1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "mpisbaij.h" 5 #include "src/mat/impls/sbaij/seq/sbaij.h" 6 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 8 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat); 10 EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 11 EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 13 EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 14 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 16 EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 18 EXTERN PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 19 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 20 EXTERN PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]); 21 EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 EXTERN_C_BEGIN 24 #undef __FUNCT__ 25 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 26 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPISBAIJ(Mat mat) 27 { 28 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 29 PetscErrorCode ierr; 30 31 PetscFunctionBegin; 32 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 33 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 34 PetscFunctionReturn(0); 35 } 36 EXTERN_C_END 37 38 EXTERN_C_BEGIN 39 #undef __FUNCT__ 40 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 41 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPISBAIJ(Mat mat) 42 { 43 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 44 PetscErrorCode ierr; 45 46 PetscFunctionBegin; 47 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 48 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 49 PetscFunctionReturn(0); 50 } 51 EXTERN_C_END 52 53 54 #define CHUNKSIZE 10 55 56 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 57 { \ 58 \ 59 brow = row/bs; \ 60 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 61 rmax = aimax[brow]; nrow = ailen[brow]; \ 62 bcol = col/bs; \ 63 ridx = row % bs; cidx = col % bs; \ 64 low = 0; high = nrow; \ 65 while (high-low > 3) { \ 66 t = (low+high)/2; \ 67 if (rp[t] > bcol) high = t; \ 68 else low = t; \ 69 } \ 70 for (_i=low; _i<high; _i++) { \ 71 if (rp[_i] > bcol) break; \ 72 if (rp[_i] == bcol) { \ 73 bap = ap + bs2*_i + bs*cidx + ridx; \ 74 if (addv == ADD_VALUES) *bap += value; \ 75 else *bap = value; \ 76 goto a_noinsert; \ 77 } \ 78 } \ 79 if (a->nonew == 1) goto a_noinsert; \ 80 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 81 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 82 N = nrow++ - 1; \ 83 /* shift up all the later entries in this row */ \ 84 for (ii=N; ii>=_i; ii--) { \ 85 rp[ii+1] = rp[ii]; \ 86 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 87 } \ 88 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 89 rp[_i] = bcol; \ 90 ap[bs2*_i + bs*cidx + ridx] = value; \ 91 a_noinsert:; \ 92 ailen[brow] = nrow; \ 93 } 94 95 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 96 { \ 97 brow = row/bs; \ 98 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 99 rmax = bimax[brow]; nrow = bilen[brow]; \ 100 bcol = col/bs; \ 101 ridx = row % bs; cidx = col % bs; \ 102 low = 0; high = nrow; \ 103 while (high-low > 3) { \ 104 t = (low+high)/2; \ 105 if (rp[t] > bcol) high = t; \ 106 else low = t; \ 107 } \ 108 for (_i=low; _i<high; _i++) { \ 109 if (rp[_i] > bcol) break; \ 110 if (rp[_i] == bcol) { \ 111 bap = ap + bs2*_i + bs*cidx + ridx; \ 112 if (addv == ADD_VALUES) *bap += value; \ 113 else *bap = value; \ 114 goto b_noinsert; \ 115 } \ 116 } \ 117 if (b->nonew == 1) goto b_noinsert; \ 118 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 119 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 120 N = nrow++ - 1; \ 121 /* shift up all the later entries in this row */ \ 122 for (ii=N; ii>=_i; ii--) { \ 123 rp[ii+1] = rp[ii]; \ 124 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 125 } \ 126 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 127 rp[_i] = bcol; \ 128 ap[bs2*_i + bs*cidx + ridx] = value; \ 129 b_noinsert:; \ 130 bilen[brow] = nrow; \ 131 } 132 133 /* Only add/insert a(i,j) with i<=j (blocks). 134 Any a(i,j) with i>j input by user is ingored. 135 */ 136 #undef __FUNCT__ 137 #define __FUNCT__ "MatSetValues_MPISBAIJ" 138 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 139 { 140 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 141 MatScalar value; 142 PetscTruth roworiented = baij->roworiented; 143 PetscErrorCode ierr; 144 PetscInt i,j,row,col; 145 PetscInt rstart_orig=mat->rmap->rstart; 146 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 147 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 148 149 /* Some Variables required in the macro */ 150 Mat A = baij->A; 151 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 152 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 153 MatScalar *aa=a->a; 154 155 Mat B = baij->B; 156 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 157 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 158 MatScalar *ba=b->a; 159 160 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 161 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 162 MatScalar *ap,*bap; 163 164 /* for stash */ 165 PetscInt n_loc, *in_loc = PETSC_NULL; 166 MatScalar *v_loc = PETSC_NULL; 167 168 PetscFunctionBegin; 169 170 if (!baij->donotstash){ 171 if (n > baij->n_loc) { 172 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 173 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 174 ierr = PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);CHKERRQ(ierr); 175 ierr = PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);CHKERRQ(ierr); 176 baij->n_loc = n; 177 } 178 in_loc = baij->in_loc; 179 v_loc = baij->v_loc; 180 } 181 182 for (i=0; i<m; i++) { 183 if (im[i] < 0) continue; 184 #if defined(PETSC_USE_DEBUG) 185 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 186 #endif 187 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 188 row = im[i] - rstart_orig; /* local row index */ 189 for (j=0; j<n; j++) { 190 if (im[i]/bs > in[j]/bs){ 191 if (a->ignore_ltriangular){ 192 continue; /* ignore lower triangular blocks */ 193 } else { 194 SETERRQ(PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 195 } 196 } 197 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 198 col = in[j] - cstart_orig; /* local col index */ 199 brow = row/bs; bcol = col/bs; 200 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 201 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 202 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 203 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 204 } else if (in[j] < 0) continue; 205 #if defined(PETSC_USE_DEBUG) 206 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);} 207 #endif 208 else { /* off-diag entry (B) */ 209 if (mat->was_assembled) { 210 if (!baij->colmap) { 211 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 212 } 213 #if defined (PETSC_USE_CTABLE) 214 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 215 col = col - 1; 216 #else 217 col = baij->colmap[in[j]/bs] - 1; 218 #endif 219 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 220 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 221 col = in[j]; 222 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 223 B = baij->B; 224 b = (Mat_SeqBAIJ*)(B)->data; 225 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 226 ba=b->a; 227 } else col += in[j]%bs; 228 } else col = in[j]; 229 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 230 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 231 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 232 } 233 } 234 } else { /* off processor entry */ 235 if (!baij->donotstash) { 236 n_loc = 0; 237 for (j=0; j<n; j++){ 238 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 239 in_loc[n_loc] = in[j]; 240 if (roworiented) { 241 v_loc[n_loc] = v[i*n+j]; 242 } else { 243 v_loc[n_loc] = v[j*m+i]; 244 } 245 n_loc++; 246 } 247 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 248 } 249 } 250 } 251 PetscFunctionReturn(0); 252 } 253 254 #undef __FUNCT__ 255 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 256 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 257 { 258 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 259 const MatScalar *value; 260 MatScalar *barray=baij->barray; 261 PetscTruth roworiented = baij->roworiented; 262 PetscErrorCode ierr; 263 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 264 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 265 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 266 267 PetscFunctionBegin; 268 if(!barray) { 269 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 270 baij->barray = barray; 271 } 272 273 if (roworiented) { 274 stepval = (n-1)*bs; 275 } else { 276 stepval = (m-1)*bs; 277 } 278 for (i=0; i<m; i++) { 279 if (im[i] < 0) continue; 280 #if defined(PETSC_USE_DEBUG) 281 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 282 #endif 283 if (im[i] >= rstart && im[i] < rend) { 284 row = im[i] - rstart; 285 for (j=0; j<n; j++) { 286 /* If NumCol = 1 then a copy is not required */ 287 if ((roworiented) && (n == 1)) { 288 barray = (MatScalar*) v + i*bs2; 289 } else if((!roworiented) && (m == 1)) { 290 barray = (MatScalar*) v + j*bs2; 291 } else { /* Here a copy is required */ 292 if (roworiented) { 293 value = v + i*(stepval+bs)*bs + j*bs; 294 } else { 295 value = v + j*(stepval+bs)*bs + i*bs; 296 } 297 for (ii=0; ii<bs; ii++,value+=stepval) { 298 for (jj=0; jj<bs; jj++) { 299 *barray++ = *value++; 300 } 301 } 302 barray -=bs2; 303 } 304 305 if (in[j] >= cstart && in[j] < cend){ 306 col = in[j] - cstart; 307 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 308 } 309 else if (in[j] < 0) continue; 310 #if defined(PETSC_USE_DEBUG) 311 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 312 #endif 313 else { 314 if (mat->was_assembled) { 315 if (!baij->colmap) { 316 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 317 } 318 319 #if defined(PETSC_USE_DEBUG) 320 #if defined (PETSC_USE_CTABLE) 321 { PetscInt data; 322 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 323 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 324 } 325 #else 326 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 327 #endif 328 #endif 329 #if defined (PETSC_USE_CTABLE) 330 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 331 col = (col - 1)/bs; 332 #else 333 col = (baij->colmap[in[j]] - 1)/bs; 334 #endif 335 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 336 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 337 col = in[j]; 338 } 339 } 340 else col = in[j]; 341 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 