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->cmap.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);CHKERRQ(ierr); 265 } else { 266 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);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);CHKERRQ(ierr); 447 } else { 448 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);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->rows_global = (PetscReal)A->rmap.N; 1407 info->columns_global = (PetscReal)A->cmap.N; 1408 info->rows_local = (PetscReal)A->rmap.N; 1409 info->columns_local = (PetscReal)A->cmap.N; 1410 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1411 info->fill_ratio_needed = 0; 1412 info->factor_mallocs = 0; 1413 PetscFunctionReturn(0); 1414 } 1415 1416 #undef __FUNCT__ 1417 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1418 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscTruth flg) 1419 { 1420 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1421 PetscErrorCode ierr; 1422 1423 PetscFunctionBegin; 1424 switch (op) { 1425 case MAT_NEW_NONZERO_LOCATIONS: 1426 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1427 case MAT_KEEP_ZEROED_ROWS: 1428 case MAT_NEW_NONZERO_LOCATION_ERR: 1429 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1430 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1431 break; 1432 case MAT_ROW_ORIENTED: 1433 a->roworiented = flg; 1434 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1435 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1436 break; 1437 case MAT_NEW_DIAGONALS: 1438 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1439 break; 1440 case MAT_IGNORE_OFF_PROC_ENTRIES: 1441 a->donotstash = flg; 1442 break; 1443 case MAT_USE_HASH_TABLE: 1444 a->ht_flag = flg; 1445 break; 1446 case MAT_SYMMETRIC: 1447 case MAT_STRUCTURALLY_SYMMETRIC: 1448 case MAT_HERMITIAN: 1449 case MAT_SYMMETRY_ETERNAL: 1450 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1451 break; 1452 default: 1453 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1454 } 1455 PetscFunctionReturn(0); 1456 } 1457 1458 #undef __FUNCT__ 1459 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1460 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1461 { 1462 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1463 Mat_SeqBAIJ *Aloc; 1464 Mat B; 1465 PetscErrorCode ierr; 1466 PetscInt M=A->rmap.N,N=A->cmap.N,*ai,*aj,i,*rvals,j,k,col; 1467 PetscInt bs=A->rmap.bs,mbs=baij->mbs; 1468 MatScalar *a; 1469 1470 PetscFunctionBegin; 1471 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1472 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1473 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1474 ierr = MatSetSizes(B,A->cmap.n,A->rmap.n,N,M);CHKERRQ(ierr); 1475 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1476 ierr = MatMPIBAIJSetPreallocation(B,A->rmap.bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1477 } else { 1478 B = *matout; 1479 } 1480 1481 /* copy over the A part */ 1482 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1483 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1484 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1485 1486 for (i=0; i<mbs; i++) { 1487 rvals[0] = bs*(baij->rstartbs + i); 1488 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1489 for (j=ai[i]; j<ai[i+1]; j++) { 1490 col = (baij->cstartbs+aj[j])*bs; 1491 for (k=0; k<bs; k++) { 1492 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1493 col++; a += bs; 1494 } 1495 } 1496 } 1497 /* copy over the B part */ 1498 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1499 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1500 for (i=0; i<mbs; i++) { 1501 rvals[0] = bs*(baij->rstartbs + i); 1502 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1503 for (j=ai[i]; j<ai[i+1]; j++) { 1504 col = baij->garray[aj[j]]*bs; 1505 for (k=0; k<bs; k++) { 1506 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1507 col++; a += bs; 1508 } 1509 } 1510 } 1511 ierr = PetscFree(rvals);CHKERRQ(ierr); 1512 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1513 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1514 1515 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1516 *matout = B; 1517 } else { 1518 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1519 } 1520 PetscFunctionReturn(0); 1521 } 1522 1523 #undef __FUNCT__ 1524 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1525 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1526 { 1527 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1528 Mat a = baij->A,b = baij->B; 1529 PetscErrorCode ierr; 1530 PetscInt s1,s2,s3; 1531 1532 PetscFunctionBegin; 1533 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1534 if (rr) { 1535 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1536 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1537 /* Overlap communication with computation. */ 1538 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1539 } 1540 if (ll) { 1541 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1542 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1543 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1544 } 1545 /* scale the diagonal block */ 1546 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1547 1548 if (rr) { 1549 /* Do a scatter end and then right scale the off-diagonal block */ 1550 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1551 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1552 } 1553 1554 PetscFunctionReturn(0); 1555 } 1556 1557 #undef __FUNCT__ 1558 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1559 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 1560 { 1561 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1562 PetscErrorCode ierr; 1563 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1564 PetscInt i,*owners = A->rmap.range; 1565 PetscInt *nprocs,j,idx,nsends,row; 1566 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1567 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1568 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap.rstart; 1569 MPI_Comm comm = ((PetscObject)A)->comm; 1570 MPI_Request *send_waits,*recv_waits; 1571 MPI_Status recv_status,*send_status; 1572 #if defined(PETSC_DEBUG) 1573 PetscTruth found = PETSC_FALSE; 1574 #endif 1575 1576 PetscFunctionBegin; 1577 /* first count number of contributors to each processor */ 1578 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1579 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1580 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1581 j = 0; 1582 for (i=0; i<N; i++) { 1583 if (lastidx > (idx = rows[i])) j = 0; 1584 lastidx = idx; 1585 