1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 5 EXTERN PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 EXTERN PetscErrorCode DisAssemble_MPIBAIJ(Mat); 7 EXTERN PetscErrorCode MatIncreaseOverlap_MPIBAIJ(Mat,PetscInt,IS[],PetscInt); 8 EXTERN PetscErrorCode MatGetSubMatrices_MPIBAIJ(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]); 9 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 10 EXTERN PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 11 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 12 EXTERN PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 13 EXTERN PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 14 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar); 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 18 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 19 { 20 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 21 PetscErrorCode ierr; 22 PetscInt i,*idxb = 0; 23 PetscScalar *va,*vb; 24 Vec vtmp; 25 26 PetscFunctionBegin; 27 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 28 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 29 if (idx) { 30 for (i=0; i<A->rmap->n; i++) {if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;} 31 } 32 33 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 34 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 35 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 36 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 37 38 for (i=0; i<A->rmap->n; i++){ 39 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {va[i] = vb[i]; if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);} 40 } 41 42 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 43 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 44 if (idxb) {ierr = PetscFree(idxb);CHKERRQ(ierr);} 45 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 46 PetscFunctionReturn(0); 47 } 48 49 EXTERN_C_BEGIN 50 #undef __FUNCT__ 51 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 52 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIBAIJ(Mat mat) 53 { 54 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 55 PetscErrorCode ierr; 56 57 PetscFunctionBegin; 58 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 59 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 60 PetscFunctionReturn(0); 61 } 62 EXTERN_C_END 63 64 EXTERN_C_BEGIN 65 #undef __FUNCT__ 66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 67 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIBAIJ(Mat mat) 68 { 69 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 70 PetscErrorCode ierr; 71 72 PetscFunctionBegin; 73 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 74 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 75 PetscFunctionReturn(0); 76 } 77 EXTERN_C_END 78 79 /* 80 Local utility routine that creates a mapping from the global column 81 number to the local number in the off-diagonal part of the local 82 storage of the matrix. This is done in a non scable way since the 83 length of colmap equals the global matrix length. 84 */ 85 #undef __FUNCT__ 86 #define __FUNCT__ "CreateColmap_MPIBAIJ_Private" 87 PetscErrorCode CreateColmap_MPIBAIJ_Private(Mat mat) 88 { 89 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 90 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 91 PetscErrorCode ierr; 92 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 93 94 PetscFunctionBegin; 95 #if defined (PETSC_USE_CTABLE) 96 ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr); 97 for (i=0; i<nbs; i++){ 98 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr); 99 } 100 #else 101 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 102 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 104 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 105 #endif 106 PetscFunctionReturn(0); 107 } 108 109 #define CHUNKSIZE 10 110 111 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 112 { \ 113 \ 114 brow = row/bs; \ 115 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 116 rmax = aimax[brow]; nrow = ailen[brow]; \ 117 bcol = col/bs; \ 118 ridx = row % bs; cidx = col % bs; \ 119 low = 0; high = nrow; \ 120 while (high-low > 3) { \ 121 t = (low+high)/2; \ 122 if (rp[t] > bcol) high = t; \ 123 else low = t; \ 124 } \ 125 for (_i=low; _i<high; _i++) { \ 126 if (rp[_i] > bcol) break; \ 127 if (rp[_i] == bcol) { \ 128 bap = ap + bs2*_i + bs*cidx + ridx; \ 129 if (addv == ADD_VALUES) *bap += value; \ 130 else *bap = value; \ 131 goto a_noinsert; \ 132 } \ 133 } \ 134 if (a->nonew == 1) goto a_noinsert; \ 135 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 136 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 137 N = nrow++ - 1; \ 138 /* shift up all the later entries in this row */ \ 139 for (ii=N; ii>=_i; ii--) { \ 140 rp[ii+1] = rp[ii]; \ 141 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 142 } \ 143 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 144 rp[_i] = bcol; \ 145 ap[bs2*_i + bs*cidx + ridx] = value; \ 146 a_noinsert:; \ 147 ailen[brow] = nrow; \ 148 } 149 150 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 151 { \ 152 brow = row/bs; \ 153 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 154 rmax = bimax[brow]; nrow = bilen[brow]; \ 155 bcol = col/bs; \ 156 ridx = row % bs; cidx = col % bs; \ 157 low = 0; high = nrow; \ 158 while (high-low > 3) { \ 159 t = (low+high)/2; \ 160 if (rp[t] > bcol) high = t; \ 161 else low = t; \ 162 } \ 163 for (_i=low; _i<high; _i++) { \ 164 if (rp[_i] > bcol) break; \ 165 if (rp[_i] == bcol) { \ 166 bap = ap + bs2*_i + bs*cidx + ridx; \ 167 if (addv == ADD_VALUES) *bap += value; \ 168 else *bap = value; \ 169 goto b_noinsert; \ 170 } \ 171 } \ 172 if (b->nonew == 1) goto b_noinsert; \ 173 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 174 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 175 CHKMEMQ;\ 176 N = nrow++ - 1; \ 177 /* shift up all the later entries in this row */ \ 178 for (ii=N; ii>=_i; ii--) { \ 179 rp[ii+1] = rp[ii]; \ 180 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 181 } \ 182 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 183 rp[_i] = bcol; \ 184 ap[bs2*_i + bs*cidx + ridx] = value; \ 185 b_noinsert:; \ 186 bilen[brow] = nrow; \ 187 } 188 189 #undef __FUNCT__ 190 #define __FUNCT__ "MatSetValues_MPIBAIJ" 191 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 192 { 193 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 194 MatScalar value; 195 PetscTruth roworiented = baij->roworiented; 196 PetscErrorCode ierr; 197 PetscInt i,j,row,col; 198 PetscInt rstart_orig=mat->rmap->rstart; 199 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 200 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 201 202 /* Some Variables required in the macro */ 203 Mat A = baij->A; 204 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 205 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 206 MatScalar *aa=a->a; 207 208 Mat B = baij->B; 209 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 210 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 211 MatScalar *ba=b->a; 212 213 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 214 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 215 MatScalar *ap,*bap; 216 217 PetscFunctionBegin; 218 for (i=0; i<m; i++) { 219 if (im[i] < 0) continue; 220 #if defined(PETSC_USE_DEBUG) 221 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 222 #endif 223 if (im[i] >= rstart_orig && im[i] < rend_orig) { 224 row = im[i] - rstart_orig; 225 for (j=0; j<n; j++) { 226 if (in[j] >= cstart_orig && in[j] < cend_orig){ 227 col = in[j] - cstart_orig; 228 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 229 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 230 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 231 } else if (in[j] < 0) continue; 232 #if defined(PETSC_USE_DEBUG) 233 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[i],mat->cmap->N-1);} 234 #endif 235 else { 236 if (mat->was_assembled) { 237 if (!baij->colmap) { 238 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 239 } 240 #if defined (PETSC_USE_CTABLE) 241 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 242 col = col - 1; 243 #else 244 col = baij->colmap[in[j]/bs] - 1; 245 #endif 246 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 247 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 248 col = in[j]; 249 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 250 B = baij->B; 251 b = (Mat_SeqBAIJ*)(B)->data; 252 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 253 ba=b->a; 254 } else col += in[j]%bs; 255 } else col = in[j]; 256 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 257 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 258 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 259 } 260 } 261 } else { 262 if (!baij->donotstash) { 263 if (roworiented) { 264 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 265 } else { 266 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 267 } 268 } 269 } 270 } 271 PetscFunctionReturn(0); 272 } 273 274 #undef __FUNCT__ 275 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 276 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 277 { 278 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 279 const PetscScalar *value; 280 MatScalar *barray=baij->barray; 281 PetscTruth roworiented = baij->roworiented; 282 PetscErrorCode ierr; 283 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 284 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 285 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 286 287 PetscFunctionBegin; 288 if(!barray) { 289 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 290 baij->barray = barray; 291 } 292 293 if (roworiented) { 294 stepval = (n-1)*bs; 295 } else { 296 stepval = (m-1)*bs; 297 } 298 for (i=0; i<m; i++) { 299 if (im[i] < 0) continue; 300 #if defined(PETSC_USE_DEBUG) 301 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 302 #endif 303 if (im[i] >= rstart && im[i] < rend) { 304 row = im[i] - rstart; 305 for (j=0; j<n; j++) { 306 /* If NumCol = 1 then a copy is not required */ 307 if ((roworiented) && (n == 1)) { 308 barray = (MatScalar*)v + i*bs2; 309 } else if((!roworiented) && (m == 1)) { 310 barray = (MatScalar*)v + j*bs2; 311 } else { /* Here a copy is required */ 312 if (roworiented) { 313 value = v + i*(stepval+bs)*bs + j*bs; 314 } else { 315 value = v + j*(stepval+bs)*bs + i*bs; 316 } 317 for (ii=0; ii<bs; ii++,value+=stepval) { 318 for (jj=0; jj<bs; jj++) { 319 *barray++ = *value++; 320 } 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_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 = CreateColmap_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_ERR_PLIB,"Incorrect colmap"); 344 } 345 #else 346 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(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 = DisAssemble_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 (!baij->donotstash) { 366 if (roworiented) { 367 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 368 } else { 369 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 370 } 371 } 372 } 373 } 374 PetscFunctionReturn(0); 375 } 376 377 #define HASH_KEY 0.6180339887 378 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 379 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 380 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 381 #undef __FUNCT__ 382 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 383 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 384 { 385 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 386 PetscTruth roworiented = baij->roworiented; 387 PetscErrorCode ierr; 388 PetscInt i,j,row,col; 389 PetscInt rstart_orig=mat->rmap->rstart; 390 PetscInt rend_orig=mat->rmap->rend,Nbs=baij->Nbs; 391 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 392 PetscReal tmp; 393 MatScalar **HD = baij->hd,value; 394 #if defined(PETSC_USE_DEBUG) 395 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 396 #endif 397 398 PetscFunctionBegin; 399 400 for (i=0; i<m; i++) { 401 #if defined(PETSC_USE_DEBUG) 402 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 403 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 404 #endif 405 row = im[i]; 406 if (row >= rstart_orig && row < rend_orig) { 407 for (j=0; j<n; j++) { 408 col = in[j]; 409 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 410 /* Look up PetscInto the Hash Table */ 411 key = (row/bs)*Nbs+(col/bs)+1; 412 h1 = HASH(size,key,tmp); 413 414 415 idx = h1; 416 #if defined(PETSC_USE_DEBUG) 417 insert_ct++; 418 total_ct++; 419 if (HT[idx] != key) { 420 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 421 if (idx == size) { 422 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 423 if (idx == h1) { 424 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 425 } 426 } 427 } 428 #else 429 if (HT[idx] != key) { 430 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 431 if (idx == size) { 432 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 433 if (idx == h1) { 434 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 435 } 436 } 437 } 438 #endif 439 /* A HASH table entry is found, so insert the values at the correct address */ 440 