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,Mat *B) 1217 { 1218 PetscErrorCode ierr; 1219 PetscFunctionBegin; 1220 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1221 PetscFunctionReturn(0); 1222 } 1223 1224 #undef __FUNCT__ 1225 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1226 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1227 { 1228 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1229 Mat a=baij->A, b=baij->B; 1230 PetscErrorCode ierr; 1231 PetscInt nv,m,n; 1232 PetscTruth flg; 1233 1234 PetscFunctionBegin; 1235 if (ll != rr){ 1236 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1237 if (!flg) 1238 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1239 } 1240 if (!ll) PetscFunctionReturn(0); 1241 1242 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1243 if (m != n) SETERRQ2(PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1244 1245 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1246 if (nv!=n) SETERRQ(PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1247 1248 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1249 1250 /* left diagonalscale the off-diagonal part */ 1251 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1252 1253 /* scale the diagonal part */ 1254 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1255 1256 /* right diagonalscale the off-diagonal part */ 1257 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1258 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #undef __FUNCT__ 1263 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1264 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1265 { 1266 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1267 PetscErrorCode ierr; 1268 1269 PetscFunctionBegin; 1270 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1271 PetscFunctionReturn(0); 1272 } 1273 1274 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatEqual_MPISBAIJ" 1278 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1279 { 1280 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1281 Mat a,b,c,d; 1282 PetscTruth flg; 1283 PetscErrorCode ierr; 1284 1285 PetscFunctionBegin; 1286 a = matA->A; b = matA->B; 1287 c = matB->A; d = matB->B; 1288 1289 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1290 if (flg) { 1291 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1292 } 1293 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1294 PetscFunctionReturn(0); 1295 } 1296 1297 #undef __FUNCT__ 1298 #define __FUNCT__ "MatCopy_MPISBAIJ" 1299 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1300 { 1301 PetscErrorCode ierr; 1302 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1303 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1304 1305 PetscFunctionBegin; 1306 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1307 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1308 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1309 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1310 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1311 } else { 1312 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1313 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1314 } 1315 PetscFunctionReturn(0); 1316 } 1317 1318 #undef __FUNCT__ 1319 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1320 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1321 { 1322 PetscErrorCode ierr; 1323 1324 PetscFunctionBegin; 1325 ierr = MatMPISBAIJSetPreallocation(A,PetscMax(A->rmap.bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1326 PetscFunctionReturn(0); 1327 } 1328 1329 #include "petscblaslapack.h" 1330 #undef __FUNCT__ 1331 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1332 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1333 { 1334 PetscErrorCode ierr; 1335 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data; 1336 PetscBLASInt bnz,one=1; 1337 Mat_SeqSBAIJ *xa,*ya; 1338 Mat_SeqBAIJ *xb,*yb; 1339 1340 PetscFunctionBegin; 1341 if (str == SAME_NONZERO_PATTERN) { 1342 PetscScalar alpha = a; 1343 xa = (Mat_SeqSBAIJ *)xx->A->data; 1344 ya = (Mat_SeqSBAIJ *)yy->A->data; 1345 bnz = PetscBLASIntCast(xa->nz); 1346 BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one); 1347 xb = (Mat_SeqBAIJ *)xx->B->data; 1348 yb = (Mat_SeqBAIJ *)yy->B->data; 1349 bnz = PetscBLASIntCast(xb->nz); 1350 BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one); 1351 } else { 1352 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1353 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1354 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1355 } 1356 PetscFunctionReturn(0); 1357 } 1358 1359 #undef __FUNCT__ 1360 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1361 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1362 { 1363 PetscErrorCode ierr; 1364 PetscInt i; 1365 PetscTruth flg; 1366 1367 PetscFunctionBegin; 1368 for (i=0; i<n; i++) { 1369 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1370 if (!flg) { 1371 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1372 } 1373 } 1374 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1375 PetscFunctionReturn(0); 1376 } 1377 1378 1379 /* -------------------------------------------------------------------*/ 1380 static struct _MatOps MatOps_Values = { 1381 MatSetValues_MPISBAIJ, 1382 MatGetRow_MPISBAIJ, 1383 MatRestoreRow_MPISBAIJ, 1384 MatMult_MPISBAIJ, 1385 /* 4*/ MatMultAdd_MPISBAIJ, 1386 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1387 