscOptionsGetBool(PETSC_NULL,"-matfdcoloring_slow",&flg,PETSC_NULL);CHKERRQ(ierr); 2356 if (!flg) {/*-----------------------------------------------------------------------------*/ 2357 /* crude, fast version */ 2358 ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr); 2359 /* loop over columns*/ 2360 for (j=0; j<nctot; j++) { 2361 if (ctype == IS_COLORING_GHOSTED) { 2362 col = ltog[cols[j]]; 2363 } else { 2364 col = cols[j]; 2365 } 2366 if (col >= cstart && col < cend) { 2367 /* column is in diagonal block of matrix */ 2368 rows = A_cj + A_ci[col-cstart]; 2369 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2370 } else { 2371 #if defined (PETSC_USE_CTABLE) 2372 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2373 colb --; 2374 #else 2375 colb = baij->colmap[col] - 1; 2376 #endif 2377 if (colb == -1) { 2378 m = 0; 2379 } else { 2380 colb = colb/bs; 2381 rows = B_cj + B_ci[colb]; 2382 m = B_ci[colb+1] - B_ci[colb]; 2383 } 2384 } 2385 /* loop over columns marking them in rowhit */ 2386 for (k=0; k<m; k++) { 2387 rowhit[*rows++] = col + 1; 2388 } 2389 } 2390 2391 /* count the number of hits */ 2392 nrows = 0; 2393 for (j=0; j<M; j++) { 2394 if (rowhit[j]) nrows++; 2395 } 2396 c->nrows[i] = nrows; 2397 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2398 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2399 ierr = PetscLogObjectMemory(c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2400 nrows = 0; 2401 for (j=0; j<M; j++) { 2402 if (rowhit[j]) { 2403 c->rows[i][nrows] = j; 2404 c->columnsforrow[i][nrows] = rowhit[j] - 1; 2405 nrows++; 2406 } 2407 } 2408 } else {/*-------------------------------------------------------------------------------*/ 2409 /* slow version, using rowhit as a linked list */ 2410 PetscInt currentcol,fm,mfm; 2411 rowhit[M] = M; 2412 nrows = 0; 2413 /* loop over columns*/ 2414 for (j=0; j<nctot; j++) { 2415 if (ctype == IS_COLORING_GHOSTED) { 2416 col = ltog[cols[j]]; 2417 } else { 2418 col = cols[j]; 2419 } 2420 if (col >= cstart && col < cend) { 2421 /* column is in diagonal block of matrix */ 2422 rows = A_cj + A_ci[col-cstart]; 2423 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2424 } else { 2425 #if defined (PETSC_USE_CTABLE) 2426 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2427 colb --; 2428 #else 2429 colb = baij->colmap[col] - 1; 2430 #endif 2431 if (colb == -1) { 2432 m = 0; 2433 } else { 2434 colb = colb/bs; 2435 rows = B_cj + B_ci[colb]; 2436 m = B_ci[colb+1] - B_ci[colb]; 2437 } 2438 } 2439 2440 /* loop over columns marking them in rowhit */ 2441 fm = M; /* fm points to first entry in linked list */ 2442 for (k=0; k<m; k++) { 2443 currentcol = *rows++; 2444 /* is it already in the list? */ 2445 do { 2446 mfm = fm; 2447 fm = rowhit[fm]; 2448 } while (fm < currentcol); 2449 /* not in list so add it */ 2450 if (fm != currentcol) { 2451 nrows++; 2452 columnsforrow[currentcol] = col; 2453 /* next three lines insert new entry into linked list */ 2454 rowhit[mfm] = currentcol; 2455 rowhit[currentcol] = fm; 2456 fm = currentcol; 2457 /* fm points to present position in list since we know the columns are sorted */ 2458 } else { 2459 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected"); 2460 } 2461 } 2462 } 2463 c->nrows[i] = nrows; 2464 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2465 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2466 ierr = PetscLogObjectMemory(c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2467 /* now store the linked list of rows into c->rows[i] */ 2468 nrows = 0; 2469 fm = rowhit[M]; 2470 do { 2471 c->rows[i][nrows] = fm; 2472 c->columnsforrow[i][nrows++] = columnsforrow[fm]; 2473 fm = rowhit[fm]; 2474 } while (fm < M); 2475 } /* ---------------------------------------------------------------------------------------*/ 2476 ierr = PetscFree(cols);CHKERRQ(ierr); 2477 } 2478 2479 /* Optimize by adding the vscale, and scaleforrow[][] fields */ 2480 /* 2481 vscale will contain the "diagonal" on processor scalings followed by the off processor 2482 */ 2483 if (ctype == IS_COLORING_GLOBAL) { 2484 PetscInt *garray; 2485 ierr = PetscMalloc(baij->B->cmap->n*sizeof(PetscInt),&garray);CHKERRQ(ierr); 2486 for (i=0; i<baij->B->cmap->n/bs; i++) { 2487 for (j=0; j<bs; j++) { 2488 garray[i*bs+j] = bs*baij->garray[i]+j; 2489 } 2490 } 2491 ierr = VecCreateGhost(((PetscObject)mat)->comm,baij->A->rmap->n,PETSC_DETERMINE,baij->B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 2492 ierr = PetscFree(garray);CHKERRQ(ierr); 2493 CHKMEMQ; 2494 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2495 for (k=0; k<c->ncolors; k++) { 2496 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2497 for (l=0; l<c->nrows[k]; l++) { 2498 col = c->columnsforrow[k][l]; 2499 if (col >= cstart && col < cend) { 2500 /* column is in diagonal block of matrix */ 2501 colb = col - cstart; 2502 } else { 2503 /* column is in "off-processor" part */ 2504 #if defined (PETSC_USE_CTABLE) 2505 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2506 colb --; 2507 #else 2508 colb = baij->colmap[col] - 1; 2509 #endif 2510 colb = colb/bs; 2511 colb += cend - cstart; 2512 } 2513 c->vscaleforrow[k][l] = colb; 2514 } 2515 } 2516 } else if (ctype == IS_COLORING_GHOSTED) { 2517 /* Get gtol mapping */ 2518 PetscInt N = mat->cmap->N, *gtol; 2519 ierr = PetscMalloc((N+1)*sizeof(PetscInt),>ol);CHKERRQ(ierr); 2520 for (i=0; i<N; i++) gtol[i] = -1; 2521 for (i=0; i<map->n; i++) gtol[ltog[i]] = i; 2522 2523 c->vscale = 0; /* will be created in MatFDColoringApply() */ 2524 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2525 for (k=0; k<c->ncolors; k++) { 2526 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2527 for (l=0; l<c->nrows[k]; l++) { 2528 col = c->columnsforrow[k][l]; /* global column index */ 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 CHKMEMQ; 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(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2559 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&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,((PetscObject)A)->comm);CHKERRQ(ierr); 2577 #else 2578 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);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,((PetscObject)A)->comm);CHKERRQ(ierr); 2636 #else 2637 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);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 (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2675 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2676 } 2677 2678 if (flag == SOR_APPLY_UPPER) { 2679 