for (; j<size; j++) { 1586 if (idx >= owners[j] && idx < owners[j+1]) { 1587 nprocs[2*j]++; 1588 nprocs[2*j+1] = 1; 1589 owner[i] = j; 1590 #if defined(PETSC_DEBUG) 1591 found = PETSC_TRUE; 1592 #endif 1593 break; 1594 } 1595 } 1596 #if defined(PETSC_DEBUG) 1597 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1598 found = PETSC_FALSE; 1599 #endif 1600 } 1601 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1602 1603 /* inform other processors of number of messages and max length*/ 1604 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1605 1606 /* post receives: */ 1607 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1608 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1609 for (i=0; i<nrecvs; i++) { 1610 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1611 } 1612 1613 /* do sends: 1614 1) starts[i] gives the starting index in svalues for stuff going to 1615 the ith processor 1616 */ 1617 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1618 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1619 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1620 starts[0] = 0; 1621 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1622 for (i=0; i<N; i++) { 1623 svalues[starts[owner[i]]++] = rows[i]; 1624 } 1625 1626 starts[0] = 0; 1627 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1628 count = 0; 1629 for (i=0; i<size; i++) { 1630 if (nprocs[2*i+1]) { 1631 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1632 } 1633 } 1634 ierr = PetscFree(starts);CHKERRQ(ierr); 1635 1636 base = owners[rank]; 1637 1638 /* wait on receives */ 1639 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1640 source = lens + nrecvs; 1641 count = nrecvs; slen = 0; 1642 while (count) { 1643 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1644 /* unpack receives into our local space */ 1645 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1646 source[imdex] = recv_status.MPI_SOURCE; 1647 lens[imdex] = n; 1648 slen += n; 1649 count--; 1650 } 1651 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1652 1653 /* move the data into the send scatter */ 1654 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1655 count = 0; 1656 for (i=0; i<nrecvs; i++) { 1657 values = rvalues + i*nmax; 1658 for (j=0; j<lens[i]; j++) { 1659 lrows[count++] = values[j] - base; 1660 } 1661 } 1662 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1663 ierr = PetscFree(lens);CHKERRQ(ierr); 1664 ierr = PetscFree(owner);CHKERRQ(ierr); 1665 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1666 1667 /* actually zap the local rows */ 1668 /* 1669 Zero the required rows. If the "diagonal block" of the matrix 1670 is square and the user wishes to set the diagonal we use separate 1671 code so that MatSetValues() is not called for each diagonal allocating 1672 new memory, thus calling lots of mallocs and slowing things down. 1673 1674 Contributed by: Matthew Knepley 1675 */ 1676 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1677 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0);CHKERRQ(ierr); 1678 if ((diag != 0.0) && (l->A->rmap.N == l->A->cmap.N)) { 1679 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag);CHKERRQ(ierr); 1680 } else if (diag != 0.0) { 1681 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1682 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1683 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1684 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1685 } 1686 for (i=0; i<slen; i++) { 1687 row = lrows[i] + rstart_bs; 1688 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1689 } 1690 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1691 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1692 } else { 1693 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1694 } 1695 1696 ierr = PetscFree(lrows);CHKERRQ(ierr); 1697 1698 /* wait on sends */ 1699 if (nsends) { 1700 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1701 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1702 ierr = PetscFree(send_status);CHKERRQ(ierr); 1703 } 1704 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1705 ierr = PetscFree(svalues);CHKERRQ(ierr); 1706 1707 PetscFunctionReturn(0); 1708 } 1709 1710 #undef __FUNCT__ 1711 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1712 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1713 { 1714 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1715 PetscErrorCode ierr; 1716 1717 PetscFunctionBegin; 1718 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1719 PetscFunctionReturn(0); 1720 } 1721 1722 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1723 1724 #undef __FUNCT__ 1725 #define __FUNCT__ "MatEqual_MPIBAIJ" 1726 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1727 { 1728 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1729 Mat a,b,c,d; 1730 PetscTruth flg; 1731 PetscErrorCode ierr; 1732 1733 PetscFunctionBegin; 1734 a = matA->A; b = matA->B; 1735 c = matB->A; d = matB->B; 1736 1737 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1738 if (flg) { 1739 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1740 } 1741 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1742 PetscFunctionReturn(0); 1743 } 1744 1745 #undef __FUNCT__ 1746 #define __FUNCT__ "MatCopy_MPIBAIJ" 1747 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1748 { 1749 PetscErrorCode ierr; 1750 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1751 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1752 1753 PetscFunctionBegin; 1754 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1755 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1756 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1757 } else { 1758 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1759 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1760 } 1761 PetscFunctionReturn(0); 1762 } 1763 1764 #undef __FUNCT__ 1765 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1766 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1767 { 1768 PetscErrorCode ierr; 1769 1770 PetscFunctionBegin; 1771 ierr = MatMPIBAIJSetPreallocation(A,PetscMax(A->rmap.bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1772 PetscFunctionReturn(0); 1773 } 1774 1775 #include "petscblaslapack.h" 1776 #undef __FUNCT__ 1777 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1778 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1779 { 1780 PetscErrorCode ierr; 1781 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1782 PetscBLASInt bnz,one=1; 1783 Mat_SeqBAIJ *x,*y; 1784 1785 PetscFunctionBegin; 1786 if (str == SAME_NONZERO_PATTERN) { 1787 