342 } 343 } 344 } else { 345 if (!baij->donotstash) { 346 if (roworiented) { 347 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 348 } else { 349 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 350 } 351 } 352 } 353 } 354 PetscFunctionReturn(0); 355 } 356 357 #undef __FUNCT__ 358 #define __FUNCT__ "MatGetValues_MPISBAIJ" 359 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 360 { 361 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 362 PetscErrorCode ierr; 363 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 364 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 365 366 PetscFunctionBegin; 367 for (i=0; i<m; i++) { 368 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 369 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 370 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 371 row = idxm[i] - bsrstart; 372 for (j=0; j<n; j++) { 373 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 374 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 375 if (idxn[j] >= bscstart && idxn[j] < bscend){ 376 col = idxn[j] - bscstart; 377 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 378 } else { 379 if (!baij->colmap) { 380 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 381 } 382 #if defined (PETSC_USE_CTABLE) 383 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 384 data --; 385 #else 386 data = baij->colmap[idxn[j]/bs]-1; 387 #endif 388 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 389 else { 390 col = data + idxn[j]%bs; 391 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 392 } 393 } 394 } 395 } else { 396 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 397 } 398 } 399 PetscFunctionReturn(0); 400 } 401 402 #undef __FUNCT__ 403 #define __FUNCT__ "MatNorm_MPISBAIJ" 404 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 405 { 406 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 407 PetscErrorCode ierr; 408 PetscReal sum[2],*lnorm2; 409 410 PetscFunctionBegin; 411 if (baij->size == 1) { 412 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 413 } else { 414 if (type == NORM_FROBENIUS) { 415 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 416 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 417 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 418 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 419 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 420 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 421 *norm = sqrt(sum[0] + 2*sum[1]); 422 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 423 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 424 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 425 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 426 PetscReal *rsum,*rsum2,vabs; 427 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 428 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 429 MatScalar *v; 430 431 ierr = PetscMalloc((2*mat->cmap->N+1)*sizeof(PetscReal),&rsum);CHKERRQ(ierr); 432 rsum2 = rsum + mat->cmap->N; 433 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 434 /* Amat */ 435 v = amat->a; jj = amat->j; 436 for (brow=0; brow<mbs; brow++) { 437 grow = bs*(rstart + brow); 438 nz = amat->i[brow+1] - amat->i[brow]; 439 for (bcol=0; bcol<nz; bcol++){ 440 gcol = bs*(rstart + *jj); jj++; 441 for (col=0; col<bs; col++){ 442 for (row=0; row<bs; row++){ 443 vabs = PetscAbsScalar(*v); v++; 444 rsum[gcol+col] += vabs; 445 /* non-diagonal block */ 446 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 447 } 448 } 449 } 450 } 451 /* Bmat */ 452 v = bmat->a; jj = bmat->j; 453 for (brow=0; brow<mbs; brow++) { 454 grow = bs*(rstart + brow); 455 nz = bmat->i[brow+1] - bmat->i[brow]; 456 for (bcol=0; bcol<nz; bcol++){ 457 gcol = bs*garray[*jj]; jj++; 458 for (col=0; col<bs; col++){ 459 for (row=0; row<bs; row++){ 460 vabs = PetscAbsScalar(*v); v++; 461 rsum[gcol+col] += vabs; 462 rsum[grow+row] += vabs; 463 } 464 } 465 } 466 } 467 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 468 *norm = 0.0; 469 for (col=0; col<mat->cmap->N; col++) { 470 if (rsum2[col] > *norm) *norm = rsum2[col]; 471 } 472 ierr = PetscFree(rsum);CHKERRQ(ierr); 473 } else { 474 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 475 } 476 } 477 PetscFunctionReturn(0); 478 } 479 480 #undef __FUNCT__ 481 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 482 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 483 { 484 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 485 PetscErrorCode ierr; 486 PetscInt nstash,reallocs; 487 InsertMode addv; 488 489 PetscFunctionBegin; 490 if (baij->donotstash) { 491 PetscFunctionReturn(0); 492 } 493 494 /* make sure all processors are either in INSERTMODE or ADDMODE */ 495 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 496 if (addv == (ADD_VALUES|INSERT_VALUES)) { 497 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 498 } 499 mat->insertmode = addv; /* in case this processor had no cache */ 500 501 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 502 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 503 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 504 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 505 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 506 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 507 PetscFunctionReturn(0); 508 } 509 510 #undef __FUNCT__ 511 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 512 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 513 { 514 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 515 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 516 PetscErrorCode ierr; 517 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 518 PetscInt *row,*col; 519 PetscTruth other_disassembled; 520 PetscMPIInt n; 521 PetscTruth r1,r2,r3; 522 MatScalar *val; 523 InsertMode addv = mat->insertmode; 524 525 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 526 PetscFunctionBegin; 527 528 if (!baij->donotstash) { 529 while (1) { 530 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 531 if (!flg) break; 532 533 for (i=0; i<n;) { 534 /* Now identify the consecutive vals belonging to the same row */ 535 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 536 if (j < n) ncols = j-i; 537 else ncols = n-i; 538 /* Now assemble all these values with a single function call */ 539 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 540 i = j; 541 } 542 } 543 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 544 /* Now process the block-stash. Since the values are stashed column-oriented, 545 set the roworiented flag to column oriented, and after MatSetValues() 546 restore the original flags */ 547 r1 = baij->roworiented; 548 r2 = a->roworiented; 549 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 550 baij->roworiented = PETSC_FALSE; 551 a->roworiented = PETSC_FALSE; 552 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 553 while (1) { 554 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 555 if (!flg) break; 556 557 for (i=0; i<n;) { 558 /* Now identify the consecutive vals belonging to the same row */ 559 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 560 if (j < n) ncols = j-i; 561 else ncols = n-i; 562 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 563 i = j; 564 } 565 } 566 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 567 baij->roworiented = r1; 568 a->roworiented = r2; 569 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 570 } 571 572 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 573 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 574 575 /* determine if any processor has disassembled, if so we must 576 also disassemble ourselfs, in order that we may reassemble. */ 577 /* 578 if nonzero structure of submatrix B cannot change then we know that 579 no processor disassembled thus we can skip this stuff 580 */ 581 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 582 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 583 if (mat->was_assembled && !other_disassembled) { 584 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 585 } 586 } 587 588 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 589 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 590 } 591 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 592 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 593 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 594 595 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 596 baij->rowvalues = 0; 597 598 PetscFunctionReturn(0); 599 } 600 601 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 602 #undef __FUNCT__ 603 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 604 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 605 { 606 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 607 PetscErrorCode ierr; 608 PetscInt bs = mat->rmap->bs; 609 PetscMPIInt size = baij->size,rank = baij->rank; 610 PetscTruth iascii,isdraw; 611 PetscViewer sviewer; 612 PetscViewerFormat format; 613 614 PetscFunctionBegin; 615 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 616 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 617 if (iascii) { 618 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 619 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 620 MatInfo info; 621 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 622 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 623 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 624 rank,mat->rmap->N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 625 mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 626 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 627 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 628 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 629 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 630 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 631 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 632 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 633 PetscFunctionReturn(0); 634 } else if (format == PETSC_VIEWER_ASCII_INFO) { 635 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 638 PetscFunctionReturn(0); 639 } 640 } 641 642 if (isdraw) { 643 PetscDraw draw; 644 PetscTruth isnull; 645 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 646 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 647 } 648 649 if (size == 1) { 650 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 651 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 652 } else { 653 /* assemble the entire matrix onto first