MatMultAdd_MPISBAIJ, 1388 0, 1389 0, 1390 0, 1391 /*10*/ 0, 1392 0, 1393 0, 1394 MatRelax_MPISBAIJ, 1395 MatTranspose_MPISBAIJ, 1396 /*15*/ MatGetInfo_MPISBAIJ, 1397 MatEqual_MPISBAIJ, 1398 MatGetDiagonal_MPISBAIJ, 1399 MatDiagonalScale_MPISBAIJ, 1400 MatNorm_MPISBAIJ, 1401 /*20*/ MatAssemblyBegin_MPISBAIJ, 1402 MatAssemblyEnd_MPISBAIJ, 1403 0, 1404 MatSetOption_MPISBAIJ, 1405 MatZeroEntries_MPISBAIJ, 1406 /*25*/ 0, 1407 0, 1408 0, 1409 0, 1410 0, 1411 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1412 0, 1413 0, 1414 0, 1415 0, 1416 /*35*/ MatDuplicate_MPISBAIJ, 1417 0, 1418 0, 1419 0, 1420 0, 1421 /*40*/ MatAXPY_MPISBAIJ, 1422 MatGetSubMatrices_MPISBAIJ, 1423 MatIncreaseOverlap_MPISBAIJ, 1424 MatGetValues_MPISBAIJ, 1425 MatCopy_MPISBAIJ, 1426 /*45*/ 0, 1427 MatScale_MPISBAIJ, 1428 0, 1429 0, 1430 0, 1431 /*50*/ 0, 1432 0, 1433 0, 1434 0, 1435 0, 1436 /*55*/ 0, 1437 0, 1438 MatSetUnfactored_MPISBAIJ, 1439 0, 1440 MatSetValuesBlocked_MPISBAIJ, 1441 /*60*/ 0, 1442 0, 1443 0, 1444 0, 1445 0, 1446 /*65*/ 0, 1447 0, 1448 0, 1449 0, 1450 0, 1451 /*70*/ MatGetRowMaxAbs_MPISBAIJ, 1452 0, 1453 0, 1454 0, 1455 0, 1456 /*75*/ 0, 1457 0, 1458 0, 1459 0, 1460 0, 1461 /*80*/ 0, 1462 0, 1463 0, 1464 0, 1465 MatLoad_MPISBAIJ, 1466 /*85*/ 0, 1467 0, 1468 0, 1469 0, 1470 0, 1471 /*90*/ 0, 1472 0, 1473 0, 1474 0, 1475 0, 1476 /*95*/ 0, 1477 0, 1478 0, 1479 0, 1480 0, 1481 /*100*/0, 1482 0, 1483 0, 1484 0, 1485 0, 1486 /*105*/0, 1487 MatRealPart_MPISBAIJ, 1488 MatImaginaryPart_MPISBAIJ, 1489 MatGetRowUpperTriangular_MPISBAIJ, 1490 MatRestoreRowUpperTriangular_MPISBAIJ 1491 }; 1492 1493 1494 EXTERN_C_BEGIN 1495 #undef __FUNCT__ 1496 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1497 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1498 { 1499 PetscFunctionBegin; 1500 *a = ((Mat_MPISBAIJ *)A->data)->A; 1501 *iscopy = PETSC_FALSE; 1502 PetscFunctionReturn(0); 1503 } 1504 EXTERN_C_END 1505 1506 EXTERN_C_BEGIN 1507 #undef __FUNCT__ 1508 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1509 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1510 { 1511 Mat_MPISBAIJ *b; 1512 PetscErrorCode ierr; 1513 PetscInt i,mbs,Mbs; 1514 1515 PetscFunctionBegin; 1516 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");CHKERRQ(ierr); 1517 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 1518 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1519 1520 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1521 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1522 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1523 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1524 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1525 1526 B->rmap.bs = B->cmap.bs = bs; 1527 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 1528 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 1529 1530 if (d_nnz) { 1531 for (i=0; i<B->rmap.n/bs; i++) { 1532 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]); 1533 } 1534 } 1535 if (o_nnz) { 1536 for (i=0; i<B->rmap.n/bs; i++) { 1537 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]); 1538 } 1539 } 1540 B->preallocated = PETSC_TRUE; 1541 1542 b = (Mat_MPISBAIJ*)B->data; 1543 mbs = B->rmap.n/bs; 1544 Mbs = B->rmap.N/bs; 1545 if (mbs*bs != B->rmap.n) { 1546 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap.N,bs); 1547 } 1548 1549 B->rmap.bs = bs; 1550 b->bs2 = bs*bs; 1551 b->mbs = mbs; 1552 b->nbs = mbs; 1553 b->Mbs = Mbs; 1554 b->Nbs = Mbs; 1555 1556 for (i=0; i<=b->size; i++) { 1557 b->rangebs[i] = B->rmap.range[i]/bs; 1558 } 1559 b->rstartbs = B->rmap.rstart/bs; 1560 b->rendbs = B->rmap.rend/bs; 1561 1562 b->cstartbs = B->cmap.rstart/bs; 1563 b->cendbs = B->cmap.rend/bs; 1564 1565 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1566 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 1567 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1568 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1569 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1570 1571 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1572 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 1573 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1574 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1575 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1576 1577 /* build cache for off array entries formed */ 1578 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 1579 1580 PetscFunctionReturn(0); 1581 } 1582 EXTERN_C_END 1583 1584 /*MC 1585 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1586 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1587 1588 Options Database Keys: 1589 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1590 1591 Level: beginner 1592 1593 .seealso: MatCreateMPISBAIJ 1594 M*/ 1595 1596 EXTERN_C_BEGIN 1597 #undef __FUNCT__ 1598 #define __FUNCT__ "MatCreate_MPISBAIJ" 1599 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPISBAIJ(Mat B) 1600 { 1601 Mat_MPISBAIJ *b; 1602 PetscErrorCode ierr; 1603 PetscTruth flg; 1604 1605 PetscFunctionBegin; 1606 1607 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1608 B->data = (void*)b; 1609 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1610 1611 B->ops->destroy = MatDestroy_MPISBAIJ; 1612 B->ops->view = MatView_MPISBAIJ; 1613 B->mapping = 0; 1614 B->factor = 0; 1615 B->assembled = PETSC_FALSE; 1616 1617 B->insertmode = NOT_SET_VALUES; 1618 