PetscScalar alpha = a; 1788 x = (Mat_SeqBAIJ *)xx->A->data; 1789 y = (Mat_SeqBAIJ *)yy->A->data; 1790 bnz = PetscBLASIntCast(x->nz); 1791 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1792 x = (Mat_SeqBAIJ *)xx->B->data; 1793 y = (Mat_SeqBAIJ *)yy->B->data; 1794 bnz = PetscBLASIntCast(x->nz); 1795 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1796 } else { 1797 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1798 } 1799 PetscFunctionReturn(0); 1800 } 1801 1802 #undef __FUNCT__ 1803 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1804 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1805 { 1806 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1807 PetscErrorCode ierr; 1808 1809 PetscFunctionBegin; 1810 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1811 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1812 PetscFunctionReturn(0); 1813 } 1814 1815 #undef __FUNCT__ 1816 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1817 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 1818 { 1819 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1820 PetscErrorCode ierr; 1821 1822 PetscFunctionBegin; 1823 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1824 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1825 PetscFunctionReturn(0); 1826 } 1827 1828 /* -------------------------------------------------------------------*/ 1829 static struct _MatOps MatOps_Values = { 1830 MatSetValues_MPIBAIJ, 1831 MatGetRow_MPIBAIJ, 1832 MatRestoreRow_MPIBAIJ, 1833 MatMult_MPIBAIJ, 1834 /* 4*/ MatMultAdd_MPIBAIJ, 1835 MatMultTranspose_MPIBAIJ, 1836 MatMultTransposeAdd_MPIBAIJ, 1837 0, 1838 0, 1839 0, 1840 /*10*/ 0, 1841 0, 1842 0, 1843 0, 1844 MatTranspose_MPIBAIJ, 1845 /*15*/ MatGetInfo_MPIBAIJ, 1846 MatEqual_MPIBAIJ, 1847 MatGetDiagonal_MPIBAIJ, 1848 MatDiagonalScale_MPIBAIJ, 1849 MatNorm_MPIBAIJ, 1850 /*20*/ MatAssemblyBegin_MPIBAIJ, 1851 MatAssemblyEnd_MPIBAIJ, 1852 0, 1853 MatSetOption_MPIBAIJ, 1854 MatZeroEntries_MPIBAIJ, 1855 /*25*/ MatZeroRows_MPIBAIJ, 1856 0, 1857 0, 1858 0, 1859 0, 1860 /*30*/ MatSetUpPreallocation_MPIBAIJ, 1861 0, 1862 0, 1863 0, 1864 0, 1865 /*35*/ MatDuplicate_MPIBAIJ, 1866 0, 1867 0, 1868 0, 1869 0, 1870 /*40*/ MatAXPY_MPIBAIJ, 1871 MatGetSubMatrices_MPIBAIJ, 1872 MatIncreaseOverlap_MPIBAIJ, 1873 MatGetValues_MPIBAIJ, 1874 MatCopy_MPIBAIJ, 1875 /*45*/ 0, 1876 MatScale_MPIBAIJ, 1877 0, 1878 0, 1879 0, 1880 /*50*/ 0, 1881 0, 1882 0, 1883 0, 1884 0, 1885 /*55*/ 0, 1886 0, 1887 MatSetUnfactored_MPIBAIJ, 1888 0, 1889 MatSetValuesBlocked_MPIBAIJ, 1890 /*60*/ 0, 1891 MatDestroy_MPIBAIJ, 1892 MatView_MPIBAIJ, 1893 0, 1894 0, 1895 /*65*/ 0, 1896 0, 1897 0, 1898 0, 1899 0, 1900 /*70*/ MatGetRowMaxAbs_MPIBAIJ, 1901 0, 1902 0, 1903 0, 1904 0, 1905 /*75*/ 0, 1906 0, 1907 0, 1908 0, 1909 0, 1910 /*80*/ 0, 1911 0, 1912 0, 1913 0, 1914 MatLoad_MPIBAIJ, 1915 /*85*/ 0, 1916 0, 1917 0, 1918 0, 1919 0, 1920 /*90*/ 0, 1921 0, 1922 0, 1923 0, 1924 0, 1925 /*95*/ 0, 1926 0, 1927 0, 1928 0, 1929 0, 1930 /*100*/0, 1931 0, 1932 0, 1933 0, 1934 0, 1935 /*105*/0, 1936 MatRealPart_MPIBAIJ, 1937 MatImaginaryPart_MPIBAIJ}; 1938 1939 1940 EXTERN_C_BEGIN 1941 #undef __FUNCT__ 1942 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 1943 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1944 { 1945 PetscFunctionBegin; 1946 *a = ((Mat_MPIBAIJ *)A->data)->A; 1947 *iscopy = PETSC_FALSE; 1948 PetscFunctionReturn(0); 1949 } 1950 EXTERN_C_END 1951 1952 EXTERN_C_BEGIN 1953 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 1954 EXTERN_C_END 1955 1956 #undef __FUNCT__ 1957 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 1958 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 1959 { 1960 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)B->data; 1961 PetscInt m = B->rmap.n/bs,cstart = baij->cstartbs, cend = baij->cendbs,j,nnz,i,d; 1962 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart = baij->rstartbs,ii; 1963 const PetscInt *JJ; 1964 PetscScalar *values; 1965 PetscErrorCode ierr; 1966 1967 PetscFunctionBegin; 1968 #if defined(PETSC_OPT_g) 1969 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_RANGE,"Ii[0] must be 0 it is %D",Ii[0]); 1970 #endif 1971 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1972 o_nnz = d_nnz + m; 1973 1974 for (i=0; i<m; i++) { 1975 nnz = Ii[i+1]- Ii[i]; 1976 JJ = J + Ii[i]; 1977 nnz_max = PetscMax(nnz_max,nnz); 1978 #if defined(PETSC_OPT_g) 1979 if (nnz < 0) SETERRQ1(PETSC_ERR_ARG_RANGE,"Local row %D has a negative %D number of columns",i,nnz); 1980 #endif 1981 for (j=0; j<nnz; j++) { 1982 if (*JJ >= cstart) break; 1983 JJ++; 1984 } 1985 d = 0; 1986 for (; j<nnz; j++) { 1987 if (*JJ++ >= cend) break; 1988 d++; 1989 } 1990 d_nnz[i] = d; 1991 o_nnz[i] = nnz - d; 1992 } 1993 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1994 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1995 1996 if (v) values = (PetscScalar*)v; 1997 else { 1998 ierr = PetscMalloc(bs*bs*(nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 1999 ierr = PetscMemzero(values,bs*bs*nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2000 } 2001 2002 for (i=0; i<m; i++) { 2003 ii = i + rstart; 2004 nnz = Ii[i+1]- Ii[i]; 2005 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 2006 } 2007 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2008 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2009 2010 if (!v) { 2011 ierr = PetscFree(values);CHKERRQ(ierr); 2012 } 2013 PetscFunctionReturn(0); 2014 } 2015 2016 #undef __FUNCT__ 2017 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2018 /*@C 2019 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2020 (the default parallel PETSc format). 