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 441 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 442 } 443 } else { 444 if (!baij->donotstash) { 445 if (roworiented) { 446 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 447 } else { 448 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 449 } 450 } 451 } 452 } 453 #if defined(PETSC_USE_DEBUG) 454 baij->ht_total_ct = total_ct; 455 baij->ht_insert_ct = insert_ct; 456 #endif 457 PetscFunctionReturn(0); 458 } 459 460 #undef __FUNCT__ 461 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 462 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 463 { 464 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 465 PetscTruth roworiented = baij->roworiented; 466 PetscErrorCode ierr; 467 PetscInt i,j,ii,jj,row,col; 468 PetscInt rstart=baij->rstartbs; 469 PetscInt rend=mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 470 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 471 PetscReal tmp; 472 MatScalar **HD = baij->hd,*baij_a; 473 const PetscScalar *v_t,*value; 474 #if defined(PETSC_USE_DEBUG) 475 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 476 #endif 477 478 PetscFunctionBegin; 479 480 if (roworiented) { 481 stepval = (n-1)*bs; 482 } else { 483 stepval = (m-1)*bs; 484 } 485 for (i=0; i<m; i++) { 486 #if defined(PETSC_USE_DEBUG) 487 if (im[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 488 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 489 #endif 490 row = im[i]; 491 v_t = v + i*nbs2; 492 if (row >= rstart && row < rend) { 493 for (j=0; j<n; j++) { 494 col = in[j]; 495 496 /* Look up into the Hash Table */ 497 key = row*Nbs+col+1; 498 h1 = HASH(size,key,tmp); 499 500 idx = h1; 501 #if defined(PETSC_USE_DEBUG) 502 total_ct++; 503 insert_ct++; 504 if (HT[idx] != key) { 505 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 506 if (idx == size) { 507 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 508 if (idx == h1) { 509 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 510 } 511 } 512 } 513 #else 514 if (HT[idx] != key) { 515 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 516 if (idx == size) { 517 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 518 if (idx == h1) { 519 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 520 } 521 } 522 } 523 #endif 524 baij_a = HD[idx]; 525 if (roworiented) { 526 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 527 /* value = v + (i*(stepval+bs)+j)*bs; */ 528 value = v_t; 529 v_t += bs; 530 if (addv == ADD_VALUES) { 531 for (ii=0; ii<bs; ii++,value+=stepval) { 532 for (jj=ii; jj<bs2; jj+=bs) { 533 baij_a[jj] += *value++; 534 } 535 } 536 } else { 537 for (ii=0; ii<bs; ii++,value+=stepval) { 538 for (jj=ii; jj<bs2; jj+=bs) { 539 baij_a[jj] = *value++; 540 } 541 } 542 } 543 } else { 544 value = v + j*(stepval+bs)*bs + i*bs; 545 if (addv == ADD_VALUES) { 546 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 547 for (jj=0; jj<bs; jj++) { 548 baij_a[jj] += *value++; 549 } 550 } 551 } else { 552 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 553 for (jj=0; jj<bs; jj++) { 554 baij_a[jj] = *value++; 555 } 556 } 557 } 558 } 559 } 560 } else { 561 if (!baij->donotstash) { 562 if (roworiented) { 563 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 564 } else { 565 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 566 } 567 } 568 } 569 } 570 #if defined(PETSC_USE_DEBUG) 571 baij->ht_total_ct = total_ct; 572 baij->ht_insert_ct = insert_ct; 573 #endif 574 PetscFunctionReturn(0); 575 } 576 577 #undef __FUNCT__ 578 #define __FUNCT__ "MatGetValues_MPIBAIJ" 579 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 580 { 581 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 582 PetscErrorCode ierr; 583 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 584 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 585 586 PetscFunctionBegin; 587 for (i=0; i<m; i++) { 588 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 589 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 590 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 591 row = idxm[i] - bsrstart; 592 for (j=0; j<n; j++) { 593 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 594 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 595 if (idxn[j] >= bscstart && idxn[j] < bscend){ 596 col = idxn[j] - bscstart; 597 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 598 } else { 599 if (!baij->colmap) { 600 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 601 } 602 #if defined (PETSC_USE_CTABLE) 603 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 604 data --; 605 #else 606 data = baij->colmap[idxn[j]/bs]-1; 607 #endif 608 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 609 else { 610 col = data + idxn[j]%bs; 611 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 612 } 613 } 614 } 615 } else { 616 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 617 } 618 } 619 PetscFunctionReturn(0); 620 } 621 622 #undef __FUNCT__ 623 #define __FUNCT__ "MatNorm_MPIBAIJ" 624 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 625 { 626 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 627 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 628 PetscErrorCode ierr; 629 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 630 PetscReal sum = 0.0; 631 MatScalar *v; 632 633 PetscFunctionBegin; 634 if (baij->size == 1) { 635 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 636 } else { 637 if (type == NORM_FROBENIUS) { 638 v = amat->a; 639 nz = amat->nz*bs2; 640 for (i=0; i<nz; i++) { 641 #if defined(PETSC_USE_COMPLEX) 642 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 643 #else 644 sum += (*v)*(*v); v++; 645 #endif 646 } 647 v = bmat->a; 648 nz = bmat->nz*bs2; 649 for (i=0; i<nz; i++) { 650 #if defined(PETSC_USE_COMPLEX) 651 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 652 #else 653 sum += (*v)*(*v); v++; 654 #endif 655 } 656 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 657 *nrm = sqrt(*nrm); 658 } else if (type == NORM_1) { /* max column sum */ 659 PetscReal *tmp,*tmp2; 660 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 661 ierr = PetscMalloc((2*mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 662 tmp2 = tmp + mat->cmap->N; 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,MPI_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 = PetscFree(tmp);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,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 719 ierr = PetscFree(sums);CHKERRQ(ierr); 720 } else { 721 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 722 } 723 } 724 PetscFunctionReturn(0); 725 } 726 727 /* 728 Creates the hash table, and sets the table 729 This table is created only once. 730 If new entried need to be added to the matrix 731 then the hash table has to be destroyed and 732 recreated. 733 */ 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 736 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 737 { 738 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 739 Mat A = baij->A,B=baij->B; 740 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 741 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 742 PetscErrorCode ierr; 743 PetscInt size,bs2=baij->bs2,rstart=baij->rstartbs; 744 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 745 PetscInt *HT,key; 746 MatScalar **HD; 747 PetscReal tmp; 748 #if defined(PETSC_USE_INFO) 749 PetscInt ct=0,max=0; 750 #endif 751 752 PetscFunctionBegin; 753 baij->ht_size=(PetscInt)(factor*nz); 754 size = baij->ht_size; 755 756 if (baij->ht) { 757 PetscFunctionReturn(0); 758 } 759 760 /* Allocate Memory for Hash Table */ 761 ierr = PetscMalloc((size)*(sizeof(PetscInt)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr); 762 baij->ht = (PetscInt*)(baij->hd + size); 763 HD = baij->hd; 764 HT = baij->ht; 765 766 767 ierr = PetscMemzero(HD,size*(sizeof(PetscInt)+sizeof(PetscScalar*)));CHKERRQ(ierr); 768 769 770 /* Loop Over A */ 771 for (i=0; i<a->mbs; i++) { 772 for (j=ai[i]; j<ai[i+1]; j++) { 773 row = i+rstart; 774 col = aj[j]+cstart; 775 776 key = row*Nbs + col + 1; 777 h1 = HASH(size,key,tmp); 778 for (k=0; k<size; k++){ 779 if (!HT[(h1+k)%size]) { 780 HT[(h1+k)%size] = key; 781 HD[(h1+k)%size] = a->a + j*bs2; 782 break; 783 #if defined(PETSC_USE_INFO) 784 } else { 785 ct++; 786 #endif 787 } 788 } 789 #if defined(PETSC_USE_INFO) 790 if (k> max) max = k; 791 #endif 792 } 793 } 794 /* Loop Over B */ 795 for (i=0; i<b->mbs; i++) { 796 for (j=bi[i]; j<bi[i+1]; j++) { 797 row = i+rstart; 798 col = garray[bj[j]]; 799 key = row*Nbs + col + 1; 800 h1 = HASH(size,key,tmp); 801 for (k=0; k<size; k++){ 802 if (!HT[(h1+k)%size]) { 803 HT[(h1+k)%size] = key; 804 HD[(h1+k)%size] = b->a + j*bs2; 805 break; 806 #if defined(PETSC_USE_INFO) 807 } else { 808 ct++; 809 #endif 810 } 811 } 812 #if defined(PETSC_USE_INFO) 813 if (k> max) max = k; 814 #endif 815 } 816 } 817 818 /* Print Summary */ 819 #if defined(PETSC_USE_INFO) 820 for (i=0,j=0; i<size; i++) { 821 if (HT[i]) {j++;} 822 } 823 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 824 #endif 825 PetscFunctionReturn(0); 826 } 827 828 #undef __FUNCT__ 829 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 830 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 831 { 832 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 833 PetscErrorCode ierr; 834 PetscInt nstash,reallocs; 835 InsertMode addv; 836 837 PetscFunctionBegin; 838 if (baij->donotstash) { 839 PetscFunctionReturn(0); 840 } 841 842 /* make sure all processors are either in INSERTMODE or ADDMODE */ 843 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 844 if (addv == (ADD_VALUES|INSERT_VALUES)) { 845 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 846 } 847 mat->insertmode = addv; /* in case this processor had no cache */ 848 849 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 850 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 851 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 852 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 853 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 854 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 855 PetscFunctionReturn(0); 856 } 857 858 #undef __FUNCT__ 859 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 860 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 861 { 862 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 863 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data; 864 PetscErrorCode ierr; 865 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 866 PetscInt *row,*col; 867 PetscTruth r1,r2,r3,other_disassembled; 868 MatScalar *val; 869 InsertMode addv = mat->insertmode; 870 PetscMPIInt n; 871 872 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 873 PetscFunctionBegin; 874 if (!baij->donotstash) { 875 while (1) { 876 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 877 if (!flg) break; 878 879 for (i=0; i<n;) { 880 /* Now identify the consecutive vals belonging to the same row */ 881 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 882 if (j < n) ncols = j-i; 883 else ncols = n-i; 884 /* Now assemble all these values with a single function call */ 885 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 886 i = j; 887 } 888 } 889 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 890 /* Now process the block-stash. Since the values are stashed column-oriented, 891 set the roworiented flag to column oriented, and after MatSetValues() 892 restore the original flags */ 893 r1 = baij->roworiented; 894 r2 = a->roworiented; 895 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 896 baij->roworiented = PETSC_FALSE; 897 a->roworiented = PETSC_FALSE; 898 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 899 while (1) { 900 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 901 if (!flg) break; 902 903 for (i=0; i<n;) { 904 /* Now identify the consecutive vals belonging to the same row */ 905 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 906 if (j < n) ncols = j-i; 907 else ncols = n-i; 908 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 909 i = j; 910 } 911 } 912 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 913 baij->roworiented = r1; 914 a->roworiented = r2; 915 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 916 } 917 918 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 919 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 920 921 /* determine if any processor has disassembled, if so we must 922 also disassemble ourselfs, in order that we may reassemble. */ 923 /* 924 if nonzero structure of submatrix B cannot change then we know that 925 no processor disassembled thus we can skip this stuff 926 */ 927 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 928 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 929 if (mat->was_assembled && !other_disassembled) { 930 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 931 } 932 } 933 934 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 935 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 936 } 937 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 938 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 939 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 