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 1619 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 1620 1621 /* build local table of row and column ownerships */ 1622 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1623 1624 /* build cache for off array entries formed */ 1625 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 1626 b->donotstash = PETSC_FALSE; 1627 b->colmap = PETSC_NULL; 1628 b->garray = PETSC_NULL; 1629 b->roworiented = PETSC_TRUE; 1630 1631 /* stuff used in block assembly */ 1632 b->barray = 0; 1633 1634 /* stuff used for matrix vector multiply */ 1635 b->lvec = 0; 1636 b->Mvctx = 0; 1637 b->slvec0 = 0; 1638 b->slvec0b = 0; 1639 b->slvec1 = 0; 1640 b->slvec1a = 0; 1641 b->slvec1b = 0; 1642 b->sMvctx = 0; 1643 1644 /* stuff for MatGetRow() */ 1645 b->rowindices = 0; 1646 b->rowvalues = 0; 1647 b->getrowactive = PETSC_FALSE; 1648 1649 /* hash table stuff */ 1650 b->ht = 0; 1651 b->hd = 0; 1652 b->ht_size = 0; 1653 b->ht_flag = PETSC_FALSE; 1654 b->ht_fact = 0; 1655 b->ht_total_ct = 0; 1656 b->ht_insert_ct = 0; 1657 1658 b->in_loc = 0; 1659 b->v_loc = 0; 1660 b->n_loc = 0; 1661 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1662 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1663 if (flg) { 1664 PetscReal fact = 1.39; 1665 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1666 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1667 if (fact <= 1.0) fact = 1.39; 1668 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1669 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1670 } 1671 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1672 1673 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1674 "MatStoreValues_MPISBAIJ", 1675 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1676 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1677 "MatRetrieveValues_MPISBAIJ", 1678 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1679 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1680 "MatGetDiagonalBlock_MPISBAIJ", 1681 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1682 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1683 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1684 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1685 B->symmetric = PETSC_TRUE; 1686 B->structurally_symmetric = PETSC_TRUE; 1687 B->symmetric_set = PETSC_TRUE; 1688 B->structurally_symmetric_set = PETSC_TRUE; 1689 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1690 PetscFunctionReturn(0); 1691 } 1692 EXTERN_C_END 1693 1694 /*MC 1695 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1696 1697 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1698 and MATMPISBAIJ otherwise. 1699 1700 Options Database Keys: 1701 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1702 1703 Level: beginner 1704 1705 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1706 M*/ 1707 1708 EXTERN_C_BEGIN 1709 #undef __FUNCT__ 1710 #define __FUNCT__ "MatCreate_SBAIJ" 1711 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SBAIJ(Mat A) 1712 { 1713 PetscErrorCode ierr; 1714 PetscMPIInt size; 1715 1716 PetscFunctionBegin; 1717 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 1718 if (size == 1) { 1719 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1720 } else { 1721 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1722 } 1723 PetscFunctionReturn(0); 1724 } 1725 EXTERN_C_END 1726 1727 #undef __FUNCT__ 1728 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1729 /*@C 1730 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1731 the user should preallocate the matrix storage by setting the parameters 1732 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1733 performance can be increased by more than a factor of 50. 1734 1735 Collective on Mat 1736 1737 Input Parameters: 1738 + A - the matrix 1739 . bs - size of blockk 1740 . d_nz - number of block nonzeros per block row in diagonal portion of local 1741 submatrix (same for all local rows) 1742 . d_nnz - array containing the number of block nonzeros in the various block rows 1743 in the upper triangular and diagonal part of the in diagonal portion of the local 1744 (possibly different for each block row) or PETSC_NULL. You must leave room 1745 for the diagonal entry even if it is zero. 1746 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1747 submatrix (same for all local rows). 1748 - o_nnz - array containing the number of nonzeros in the various block rows of the 1749 off-diagonal portion of the local submatrix (possibly different for 1750 each block row) or PETSC_NULL. 1751 1752 1753 Options Database Keys: 1754 . -mat_no_unroll - uses code that does not unroll the loops in the 1755 block calculations (much slower) 1756 . -mat_block_size - size of the blocks to use 1757 1758 Notes: 1759 1760 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1761 than it must be used on all processors that share the object for that argument. 1762 1763 If the *_nnz parameter is given then the *_nz parameter is ignored 1764 1765 Storage Information: 1766 For a square global matrix we define each processor's diagonal portion 1767 to be its local rows and the corresponding columns (a square submatrix); 1768 each processor's off-diagonal portion encompasses the remainder of the 1769 local matrix (a rectangular submatrix). 