processor. */ 654 Mat A; 655 Mat_SeqSBAIJ *Aloc; 656 Mat_SeqBAIJ *Bloc; 657 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 658 MatScalar *a; 659 660 /* Should this be the same type as mat? */ 661 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 662 if (!rank) { 663 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 664 } else { 665 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 666 } 667 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 668 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 669 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 670 671 /* copy over the A part */ 672 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 673 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 674 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 675 676 for (i=0; i<mbs; i++) { 677 rvals[0] = bs*(baij->rstartbs + i); 678 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 679 for (j=ai[i]; j<ai[i+1]; j++) { 680 col = (baij->cstartbs+aj[j])*bs; 681 for (k=0; k<bs; k++) { 682 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 683 col++; a += bs; 684 } 685 } 686 } 687 /* copy over the B part */ 688 Bloc = (Mat_SeqBAIJ*)baij->B->data; 689 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 690 for (i=0; i<mbs; i++) { 691 692 rvals[0] = bs*(baij->rstartbs + i); 693 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 694 for (j=ai[i]; j<ai[i+1]; j++) { 695 col = baij->garray[aj[j]]*bs; 696 for (k=0; k<bs; k++) { 697 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 698 col++; a += bs; 699 } 700 } 701 } 702 ierr = PetscFree(rvals);CHKERRQ(ierr); 703 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 704 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 705 /* 706 Everyone has to call to draw the matrix since the graphics waits are 707 synchronized across all processors that share the PetscDraw object 708 */ 709 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 710 if (!rank) { 711 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 712 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 713 } 714 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 715 ierr = MatDestroy(A);CHKERRQ(ierr); 716 } 717 PetscFunctionReturn(0); 718 } 719 720 #undef __FUNCT__ 721 #define __FUNCT__ "MatView_MPISBAIJ" 722 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 723 { 724 PetscErrorCode ierr; 725 PetscTruth iascii,isdraw,issocket,isbinary; 726 727 PetscFunctionBegin; 728 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 729 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 730 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 731 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 732 if (iascii || isdraw || issocket || isbinary) { 733 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 734 } else { 735 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 736 } 737 PetscFunctionReturn(0); 738 } 739 740 #undef __FUNCT__ 741 #define __FUNCT__ "MatDestroy_MPISBAIJ" 742 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 743 { 744 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 745 PetscErrorCode ierr; 746 747 PetscFunctionBegin; 748 #if defined(PETSC_USE_LOG) 749 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 750 #endif 751 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 752 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 753 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 754 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 755 #if defined (PETSC_USE_CTABLE) 756 if (baij->colmap) {ierr = PetscTableDestroy(baij->colmap);CHKERRQ(ierr);} 757 #else 758 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 759 #endif 760 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 761 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 762 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 763 if (baij->slvec0) { 764 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 765 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 766 } 767 if (baij->slvec1) { 768 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 769 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 770 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 771 } 772 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 773 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 774 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 775 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 776 #if defined(PETSC_USE_MAT_SINGLE) 777 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 778 #endif 779 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 780 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 781 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 782 ierr = PetscFree(baij);CHKERRQ(ierr); 783 784 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 785 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 786 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 787 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 788 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 789 PetscFunctionReturn(0); 790 } 791 792 #undef __FUNCT__ 793 #define __FUNCT__ "MatMult_MPISBAIJ" 794 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 795 { 796 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 797 PetscErrorCode ierr; 798 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 799 PetscScalar *x,*from,zero=0.0; 800 801 PetscFunctionBegin; 802 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 803 if (nt != A->cmap->n) { 804 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 805 } 806 807 /* diagonal part */ 808 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 809 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 810 811 /* subdiagonal part */ 812 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 813 814 /* copy x into the vec slvec0 */ 815 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 816 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 817 818 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 819 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 823 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 824 /* supperdiagonal part */ 825 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 826 PetscFunctionReturn(0); 827 } 828 829 #undef __FUNCT__ 830 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 831 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 832 { 833 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 834 PetscErrorCode ierr; 835 PetscInt nt; 836 837 PetscFunctionBegin; 838 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 839 if (nt != A->cmap->n) { 840 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 841 } 842 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 843 if (nt != A->rmap->N) { 844 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 845 } 846 847 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 848 /* do diagonal part */ 849 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 850 /* do supperdiagonal part */ 851 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 852 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 853 /* do subdiagonal part */ 854 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 855 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 856 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 857 858 PetscFunctionReturn(0); 859 } 860 861 #undef __FUNCT__ 862 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 863 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 864 { 865 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 866 PetscErrorCode ierr; 867 PetscInt mbs=a->mbs,bs=A->rmap->bs; 868 PetscScalar *x,*from,zero=0.0; 869 870 PetscFunctionBegin; 871 /* 872 PetscSynchronizedPrintf(((PetscObject)A)->comm," MatMultAdd is called ...\n"); 873 PetscSynchronizedFlush(((PetscObject)A)->comm); 874 */ 875 /* diagonal part */ 876 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 877 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 878 879 /* subdiagonal part */ 880 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 881 882 /* copy x into the vec slvec0 */ 883 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 884 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 885 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 886 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 887 888 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 889 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 890 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 891 892 /* supperdiagonal part */ 893 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 894 895 PetscFunctionReturn(0); 896 } 897 898 #undef __FUNCT__ 899 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 900 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 901 { 902 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 903 PetscErrorCode ierr; 904 905 PetscFunctionBegin; 906 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 907 /* do diagonal part */ 908 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 909 /* do supperdiagonal part */ 910 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 911 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 912 913 /* do subdiagonal part */ 914 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 915 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 916 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 917 918 PetscFunctionReturn(0); 919 } 920 921 /* 922 This only works correctly for square matrices where the subblock A->A is the 923 diagonal block 924 */ 925 #undef __FUNCT__ 926 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 927 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 928 { 929 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 930 PetscErrorCode ierr; 931 932 PetscFunctionBegin; 933 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 934 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 935 PetscFunctionReturn(0); 936 } 937 938 #undef __FUNCT__ 939 #define __FUNCT__ "MatScale_MPISBAIJ" 940 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 941 { 942 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 943 PetscErrorCode ierr; 944 945 PetscFunctionBegin; 946 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 947 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatGetRow_MPISBAIJ" 953 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 954 { 955 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 956 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 957 PetscErrorCode ierr; 958 