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2680 PetscFunctionReturn(0); 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(((PetscObject)matin)->comm,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,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 = { 2755 MatSetValues_MPIBAIJ, 2756 MatGetRow_MPIBAIJ, 2757 MatRestoreRow_MPIBAIJ, 2758 MatMult_MPIBAIJ, 2759 /* 4*/ MatMultAdd_MPIBAIJ, 2760 MatMultTranspose_MPIBAIJ, 2761 MatMultTransposeAdd_MPIBAIJ, 2762 0, 2763 0, 2764 0, 2765 /*10*/ 0, 2766 0, 2767 0, 2768 MatSOR_MPIBAIJ, 2769 MatTranspose_MPIBAIJ, 2770 /*15*/ MatGetInfo_MPIBAIJ, 2771 MatEqual_MPIBAIJ, 2772 MatGetDiagonal_MPIBAIJ, 2773 MatDiagonalScale_MPIBAIJ, 2774 MatNorm_MPIBAIJ, 2775 /*20*/ MatAssemblyBegin_MPIBAIJ, 2776 MatAssemblyEnd_MPIBAIJ, 2777 MatSetOption_MPIBAIJ, 2778 MatZeroEntries_MPIBAIJ, 2779 /*24*/ MatZeroRows_MPIBAIJ, 2780 0, 2781 0, 2782 0, 2783 0, 2784 /*29*/ MatSetUp_MPIBAIJ, 2785 0, 2786 0, 2787 0, 2788 0, 2789 /*34*/ MatDuplicate_MPIBAIJ, 2790 0, 2791 0, 2792 0, 2793 0, 2794 /*39*/ MatAXPY_MPIBAIJ, 2795 MatGetSubMatrices_MPIBAIJ, 2796 MatIncreaseOverlap_MPIBAIJ, 2797 MatGetValues_MPIBAIJ, 2798 MatCopy_MPIBAIJ, 2799 /*44*/ 0, 2800 MatScale_MPIBAIJ, 2801 0, 2802 0, 2803 0, 2804 /*49*/ 0, 2805 0, 2806 0, 2807 0, 2808 0, 2809 /*54*/ MatFDColoringCreate_MPIBAIJ, 2810 0, 2811 MatSetUnfactored_MPIBAIJ, 2812 MatPermute_MPIBAIJ, 2813 MatSetValuesBlocked_MPIBAIJ, 2814 /*59*/ MatGetSubMatrix_MPIBAIJ, 2815 MatDestroy_MPIBAIJ, 2816 MatView_MPIBAIJ, 2817 0, 2818 0, 2819 /*64*/ 0, 2820 0, 2821 0, 2822 0, 2823 0, 2824 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2825 0, 2826 0, 2827 0, 2828 0, 2829 /*74*/ 0, 2830 MatFDColoringApply_BAIJ, 2831 0, 2832 0, 2833 0, 2834 /*79*/ 0, 2835 0, 2836 0, 2837 0, 2838 MatLoad_MPIBAIJ, 2839 /*84*/ 0, 2840 0, 2841 0, 2842 0, 2843 0, 2844 /*89*/ 0, 2845 0, 2846 0, 2847 0, 2848 0, 2849 /*94*/ 0, 2850 0, 2851 0, 2852 0, 2853 0, 2854 /*99*/ 0, 2855 0, 2856 0, 2857 0, 2858 0, 2859 /*104*/0, 2860 MatRealPart_MPIBAIJ, 2861 MatImaginaryPart_MPIBAIJ, 2862 0, 2863 0, 2864 /*109*/0, 2865 0, 2866 0, 2867 0, 2868 0, 2869 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2870 0, 2871 MatGetGhosts_MPIBAIJ, 2872 0, 2873 0, 2874 /*119*/0, 2875 0, 2876 0, 2877 0, 2878 0, 2879 /*124*/0, 2880 0, 2881 MatInvertBlockDiagonal_MPIBAIJ 2882 }; 2883 2884 EXTERN_C_BEGIN 2885 #undef __FUNCT__ 2886 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2887 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2888 { 2889 PetscFunctionBegin; 2890 *a = ((Mat_MPIBAIJ *)A->data)->A; 2891 PetscFunctionReturn(0); 2892 } 2893 EXTERN_C_END 2894 2895 EXTERN_C_BEGIN 2896 extern PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2897 EXTERN_C_END 2898 2899 EXTERN_C_BEGIN 2900 #undef __FUNCT__ 2901 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2902 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2903 { 2904 PetscInt m,rstart,cstart,cend; 2905 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2906 const PetscInt *JJ=0; 2907 PetscScalar *values=0; 2908 PetscErrorCode ierr; 2909 2910 PetscFunctionBegin; 2911 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2912 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2913 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2914 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2915 m = B->rmap->n/bs; 2916 rstart = B->rmap->rstart/bs; 2917 cstart = B->cmap->rstart/bs; 2918 cend = B->cmap->rend/bs; 2919 2920 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2921 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 2922 for (i=0; i<m; i++) { 2923 nz = ii[i+1] - ii[i]; 2924 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2925 nz_max = PetscMax(nz_max,nz); 2926 JJ = jj + ii[i]; 2927 for (j=0; j<nz; j++) { 2928 if (*JJ >= cstart) break; 2929 JJ++; 2930 } 2931 d = 0; 2932 for (; j<nz; j++) { 2933 if (*JJ++ >= cend) break; 2934 d++; 2935 } 2936 d_nnz[i] = d; 2937 o_nnz[i] = nz - d; 2938 } 2939 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2940 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2941 2942 values = (PetscScalar*)V; 2943 if (!values) { 2944 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2945 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2946 } 2947 for (i=0; i<m; i++) { 2948 PetscInt row = i + rstart; 2949 PetscInt ncols = ii[i+1] - ii[i]; 2950 const PetscInt *icols = jj + ii[i]; 2951 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2952 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2953 } 2954 2955 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2956 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2957 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2958 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2959 PetscFunctionReturn(0); 2960 } 2961 EXTERN_C_END 2962 2963 #undef __FUNCT__ 2964 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2965 /*@C 2966 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2967 (the default parallel PETSc format). 2968 2969 Collective on MPI_Comm 2970 2971 Input Parameters: 2972 + A - the matrix 2973 . bs - the block size 2974 . i - the indices into j for the start of each local row (starts with zero) 2975 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2976 - v - optional values in the matrix 2977 2978 Level: developer 2979 2980 .keywords: matrix, aij, compressed row, sparse, parallel 2981 2982 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2983 @*/ 2984 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2985 { 2986 PetscErrorCode ierr; 2987 2988 PetscFunctionBegin; 2989 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2990 PetscValidType(B,1); 2991 PetscValidLogicalCollectiveInt(B,bs,2); 2992 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2993 PetscFunctionReturn(0); 2994 } 2995 2996 EXTERN_C_BEGIN 2997 #undef __FUNCT__ 2998 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2999 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 3000 { 3001 Mat_MPIBAIJ *b; 3002 PetscErrorCode ierr; 3003 PetscInt i; 3004 PetscBool d_realalloc = PETSC_FALSE,o_realalloc = PETSC_FALSE; 3005 3006 PetscFunctionBegin; 3007 if (d_nz >= 0 || d_nnz) d_realalloc = PETSC_TRUE; 3008 if (o_nz >= 0 || o_nnz) o_realalloc = PETSC_TRUE; 3009 3010 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 3011 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 3012 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 3013 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 3014 3015 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 3016 