1770 1771 The user can specify preallocated storage for the diagonal part of 1772 the local submatrix with either d_nz or d_nnz (not both). Set 1773 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1774 memory allocation. Likewise, specify preallocated storage for the 1775 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1776 1777 You can call MatGetInfo() to get information on how effective the preallocation was; 1778 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1779 You can also run with the option -info and look for messages with the string 1780 malloc in them to see if additional memory allocation was needed. 1781 1782 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1783 the figure below we depict these three local rows and all columns (0-11). 1784 1785 .vb 1786 0 1 2 3 4 5 6 7 8 9 10 11 1787 ------------------- 1788 row 3 | o o o d d d o o o o o o 1789 row 4 | o o o d d d o o o o o o 1790 row 5 | o o o d d d o o o o o o 1791 ------------------- 1792 .ve 1793 1794 Thus, any entries in the d locations are stored in the d (diagonal) 1795 submatrix, and any entries in the o locations are stored in the 1796 o (off-diagonal) submatrix. Note that the d matrix is stored in 1797 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1798 1799 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1800 plus the diagonal part of the d matrix, 1801 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1802 In general, for PDE problems in which most nonzeros are near the diagonal, 1803 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1804 or you will get TERRIBLE performance; see the users' manual chapter on 1805 matrices. 1806 1807 Level: intermediate 1808 1809 .keywords: matrix, block, aij, compressed row, sparse, parallel 1810 1811 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1812 @*/ 1813 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1814 { 1815 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1816 1817 PetscFunctionBegin; 1818 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1819 if (f) { 1820 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1821 } 1822 PetscFunctionReturn(0); 1823 } 1824 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatCreateMPISBAIJ" 1827 /*@C 1828 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1829 (block compressed row). For good matrix assembly performance 1830 the user should preallocate the matrix storage by setting the parameters 1831 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1832 performance can be increased by more than a factor of 50. 1833 1834 Collective on MPI_Comm 1835 1836 Input Parameters: 1837 + comm - MPI communicator 1838 . bs - size of blockk 1839 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1840 This value should be the same as the local size used in creating the 1841 y vector for the matrix-vector product y = Ax. 1842 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1843 This value should be the same as the local size used in creating the 1844 x vector for the matrix-vector product y = Ax. 1845 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1846 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1847 . d_nz - number of block nonzeros per block row in diagonal portion of local 1848 submatrix (same for all local rows) 1849 . d_nnz - array containing the number of block nonzeros in the various block rows 1850 in the upper triangular portion of the in diagonal portion of the local 1851 (possibly different for each block block row) or PETSC_NULL. 1852 You must leave room for the diagonal entry even if it is zero. 1853 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1854 submatrix (same for all local rows). 1855 - o_nnz - array containing the number of nonzeros in the various block rows of the 1856 off-diagonal portion of the local submatrix (possibly different for 1857 each block row) or PETSC_NULL. 1858 1859 Output Parameter: 1860 . A - the matrix 1861 1862 Options Database Keys: 1863 . -mat_no_unroll - uses code that does not unroll the loops in the 1864 block calculations (much slower) 1865 . -mat_block_size - size of the blocks to use 1866 . -mat_mpi - use the parallel matrix data structures even on one processor 1867 (defaults to using SeqBAIJ format on one processor) 1868 1869 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1870 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 1871 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 1872 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1873 1874 Notes: 1875 The number of rows and columns must be divisible by blocksize. 1876 This matrix type does not support complex Hermitian operation. 1877 1878 The user MUST specify either the local or global matrix dimensions 1879 (possibly both). 1880 1881 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1882 than it must be used on all processors that share the object for that argument. 1883 1884 If the *_nnz parameter is given then the *_nz parameter is ignored 1885 1886 Storage Information: 1887 For a square global matrix we define each processor's diagonal portion 1888 to be its local rows and the corresponding columns (a square submatrix); 1889 each processor's off-diagonal portion encompasses the remainder of the 1890 local matrix (a rectangular submatrix). 1891 1892 The user can specify preallocated storage for the diagonal part of 1893 the local submatrix with either d_nz or d_nnz (not both). Set 1894 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1895 memory allocation. Likewise, specify preallocated storage for the 1896 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1897 1898 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1899 the figure below we depict these three local rows and all columns (0-11). 