1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/aij/mpi/mpiaij.h" /*I "petscmat.h" I*/ 4 #include "src/inline/spops.h" 5 6 #undef __FUNCT__ 7 #define __FUNCT__ "MatDistribute_MPIAIJ" 8 /* 9 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 10 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 11 12 Only for square matrices 13 */ 14 PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 15 { 16 PetscMPIInt rank,size; 17 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld; 18 PetscErrorCode ierr; 19 Mat mat; 20 Mat_SeqAIJ *gmata; 21 PetscMPIInt tag; 22 MPI_Status status; 23 PetscTruth aij; 24 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 25 26 PetscFunctionBegin; 27 CHKMEMQ; 28 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 29 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 30 if (!rank) { 31 ierr = PetscTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 32 if (!aij) SETERRQ1(PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 33 } 34 if (reuse == MAT_INITIAL_MATRIX) { 35 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 36 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 37 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 38 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 39 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 40 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 41 rowners[0] = 0; 42 for (i=2; i<=size; i++) { 43 rowners[i] += rowners[i-1]; 44 } 45 rstart = rowners[rank]; 46 rend = rowners[rank+1]; 47 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 48 if (!rank) { 49 gmata = (Mat_SeqAIJ*) gmat->data; 50 /* send row lengths to all processors */ 51 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 52 for (i=1; i<size; i++) { 53 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 54 } 55 /* determine number diagonal and off-diagonal counts */ 56 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 57 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 58 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 59 jj = 0; 60 for (i=0; i<m; i++) { 61 for (j=0; j<dlens[i]; j++) { 62 if (gmata->j[jj] < rstart) ld[i]++; 63 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 64 jj++; 65 } 66 } 67 /* send column indices to other processes */ 68 for (i=1; i<size; i++) { 69 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 70 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 71 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 72 } 73 74 /* send numerical values to other processes */ 75 for (i=1; i<size; i++) { 76 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 77 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 78 } 79 gmataa = gmata->a; 80 gmataj = gmata->j; 81 82 } else { 83 /* receive row lengths */ 84 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 85 /* receive column indices */ 86 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 87 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 88 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 89 /* determine number diagonal and off-diagonal counts */ 90 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 91 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 92 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 93 jj = 0; 94 for (i=0; i<m; i++) { 95 for (j=0; j<dlens[i]; j++) { 96 if (gmataj[jj] < rstart) ld[i]++; 97 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 98 jj++; 99 } 100 } 101 /* receive numerical values */ 102 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 103 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 104 } 105 /* set preallocation */ 106 for (i=0; i<m; i++) { 107 dlens[i] -= olens[i]; 108 } 109 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 110 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 111 112 for (i=0; i<m; i++) { 113 dlens[i] += olens[i]; 114 } 115 cnt = 0; 116 for (i=0; i<m; i++) { 117 row = rstart + i; 118 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 119 cnt += dlens[i]; 120 } 121 if (rank) { 122 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 123 } 124 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 125 ierr = PetscFree(rowners);CHKERRQ(ierr); 126 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 127 *inmat = mat; 128 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 129 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 130 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 131 mat = *inmat; 132 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 133 if (!rank) { 134 /* send numerical values to other processes */ 135 gmata = (Mat_SeqAIJ*) gmat->data; 136 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 137 gmataa = gmata->a; 138 for (i=1; i<size; i++) { 139 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 140 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 141 } 142 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 143 } else { 144 /* receive numerical values from process 0*/ 145 nz = Ad->nz + Ao->nz; 146 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 147 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 148 } 149 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 150 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 151 ad = Ad->a; 152 ao = Ao->a; 153 if (mat->rmap.n) { 154 i = 0; 155 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 156 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 157 } 158 for (i=1; i<mat->rmap.n; i++) { 159 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 160 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 161 } 162 i--; 163 if (mat->rmap.n) { 164 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 165 } 166 if (rank) { 167 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 168 } 169 } 170 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 171 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 172 CHKMEMQ; 173 PetscFunctionReturn(0); 174 } 175 176 /* 177 Local utility routine that creates a mapping from the global column 178 number to the local number in the off-diagonal part of the local 179 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 180 a slightly higher hash table cost; without it it is not scalable (each processor 181 has an order N integer array but is fast to acess. 182 */ 183 #undef __FUNCT__ 184 #define __FUNCT__ "CreateColmap_MPIAIJ_Private" 185 PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat) 186 { 187 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 188 PetscErrorCode ierr; 189 PetscInt n = aij->B->cmap.n,i; 190 191 PetscFunctionBegin; 192 #if defined (PETSC_USE_CTABLE) 193 ierr = PetscTableCreate(n,&aij->colmap);CHKERRQ(ierr); 194 for (i=0; i<n; i++){ 195 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);CHKERRQ(ierr); 196 } 197 #else 198 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 199 ierr = PetscLogObjectMemory(mat,mat->cmap.N*sizeof(PetscInt));CHKERRQ(ierr); 200 ierr = PetscMemzero(aij->colmap,mat->cmap.N*sizeof(PetscInt));CHKERRQ(ierr); 201 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 202 #endif 203 PetscFunctionReturn(0); 204 } 205 206 207 #define CHUNKSIZE 15 208 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 209 { \ 210 if (col <= lastcol1) low1 = 0; else high1 = nrow1; \ 211 lastcol1 = col;\ 212 while (high1-low1 > 5) { \ 213 t = (low1+high1)/2; \ 214 if (rp1[t] > col) high1 = t; \ 215 else low1 = t; \ 216 } \ 217 for (_i=low1; _i<high1; _i++) { \ 218 if (rp1[_i] > col) break; \ 219 if (rp1[_i] == col) { \ 220 if (addv == ADD_VALUES) ap1[_i] += value; \ 221 else ap1[_i] = value; \ 222 goto a_noinsert; \ 223 } \ 224 } \ 225 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 226 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 227 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 228 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 229 N = nrow1++ - 1; a->nz++; high1++; \ 230 /* shift up all the later entries in this row */ \ 231 for (ii=N; ii>=_i; ii--) { \ 232 rp1[ii+1] = rp1[ii]; \ 233 ap1[ii+1] = ap1[ii]; \ 234 } \ 235 rp1[_i] = col; \ 236 ap1[_i] = value; \ 237 a_noinsert: ; \ 238 ailen[row] = nrow1; \ 239 } 240 241 242 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 243 { \ 244 if (col <= lastcol2) low2 = 0; else high2 = nrow2; \ 245 lastcol2 = col;\ 246 while (high2-low2 > 5) { \ 247 t = (low2+high2)/2; \ 248 if (rp2[t] > col) high2 = t; \ 249 else low2 = t; \ 250 } \ 251 for (_i=low2; _i<high2; _i++) { \ 252 if (rp2[_i] > col) break; \ 253 if (rp2[_i] == col) { \ 254 if (addv == ADD_VALUES) ap2[_i] += value; \ 255 else ap2[_i] = value; \ 256 goto b_noinsert; \ 257 } \ 258 } \ 259 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 260 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 261 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 262 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 263 N = nrow2++ - 1; b->nz++; high2++; \ 264 /* shift up all the later entries in this row */ \ 265 for (ii=N; ii>=_i; ii--) { \ 266 rp2[ii+1] = rp2[ii]; \ 267 ap2[ii+1] = ap2[ii]; \ 268 } \ 269 rp2[_i] = col; \ 270 ap2[_i] = value; \ 271 b_noinsert: ; \ 272 bilen[row] = nrow2; \ 273 } 274 275 #undef __FUNCT__ 276 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 277 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 278 { 279 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 280 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 281 PetscErrorCode ierr; 282 PetscInt l,*garray = mat->garray,diag; 283 284 PetscFunctionBegin; 285 /* code only works for square matrices A */ 286 287 /* find size of row to the left of the diagonal part */ 288 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 289 row = row - diag; 290 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 291 if (garray[b->j[b->i[row]+l]] > diag) break; 292 } 293 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 294 295 /* diagonal part */ 296 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 297 298 /* right of diagonal part */ 299 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 300 PetscFunctionReturn(0); 301 } 302 303 #undef __FUNCT__ 304 #define __FUNCT__ "MatSetValues_MPIAIJ" 305 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 306 { 307 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 308 PetscScalar value; 309 PetscErrorCode ierr; 310 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 311 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 312 PetscTruth roworiented = aij->roworiented; 313 314 /* Some Variables required in the macro */ 315 Mat A = aij->A; 316 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 317 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 318 MatScalar *aa = a->a; 319 PetscTruth ignorezeroentries = a->ignorezeroentries; 320 Mat B = aij->B; 321 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 322 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 323 MatScalar *ba = b->a; 324 325 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 326 PetscInt nonew = a->nonew; 327 MatScalar *ap1,*ap2; 328 329 PetscFunctionBegin; 330 for (i=0; i<m; i++) { 331 if (im[i] < 0) continue; 332 #if defined(PETSC_USE_DEBUG) 333 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 334 #endif 335 if (im[i] >= rstart && im[i] < rend) { 336 row = im[i] - rstart; 337 lastcol1 = -1; 338 rp1 = aj + ai[row]; 339 ap1 = aa + ai[row]; 340 rmax1 = aimax[row]; 341 nrow1 = ailen[row]; 342 low1 = 0; 343 high1 = nrow1; 344 lastcol2 = -1; 345 rp2 = bj + bi[row]; 346 ap2 = ba + bi[row]; 347 rmax2 = bimax[row]; 348 nrow2 = bilen[row]; 349 low2 = 0; 350 high2 = nrow2; 351 352 for (j=0; j<n; j++) { 353 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 354 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 355 if (in[j] >= cstart && in[j] < cend){ 356 col = in[j] - cstart; 357 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 358 } else if (in[j] < 0) continue; 359 #if defined(PETSC_USE_DEBUG) 360 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);} 361 #endif 362 else { 363 if (mat->was_assembled) { 364 if (!aij->colmap) { 365 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 366 } 367 #if defined (PETSC_USE_CTABLE) 368 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 369 col--; 370 #else 371 col = aij->colmap[in[j]] - 1; 372 #endif 373 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 374 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 375 col = in[j]; 376 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 377 B = aij->B; 378 b = (Mat_SeqAIJ*)B->data; 379 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 380 rp2 = bj + bi[row]; 381 ap2 = ba + bi[row]; 382 rmax2 = bimax[row]; 383 nrow2 = bilen[row]; 384 low2 = 0; 385 high2 = nrow2; 386 bm = aij->B->rmap.n; 387 ba = b->a; 388 } 389 } else col = in[j]; 390 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 391 } 392 } 393 } else { 394 if (!aij->donotstash) { 395 if (roworiented) { 396 if (ignorezeroentries && v[i*n] == 0.0) continue; 397 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 398 } else { 399 if (ignorezeroentries && v[i] == 0.0) continue; 400 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 401 } 402 } 403 } 404 } 405 PetscFunctionReturn(0); 406 } 407 408 #undef __FUNCT__ 409 #define __FUNCT__ "MatGetValues_MPIAIJ" 410 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 411 { 412 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 413 PetscErrorCode ierr; 414 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 415 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 416 417 PetscFunctionBegin; 418 for (i=0; i<m; i++) { 419 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 420 if (idxm[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap.N-1); 421 if (idxm[i] >= rstart && idxm[i] < rend) { 422 row = idxm[i] - rstart; 423 for (j=0; j<n; j++) { 424 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 425 if (idxn[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap.N-1); 426 if (idxn[j] >= cstart && idxn[j] < cend){ 427 col = idxn[j] - cstart; 428 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 429 } else { 430 if (!aij->colmap) { 431 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 432 } 433 #if defined (PETSC_USE_CTABLE) 434 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 435 col --; 436 #else 437 col = aij->colmap[idxn[j]] - 1; 438 #endif 439 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 440 else { 441 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 442 } 443 } 444 } 445 } else { 446 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 447 } 448 } 449 PetscFunctionReturn(0); 450 } 451 452 #undef __FUNCT__ 453 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 454 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 455 { 456 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 457 PetscErrorCode ierr; 458 PetscInt nstash,reallocs; 459 InsertMode addv; 460 461 PetscFunctionBegin; 462 if (aij->donotstash) { 463 PetscFunctionReturn(0); 464 } 465 466 /* make sure all processors are either in INSERTMODE or ADDMODE */ 467 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 468 if (addv == (ADD_VALUES|INSERT_VALUES)) { 469 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 470 } 471 mat->insertmode = addv; /* in case this processor had no cache */ 472 473 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap.range);CHKERRQ(ierr); 474 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 475 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 481 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data; 485 PetscErrorCode ierr; 486 PetscMPIInt n; 487 PetscInt i,j,rstart,ncols,flg; 488 PetscInt *row,*col; 489 PetscTruth other_disassembled; 490 PetscScalar *val; 491 InsertMode addv = mat->insertmode; 492 493 /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */ 494 PetscFunctionBegin; 495 if (!aij->donotstash) { 496 while (1) { 497 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 498 if (!flg) break; 499 500 for (i=0; i<n;) { 501 /* Now identify the consecutive vals belonging to the same row */ 502 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 503 if (j < n) ncols = j-i; 504 else ncols = n-i; 505 /* Now assemble all these values with a single function call */ 506 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 507 i = j; 508 } 509 } 510 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 511 } 512 a->compressedrow.use = PETSC_FALSE; 513 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 514 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 515 516 /* determine if any processor has disassembled, if so we must 517 also disassemble ourselfs, in order that we may reassemble. */ 518 /* 519 if nonzero structure of submatrix B cannot change then we know that 520 no processor disassembled thus we can skip this stuff 521 */ 522 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 523 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 524 if (mat->was_assembled && !other_disassembled) { 525 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 526 } 527 } 528 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 529 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 530 } 531 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 532 ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 533 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 534 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 535 536 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 537 aij->rowvalues = 0; 538 539 /* used by MatAXPY() */ 540 a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 541 a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 542 543 PetscFunctionReturn(0); 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 548 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 549 { 550 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 551 PetscErrorCode ierr; 552 553 PetscFunctionBegin; 554 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 555 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 556 PetscFunctionReturn(0); 