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 3017 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3018 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3019 3020 if (d_nnz) { 3021 for (i=0; i<B->rmap->n/bs; i++) { 3022 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]); 3023 } 3024 } 3025 if (o_nnz) { 3026 for (i=0; i<B->rmap->n/bs; i++) { 3027 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]); 3028 } 3029 } 3030 3031 b = (Mat_MPIBAIJ*)B->data; 3032 b->bs2 = bs*bs; 3033 b->mbs = B->rmap->n/bs; 3034 b->nbs = B->cmap->n/bs; 3035 b->Mbs = B->rmap->N/bs; 3036 b->Nbs = B->cmap->N/bs; 3037 3038 for (i=0; i<=b->size; i++) { 3039 b->rangebs[i] = B->rmap->range[i]/bs; 3040 } 3041 b->rstartbs = B->rmap->rstart/bs; 3042 b->rendbs = B->rmap->rend/bs; 3043 b->cstartbs = B->cmap->rstart/bs; 3044 b->cendbs = B->cmap->rend/bs; 3045 3046 if (!B->preallocated) { 3047 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3048 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3049 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 3050 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3051 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3052 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3053 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 3054 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3055 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 3056 } 3057 3058 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3059 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 3060 /* Do not error if the user did not give real preallocation information. Ugly because this would overwrite a previous user call to MatSetOption(). */ 3061 if (!d_realalloc) {ierr = MatSetOption(b->A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3062 if (!o_realalloc) {ierr = MatSetOption(b->B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3063 B->preallocated = PETSC_TRUE; 3064 PetscFunctionReturn(0); 3065 } 3066 EXTERN_C_END 3067 3068 EXTERN_C_BEGIN 3069 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 3070 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 3071 EXTERN_C_END 3072 3073 3074 EXTERN_C_BEGIN 3075 #undef __FUNCT__ 3076 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 3077 PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, const MatType newtype,MatReuse reuse,Mat *adj) 3078 { 3079 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 3080 PetscErrorCode ierr; 3081 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 3082 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 3083 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 3084 3085 PetscFunctionBegin; 3086 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 3087 ii[0] = 0; 3088 CHKMEMQ; 3089 for (i=0; i<M; i++) { 3090 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]); 3091 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]); 3092 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 3093 /* remove one from count of matrix has diagonal */ 3094 for (j=id[i]; j<id[i+1]; j++) { 3095 if (jd[j] == i) {ii[i+1]--;break;} 3096 } 3097 CHKMEMQ; 3098 } 3099 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 3100 cnt = 0; 3101 for (i=0; i<M; i++) { 3102 for (j=io[i]; j<io[i+1]; j++) { 3103 if (garray[jo[j]] > rstart) break; 3104 jj[cnt++] = garray[jo[j]]; 3105 CHKMEMQ; 3106 } 3107 for (k=id[i]; k<id[i+1]; k++) { 3108 if (jd[k] != i) { 3109 jj[cnt++] = rstart + jd[k]; 3110 CHKMEMQ; 3111 } 3112 } 3113 for (;j<io[i+1]; j++) { 3114 jj[cnt++] = garray[jo[j]]; 3115 CHKMEMQ; 3116 } 3117 } 3118 ierr = MatCreateMPIAdj(((PetscObject)B)->comm,M,B->cmap->N/B->rmap->bs,ii,jj,PETSC_NULL,adj);CHKERRQ(ierr); 3119 PetscFunctionReturn(0); 3120 } 3121 EXTERN_C_END 3122 3123 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3124 EXTERN_C_BEGIN 3125 PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,const MatType,MatReuse,Mat*); 3126 EXTERN_C_END 3127 3128 EXTERN_C_BEGIN 3129 #undef __FUNCT__ 3130 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 3131 PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,const MatType newtype,MatReuse reuse,Mat *newmat) 3132 { 3133 PetscErrorCode ierr; 3134 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3135 Mat B; 3136 Mat_MPIAIJ *b; 3137 3138 PetscFunctionBegin; 3139 if (!A->assembled) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_SUP,"Matrix must be assembled"); 3140 3141 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 3142 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 3143 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 3144 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3145 ierr = MatMPIAIJSetPreallocation(B,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 3146 b = (Mat_MPIAIJ*) B->data; 3147 3148 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 3149 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3150 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 3151 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 3152 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 3153 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3154 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3155 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3156 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3157 if (reuse == MAT_REUSE_MATRIX) { 3158 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 3159 } else { 3160 *newmat = B; 3161 } 3162 PetscFunctionReturn(0); 3163 } 3164 EXTERN_C_END 3165 3166 EXTERN_C_BEGIN 3167 #if defined(PETSC_HAVE_MUMPS) 3168 extern PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 3169 #endif 3170 EXTERN_C_END 3171 3172 /*MC 3173 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 3174 3175 Options Database Keys: 3176 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3177 . -mat_block_size <bs> - set the blocksize used to store the matrix 3178 - -mat_use_hash_table <fact> 3179 3180 Level: beginner 3181 3182 .seealso: MatCreateMPIBAIJ 3183 M*/ 3184 3185 EXTERN_C_BEGIN 3186 extern PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,const MatType,MatReuse,Mat*); 3187 EXTERN_C_END 3188 3189 EXTERN_C_BEGIN 3190 #undef __FUNCT__ 3191 #define __FUNCT__ "MatCreate_MPIBAIJ" 3192 PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3193 { 3194 Mat_MPIBAIJ *b; 3195 PetscErrorCode ierr; 3196 PetscBool flg; 3197 3198 PetscFunctionBegin; 3199 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 3200 B->data = (void*)b; 3201 3202 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3203 B->assembled = PETSC_FALSE; 3204 3205 