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 959 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 960 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 961 962 PetscFunctionBegin; 963 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 964 mat->getrowactive = PETSC_TRUE; 965 966 if (!mat->rowvalues && (idx || v)) { 967 /* 968 allocate enough space to hold information from the longest row. 969 */ 970 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 971 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 972 PetscInt max = 1,mbs = mat->mbs,tmp; 973 for (i=0; i<mbs; i++) { 974 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 975 if (max < tmp) { max = tmp; } 976 } 977 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 978 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 979 } 980 981 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 982 lrow = row - brstart; /* local row index */ 983 984 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 985 if (!v) {pvA = 0; pvB = 0;} 986 if (!idx) {pcA = 0; if (!v) pcB = 0;} 987 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 988 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 989 nztot = nzA + nzB; 990 991 cmap = mat->garray; 992 if (v || idx) { 993 if (nztot) { 994 /* Sort by increasing column numbers, assuming A and B already sorted */ 995 PetscInt imark = -1; 996 if (v) { 997 *v = v_p = mat->rowvalues; 998 for (i=0; i<nzB; i++) { 999 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1000 else break; 1001 } 1002 imark = i; 1003 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1004 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1005 } 1006 if (idx) { 1007 *idx = idx_p = mat->rowindices; 1008 if (imark > -1) { 1009 for (i=0; i<imark; i++) { 1010 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1011 } 1012 } else { 1013 for (i=0; i<nzB; i++) { 1014 if (cmap[cworkB[i]/bs] < cstart) 1015 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1016 else break; 1017 } 1018 imark = i; 1019 } 1020 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1021 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1022 } 1023 } else { 1024 if (idx) *idx = 0; 1025 if (v) *v = 0; 1026 } 1027 } 1028 *nz = nztot; 1029 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1030 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1031 PetscFunctionReturn(0); 1032 } 1033 1034 #undef __FUNCT__ 1035 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1036 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1037 { 1038 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1039 1040 PetscFunctionBegin; 1041 if (!baij->getrowactive) { 1042 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1043 } 1044 baij->getrowactive = PETSC_FALSE; 1045 PetscFunctionReturn(0); 1046 } 1047 1048 #undef __FUNCT__ 1049 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1050 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1051 { 1052 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1053 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1054 1055 PetscFunctionBegin; 1056 aA->getrow_utriangular = PETSC_TRUE; 1057 PetscFunctionReturn(0); 1058 } 1059 #undef __FUNCT__ 1060 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1061 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1062 { 1063 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1064 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1065 1066 PetscFunctionBegin; 1067 aA->getrow_utriangular = PETSC_FALSE; 1068 PetscFunctionReturn(0); 1069 } 1070 1071 #undef __FUNCT__ 1072 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1073 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1074 { 1075 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1076 PetscErrorCode ierr; 1077 1078 PetscFunctionBegin; 1079 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1080 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1081 PetscFunctionReturn(0); 1082 } 1083 1084 #undef __FUNCT__ 1085 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1086 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1087 { 1088 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1089 PetscErrorCode ierr; 1090 1091 PetscFunctionBegin; 1092 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1093 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1094 PetscFunctionReturn(0); 1095 } 1096 1097 #undef __FUNCT__ 1098 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1099 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1100 { 1101 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1102 PetscErrorCode ierr; 1103 1104 PetscFunctionBegin; 1105 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1106 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1107 PetscFunctionReturn(0); 1108 } 1109 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1112 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1113 { 1114 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1115 Mat A = a->A,B = a->B; 1116 PetscErrorCode ierr; 1117 PetscReal isend[5],irecv[5]; 1118 1119 PetscFunctionBegin; 1120 info->block_size = (PetscReal)matin->rmap->bs; 1121 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1122 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1123 isend[3] = info->memory; isend[4] = info->mallocs; 1124 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1125 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1126 isend[3] += info->memory; isend[4] += info->mallocs; 1127 if (flag == MAT_LOCAL) { 1128 info->nz_used = isend[0]; 1129 info->nz_allocated = isend[1]; 1130 info->nz_unneeded = isend[2]; 1131 info->memory = isend[3]; 1132 info->mallocs = isend[4]; 1133 } else if (flag == MAT_GLOBAL_MAX) { 1134 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1135 info->nz_used = irecv[0]; 1136 info->nz_allocated = irecv[1]; 1137 info->nz_unneeded = irecv[2]; 1138 info->memory = irecv[3]; 1139 info->mallocs = irecv[4]; 1140 } else if (flag == MAT_GLOBAL_SUM) { 1141 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1142 info->nz_used = irecv[0]; 1143 info->nz_allocated = irecv[1]; 1144 info->nz_unneeded = irecv[2]; 1145 info->memory = irecv[3]; 1146 info->mallocs = irecv[4]; 1147 } else { 1148 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1149 } 1150 info->rows_global = (PetscReal)A->rmap->N; 1151 info->columns_global = (PetscReal)A->cmap->N; 1152 info->rows_local = (PetscReal)A->rmap->N; 1153 info->columns_local = (PetscReal)A->cmap->N; 1154 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1155 info->fill_ratio_needed = 0; 1156 info->factor_mallocs = 0; 1157 PetscFunctionReturn(0); 1158 } 1159 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1162 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscTruth flg) 1163 { 1164 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1165 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1166 PetscErrorCode ierr; 1167 1168 PetscFunctionBegin; 1169 switch (op) { 1170 case MAT_NEW_NONZERO_LOCATIONS: 1171 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1172 case MAT_KEEP_ZEROED_ROWS: 1173 case MAT_NEW_NONZERO_LOCATION_ERR: 1174 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1175 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1176 break; 1177 case MAT_ROW_ORIENTED: 1178 a->roworiented = flg; 1179 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1180 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1181 break; 1182 case MAT_NEW_DIAGONALS: 1183 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1184 break; 1185 case MAT_IGNORE_OFF_PROC_ENTRIES: 1186 a->donotstash = flg; 1187 break; 1188 case MAT_USE_HASH_TABLE: 1189 a->ht_flag = flg; 1190 break; 1191 case MAT_HERMITIAN: 1192 if (flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1193 case MAT_SYMMETRIC: 1194 case MAT_STRUCTURALLY_SYMMETRIC: 1195 case MAT_SYMMETRY_ETERNAL: 1196 if (!flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1197 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1198 break; 1199 case MAT_IGNORE_LOWER_TRIANGULAR: 1200 aA->ignore_ltriangular = flg; 1201 break; 1202 case MAT_ERROR_LOWER_TRIANGULAR: 1203 aA->ignore_ltriangular = flg; 1204 break; 1205 case MAT_GETROW_UPPERTRIANGULAR: 1206 aA->getrow_utriangular = flg; 1207 break; 1208 default: 1209 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1210 } 1211 PetscFunctionReturn(0); 1212 } 1213 1214 #undef __FUNCT__ 1215 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1216 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1217 { 1218 PetscErrorCode ierr; 1219 PetscFunctionBegin; 1220 if (MAT_INITIAL_MATRIX || *B != A) { 1221 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1222 } 1223 PetscFunctionReturn(0); 1224 } 1225 1226 #undef __FUNCT__ 1227 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1228 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1229 { 1230 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1231 Mat a=baij->A, b=baij->B; 1232 PetscErrorCode ierr; 1233 PetscInt nv,m,n; 1234 PetscTruth flg; 1235 1236 PetscFunctionBegin; 1237 if (ll != rr){ 1238 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1239 if (!flg) 1240 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1241 } 1242 if (!ll) PetscFunctionReturn(0); 1243 1244 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1245 if (m != n) SETERRQ2(PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1246 1247 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1248 if (nv!