557 } 558 559 #undef __FUNCT__ 560 #define __FUNCT__ "MatZeroRows_MPIAIJ" 561 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 562 { 563 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 564 PetscErrorCode ierr; 565 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 566 PetscInt i,*owners = A->rmap.range; 567 PetscInt *nprocs,j,idx,nsends,row; 568 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 569 PetscInt *rvalues,count,base,slen,*source; 570 PetscInt *lens,*lrows,*values,rstart=A->rmap.rstart; 571 MPI_Comm comm = ((PetscObject)A)->comm; 572 MPI_Request *send_waits,*recv_waits; 573 MPI_Status recv_status,*send_status; 574 #if defined(PETSC_DEBUG) 575 PetscTruth found = PETSC_FALSE; 576 #endif 577 578 PetscFunctionBegin; 579 /* first count number of contributors to each processor */ 580 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 581 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 582 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 583 j = 0; 584 for (i=0; i<N; i++) { 585 if (lastidx > (idx = rows[i])) j = 0; 586 lastidx = idx; 587 for (; j<size; j++) { 588 if (idx >= owners[j] && idx < owners[j+1]) { 589 nprocs[2*j]++; 590 nprocs[2*j+1] = 1; 591 owner[i] = j; 592 #if defined(PETSC_DEBUG) 593 found = PETSC_TRUE; 594 #endif 595 break; 596 } 597 } 598 #if defined(PETSC_DEBUG) 599 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 600 found = PETSC_FALSE; 601 #endif 602 } 603 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 604 605 /* inform other processors of number of messages and max length*/ 606 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 607 608 /* post receives: */ 609 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 610 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 611 for (i=0; i<nrecvs; i++) { 612 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 613 } 614 615 /* do sends: 616 1) starts[i] gives the starting index in svalues for stuff going to 617 the ith processor 618 */ 619 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 620 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 621 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 622 starts[0] = 0; 623 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 624 for (i=0; i<N; i++) { 625 svalues[starts[owner[i]]++] = rows[i]; 626 } 627 628 starts[0] = 0; 629 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 630 count = 0; 631 for (i=0; i<size; i++) { 632 if (nprocs[2*i+1]) { 633 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 634 } 635 } 636 ierr = PetscFree(starts);CHKERRQ(ierr); 637 638 base = owners[rank]; 639 640 /* wait on receives */ 641 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 642 source = lens + nrecvs; 643 count = nrecvs; slen = 0; 644 while (count) { 645 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 646 /* unpack receives into our local space */ 647 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 648 source[imdex] = recv_status.MPI_SOURCE; 649 lens[imdex] = n; 650 slen += n; 651 count--; 652 } 653 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 654 655 /* move the data into the send scatter */ 656 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 657 count = 0; 658 for (i=0; i<nrecvs; i++) { 659 values = rvalues + i*nmax; 660 for (j=0; j<lens[i]; j++) { 661 lrows[count++] = values[j] - base; 662 } 663 } 664 ierr = PetscFree(rvalues);CHKERRQ(ierr); 665 ierr = PetscFree(lens);CHKERRQ(ierr); 666 ierr = PetscFree(owner);CHKERRQ(ierr); 667 ierr = PetscFree(nprocs);CHKERRQ(ierr); 668 669 /* actually zap the local rows */ 670 /* 671 Zero the required rows. If the "diagonal block" of the matrix 672 is square and the user wishes to set the diagonal we use separate 673 code so that MatSetValues() is not called for each diagonal allocating 674 new memory, thus calling lots of mallocs and slowing things down. 675 676 Contributed by: Matthew Knepley 677 */ 678 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 679 ierr = MatZeroRows(l->B,slen,lrows,0.0);CHKERRQ(ierr); 680 if ((diag != 0.0) && (l->A->rmap.N == l->A->cmap.N)) { 681 ierr = MatZeroRows(l->A,slen,lrows,diag);CHKERRQ(ierr); 682 } else if (diag != 0.0) { 683 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 684 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 685 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 686 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 687 } 688 for (i = 0; i < slen; i++) { 689 row = lrows[i] + rstart; 690 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 691 } 692 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 693 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 694 } else { 695 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 696 } 697 ierr = PetscFree(lrows);CHKERRQ(ierr); 698 699 /* wait on sends */ 700 if (nsends) { 701 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 702 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 703 ierr = PetscFree(send_status);CHKERRQ(ierr); 704 } 705 ierr = PetscFree(send_waits);CHKERRQ(ierr); 706 ierr = PetscFree(svalues);CHKERRQ(ierr); 707 708 PetscFunctionReturn(0); 709 } 710 711 #undef __FUNCT__ 712 #define __FUNCT__ "MatMult_MPIAIJ" 713 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 714 { 715 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 716 PetscErrorCode ierr; 717 PetscInt nt; 718 719 PetscFunctionBegin; 720 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 721 if (nt != A->cmap.n) { 722 SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap.n,nt); 723 } 724 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 725 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 726 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 727 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 728 PetscFunctionReturn(0); 729 } 730 731 #undef __FUNCT__ 732 #define __FUNCT__ "MatMultAdd_MPIAIJ" 733 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 734 { 735 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 736 PetscErrorCode ierr; 737 738 PetscFunctionBegin; 739 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 740 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 741 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 742 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 743 PetscFunctionReturn(0); 744 } 745 746 #undef __FUNCT__ 747 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 748 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 749 { 750 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 751 PetscErrorCode ierr; 752 PetscTruth merged; 753 754 PetscFunctionBegin; 755 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 756 /* do nondiagonal part */ 757 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 758 if (!merged) { 759 /* send it on its way */ 760 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 761 /* do local part */ 762 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 763 /* receive remote parts: note this assumes the values are not actually */ 764 /* added in yy until the next line, */ 765 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 766 } else { 767 /* do local part */ 768 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 769 /* send it on its way */ 770 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 771 /* values actually were received in the Begin() but we need to call this nop */ 772 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 773 } 774 PetscFunctionReturn(0); 775 } 776 777 EXTERN_C_BEGIN 778 #undef __FUNCT__ 779 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 780 PetscErrorCode PETSCMAT_DLLEXPORT MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f) 781 { 782 MPI_Comm comm; 783 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 784 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 785 IS Me,Notme; 786 PetscErrorCode ierr; 787 PetscInt M,N,first,last,*notme,i; 788 PetscMPIInt size; 789 790 PetscFunctionBegin; 791 792 /* Easy test: symmetric diagonal block */ 793 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 794 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 795 if (!*f) PetscFunctionReturn(0); 796 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 797 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 798 if (size == 1) PetscFunctionReturn(0); 799 800 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 801 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 802 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 803 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 804 for (i=0; i<first; i++) notme[i] = i; 805 for (i=last; i<M; i++) notme[i-last+first] = i; 806 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);CHKERRQ(ierr); 807 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 808 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 809 Aoff = Aoffs[0]; 810 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 811 Boff = Boffs[0]; 812 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 813 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 814 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 815 ierr = ISDestroy(Me);CHKERRQ(ierr); 816 ierr = ISDestroy(Notme);CHKERRQ(ierr); 817 818 PetscFunctionReturn(0); 819 } 820 EXTERN_C_END 821 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 824 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 825 { 826 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 827 PetscErrorCode ierr; 828 829 PetscFunctionBegin; 830 /* do nondiagonal part */ 831 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 832 /* send it on its way */ 833 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 834 /* do local part */ 835 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 836 /* receive remote parts */ 837 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 838 PetscFunctionReturn(0); 839 } 840 841 /* 842 This only works correctly for square matrices where the subblock A->A is the 843 diagonal block 844 */ 845 #undef __FUNCT__ 846 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 847 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 848 { 849 PetscErrorCode ierr; 850 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 851 852 PetscFunctionBegin; 853 if (A->rmap.N != A->cmap.N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 854 if (A->rmap.rstart != A->cmap.rstart || A->rmap.rend != A->cmap.rend) { 855 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 856 } 857 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 858 PetscFunctionReturn(0); 859 } 860 861 #undef __FUNCT__ 862 #define __FUNCT__ "MatScale_MPIAIJ" 863 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 864 { 865 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 866 PetscErrorCode ierr; 867 868 PetscFunctionBegin; 869 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 870 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 871 PetscFunctionReturn(0); 872 } 873 874 #undef __FUNCT__ 875 #define __FUNCT__ "MatDestroy_MPIAIJ" 876 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 877 { 878 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 879 PetscErrorCode ierr; 880 881 PetscFunctionBegin; 882 #if defined(PETSC_USE_LOG) 883 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap.N,mat->cmap.N); 884 #endif 885 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 886 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 887 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 888 #if defined (PETSC_USE_CTABLE) 889 if (aij->colmap) {ierr = PetscTableDestroy(aij->colmap);CHKERRQ(ierr);} 890 #else 891 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 892 #endif 893 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 894 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 895 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 896 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 897 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 898 ierr = PetscFree(aij);CHKERRQ(ierr); 899 900 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 901 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 902 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 903 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 904 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 905 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 906 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 907 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 908 PetscFunctionReturn(0); 909 } 910 911 #undef __FUNCT__ 912 #define __FUNCT__ "MatView_MPIAIJ_Binary" 913 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 914 { 915 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 916 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 917 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 918 PetscErrorCode ierr; 919 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 920 int fd; 921 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 922 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap.rstart,rnz; 923 PetscScalar *column_values; 924 925 PetscFunctionBegin; 926 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 927 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 928 nz = A->nz + B->nz; 929 if (!rank) { 930 header[0] = MAT_FILE_COOKIE; 931 header[1] = mat->rmap.N; 932 header[2] = mat->cmap.N; 933 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 934 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 935 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 936 /* get largest number of rows any processor has */ 937 rlen = mat->rmap.n; 938 range = mat->rmap.range; 939 for (i=1; i<size; i++) { 940 rlen = PetscMax(rlen,range[i+1] - range[i]); 941 } 942 } else { 943 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 944 rlen = mat->rmap.n; 945 } 946 947 /* load up the local row counts */ 948 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 949 for (i=0; i<mat->rmap.n; i++) { 950 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 951 } 952 953 /* store the row lengths to the file */ 954 if (!rank) { 955 MPI_Status status; 956 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap.n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 957 for (i=1; i<size; i++) { 958 rlen = range[i+1] - range[i]; 959 ierr = MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 960 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 961 } 962 } else { 963 ierr = MPI_Send(row_lengths,mat->rmap.n,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 964 } 965 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 966 967 /* load up the local column indices */ 968 nzmax = nz; /* )th processor needs space a largest processor needs */ 969 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 970 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 971 cnt = 0; 972 for (i=0; i<mat->rmap.n; i++) { 973 for (j=B->i[i]; j<B->i[i+1]; j++) { 974 if ( (col = garray[B->j[j]]) > cstart) break; 975 column_indices[cnt++] = col; 976 } 977 for (k=A->i[i]; k<A->i[i+1]; k++) { 978 column_indices[cnt++] = A->j[k] + cstart; 979 } 980 for (; j<B->i[i+1]; j++) { 981 column_indices[cnt++] = garray[B->j[j]]; 982 } 983 } 984 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 985 986 /* store the column indices to the file */ 987 if (!rank) { 988 MPI_Status status; 989 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 990 for (i=1; i<size; i++) { 991 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 992 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 993 ierr = MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 994 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 995 } 996 } else { 997 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 998 ierr = MPI_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 999 } 1000 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1001 1002 /* load up the local column values */ 1003 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1004 cnt = 0; 1005 for (i=0; i<mat->rmap.n; i++) { 1006 for (j=B->i[i]; j<B->i[i+1]; j++) { 1007 if ( garray[B->j[j]] > cstart) break; 1008 column_values[cnt++] = B->a[j]; 1009 } 1010 for (k=A->i[i]; k<A->i[i+1]; k++) { 1011 column_values[cnt++] = A->a[k]; 1012 } 1013 for (; j<B->i[i+1]; j++) { 1014 column_values[cnt++] = B->a[j]; 1015 } 1016 } 1017 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1018 1019 /* store the column values to the file */ 1020 if (!rank) { 1021 MPI_Status status; 1022 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1023 for (i=1; i<size; i++) { 1024 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1025 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1026 ierr = MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1027 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1028 } 1029 } else { 1030 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1031 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1032 } 1033 ierr = PetscFree(column_values);CHKERRQ(ierr); 1034 PetscFunctionReturn(0); 1035 } 1036 1037 #undef __FUNCT__ 1038 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1039 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1040 { 1041 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1042 PetscErrorCode ierr; 1043 PetscMPIInt rank = aij->rank,size = aij->size; 1044 PetscTruth isdraw,iascii,isbinary; 1045 PetscViewer sviewer; 1046 PetscViewerFormat format; 1047 1048 PetscFunctionBegin; 1049 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1050 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1051 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1052 if (iascii) { 1053 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1054 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1055 MatInfo info; 1056 PetscTruth inodes; 1057 1058 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1059 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1060 ierr = MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);CHKERRQ(ierr); 1061 if (!inodes) { 1062 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1063 rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1064 } else { 1065 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1066 rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1067 } 1068 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1069 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1070 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1071 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1072 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1073 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1074 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1075 PetscFunctionReturn(0); 1076 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1077 PetscInt inodecount,inodelimit,*inodes; 1078 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1079 if (inodes) { 1080 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1081 } else { 1082 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1083 } 1084 PetscFunctionReturn(0); 1085 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1086 PetscFunctionReturn(0); 1087 } 1088 } else if (isbinary) { 1089 if (size == 1) { 1090 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1091 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1092 } else { 1093 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1094 } 1095 PetscFunctionReturn(0); 1096 } else if (isdraw) { 1097 PetscDraw draw; 1098 PetscTruth isnull; 1099 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1100 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1101 } 1102 1103 if (size == 1) { 1104 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1105 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1106 } else { 1107 /* assemble the entire matrix onto first processor. */ 1108 Mat A; 1109 Mat_SeqAIJ *Aloc; 1110 PetscInt M = mat->rmap.N,N = mat->cmap.N,m,*ai,*aj,row,*cols,i,*ct; 1111 MatScalar *a; 1112 1113 if (mat->rmap.N > 1024) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 512 rows, use binary format instead"); 1114 1115 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1116 if (!rank) { 1117 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1118 } else { 1119 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1120 } 1121 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1122 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1123 ierr = MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1124 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1125 1126 /* copy over the A part */ 1127 Aloc = (Mat_SeqAIJ*)aij->A->data; 1128 m = aij->A->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1129 row = mat->rmap.rstart; 1130 for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap.rstart ;} 1131 for (i=0; i<m; i++) { 1132 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1133 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1134 } 1135 aj = Aloc->j; 1136 for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap.rstart;} 1137 1138 /* copy over the B part */ 1139 Aloc = (Mat_SeqAIJ*)aij->B->data; 1140 m = aij->B->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1141 row = mat->rmap.rstart; 1142 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1143 ct = cols; 1144 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 1145 for (i=0; i<m; i++) { 1146 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1147 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1148 } 1149 ierr = PetscFree(ct);CHKERRQ(ierr); 1150 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1151 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1152 /* 1153 Everyone has to call to draw the matrix since the graphics waits are 1154 synchronized across all processors that share the PetscDraw object 1155 */ 1156 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1157 if (!rank) { 1158 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1159 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1160 } 1161 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1162 ierr = MatDestroy(A);CHKERRQ(ierr); 1163 } 1164 PetscFunctionReturn(0); 1165 } 1166 1167 #undef __FUNCT__ 1168 #define __FUNCT__ "MatView_MPIAIJ" 1169 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1170 { 1171 PetscErrorCode ierr; 1172 PetscTruth iascii,isdraw,issocket,isbinary; 1173 1174 PetscFunctionBegin; 1175 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1176 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1177 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1178 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1179 if (iascii || isdraw || isbinary || issocket) { 1180 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1181 } else { 1182 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1183 } 1184 PetscFunctionReturn(0); 1185 } 1186 1187 #undef __FUNCT__ 1188 #define __FUNCT__ "MatRelax_MPIAIJ" 1189 PetscErrorCode MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1190 { 1191 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1192 PetscErrorCode ierr; 1193 Vec bb1; 1194 1195 PetscFunctionBegin; 1196 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1197 1198 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1199 if (flag & SOR_ZERO_INITIAL_GUESS) { 1200 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 1201 its--; 1202 } 1203 1204 while (its--) { 1205 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1206 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1207 1208 /* update rhs: bb1 = bb - B*x */ 1209 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1210 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1211 1212 /* local sweep */ 1213 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 1214 } 1215 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1216 if (flag & SOR_ZERO_INITIAL_GUESS) { 1217 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1218 its--; 1219 } 1220 while (its--) { 1221 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1222 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1223 1224 /* update rhs: bb1 = bb - B*x */ 1225 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1226 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1227 1228 /* local sweep */ 1229 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1230 } 1231 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1232 if (flag & SOR_ZERO_INITIAL_GUESS) { 1233 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1234 its--; 1235 } 1236 while (its--) { 1237 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1238 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1239 1240 /* update rhs: bb1 = bb - B*x */ 1241 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1242 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1243 1244 /* local sweep */ 1245 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1246 } 1247 } else { 1248 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1249 } 1250 1251 ierr = VecDestroy(bb1);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatPermute_MPIAIJ" 1257 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1258 { 1259 MPI_Comm comm,pcomm; 1260 PetscInt first,local_size,nrows,*rows; 1261 int ntids; 1262 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1263 PetscErrorCode ierr; 1264 1265 PetscFunctionBegin; 1266 ierr = PetscObjectGetComm((PetscObject)A,&comm); CHKERRQ(ierr); 1267 /* make a collective version of 'rowp' */ 1268 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm); CHKERRQ(ierr); 1269 if (pcomm==comm) { 1270 crowp = rowp; 1271 } else { 1272 ierr = ISGetSize(rowp,&nrows); CHKERRQ(ierr); 1273 ierr = ISGetIndices(rowp,&rows); CHKERRQ(ierr); 1274 ierr = ISCreateGeneral(comm,nrows,rows,&crowp); CHKERRQ(ierr); 1275 ierr = ISRestoreIndices(rowp,&rows); CHKERRQ(ierr); 1276 } 1277 /* collect the global row permutation and invert it */ 1278 ierr = ISAllGather(crowp,&growp); CHKERRQ(ierr); 1279 ierr = ISSetPermutation(growp); CHKERRQ(ierr); 1280 if (pcomm!=comm) { 1281 ierr = ISDestroy(crowp); CHKERRQ(ierr); 1282 } 1283 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1284 /* get the local target indices */ 1285 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL); CHKERRQ(ierr); 1286 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL); CHKERRQ(ierr); 1287 ierr = ISGetIndices(irowp,&rows); CHKERRQ(ierr); 1288 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp); CHKERRQ(ierr); 1289 ierr = ISRestoreIndices(irowp,&rows); CHKERRQ(ierr); 1290 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1291 /* the column permutation is so much easier; 1292 make a local version of 'colp' and invert it */ 1293 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm); CHKERRQ(ierr); 1294 ierr = MPI_Comm_size(pcomm,&ntids); CHKERRQ(ierr); 1295 if (ntids==1) { 1296 lcolp = colp; 1297 } else { 1298 ierr = ISGetSize(colp,&nrows); CHKERRQ(ierr); 1299 ierr = ISGetIndices(colp,&rows); CHKERRQ(ierr); 1300 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp); CHKERRQ(ierr); 1301 } 1302 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp); CHKERRQ(ierr); 1303 ierr = ISSetPermutation(lcolp); CHKERRQ(ierr); 1304 if (ntids>1) { 1305 ierr = ISRestoreIndices(colp,&rows); CHKERRQ(ierr); 1306 ierr = ISDestroy(lcolp); CHKERRQ(ierr); 1307 } 1308 /* now we just get the submatrix */ 1309 ierr = MatGetSubMatrix(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B); CHKERRQ(ierr); 1310 /* clean up */ 1311 ierr = ISDestroy(lrowp); CHKERRQ(ierr); 1312 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1313 PetscFunctionReturn(0); 1314 } 1315 1316 #undef __FUNCT__ 1317 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1318 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1319 { 1320 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1321 Mat A = mat->A,B = mat->B; 1322 PetscErrorCode ierr; 1323 PetscReal isend[5],irecv[5]; 1324 1325 PetscFunctionBegin; 1326 info->block_size = 1.0; 1327 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1328 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1329 isend[3] = info->memory; isend[4] = info->mallocs; 1330 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1331 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1332 isend[3] += info->memory; isend[4] += info->mallocs; 1333 if (flag == MAT_LOCAL) { 1334 info->nz_used = isend[0]; 1335 info->nz_allocated = isend[1]; 1336 info->nz_unneeded = isend[2]; 1337 info->memory = isend[3]; 1338 info->mallocs = isend[4]; 1339 } else if (flag == MAT_GLOBAL_MAX) { 1340 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1341 info->nz_used = irecv[0]; 1342 info->nz_allocated = irecv[1]; 1343 info->nz_unneeded = irecv[2]; 1344 info->memory = irecv[3]; 1345 info->mallocs = irecv[4]; 1346 } else if (flag == MAT_GLOBAL_SUM) { 1347 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1348 info->nz_used = irecv[0]; 1349 info->nz_allocated = irecv[1]; 1350 info->nz_unneeded = irecv[2]; 1351 info->memory = irecv[3]; 1352 info->mallocs = irecv[4]; 1353 } 1354 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1355 info->fill_ratio_needed = 0; 1356 info->factor_mallocs = 0; 1357 info->rows_global = (double)matin->rmap.N; 1358 info->columns_global = (double)matin->cmap.N; 1359 info->rows_local = (double)matin->rmap.n; 1360 info->columns_local = (double)matin->cmap.N; 1361 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNCT__ 1366 #define __FUNCT__ "MatSetOption_MPIAIJ" 1367 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg) 1368 { 1369 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1370 PetscErrorCode ierr; 1371 1372 PetscFunctionBegin; 1373 switch (op) { 1374 case MAT_NEW_NONZERO_LOCATIONS: 1375 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1376 case MAT_KEEP_ZEROED_ROWS: 1377 case MAT_NEW_NONZERO_LOCATION_ERR: 1378 case MAT_USE_INODES: 1379 case MAT_IGNORE_ZERO_ENTRIES: 1380 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1381 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1382 break; 1383 case MAT_ROW_ORIENTED: 1384 a->roworiented = flg; 1385 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1386 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1387 break; 1388 case MAT_NEW_DIAGONALS: 1389 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1390 break; 1391 case MAT_IGNORE_OFF_PROC_ENTRIES: 1392 a->donotstash = PETSC_TRUE; 1393 break; 1394 case MAT_SYMMETRIC: 1395 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1396 break; 1397 case MAT_STRUCTURALLY_SYMMETRIC: 1398 case MAT_HERMITIAN: 1399 case MAT_SYMMETRY_ETERNAL: 1400 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1401 break; 1402 default: 1403 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1404 } 1405 PetscFunctionReturn(0); 1406 } 1407 1408 #undef __FUNCT__ 1409 #define __FUNCT__ "MatGetRow_MPIAIJ" 1410 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1411 { 1412 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1413 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1414 PetscErrorCode ierr; 1415 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap.rstart; 1416 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap.rstart,rend = matin->rmap.rend; 1417 PetscInt *cmap,*idx_p; 1418 1419 PetscFunctionBegin; 1420 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1421 mat->getrowactive = PETSC_TRUE; 1422 1423 if (!mat->rowvalues && (idx || v)) { 1424 /* 1425 allocate enough space to hold information from the longest row. 1426 */ 1427 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1428 PetscInt max = 1,tmp; 1429 for (i=0; i<matin->rmap.n; i++) { 1430 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1431 if (max < tmp) { max = tmp; } 1432 } 1433 ierr = PetscMalloc(max*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1434 mat->rowindices = (PetscInt*)(mat->rowvalues + max); 1435 } 1436 1437 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1438 lrow = row - rstart; 1439 1440 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1441 if (!v) {pvA = 0; pvB = 0;} 1442 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1443 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1444 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1445 nztot = nzA + nzB; 1446 1447 cmap = mat->garray; 1448 if (v || idx) { 1449 if (nztot) { 1450 /* Sort by increasing column numbers, assuming A and B already sorted */ 1451 PetscInt imark = -1; 1452 if (v) { 1453 *v = v_p = mat->rowvalues; 1454 for (i=0; i<nzB; i++) { 1455 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1456 else break; 1457 } 1458 imark = i; 1459 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1460 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1461 } 1462 if (idx) { 1463 *idx = idx_p = mat->rowindices; 1464 if (imark > -1) { 1465 for (i=0; i<imark; i++) { 1466 idx_p[i] = cmap[cworkB[i]]; 1467 } 1468 } else { 1469 for (i=0; i<nzB; i++) { 1470 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1471 else break; 1472 } 1473 imark = i; 1474 } 1475 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1476 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1477 } 1478 } else { 1479 if (idx) *idx = 0; 1480 if (v) *v = 0; 1481 } 1482 } 1483 *nz = nztot; 1484 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1485 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1486 PetscFunctionReturn(0); 1487 } 1488 1489 #undef __FUNCT__ 1490 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1491 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1492 { 1493 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1494 1495 PetscFunctionBegin; 1496 if (!aij->getrowactive) { 1497 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1498 } 1499 aij->getrowactive = PETSC_FALSE; 1500 PetscFunctionReturn(0); 1501 } 1502 1503 #undef __FUNCT__ 1504 #define __FUNCT__ "MatNorm_MPIAIJ" 1505 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1506 { 1507 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1508 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1509 PetscErrorCode ierr; 1510 PetscInt i,j,cstart = mat->cmap.rstart; 1511 PetscReal sum = 0.0; 1512 MatScalar *v; 1513 1514 PetscFunctionBegin; 1515 if (aij->size == 1) { 1516 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1517 } else { 1518 if (type == NORM_FROBENIUS) { 1519 v = amat->a; 1520 for (i=0; i<amat->nz; i++) { 1521 #if defined(PETSC_USE_COMPLEX) 1522 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1523 #else 1524 sum += (*v)*(*v); v++; 1525 #endif 1526 } 1527 v = bmat->a; 1528 for (i=0; i<bmat->nz; i++) { 1529 #if defined(PETSC_USE_COMPLEX) 1530 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1531 #else 1532 sum += (*v)*(*v); v++; 1533 #endif 1534 } 1535 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1536 *norm = sqrt(*norm); 1537 } else if (type == NORM_1) { /* max column norm */ 1538 PetscReal *tmp,*tmp2; 1539 PetscInt *jj,*garray = aij->garray; 1540 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1541 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1542 ierr = PetscMemzero(tmp,mat->cmap.N*sizeof(PetscReal));CHKERRQ(ierr); 1543 *norm = 0.0; 1544 v = amat->a; jj = amat->j; 1545 for (j=0; j<amat->nz; j++) { 1546 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1547 } 1548 v = bmat->a; jj = bmat->j; 1549 for (j=0; j<bmat->nz; j++) { 1550 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1551 } 1552 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap.N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1553 for (j=0; j<mat->cmap.N; j++) { 1554 if (tmp2[j] > *norm) *norm = tmp2[j]; 1555 } 1556 ierr = PetscFree(tmp);CHKERRQ(ierr); 1557 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1558 } else if (type == NORM_INFINITY) { /* max row norm */ 1559 PetscReal ntemp = 0.0; 1560 for (j=0; j<aij->A->rmap.n; j++) { 1561 v = amat->a + amat->i[j]; 1562 sum = 0.0; 1563 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1564 sum += PetscAbsScalar(*v); v++; 1565 } 1566 v = bmat->a + bmat->i[j]; 1567 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1568 sum += PetscAbsScalar(*v); v++; 1569 } 1570 if (sum > ntemp) ntemp = sum; 1571 } 1572 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 1573 } else { 1574 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1575 } 1576 } 1577 PetscFunctionReturn(0); 1578 } 1579 1580 #undef __FUNCT__ 1581 #define __FUNCT__ "MatTranspose_MPIAIJ" 1582 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1583 { 1584 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1585 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1586 PetscErrorCode ierr; 1587 PetscInt M = A->rmap.N,N = A->cmap.N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i,*d_nnz; 1588 PetscInt cstart=A->cmap.rstart,ncol; 1589 Mat B; 1590 MatScalar *array; 1591 1592 PetscFunctionBegin; 1593 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1594 1595 ma = A->rmap.n; na = A->cmap.n; mb = a->B->rmap.n; 1596 ai = Aloc->i; aj = Aloc->j; 1597 bi = Bloc->i; bj = Bloc->j; 1598 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1599 /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */ 1600 ierr = PetscMalloc((1+na)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1601 ierr = PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));CHKERRQ(ierr); 1602 for (i=0; i<ai[ma]; i++){ 1603 d_nnz[aj[i]] ++; 1604 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1605 } 1606 1607 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1608 ierr = MatSetSizes(B,A->cmap.n,A->rmap.n,N,M);CHKERRQ(ierr); 1609 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1610 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);CHKERRQ(ierr); 1611 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1612 } else { 1613 B = *matout; 1614 } 1615 1616 /* copy over the A part */ 1617 array = Aloc->a; 1618 row = A->rmap.rstart; 1619 for (i=0; i<ma; i++) { 1620 ncol = ai[i+1]-ai[i]; 1621 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1622 row++; array += ncol; aj += ncol; 1623 } 1624 aj = Aloc->j; 1625 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1626 1627 /* copy over the B part */ 1628 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1629 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 1630 array = Bloc->a; 1631 row = A->rmap.rstart; 1632 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 1633 cols_tmp = cols; 1634 for (i=0; i<mb; i++) { 1635 ncol = bi[i+1]-bi[i]; 1636 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1637 row++; array += ncol; cols_tmp += ncol; 1638 } 1639 ierr = PetscFree(cols);CHKERRQ(ierr); 1640 1641 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1642 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1643 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1644 *matout = B; 1645 } else { 1646 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1647 } 1648 PetscFunctionReturn(0); 1649 } 1650 1651 #undef __FUNCT__ 1652 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1653 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1654 { 1655 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1656 Mat a = aij->A,b = aij->B; 1657 PetscErrorCode ierr; 1658 PetscInt s1,s2,s3; 1659 1660 PetscFunctionBegin; 1661 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1662 if (rr) { 1663 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1664 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1665 /* Overlap communication with computation. */ 1666 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1667 } 1668 if (ll) { 1669 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1670 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1671 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1672 } 1673 /* scale the diagonal block */ 1674 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1675 1676 if (rr) { 1677 /* Do a scatter end and then right scale the off-diagonal block */ 1678 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1679 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1680 } 1681 1682 PetscFunctionReturn(0); 1683 } 1684 1685 #undef __FUNCT__ 1686 #define __FUNCT__ "MatSetBlockSize_MPIAIJ" 1687 PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs) 1688 { 1689 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1690 PetscErrorCode ierr; 1691 1692 PetscFunctionBegin; 1693 ierr = MatSetBlockSize(a->A,bs);CHKERRQ(ierr); 1694 ierr = MatSetBlockSize(a->B,bs);CHKERRQ(ierr); 1695 PetscFunctionReturn(0); 1696 } 1697 #undef __FUNCT__ 1698 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1699 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 1700 { 1701 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1702 PetscErrorCode ierr; 1703 1704 PetscFunctionBegin; 1705 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1706 PetscFunctionReturn(0); 1707 } 1708 1709 #undef __FUNCT__ 1710 #define __FUNCT__ "MatEqual_MPIAIJ" 1711 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1712 { 1713 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1714 Mat a,b,c,d; 1715 PetscTruth flg; 1716 PetscErrorCode ierr; 1717 1718 PetscFunctionBegin; 1719 a = matA->A; b = matA->B; 1720 c = matB->A; d = matB->B; 1721 1722 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1723 if (flg) { 1724 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1725 } 1726 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1727 PetscFunctionReturn(0); 1728 } 1729 1730 #undef __FUNCT__ 1731 #define __FUNCT__ "MatCopy_MPIAIJ" 1732 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1733 { 1734 PetscErrorCode ierr; 1735 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1736 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1737 1738 PetscFunctionBegin; 1739 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1740 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1741 /* because of the column compression in the off-processor part of the matrix a->B, 1742 the number of columns in a->B and b->B may be different, hence we cannot call 1743 the MatCopy() directly on the two parts. If need be, we can provide a more 1744 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1745 then copying the submatrices */ 1746 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1747 } else { 1748 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1749 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1750 } 1751 PetscFunctionReturn(0); 1752 } 1753 1754 #undef __FUNCT__ 1755 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1756 PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A) 1757 { 1758 PetscErrorCode ierr; 1759 1760 PetscFunctionBegin; 1761 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1762 PetscFunctionReturn(0); 1763 } 1764 1765 #include "petscblaslapack.h" 1766 #undef __FUNCT__ 1767 #define __FUNCT__ "MatAXPY_MPIAIJ" 1768 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1769 { 1770 PetscErrorCode ierr; 1771 PetscInt i; 1772 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1773 PetscBLASInt bnz,one=1; 1774 Mat_SeqAIJ *x,*y; 1775 1776 PetscFunctionBegin; 1777 if (str == SAME_NONZERO_PATTERN) { 1778 PetscScalar alpha = a; 1779 x = (Mat_SeqAIJ *)xx->A->data; 1780 y = (Mat_SeqAIJ *)yy->A->data; 1781 bnz = PetscBLASIntCast(x->nz); 1782 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1783 x = (Mat_SeqAIJ *)xx->B->data; 1784 y = (Mat_SeqAIJ *)yy->B->data; 1785 bnz = PetscBLASIntCast(x->nz); 1786 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1787 } else if (str == SUBSET_NONZERO_PATTERN) { 1788 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 1789 1790 x = (Mat_SeqAIJ *)xx->B->data; 1791 y = (Mat_SeqAIJ *)yy->B->data; 1792 if (y->xtoy && y->XtoY != xx->B) { 1793 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1794 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1795 } 1796 if (!y->xtoy) { /* get xtoy */ 1797 ierr = MatAXPYGetxtoy_Private(xx->B->rmap.n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1798 y->XtoY = xx->B; 1799 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 1800 } 1801 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 1802 } else { 1803 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1804 } 1805 PetscFunctionReturn(0); 1806 } 1807 1808 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat); 1809 1810 #undef __FUNCT__ 1811 #define __FUNCT__ "MatConjugate_MPIAIJ" 1812 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_MPIAIJ(Mat mat) 1813 { 1814 #if defined(PETSC_USE_COMPLEX) 1815 PetscErrorCode ierr; 1816 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1817 1818 PetscFunctionBegin; 1819 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 1820 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 1821 #else 1822 PetscFunctionBegin; 1823 #endif 1824 PetscFunctionReturn(0); 1825 } 1826 1827 #undef __FUNCT__ 1828 #define __FUNCT__ "MatRealPart_MPIAIJ" 1829 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 1830 { 1831 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1832 PetscErrorCode ierr; 1833 1834 PetscFunctionBegin; 1835 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1836 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1837 PetscFunctionReturn(0); 1838 } 1839 1840 #undef __FUNCT__ 1841 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 1842 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 1843 { 1844 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1845 PetscErrorCode ierr; 1846 1847 PetscFunctionBegin; 1848 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1849 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1850 PetscFunctionReturn(0); 1851 } 1852 1853 #ifdef PETSC_HAVE_PBGL 1854 1855 #include <boost/parallel/mpi/bsp_process_group.hpp> 1856 #include <boost/graph/distributed/ilu_default_graph.hpp> 1857 #include <boost/graph/distributed/ilu_0_block.hpp> 1858 #include <boost/graph/distributed/ilu_preconditioner.hpp> 1859 #include <boost/graph/distributed/petsc/interface.hpp> 1860 #include <boost/multi_array.hpp> 1861 #include <boost/parallel/distributed_property_map.hpp> 1862 1863 #undef __FUNCT__ 1864 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 1865 /* 1866 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1867 */ 1868 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat A, IS isrow, IS iscol, MatFactorInfo *info, Mat *fact) 1869 { 1870 namespace petsc = boost::distributed::petsc; 1871 1872 namespace graph_dist = boost::graph::distributed; 1873 using boost::graph::distributed::ilu_default::process_group_type; 1874 using boost::graph::ilu_permuted; 1875 1876 PetscTruth row_identity, col_identity; 1877 PetscContainer c; 1878 PetscInt m, n, M, N; 1879 PetscErrorCode ierr; 1880 1881 PetscFunctionBegin; 1882 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 1883 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 1884 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 1885 if (!row_identity || !col_identity) { 1886 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 1887 } 1888 1889 process_group_type pg; 1890 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1891 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 1892 lgraph_type& level_graph = *lgraph_p; 1893 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1894 1895 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 1896 ilu_permuted(level_graph); 1897 1898 /* put together the new matrix */ 1899 ierr = MatCreate(((PetscObject)A)->comm, fact);CHKERRQ(ierr); 1900 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 1901 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 1902 ierr = MatSetSizes(*fact, m, n, M, N);CHKERRQ(ierr); 1903 ierr = MatSetType(*fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 1904 ierr = MatAssemblyBegin(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1905 ierr = MatAssemblyEnd(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1906 (*fact)->factor = FACTOR_LU; 1907 1908 ierr = PetscContainerCreate(((PetscObject)A)->comm, &c); 1909 ierr = PetscContainerSetPointer(c, lgraph_p); 1910 ierr = PetscObjectCompose((PetscObject) (*fact), "graph", (PetscObject) c); 1911 PetscFunctionReturn(0); 1912 } 1913 1914 #undef __FUNCT__ 1915 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 1916 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat A, MatFactorInfo *info, Mat *B) 1917 { 1918 PetscFunctionBegin; 1919 PetscFunctionReturn(0); 1920 } 1921 1922 #undef __FUNCT__ 1923 #define __FUNCT__ "MatSolve_MPIAIJ" 1924 /* 1925 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1926 */ 1927 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 1928 { 1929 namespace graph_dist = boost::graph::distributed; 1930 1931 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1932 lgraph_type* lgraph_p; 1933 PetscContainer c; 1934 PetscErrorCode ierr; 1935 1936 PetscFunctionBegin; 1937 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 1938 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 1939 ierr = VecCopy(b, x); CHKERRQ(ierr); 1940 1941 PetscScalar* array_x; 1942 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 1943 PetscInt sx; 1944 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 1945 1946 PetscScalar* array_b; 1947 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 1948 PetscInt sb; 1949 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 1950 1951 lgraph_type& level_graph = *lgraph_p; 1952 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1953 1954 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 1955 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 1956 ref_x(array_x, boost::extents[num_vertices(graph)]); 1957 1958 typedef boost::iterator_property_map<array_ref_type::iterator, 1959 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 1960 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 1961 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 1962 1963 ilu_set_solve(*lgraph_p, vector_b, vector_x); 1964 1965 PetscFunctionReturn(0); 1966 } 1967 #endif 1968 1969 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 1970 PetscInt nzlocal,nsends,nrecvs; 1971 PetscMPIInt *send_rank; 1972 PetscInt *sbuf_nz,*sbuf_j,**rbuf_j; 1973 PetscScalar *sbuf_a,**rbuf_a; 1974 PetscErrorCode (*MatDestroy)(Mat); 1975 } Mat_Redundant; 1976 1977 #undef __FUNCT__ 1978 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 1979 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 1980 { 1981 PetscErrorCode ierr; 1982 Mat_Redundant *redund=(Mat_Redundant*)ptr; 1983 PetscInt i; 1984 1985 PetscFunctionBegin; 1986 ierr = PetscFree(redund->send_rank);CHKERRQ(ierr); 1987 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1988 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1989 for (i=0; i<redund->nrecvs; i++){ 1990 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1991 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1992 } 1993 ierr = PetscFree3(redund->sbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1994 ierr = PetscFree(redund);CHKERRQ(ierr); 1995 PetscFunctionReturn(0); 1996 } 1997 1998 #undef __FUNCT__ 1999 #define __FUNCT__ "MatDestroy_MatRedundant" 2000 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2001 { 2002 PetscErrorCode ierr; 2003 PetscContainer container; 2004 Mat_Redundant *redund=PETSC_NULL; 2005 2006 PetscFunctionBegin; 2007 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2008 if (container) { 2009 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2010 } else { 2011 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2012 } 2013 A->ops->destroy = redund->MatDestroy; 2014 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 2015 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 2016 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 2017 PetscFunctionReturn(0); 2018 } 2019 2020 #undef __FUNCT__ 2021 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2022 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 2023 { 2024 PetscMPIInt rank,size; 2025 MPI_Comm comm=((PetscObject)mat)->comm; 2026 PetscErrorCode ierr; 2027 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 2028 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 2029 PetscInt *rowrange=mat->rmap.range; 2030 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2031 Mat A=aij->A,B=aij->B,C=*matredundant; 2032 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2033 PetscScalar *sbuf_a; 2034 PetscInt nzlocal=a->nz+b->nz; 2035 PetscInt j,cstart=mat->cmap.rstart,cend=mat->cmap.rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2036 PetscInt rstart=mat->rmap.rstart,rend=mat->rmap.rend,*bmap=aij->garray,M,N; 2037 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2038 MatScalar *aworkA,*aworkB; 2039 PetscScalar *vals; 2040 PetscMPIInt tag1,tag2,tag3,imdex; 2041 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 2042 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 2043 MPI_Status recv_status,*send_status; 2044 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 2045 PetscInt **rbuf_j=PETSC_NULL; 2046 PetscScalar **rbuf_a=PETSC_NULL; 2047 Mat_Redundant *redund=PETSC_NULL; 2048 PetscContainer container; 2049 2050 PetscFunctionBegin; 2051 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2052 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2053 2054 if (reuse == MAT_REUSE_MATRIX) { 2055 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2056 if (M != N || M != mat->rmap.N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2057 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 2058 if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 2059 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2060 if (container) { 2061 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2062 } else { 2063 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2064 } 2065 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2066 2067 nsends = redund->nsends; 2068 nrecvs = redund->nrecvs; 2069 send_rank = redund->send_rank; recv_rank = send_rank + size; 2070 sbuf_nz = redund->sbuf_nz; rbuf_nz = sbuf_nz + nsends; 2071 sbuf_j = redund->sbuf_j; 2072 sbuf_a = redund->sbuf_a; 2073 rbuf_j = redund->rbuf_j; 2074 rbuf_a = redund->rbuf_a; 2075 } 2076 2077 if (reuse == MAT_INITIAL_MATRIX){ 2078 PetscMPIInt subrank,subsize; 