B->insertmode = NOT_SET_VALUES; 3206 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 3207 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 3208 3209 /* build local table of row and column ownerships */ 3210 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 3211 3212 /* build cache for off array entries formed */ 3213 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 3214 b->donotstash = PETSC_FALSE; 3215 b->colmap = PETSC_NULL; 3216 b->garray = PETSC_NULL; 3217 b->roworiented = PETSC_TRUE; 3218 3219 /* stuff used in block assembly */ 3220 b->barray = 0; 3221 3222 /* stuff used for matrix vector multiply */ 3223 b->lvec = 0; 3224 b->Mvctx = 0; 3225 3226 /* stuff for MatGetRow() */ 3227 b->rowindices = 0; 3228 b->rowvalues = 0; 3229 b->getrowactive = PETSC_FALSE; 3230 3231 /* hash table stuff */ 3232 b->ht = 0; 3233 b->hd = 0; 3234 b->ht_size = 0; 3235 b->ht_flag = PETSC_FALSE; 3236 b->ht_fact = 0; 3237 b->ht_total_ct = 0; 3238 b->ht_insert_ct = 0; 3239 3240 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3241 b->ijonly = PETSC_FALSE; 3242 3243 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3244 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 3245 if (flg) { 3246 PetscReal fact = 1.39; 3247 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3248 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 3249 if (fact <= 1.0) fact = 1.39; 3250 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3251 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3252 } 3253 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3254 3255 #if defined(PETSC_HAVE_MUMPS) 3256 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", "MatGetFactor_baij_mumps",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3257 #endif 3258 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiadj_C", 3259 "MatConvert_MPIBAIJ_MPIAdj", 3260 MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3261 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiaij_C", 3262 "MatConvert_MPIBAIJ_MPIAIJ", 3263 MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3264 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C", 3265 "MatConvert_MPIBAIJ_MPISBAIJ", 3266 MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3267 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 3268 "MatStoreValues_MPIBAIJ", 3269 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3270 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 3271 "MatRetrieveValues_MPIBAIJ", 3272 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3273 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 3274 "MatGetDiagonalBlock_MPIBAIJ", 3275 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3276 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 3277 "MatMPIBAIJSetPreallocation_MPIBAIJ", 3278 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3279 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 3280 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 3281 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3282 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 3283 "MatDiagonalScaleLocal_MPIBAIJ", 3284 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3285 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 3286 "MatSetHashTableFactor_MPIBAIJ", 3287 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3288 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C", 3289 "MatConvert_MPIBAIJ_MPIBSTRM", 3290 MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3291 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3292 PetscFunctionReturn(0); 3293 } 3294 EXTERN_C_END 3295 3296 /*MC 3297 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3298 3299 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3300 and MATMPIBAIJ otherwise. 3301 3302 Options Database Keys: 3303 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3304 3305 Level: beginner 3306 3307 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3308 M*/ 3309 3310 #undef __FUNCT__ 3311 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3312 /*@C 3313 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3314 (block compressed row). For good matrix assembly performance 3315 the user should preallocate the matrix storage by setting the parameters 3316 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3317 performance can be increased by more than a factor of 50. 3318 3319 Collective on Mat 3320 3321 Input Parameters: 3322 + A - the matrix 3323 . bs - size of blockk 3324 . d_nz - number of block nonzeros per block row in diagonal portion of local 3325 submatrix (same for all local rows) 3326 . d_nnz - array containing the number of block nonzeros in the various block rows 3327 of the in diagonal portion of the local (possibly different for each block 3328 row) or PETSC_NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3329 set it even if it is zero. 3330 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3331 submatrix (same for all local rows). 3332 - o_nnz - array containing the number of nonzeros in the various block rows of the 3333 off-diagonal portion of the local submatrix (possibly different for 3334 each block row) or PETSC_NULL. 3335 3336 If the *_nnz parameter is given then the *_nz parameter is ignored 3337 3338 Options Database Keys: 3339 + -mat_block_size - size of the blocks to use 3340 - -mat_use_hash_table <fact> 3341 3342 Notes: 3343 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3344 than it must be used on all processors that share the object for that argument. 3345 3346 Storage Information: 3347 For a square global matrix we define each processor's diagonal portion 3348 to be its local rows and the corresponding columns (a square submatrix); 3349 each processor's off-diagonal portion encompasses the remainder of the 3350 local matrix (a rectangular submatrix). 3351 3352 The user can specify preallocated storage for the diagonal part of 3353 the local submatrix with either d_nz or d_nnz (not both). Set 3354 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 3355 memory allocation. Likewise, specify preallocated storage for the 3356 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3357 3358 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3359 the figure below we depict these three local rows and all columns (0-11). 3360 3361 .vb 3362 0 1 2 3 4 5 6 7 8 9 10 11 3363 ------------------- 3364 row 3 | o o o d d d o o o o o o 3365 row 4 | o o o d d d o o o o o o 3366 row 5 | o o o d d d o o o o o o 3367 ------------------- 3368 .ve 3369 3370 Thus, any entries in the d locations are stored in the d (diagonal) 3371 submatrix, and any entries in the o locations are stored in the 3372 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3373 stored simply in the MATSEQBAIJ format for compressed row storage. 