940 941 #if defined(PETSC_USE_INFO) 942 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 943 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 944 baij->ht_total_ct = 0; 945 baij->ht_insert_ct = 0; 946 } 947 #endif 948 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 949 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 950 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 951 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 952 } 953 954 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 955 baij->rowvalues = 0; 956 PetscFunctionReturn(0); 957 } 958 959 #undef __FUNCT__ 960 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 961 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 962 { 963 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 964 PetscErrorCode ierr; 965 PetscMPIInt size = baij->size,rank = baij->rank; 966 PetscInt bs = mat->rmap->bs; 967 PetscTruth iascii,isdraw; 968 PetscViewer sviewer; 969 PetscViewerFormat format; 970 971 PetscFunctionBegin; 972 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 973 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 974 if (iascii) { 975 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 976 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 977 MatInfo info; 978 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 979 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 980 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 981 rank,mat->rmap->N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 982 mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 983 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 984 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 985 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 986 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 987 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 988 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 989 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 990 PetscFunctionReturn(0); 991 } else if (format == PETSC_VIEWER_ASCII_INFO) { 992 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 993 PetscFunctionReturn(0); 994 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 995 PetscFunctionReturn(0); 996 } 997 } 998 999 if (isdraw) { 1000 PetscDraw draw; 1001 PetscTruth isnull; 1002 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1003 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1004 } 1005 1006 if (size == 1) { 1007 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1008 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1009 } else { 1010 /* assemble the entire matrix onto first processor. */ 1011 Mat A; 1012 Mat_SeqBAIJ *Aloc; 1013 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1014 MatScalar *a; 1015 1016 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1017 /* Perhaps this should be the type of mat? */ 1018 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1019 if (!rank) { 1020 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1021 } else { 1022 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1023 } 1024 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1025 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1026 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1027 1028 /* copy over the A part */ 1029 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1030 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1031 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1032 1033 for (i=0; i<mbs; i++) { 1034 rvals[0] = bs*(baij->rstartbs + i); 1035 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1036 for (j=ai[i]; j<ai[i+1]; j++) { 1037 col = (baij->cstartbs+aj[j])*bs; 1038 for (k=0; k<bs; k++) { 1039 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1040 col++; a += bs; 1041 } 1042 } 1043 } 1044 /* copy over the B part */ 1045 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1046 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1047 for (i=0; i<mbs; i++) { 1048 rvals[0] = bs*(baij->rstartbs + i); 1049 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1050 for (j=ai[i]; j<ai[i+1]; j++) { 1051 col = baij->garray[aj[j]]*bs; 1052 for (k=0; k<bs; k++) { 1053 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1054 col++; a += bs; 1055 } 1056 } 1057 } 1058 ierr = PetscFree(rvals);CHKERRQ(ierr); 1059 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1060 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1061 /* 1062 Everyone has to call to draw the matrix since the graphics waits are 1063 synchronized across all processors that share the PetscDraw object 1064 */ 1065 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1066 if (!rank) { 1067 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1068 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1069 } 1070 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1071 ierr = MatDestroy(A);CHKERRQ(ierr); 1072 } 1073 PetscFunctionReturn(0); 1074 } 1075 1076 #undef __FUNCT__ 1077 #define __FUNCT__ "MatView_MPIBAIJ" 1078 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1079 { 1080 PetscErrorCode ierr; 1081 PetscTruth iascii,isdraw,issocket,isbinary; 1082 1083 PetscFunctionBegin; 1084 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1085 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1086 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1087 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1088 if (iascii || isdraw || issocket || isbinary) { 1089 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1090 } else { 1091 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1092 } 1093 PetscFunctionReturn(0); 1094 } 1095 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1098 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1099 { 1100 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1101 PetscErrorCode ierr; 1102 1103 PetscFunctionBegin; 1104 #if defined(PETSC_USE_LOG) 1105 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1106 #endif 1107 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1108 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1109 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1110 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1111 #if defined (PETSC_USE_CTABLE) 1112 if (baij->colmap) {ierr = PetscTableDestroy(baij->colmap);CHKERRQ(ierr);} 1113 #else 1114 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1115 #endif 1116 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1117 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1118 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1119 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1120 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1121 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 1122 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1123 ierr = PetscFree(baij);CHKERRQ(ierr); 1124 1125 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1127 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1128 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1129 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1130 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1131 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1132 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatMult_MPIBAIJ" 1138 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1139 { 1140 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1141 PetscErrorCode ierr; 1142 PetscInt nt; 1143 1144 PetscFunctionBegin; 1145 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1146 if (nt != A->cmap->n) { 1147 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1148 } 1149 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1150 if (nt != A->rmap->n) { 1151 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1152 } 1153 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1154 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1155 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1156 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1162 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1163 { 1164 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1165 PetscErrorCode ierr; 1166 1167 PetscFunctionBegin; 1168 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1169 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1170 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1171 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1172 PetscFunctionReturn(0); 1173 } 1174 1175 #undef __FUNCT__ 1176 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1177 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1178 { 1179 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1180 PetscErrorCode ierr; 1181 PetscTruth merged; 1182 1183 PetscFunctionBegin; 1184 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1185 /* do nondiagonal part */ 1186 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1187 if (!merged) { 1188 /* send it on its way */ 1189 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1190 /* do local part */ 1191 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1192 /* receive remote parts: note this assumes the values are not actually */ 1193 /* inserted in yy until the next line */ 1194 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1195 } else { 1196 /* do local part */ 1197 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1198 /* send it on its way */ 1199 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1200 /* values actually were received in the Begin() but we need to call this nop */ 1201 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1202 } 1203 PetscFunctionReturn(0); 1204 } 1205 1206 #undef __FUNCT__ 1207 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1208 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1209 { 1210 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1211 PetscErrorCode ierr; 1212 1213 PetscFunctionBegin; 1214 /* do nondiagonal part */ 1215 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1216 /* send it on its way */ 1217 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1218 /* do local part */ 1219 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1220 /* receive remote parts: note this assumes the values are not actually */ 1221 /* inserted in yy until the next line, which is true for my implementation*/ 1222 /* but is not perhaps always true. */ 1223 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1224 PetscFunctionReturn(0); 1225 } 1226 1227 /* 1228 This only works correctly for square matrices where the subblock A->A is the 1229 diagonal block 1230 */ 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1233 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1234 { 1235 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1236 PetscErrorCode ierr; 1237 1238 PetscFunctionBegin; 1239 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1240 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatScale_MPIBAIJ" 1246 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1247 { 1248 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1249 PetscErrorCode ierr; 1250 1251 PetscFunctionBegin; 1252 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1253 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1254 PetscFunctionReturn(0); 1255 } 1256 1257 #undef __FUNCT__ 1258 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1259 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1260 { 1261 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1262 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1263 PetscErrorCode ierr; 1264 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1265 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1266 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1267 1268 PetscFunctionBegin; 1269 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1270 mat->getrowactive = PETSC_TRUE; 1271 1272 if (!mat->rowvalues && (idx || v)) { 1273 /* 1274 allocate enough space to hold information from the longest row. 1275 */ 1276 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1277 PetscInt max = 1,mbs = mat->mbs,tmp; 1278 for (i=0; i<mbs; i++) { 1279 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1280 if (max < tmp) { max = tmp; } 1281 } 1282 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1283 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1284 } 1285 1286 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1287 lrow = row - brstart; 1288 1289 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1290 if (!v) {pvA = 0; pvB = 0;} 1291 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1292 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1293 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1294 nztot = nzA + nzB; 1295 1296 cmap = mat->garray; 1297 if (v || idx) { 1298 if (nztot) { 1299 /* Sort by increasing column numbers, assuming A and B already sorted */ 1300 PetscInt imark = -1; 1301 if (v) { 1302 *v = v_p = mat->rowvalues; 1303 for (i=0; i<nzB; i++) { 1304 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1305 else break; 1306 } 1307 imark = i; 1308 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1309 