2021 2022 Collective on MPI_Comm 2023 2024 Input Parameters: 2025 + A - the matrix 2026 . i - the indices into j for the start of each local row (starts with zero) 2027 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2028 - v - optional values in the matrix 2029 2030 Level: developer 2031 2032 .keywords: matrix, aij, compressed row, sparse, parallel 2033 2034 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2035 @*/ 2036 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2037 { 2038 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2039 2040 PetscFunctionBegin; 2041 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2042 if (f) { 2043 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2044 } 2045 PetscFunctionReturn(0); 2046 } 2047 2048 EXTERN_C_BEGIN 2049 #undef __FUNCT__ 2050 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2051 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2052 { 2053 Mat_MPIBAIJ *b; 2054 PetscErrorCode ierr; 2055 PetscInt i; 2056 2057 PetscFunctionBegin; 2058 B->preallocated = PETSC_TRUE; 2059 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2060 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2061 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2062 2063 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2064 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2065 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2066 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2067 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2068 2069 B->rmap.bs = bs; 2070 B->cmap.bs = bs; 2071 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2072 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2073 2074 if (d_nnz) { 2075 for (i=0; i<B->rmap.n/bs; i++) { 2076 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]); 2077 } 2078 } 2079 if (o_nnz) { 2080 for (i=0; i<B->rmap.n/bs; i++) { 2081 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]); 2082 } 2083 } 2084 2085 b = (Mat_MPIBAIJ*)B->data; 2086 b->bs2 = bs*bs; 2087 b->mbs = B->rmap.n/bs; 2088 b->nbs = B->cmap.n/bs; 2089 b->Mbs = B->rmap.N/bs; 2090 b->Nbs = B->cmap.N/bs; 2091 2092 for (i=0; i<=b->size; i++) { 2093 b->rangebs[i] = B->rmap.range[i]/bs; 2094 } 2095 b->rstartbs = B->rmap.rstart/bs; 2096 b->rendbs = B->rmap.rend/bs; 2097 b->cstartbs = B->cmap.rstart/bs; 2098 b->cendbs = B->cmap.rend/bs; 2099 2100 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2101 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2102 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2103 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2104 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2105 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2106 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2107 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2108 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2109 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2110 2111 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 2112 2113 PetscFunctionReturn(0); 2114 } 2115 EXTERN_C_END 2116 2117 EXTERN_C_BEGIN 2118 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2119 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2120 EXTERN_C_END 2121 2122 /*MC 2123 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2124 2125 Options Database Keys: 2126 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2127 . -mat_block_size <bs> - set the blocksize used to store the matrix 2128 - -mat_use_hash_table <fact> 2129 2130 Level: beginner 2131 2132 .seealso: MatCreateMPIBAIJ 2133 M*/ 2134 2135 EXTERN_C_BEGIN 2136 #undef __FUNCT__ 2137 #define __FUNCT__ "MatCreate_MPIBAIJ" 2138 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2139 { 2140 Mat_MPIBAIJ *b; 2141 PetscErrorCode ierr; 2142 PetscTruth flg; 2143 2144 PetscFunctionBegin; 2145 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2146 B->data = (void*)b; 2147 2148 2149 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2150 B->mapping = 0; 2151 B->assembled = PETSC_FALSE; 2152 2153 B->insertmode = NOT_SET_VALUES; 2154 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 2155 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 2156 2157 /* build local table of row and column ownerships */ 2158 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2159 2160 /* build cache for off array entries formed */ 2161 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 2162 b->donotstash = PETSC_FALSE; 2163 b->colmap = PETSC_NULL; 2164 b->garray = PETSC_NULL; 2165 b->roworiented = PETSC_TRUE; 2166 2167 /* stuff used in block assembly */ 2168 b->barray = 0; 2169 2170 /* stuff used for matrix vector multiply */ 2171 b->lvec = 0; 2172 b->Mvctx = 0; 2173 2174 /* stuff for MatGetRow() */ 2175 b->rowindices = 0; 2176 b->rowvalues = 0; 2177 b->getrowactive = PETSC_FALSE; 2178 2179 /* hash table stuff */ 2180 b->ht = 0; 2181 b->hd = 0; 2182 b->ht_size = 0; 2183 b->ht_flag = PETSC_FALSE; 2184 b->ht_fact = 0; 2185 b->ht_total_ct = 0; 2186 b->ht_insert_ct = 0; 2187 2188 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 2189 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 2190 if (flg) { 2191 PetscReal fact = 1.39; 2192 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 2193 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 2194 if (fact <= 1.0) fact = 1.39; 2195 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2196 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 2197 } 2198 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2199 2200 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2201 "MatStoreValues_MPIBAIJ", 2202 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2203 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2204 "MatRetrieveValues_MPIBAIJ", 2205 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2206 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2207 "MatGetDiagonalBlock_MPIBAIJ", 2208 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2209 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2210 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2211 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2212 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2213 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 2214 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2215 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2216 "MatDiagonalScaleLocal_MPIBAIJ", 2217 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2218 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2219 "MatSetHashTableFactor_MPIBAIJ", 2220 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2221 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 2222 PetscFunctionReturn(0); 2223 } 2224 EXTERN_C_END 2225 2226 /*MC 2227 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2228 2229 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2230 and MATMPIBAIJ otherwise. 2231 2232 Options Database Keys: 2233 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2234 2235 Level: beginner 2236 2237 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2238 M*/ 2239 2240 EXTERN_C_BEGIN 2241 #undef __FUNCT__ 2242 #define __FUNCT__ "MatCreate_BAIJ" 2243 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2244 { 2245 PetscErrorCode ierr; 2246 PetscMPIInt size; 2247 2248 PetscFunctionBegin; 2249 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2250 if (size == 1) { 2251 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2252 } else { 2253 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2254 } 2255 PetscFunctionReturn(0); 2256 } 2257 EXTERN_C_END 2258 2259 #undef __FUNCT__ 2260 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2261 /*@C 2262 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2263 (block compressed row). For good matrix assembly performance 2264 the user should preallocate the matrix storage by setting the parameters 2265 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2266 performance can be increased by more than a factor of 50. 