3374 3375 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3376 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3377 In general, for PDE problems in which most nonzeros are near the diagonal, 3378 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3379 or you will get TERRIBLE performance; see the users' manual chapter on 3380 matrices. 3381 3382 You can call MatGetInfo() to get information on how effective the preallocation was; 3383 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3384 You can also run with the option -info and look for messages with the string 3385 malloc in them to see if additional memory allocation was needed. 3386 3387 Level: intermediate 3388 3389 .keywords: matrix, block, aij, compressed row, sparse, parallel 3390 3391 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR() 3392 @*/ 3393 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3394 { 3395 PetscErrorCode ierr; 3396 3397 PetscFunctionBegin; 3398 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3399 PetscValidType(B,1); 3400 PetscValidLogicalCollectiveInt(B,bs,2); 3401 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); 3402 PetscFunctionReturn(0); 3403 } 3404 3405 #undef __FUNCT__ 3406 #define __FUNCT__ "MatCreateBAIJ" 3407 /*@C 3408 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3409 (block compressed row). For good matrix assembly performance 3410 the user should preallocate the matrix storage by setting the parameters 3411 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3412 performance can be increased by more than a factor of 50. 3413 3414 Collective on MPI_Comm 3415 3416 Input Parameters: 3417 + comm - MPI communicator 3418 . bs - size of blockk 3419 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3420 This value should be the same as the local size used in creating the 3421 y vector for the matrix-vector product y = Ax. 3422 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3423 This value should be the same as the local size used in creating the 3424 x vector for the matrix-vector product y = Ax. 3425 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3426 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3427 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3428 submatrix (same for all local rows) 3429 . d_nnz - array containing the number of nonzero blocks in the various block rows 3430 of the in diagonal portion of the local (possibly different for each block 3431 row) or PETSC_NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3432 and set it even if it is zero. 3433 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3434 submatrix (same for all local rows). 3435 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3436 off-diagonal portion of the local submatrix (possibly different for 3437 each block row) or PETSC_NULL. 3438 3439 Output Parameter: 3440 . A - the matrix 3441 3442 Options Database Keys: 3443 + -mat_block_size - size of the blocks to use 3444 - -mat_use_hash_table <fact> 3445 3446 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3447 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3448 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3449 3450 Notes: 3451 If the *_nnz parameter is given then the *_nz parameter is ignored 3452 3453 A nonzero block is any block that as 1 or more nonzeros in it 3454 3455 The user MUST specify either the local or global matrix dimensions 3456 (possibly both). 3457 3458 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3459 than it must be used on all processors that share the object for that argument. 3460 3461 Storage Information: 3462 For a square global matrix we define each processor's diagonal portion 3463 to be its local rows and the corresponding columns (a square submatrix); 3464 each processor's off-diagonal portion encompasses the remainder of the 3465 local matrix (a rectangular submatrix). 3466 3467 The user can specify preallocated storage for the diagonal part of 3468 the local submatrix with either d_nz or d_nnz (not both). Set 3469 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 3470 memory allocation. Likewise, specify preallocated storage for the 3471 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3472 3473 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3474 the figure below we depict these three local rows and all columns (0-11). 3475 3476 .vb 3477 0 1 2 3 4 5 6 7 8 9 10 11 3478 ------------------- 3479 row 3 | o o o d d d o o o o o o 3480 row 4 | o o o d d d o o o o o o 3481 row 5 | o o o d d d o o o o o o 3482 ------------------- 3483 .ve 3484 3485 Thus, any entries in the d locations are stored in the d (diagonal) 3486 submatrix, and any entries in the o locations are stored in the 3487 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3488 stored simply in the MATSEQBAIJ format for compressed row storage. 3489 3490 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3491 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3492 In general, for PDE problems in which most nonzeros are near the diagonal, 3493 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3494 or you will get TERRIBLE performance; see the users' manual chapter on 3495 matrices. 3496 3497 Level: intermediate 3498 3499 .keywords: matrix, block, aij, compressed row, sparse, parallel 3500 3501 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3502 @*/ 3503 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) 3504 { 3505 PetscErrorCode ierr; 3506 PetscMPIInt size; 3507 3508 PetscFunctionBegin; 3509 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3510 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3511 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3512 if (size > 1) { 3513 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3514 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3515 } else { 3516 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3517 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3518 } 3519 PetscFunctionReturn(0); 3520 } 3521 3522 #undef __FUNCT__ 3523 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3524 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3525 { 3526 Mat mat; 3527 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3528 PetscErrorCode ierr; 3529 PetscInt len=0; 3530 3531 PetscFunctionBegin; 3532 *newmat = 0; 