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1310 } 1311 if (idx) { 1312 *idx = idx_p = mat->rowindices; 1313 if (imark > -1) { 1314 for (i=0; i<imark; i++) { 1315 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1316 } 1317 } else { 1318 for (i=0; i<nzB; i++) { 1319 if (cmap[cworkB[i]/bs] < cstart) 1320 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1321 else break; 1322 } 1323 imark = i; 1324 } 1325 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1326 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1327 } 1328 } else { 1329 if (idx) *idx = 0; 1330 if (v) *v = 0; 1331 } 1332 } 1333 *nz = nztot; 1334 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1335 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1336 PetscFunctionReturn(0); 1337 } 1338 1339 #undef __FUNCT__ 1340 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1341 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1342 { 1343 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1344 1345 PetscFunctionBegin; 1346 if (!baij->getrowactive) { 1347 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1348 } 1349 baij->getrowactive = PETSC_FALSE; 1350 PetscFunctionReturn(0); 1351 } 1352 1353 #undef __FUNCT__ 1354 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1355 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1356 { 1357 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1358 PetscErrorCode ierr; 1359 1360 PetscFunctionBegin; 1361 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1362 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1363 PetscFunctionReturn(0); 1364 } 1365 1366 #undef __FUNCT__ 1367 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1368 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1369 { 1370 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1371 Mat A = a->A,B = a->B; 1372 PetscErrorCode ierr; 1373 PetscReal isend[5],irecv[5]; 1374 1375 PetscFunctionBegin; 1376 info->block_size = (PetscReal)matin->rmap->bs; 1377 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1378 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1379 isend[3] = info->memory; isend[4] = info->mallocs; 1380 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1381 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1382 isend[3] += info->memory; isend[4] += info->mallocs; 1383 if (flag == MAT_LOCAL) { 1384 info->nz_used = isend[0]; 1385 info->nz_allocated = isend[1]; 1386 info->nz_unneeded = isend[2]; 1387 info->memory = isend[3]; 1388 info->mallocs = isend[4]; 1389 } else if (flag == MAT_GLOBAL_MAX) { 1390 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1391 info->nz_used = irecv[0]; 1392 info->nz_allocated = irecv[1]; 1393 info->nz_unneeded = irecv[2]; 1394 info->memory = irecv[3]; 1395 info->mallocs = irecv[4]; 1396 } else if (flag == MAT_GLOBAL_SUM) { 1397 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1398 info->nz_used = irecv[0]; 1399 info->nz_allocated = irecv[1]; 1400 info->nz_unneeded = irecv[2]; 1401 info->memory = irecv[3]; 1402 info->mallocs = irecv[4]; 1403 } else { 1404 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1405 } 1406 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1407 info->fill_ratio_needed = 0; 1408 info->factor_mallocs = 0; 1409 PetscFunctionReturn(0); 1410 } 1411 1412 #undef __FUNCT__ 1413 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1414 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscTruth flg) 1415 { 1416 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1417 PetscErrorCode ierr; 1418 1419 PetscFunctionBegin; 1420 switch (op) { 1421 case MAT_NEW_NONZERO_LOCATIONS: 1422 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1423 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1424 case MAT_KEEP_NONZERO_PATTERN: 1425 case MAT_NEW_NONZERO_LOCATION_ERR: 1426 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1427 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1428 break; 1429 case MAT_ROW_ORIENTED: 1430 a->roworiented = flg; 1431 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1432 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1433 break; 1434 case MAT_NEW_DIAGONALS: 1435 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1436 break; 1437 case MAT_IGNORE_OFF_PROC_ENTRIES: 1438 a->donotstash = flg; 1439 break; 1440 case MAT_USE_HASH_TABLE: 1441 a->ht_flag = flg; 1442 break; 1443 case MAT_SYMMETRIC: 1444 case MAT_STRUCTURALLY_SYMMETRIC: 1445 case MAT_HERMITIAN: 1446 case MAT_SYMMETRY_ETERNAL: 1447 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1448 break; 1449 default: 1450 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1451 } 1452 PetscFunctionReturn(0); 1453 } 1454 1455 #undef __FUNCT__ 1456 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1457 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1458 { 1459 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1460 Mat_SeqBAIJ *Aloc; 1461 Mat B; 1462 PetscErrorCode ierr; 1463 PetscInt M=A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1464 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1465 MatScalar *a; 1466 1467 PetscFunctionBegin; 1468 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1469 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1470 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1471 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1472 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1473 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1474 } else { 1475 B = *matout; 1476 } 1477 1478 /* copy over the A part */ 1479 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1480 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1481 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1482 1483 for (i=0; i<mbs; i++) { 1484 rvals[0] = bs*(baij->rstartbs + i); 1485 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1486 for (j=ai[i]; j<ai[i+1]; j++) { 1487 col = (baij->cstartbs+aj[j])*bs; 1488 for (k=0; k<bs; k++) { 1489 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1490 col++; a += bs; 1491 } 1492 } 1493 } 1494 /* copy over the B part */ 1495 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1496 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1497 for (i=0; i<mbs; i++) { 1498 rvals[0] = bs*(baij->rstartbs + i); 1499 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1500 for (j=ai[i]; j<ai[i+1]; j++) { 1501 col = baij->garray[aj[j]]*bs; 1502 for (k=0; k<bs; k++) { 1503 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1504 col++; a += bs; 1505 } 1506 } 1507 } 1508 ierr = PetscFree(rvals);CHKERRQ(ierr); 1509 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1510 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1511 1512 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1513 *matout = B; 1514 } else { 1515 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1516 } 1517 PetscFunctionReturn(0); 1518 } 1519 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1522 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1523 { 1524 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1525 Mat a = baij->A,b = baij->B; 1526 PetscErrorCode ierr; 1527 PetscInt s1,s2,s3; 1528 1529 PetscFunctionBegin; 1530 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1531 if (rr) { 1532 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1533 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1534 /* Overlap communication with computation. */ 1535 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1536 } 1537 if (ll) { 1538 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1539 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1540 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1541 } 1542 /* scale the diagonal block */ 1543 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1544 1545 if (rr) { 1546 /* Do a scatter end and then right scale the off-diagonal block */ 1547 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1548 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1549 } 1550 1551 PetscFunctionReturn(0); 1552 } 1553 1554 #undef __FUNCT__ 1555 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1556 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 1557 { 1558 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1559 PetscErrorCode ierr; 1560 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1561 PetscInt i,*owners = A->rmap->range; 1562 PetscInt *nprocs,j,idx,nsends,row; 1563 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1564 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1565 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1566 MPI_Comm comm = ((PetscObject)A)->comm; 1567 MPI_Request *send_waits,*recv_waits; 1568 MPI_Status recv_status,*send_status; 1569 #if defined(PETSC_DEBUG) 1570 PetscTruth found = PETSC_FALSE; 1571 #endif 1572 1573 PetscFunctionBegin; 1574 /* first count number of contributors to each processor */ 1575 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1576 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1577 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1578 j = 0; 1579 for (i=0; i<N; i++) { 1580 if (lastidx > (idx = rows[i])) j = 0; 1581 lastidx = idx; 1582 for (; j<size; j++) { 1583 if (idx >= owners[j] && idx < owners[j+1]) { 1584 nprocs[2*j]++; 1585 nprocs[2*j+1] = 1; 1586 owner[i] = j; 1587 #if defined(PETSC_DEBUG) 1588 found = PETSC_TRUE; 1589 #endif 1590 break; 1591 } 1592 } 1593 #if defined(PETSC_DEBUG) 1594 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1595 found = PETSC_FALSE; 1596 #endif 1597 } 1598 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1599 1600 /* inform other processors of number of messages and max length*/ 1601 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1602 1603 /* post receives: */ 1604 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1605 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1606 for (i=0; i<nrecvs; i++) { 1607 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1608 } 1609 1610 /* do sends: 1611 1) starts[i] gives the starting index in svalues for stuff going to 1612 the ith processor 1613 */ 1614 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1615 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1616 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1617 starts[0] = 0; 1618 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1619 for (i=0; i<N; i++) { 1620 svalues[starts[owner[i]]++] = rows[i]; 1621 } 1622 1623 starts[0] = 0; 1624 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1625 count = 0; 1626 for (i=0; i<size; i++) { 1627 if (nprocs[2*i+1]) { 1628 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1629 } 1630 } 1631 ierr = PetscFree(starts);CHKERRQ(ierr); 1632 1633 base = owners[rank]; 1634 1635 /* wait on receives */ 1636 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1637 source = lens + nrecvs; 1638 count = nrecvs; slen = 0; 1639 while (count) { 1640 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1641 /* unpack receives into our local space */ 1642 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1643 source[imdex] = recv_status.MPI_SOURCE; 1644 lens[imdex] = n; 1645 slen += n; 1646 count--; 1647 } 1648 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1649 1650 /* move the data into the send scatter */ 1651 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1652 count = 0; 1653 for (i=0; i<nrecvs; i++) { 1654 values = rvalues + i*nmax; 1655 for (j=0; j<lens[i]; j++) { 1656 lrows[count++] = values[j] - base; 1657 } 1658 } 1659 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1660 ierr = PetscFree(lens);CHKERRQ(ierr); 1661 ierr = PetscFree(owner);CHKERRQ(ierr); 1662 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1663 1664 /* actually zap the local rows */ 1665 /* 1666 Zero the required rows. If the "diagonal block" of the matrix 1667 is square and the user wishes to set the diagonal we use separate 1668 code so that MatSetValues() is not called for each diagonal allocating 1669 new memory, thus calling lots of mallocs and slowing things down. 1670 1671 Contributed by: Matthew Knepley 1672 */ 1673 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1674 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0);CHKERRQ(ierr); 1675 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1676 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag);CHKERRQ(ierr); 1677 } else if (diag != 0.0) { 1678 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1679 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1680 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1681 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1682 } 1683 for (i=0; i<slen; i++) { 1684 row = lrows[i] + rstart_bs; 1685 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1686 } 1687 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1688 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1689 } else { 1690 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1691 } 1692 1693 ierr = PetscFree(lrows);CHKERRQ(ierr); 1694 1695 /* wait on sends */ 1696 if (nsends) { 1697 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1698 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1699 ierr = PetscFree(send_status);CHKERRQ(ierr); 1700 } 1701 