2079 PetscInt nleftover,np_subcomm; 2080 /* get the destination processors' id send_rank, nsends and nrecvs */ 2081 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2082 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2083 ierr = PetscMalloc((2*size+1)*sizeof(PetscMPIInt),&send_rank); 2084 recv_rank = send_rank + size; 2085 np_subcomm = size/nsubcomm; 2086 nleftover = size - nsubcomm*np_subcomm; 2087 nsends = 0; nrecvs = 0; 2088 for (i=0; i<size; i++){ /* i=rank*/ 2089 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 2090 send_rank[nsends] = i; nsends++; 2091 recv_rank[nrecvs++] = i; 2092 } 2093 } 2094 if (rank >= size - nleftover){/* this proc is a leftover processor */ 2095 i = size-nleftover-1; 2096 j = 0; 2097 while (j < nsubcomm - nleftover){ 2098 send_rank[nsends++] = i; 2099 i--; j++; 2100 } 2101 } 2102 2103 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 2104 for (i=0; i<nleftover; i++){ 2105 recv_rank[nrecvs++] = size-nleftover+i; 2106 } 2107 } 2108 2109 /* allocate sbuf_j, sbuf_a */ 2110 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2111 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2112 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2113 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2114 2115 /* copy mat's local entries into the buffers */ 2116 if (reuse == MAT_INITIAL_MATRIX){ 2117 rownz_max = 0; 2118 rptr = sbuf_j; 2119 cols = sbuf_j + rend-rstart + 1; 2120 vals = sbuf_a; 2121 rptr[0] = 0; 2122 for (i=0; i<rend-rstart; i++){ 2123 row = i + rstart; 2124 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2125 ncols = nzA + nzB; 2126 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2127 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2128 /* load the column indices for this row into cols */ 2129 lwrite = 0; 2130 for (l=0; l<nzB; l++) { 2131 if ((ctmp = bmap[cworkB[l]]) < cstart){ 2132 vals[lwrite] = aworkB[l]; 2133 cols[lwrite++] = ctmp; 2134 } 2135 } 2136 for (l=0; l<nzA; l++){ 2137 vals[lwrite] = aworkA[l]; 2138 cols[lwrite++] = cstart + cworkA[l]; 2139 } 2140 for (l=0; l<nzB; l++) { 2141 if ((ctmp = bmap[cworkB[l]]) >= cend){ 2142 vals[lwrite] = aworkB[l]; 2143 cols[lwrite++] = ctmp; 2144 } 2145 } 2146 vals += ncols; 2147 cols += ncols; 2148 rptr[i+1] = rptr[i] + ncols; 2149 if (rownz_max < ncols) rownz_max = ncols; 2150 } 2151 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(1, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2152 } else { /* only copy matrix values into sbuf_a */ 2153 rptr = sbuf_j; 2154 vals = sbuf_a; 2155 rptr[0] = 0; 2156 for (i=0; i<rend-rstart; i++){ 2157 row = i + rstart; 2158 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2159 ncols = nzA + nzB; 2160 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2161 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2162 lwrite = 0; 2163 for (l=0; l<nzB; l++) { 2164 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2165 } 2166 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2167 for (l=0; l<nzB; l++) { 2168 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2169 } 2170 vals += ncols; 2171 rptr[i+1] = rptr[i] + ncols; 2172 } 2173 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2174 2175 /* send nzlocal to others, and recv other's nzlocal */ 2176 /*--------------------------------------------------*/ 2177 if (reuse == MAT_INITIAL_MATRIX){ 2178 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2179 s_waits2 = s_waits3 + nsends; 2180 s_waits1 = s_waits2 + nsends; 2181 r_waits1 = s_waits1 + nsends; 2182 r_waits2 = r_waits1 + nrecvs; 2183 r_waits3 = r_waits2 + nrecvs; 2184 } else { 2185 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2186 r_waits3 = s_waits3 + nsends; 2187 } 2188 2189 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2190 if (reuse == MAT_INITIAL_MATRIX){ 2191 /* get new tags to keep the communication clean */ 2192 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2193 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2194 ierr = PetscMalloc3(nsends+nrecvs+1,PetscInt,&sbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2195 rbuf_nz = sbuf_nz + nsends; 2196 2197 /* post receives of other's nzlocal */ 2198 for (i=0; i<nrecvs; i++){ 2199 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2200 } 2201 /* send nzlocal to others */ 2202 for (i=0; i<nsends; i++){ 2203 sbuf_nz[i] = nzlocal; 2204 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2205 } 2206 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2207 count = nrecvs; 2208 while (count) { 2209 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2210 recv_rank[imdex] = recv_status.MPI_SOURCE; 2211 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2212 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2213 2214 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2215 rbuf_nz[imdex] += i + 2; 2216 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2217 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2218 count--; 2219 } 2220 /* wait on sends of nzlocal */ 2221 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2222 /* send mat->i,j to others, and recv from other's */ 2223 /*------------------------------------------------*/ 2224 for (i=0; i<nsends; i++){ 2225 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2226 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2227 } 2228 /* wait on receives of mat->i,j */ 2229 /*------------------------------*/ 2230 count = nrecvs; 2231 while (count) { 2232 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2233 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2234 count--; 2235 } 2236 /* wait on sends of mat->i,j */ 2237 /*---------------------------*/ 2238 if (nsends) { 2239 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2240 } 2241 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2242 2243 /* post receives, send and receive mat->a */ 2244 /*----------------------------------------*/ 2245 for (imdex=0; imdex<nrecvs; imdex++) { 2246 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2247 } 2248 for (i=0; i<nsends; i++){ 2249 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2250 } 2251 count = nrecvs; 2252 while (count) { 2253 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2254 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2255 count--; 2256 } 2257 if (nsends) { 2258 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2259 } 2260 2261 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2262 2263 /* create redundant matrix */ 2264 /*-------------------------*/ 2265 if (reuse == MAT_INITIAL_MATRIX){ 2266 /* compute rownz_max for preallocation */ 2267 for (imdex=0; imdex<nrecvs; imdex++){ 2268 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2269 rptr = rbuf_j[imdex]; 2270 for (i=0; i<j; i++){ 2271 ncols = rptr[i+1] - rptr[i]; 2272 if (rownz_max < ncols) rownz_max = ncols; 2273 } 2274 } 2275 2276 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2277 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2278 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2279 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2280 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2281 } else { 2282 C = *matredundant; 2283 } 2284 2285 /* insert local matrix entries */ 2286 rptr = sbuf_j; 2287 cols = sbuf_j + rend-rstart + 1; 2288 vals = sbuf_a; 2289 for (i=0; i<rend-rstart; i++){ 2290 row = i + rstart; 2291 ncols = rptr[i+1] - rptr[i]; 2292 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2293 vals += ncols; 2294 cols += ncols; 2295 } 2296 /* insert received matrix entries */ 2297 for (imdex=0; imdex<nrecvs; imdex++){ 2298 rstart = rowrange[recv_rank[imdex]]; 2299 rend = rowrange[recv_rank[imdex]+1]; 2300 rptr = rbuf_j[imdex]; 2301 cols = rbuf_j[imdex] + rend-rstart + 1; 2302 vals = rbuf_a[imdex]; 2303 for (i=0; i<rend-rstart; i++){ 2304 row = i + rstart; 2305 ncols = rptr[i+1] - rptr[i]; 2306 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2307 vals += ncols; 2308 cols += ncols; 2309 } 2310 } 2311 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2312 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2313 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2314 if (M != mat->rmap.N || N != mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_INCOMP,"redundant mat size %d != input mat size %d",M,mat->rmap.N); 2315 if (reuse == MAT_INITIAL_MATRIX){ 2316 PetscContainer container; 2317 *matredundant = C; 2318 /* create a supporting struct and attach it to C for reuse */ 2319 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2320 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2321 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2322 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2323 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2324 2325 redund->nzlocal = nzlocal; 2326 redund->nsends = nsends; 2327 redund->nrecvs = nrecvs; 2328 redund->send_rank = send_rank; 2329 redund->sbuf_nz = sbuf_nz; 2330 redund->sbuf_j = sbuf_j; 2331 redund->sbuf_a = sbuf_a; 2332 redund->rbuf_j = rbuf_j; 2333 redund->rbuf_a = rbuf_a; 2334 2335 redund->MatDestroy = C->ops->destroy; 2336 C->ops->destroy = MatDestroy_MatRedundant; 2337 } 2338 PetscFunctionReturn(0); 2339 } 2340 2341 #undef __FUNCT__ 2342 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2343 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2344 { 2345 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2346 PetscErrorCode ierr; 2347 PetscInt i,*idxb = 0; 2348 PetscScalar *va,*vb; 2349 Vec vtmp; 2350 2351 PetscFunctionBegin; 2352 ierr = PetscMemzero(idx,A->cmap.n*sizeof(PetscInt));CHKERRQ(ierr); 2353 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2354 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2355 if (idx) { 2356 for (i=0; i<A->cmap.n; i++) { 2357 if (PetscAbsScalar(va[i])) idx[i] += A->cmap.rstart; 2358 } 2359 } 2360 2361 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap.n,&vtmp);CHKERRQ(ierr); 2362 if (idx) { 2363 ierr = PetscMalloc(A->rmap.n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2364 } 2365 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2366 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2367 2368 for (i=0; i<A->rmap.n; i++){ 2369 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2370 va[i] = vb[i]; 2371 if (idx) idx[i] = a->garray[idxb[i]]; 2372 } 2373 } 2374 2375 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2376 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2377 if (idxb) { 2378 ierr = PetscFree(idxb);CHKERRQ(ierr); 2379 } 2380 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 2381 PetscFunctionReturn(0); 2382 } 2383 2384 #undef __FUNCT__ 2385 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2386 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2387 { 2388 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2389 PetscInt n = A->rmap.n; 2390 PetscInt cstart = A->cmap.rstart; 2391 PetscInt *cmap = mat->garray; 2392 PetscInt *diagIdx, *offdiagIdx; 2393 Vec diagV, offdiagV; 2394 PetscScalar *a, *diagA, *offdiagA; 2395 PetscInt r; 2396 PetscErrorCode ierr; 2397 2398 PetscFunctionBegin; 2399 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2400 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2401 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2402 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2403 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2404 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2405 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2406 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2407 for(r = 0; r < n; ++r) { 2408 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2409 a[r] = diagA[r]; 2410 idx[r] = cstart + diagIdx[r]; 2411 } else { 2412 a[r] = offdiagA[r]; 2413 idx[r] = cmap[offdiagIdx[r]]; 2414 } 2415 } 2416 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2417 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2418 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2419 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2420 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2421 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2422 PetscFunctionReturn(0); 2423 } 2424 2425 #undef __FUNCT__ 2426 #define __FUNCT__ "MatGetSeqNonzerostructure_MPIAIJ" 2427 PetscErrorCode MatGetSeqNonzerostructure_MPIAIJ(Mat mat,Mat *newmat[]) 2428 { 2429 PetscErrorCode ierr; 2430 2431 PetscFunctionBegin; 2432 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,newmat);CHKERRQ(ierr); 2433 PetscFunctionReturn(0); 2434 } 2435 2436 /* -------------------------------------------------------------------*/ 2437 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2438 MatGetRow_MPIAIJ, 2439 MatRestoreRow_MPIAIJ, 2440 MatMult_MPIAIJ, 2441 /* 4*/ MatMultAdd_MPIAIJ, 2442 MatMultTranspose_MPIAIJ, 2443 MatMultTransposeAdd_MPIAIJ, 2444 #ifdef PETSC_HAVE_PBGL 2445 MatSolve_MPIAIJ, 2446 #else 2447 0, 2448 #endif 2449 0, 2450 0, 2451 /*10*/ 0, 2452 0, 2453 0, 2454 MatRelax_MPIAIJ, 2455 MatTranspose_MPIAIJ, 2456 /*15*/ MatGetInfo_MPIAIJ, 2457 MatEqual_MPIAIJ, 2458 MatGetDiagonal_MPIAIJ, 2459 MatDiagonalScale_MPIAIJ, 2460 MatNorm_MPIAIJ, 2461 /*20*/ MatAssemblyBegin_MPIAIJ, 2462 MatAssemblyEnd_MPIAIJ, 2463 0, 2464 MatSetOption_MPIAIJ, 2465 MatZeroEntries_MPIAIJ, 2466 /*25*/ MatZeroRows_MPIAIJ, 2467 0, 2468 #ifdef PETSC_HAVE_PBGL 2469 MatLUFactorNumeric_MPIAIJ, 2470 #else 2471 0, 2472 #endif 2473 0, 2474 0, 2475 /*30*/ MatSetUpPreallocation_MPIAIJ, 2476 #ifdef PETSC_HAVE_PBGL 2477 MatILUFactorSymbolic_MPIAIJ, 2478 #else 2479 0, 2480 #endif 2481 0, 2482 0, 2483 0, 2484 /*35*/ MatDuplicate_MPIAIJ, 2485 0, 2486 0, 2487 0, 2488 0, 2489 /*40*/ MatAXPY_MPIAIJ, 2490 MatGetSubMatrices_MPIAIJ, 2491 MatIncreaseOverlap_MPIAIJ, 2492 MatGetValues_MPIAIJ, 2493 MatCopy_MPIAIJ, 2494 /*45*/ 0, 2495 MatScale_MPIAIJ, 2496 0, 2497 0, 2498 0, 2499 /*50*/ MatSetBlockSize_MPIAIJ, 2500 0, 2501 0, 2502 0, 2503 0, 2504 /*55*/ MatFDColoringCreate_MPIAIJ, 2505 0, 2506 MatSetUnfactored_MPIAIJ, 2507 MatPermute_MPIAIJ, 2508 0, 2509 /*60*/ MatGetSubMatrix_MPIAIJ, 2510 MatDestroy_MPIAIJ, 2511 MatView_MPIAIJ, 2512 0, 2513 0, 2514 /*65*/ 0, 2515 0, 2516 0, 2517 0, 2518 0, 2519 /*70*/ MatGetRowMaxAbs_MPIAIJ, 2520 0, 2521 MatSetColoring_MPIAIJ, 2522 #if defined(PETSC_HAVE_ADIC) 2523 MatSetValuesAdic_MPIAIJ, 2524 #else 2525 0, 2526 #endif 2527 MatSetValuesAdifor_MPIAIJ, 2528 /*75*/ 0, 2529 0, 2530 0, 2531 0, 2532 0, 2533 /*80*/ 0, 2534 0, 2535 0, 2536 0, 2537 /*84*/ MatLoad_MPIAIJ, 2538 0, 2539 0, 2540 0, 2541 0, 2542 0, 2543 /*90*/ MatMatMult_MPIAIJ_MPIAIJ, 2544 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2545 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2546 MatPtAP_Basic, 2547 MatPtAPSymbolic_MPIAIJ, 2548 /*95*/ MatPtAPNumeric_MPIAIJ, 2549 0, 2550 0, 2551 0, 2552 0, 2553 /*100*/0, 2554 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2555 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2556 MatConjugate_MPIAIJ, 2557 0, 2558 /*105*/MatSetValuesRow_MPIAIJ, 2559 MatRealPart_MPIAIJ, 2560 MatImaginaryPart_MPIAIJ, 2561 0, 2562 0, 2563 /*110*/0, 2564 MatGetRedundantMatrix_MPIAIJ, 2565 MatGetRowMin_MPIAIJ, 2566 0, 2567 0, 2568 /*115*/MatGetSeqNonzerostructure_MPIAIJ}; 2569 2570 /* ----------------------------------------------------------------------------------------*/ 2571 2572 EXTERN_C_BEGIN 2573 #undef __FUNCT__ 2574 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2575 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2576 { 2577 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2578 PetscErrorCode ierr; 2579 2580 PetscFunctionBegin; 2581 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2582 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2583 PetscFunctionReturn(0); 2584 } 2585 EXTERN_C_END 2586 2587 EXTERN_C_BEGIN 2588 #undef __FUNCT__ 2589 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2590 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2591 { 2592 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2593 PetscErrorCode ierr; 2594 2595 PetscFunctionBegin; 2596 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2597 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2598 PetscFunctionReturn(0); 2599 } 2600 EXTERN_C_END 2601 2602 #include "petscpc.h" 2603 EXTERN_C_BEGIN 2604 #undef __FUNCT__ 2605 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2606 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2607 { 2608 Mat_MPIAIJ *b; 2609 PetscErrorCode ierr; 2610 PetscInt i; 2611 2612 PetscFunctionBegin; 2613 B->preallocated = PETSC_TRUE; 2614 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2615 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2616 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2617 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2618 2619 B->rmap.bs = B->cmap.bs = 1; 2620 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2621 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2622 if (d_nnz) { 2623 for (i=0; i<B->rmap.n; i++) { 2624 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than 0: local row %D value %D",i,d_nnz[i]); 2625 } 2626 } 2627 if (o_nnz) { 2628 for (i=0; i<B->rmap.n; i++) { 2629 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than 0: local row %D value %D",i,o_nnz[i]); 2630 } 2631 } 2632 b = (Mat_MPIAIJ*)B->data; 2633 2634 /* Explicitly create 2 MATSEQAIJ matrices. */ 2635 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2636 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2637 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2638 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2639 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2640 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2641 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2642 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2643 2644 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2645 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2646 2647 PetscFunctionReturn(0); 2648 } 2649 EXTERN_C_END 2650 2651 #undef __FUNCT__ 2652 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2653 