3533 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 3534 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3535 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3536 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3537 3538 mat->factortype = matin->factortype; 3539 mat->preallocated = PETSC_TRUE; 3540 mat->assembled = PETSC_TRUE; 3541 mat->insertmode = NOT_SET_VALUES; 3542 3543 a = (Mat_MPIBAIJ*)mat->data; 3544 mat->rmap->bs = matin->rmap->bs; 3545 a->bs2 = oldmat->bs2; 3546 a->mbs = oldmat->mbs; 3547 a->nbs = oldmat->nbs; 3548 a->Mbs = oldmat->Mbs; 3549 a->Nbs = oldmat->Nbs; 3550 3551 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3552 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3553 3554 a->size = oldmat->size; 3555 a->rank = oldmat->rank; 3556 a->donotstash = oldmat->donotstash; 3557 a->roworiented = oldmat->roworiented; 3558 a->rowindices = 0; 3559 a->rowvalues = 0; 3560 a->getrowactive = PETSC_FALSE; 3561 a->barray = 0; 3562 a->rstartbs = oldmat->rstartbs; 3563 a->rendbs = oldmat->rendbs; 3564 a->cstartbs = oldmat->cstartbs; 3565 a->cendbs = oldmat->cendbs; 3566 3567 /* hash table stuff */ 3568 a->ht = 0; 3569 a->hd = 0; 3570 a->ht_size = 0; 3571 a->ht_flag = oldmat->ht_flag; 3572 a->ht_fact = oldmat->ht_fact; 3573 a->ht_total_ct = 0; 3574 a->ht_insert_ct = 0; 3575 3576 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3577 if (oldmat->colmap) { 3578 #if defined (PETSC_USE_CTABLE) 3579 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3580 #else 3581 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3582 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3583 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3584 #endif 3585 } else a->colmap = 0; 3586 3587 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3588 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3589 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3590 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3591 } else a->garray = 0; 3592 3593 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3594 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3595 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3596 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3597 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3598 3599 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3600 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3601 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3602 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3603 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3604 *newmat = mat; 3605 3606 PetscFunctionReturn(0); 3607 } 3608 3609 #undef __FUNCT__ 3610 #define __FUNCT__ "MatLoad_MPIBAIJ" 3611 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3612 { 3613 PetscErrorCode ierr; 3614 int fd; 3615 PetscInt i,nz,j,rstart,rend; 3616 PetscScalar *vals,*buf; 3617 MPI_Comm comm = ((PetscObject)viewer)->comm; 3618 MPI_Status status; 3619 PetscMPIInt rank,size,maxnz; 3620 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3621 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 3622 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3623 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3624 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 3625 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3626 3627 PetscFunctionBegin; 3628 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3629 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 3630 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3631 3632 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3633 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3634 if (!rank) { 3635 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3636 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 3637 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3638 } 3639 3640 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3641 3642 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3643 M = header[1]; N = header[2]; 3644 3645 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3646 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3647 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3648 3649 /* If global sizes are set, check if they are consistent with that given in the file */ 3650 if (sizesset) { 3651 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3652 } 3653 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); 3654 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); 3655 3656 if (M != N) SETERRQ(((PetscObject)viewer)->comm,PETSC_ERR_SUP,"Can only do square matrices"); 3657 3658 /* 3659 This code adds extra rows to make sure the number of rows is 3660 divisible by the blocksize 3661 */ 3662 Mbs = M/bs; 3663 extra_rows = bs - M + bs*Mbs; 3664 if (extra_rows == bs) extra_rows = 0; 3665 else Mbs++; 3666 if (extra_rows && !rank) { 3667 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3668 } 3669 3670 /* determine ownership of all rows */ 3671 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3672 mbs = Mbs/size + ((Mbs % size) > rank); 3673 m = mbs*bs; 3674 } else { /* User set */ 3675 m = newmat->rmap->n; 3676 mbs = m/bs; 3677 } 3678 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 3679 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3680 3681 /* process 0 needs enough room for process with most rows */ 3682 if (!rank) { 3683 mmax = rowners[1]; 3684 for (i=2; i<size; i++) { 3685 mmax = PetscMax(mmax,rowners[i]); 3686 } 3687 mmax*=bs; 3688 } else mmax = m; 3689 3690 rowners[0] = 0; 3691 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3692 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3693 rstart = rowners[rank]; 3694 rend = rowners[rank+1]; 3695 3696 /* distribute row lengths to all processors */ 3697 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 3698 if (!rank) { 3699 mend = m; 3700 if (size == 1) mend = mend - extra_rows; 3701 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3702 for (j=mend; j<m; j++) locrowlens[j] = 1; 3703 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3704 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3705 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3706 for (j=0; j<m; j++) { 3707 procsnz[0] += locrowlens[j]; 3708 } 3709 for (i=1; i<size; i++) { 3710 mend = browners[i+1] - browners[i]; 3711 if (i == size-1) mend = mend - extra_rows; 3712 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3713 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3714 /* calculate the number of nonzeros on each processor */ 3715 for (j=0; j<browners[i+1]-browners[i]; j++) { 3716 procsnz[i] += rowlengths[j]; 3717 } 3718 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3719 } 3720 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3721 } else { 3722 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3723 } 3724 3725 if (!rank) { 3726 /* determine max buffer needed and allocate it */ 3727 maxnz = procsnz[0]; 3728 for (i=1; i<size; i++) { 3729 maxnz = PetscMax(maxnz,procsnz[i]); 3730 } 3731 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3732 3733 /* read in my part of the matrix column indices */ 3734 nz = procsnz[0]; 3735 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3736 mycols = ibuf; 3737 if (size == 1) nz -= extra_rows; 3738 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3739 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 3740 3741 /* read in every ones (except the last) and ship off */ 3742 for (i=1; i<size-1; i++) { 3743 nz = procsnz[i]; 3744 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3745 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3746 } 3747 /* read in the stuff for the last proc */ 3748 if (size != 1) { 3749 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3750 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3751 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3752 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3753 } 3754 ierr = PetscFree(cols);CHKERRQ(ierr); 3755 } else { 3756 /* determine buffer space needed for message */ 3757 nz = 0; 3758 for (i=0; i<m; i++) { 3759 nz += locrowlens[i]; 3760 } 3761 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3762 mycols = ibuf; 3763 /* receive message of column indices*/ 3764 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3765 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3766 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3767 } 3768 3769 /* loop over local rows, determining number of off diagonal entries */ 3770 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3771 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3772 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3773 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3774 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3775 rowcount = 0; nzcount = 0; 3776 for (i=0; i<mbs; i++) { 3777 dcount = 0; 3778 odcount = 0; 3779 for (j=0; j<bs; j++) { 3780 kmax = locrowlens[rowcount]; 3781 for (k=0; k<kmax; k++) { 3782 tmp = mycols[nzcount++]/bs; 3783 if (!mask[tmp]) { 3784 mask[tmp] = 1; 3785 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3786 else masked1[dcount++] = tmp; 3787 } 3788 } 3789 rowcount++; 3790 } 3791 3792 dlens[i] = dcount; 3793 odlens[i] = odcount; 3794 3795 /* zero out the mask elements we set */ 3796 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3797 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3798 } 3799 3800 3801 if (!sizesset) { 3802 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3803 } 3804 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3805 3806 if (!rank) { 3807 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3808 /* read in my part of the matrix numerical values */ 3809 nz = procsnz[0]; 3810 vals = buf; 3811 mycols = ibuf; 3812 if (size == 1) nz -= extra_rows; 3813 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3814 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 3815 3816 /* insert into matrix */ 3817 jj = rstart*bs; 3818 for (i=0; i<m; i++) { 3819 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3820 mycols += locrowlens[i]; 3821 vals += locrowlens[i]; 3822 jj++; 3823 } 3824 /* read in other processors (except the last one) and ship out */ 3825 for (i=1; i<size-1; i++) { 3826 nz = procsnz[i]; 3827 vals = buf; 3828 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3829 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3830 } 3831 /* the last proc */ 3832 if (size != 1){ 3833 nz = procsnz[i] - extra_rows; 3834 vals = buf; 3835 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3836 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3837 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3838 } 3839 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3840 } else { 3841 /* receive numeric values */ 3842 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3843 3844 /* receive message of values*/ 3845 vals = buf; 3846 mycols = ibuf; 3847 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 3848 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 3849 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3850 3851 /* insert into matrix */ 3852 jj = rstart*bs; 3853 for (i=0; i<m; i++) { 3854 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3855 mycols += locrowlens[i]; 3856 vals += locrowlens[i]; 3857 jj++; 3858 } 3859 } 3860 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3861 ierr = PetscFree(buf);CHKERRQ(ierr); 3862 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3863 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3864 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3865 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3866 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3867 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3868 3869 PetscFunctionReturn(0); 3870 } 3871 3872 #undef __FUNCT__ 3873 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3874 /*@ 3875 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3876 3877 Input Parameters: 3878 . mat - the matrix 3879 . fact - factor 3880 3881 Not Collective, each process can use a different factor 3882 3883 Level: advanced 3884 3885 Notes: 3886 This can also be set by the command line option: -mat_use_hash_table <fact> 3887 3888 .keywords: matrix, hashtable, factor, HT 3889 3890 .seealso: MatSetOption() 3891 @*/ 3892 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3893 { 3894 PetscErrorCode ierr; 3895 3896 PetscFunctionBegin; 3897 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3898 PetscFunctionReturn(0); 3899 } 3900 3901 EXTERN_C_BEGIN 3902 #undef __FUNCT__ 3903 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3904 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3905 { 3906 Mat_MPIBAIJ *baij; 3907 3908 PetscFunctionBegin; 3909 baij = (Mat_MPIBAIJ*)mat->data; 3910 baij->ht_fact = fact; 3911 PetscFunctionReturn(0); 3912 } 3913 EXTERN_C_END 3914 3915 #undef __FUNCT__ 3916 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3917 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3918 { 3919 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 