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1702 ierr = PetscFree(svalues);CHKERRQ(ierr); 1703 1704 PetscFunctionReturn(0); 1705 } 1706 1707 #undef __FUNCT__ 1708 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1709 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1710 { 1711 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1712 PetscErrorCode ierr; 1713 1714 PetscFunctionBegin; 1715 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1716 PetscFunctionReturn(0); 1717 } 1718 1719 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1720 1721 #undef __FUNCT__ 1722 #define __FUNCT__ "MatEqual_MPIBAIJ" 1723 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1724 { 1725 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1726 Mat a,b,c,d; 1727 PetscTruth flg; 1728 PetscErrorCode ierr; 1729 1730 PetscFunctionBegin; 1731 a = matA->A; b = matA->B; 1732 c = matB->A; d = matB->B; 1733 1734 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1735 if (flg) { 1736 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1737 } 1738 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1739 PetscFunctionReturn(0); 1740 } 1741 1742 #undef __FUNCT__ 1743 #define __FUNCT__ "MatCopy_MPIBAIJ" 1744 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1745 { 1746 PetscErrorCode ierr; 1747 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1748 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1749 1750 PetscFunctionBegin; 1751 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1752 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1753 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1754 } else { 1755 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1756 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1757 } 1758 PetscFunctionReturn(0); 1759 } 1760 1761 #undef __FUNCT__ 1762 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1763 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1764 { 1765 PetscErrorCode ierr; 1766 1767 PetscFunctionBegin; 1768 ierr = MatMPIBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1769 PetscFunctionReturn(0); 1770 } 1771 1772 #include "petscblaslapack.h" 1773 #undef __FUNCT__ 1774 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1775 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1776 { 1777 PetscErrorCode ierr; 1778 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1779 PetscBLASInt bnz,one=1; 1780 Mat_SeqBAIJ *x,*y; 1781 1782 PetscFunctionBegin; 1783 if (str == SAME_NONZERO_PATTERN) { 1784 PetscScalar alpha = a; 1785 x = (Mat_SeqBAIJ *)xx->A->data; 1786 y = (Mat_SeqBAIJ *)yy->A->data; 1787 bnz = PetscBLASIntCast(x->nz); 1788 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1789 x = (Mat_SeqBAIJ *)xx->B->data; 1790 y = (Mat_SeqBAIJ *)yy->B->data; 1791 bnz = PetscBLASIntCast(x->nz); 1792 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1793 } else { 1794 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1795 } 1796 PetscFunctionReturn(0); 1797 } 1798 1799 #undef __FUNCT__ 1800 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1801 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1802 { 1803 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1804 PetscErrorCode ierr; 1805 1806 PetscFunctionBegin; 1807 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1808 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1814 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 1815 { 1816 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1817 PetscErrorCode ierr; 1818 1819 PetscFunctionBegin; 1820 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1821 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1822 PetscFunctionReturn(0); 1823 } 1824 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 1827 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 1828 { 1829 PetscErrorCode ierr; 1830 IS iscol_local; 1831 PetscInt csize; 1832 1833 PetscFunctionBegin; 1834 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 1835 if (call == MAT_REUSE_MATRIX) { 1836 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 1837 if (!iscol_local) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 1838 } else { 1839 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 1840 } 1841 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 1842 if (call == MAT_INITIAL_MATRIX) { 1843 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 1844 ierr = ISDestroy(iscol_local);CHKERRQ(ierr); 1845 } 1846 PetscFunctionReturn(0); 1847 } 1848 1849 #undef __FUNCT__ 1850 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 1851 /* 1852 Not great since it makes two copies of the submatrix, first an SeqBAIJ 1853 in local and then by concatenating the local matrices the end result. 1854 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 1855 */ 1856 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 1857 { 1858 PetscErrorCode ierr; 1859 PetscMPIInt rank,size; 1860 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 1861 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 1862 Mat *local,M,Mreuse; 1863 MatScalar *vwork,*aa; 1864 MPI_Comm comm = ((PetscObject)mat)->comm; 1865 Mat_SeqBAIJ *aij; 1866 1867 1868 PetscFunctionBegin; 1869 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1870 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1871 1872 if (call == MAT_REUSE_MATRIX) { 1873 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 1874 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 1875 local = &Mreuse; 1876 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 1877 } else { 1878 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 1879 Mreuse = *local; 1880 ierr = PetscFree(local);CHKERRQ(ierr); 1881 } 1882 1883 /* 1884 m - number of local rows 1885 n - number of columns (same on all processors) 1886 rstart - first row in new global matrix generated 1887 */ 1888 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 1889 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 1890 m = m/bs; 1891 n = n/bs; 1892 1893 if (call == MAT_INITIAL_MATRIX) { 1894 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 1895 ii = aij->i; 1896 jj = aij->j; 1897 1898 /* 1899 Determine the number of non-zeros in the diagonal and off-diagonal 1900 portions of the matrix in order to do correct preallocation 1901 */ 1902 1903 /* first get start and end of "diagonal" columns */ 1904 if (csize == PETSC_DECIDE) { 1905 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 1906 if (mglobal == n*bs) { /* square matrix */ 1907 nlocal = m; 1908 } else { 1909 nlocal = n/size + ((n % size) > rank); 1910 } 1911 } else { 1912 nlocal = csize/bs; 1913 } 1914 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 1915 rstart = rend - nlocal; 1916 if (rank == size - 1 && rend != n) { 1917 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 1918 } 1919 1920 /* next, compute all the lengths */ 1921 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 1922 olens = dlens + m; 1923 for (i=0; i<m; i++) { 1924 jend = ii[i+1] - ii[i]; 1925 olen = 0; 1926 dlen = 0; 1927 for (j=0; j<jend; j++) { 1928 if (*jj < rstart || *jj >= rend) olen++; 1929 else dlen++; 1930 jj++; 1931 } 1932 olens[i] = olen; 1933 dlens[i] = dlen; 1934 } 1935 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 1936 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 1937 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 1938 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 1939 ierr = PetscFree(dlens);CHKERRQ(ierr); 1940 } else { 1941 PetscInt ml,nl; 1942 1943 M = *newmat; 1944 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 1945 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 1946 ierr = MatZeroEntries(M);CHKERRQ(ierr); 1947 /* 1948 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 1949 rather than the slower MatSetValues(). 1950 */ 1951 M->was_assembled = PETSC_TRUE; 1952 M->assembled = PETSC_FALSE; 1953 } 1954 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 1955 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 1956 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 1957 ii = aij->i; 1958 jj = aij->j; 1959 aa = aij->a; 1960 for (i=0; i<m; i++) { 1961 row = rstart/bs + i; 1962 nz = ii[i+1] - ii[i]; 1963 cwork = jj; jj += nz; 1964 vwork = aa; aa += nz; 1965 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 1966 } 1967 1968 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1969 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1970 *newmat = M; 1971 1972 /* save submatrix used in processor for next request */ 1973 if (call == MAT_INITIAL_MATRIX) { 1974 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 1975 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 1976 } 1977 1978 PetscFunctionReturn(0); 1979 } 1980 1981 #undef __FUNCT__ 1982 #define __FUNCT__ "MatPermute_MPIBAIJ" 1983 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 1984 { 1985 MPI_Comm comm,pcomm; 1986 PetscInt first,local_size,nrows; 1987 const PetscInt *rows; 1988 PetscMPIInt size; 1989 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1990 PetscErrorCode ierr; 1991 1992 PetscFunctionBegin; 1993 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1994 /* make a collective version of 'rowp' */ 1995 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 1996 if (pcomm==comm) { 1997 crowp = rowp; 1998 } else { 1999 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2000 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2001 ierr = ISCreateGeneral(comm,nrows,rows,&crowp);CHKERRQ(ierr); 2002 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2003 } 2004 /* collect the global row permutation and invert it */ 2005 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 2006 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 2007 if (pcomm!=comm) { 2008 ierr = ISDestroy(crowp);CHKERRQ(ierr); 2009 } 2010 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2011 /* get the local target indices */ 2012 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 2013 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL);CHKERRQ(ierr); 2014 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 2015 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp);CHKERRQ(ierr); 2016 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 2017 ierr = ISDestroy(irowp);CHKERRQ(ierr); 2018 /* the column permutation is so much easier; 2019 make a local version of 'colp' and invert it */ 2020 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2021 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2022 if (size==1) { 2023 lcolp = colp; 2024 } else { 2025 ierr = ISGetSize(colp,&nrows);CHKERRQ(ierr); 2026 ierr = ISGetIndices(colp,&rows);CHKERRQ(ierr); 2027 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp);CHKERRQ(ierr); 2028 } 2029 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2030 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2031 ierr = ISSetPermutation(icolp);CHKERRQ(ierr); 2032 if (size>1) { 2033 ierr = ISRestoreIndices(colp,&rows);CHKERRQ(ierr); 2034 ierr = ISDestroy(lcolp);CHKERRQ(ierr); 2035 } 2036 /* now we just get the submatrix */ 2037 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2038 /* clean up */ 2039 ierr = ISDestroy(lrowp);CHKERRQ(ierr); 2040 ierr = ISDestroy(icolp);CHKERRQ(ierr); 2041 PetscFunctionReturn(0); 2042 } 2043 2044 #undef __FUNCT__ 2045 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2046 PetscErrorCode PETSCMAT_DLLEXPORT MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2047 { 2048 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2049 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2050 2051 PetscFunctionBegin; 2052 if (nghosts) { *nghosts = B->nbs;} 2053 if (ghosts) {*ghosts = baij->garray;} 2054 PetscFunctionReturn(0); 2055 } 2056 2057 extern PetscErrorCode MatFDColoringCreate_MPIAIJ(Mat,ISColoring,MatFDColoring); 2058 2059 /* -------------------------------------------------------------------*/ 2060 static struct _MatOps MatOps_Values = { 2061 MatSetValues_MPIBAIJ, 2062 MatGetRow_MPIBAIJ, 2063 MatRestoreRow_MPIBAIJ, 2064 MatMult_MPIBAIJ, 2065 /* 4*/ MatMultAdd_MPIBAIJ, 2066 MatMultTranspose_MPIBAIJ, 2067 MatMultTransposeAdd_MPIBAIJ, 2068 0, 2069 0, 2070 0, 2071 /*10*/ 0, 2072 0, 2073 0, 2074 0, 2075 MatTranspose_MPIBAIJ, 2076 /*15*/ MatGetInfo_MPIBAIJ, 2077 MatEqual_MPIBAIJ, 2078 MatGetDiagonal_MPIBAIJ, 2079 MatDiagonalScale_MPIBAIJ, 2080 MatNorm_MPIBAIJ, 2081 /*20*/ MatAssemblyBegin_MPIBAIJ, 2082 MatAssemblyEnd_MPIBAIJ, 2083 MatSetOption_MPIBAIJ, 2084 MatZeroEntries_MPIBAIJ, 2085 /*24*/ MatZeroRows_MPIBAIJ, 2086 0, 2087 0, 2088 0, 2089 0, 2090 /*29*/ MatSetUpPreallocation_MPIBAIJ, 2091 0, 2092 0, 2093 0, 2094 0, 2095 /*34*/ MatDuplicate_MPIBAIJ, 2096 0, 2097 0, 2098 0, 2099 0, 2100 /*39*/ MatAXPY_MPIBAIJ, 2101 MatGetSubMatrices_MPIBAIJ, 2102 MatIncreaseOverlap_MPIBAIJ, 2103 MatGetValues_MPIBAIJ, 2104 MatCopy_MPIBAIJ, 2105 /*44*/ 0, 2106 MatScale_MPIBAIJ, 2107 0, 2108 0, 2109 0, 2110 /*49*/ 0, 2111 0, 2112 0, 2113 0, 2114 0, 2115 /*54*/ MatFDColoringCreate_MPIAIJ, 2116 0, 2117 MatSetUnfactored_MPIBAIJ, 2118 MatPermute_MPIBAIJ, 2119 MatSetValuesBlocked_MPIBAIJ, 2120 /*59*/ MatGetSubMatrix_MPIBAIJ, 2121 MatDestroy_MPIBAIJ, 2122 MatView_MPIBAIJ, 2123 0, 2124 0, 2125 /*64*/ 0, 2126 0, 2127 0, 2128 0, 2129 0, 2130 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2131 0, 2132 0, 2133 0, 2134 0, 2135 /*74*/ 0, 2136 0, 2137 0, 2138 0, 2139 0, 2140 /*79*/ 0, 2141 0, 2142 0, 2143 0, 2144 MatLoad_MPIBAIJ, 2145 /*84*/ 0, 2146 0, 2147 0, 2148 0, 2149 0, 2150 /*89*/ 0, 2151 0, 2152 0, 2153 0, 2154 0, 2155 /*94*/ 0, 2156 0, 2157 0, 2158 0, 2159 0, 2160 /*99*/ 0, 2161 0, 2162 0, 2163 0, 2164 0, 2165 /*104*/0, 2166 MatRealPart_MPIBAIJ, 2167 MatImaginaryPart_MPIBAIJ, 2168 0, 2169 0, 2170 /*109*/0, 2171 0, 2172 0, 2173 0, 2174 0, 2175 /*114*/0, 2176 0, 2177 MatGetGhosts_MPIBAIJ 2178 }; 2179 2180 2181 EXTERN_C_BEGIN 2182 #undef __FUNCT__ 2183 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2184 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 2185 { 2186 PetscFunctionBegin; 2187 *a = ((Mat_MPIBAIJ *)A->data)->A; 2188 *iscopy = PETSC_FALSE; 2189 PetscFunctionReturn(0); 2190 } 2191 EXTERN_C_END 2192 2193 EXTERN_C_BEGIN 2194 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2195 EXTERN_C_END 2196 2197 EXTERN_C_BEGIN 2198 #undef __FUNCT__ 2199 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2200 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2201 { 2202 PetscInt m,rstart,cstart,cend; 2203 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2204 const PetscInt *JJ=0; 2205 PetscScalar *values=0; 2206 PetscErrorCode ierr; 2207 2208 PetscFunctionBegin; 2209 2210 if (bs < 1) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 2211 ierr = PetscMapSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2212 ierr = PetscMapSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2213 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2214 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2215 m = B->rmap->n/bs; 2216 rstart = B->rmap->rstart/bs; 2217 cstart = B->cmap->rstart/bs; 2218 cend = B->cmap->rend/bs; 2219 2220 if (ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2221 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2222 o_nnz = d_nnz + m; 2223 for (i=0; i<m; i++) { 2224 nz = ii[i+1] - ii[i]; 2225 if (nz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2226 nz_max = PetscMax(nz_max,nz); 2227 JJ = jj + ii[i]; 2228 for (j=0; j<nz; j++) { 2229 if (*JJ >= cstart) break; 2230 JJ++; 2231 } 2232 d = 0; 2233 for (; j<nz; j++) { 2234 if (*JJ++ >= cend) break; 2235 d++; 2236 } 2237 d_nnz[i] = d; 2238 o_nnz[i] = nz - d; 2239 } 2240 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2241 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2242 2243 values = (PetscScalar*)V; 2244 if (!values) { 2245 ierr = PetscMalloc(bs*bs*(nz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2246 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2247 } 2248 for (i=0; i<m; i++) { 2249 PetscInt row = i + rstart; 2250 PetscInt ncols = ii[i+1] - ii[i]; 2251 const PetscInt *icols = jj + ii[i]; 2252 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2253 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2254 } 2255 2256 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2257 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2258 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2259 2260 PetscFunctionReturn(0); 2261 } 2262 EXTERN_C_END 2263 2264 #undef __FUNCT__ 2265 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2266 /*@C 2267 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2268 (the default parallel PETSc format). 2269 2270 Collective on MPI_Comm 2271 2272 Input Parameters: 2273 + A - the matrix 2274 . i - the indices into j for the start of each local row (starts with zero) 2275 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2276 - v - optional values in the matrix 2277 2278 Level: developer 2279 2280 .keywords: matrix, aij, compressed row, sparse, parallel 2281 2282 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2283 @*/ 2284 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2285 { 2286 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2287 2288 PetscFunctionBegin; 2289 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2290 if (f) { 2291 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2292 } 2293 PetscFunctionReturn(0); 2294 } 2295 2296 EXTERN_C_BEGIN 2297 #undef __FUNCT__ 2298 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2299 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2300 { 2301 Mat_MPIBAIJ *b; 2302 PetscErrorCode ierr; 2303 PetscInt i, newbs = PetscAbs(bs); 2304 2305 PetscFunctionBegin; 2306 if (bs < 0) { 2307 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2308 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 2309 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2310 bs = PetscAbs(bs); 2311 } 2312 if ((d_nnz || o_nnz) && newbs != bs) { 2313 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 2314 } 2315 bs = newbs; 2316 2317 2318 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2319 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2320 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2321 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2322 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2323 2324 ierr = PetscMapSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2325 ierr = PetscMapSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2326 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2327 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2328 2329 if (d_nnz) { 2330 for (i=0; i<B->rmap->n/bs; i++) { 2331 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2332 } 2333 } 2334 if (o_nnz) { 2335 for (i=0; i<B->rmap->n/bs; i++) { 2336 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2337 } 2338 } 2339 2340 b = (Mat_MPIBAIJ*)B->data; 2341 b->bs2 = bs*bs; 2342 b->mbs = B->rmap->n/bs; 2343 b->nbs = B->cmap->n/bs; 2344 b->Mbs = B->rmap->N/bs; 2345 b->Nbs = B->cmap->N/bs; 2346 2347 for (i=0; i<=b->size; i++) { 2348 b->rangebs[i] = B->rmap->range[i]/bs; 2349 } 2350 b->rstartbs = B->rmap->rstart/bs; 2351 b->rendbs = B->rmap->rend/bs; 2352 b->cstartbs = B->cmap->rstart/bs; 2353 b->cendbs = B->cmap->rend/bs; 2354 2355 if (!B->preallocated) { 2356 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2357 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2358 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2359 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2360 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2361 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2362 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2363 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2364 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 2365 } 2366 2367 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2368 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2369 B->preallocated = PETSC_TRUE; 2370 PetscFunctionReturn(0); 2371 } 2372 EXTERN_C_END 2373 2374 EXTERN_C_BEGIN 2375 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2376 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2377 EXTERN_C_END 2378 2379 2380 EXTERN_C_BEGIN 2381 #undef __FUNCT__ 2382 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2383 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPIAdj(Mat B, const MatType newtype,MatReuse reuse,Mat *adj) 2384 { 2385 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2386 PetscErrorCode ierr; 2387 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2388 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2389 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2390 2391 PetscFunctionBegin; 2392 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 2393 ii[0] = 0; 2394 CHKMEMQ; 2395 for (i=0; i<M; i++) { 2396 if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]); 2397 if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]); 2398 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2399 /* remove one from count of matrix has diagonal */ 2400 for (j=id[i]; j<id[i+1]; j++) { 2401 if (jd[j] == i) {ii[i+1]--;break;} 2402 } 2403 CHKMEMQ; 2404 } 2405 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 2406 cnt = 0; 2407 for (i=0; i<M; i++) { 2408 for (j=io[i]; j<io[i+1]; j++) { 2409 if (garray[jo[j]] > rstart) break; 2410 jj[cnt++] = garray[jo[j]]; 2411 CHKMEMQ; 2412 } 2413 for (k=id[i]; k<id[i+1]; k++) { 2414 if (jd[k] != i) { 2415 jj[cnt++] = rstart + jd[k]; 2416 CHKMEMQ; 2417 } 2418 } 2419 for (;j<io[i+1]; j++) { 2420 jj[cnt++] = garray[jo[j]]; 2421 CHKMEMQ; 2422 } 2423 } 2424 ierr = MatCreateMPIAdj(((PetscObject)B)->comm,M,B->cmap->N/B->rmap->bs,ii,jj,PETSC_NULL,adj);CHKERRQ(ierr); 2425 PetscFunctionReturn(0); 2426 } 2427 EXTERN_C_END 2428 2429 /*MC 2430 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2431 2432 Options Database Keys: 2433 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2434 . -mat_block_size <bs> - set the blocksize used to store the matrix 2435 - -mat_use_hash_table <fact> 2436 2437 Level: beginner 2438 2439 .seealso: MatCreateMPIBAIJ 2440 M*/ 2441 2442 EXTERN_C_BEGIN 2443 #undef __FUNCT__ 2444 #define __FUNCT__ "MatCreate_MPIBAIJ" 2445 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2446 { 2447 Mat_MPIBAIJ *b; 2448 PetscErrorCode ierr; 2449 PetscTruth flg; 2450 2451 PetscFunctionBegin; 2452 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2453 B->data = (void*)b; 2454 2455 2456 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2457 B->mapping = 0; 2458 B->assembled = PETSC_FALSE; 2459 2460 B->insertmode = NOT_SET_VALUES; 2461 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 2462 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 2463 2464 /* build local table of row and column ownerships */ 2465 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2466 2467 /* build cache for off array entries formed */ 2468 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 2469 b->donotstash = PETSC_FALSE; 2470 b->colmap = PETSC_NULL; 2471 b->garray = PETSC_NULL; 2472 b->roworiented = PETSC_TRUE; 2473 2474 /* stuff used in block assembly */ 2475 b->barray = 0; 2476 2477 /* stuff used for matrix vector multiply */ 2478 b->lvec = 0; 2479 b->Mvctx = 0; 2480 2481 /* stuff for MatGetRow() */ 2482 b->rowindices = 0; 2483 b->rowvalues = 0; 2484 b->getrowactive = PETSC_FALSE; 2485 2486 /* hash table stuff */ 2487 b->ht = 0; 2488 b->hd = 0; 2489 b->ht_size = 0; 2490 b->ht_flag = PETSC_FALSE; 2491 b->ht_fact = 0; 2492 b->ht_total_ct = 0; 2493 b->ht_insert_ct = 0; 2494 2495 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 2496 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 2497 if (flg) { 2498 PetscReal fact = 1.39; 2499 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 2500 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 2501 if (fact <= 1.0) fact = 1.39; 2502 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2503 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 2504 } 2505 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2506 2507 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiadj_C", 2508 "MatConvert_MPIBAIJ_MPIAdj", 2509 MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 2510 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2511 "MatStoreValues_MPIBAIJ", 2512 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2513 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2514 "MatRetrieveValues_MPIBAIJ", 2515 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2516 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2517 "MatGetDiagonalBlock_MPIBAIJ", 2518 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2519 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2520 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2521 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2522 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2523 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 2524 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2525 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2526 "MatDiagonalScaleLocal_MPIBAIJ", 2527 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2528 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2529 "MatSetHashTableFactor_MPIBAIJ", 2530 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2531 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 2532 PetscFunctionReturn(0); 2533 } 2534 EXTERN_C_END 2535 2536 /*MC 2537 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2538 2539 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2540 and MATMPIBAIJ otherwise. 2541 2542 Options Database Keys: 2543 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2544 2545 Level: beginner 2546 2547 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2548 M*/ 2549 2550 EXTERN_C_BEGIN 2551 #undef __FUNCT__ 2552 #define __FUNCT__ "MatCreate_BAIJ" 2553 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2554 { 2555 PetscErrorCode ierr; 2556 PetscMPIInt size; 2557 2558 PetscFunctionBegin; 2559 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2560 if (size == 1) { 2561 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2562 } else { 2563 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2564 } 2565 PetscFunctionReturn(0); 2566 } 2567 EXTERN_C_END 2568 2569 #undef __FUNCT__ 2570 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2571 /*@C 2572 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2573 (block compressed row). For good matrix assembly performance 2574 the user should preallocate the matrix storage by setting the parameters 2575 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2576 performance can be increased by more than a factor of 50. 