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2654 { 2655 Mat mat; 2656 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2657 PetscErrorCode ierr; 2658 2659 PetscFunctionBegin; 2660 *newmat = 0; 2661 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2662 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2663 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2664 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2665 a = (Mat_MPIAIJ*)mat->data; 2666 2667 mat->factor = matin->factor; 2668 mat->rmap.bs = matin->rmap.bs; 2669 mat->assembled = PETSC_TRUE; 2670 mat->insertmode = NOT_SET_VALUES; 2671 mat->preallocated = PETSC_TRUE; 2672 2673 a->size = oldmat->size; 2674 a->rank = oldmat->rank; 2675 a->donotstash = oldmat->donotstash; 2676 a->roworiented = oldmat->roworiented; 2677 a->rowindices = 0; 2678 a->rowvalues = 0; 2679 a->getrowactive = PETSC_FALSE; 2680 2681 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2682 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2683 2684 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2685 if (oldmat->colmap) { 2686 #if defined (PETSC_USE_CTABLE) 2687 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2688 #else 2689 ierr = PetscMalloc((mat->cmap.N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2690 ierr = PetscLogObjectMemory(mat,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2691 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2692 #endif 2693 } else a->colmap = 0; 2694 if (oldmat->garray) { 2695 PetscInt len; 2696 len = oldmat->B->cmap.n; 2697 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2698 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2699 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2700 } else a->garray = 0; 2701 2702 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2703 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2704 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2705 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2706 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2707 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2708 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2709 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2710 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2711 *newmat = mat; 2712 PetscFunctionReturn(0); 2713 } 2714 2715 #include "petscsys.h" 2716 2717 #undef __FUNCT__ 2718 #define __FUNCT__ "MatLoad_MPIAIJ" 2719 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2720 { 2721 Mat A; 2722 PetscScalar *vals,*svals; 2723 MPI_Comm comm = ((PetscObject)viewer)->comm; 2724 MPI_Status status; 2725 PetscErrorCode ierr; 2726 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2727 PetscInt i,nz,j,rstart,rend,mmax; 2728 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2729 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2730 PetscInt cend,cstart,n,*rowners; 2731 int fd; 2732 2733 PetscFunctionBegin; 2734 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2735 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2736 if (!rank) { 2737 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2738 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2739 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2740 } 2741 2742 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2743 M = header[1]; N = header[2]; 2744 /* determine ownership of all rows */ 2745 m = M/size + ((M % size) > rank); 2746 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2747 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2748 2749 /* First process needs enough room for process with most rows */ 2750 if (!rank) { 2751 mmax = rowners[1]; 2752 for (i=2; i<size; i++) { 2753 mmax = PetscMax(mmax,rowners[i]); 2754 } 2755 } else mmax = m; 2756 2757 rowners[0] = 0; 2758 for (i=2; i<=size; i++) { 2759 rowners[i] += rowners[i-1]; 2760 } 2761 rstart = rowners[rank]; 2762 rend = rowners[rank+1]; 2763 2764 /* distribute row lengths to all processors */ 2765 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2766 if (!rank) { 2767 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2768 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2769 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2770 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2771 for (j=0; j<m; j++) { 2772 procsnz[0] += ourlens[j]; 2773 } 2774 for (i=1; i<size; i++) { 2775 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2776 /* calculate the number of nonzeros on each processor */ 2777 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2778 procsnz[i] += rowlengths[j]; 2779 } 2780 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2781 } 2782 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2783 } else { 2784 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2785 } 2786 2787 if (!rank) { 2788 /* determine max buffer needed and allocate it */ 2789 maxnz = 0; 2790 for (i=0; i<size; i++) { 2791 maxnz = PetscMax(maxnz,procsnz[i]); 2792 } 2793 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2794 2795 /* read in my part of the matrix column indices */ 2796 nz = procsnz[0]; 2797 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2798 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2799 2800 /* read in every one elses and ship off */ 2801 for (i=1; i<size; i++) { 2802 nz = procsnz[i]; 2803 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2804 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2805 } 2806 ierr = PetscFree(cols);CHKERRQ(ierr); 2807 } else { 2808 /* determine buffer space needed for message */ 2809 nz = 0; 2810 for (i=0; i<m; i++) { 2811 nz += ourlens[i]; 2812 } 2813 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2814 2815 /* receive message of column indices*/ 2816 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2817 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2818 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2819 } 2820 2821 /* determine column ownership if matrix is not square */ 2822 if (N != M) { 2823 n = N/size + ((N % size) > rank); 2824 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2825 cstart = cend - n; 2826 } else { 2827 cstart = rstart; 2828 cend = rend; 2829 n = cend - cstart; 2830 } 2831 2832 /* loop over local rows, determining number of off diagonal entries */ 2833 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2834 jj = 0; 2835 for (i=0; i<m; i++) { 2836 for (j=0; j<ourlens[i]; j++) { 2837 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2838 jj++; 2839 } 2840 } 2841 2842 /* create our matrix */ 2843 for (i=0; i<m; i++) { 2844 ourlens[i] -= offlens[i]; 2845 } 2846 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2847 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2848 ierr = MatSetType(A,type);CHKERRQ(ierr); 2849 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2850 2851 for (i=0; i<m; i++) { 2852 ourlens[i] += offlens[i]; 2853 } 2854 2855 if (!rank) { 2856 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2857 2858 /* read in my part of the matrix numerical values */ 2859 nz = procsnz[0]; 2860 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2861 2862 /* insert into matrix */ 2863 jj = rstart; 2864 smycols = mycols; 2865 svals = vals; 2866 for (i=0; i<m; i++) { 2867 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2868 smycols += ourlens[i]; 2869 svals += ourlens[i]; 2870 jj++; 2871 } 2872 2873 /* read in other processors and ship out */ 2874 for (i=1; i<size; i++) { 2875 nz = procsnz[i]; 2876 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2877 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2878 } 2879 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2880 } else { 2881 /* receive numeric values */ 2882 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2883 2884 /* receive message of values*/ 2885 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2886 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2887 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2888 2889 /* insert into matrix */ 2890 jj = rstart; 2891 smycols = mycols; 2892 svals = vals; 2893 for (i=0; i<m; i++) { 2894 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2895 smycols += ourlens[i]; 2896 svals += ourlens[i]; 2897 jj++; 2898 } 2899 } 2900 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2901 ierr = PetscFree(vals);CHKERRQ(ierr); 2902 ierr = PetscFree(mycols);CHKERRQ(ierr); 2903 ierr = PetscFree(rowners);CHKERRQ(ierr); 2904 2905 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2906 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2907 *newmat = A; 2908 PetscFunctionReturn(0); 2909 } 2910 2911 #undef __FUNCT__ 2912 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2913 /* 2914 Not great since it makes two copies of the submatrix, first an SeqAIJ 2915 in local and then by concatenating the local matrices the end result. 2916 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2917 */ 2918 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2919 { 2920 PetscErrorCode ierr; 2921 PetscMPIInt rank,size; 2922 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 2923 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2924 Mat *local,M,Mreuse; 2925 MatScalar *vwork,*aa; 2926 MPI_Comm comm = ((PetscObject)mat)->comm; 2927 Mat_SeqAIJ *aij; 2928 2929 2930 PetscFunctionBegin; 2931 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2932 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2933 2934 if (call == MAT_REUSE_MATRIX) { 2935 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2936 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2937 local = &Mreuse; 2938 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2939 } else { 2940 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2941 Mreuse = *local; 2942 ierr = PetscFree(local);CHKERRQ(ierr); 2943 } 2944 2945 /* 2946 m - number of local rows 2947 n - number of columns (same on all processors) 2948 rstart - first row in new global matrix generated 2949 */ 2950 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2951 if (call == MAT_INITIAL_MATRIX) { 2952 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2953 ii = aij->i; 2954 jj = aij->j; 2955 2956 /* 2957 Determine the number of non-zeros in the diagonal and off-diagonal 2958 portions of the matrix in order to do correct preallocation 2959 */ 2960 2961 /* first get start and end of "diagonal" columns */ 2962 if (csize == PETSC_DECIDE) { 2963 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2964 if (mglobal == n) { /* square matrix */ 2965 nlocal = m; 2966 } else { 2967 nlocal = n/size + ((n % size) > rank); 2968 } 2969 } else { 2970 nlocal = csize; 2971 } 2972 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2973 rstart = rend - nlocal; 2974 if (rank == size - 1 && rend != n) { 2975 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2976 } 2977 2978 /* next, compute all the lengths */ 2979 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2980 olens = dlens + m; 2981 for (i=0; i<m; i++) { 2982 jend = ii[i+1] - ii[i]; 2983 olen = 0; 2984 dlen = 0; 2985 for (j=0; j<jend; j++) { 2986 if (*jj < rstart || *jj >= rend) olen++; 2987 else dlen++; 2988 jj++; 2989 } 2990 olens[i] = olen; 2991 dlens[i] = dlen; 2992 } 2993 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2994 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 2995 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2996 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 2997 ierr = PetscFree(dlens);CHKERRQ(ierr); 2998 } else { 2999 PetscInt ml,nl; 3000 3001 M = *newmat; 3002 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3003 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3004 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3005 /* 3006 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3007 rather than the slower MatSetValues(). 3008 */ 3009 M->was_assembled = PETSC_TRUE; 3010 M->assembled = PETSC_FALSE; 3011 } 3012 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3013 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3014 ii = aij->i; 3015 jj = aij->j; 3016 aa = aij->a; 3017 for (i=0; i<m; i++) { 3018 row = rstart + i; 3019 nz = ii[i+1] - ii[i]; 3020 cwork = jj; jj += nz; 3021 vwork = aa; aa += nz; 3022 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3023 } 3024 3025 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3026 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3027 *newmat = M; 3028 3029 /* save submatrix used in processor for next request */ 3030 if (call == MAT_INITIAL_MATRIX) { 3031 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3032 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 3033 } 3034 3035 PetscFunctionReturn(0); 3036 } 3037 3038 EXTERN_C_BEGIN 3039 #undef __FUNCT__ 3040 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3041 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3042 { 3043 PetscInt m,cstart, cend,j,nnz,i,d; 3044 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3045 const PetscInt *JJ; 3046 PetscScalar *values; 3047 PetscErrorCode ierr; 3048 3049 PetscFunctionBegin; 3050 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3051 3052 B->rmap.bs = B->cmap.bs = 1; 3053 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 3054 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 3055 m = B->rmap.n; 3056 cstart = B->cmap.rstart; 3057 cend = B->cmap.rend; 3058 rstart = B->rmap.rstart; 3059 3060 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 3061 o_nnz = d_nnz + m; 3062 3063 #if defined(PETSC_USE_DEBUGGING) 3064 for (i=0; i<m; i++) { 3065 nnz = Ii[i+1]- Ii[i]; 3066 JJ = J + Ii[i]; 3067 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3068 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3069 if (nnz && (JJ[nnz-1] >= B->cmap.N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap.N); 3070 for (j=1; j<nnz; j++) { 3071 if (JJ[i] <= JJ[i-1]) SETERRRQ(PETSC_ERR_ARG_WRONGSTATE,"Row %D has unsorted column index at %D location in column indices",i,j); 3072 } 3073 } 3074 #endif 3075 3076 for (i=0; i<m; i++) { 3077 nnz = Ii[i+1]- Ii[i]; 3078 JJ = J + Ii[i]; 3079 nnz_max = PetscMax(nnz_max,nnz); 3080 for (j=0; j<nnz; j++) { 3081 if (*JJ >= cstart) break; 3082 JJ++; 3083 } 3084 d = 0; 3085 for (; j<nnz; j++) { 3086 if (*JJ++ >= cend) break; 3087 d++; 3088 } 3089 d_nnz[i] = d; 3090 o_nnz[i] = nnz - d; 3091 } 3092 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3093 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 3094 3095 if (v) values = (PetscScalar*)v; 3096 else { 3097 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3098 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3099 } 3100 3101 for (i=0; i<m; i++) { 3102 ii = i + rstart; 3103 nnz = Ii[i+1]- Ii[i]; 3104 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3105 } 3106 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3107 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3108 3109 if (!v) { 3110 ierr = PetscFree(values);CHKERRQ(ierr); 3111 } 3112 PetscFunctionReturn(0); 3113 } 3114 EXTERN_C_END 3115 3116 #undef __FUNCT__ 3117 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3118 /*@ 3119 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3120 (the default parallel PETSc format). 3121 3122 Collective on MPI_Comm 3123 3124 Input Parameters: 3125 + B - the matrix 3126 . i - the indices into j for the start of each local row (starts with zero) 3127 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3128 - v - optional values in the matrix 3129 3130 Level: developer 3131 3132 Notes: 3133 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3134 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3135 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3136 3137 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3138 3139 The format which is used for the sparse matrix input, is equivalent to a 3140 row-major ordering.. i.e for the following matrix, the input data expected is 3141 as shown: 3142 3143 1 0 0 3144 2 0 3 P0 3145 ------- 3146 4 5 6 P1 3147 3148 Process0 [P0]: rows_owned=[0,1] 3149 i = {0,1,3} [size = nrow+1 = 2+1] 3150 j = {0,0,2} [size = nz = 6] 3151 v = {1,2,3} [size = nz = 6] 3152 3153 Process1 [P1]: rows_owned=[2] 3154 i = {0,3} [size = nrow+1 = 1+1] 3155 j = {0,1,2} [size = nz = 6] 3156 v = {4,5,6} [size = nz = 6] 3157 3158 The column indices for each row MUST be sorted. 3159 3160 .keywords: matrix, aij, compressed row, sparse, parallel 3161 3162 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 3163 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3164 @*/ 3165 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3166 { 3167 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3168 3169 PetscFunctionBegin; 3170 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3171 if (f) { 3172 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3173 } 3174 PetscFunctionReturn(0); 3175 } 3176 3177 #undef __FUNCT__ 3178 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3179 /*@C 3180 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3181 (the default parallel PETSc format). For good matrix assembly performance 3182 the user should preallocate the matrix storage by setting the parameters 3183 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3184 performance can be increased by more than a factor of 50. 3185 3186 Collective on MPI_Comm 3187 3188 Input Parameters: 3189 + A - the matrix 3190 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3191 (same value is used for all local rows) 3192 . d_nnz - array containing the number of nonzeros in the various rows of the 3193 DIAGONAL portion of the local submatrix (possibly different for each row) 3194 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3195 The size of this array is equal to the number of local rows, i.e 'm'. 3196 You must leave room for the diagonal entry even if it is zero. 3197 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3198 submatrix (same value is used for all local rows). 