=n) SETERRQ(PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1249 1250 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1251 1252 /* left diagonalscale the off-diagonal part */ 1253 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1254 1255 /* scale the diagonal part */ 1256 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1257 1258 /* right diagonalscale the off-diagonal part */ 1259 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1260 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1261 PetscFunctionReturn(0); 1262 } 1263 1264 #undef __FUNCT__ 1265 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1266 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1267 { 1268 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1269 PetscErrorCode ierr; 1270 1271 PetscFunctionBegin; 1272 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1273 PetscFunctionReturn(0); 1274 } 1275 1276 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1277 1278 #undef __FUNCT__ 1279 #define __FUNCT__ "MatEqual_MPISBAIJ" 1280 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1281 { 1282 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1283 Mat a,b,c,d; 1284 PetscTruth flg; 1285 PetscErrorCode ierr; 1286 1287 PetscFunctionBegin; 1288 a = matA->A; b = matA->B; 1289 c = matB->A; d = matB->B; 1290 1291 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1292 if (flg) { 1293 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1294 } 1295 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1296 PetscFunctionReturn(0); 1297 } 1298 1299 #undef __FUNCT__ 1300 #define __FUNCT__ "MatCopy_MPISBAIJ" 1301 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1302 { 1303 PetscErrorCode ierr; 1304 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1305 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1306 1307 PetscFunctionBegin; 1308 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1309 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1310 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1311 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1312 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1313 } else { 1314 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1315 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1316 } 1317 PetscFunctionReturn(0); 1318 } 1319 1320 #undef __FUNCT__ 1321 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1322 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1323 { 1324 PetscErrorCode ierr; 1325 1326 PetscFunctionBegin; 1327 ierr = MatMPISBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1328 PetscFunctionReturn(0); 1329 } 1330 1331 #include "petscblaslapack.h" 1332 #undef __FUNCT__ 1333 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1334 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1335 { 1336 PetscErrorCode ierr; 1337 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data; 1338 PetscBLASInt bnz,one=1; 1339 Mat_SeqSBAIJ *xa,*ya; 1340 Mat_SeqBAIJ *xb,*yb; 1341 1342 PetscFunctionBegin; 1343 if (str == SAME_NONZERO_PATTERN) { 1344 PetscScalar alpha = a; 1345 xa = (Mat_SeqSBAIJ *)xx->A->data; 1346 ya = (Mat_SeqSBAIJ *)yy->A->data; 1347 bnz = PetscBLASIntCast(xa->nz); 1348 BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one); 1349 xb = (Mat_SeqBAIJ *)xx->B->data; 1350 yb = (Mat_SeqBAIJ *)yy->B->data; 1351 bnz = PetscBLASIntCast(xb->nz); 1352 BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one); 1353 } else { 1354 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1355 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1356 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1357 } 1358 PetscFunctionReturn(0); 1359 } 1360 1361 #undef __FUNCT__ 1362 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1363 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1364 { 1365 PetscErrorCode ierr; 1366 PetscInt i; 1367 PetscTruth flg; 1368 1369 PetscFunctionBegin; 1370 for (i=0; i<n; i++) { 1371 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1372 if (!flg) { 1373 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1374 } 1375 } 1376 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1377 PetscFunctionReturn(0); 1378 } 1379 1380 1381 /* -------------------------------------------------------------------*/ 1382 static struct _MatOps MatOps_Values = { 1383 MatSetValues_MPISBAIJ, 1384 MatGetRow_MPISBAIJ, 1385 MatRestoreRow_MPISBAIJ, 1386 MatMult_MPISBAIJ, 1387 /* 4*/ MatMultAdd_MPISBAIJ, 1388 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1389 MatMultAdd_MPISBAIJ, 1390 0, 1391 0, 1392 0, 1393 /*10*/ 0, 1394 0, 1395 0, 1396 MatRelax_MPISBAIJ, 1397 MatTranspose_MPISBAIJ, 1398 /*15*/ MatGetInfo_MPISBAIJ, 1399 MatEqual_MPISBAIJ, 1400 MatGetDiagonal_MPISBAIJ, 1401 MatDiagonalScale_MPISBAIJ, 1402 MatNorm_MPISBAIJ, 1403 /*20*/ MatAssemblyBegin_MPISBAIJ, 1404 MatAssemblyEnd_MPISBAIJ, 1405 0, 1406 MatSetOption_MPISBAIJ, 1407 MatZeroEntries_MPISBAIJ, 1408 /*25*/ 0, 1409 0, 1410 0, 1411 0, 1412 0, 1413 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1414 0, 1415 0, 1416 0, 1417 0, 1418 /*35*/ MatDuplicate_MPISBAIJ, 1419 0, 1420 0, 1421 0, 1422 0, 1423 /*40*/ MatAXPY_MPISBAIJ, 1424 MatGetSubMatrices_MPISBAIJ, 1425 MatIncreaseOverlap_MPISBAIJ, 1426 MatGetValues_MPISBAIJ, 1427 MatCopy_MPISBAIJ, 1428 /*45*/ 0, 1429 MatScale_MPISBAIJ, 1430 0, 1431 0, 1432 0, 1433 /*50*/ 0, 1434 0, 1435 0, 1436 0, 1437 0, 1438 /*55*/ 0, 1439 0, 1440 MatSetUnfactored_MPISBAIJ, 1441 0, 1442 MatSetValuesBlocked_MPISBAIJ, 1443 /*60*/ 0, 1444 0, 1445 0, 1446 0, 1447 0, 1448 /*65*/ 0, 1449 0, 1450 0, 1451 0, 1452 0, 1453 /*70*/ MatGetRowMaxAbs_MPISBAIJ, 1454 0, 1455 0, 1456 0, 1457 0, 1458 /*75*/ 0, 1459 0, 1460 0, 1461 0, 1462 0, 1463 /*80*/ 0, 1464 0, 1465 0, 1466 0, 1467 MatLoad_MPISBAIJ, 1468 /*85*/ 0, 1469 0, 1470 0, 1471 0, 1472 0, 1473 /*90*/ 0, 1474 0, 1475 0, 1476 0, 1477 0, 1478 /*95*/ 0, 1479 0, 1480 0, 1481 0, 1482 0, 1483 /*100*/0, 1484 0, 1485 0, 1486 0, 1487 0, 1488 /*105*/0, 1489 MatRealPart_MPISBAIJ, 1490 MatImaginaryPart_MPISBAIJ, 1491 MatGetRowUpperTriangular_MPISBAIJ, 1492 MatRestoreRowUpperTriangular_MPISBAIJ 1493 }; 1494 1495 1496 EXTERN_C_BEGIN 1497 #undef __FUNCT__ 1498 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1499 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1500 { 1501 PetscFunctionBegin; 1502 *a = ((Mat_MPISBAIJ *)A->data)->A; 1503 *iscopy = PETSC_FALSE; 1504 PetscFunctionReturn(0); 1505 } 1506 EXTERN_C_END 1507 1508 EXTERN_C_BEGIN 1509 #undef __FUNCT__ 1510 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1511 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1512 { 1513 Mat_MPISBAIJ *b; 1514 PetscErrorCode ierr; 1515 PetscInt i,mbs,Mbs,newbs = PetscAbs(bs); 1516 1517 PetscFunctionBegin; 1518 if (bs < 0){ 1519 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");CHKERRQ(ierr); 1520 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 1521 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1522 bs = PetscAbs(bs); 1523 } 1524 if ((d_nnz || o_nnz) && newbs != bs) { 1525 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 1526 } 1527 bs = newbs; 1528 1529 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1530 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1531 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1532 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1533 1534 B->rmap->bs = B->cmap->bs = bs; 1535 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 1536 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 1537 1538 if (d_nnz) { 1539 for (i=0; i<B->rmap->n/bs; i++) { 1540 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]); 1541 } 1542 } 1543 if (o_nnz) { 1544 for (i=0; i<B->rmap->n/bs; i++) { 1545 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]); 1546 } 1547 } 1548 B->preallocated = PETSC_TRUE; 1549 1550 b = (Mat_MPISBAIJ*)B->data; 1551 mbs = B->rmap->n/bs; 1552 Mbs = B->rmap->N/bs; 1553 if (mbs*bs != B->rmap->n) { 1554 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs); 1555 } 1556 1557 B->rmap->bs = bs; 1558 b->bs2 = bs*bs; 1559 b->mbs = mbs; 1560 b->nbs = mbs; 1561 b->Mbs = Mbs; 1562 b->Nbs = Mbs; 1563 1564 for (i=0; i<=b->size; i++) { 1565 b->rangebs[i] = B->rmap->range[i]/bs; 1566 } 1567 b->rstartbs = B->rmap->rstart/bs; 1568 b->rendbs = B->rmap->rend/bs; 1569 1570 b->cstartbs = B->cmap->rstart/bs; 1571 b->cendbs = B->cmap->rend/bs; 1572 1573 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1574 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1575 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1576 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1577 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1578 1579 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1580 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1581 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1582 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1583 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1584 1585 /* build cache for off array entries formed */ 1586 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 1587 1588 PetscFunctionReturn(0); 1589 } 1590 EXTERN_C_END 1591 1592 EXTERN_C_BEGIN 1593 #if defined(PETSC_HAVE_MUMPS) 1594 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_mumps(Mat,MatFactorType,Mat*); 1595 #endif 1596 #if defined(PETSC_HAVE_SPOOLES) 1597 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_spooles(Mat,MatFactorType,Mat*); 1598 #endif 1599 EXTERN_C_END 1600 1601 /*MC 1602 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1603 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1604 1605 Options Database Keys: 1606 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1607 1608 Level: beginner 1609 1610 .seealso: MatCreateMPISBAIJ 1611 M*/ 1612 1613 EXTERN_C_BEGIN 1614 #undef __FUNCT__ 1615 #define __FUNCT__ "MatCreate_MPISBAIJ" 1616 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPISBAIJ(Mat B) 1617 { 1618 Mat_MPISBAIJ *b; 1619 PetscErrorCode ierr; 1620 PetscTruth flg; 1621 1622 PetscFunctionBegin; 1623 1624 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1625 B->data = (void*)b; 1626 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1627 1628 B->ops->destroy = MatDestroy_MPISBAIJ; 1629 B->ops->view = MatView_MPISBAIJ; 1630 B->mapping = 0; 1631 B->assembled = PETSC_FALSE; 1632 1633 B->insertmode = NOT_SET_VALUES; 1634 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 1635 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 1636 1637 /* build local table of row and column ownerships */ 1638 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1639 1640 /* build cache for off array entries formed */ 1641 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 1642 b->donotstash = PETSC_FALSE; 1643 b->colmap = PETSC_NULL; 1644 b->garray = PETSC_NULL; 1645 b->roworiented = PETSC_TRUE; 1646 1647 /* stuff used in block assembly */ 1648 b->barray = 0; 1649 1650 /* stuff used for matrix vector multiply */ 1651 b->lvec = 0; 1652 b->Mvctx = 0; 1653 b->slvec0 = 0; 1654 b->slvec0b = 0; 1655 b->slvec1 = 0; 1656 b->slvec1a = 0; 1657 b->slvec1b = 0; 1658 b->sMvctx = 0; 1659 1660 /* stuff for MatGetRow() */ 1661 b->rowindices = 0; 1662 b->rowvalues = 0; 1663 b->getrowactive = PETSC_FALSE; 1664 1665 /* hash table stuff */ 1666 b->ht = 0; 1667 b->hd = 0; 1668 b->ht_size = 0; 1669 b->ht_flag = PETSC_FALSE; 1670 b->ht_fact = 0; 1671 b->ht_total_ct = 0; 1672 b->ht_insert_ct = 0; 1673 1674 b->in_loc = 0; 1675 b->v_loc = 0; 1676 b->n_loc = 0; 1677 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1678 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1679 if (flg) { 1680 PetscReal fact = 1.39; 1681 