2577 2578 Collective on Mat 2579 2580 Input Parameters: 2581 + A - the matrix 2582 . bs - size of blockk 2583 . d_nz - number of block nonzeros per block row in diagonal portion of local 2584 submatrix (same for all local rows) 2585 . d_nnz - array containing the number of block nonzeros in the various block rows 2586 of the in diagonal portion of the local (possibly different for each block 2587 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2588 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2589 submatrix (same for all local rows). 2590 - o_nnz - array containing the number of nonzeros in the various block rows of the 2591 off-diagonal portion of the local submatrix (possibly different for 2592 each block row) or PETSC_NULL. 2593 2594 If the *_nnz parameter is given then the *_nz parameter is ignored 2595 2596 Options Database Keys: 2597 + -mat_block_size - size of the blocks to use 2598 - -mat_use_hash_table <fact> 2599 2600 Notes: 2601 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2602 than it must be used on all processors that share the object for that argument. 2603 2604 Storage Information: 2605 For a square global matrix we define each processor's diagonal portion 2606 to be its local rows and the corresponding columns (a square submatrix); 2607 each processor's off-diagonal portion encompasses the remainder of the 2608 local matrix (a rectangular submatrix). 2609 2610 The user can specify preallocated storage for the diagonal part of 2611 the local submatrix with either d_nz or d_nnz (not both). Set 2612 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2613 memory allocation. Likewise, specify preallocated storage for the 2614 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2615 2616 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2617 the figure below we depict these three local rows and all columns (0-11). 2618 2619 .vb 2620 0 1 2 3 4 5 6 7 8 9 10 11 2621 ------------------- 2622 row 3 | o o o d d d o o o o o o 2623 row 4 | o o o d d d o o o o o o 2624 row 5 | o o o d d d o o o o o o 2625 ------------------- 2626 .ve 2627 2628 Thus, any entries in the d locations are stored in the d (diagonal) 2629 submatrix, and any entries in the o locations are stored in the 2630 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2631 stored simply in the MATSEQBAIJ format for compressed row storage. 2632 2633 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2634 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2635 In general, for PDE problems in which most nonzeros are near the diagonal, 2636 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2637 or you will get TERRIBLE performance; see the users' manual chapter on 2638 matrices. 2639 2640 You can call MatGetInfo() to get information on how effective the preallocation was; 2641 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2642 You can also run with the option -info and look for messages with the string 2643 malloc in them to see if additional memory allocation was needed. 2644 2645 Level: intermediate 2646 2647 .keywords: matrix, block, aij, compressed row, sparse, parallel 2648 2649 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2650 @*/ 2651 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2652 { 2653 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2654 2655 PetscFunctionBegin; 2656 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2657 if (f) { 2658 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2659 } 2660 PetscFunctionReturn(0); 2661 } 2662 2663 #undef __FUNCT__ 2664 #define __FUNCT__ "MatCreateMPIBAIJ" 2665 /*@C 2666 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2667 (block compressed row). For good matrix assembly performance 2668 the user should preallocate the matrix storage by setting the parameters 2669 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2670 performance can be increased by more than a factor of 50. 2671 2672 Collective on MPI_Comm 2673 2674 Input Parameters: 2675 + comm - MPI communicator 2676 . bs - size of blockk 2677 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2678 This value should be the same as the local size used in creating the 2679 y vector for the matrix-vector product y = Ax. 2680 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2681 This value should be the same as the local size used in creating the 2682 x vector for the matrix-vector product y = Ax. 2683 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2684 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2685 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2686 submatrix (same for all local rows) 2687 . d_nnz - array containing the number of nonzero blocks in the various block rows 2688 of the in diagonal portion of the local (possibly different for each block 2689 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2690 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2691 submatrix (same for all local rows). 2692 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2693 off-diagonal portion of the local submatrix (possibly different for 2694 each block row) or PETSC_NULL. 2695 2696 Output Parameter: 2697 . A - the matrix 2698 2699 Options Database Keys: 2700 + -mat_block_size - size of the blocks to use 2701 - -mat_use_hash_table <fact> 2702 2703 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2704 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2705 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2706 2707 Notes: 2708 If the *_nnz parameter is given then the *_nz parameter is ignored 2709 2710 A nonzero block is any block that as 1 or more nonzeros in it 2711 2712 The user MUST specify either the local or global matrix dimensions 2713 (possibly both). 2714 2715 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2716 than it must be used on all processors that share the object for that argument. 2717 2718 Storage Information: 2719 For a square global matrix we define each processor's diagonal portion 2720 to be its local rows and the corresponding columns (a square submatrix); 2721 each processor's off-diagonal portion encompasses the remainder of the 2722 local matrix (a rectangular submatrix). 2723 2724 The user can specify preallocated storage for the diagonal part of 2725 the local submatrix with either d_nz or d_nnz (not both). Set 2726 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2727 memory allocation. Likewise, specify preallocated storage for the 2728 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2729 2730 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2731 the figure below we depict these three local rows and all columns (0-11). 2732 2733 .vb 2734 0 1 2 3 4 5 6 7 8 9 10 11 2735 ------------------- 2736 row 3 | o o o d d d o o o o o o 2737 row 4 | o o o d d d o o o o o o 2738 row 5 | o o o d d d o o o o o o 2739 ------------------- 2740 .ve 2741 2742 Thus, any entries in the d locations are stored in the d (diagonal) 2743 submatrix, and any entries in the o locations are stored in the 2744 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2745 stored simply in the MATSEQBAIJ format for compressed row storage. 2746 2747 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2748 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2749 In general, for PDE problems in which most nonzeros are near the diagonal, 2750 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2751 or you will get TERRIBLE performance; see the users' manual chapter on 2752 matrices. 2753 2754 Level: intermediate 2755 2756 .keywords: matrix, block, aij, compressed row, sparse, parallel 2757 2758 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2759 @*/ 2760 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIBAIJ(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) 2761 { 2762 PetscErrorCode ierr; 2763 PetscMPIInt size; 2764 2765 PetscFunctionBegin; 2766 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2767 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2768 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2769 if (size > 1) { 2770 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2771 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2772 } else { 2773 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2774 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2775 } 2776 PetscFunctionReturn(0); 2777 } 2778 2779 #undef __FUNCT__ 2780 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2781 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2782 { 2783 Mat mat; 2784 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2785 PetscErrorCode ierr; 2786 PetscInt len=0; 2787 2788 PetscFunctionBegin; 2789 *newmat = 0; 2790 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2791 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2792 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2793 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2794 2795 mat->factor = matin->factor; 2796 mat->preallocated = PETSC_TRUE; 2797 mat->assembled = PETSC_TRUE; 2798 mat->insertmode = NOT_SET_VALUES; 2799 2800 a = (Mat_MPIBAIJ*)mat->data; 2801 mat->rmap->bs = matin->rmap->bs; 2802 a->bs2 = oldmat->bs2; 2803 a->mbs = oldmat->mbs; 2804 a->nbs = oldmat->nbs; 2805 a->Mbs = oldmat->Mbs; 2806 a->Nbs = oldmat->Nbs; 2807 2808 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2809 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2810 2811 a->size = oldmat->size; 2812 a->rank = oldmat->rank; 2813 a->donotstash = oldmat->donotstash; 2814 a->roworiented = oldmat->roworiented; 2815 a->rowindices = 0; 2816 a->rowvalues = 0; 2817 a->getrowactive = PETSC_FALSE; 2818 a->barray = 0; 2819 a->rstartbs = oldmat->rstartbs; 2820 a->rendbs = oldmat->rendbs; 2821 a->cstartbs = oldmat->cstartbs; 2822 a->cendbs = oldmat->cendbs; 2823 2824 /* hash table stuff */ 2825 a->ht = 0; 2826 a->hd = 0; 2827 a->ht_size = 0; 2828 a->ht_flag = oldmat->ht_flag; 2829 a->ht_fact = oldmat->ht_fact; 2830 a->ht_total_ct = 0; 2831 a->ht_insert_ct = 0; 2832 2833 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 2834 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2835 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2836 if (oldmat->colmap) { 2837 #if defined (PETSC_USE_CTABLE) 2838 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2839 #else 2840 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2841 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2842 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2843 #endif 2844 } else a->colmap = 0; 2845 2846 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2847 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2848 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2849 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2850 } else a->garray = 0; 2851 2852 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2853 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2854 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2855 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2856 2857 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2858 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2859 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2860 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2861 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2862 *newmat = mat; 2863 2864 PetscFunctionReturn(0); 2865 } 2866 2867 #include "petscsys.h" 2868 2869 #undef __FUNCT__ 2870 #define __FUNCT__ "MatLoad_MPIBAIJ" 2871 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2872 { 2873 Mat A; 2874 PetscErrorCode ierr; 2875 int fd; 2876 PetscInt i,nz,j,rstart,rend; 2877 PetscScalar *vals,*buf; 2878 MPI_Comm comm = ((PetscObject)viewer)->comm; 2879 MPI_Status status; 2880 PetscMPIInt rank,size,maxnz; 2881 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2882 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 2883 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2884 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2885 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 2886 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2887 2888 PetscFunctionBegin; 2889 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 2890 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2891 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2892 2893 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2894 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2895 if (!rank) { 2896 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2897 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2898 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2899 } 2900 2901 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2902 M = header[1]; N = header[2]; 2903 2904 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2905 2906 /* 2907 This code adds extra rows to make sure the