2267 2268 Collective on Mat 2269 2270 Input Parameters: 2271 + A - the matrix 2272 . bs - size of blockk 2273 . d_nz - number of block nonzeros per block row in diagonal portion of local 2274 submatrix (same for all local rows) 2275 . d_nnz - array containing the number of block nonzeros in the various block rows 2276 of the in diagonal portion of the local (possibly different for each block 2277 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2278 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2279 submatrix (same for all local rows). 2280 - o_nnz - array containing the number of nonzeros in the various block rows of the 2281 off-diagonal portion of the local submatrix (possibly different for 2282 each block row) or PETSC_NULL. 2283 2284 If the *_nnz parameter is given then the *_nz parameter is ignored 2285 2286 Options Database Keys: 2287 + -mat_block_size - size of the blocks to use 2288 - -mat_use_hash_table <fact> 2289 2290 Notes: 2291 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2292 than it must be used on all processors that share the object for that argument. 2293 2294 Storage Information: 2295 For a square global matrix we define each processor's diagonal portion 2296 to be its local rows and the corresponding columns (a square submatrix); 2297 each processor's off-diagonal portion encompasses the remainder of the 2298 local matrix (a rectangular submatrix). 2299 2300 The user can specify preallocated storage for the diagonal part of 2301 the local submatrix with either d_nz or d_nnz (not both). Set 2302 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2303 memory allocation. Likewise, specify preallocated storage for the 2304 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2305 2306 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2307 the figure below we depict these three local rows and all columns (0-11). 2308 2309 .vb 2310 0 1 2 3 4 5 6 7 8 9 10 11 2311 ------------------- 2312 row 3 | o o o d d d o o o o o o 2313 row 4 | o o o d d d o o o o o o 2314 row 5 | o o o d d d o o o o o o 2315 ------------------- 2316 .ve 2317 2318 Thus, any entries in the d locations are stored in the d (diagonal) 2319 submatrix, and any entries in the o locations are stored in the 2320 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2321 stored simply in the MATSEQBAIJ format for compressed row storage. 2322 2323 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2324 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2325 In general, for PDE problems in which most nonzeros are near the diagonal, 2326 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2327 or you will get TERRIBLE performance; see the users' manual chapter on 2328 matrices. 2329 2330 You can call MatGetInfo() to get information on how effective the preallocation was; 2331 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2332 You can also run with the option -info and look for messages with the string 2333 malloc in them to see if additional memory allocation was needed. 2334 2335 Level: intermediate 2336 2337 .keywords: matrix, block, aij, compressed row, sparse, parallel 2338 2339 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2340 @*/ 2341 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2342 { 2343 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2344 2345 PetscFunctionBegin; 2346 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2347 if (f) { 2348 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2349 } 2350 PetscFunctionReturn(0); 2351 } 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatCreateMPIBAIJ" 2355 /*@C 2356 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2357 (block compressed row). For good matrix assembly performance 2358 the user should preallocate the matrix storage by setting the parameters 2359 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2360 performance can be increased by more than a factor of 50. 2361 2362 Collective on MPI_Comm 2363 2364 Input Parameters: 2365 + comm - MPI communicator 2366 . bs - size of blockk 2367 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2368 This value should be the same as the local size used in creating the 2369 y vector for the matrix-vector product y = Ax. 2370 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2371 This value should be the same as the local size used in creating the 2372 x vector for the matrix-vector product y = Ax. 2373 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2374 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2375 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2376 submatrix (same for all local rows) 2377 . d_nnz - array containing the number of nonzero blocks in the various block rows 2378 of the in diagonal portion of the local (possibly different for each block 2379 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2380 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2381 submatrix (same for all local rows). 2382 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2383 off-diagonal portion of the local submatrix (possibly different for 2384 each block row) or PETSC_NULL. 2385 2386 Output Parameter: 2387 . A - the matrix 2388 2389 Options Database Keys: 2390 + -mat_block_size - size of the blocks to use 2391 - -mat_use_hash_table <fact> 2392 2393 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2394 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 2395 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 2396 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2397 2398 Notes: 2399 If the *_nnz parameter is given then the *_nz parameter is ignored 2400 2401 A nonzero block is any block that as 1 or more nonzeros in it 2402 2403 The user MUST specify either the local or global matrix dimensions 2404 (possibly both). 2405 2406 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2407 than it must be used on all processors that share the object for that argument. 2408 2409 Storage Information: 2410 For a square global matrix we define each processor's diagonal portion 2411 to be its local rows and the corresponding columns (a square submatrix); 2412 each processor's off-diagonal portion encompasses the remainder of the 2413 local matrix (a rectangular submatrix). 