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1682 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1683 if (fact <= 1.0) fact = 1.39; 1684 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1685 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1686 } 1687 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1688 1689 #if defined(PETSC_HAVE_MUMPS) 1690 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_mumps_C", 1691 "MatGetFactor_mpisbaij_mumps", 1692 MatGetFactor_mpisbaij_mumps);CHKERRQ(ierr); 1693 #endif 1694 #if defined(PETSC_HAVE_SPOOLES) 1695 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_spooles_C", 1696 "MatGetFactor_mpisbaij_spooles", 1697 MatGetFactor_mpisbaij_spooles);CHKERRQ(ierr); 1698 #endif 1699 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1700 "MatStoreValues_MPISBAIJ", 1701 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1702 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1703 "MatRetrieveValues_MPISBAIJ", 1704 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1705 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1706 "MatGetDiagonalBlock_MPISBAIJ", 1707 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1708 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1709 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1710 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1711 B->symmetric = PETSC_TRUE; 1712 B->structurally_symmetric = PETSC_TRUE; 1713 B->symmetric_set = PETSC_TRUE; 1714 B->structurally_symmetric_set = PETSC_TRUE; 1715 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1716 PetscFunctionReturn(0); 1717 } 1718 EXTERN_C_END 1719 1720 /*MC 1721 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1722 1723 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1724 and MATMPISBAIJ otherwise. 1725 1726 Options Database Keys: 1727 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1728 1729 Level: beginner 1730 1731 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1732 M*/ 1733 1734 EXTERN_C_BEGIN 1735 #undef __FUNCT__ 1736 #define __FUNCT__ "MatCreate_SBAIJ" 1737 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SBAIJ(Mat A) 1738 { 1739 PetscErrorCode ierr; 1740 PetscMPIInt size; 1741 1742 PetscFunctionBegin; 1743 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 1744 if (size == 1) { 1745 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1746 } else { 1747 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1748 } 1749 PetscFunctionReturn(0); 1750 } 1751 EXTERN_C_END 1752 1753 #undef __FUNCT__ 1754 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1755 /*@C 1756 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1757 the user should preallocate the matrix storage by setting the parameters 1758 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1759 performance can be increased by more than a factor of 50. 1760 1761 Collective on Mat 1762 1763 Input Parameters: 1764 + A - the matrix 1765 . bs - size of blockk 1766 . d_nz - number of block nonzeros per block row in diagonal portion of local 1767 submatrix (same for all local rows) 1768 . d_nnz - array containing the number of block nonzeros in the various block rows 1769 in the upper triangular and diagonal part of the in diagonal portion of the local 1770 (possibly different for each block row) or PETSC_NULL. You must leave room 1771 for the diagonal entry even if it is zero. 1772 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1773 submatrix (same for all local rows). 1774 - o_nnz - array containing the number of nonzeros in the various block rows of the 1775 off-diagonal portion of the local submatrix (possibly different for 1776 each block row) or PETSC_NULL. 1777 1778 1779 Options Database Keys: 1780 . -mat_no_unroll - uses code that does not unroll the loops in the 1781 block calculations (much slower) 1782 . -mat_block_size - size of the blocks to use 1783 1784 Notes: 1785 1786 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1787 than it must be used on all processors that share the object for that argument. 1788 1789 If the *_nnz parameter is given then the *_nz parameter is ignored 1790 1791 Storage Information: 1792 For a square global matrix we define each processor's diagonal portion 1793 to be its local rows and the corresponding columns (a square submatrix); 1794 each processor's off-diagonal portion encompasses the remainder of the 1795 local matrix (a rectangular submatrix). 1796 1797 The user can specify preallocated storage for the diagonal part of 1798 the local submatrix with either d_nz or d_nnz (not both). Set 1799 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1800 memory allocation. Likewise, specify preallocated storage for the 1801 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1802 1803 You can call MatGetInfo() to get information on how effective the preallocation was; 1804 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1805 You can also run with the option -info and look for messages with the string 1806 malloc in them to see if additional memory allocation was needed. 1807 1808 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1809 the figure below we depict these three local rows and all columns (0-11). 1810 1811 .vb 1812 0 1 2 3 4 5 6 7 8 9 10 11 1813 ------------------- 1814 row 3 | o o o d d d o o o o o o 1815 row 4 | o o o d d d o o o o o o 1816 row 5 | o o o d d d o o o o o o 1817 ------------------- 1818 .ve 1819 1820 Thus, any entries in the d locations are stored in the d (diagonal) 1821 submatrix, and any entries in the o locations are stored in the 1822 o (off-diagonal) submatrix. Note that the d matrix is stored in 1823 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1824 1825 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1826 plus the diagonal part of the d matrix, 1827 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1828 In general, for PDE problems in which most nonzeros are near the diagonal, 1829 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1830 or you will get TERRIBLE performance; see the users' manual chapter on 1831 matrices. 1832 1833 Level: intermediate 1834 1835 .keywords: matrix, block, aij, compressed row, sparse, parallel 1836 1837 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1838 @*/ 1839 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1840 { 1841 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1842 1843 PetscFunctionBegin; 1844 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1845 if (f) { 1846 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1847 } 1848 PetscFunctionReturn(0); 1849 } 1850 1851 #undef __FUNCT__ 1852 #define __FUNCT__ "MatCreateMPISBAIJ" 1853 /*@C 1854 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1855 (block compressed row). For good matrix assembly performance 1856 the user should preallocate the matrix storage by setting the parameters 1857 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1858 performance can be increased by more than a factor of 50. 1859 1860 Collective on MPI_Comm 1861 1862 Input Parameters: 1863 + comm - MPI communicator 1864 . bs - size of blockk 1865 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1866 This value should be the same as the local size used in creating the 1867 y vector for the matrix-vector product y = Ax. 1868 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1869 This value should be the same as the local size used in creating the 1870 x vector for the matrix-vector product y = Ax. 1871 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1872 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1873 . d_nz - number of block nonzeros per block row in diagonal portion of local 1874 submatrix (same for all local rows) 1875 . d_nnz - array containing the number of block nonzeros in the various block rows 1876 in the upper triangular portion of the in diagonal portion of the local 1877 (possibly different for each block block row) or PETSC_NULL. 1878 You must leave room for the diagonal entry even if it is zero. 1879 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1880 submatrix (same for all local rows). 1881 - o_nnz - array containing the number of nonzeros in the various block rows of the 1882 off-diagonal portion of the local submatrix (possibly different for 1883 each block row) or PETSC_NULL. 1884 1885 Output Parameter: 1886 . A - the matrix 1887 1888 Options Database Keys: 1889 . -mat_no_unroll - uses code that does not unroll the loops in the 1890 block calculations (much slower) 1891 . -mat_block_size - size of the blocks to use 1892 . -mat_mpi - use the parallel matrix data structures even on one processor 1893 (defaults to using SeqBAIJ format on one processor) 1894 1895 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1896 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 1897 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 1898 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1899 1900 Notes: 1901 The number of rows and columns must be divisible by blocksize. 1902 This matrix type does not support complex Hermitian operation. 1903 1904 The user MUST specify either the local or global matrix dimensions 1905 (possibly both). 1906 1907 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1908 than it must be used on all processors that share the object for that argument. 1909 1910 If the *_nnz parameter is given then the *_nz parameter is ignored 1911 1912 Storage Information: 1913 For a square global matrix we define each processor's diagonal portion 1914 to be its local rows and the corresponding columns (a square submatrix); 1915 each processor's off-diagonal portion encompasses the remainder of the 1916 local matrix (a rectangular submatrix). 1917 1918 The user can specify preallocated storage for the diagonal part of 1919 the local submatrix with either d_nz or d_nnz (not both). Set 1920 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1921 memory allocation. Likewise, specify preallocated storage for the 1922 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1923 1924 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1925 the figure below we depict these three local rows and all columns (0-11). 