number of rows is 2908 divisible by the blocksize 2909 */ 2910 Mbs = M/bs; 2911 extra_rows = bs - M + bs*Mbs; 2912 if (extra_rows == bs) extra_rows = 0; 2913 else Mbs++; 2914 if (extra_rows && !rank) { 2915 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2916 } 2917 2918 /* determine ownership of all rows */ 2919 mbs = Mbs/size + ((Mbs % size) > rank); 2920 m = mbs*bs; 2921 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2922 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2923 2924 /* process 0 needs enough room for process with most rows */ 2925 if (!rank) { 2926 mmax = rowners[1]; 2927 for (i=2; i<size; i++) { 2928 mmax = PetscMax(mmax,rowners[i]); 2929 } 2930 mmax*=bs; 2931 } else mmax = m; 2932 2933 rowners[0] = 0; 2934 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2935 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2936 rstart = rowners[rank]; 2937 rend = rowners[rank+1]; 2938 2939 /* distribute row lengths to all processors */ 2940 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2941 if (!rank) { 2942 mend = m; 2943 if (size == 1) mend = mend - extra_rows; 2944 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2945 for (j=mend; j<m; j++) locrowlens[j] = 1; 2946 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2947 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2948 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2949 for (j=0; j<m; j++) { 2950 procsnz[0] += locrowlens[j]; 2951 } 2952 for (i=1; i<size; i++) { 2953 mend = browners[i+1] - browners[i]; 2954 if (i == size-1) mend = mend - extra_rows; 2955 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2956 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2957 /* calculate the number of nonzeros on each processor */ 2958 for (j=0; j<browners[i+1]-browners[i]; j++) { 2959 procsnz[i] += rowlengths[j]; 2960 } 2961 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2962 } 2963 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2964 } else { 2965 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2966 } 2967 2968 if (!rank) { 2969 /* determine max buffer needed and allocate it */ 2970 maxnz = procsnz[0]; 2971 for (i=1; i<size; i++) { 2972 maxnz = PetscMax(maxnz,procsnz[i]); 2973 } 2974 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2975 2976 /* read in my part of the matrix column indices */ 2977 nz = procsnz[0]; 2978 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2979 mycols = ibuf; 2980 if (size == 1) nz -= extra_rows; 2981 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2982 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2983 2984 /* read in every ones (except the last) and ship off */ 2985 for (i=1; i<size-1; i++) { 2986 nz = procsnz[i]; 2987 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2988 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2989 } 2990 /* read in the stuff for the last proc */ 2991 if (size != 1) { 2992 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2993 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2994 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2995 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2996 } 2997 ierr = PetscFree(cols);CHKERRQ(ierr); 2998 } else { 2999 /* determine buffer space needed for message */ 3000 nz = 0; 3001 for (i=0; i<m; i++) { 3002 nz += locrowlens[i]; 3003 } 3004 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3005 mycols = ibuf; 3006 /* receive message of column indices*/ 3007 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3008 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3009 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3010 } 3011 3012 /* loop over local rows, determining number of off diagonal entries */ 3013 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3014 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3015 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3016 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3017 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3018 rowcount = 0; nzcount = 0; 3019 for (i=0; i<mbs; i++) { 3020 dcount = 0; 3021 odcount = 0; 3022 for (j=0; j<bs; j++) { 3023 kmax = locrowlens[rowcount]; 3024 for (k=0; k<kmax; k++) { 3025 tmp = mycols[nzcount++]/bs; 3026 if (!mask[tmp]) { 3027 mask[tmp] = 1; 3028 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3029 else masked1[dcount++] = tmp; 3030 } 3031 } 3032 rowcount++; 3033 } 3034 3035 dlens[i] = dcount; 3036 odlens[i] = odcount; 3037 3038 /* zero out the mask elements we set */ 3039 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3040 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3041 } 3042 3043 /* create our matrix */ 3044 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 3045 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3046 ierr = MatSetType(A,type);CHKERRQ(ierr) 3047 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3048 3049 if (!rank) { 3050 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3051 /* read in my part of the matrix numerical values */ 3052 nz = procsnz[0]; 3053 vals = buf; 3054 mycols = ibuf; 3055 if (size == 1) nz -= extra_rows; 3056 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3057 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 3058 3059 /* insert into matrix */ 3060 jj = rstart*bs; 3061 for (i=0; i<m; i++) { 3062 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3063 mycols += locrowlens[i]; 3064 vals += locrowlens[i]; 3065 jj++; 3066 } 3067 /* read in other processors (except the last one) and ship out */ 3068 for (i=1; i<size-1; i++) { 3069 nz = procsnz[i]; 3070 vals = buf; 3071 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3072 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 3073 } 3074 /* the last proc */ 3075 if (size != 1){ 3076 nz = procsnz[i] - extra_rows; 3077 vals = buf; 3078 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3079 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3080 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 3081 } 3082 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3083 } else { 3084 /* receive numeric values */ 3085 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3086 3087 /* receive message of values*/ 3088 vals = buf; 3089 mycols = ibuf; 3090 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 3091 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 3092 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3093 3094 /* insert into matrix */ 3095 jj = rstart*bs; 3096 for (i=0; i<m; i++) { 3097 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3098 mycols += locrowlens[i]; 3099 vals += locrowlens[i]; 3100 jj++; 3101 } 3102 } 3103 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3104 ierr = PetscFree(buf);CHKERRQ(ierr); 3105 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3106 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3107 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3108 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3109 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3110 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3111 3112 *newmat = A; 3113 PetscFunctionReturn(0); 3114 } 3115 3116 #undef __FUNCT__ 3117 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3118 /*@ 3119 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3120 3121 Input Parameters: 3122 . mat - the matrix 3123 . fact - factor 3124 3125 Collective on Mat 3126 3127 Level: advanced 3128 3129 Notes: 3130 This can also be set by the command line option: -mat_use_hash_table <fact> 3131 3132 .keywords: matrix, hashtable, factor, HT 3133 3134 .seealso: MatSetOption() 3135 @*/ 3136 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3137 { 3138 PetscErrorCode ierr,(*f)(Mat,PetscReal); 3139 3140 PetscFunctionBegin; 3141 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 3142 if (f) { 3143 ierr = (*f)(mat,fact);CHKERRQ(ierr); 3144 } 3145 PetscFunctionReturn(0); 3146 } 3147 3148 EXTERN_C_BEGIN 3149 #undef __FUNCT__ 3150 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3151 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3152 { 3153 Mat_MPIBAIJ *baij; 3154 3155 PetscFunctionBegin; 3156 baij = (Mat_MPIBAIJ*)mat->data; 3157 baij->ht_fact = fact; 3158 PetscFunctionReturn(0); 3159 } 3160 EXTERN_C_END 3161 3162 #undef __FUNCT__ 3163 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3164 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3165 { 3166 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 3167 PetscFunctionBegin; 3168 *Ad = a->A; 3169 *Ao = a->B; 3170 *colmap = a->garray; 3171 PetscFunctionReturn(0); 3172 } 3173 3174 /* 3175 Special version for direct calls from Fortran (to eliminate two function call overheads 3176 */ 3177 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3178 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3179 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3180 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3181 #endif 3182 3183 #undef __FUNCT__ 3184 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3185 /*@C 3186 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3187 3188 Collective on Mat 3189 3190 Input Parameters: 3191 + mat - the matrix 3192 . min - number of input rows 3193 . im - input rows 3194 . nin - number of input columns 3195 . in - input columns 3196 . v - numerical values input 3197 - addvin - INSERT_VALUES or ADD_VALUES 3198 3199 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3200 3201 Level: advanced 3202 3203 .seealso: MatSetValuesBlocked() 3204 @*/ 3205 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3206 { 3207 /* convert input arguments to C version */ 3208 Mat mat = *matin; 3209 PetscInt m = *min, n = *nin; 3210 InsertMode addv = *addvin; 3211 3212 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3213 const MatScalar *value; 3214 MatScalar *barray=baij->barray; 3215 PetscTruth roworiented = baij->roworiented; 3216 PetscErrorCode ierr; 3217 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3218 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3219 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3220 3221 PetscFunctionBegin; 3222 /* tasks normally handled by MatSetValuesBlocked() */ 3223 if (mat->insertmode == NOT_SET_VALUES) { 3224 mat->insertmode = addv; 3225 } 3226 #if defined(PETSC_USE_DEBUG) 3227 else if (mat->insertmode != addv) { 3228 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3229 } 3230 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3231 #endif 3232 if (mat->assembled) { 3233 mat->was_assembled = PETSC_TRUE; 3234 mat->assembled = PETSC_FALSE; 3235 } 3236 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3237 3238 3239 if(!barray) { 3240 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3241 baij->barray = barray; 3242 } 3243 3244 if (roworiented) { 3245 stepval = (n-1)*bs; 3246 } else { 3247 stepval = (m-1)*bs; 3248 } 3249 for (i=0; i<m; i++) { 3250 if (im[i] < 0) continue; 3251 #if defined(PETSC_USE_DEBUG) 3252 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 3253 #endif 3254 if (im[i] >= rstart && im[i] < rend) { 3255 row = im[i] - rstart; 3256 for (j=0; j<n; j++) { 3257 /* If NumCol = 1 then a copy is not required */ 3258 if ((roworiented) && (n == 1)) { 3259 barray = (MatScalar*)v + i*bs2; 3260 } else if((!roworiented) && (m == 1)) { 3261 barray = (MatScalar*)v + j*bs2; 3262 } else { /* Here a copy is required */ 3263 if (roworiented) { 3264 value = v + i*(stepval+bs)*bs + j*bs; 3265 } else { 3266 value = v + j*(stepval+bs)*bs + i*bs; 3267 } 3268 for (ii=0; ii<bs; ii++,value+=stepval) { 3269 for (jj=0; jj<bs; jj++) { 3270 *barray++ = *value++; 3271 } 3272 } 3273 barray -=bs2; 3274 } 3275 3276 if (in[j] >= cstart && in[j] < cend){ 3277 col = in[j] - cstart; 3278 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3279 } 3280 else if (in[j] < 0) continue; 3281 #if defined(PETSC_USE_DEBUG) 3282 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 3283 #endif 3284 else { 3285 if (mat->was_assembled) { 3286 if (!baij->colmap) { 3287 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3288 } 3289 3290 #if defined(PETSC_USE_DEBUG) 3291 #if defined (PETSC_USE_CTABLE) 3292 { PetscInt data; 3293 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3294 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3295 } 3296 #else 3297 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3298 #endif 3299 #endif 3300 #if defined (PETSC_USE_CTABLE) 3301 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3302 col = (col - 1)/bs; 3303 #else 3304 col = (baij->colmap[in[j]] - 1)/bs; 3305 #endif 3306 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3307 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3308 col = in[j]; 3309 } 3310 } 3311 else col = in[j]; 3312 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3313 } 3314 } 3315 } else { 3316 if (!baij->donotstash) { 3317 if (roworiented) { 3318 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3319 } else { 3320 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3321 } 3322 } 3323 } 3324 } 3325 3326 /* task normally handled by MatSetValuesBlocked() */ 3327 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3328 PetscFunctionReturn(0); 3329 } 3330