1900 1901 .vb 1902 0 1 2 3 4 5 6 7 8 9 10 11 1903 ------------------- 1904 row 3 | o o o d d d o o o o o o 1905 row 4 | o o o d d d o o o o o o 1906 row 5 | o o o d d d o o o o o o 1907 ------------------- 1908 .ve 1909 1910 Thus, any entries in the d locations are stored in the d (diagonal) 1911 submatrix, and any entries in the o locations are stored in the 1912 o (off-diagonal) submatrix. Note that the d matrix is stored in 1913 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1914 1915 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1916 plus the diagonal part of the d matrix, 1917 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1918 In general, for PDE problems in which most nonzeros are near the diagonal, 1919 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1920 or you will get TERRIBLE performance; see the users' manual chapter on 1921 matrices. 1922 1923 Level: intermediate 1924 1925 .keywords: matrix, block, aij, compressed row, sparse, parallel 1926 1927 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1928 @*/ 1929 1930 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) 1931 { 1932 PetscErrorCode ierr; 1933 PetscMPIInt size; 1934 1935 PetscFunctionBegin; 1936 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1937 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1938 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1939 if (size > 1) { 1940 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1941 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1942 } else { 1943 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1944 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1945 } 1946 PetscFunctionReturn(0); 1947 } 1948 1949 1950 #undef __FUNCT__ 1951 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1952 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1953 { 1954 Mat mat; 1955 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1956 PetscErrorCode ierr; 1957 PetscInt len=0,nt,bs=matin->rmap.bs,mbs=oldmat->mbs; 1958 PetscScalar *array; 1959 1960 PetscFunctionBegin; 1961 *newmat = 0; 1962 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 1963 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 1964 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 1965 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1966 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 1967 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 1968 1969 mat->factor = matin->factor; 1970 mat->preallocated = PETSC_TRUE; 1971 mat->assembled = PETSC_TRUE; 1972 mat->insertmode = NOT_SET_VALUES; 1973 1974 a = (Mat_MPISBAIJ*)mat->data; 1975 a->bs2 = oldmat->bs2; 1976 a->mbs = oldmat->mbs; 1977 a->nbs = oldmat->nbs; 1978 a->Mbs = oldmat->Mbs; 1979 a->Nbs = oldmat->Nbs; 1980 1981 1982 a->size = oldmat->size; 1983 a->rank = oldmat->rank; 1984 a->donotstash = oldmat->donotstash; 1985 a->roworiented = oldmat->roworiented; 1986 a->rowindices = 0; 1987 a->rowvalues = 0; 1988 a->getrowactive = PETSC_FALSE; 1989 a->barray = 0; 1990 a->rstartbs = oldmat->rstartbs; 1991 a->rendbs = oldmat->rendbs; 1992 a->cstartbs = oldmat->cstartbs; 1993 a->cendbs = oldmat->cendbs; 1994 1995 /* hash table stuff */ 1996 a->ht = 0; 1997 a->hd = 0; 1998 a->ht_size = 0; 1999 a->ht_flag = oldmat->ht_flag; 2000 a->ht_fact = oldmat->ht_fact; 2001 a->ht_total_ct = 0; 2002 a->ht_insert_ct = 0; 2003 2004 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2005 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2006 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap.bs,&mat->bstash);CHKERRQ(ierr); 2007 if (oldmat->colmap) { 2008 #if defined (PETSC_USE_CTABLE) 2009 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2010 #else 2011 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2012 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2013 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2014 #endif 2015 } else a->colmap = 0; 2016 2017 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2018 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2019 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2020 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2021 } else a->garray = 0; 2022 2023 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2024 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2025 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2026 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2027 2028 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2029 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2030 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2031 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2032 2033 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2034 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2035 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2036 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2037 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2038 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2039 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2040 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2041 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2042 