1926 1927 .vb 1928 0 1 2 3 4 5 6 7 8 9 10 11 1929 ------------------- 1930 row 3 | o o o d d d o o o o o o 1931 row 4 | o o o d d d o o o o o o 1932 row 5 | o o o d d d o o o o o o 1933 ------------------- 1934 .ve 1935 1936 Thus, any entries in the d locations are stored in the d (diagonal) 1937 submatrix, and any entries in the o locations are stored in the 1938 o (off-diagonal) submatrix. Note that the d matrix is stored in 1939 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1940 1941 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1942 plus the diagonal part of the d matrix, 1943 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1944 In general, for PDE problems in which most nonzeros are near the diagonal, 1945 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1946 or you will get TERRIBLE performance; see the users' manual chapter on 1947 matrices. 1948 1949 Level: intermediate 1950 1951 .keywords: matrix, block, aij, compressed row, sparse, parallel 1952 1953 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1954 @*/ 1955 1956 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPISBAIJ(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) 1957 { 1958 PetscErrorCode ierr; 1959 PetscMPIInt size; 1960 1961 PetscFunctionBegin; 1962 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1963 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1964 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1965 if (size > 1) { 1966 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1967 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1968 } else { 1969 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1970 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1971 } 1972 PetscFunctionReturn(0); 1973 } 1974 1975 1976 #undef __FUNCT__ 1977 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1978 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1979 { 1980 Mat mat; 1981 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1982 PetscErrorCode ierr; 1983 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 1984 PetscScalar *array; 1985 1986 PetscFunctionBegin; 1987 *newmat = 0; 1988 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 1989 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 1990 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 1991 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1992 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 1993 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 1994 1995 mat->factor = matin->factor; 1996 mat->preallocated = PETSC_TRUE; 1997 mat->assembled = PETSC_TRUE; 1998 mat->insertmode = NOT_SET_VALUES; 1999 2000 a = (Mat_MPISBAIJ*)mat->data; 2001 a->bs2 = oldmat->bs2; 2002 a->mbs = oldmat->mbs; 2003 a->nbs = oldmat->nbs; 2004 a->Mbs = oldmat->Mbs; 2005 a->Nbs = oldmat->Nbs; 2006 2007 2008 a->size = oldmat->size; 2009 a->rank = oldmat->rank; 2010 a->donotstash = oldmat->donotstash; 2011 a->roworiented = oldmat->roworiented; 2012 a->rowindices = 0; 2013 a->rowvalues = 0; 2014 a->getrowactive = PETSC_FALSE; 2015 a->barray = 0; 2016 a->rstartbs = oldmat->rstartbs; 2017 a->rendbs = oldmat->rendbs; 2018 a->cstartbs = oldmat->cstartbs; 2019 a->cendbs = oldmat->cendbs; 2020 2021 /* hash table stuff */ 2022 a->ht = 0; 2023 a->hd = 0; 2024 a->ht_size = 0; 2025 a->ht_flag = oldmat->ht_flag; 2026 a->ht_fact = oldmat->ht_fact; 2027 a->ht_total_ct = 0; 2028 a->ht_insert_ct = 0; 2029 2030 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2031 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2032 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2033 if (oldmat->colmap) { 2034 #if defined (PETSC_USE_CTABLE) 2035 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2036 #else 2037 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2038 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2039 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2040 #endif 2041 } else a->colmap = 0; 2042 2043 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2044 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2045 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2046 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2047 } else a->garray = 0; 2048 2049 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2050 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2051 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2052 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2053 2054 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2055 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2056 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2057 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2058 2059 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2060 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2061 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2062 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2063 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2064 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2065 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2066 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2067 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2068 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2069 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2070 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2071 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2072 2073 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2074 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2075 a->sMvctx = oldmat->sMvctx; 2076 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2077 2078 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2079 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2080 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2081 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2082 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2083 *newmat = mat; 2084 PetscFunctionReturn(0); 2085 } 2086 2087 #include "petscsys.h" 2088 2089 #undef __FUNCT__ 2090 #define __FUNCT__ "MatLoad_MPISBAIJ" 2091 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2092 { 2093 Mat A; 2094 PetscErrorCode ierr; 2095 PetscInt i,nz,j,rstart,rend; 2096 PetscScalar *vals,*buf; 2097 MPI_Comm comm = ((PetscObject)viewer)->comm; 2098 MPI_Status status; 2099 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens,mmbs; 2100 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2101 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2102 PetscInt bs=1,Mbs,mbs,extra_rows; 2103 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2104 PetscInt dcount,kmax,k,nzcount,tmp; 2105 int fd; 2106 2107 PetscFunctionBegin; 2108 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2109 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2110 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2111 2112 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2113 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2114 if (!rank) { 2115 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2116 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2117 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2118 if (header[3] < 0) { 2119 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2120 } 2121 } 2122 2123 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2124 M = header[1]; N = header[2]; 2125 2126 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2127 2128 /* 2129 This code adds extra rows to make sure the number of rows is 2130 divisible by the blocksize 2131 */ 2132 Mbs = M/bs; 2133 extra_rows = bs - M + bs*(Mbs); 2134 if (extra_rows == bs) extra_rows = 0; 2135 else Mbs++; 2136 if (extra_rows &&!rank) { 2137 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2138 } 2139 2140 /* determine ownership of all rows */ 2141 mbs = Mbs/size + ((Mbs % size) > rank); 2142 m = mbs*bs; 2143 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2144 browners = rowners + size + 1; 2145 mmbs = PetscMPIIntCast(mbs); 2146 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2147 rowners[0] = 0; 2148 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2149 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2150 rstart = rowners[rank]; 2151 rend = rowners[rank+1]; 2152 2153 /* distribute row lengths to all processors */ 2154 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);CHKERRQ(ierr); 2155 if (!rank) { 2156 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2157 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2158 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2159 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2160 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2161 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2162 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2163 } else { 2164 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2165 } 2166 2167 if (!rank) { /* procs[0] */ 2168 /* calculate the number of nonzeros on each processor */ 2169 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2170 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2171 for (i=0; i<size; i++) { 2172 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2173 procsnz[i] += rowlengths[j]; 2174 } 2175 } 2176 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2177 2178 /* determine max buffer needed and allocate it */ 2179 maxnz = 0; 2180 for (i=0; i<size; i++) { 2181 maxnz = PetscMax(maxnz,procsnz[i]); 2182 } 2183 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2184 2185 /* read in my part of the matrix column indices */ 2186 nz = procsnz[0]; 2187 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2188 mycols = ibuf; 2189 if (size == 1) nz -= extra_rows; 2190 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2191 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2192 2193 /* read in every ones (except the last) and ship off */ 2194 for (i=1; i<size-1; i++) { 2195 nz = procsnz[i]; 2196 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2197 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2198 } 2199 /* read in the stuff for the last proc */ 2200 if (size != 1) { 2201 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2202 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2203 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2204 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2205 } 2206 ierr = PetscFree(cols);CHKERRQ(ierr); 2207 } else { /* procs[i], i>0 */ 2208 /* determine buffer space needed for message */ 2209 nz = 0; 2210 for (i=0; i<m; i++) { 2211 nz += locrowlens[i]; 2212 } 2213 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2214 mycols = ibuf; 2215 /* receive message of column indices*/ 2216 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2217 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2218 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2219 } 2220 2221 /* loop over local rows, determining