3920 PetscFunctionBegin; 3921 *Ad = a->A; 3922 *Ao = a->B; 3923 *colmap = a->garray; 3924 PetscFunctionReturn(0); 3925 } 3926 3927 /* 3928 Special version for direct calls from Fortran (to eliminate two function call overheads 3929 */ 3930 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3931 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3932 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3933 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3934 #endif 3935 3936 #undef __FUNCT__ 3937 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3938 /*@C 3939 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3940 3941 Collective on Mat 3942 3943 Input Parameters: 3944 + mat - the matrix 3945 . min - number of input rows 3946 . im - input rows 3947 . nin - number of input columns 3948 . in - input columns 3949 . v - numerical values input 3950 - addvin - INSERT_VALUES or ADD_VALUES 3951 3952 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3953 3954 Level: advanced 3955 3956 .seealso: MatSetValuesBlocked() 3957 @*/ 3958 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3959 { 3960 /* convert input arguments to C version */ 3961 Mat mat = *matin; 3962 PetscInt m = *min, n = *nin; 3963 InsertMode addv = *addvin; 3964 3965 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3966 const MatScalar *value; 3967 MatScalar *barray=baij->barray; 3968 PetscBool roworiented = baij->roworiented; 3969 PetscErrorCode ierr; 3970 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3971 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3972 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3973 3974 PetscFunctionBegin; 3975 /* tasks normally handled by MatSetValuesBlocked() */ 3976 if (mat->insertmode == NOT_SET_VALUES) { 3977 mat->insertmode = addv; 3978 } 3979 #if defined(PETSC_USE_DEBUG) 3980 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3981 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3982 #endif 3983 if (mat->assembled) { 3984 mat->was_assembled = PETSC_TRUE; 3985 mat->assembled = PETSC_FALSE; 3986 } 3987 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3988 3989 3990 if(!barray) { 3991 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3992 baij->barray = barray; 3993 } 3994 3995 if (roworiented) { 3996 stepval = (n-1)*bs; 3997 } else { 3998 stepval = (m-1)*bs; 3999 } 4000 for (i=0; i<m; i++) { 4001 if (im[i] < 0) continue; 4002 #if defined(PETSC_USE_DEBUG) 4003 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); 4004 #endif 4005 if (im[i] >= rstart && im[i] < rend) { 4006 row = im[i] - rstart; 4007 for (j=0; j<n; j++) { 4008 /* If NumCol = 1 then a copy is not required */ 4009 if ((roworiented) && (n == 1)) { 4010 barray = (MatScalar*)v + i*bs2; 4011 } else if((!roworiented) && (m == 1)) { 4012 barray = (MatScalar*)v + j*bs2; 4013 } else { /* Here a copy is required */ 4014 if (roworiented) { 4015 value = v + i*(stepval+bs)*bs + j*bs; 4016 } else { 4017 value = v + j*(stepval+bs)*bs + i*bs; 4018 } 4019 for (ii=0; ii<bs; ii++,value+=stepval) { 4020 for (jj=0; jj<bs; jj++) { 4021 *barray++ = *value++; 4022 } 4023 } 4024 barray -=bs2; 4025 } 4026 4027 if (in[j] >= cstart && in[j] < cend){ 4028 col = in[j] - cstart; 4029 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 4030 } 4031 else if (in[j] < 0) continue; 4032 #if defined(PETSC_USE_DEBUG) 4033 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); 4034 #endif 4035 else { 4036 if (mat->was_assembled) { 4037 if (!baij->colmap) { 4038 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 4039 } 4040 4041 #if defined(PETSC_USE_DEBUG) 4042 #if defined (PETSC_USE_CTABLE) 4043 { PetscInt data; 4044 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 4045 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 4046 } 4047 #else 4048 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 4049 #endif 4050 #endif 4051 #if defined (PETSC_USE_CTABLE) 4052 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4053 col = (col - 1)/bs; 4054 #else 4055 col = (baij->colmap[in[j]] - 1)/bs; 4056 #endif 4057 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 4058 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 4059 col = in[j]; 4060 } 4061 } 4062 else col = in[j]; 4063 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 4064 } 4065 } 4066 } else { 4067 if (!baij->donotstash) { 4068 if (roworiented) { 4069 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4070 } else { 4071 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4072 } 4073 } 4074 } 4075 } 4076 4077 /* task normally handled by MatSetValuesBlocked() */ 4078 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 4079 PetscFunctionReturn(0); 4080 } 4081 4082 #undef __FUNCT__ 4083 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 4084 /*@ 4085 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 4086 CSR format the local rows. 4087 4088 Collective on MPI_Comm 4089 4090 Input Parameters: 4091 + comm - MPI communicator 4092 . bs - the block size, only a block size of 1 is supported 4093 . m - number of local rows (Cannot be PETSC_DECIDE) 4094 . n - This value should be the same as the local size used in creating the 4095 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4096 calculated if N is given) For square matrices n is almost always m. 4097 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4098 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4099 . i - row indices 4100 . j - column indices 4101 - a - matrix values 4102 4103 Output Parameter: 4104 . mat - the matrix 4105 4106 Level: intermediate 4107 4108 Notes: 4109 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4110 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4111 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4112 4113 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4114 4115 .keywords: matrix, aij, compressed row, sparse, parallel 4116 4117 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4118 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4119 @*/ 4120 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) 4121 { 4122 PetscErrorCode ierr; 4123 4124 4125 PetscFunctionBegin; 4126 if (i[0]) { 4127 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4128 } 4129 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4130 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4131 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4132 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 4133 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 4134 PetscFunctionReturn(0); 4135 } 4136