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2043 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2044 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2045 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2046 2047 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2048 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2049 a->sMvctx = oldmat->sMvctx; 2050 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2051 2052 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2053 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2054 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2055 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2056 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2057 *newmat = mat; 2058 PetscFunctionReturn(0); 2059 } 2060 2061 #include "petscsys.h" 2062 2063 #undef __FUNCT__ 2064 #define __FUNCT__ "MatLoad_MPISBAIJ" 2065 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2066 { 2067 Mat A; 2068 PetscErrorCode ierr; 2069 PetscInt i,nz,j,rstart,rend; 2070 PetscScalar *vals,*buf; 2071 MPI_Comm comm = ((PetscObject)viewer)->comm; 2072 MPI_Status status; 2073 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens,mmbs; 2074 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2075 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2076 PetscInt bs=1,Mbs,mbs,extra_rows; 2077 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2078 PetscInt dcount,kmax,k,nzcount,tmp; 2079 int fd; 2080 2081 PetscFunctionBegin; 2082 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2083 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2084 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2085 2086 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2087 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2088 if (!rank) { 2089 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2090 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2091 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2092 if (header[3] < 0) { 2093 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2094 } 2095 } 2096 2097 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2098 M = header[1]; N = header[2]; 2099 2100 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2101 2102 /* 2103 This code adds extra rows to make sure the number of rows is 2104 divisible by the blocksize 2105 */ 2106 Mbs = M/bs; 2107 extra_rows = bs - M + bs*(Mbs); 2108 if (extra_rows == bs) extra_rows = 0; 2109 else Mbs++; 2110 if (extra_rows &&!rank) { 2111 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2112 } 2113 2114 /* determine ownership of all rows */ 2115 mbs = Mbs/size + ((Mbs % size) > rank); 2116 m = mbs*bs; 2117 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2118 browners = rowners + size + 1; 2119 mmbs = PetscMPIIntCast(mbs); 2120 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2121 rowners[0] = 0; 2122 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2123 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2124 rstart = rowners[rank]; 2125 rend = rowners[rank+1]; 2126 2127 /* distribute row lengths to all processors */ 2128 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);CHKERRQ(ierr); 2129 if (!rank) { 2130 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2131 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2132 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2133 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2134 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2135 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2136 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2137 } else { 2138 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2139 } 2140 2141 if (!rank) { /* procs[0] */ 2142 /* calculate the number of nonzeros on each processor */ 2143 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2144 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2145 for (i=0; i<size; i++) { 2146 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2147 procsnz[i] += rowlengths[j]; 2148 } 2149 } 2150 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2151 2152 /* determine max buffer needed and allocate it */ 2153 maxnz = 0; 2154 for (i=0; i<size; i++) { 2155 maxnz = PetscMax(maxnz,procsnz[i]); 2156 } 2157 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2158 2159 /* read in my part of the matrix column indices */ 2160 nz = procsnz[0]; 2161 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2162 mycols = ibuf; 2163 if (size == 1) nz -= extra_rows; 2164 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2165 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2166 2167 /* read in every ones (except the last) and ship off */ 2168 for (i=1; i<size-1; i++) { 2169 nz = procsnz[i]; 2170 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2171 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2172 } 2173 /* read in the stuff for the last proc */ 2174 if (size != 1) { 2175 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2176 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2177 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2178 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2179 } 2180 ierr = PetscFree(cols);CHKERRQ(ierr); 2181 } else { /* procs[i], i>0 */ 2182 /* determine buffer space needed for message */ 2183 nz = 0; 2184 for (i=0; i<m; i++) { 2185 nz += locrowlens[i]; 2186 } 2187 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2188 