number of off diagonal entries */ 2222 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2223 odlens = dlens + (rend-rstart); 2224 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2225 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2226 masked1 = mask + Mbs; 2227 masked2 = masked1 + Mbs; 2228 rowcount = 0; nzcount = 0; 2229 for (i=0; i<mbs; i++) { 2230 dcount = 0; 2231 odcount = 0; 2232 for (j=0; j<bs; j++) { 2233 kmax = locrowlens[rowcount]; 2234 for (k=0; k<kmax; k++) { 2235 tmp = mycols[nzcount++]/bs; /* block col. index */ 2236 if (!mask[tmp]) { 2237 mask[tmp] = 1; 2238 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2239 else masked1[dcount++] = tmp; /* entry in diag portion */ 2240 } 2241 } 2242 rowcount++; 2243 } 2244 2245 dlens[i] = dcount; /* d_nzz[i] */ 2246 odlens[i] = odcount; /* o_nzz[i] */ 2247 2248 /* zero out the mask elements we set */ 2249 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2250 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2251 } 2252 2253 /* create our matrix */ 2254 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2255 ierr = MatSetSizes(A,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2256 ierr = MatSetType(A,type);CHKERRQ(ierr); 2257 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2258 2259 if (!rank) { 2260 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2261 /* read in my part of the matrix numerical values */ 2262 nz = procsnz[0]; 2263 vals = buf; 2264 mycols = ibuf; 2265 if (size == 1) nz -= extra_rows; 2266 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2267 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2268 2269 /* insert into matrix */ 2270 jj = rstart*bs; 2271 for (i=0; i<m; i++) { 2272 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2273 mycols += locrowlens[i]; 2274 vals += locrowlens[i]; 2275 jj++; 2276 } 2277 2278 /* read in other processors (except the last one) and ship out */ 2279 for (i=1; i<size-1; i++) { 2280 nz = procsnz[i]; 2281 vals = buf; 2282 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2283 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2284 } 2285 /* the last proc */ 2286 if (size != 1){ 2287 nz = procsnz[i] - extra_rows; 2288 vals = buf; 2289 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2290 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2291 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2292 } 2293 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2294 2295 } else { 2296 /* receive numeric values */ 2297 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2298 2299 /* receive message of values*/ 2300 vals = buf; 2301 mycols = ibuf; 2302 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2303 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2304 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2305 2306 /* insert into matrix */ 2307 jj = rstart*bs; 2308 for (i=0; i<m; i++) { 2309 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2310 mycols += locrowlens[i]; 2311 vals += locrowlens[i]; 2312 jj++; 2313 } 2314 } 2315 2316 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2317 ierr = PetscFree(buf);CHKERRQ(ierr); 2318 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2319 ierr = PetscFree(rowners);CHKERRQ(ierr); 2320 ierr = PetscFree(dlens);CHKERRQ(ierr); 2321 ierr = PetscFree(mask);CHKERRQ(ierr); 2322 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2323 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2324 *newmat = A; 2325 PetscFunctionReturn(0); 2326 } 2327 2328 #undef __FUNCT__ 2329 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2330 /*XXXXX@ 2331 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2332 2333 Input Parameters: 2334 . mat - the matrix 2335 . fact - factor 2336 2337 Collective on Mat 2338 2339 Level: advanced 2340 2341 Notes: 2342 This can also be set by the command line option: -mat_use_hash_table fact 2343 2344 .keywords: matrix, hashtable, factor, HT 2345 2346 .seealso: MatSetOption() 2347 @XXXXX*/ 2348 2349 2350 #undef __FUNCT__ 2351 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2352 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2353 { 2354 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2355 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2356 PetscReal atmp; 2357 PetscReal *work,*svalues,*rvalues; 2358 PetscErrorCode ierr; 2359 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2360 PetscMPIInt rank,size; 2361 PetscInt *rowners_bs,dest,count,source; 2362 PetscScalar *va; 2363 MatScalar *ba; 2364 MPI_Status stat; 2365 2366 PetscFunctionBegin; 2367 if (idx) SETERRQ(PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2368 ierr = MatGetRowMaxAbs(a->A,v,PETSC_NULL);CHKERRQ(ierr); 2369 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2370 2371 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2372 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2373 2374 bs = A->rmap->bs; 2375 mbs = a->mbs; 2376 Mbs = a->Mbs; 2377 ba = b->a; 2378 bi = b->i; 2379 bj = b->j; 2380 2381 /* find ownerships */ 2382 rowners_bs = A->rmap->range; 2383 2384 /* each proc creates an array to be distributed */ 2385 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2386 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2387 2388 /* row_max for B */ 2389 if (rank != size-1){ 2390 for (i=0; i<mbs; i++) { 2391 ncols = bi[1] - bi[0]; bi++; 2392 brow = bs*i; 2393 for (j=0; j<ncols; j++){ 2394 bcol = bs*(*bj); 2395 for (kcol=0; kcol<bs; kcol++){ 2396 col = bcol + kcol; /* local col index */ 2397 col += rowners_bs[rank+1]; /* global col index */ 2398 for (krow=0; krow<bs; krow++){ 2399 atmp = PetscAbsScalar(*ba); ba++; 2400 row = brow + krow; /* local row index */ 2401 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2402 if (work[col] < atmp) work[col] = atmp; 2403 } 2404 } 2405 bj++; 2406 } 2407 } 2408 2409 /* send values to its owners */ 2410 for (dest=rank+1; dest<size; dest++){ 2411 svalues = work + rowners_bs[dest]; 2412 count = rowners_bs[dest+1]-rowners_bs[dest]; 2413 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);CHKERRQ(ierr); 2414 } 2415 } 2416 2417 /* receive values */ 2418 if (rank){ 2419 rvalues = work; 2420 count = rowners_bs[rank+1]-rowners_bs[rank]; 2421 for (source=0; source<rank; source++){ 2422 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);CHKERRQ(ierr); 2423 /* process values */ 2424 for (i=0; i<count; i++){ 2425 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2426 } 2427 } 2428 } 2429 2430 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2431 ierr = PetscFree(work);CHKERRQ(ierr); 2432 PetscFunctionReturn(0); 2433 } 2434 2435 #undef __FUNCT__ 2436 #define __FUNCT__ "MatRelax_MPISBAIJ" 2437 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2438 { 2439 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2440 PetscErrorCode ierr; 2441 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2442 PetscScalar *x,*b,*ptr,zero=0.0; 2443 Vec bb1; 2444 2445 PetscFunctionBegin; 2446 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2447 if (bs > 1) 2448 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2449 2450 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2451 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2452 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2453 its--; 2454 } 2455 2456 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2457 while (its--){ 2458 2459 /* lower triangular part: slvec0b = - B^T*xx */ 2460 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2461 2462 /* copy xx into slvec0a */ 2463 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2464 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2465 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2466 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2467 2468 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2469 2470 /* copy bb into slvec1a */ 2471 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2472 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2473 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2474 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2475 2476 /* set slvec1b = 0 */ 2477 ierr = VecSet(mat->slvec1b,zero);CHKERRQ(ierr); 2478 2479 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2480 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2481 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2482 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2483 2484 /* upper triangular part: bb1 = bb1 - B*x */ 2485 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2486 2487 /* local diagonal sweep */ 2488 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2489 } 2490 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2491 } else { 2492 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2493 } 2494 PetscFunctionReturn(0); 2495 } 2496 2497 #undef __FUNCT__ 2498 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2499 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2500 { 2501 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2502 PetscErrorCode ierr; 2503 Vec lvec1,bb1; 2504 2505 PetscFunctionBegin; 2506 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2507 if (matin->rmap->bs > 1) 2508 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2509 2510 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2511 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2512 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2513 its--; 2514 } 2515 2516 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2517 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2518 while (its--){ 2519 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2520 2521 /* lower diagonal part: bb1 = bb - B^T*xx */ 2522 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2523 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2524 2525 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2526 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2527 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2528 2529 /* upper diagonal part: bb1 = bb1 - B*x */ 2530 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2531 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2532 2533 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2534 2535 /* diagonal sweep */ 2536 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2537 } 2538 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2539 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2540 } else { 2541 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2542 } 2543 PetscFunctionReturn(0); 2544 } 2545 2546