2414 2415 The user can specify preallocated storage for the diagonal part of 2416 the local submatrix with either d_nz or d_nnz (not both). Set 2417 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2418 memory allocation. Likewise, specify preallocated storage for the 2419 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2420 2421 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2422 the figure below we depict these three local rows and all columns (0-11). 2423 2424 .vb 2425 0 1 2 3 4 5 6 7 8 9 10 11 2426 ------------------- 2427 row 3 | o o o d d d o o o o o o 2428 row 4 | o o o d d d o o o o o o 2429 row 5 | o o o d d d o o o o o o 2430 ------------------- 2431 .ve 2432 2433 Thus, any entries in the d locations are stored in the d (diagonal) 2434 submatrix, and any entries in the o locations are stored in the 2435 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2436 stored simply in the MATSEQBAIJ format for compressed row storage. 2437 2438 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2439 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2440 In general, for PDE problems in which most nonzeros are near the diagonal, 2441 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2442 or you will get TERRIBLE performance; see the users' manual chapter on 2443 matrices. 2444 2445 Level: intermediate 2446 2447 .keywords: matrix, block, aij, compressed row, sparse, parallel 2448 2449 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2450 @*/ 2451 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) 2452 { 2453 PetscErrorCode ierr; 2454 PetscMPIInt size; 2455 2456 PetscFunctionBegin; 2457 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2458 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2459 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2460 if (size > 1) { 2461 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2462 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2463 } else { 2464 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2465 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2466 } 2467 PetscFunctionReturn(0); 2468 } 2469 2470 #undef __FUNCT__ 2471 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2472 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2473 { 2474 Mat mat; 2475 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2476 PetscErrorCode ierr; 2477 PetscInt len=0; 2478 2479 PetscFunctionBegin; 2480 *newmat = 0; 2481 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2482 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2483 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2484 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2485 2486 mat->factor = matin->factor; 2487 mat->preallocated = PETSC_TRUE; 2488 mat->assembled = PETSC_TRUE; 2489 mat->insertmode = NOT_SET_VALUES; 2490 2491 a = (Mat_MPIBAIJ*)mat->data; 2492 mat->rmap.bs = matin->rmap.bs; 2493 a->bs2 = oldmat->bs2; 2494 a->mbs = oldmat->mbs; 2495 a->nbs = oldmat->nbs; 2496 a->Mbs = oldmat->Mbs; 2497 a->Nbs = oldmat->Nbs; 2498 2499 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2500 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2501 2502 a->size = oldmat->size; 2503 a->rank = oldmat->rank; 2504 a->donotstash = oldmat->donotstash; 2505 a->roworiented = oldmat->roworiented; 2506 a->rowindices = 0; 2507 a->rowvalues = 0; 2508 a->getrowactive = PETSC_FALSE; 2509 a->barray = 0; 2510 a->rstartbs = oldmat->rstartbs; 2511 a->rendbs = oldmat->rendbs; 2512 a->cstartbs = oldmat->cstartbs; 2513 a->cendbs = oldmat->cendbs; 2514 2515 /* hash table stuff */ 2516 a->ht = 0; 2517 a->hd = 0; 2518 a->ht_size = 0; 2519 a->ht_flag = oldmat->ht_flag; 2520 a->ht_fact = oldmat->ht_fact; 2521 a->ht_total_ct = 0; 2522 a->ht_insert_ct = 0; 2523 2524 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 2525 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2526 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap.bs,&mat->bstash);CHKERRQ(ierr); 2527 if (oldmat->colmap) { 2528 #if defined (PETSC_USE_CTABLE) 2529 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2530 #else 2531 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2532 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2533 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2534 #endif 2535 } else a->colmap = 0; 2536 2537 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2538 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2539 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2540 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2541 } else a->garray = 0; 2542 2543 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2544 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2545 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2546 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2547 2548 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2549 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2550 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2551 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2552 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2553 *newmat = mat; 2554 2555 PetscFunctionReturn(0); 2556 } 2557 2558 #include "petscsys.h" 2559 2560 #undef __FUNCT__ 2561 #define __FUNCT__ "MatLoad_MPIBAIJ" 2562 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2563 { 2564 Mat A; 2565 PetscErrorCode ierr; 2566 int fd; 2567 PetscInt i,nz,j,rstart,rend; 2568 PetscScalar *vals,*buf; 2569 MPI_Comm comm = ((PetscObject)viewer)->comm; 2570 MPI_Status status; 2571 PetscMPIInt rank,size,maxnz; 2572 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2573 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 2574 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2575 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2576 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 2577 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2578 2579 PetscFunctionBegin; 2580 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 2581 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2582 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2583 2584 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 if (!rank) { 2587 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2588 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2589 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2590 } 2591 2592 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2593 M = header[1]; N = header[2]; 2594 2595 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2596 2597 /* 2598 This code