mycols = ibuf; 2189 /* receive message of column indices*/ 2190 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2191 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2192 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2193 } 2194 2195 /* loop over local rows, determining number of off diagonal entries */ 2196 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2197 odlens = dlens + (rend-rstart); 2198 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2199 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2200 masked1 = mask + Mbs; 2201 masked2 = masked1 + Mbs; 2202 rowcount = 0; nzcount = 0; 2203 for (i=0; i<mbs; i++) { 2204 dcount = 0; 2205 odcount = 0; 2206 for (j=0; j<bs; j++) { 2207 kmax = locrowlens[rowcount]; 2208 for (k=0; k<kmax; k++) { 2209 tmp = mycols[nzcount++]/bs; /* block col. index */ 2210 if (!mask[tmp]) { 2211 mask[tmp] = 1; 2212 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2213 else masked1[dcount++] = tmp; /* entry in diag portion */ 2214 } 2215 } 2216 rowcount++; 2217 } 2218 2219 dlens[i] = dcount; /* d_nzz[i] */ 2220 odlens[i] = odcount; /* o_nzz[i] */ 2221 2222 /* zero out the mask elements we set */ 2223 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2224 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2225 } 2226 2227 /* create our matrix */ 2228 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2229 ierr = MatSetSizes(A,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2230 ierr = MatSetType(A,type);CHKERRQ(ierr); 2231 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2232 2233 if (!rank) { 2234 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2235 /* read in my part of the matrix numerical values */ 2236 nz = procsnz[0]; 2237 vals = buf; 2238 mycols = ibuf; 2239 if (size == 1) nz -= extra_rows; 2240 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2241 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2242 2243 /* insert into matrix */ 2244 jj = rstart*bs; 2245 for (i=0; i<m; i++) { 2246 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2247 mycols += locrowlens[i]; 2248 vals += locrowlens[i]; 2249 jj++; 2250 } 2251 2252 /* read in other processors (except the last one) and ship out */ 2253 for (i=1; i<size-1; i++) { 2254 nz = procsnz[i]; 2255 vals = buf; 2256 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2257 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2258 } 2259 /* the last proc */ 2260 if (size != 1){ 2261 nz = procsnz[i] - extra_rows; 2262 vals = buf; 2263 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2264 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2265 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2266 } 2267 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2268 2269 } else { 2270 /* receive numeric values */ 2271 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2272 2273 /* receive message of values*/ 2274 vals = buf; 2275 mycols = ibuf; 2276 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2277 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2278 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2279 2280 /* insert into matrix */ 2281 jj = rstart*bs; 2282 for (i=0; i<m; i++) { 2283 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2284 mycols += locrowlens[i]; 2285 vals += locrowlens[i]; 2286 jj++; 2287 } 2288 } 2289 2290 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2291 ierr = PetscFree(buf);CHKERRQ(ierr); 2292 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2293 ierr = PetscFree(rowners);CHKERRQ(ierr); 2294 ierr = PetscFree(dlens);CHKERRQ(ierr); 2295 ierr = PetscFree(mask);CHKERRQ(ierr); 2296 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2297 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2298 *newmat = A; 2299 PetscFunctionReturn(0); 2300 } 2301 2302 #undef __FUNCT__ 2303 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2304 /*XXXXX@ 2305 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2306 2307 Input Parameters: 2308 . mat - the matrix 2309 . fact - factor 2310 2311 Collective on Mat 2312 2313 Level: advanced 2314 2315 Notes: 2316 This can also be set by the command line option: -mat_use_hash_table fact 2317 2318 .keywords: matrix, hashtable, factor, HT 2319 2320 .seealso: MatSetOption() 2321 @XXXXX*/ 2322 2323 2324 #undef __FUNCT__ 2325 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2326 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2327 { 2328 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2329 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2330 PetscReal atmp; 2331 PetscReal *work,*svalues,*rvalues; 2332 PetscErrorCode ierr; 2333 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2334 PetscMPIInt rank,size; 2335 PetscInt *rowners_bs,dest,count,source; 2336 PetscScalar *va; 2337 MatScalar *ba; 2338 MPI_Status stat; 2339 2340 PetscFunctionBegin; 2341 if (idx) SETERRQ(PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2342 ierr = MatGetRowMaxAbs(a->A,v,PETSC_NULL);CHKERRQ(ierr); 2343 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2344 2345 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2346 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2347 2348 bs = A->rmap.bs; 2349 mbs = a->mbs; 2350 Mbs = a->Mbs; 2351 ba = b->a; 2352 bi = b->i; 2353 bj = b->j; 2354 2355 /* find ownerships */ 2356 rowners_bs = A->rmap.range; 2357 2358 /* each proc creates an array to be distributed */ 2359 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2360 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2361 2362 /* row_max for B */ 2363 if (rank != size-1){ 2364 for (i=0; i<mbs; i++) { 2365 ncols = bi[1] - bi[0]; bi++; 2366 brow = bs*i; 2367 for (j=0; j<ncols; j++){ 2368 bcol = bs*(*bj); 2369 for (kcol=0; kcol<bs; kcol++){ 2370 col = bcol + kcol; /* local col index */ 2371 col += rowners_bs[rank+1]; /* global col index */ 2372 for (krow=0; krow<bs; krow++){ 2373 atmp = PetscAbsScalar(*ba); ba++; 2374 row = brow + krow; /* local row index */ 2375 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2376 if (work[col] < atmp) work[col] = atmp; 2377 } 2378 } 2379 bj++; 2380 } 2381 } 2382 2383 /* send values to its owners */ 2384 for (dest=rank+1; dest<size; dest++){ 2385 svalues = work + rowners_bs[dest]; 2386 count = rowners_bs[dest+1]-rowners_bs[dest]; 2387 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);CHKERRQ(ierr); 2388 } 2389 } 2390 2391 /* receive values */ 2392 if (rank){ 2393 rvalues = work; 2394 count = rowners_bs[rank+1]-rowners_bs[rank]; 2395 for (source=0; source<rank; source++){ 2396 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);CHKERRQ(ierr); 2397 /* process values */ 2398 for (i=0; i<count; i++){ 2399 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2400 } 2401 } 2402 } 2403 2404 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2405 ierr = PetscFree(work);CHKERRQ(ierr); 2406 PetscFunctionReturn(0); 2407 } 2408 2409 #undef __FUNCT__ 2410 #define __FUNCT__ "MatRelax_MPISBAIJ" 2411 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2412 { 2413 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2414 PetscErrorCode ierr; 2415 PetscInt mbs=mat->mbs,bs=matin->rmap.bs; 2416 PetscScalar *x,*b,*ptr,zero=0.0; 2417 Vec bb1; 2418 2419 PetscFunctionBegin; 2420 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2421 if (bs > 1) 2422 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2423 2424 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2425 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2426 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2427 its--; 2428 } 2429 2430 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2431 while (its--){ 2432 2433 /* lower triangular part: slvec0b = - B^T*xx */ 2434 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2435 2436 /* copy xx into slvec0a */ 2437 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2438 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2439 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2440 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2441 2442 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2443 2444 /* copy bb into slvec1a */ 2445 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2446 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2447 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2448 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2449 2450 /* set slvec1b = 0 */ 2451 ierr = VecSet(mat->slvec1b,zero);CHKERRQ(ierr); 2452 2453 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2454 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2455 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2456 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2457 2458 /* upper triangular part: bb1 = bb1 - B*x */ 2459 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2460 2461 /* local diagonal sweep */ 2462 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2463 } 2464 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2465 } else { 2466 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2467 } 2468 PetscFunctionReturn(0); 2469 } 2470 2471 #undef __FUNCT__ 2472 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2473 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2474 { 2475 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2476 PetscErrorCode ierr; 2477 Vec lvec1,bb1; 2478 2479 PetscFunctionBegin; 2480 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2481 if (matin->rmap.bs > 1) 2482 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2483 2484 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2485 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2486 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2487 its--; 2488 } 2489 2490 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2491 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2492 while (its--){ 2493 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2494 2495 /* lower diagonal part: bb1 = bb - B^T*xx */ 2496 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2497 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2498 2499 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2500 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2501 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2502 2503 /* upper diagonal part: bb1 = bb1 - B*x */ 2504 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2505 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2506 2507 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2508 2509 /* diagonal sweep */ 2510 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2511 } 2512 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2513 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2514 } else { 2515 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2516 } 2517 PetscFunctionReturn(0); 2518 } 2519 2520