adds extra rows to make sure the number of rows is 2599 divisible by the blocksize 2600 */ 2601 Mbs = M/bs; 2602 extra_rows = bs - M + bs*Mbs; 2603 if (extra_rows == bs) extra_rows = 0; 2604 else Mbs++; 2605 if (extra_rows && !rank) { 2606 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2607 } 2608 2609 /* determine ownership of all rows */ 2610 mbs = Mbs/size + ((Mbs % size) > rank); 2611 m = mbs*bs; 2612 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2613 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2614 2615 /* process 0 needs enough room for process with most rows */ 2616 if (!rank) { 2617 mmax = rowners[1]; 2618 for (i=2; i<size; i++) { 2619 mmax = PetscMax(mmax,rowners[i]); 2620 } 2621 mmax*=bs; 2622 } else mmax = m; 2623 2624 rowners[0] = 0; 2625 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2626 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2627 rstart = rowners[rank]; 2628 rend = rowners[rank+1]; 2629 2630 /* distribute row lengths to all processors */ 2631 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2632 if (!rank) { 2633 mend = m; 2634 if (size == 1) mend = mend - extra_rows; 2635 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2636 for (j=mend; j<m; j++) locrowlens[j] = 1; 2637 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2638 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2639 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2640 for (j=0; j<m; j++) { 2641 procsnz[0] += locrowlens[j]; 2642 } 2643 for (i=1; i<size; i++) { 2644 mend = browners[i+1] - browners[i]; 2645 if (i == size-1) mend = mend - extra_rows; 2646 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2647 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2648 /* calculate the number of nonzeros on each processor */ 2649 for (j=0; j<browners[i+1]-browners[i]; j++) { 2650 procsnz[i] += rowlengths[j]; 2651 } 2652 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2653 } 2654 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2655 } else { 2656 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2657 } 2658 2659 if (!rank) { 2660 /* determine max buffer needed and allocate it */ 2661 maxnz = procsnz[0]; 2662 for (i=1; i<size; i++) { 2663 maxnz = PetscMax(maxnz,procsnz[i]); 2664 } 2665 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2666 2667 /* read in my part of the matrix column indices */ 2668 nz = procsnz[0]; 2669 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2670 mycols = ibuf; 2671 if (size == 1) nz -= extra_rows; 2672 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2673 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2674 2675 /* read in every ones (except the last) and ship off */ 2676 for (i=1; i<size-1; i++) { 2677 nz = procsnz[i]; 2678 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2679 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2680 } 2681 /* read in the stuff for the last proc */ 2682 if (size != 1) { 2683 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2684 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2685 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2686 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2687 } 2688 ierr = PetscFree(cols);CHKERRQ(ierr); 2689 } else { 2690 /* determine buffer space needed for message */ 2691 nz = 0; 2692 for (i=0; i<m; i++) { 2693 nz += locrowlens[i]; 2694 } 2695 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2696 mycols = ibuf; 2697 /* receive message of column indices*/ 2698 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2699 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2700 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2701 } 2702 2703 /* loop over local rows, determining number of off diagonal entries */ 2704 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2705 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2706 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2707 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2708 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2709 rowcount = 0; nzcount = 0; 2710 for (i=0; i<mbs; i++) { 2711 dcount = 0; 2712 odcount = 0; 2713 for (j=0; j<bs; j++) { 2714 kmax = locrowlens[rowcount]; 2715 for (k=0; k<kmax; k++) { 2716 tmp = mycols[nzcount++]/bs; 2717 if (!mask[tmp]) { 2718 mask[tmp] = 1; 2719 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2720 else masked1[dcount++] = tmp; 2721 } 2722 } 2723 rowcount++; 2724 } 2725 2726 dlens[i] = dcount; 2727 odlens[i] = odcount; 2728 2729 /* zero out the mask elements we set */ 2730 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2731 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2732 } 2733 2734 /* create our matrix */ 2735 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2736 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2737 ierr = MatSetType(A,type);CHKERRQ(ierr) 2738 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2739 2740 if (!rank) { 2741 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2742 /* read in my part of the matrix numerical values */ 2743 nz = procsnz[0]; 2744 vals = buf; 2745 mycols = ibuf; 2746 if (size == 1) nz -= extra_rows; 2747 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2748 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2749 2750 /* insert into matrix */ 2751 jj = rstart*bs; 2752 for (i=0; i<m; i++) { 2753 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2754 mycols += locrowlens[i]; 2755 vals += locrowlens[i]; 2756 jj++; 2757 } 2758 /* read in other processors (except the last one) and ship out */ 2759 for (i=1; i<size-1; i++) { 2760 nz = procsnz[i]; 2761 vals = buf; 2762 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2763 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2764 } 2765 /* the last proc */ 2766 if (size != 1){ 2767 nz = procsnz[i] - extra_rows; 2768 vals = buf; 2769 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2770 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2771 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2772 } 2773 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2774 } else { 2775 /* receive numeric values */ 2776 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2777 2778 /* receive message of values*/ 2779 vals = buf; 2780 mycols = ibuf; 2781 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2782 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2783 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2784 2785 /* insert into matrix */ 2786 jj = rstart*bs; 2787 for (i=0; i<m; i++) { 2788 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2789 mycols += locrowlens[i]; 2790 vals += locrowlens[i]; 2791 jj++; 2792 } 2793 } 2794 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2795 ierr = PetscFree(buf);CHKERRQ(ierr); 2796 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2797 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2798 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2799 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2800 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2801 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2802 2803 *newmat = A; 2804 PetscFunctionReturn(0); 2805 } 2806 2807 #undef __FUNCT__ 2808 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2809 /*@ 2810 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2811 2812 Input Parameters: 2813 . mat - the matrix 2814 . fact - factor 2815 2816 Collective on Mat 2817 2818 Level: advanced 2819 2820 Notes: 2821 This can also be set by the command line option: -mat_use_hash_table <fact> 2822 2823 .keywords: matrix, hashtable, factor, HT 2824 2825 .seealso: MatSetOption() 2826 @*/ 2827 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2828 { 2829 PetscErrorCode ierr,(*f)(Mat,PetscReal); 2830 2831 PetscFunctionBegin; 2832 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 2833 if (f) { 2834 ierr = (*f)(mat,fact);CHKERRQ(ierr); 2835 } 2836 PetscFunctionReturn(0); 2837 } 2838 2839 EXTERN_C_BEGIN 2840 #undef __FUNCT__ 2841 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 2842 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 2843 { 2844 Mat_MPIBAIJ *baij; 2845 2846 PetscFunctionBegin; 2847 baij = (Mat_MPIBAIJ*)mat->data; 2848 baij->ht_fact = fact; 2849 PetscFunctionReturn(0); 2850 } 2851 EXTERN_C_END 2852 2853 #undef __FUNCT__ 2854 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2855 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 2856 { 2857 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2858 PetscFunctionBegin; 2859 *Ad = a->A; 2860 *Ao = a->B; 2861 *colmap = a->garray; 2862 PetscFunctionReturn(0); 2863 } 2864 2865 /* 2866 Special version for direct calls from Fortran (to eliminate two function call overheads 2867 */ 2868 #if defined(PETSC_HAVE_FORTRAN_CAPS) 2869 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 2870 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 2871 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 2872 #endif 2873 2874 #undef __FUNCT__ 2875 #define __FUNCT__ "matmpibiajsetvaluesblocked" 2876 /*@C 2877 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 2878 2879 Collective on Mat 2880 2881 Input Parameters: 2882 + mat - the matrix 2883 . min - number of input rows 2884 . im - input rows 2885 . nin - number of input columns 2886 . in - input columns 2887 . v - numerical values input 2888 - addvin - INSERT_VALUES or ADD_VALUES 2889 2890 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 2891 2892 Level: advanced 2893 2894 .seealso: MatSetValuesBlocked() 2895 @*/ 2896 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 2897 { 2898 /* convert input arguments to C version */ 2899 Mat mat = *matin; 2900 PetscInt m = *min, n = *nin; 2901 InsertMode addv = *addvin; 2902 2903 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2904 const MatScalar *value; 2905 MatScalar *barray=baij->barray; 2906 PetscTruth roworiented = baij->roworiented; 2907 PetscErrorCode ierr; 2908 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 2909 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 2910 PetscInt cend=baij->cendbs,bs=mat->rmap.bs,bs2=baij->bs2; 2911 2912 PetscFunctionBegin; 2913 /* tasks normally handled by MatSetValuesBlocked() */ 2914 if (mat->insertmode == NOT_SET_VALUES) { 2915 mat->insertmode = addv; 2916 } 2917 #if defined(PETSC_USE_DEBUG) 2918 else if (mat->insertmode != addv) { 2919 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 2920 } 2921 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2922 #endif 2923 if (mat->assembled) { 2924 mat->was_assembled = PETSC_TRUE; 2925 mat->assembled = PETSC_FALSE; 2926 } 2927 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 2928 2929 2930 if(!barray) { 2931 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 2932 baij->barray = barray; 2933 } 2934 2935 if (roworiented) { 2936 stepval = (n-1)*bs; 2937 } else { 2938 stepval = (m-1)*bs; 2939 } 2940 for (i=0; i<m; i++) { 2941 if (im[i] < 0) continue; 2942 #if defined(PETSC_USE_DEBUG) 2943 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 2944 #endif 2945 if (im[i] >= rstart && im[i] < rend) { 2946 row = im[i] - rstart; 2947 for (j=0; j<n; j++) { 2948 /* If NumCol = 1 then a copy is not required */ 2949 if ((roworiented) && (n == 1)) { 2950 barray = (MatScalar*)v + i*bs2; 2951 } else if((!roworiented) && (m == 1)) { 2952 barray = (MatScalar*)v + j*bs2; 2953 } else { /* Here a copy is required */ 2954 if (roworiented) { 2955 value = v + i*(stepval+bs)*bs + j*bs; 2956 } else { 2957 value = v + j*(stepval+bs)*bs + i*bs; 2958 } 2959 for (ii=0; ii<bs; ii++,value+=stepval) { 2960 for (jj=0; jj<bs; jj++) { 2961 *barray++ = *value++; 2962 } 2963 } 2964 barray -=bs2; 2965 } 2966 2967 if (in[j] >= cstart && in[j] < cend){ 2968 col = in[j] - cstart; 2969 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 2970 } 2971 else if (in[j] < 0) continue; 2972 #if defined(PETSC_USE_DEBUG) 2973 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 2974 #endif 2975 else { 2976 if (mat->was_assembled) { 2977 if (!baij->colmap) { 2978 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2979 } 2980 2981 #if defined(PETSC_USE_DEBUG) 2982 #if defined (PETSC_USE_CTABLE) 2983 { PetscInt data; 2984 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 2985 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 2986 } 2987 #else 2988 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 2989 #endif 2990 #endif 2991 #if defined (PETSC_USE_CTABLE) 2992 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 2993 col = (col - 1)/bs; 2994 #else 2995 col = (baij->colmap[in[j]] - 1)/bs; 2996 #endif 2997 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 2998 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 2999 col = in[j]; 3000 } 3001 } 3002 else col = in[j]; 3003 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3004 } 3005 } 3006 } else { 3007 if (!baij->donotstash) { 3008 if (roworiented) { 3009 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3010 } else { 3011 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3012 } 3013 } 3014 } 3015 } 3016 3017 /* task normally handled by MatSetValuesBlocked() */ 3018 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3019 PetscFunctionReturn(0); 3020 } 3021