3199 - o_nnz - array containing the number of nonzeros in the various rows of the 3200 OFF-DIAGONAL portion of the local submatrix (possibly different for 3201 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3202 structure. The size of this array is equal to the number 3203 of local rows, i.e 'm'. 3204 3205 If the *_nnz parameter is given then the *_nz parameter is ignored 3206 3207 The AIJ format (also called the Yale sparse matrix format or 3208 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3209 storage. The stored row and column indices begin with zero. See the users manual for details. 3210 3211 The parallel matrix is partitioned such that the first m0 rows belong to 3212 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3213 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3214 3215 The DIAGONAL portion of the local submatrix of a processor can be defined 3216 as the submatrix which is obtained by extraction the part corresponding 3217 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 3218 first row that belongs to the processor, and r2 is the last row belonging 3219 to the this processor. This is a square mxm matrix. The remaining portion 3220 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 3221 3222 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3223 3224 You can call MatGetInfo() to get information on how effective the preallocation was; 3225 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3226 You can also run with the option -info and look for messages with the string 3227 malloc in them to see if additional memory allocation was needed. 3228 3229 Example usage: 3230 3231 Consider the following 8x8 matrix with 34 non-zero values, that is 3232 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3233 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3234 as follows: 3235 3236 .vb 3237 1 2 0 | 0 3 0 | 0 4 3238 Proc0 0 5 6 | 7 0 0 | 8 0 3239 9 0 10 | 11 0 0 | 12 0 3240 ------------------------------------- 3241 13 0 14 | 15 16 17 | 0 0 3242 Proc1 0 18 0 | 19 20 21 | 0 0 3243 0 0 0 | 22 23 0 | 24 0 3244 ------------------------------------- 3245 Proc2 25 26 27 | 0 0 28 | 29 0 3246 30 0 0 | 31 32 33 | 0 34 3247 .ve 3248 3249 This can be represented as a collection of submatrices as: 3250 3251 .vb 3252 A B C 3253 D E F 3254 G H I 3255 .ve 3256 3257 Where the submatrices A,B,C are owned by proc0, D,E,F are 3258 owned by proc1, G,H,I are owned by proc2. 3259 3260 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3261 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3262 The 'M','N' parameters are 8,8, and have the same values on all procs. 3263 3264 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3265 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3266 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3267 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3268 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3269 matrix, ans [DF] as another SeqAIJ matrix. 3270 3271 When d_nz, o_nz parameters are specified, d_nz storage elements are 3272 allocated for every row of the local diagonal submatrix, and o_nz 3273 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3274 One way to choose d_nz and o_nz is to use the max nonzerors per local 3275 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3276 In this case, the values of d_nz,o_nz are: 3277 .vb 3278 proc0 : dnz = 2, o_nz = 2 3279 proc1 : dnz = 3, o_nz = 2 3280 proc2 : dnz = 1, o_nz = 4 3281 .ve 3282 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3283 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3284 for proc3. i.e we are using 12+15+10=37 storage locations to store 3285 34 values. 3286 3287 When d_nnz, o_nnz parameters are specified, the storage is specified 3288 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3289 In the above case the values for d_nnz,o_nnz are: 3290 .vb 3291 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3292 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3293 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3294 .ve 3295 Here the space allocated is sum of all the above values i.e 34, and 3296 hence pre-allocation is perfect. 3297 3298 Level: intermediate 3299 3300 .keywords: matrix, aij, compressed row, sparse, parallel 3301 3302 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3303 MPIAIJ, MatGetInfo() 3304 @*/ 3305 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3306 { 3307 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3308 3309 PetscFunctionBegin; 3310 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3311 if (f) { 3312 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3313 } 3314 PetscFunctionReturn(0); 3315 } 3316 3317 #undef __FUNCT__ 3318 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3319 /*@ 3320 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3321 CSR format the local rows. 3322 3323 Collective on MPI_Comm 3324 3325 Input Parameters: 3326 + comm - MPI communicator 3327 . m - number of local rows (Cannot be PETSC_DECIDE) 3328 . n - This value should be the same as the local size used in creating the 3329 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3330 calculated if N is given) For square matrices n is almost always m. 3331 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3332 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3333 . i - row indices 3334 . j - column indices 3335 - a - matrix values 3336 3337 Output Parameter: 3338 . mat - the matrix 3339 3340 Level: intermediate 3341 3342 Notes: 3343 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3344 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3345 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3346 3347 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3348 3349 The format which is used for the sparse matrix input, is equivalent to a 3350 row-major ordering.. i.e for the following matrix, the input data expected is 3351 as shown: 3352 3353 1 0 0 3354 2 0 3 P0 3355 ------- 3356 4 5 6 P1 3357 3358 Process0 [P0]: rows_owned=[0,1] 3359 i = {0,1,3} [size = nrow+1 = 2+1] 3360 j = {0,0,2} [size = nz = 6] 3361 v = {1,2,3} [size = nz = 6] 3362 3363 Process1 [P1]: rows_owned=[2] 3364 i = {0,3} [size = nrow+1 = 1+1] 3365 j = {0,1,2} [size = nz = 6] 3366 v = {4,5,6} [size = nz = 6] 3367 3368 .keywords: matrix, aij, compressed row, sparse, parallel 3369 3370 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3371 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3372 @*/ 3373 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3374 { 3375 PetscErrorCode ierr; 3376 3377 PetscFunctionBegin; 3378 if (i[0]) { 3379 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3380 } 3381 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3382 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3383 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3384 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3385 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3386 PetscFunctionReturn(0); 3387 } 3388 3389 #undef __FUNCT__ 3390 #define __FUNCT__ "MatCreateMPIAIJ" 3391 /*@C 3392 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3393 (the default parallel PETSc format). For good matrix assembly performance 3394 the user should preallocate the matrix storage by setting the parameters 3395 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3396 performance can be increased by more than a factor of 50. 3397 3398 Collective on MPI_Comm 3399 3400 Input Parameters: 3401 + comm - MPI communicator 3402 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3403 This value should be the same as the local size used in creating the 3404 y vector for the matrix-vector product y = Ax. 3405 . n - This value should be the same as the local size used in creating the 3406 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3407 calculated if N is given) For square matrices n is almost always m. 3408 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3409 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3410 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3411 (same value is used for all local rows) 3412 . d_nnz - array containing the number of nonzeros in the various rows of the 3413 DIAGONAL portion of the local submatrix (possibly different for each row) 3414 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3415 The size of this array is equal to the number of local rows, i.e 'm'. 3416 You must leave room for the diagonal entry even if it is zero. 3417 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3418 submatrix (same value is used for all local rows). 3419 - o_nnz - array containing the number of nonzeros in the various rows of the 3420 OFF-DIAGONAL portion of the local submatrix (possibly different for 3421 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3422 structure. The size of this array is equal to the number 3423 of local rows, i.e 'm'. 3424 3425 Output Parameter: 3426 . A - the matrix 3427 3428 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3429 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3430 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3431 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3432 3433 Notes: 3434 If the *_nnz parameter is given then the *_nz parameter is ignored 3435 3436 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3437 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3438 storage requirements for this matrix. 3439 3440 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3441 processor than it must be used on all processors that share the object for 3442 that argument. 3443 3444 The user MUST specify either the local or global matrix dimensions 3445 (possibly both). 3446 3447 The parallel matrix is partitioned across processors such that the 3448 first m0 rows belong to process 0, the next m1 rows belong to 3449 process 1, the next m2 rows belong to process 2 etc.. where 3450 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3451 values corresponding to [m x N] submatrix. 3452 3453 The columns are logically partitioned with the n0 columns belonging 3454 to 0th partition, the next n1 columns belonging to the next 3455 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3456 3457 The DIAGONAL portion of the local submatrix on any given processor 3458 is the submatrix corresponding to the rows and columns m,n 3459 corresponding to the given processor. i.e diagonal matrix on 3460 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3461 etc. The remaining portion of the local submatrix [m x (N-n)] 3462 constitute the OFF-DIAGONAL portion. The example below better 3463 illustrates this concept. 3464 3465 For a square global matrix we define each processor's diagonal portion 3466 to be its local rows and the corresponding columns (a square submatrix); 3467 each processor's off-diagonal portion encompasses the remainder of the 3468 local matrix (a rectangular submatrix). 3469 3470 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3471 3472 When calling this routine with a single process communicator, a matrix of 3473 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3474 type of communicator, use the construction mechanism: 3475 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3476 3477 By default, this format uses inodes (identical nodes) when possible. 3478 We search for consecutive rows with the same nonzero structure, thereby 3479 reusing matrix information to achieve increased efficiency. 3480 3481 Options Database Keys: 3482 + -mat_no_inode - Do not use inodes 3483 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3484 - -mat_aij_oneindex - Internally use indexing starting at 1 3485 rather than 0. Note that when calling MatSetValues(), 3486 the user still MUST index entries starting at 0! 3487 3488 3489 Example usage: 3490 3491 Consider the following 8x8 matrix with 34 non-zero values, that is 3492 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3493 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3494 as follows: 3495 3496 .vb 3497 1 2 0 | 0 3 0 | 0 4 3498 Proc0 0 5 6 | 7 0 0 | 8 0 3499 9 0 10 | 11 0 0 | 12 0 3500 ------------------------------------- 3501 13 0 14 | 15 16 17 | 0 0 3502 Proc1 0 18 0 | 19 20 21 | 0 0 3503 0 0 0 | 22 23 0 | 24 0 3504 ------------------------------------- 3505 Proc2 25 26 27 | 0 0 28 | 29 0 3506 30 0 0 | 31 32 33 | 0 34 3507 .ve 3508 3509 This can be represented as a collection of submatrices as: 3510 3511 .vb 3512 A B C 3513 D E F 3514 G H I 3515 .ve 3516 3517 Where the submatrices A,B,C are owned by proc0, D,E,F are 3518 owned by proc1, G,H,I are owned by proc2. 3519 3520 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3521 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3522 The 'M','N' parameters are 8,8, and have the same values on all procs. 3523 3524 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3525 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3526 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3527 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3528 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3529 matrix, ans [DF] as another SeqAIJ matrix. 3530 3531 When d_nz, o_nz parameters are specified, d_nz storage elements are 3532 allocated for every row of the local diagonal submatrix, and o_nz 3533 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3534 One way to choose d_nz and o_nz is to use the max nonzerors per local 3535 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3536 In this case, the values of d_nz,o_nz are: 3537 .vb 3538 proc0 : dnz = 2, o_nz = 2 3539 proc1 : dnz = 3, o_nz = 2 3540 proc2 : dnz = 1, o_nz = 4 3541 .ve 3542 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3543 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3544 for proc3. i.e we are using 12+15+10=37 storage locations to store 3545 34 values. 3546 3547 When d_nnz, o_nnz parameters are specified, the storage is specified 3548 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3549 In the above case the values for d_nnz,o_nnz are: 3550 .vb 3551 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3552 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3553 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3554 .ve 3555 Here the space allocated is sum of all the above values i.e 34, and 3556 hence pre-allocation is perfect. 3557 3558 Level: intermediate 3559 3560 .keywords: matrix, aij, compressed row, sparse, parallel 3561 3562 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3563 MPIAIJ, MatCreateMPIAIJWithArrays() 3564 @*/ 3565 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3566 { 3567 PetscErrorCode ierr; 3568 PetscMPIInt size; 3569 3570 PetscFunctionBegin; 3571 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3572 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3573 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3574 if (size > 1) { 3575 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3576 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3577 } else { 3578 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3579 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3580 } 3581 PetscFunctionReturn(0); 3582 } 3583 3584 #undef __FUNCT__ 3585 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3586 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3587 { 3588 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3589 3590 PetscFunctionBegin; 3591 *Ad = a->A; 3592 *Ao = a->B; 3593 *colmap = a->garray; 3594 PetscFunctionReturn(0); 3595 } 3596 3597 #undef __FUNCT__ 3598 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3599 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3600 { 3601 PetscErrorCode ierr; 3602 PetscInt i; 3603 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3604 3605 PetscFunctionBegin; 3606 if (coloring->ctype == IS_COLORING_GLOBAL) { 3607 ISColoringValue *allcolors,*colors; 3608 ISColoring ocoloring; 3609 3610 /* set coloring for diagonal portion */ 3611 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3612 3613 /* set coloring for off-diagonal portion */ 3614 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3615 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3616 for (i=0; i<a->B->cmap.n; i++) { 3617 colors[i] = allcolors[a->garray[i]]; 3618 } 3619 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3620 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3621 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3622 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3623 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3624 ISColoringValue *colors; 3625 PetscInt *larray; 3626 ISColoring ocoloring; 3627 3628 /* set coloring for diagonal portion */ 3629 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3630 for (i=0; i<a->A->cmap.n; i++) { 3631 larray[i] = i + A->cmap.rstart; 3632 } 3633 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap.n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3634 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3635 for (i=0; i<a->A->cmap.n; i++) { 3636 colors[i] = coloring->colors[larray[i]]; 3637 } 3638 ierr = PetscFree(larray);CHKERRQ(ierr); 3639 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3640 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3641 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3642 3643 /* set coloring for off-diagonal portion */ 3644 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3645 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap.n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3646 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3647 for (i=0; i<a->B->cmap.n; i++) { 3648 colors[i] = coloring->colors[larray[i]]; 3649 } 3650 ierr = PetscFree(larray);CHKERRQ(ierr); 3651 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3652 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3653 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3654 } else { 3655 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3656 } 3657 3658 PetscFunctionReturn(0); 3659 } 3660 3661 #if defined(PETSC_HAVE_ADIC) 3662 #undef __FUNCT__ 3663 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3664 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3665 { 3666 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3667 PetscErrorCode ierr; 3668 3669 PetscFunctionBegin; 3670 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3671 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3672 PetscFunctionReturn(0); 3673 } 3674 #endif 3675 3676 #undef __FUNCT__ 3677 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3678 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3679 { 3680 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3681 PetscErrorCode ierr; 3682 3683 PetscFunctionBegin; 3684 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3685 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3686 PetscFunctionReturn(0); 3687 } 3688 3689 #undef __FUNCT__ 3690 #define __FUNCT__ "MatMerge" 3691 /*@ 3692 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3693 matrices from each processor 3694 3695 Collective on MPI_Comm 3696 3697 Input Parameters: 3698 + comm - the communicators the parallel matrix will live on 3699 . inmat - the input sequential matrices 3700 . n - number of local columns (or PETSC_DECIDE) 3701 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3702 3703 Output Parameter: 3704 . outmat - the parallel matrix generated 3705 3706 Level: advanced 3707 3708 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3709 3710 @*/ 3711 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3712 { 3713 PetscErrorCode ierr; 3714 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3715 PetscInt *indx; 3716 PetscScalar *values; 3717 3718 PetscFunctionBegin; 3719 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3720 if (scall == MAT_INITIAL_MATRIX){ 3721 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3722 if (n == PETSC_DECIDE){ 3723 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3724 } 3725 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3726 rstart -= m; 3727 3728 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3729 for (i=0;i<m;i++) { 3730 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3731 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3732 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3733 } 3734 /* This routine will ONLY return MPIAIJ type matrix */ 3735 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3736 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3737 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3738 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3739 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3740 3741 } else if (scall == MAT_REUSE_MATRIX){ 3742 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3743 } else { 3744 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3745 } 3746 3747 for (i=0;i<m;i++) { 3748 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3749 Ii = i + rstart; 3750 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3751 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3752 } 3753 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3754 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3755 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3756 3757 PetscFunctionReturn(0); 3758 } 3759 3760 #undef __FUNCT__ 3761 #define __FUNCT__ "MatFileSplit" 3762 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3763 { 3764 PetscErrorCode ierr; 3765 PetscMPIInt rank; 3766 PetscInt m,N,i,rstart,nnz; 3767 size_t len; 3768 const PetscInt *indx; 3769 PetscViewer out; 3770 char *name; 3771 Mat B; 3772 const PetscScalar *values; 3773 3774 PetscFunctionBegin; 3775 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3776 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3777 /* Should this be the type of the diagonal block of A? */ 3778 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3779 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3780 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3781 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3782 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3783 for (i=0;i<m;i++) { 3784 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3785 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3786 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3787 } 3788 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3789 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3790 3791 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3792 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3793 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3794 sprintf(name,"%s.%d",outfile,rank); 3795 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3796 ierr = PetscFree(name); 3797 ierr = MatView(B,out);CHKERRQ(ierr); 3798 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3799 ierr = MatDestroy(B);CHKERRQ(ierr); 3800 PetscFunctionReturn(0); 3801 } 3802 3803 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3804 #undef __FUNCT__ 3805 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3806 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3807 { 3808 PetscErrorCode ierr; 3809 Mat_Merge_SeqsToMPI *merge; 3810 PetscContainer container; 3811 3812 PetscFunctionBegin; 3813 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3814 if (container) { 3815 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3816 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3817 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3818 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3819 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3820 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3821 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3822 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3823 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3824 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3825 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3826 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3827 3828 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3829 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3830 } 3831 ierr = PetscFree(merge);CHKERRQ(ierr); 3832 3833 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3834 PetscFunctionReturn(0); 3835 } 3836 3837 #include "src/mat/utils/freespace.h" 3838 #include "petscbt.h" 3839 3840 #undef __FUNCT__ 3841 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3842 /*@C 3843 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3844 matrices from each processor 3845 3846 Collective on MPI_Comm 3847 3848 Input Parameters: 3849 + comm - the communicators the parallel matrix will live on 3850 . seqmat - the input sequential matrices 3851 . m - number of local rows (or PETSC_DECIDE) 3852 . n - number of local columns (or PETSC_DECIDE) 3853 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3854 3855 Output Parameter: 3856 . mpimat - the parallel matrix generated 3857 3858 Level: advanced 3859 3860 Notes: 3861 The dimensions of the sequential matrix in each processor MUST be the same. 3862 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3863 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3864 @*/ 3865 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3866 { 3867 PetscErrorCode ierr; 3868 MPI_Comm comm=((PetscObject)mpimat)->comm; 3869 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3870 PetscMPIInt size,rank,taga,*len_s; 3871 PetscInt N=mpimat->cmap.N,i,j,*owners,*ai=a->i,*aj=a->j; 3872 PetscInt proc,m; 3873 PetscInt **buf_ri,**buf_rj; 3874 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3875 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3876 MPI_Request *s_waits,*r_waits; 3877 MPI_Status *status; 3878 MatScalar *aa=a->a; 3879 MatScalar **abuf_r,*ba_i; 3880 Mat_Merge_SeqsToMPI *merge; 3881 PetscContainer container; 3882 3883 PetscFunctionBegin; 3884 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3885 3886 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3887 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3888 3889 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3890 if (container) { 3891 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3892 } 3893 bi = merge->bi; 3894 bj = merge->bj; 3895 buf_ri = merge->buf_ri; 3896 buf_rj = merge->buf_rj; 3897 3898 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3899 owners = merge->rowmap.range; 3900 len_s = merge->len_s; 3901 3902 /* send and recv matrix values */ 3903 /*-----------------------------*/ 3904 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3905 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3906 3907 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3908 for (proc=0,k=0; proc<size; proc++){ 3909 if (!len_s[proc]) continue; 3910 i = owners[proc]; 3911 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3912 k++; 3913 } 3914 3915 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3916 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3917 ierr = PetscFree(status);CHKERRQ(ierr); 3918 3919 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3920 ierr = PetscFree(r_waits);CHKERRQ(ierr); 3921 3922 /* insert mat values of mpimat */ 3923 /*----------------------------*/ 3924 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 3925 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3926 nextrow = buf_ri_k + merge->nrecv; 3927 nextai = nextrow + merge->nrecv; 3928 3929 for (k=0; k<merge->nrecv; k++){ 3930 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3931 nrows = *(buf_ri_k[k]); 3932 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 3933 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3934 } 3935 3936 /* set values of ba */ 3937 m = merge->rowmap.n; 3938 for (i=0; i<m; i++) { 3939 arow = owners[rank] + i; 3940 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 3941 bnzi = bi[i+1] - bi[i]; 3942 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 3943 3944 /* add local non-zero vals of this proc's seqmat into ba */ 3945 anzi = ai[arow+1] - ai[arow]; 3946 aj = a->j + ai[arow]; 3947 aa = a->a + ai[arow]; 3948 nextaj = 0; 3949 for (j=0; nextaj<anzi; j++){ 3950 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3951 ba_i[j] += aa[nextaj++]; 3952 } 3953 } 3954 3955 /* add received vals into ba */ 3956 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3957 /* i-th row */ 3958 if (i == *nextrow[k]) { 3959 anzi = *(nextai[k]+1) - *nextai[k]; 3960 aj = buf_rj[k] + *(nextai[k]); 3961 aa = abuf_r[k] + *(nextai[k]); 3962 nextaj = 0; 3963 for (j=0; nextaj<anzi; j++){ 3964 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3965 ba_i[j] += aa[nextaj++]; 3966 } 3967 } 3968 nextrow[k]++; nextai[k]++; 3969 } 3970 } 3971 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 3972 } 3973 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3974 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3975 3976 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 3977 ierr = PetscFree(ba_i);CHKERRQ(ierr); 3978 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3979 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3980 PetscFunctionReturn(0); 3981 } 3982 3983 #undef __FUNCT__ 3984 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 3985 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 3986 { 3987 PetscErrorCode ierr; 3988 Mat B_mpi; 3989 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3990 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 3991 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 3992 PetscInt M=seqmat->rmap.n,N=seqmat->cmap.n,i,*owners,*ai=a->i,*aj=a->j; 3993 PetscInt len,proc,*dnz,*onz; 3994 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 3995 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 3996 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 3997 MPI_Status *status; 3998 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 3999 PetscBT lnkbt; 4000 Mat_Merge_SeqsToMPI *merge; 4001 PetscContainer container; 4002 4003 PetscFunctionBegin; 4004 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4005 4006 /* make sure it is a PETSc comm */ 4007 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4008 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4009 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4010 4011 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4012 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4013 4014 /* determine row ownership */ 4015 /*---------------------------------------------------------*/ 4016 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 4017 merge->rowmap.n = m; 4018 merge->rowmap.N = M; 4019 merge->rowmap.bs = 1; 4020 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 4021 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4022 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4023 4024 m = merge->rowmap.n; 4025 M = merge->rowmap.N; 4026 owners = merge->rowmap.range; 4027 4028 /* determine the number of messages to send, their lengths */ 4029 /*---------------------------------------------------------*/ 4030 len_s = merge->len_s; 4031 4032 len = 0; /* length of buf_si[] */ 4033 merge->nsend = 0; 4034 for (proc=0; proc<size; proc++){ 4035 len_si[proc] = 0; 4036 if (proc == rank){ 4037 len_s[proc] = 0; 4038 } else { 4039 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4040 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4041 } 4042 if (len_s[proc]) { 4043 merge->nsend++; 4044 nrows = 0; 4045 for (i=owners[proc]; i<owners[proc+1]; i++){ 4046 if (ai[i+1] > ai[i]) nrows++; 4047 } 4048 len_si[proc] = 2*(nrows+1); 4049 len += len_si[proc]; 4050 } 4051 } 4052 4053 /* determine the number and length of messages to receive for ij-structure */ 4054 /*-------------------------------------------------------------------------*/ 4055 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4056 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4057 4058 /* post the Irecv of j-structure */ 4059 /*-------------------------------*/ 4060 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4061 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4062 4063 /* post the Isend of j-structure */ 4064 /*--------------------------------*/ 4065 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 4066 sj_waits = si_waits + merge->nsend; 4067 4068 for (proc=0, k=0; proc<size; proc++){ 4069 if (!len_s[proc]) continue; 4070 i = owners[proc]; 4071 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4072 k++; 4073 } 4074 4075 /* receives and sends of j-structure are complete */ 4076 /*------------------------------------------------*/ 4077 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4078 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4079 4080 /* send and recv i-structure */ 4081 /*---------------------------*/ 4082 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4083 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4084 4085 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4086 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4087 for (proc=0,k=0; proc<size; proc++){ 4088 if (!len_s[proc]) continue; 4089 /* form outgoing message for i-structure: 4090 buf_si[0]: nrows to be sent 4091 [1:nrows]: row index (global) 4092 [nrows+1:2*nrows+1]: i-structure index 4093 */ 4094 /*-------------------------------------------*/ 4095 nrows = len_si[proc]/2 - 1; 4096 buf_si_i = buf_si + nrows+1; 4097 buf_si[0] = nrows; 4098 buf_si_i[0] = 0; 4099 nrows = 0; 4100 for (i=owners[proc]; i<owners[proc+1]; i++){ 4101 anzi = ai[i+1] - ai[i]; 4102 if (anzi) { 4103 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4104 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4105 nrows++; 4106 } 4107 } 4108 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4109 k++; 4110 buf_si += len_si[proc]; 4111 } 4112 4113 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4114 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4115 4116 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4117 for (i=0; i<merge->nrecv; i++){ 4118 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 4119 } 4120 4121 ierr = PetscFree(len_si);CHKERRQ(ierr); 4122 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4123 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4124 ierr = PetscFree(si_waits);CHKERRQ(ierr); 4125 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4126 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4127 ierr = PetscFree(status);CHKERRQ(ierr); 4128 4129 /* compute a local seq matrix in each processor */ 4130 /*----------------------------------------------*/ 4131 /* allocate bi array and free space for accumulating nonzero column info */ 4132 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4133 bi[0] = 0; 4134 4135 /* create and initialize a linked list */ 4136 nlnk = N+1; 4137 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4138 4139 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4140 len = 0; 4141 len = ai[owners[rank+1]] - ai[owners[rank]]; 4142 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4143 current_space = free_space; 4144 4145 /* determine symbolic info for each local row */ 4146 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4147 nextrow = buf_ri_k + merge->nrecv; 4148 nextai = nextrow + merge->nrecv; 4149 for (k=0; k<merge->nrecv; k++){ 4150 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4151 nrows = *buf_ri_k[k]; 4152 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4153 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4154 } 4155 4156 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4157 len = 0; 4158 for (i=0;i<m;i++) { 4159 bnzi = 0; 4160 /* add local non-zero cols of this proc's seqmat into lnk */ 4161 arow = owners[rank] + i; 4162 anzi = ai[arow+1] - ai[arow]; 4163 aj = a->j + ai[arow]; 4164 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4165 bnzi += nlnk; 4166 /* add received col data into lnk */ 4167 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4168 if (i == *nextrow[k]) { /* i-th row */ 4169 anzi = *(nextai[k]+1) - *nextai[k]; 4170 aj = buf_rj[k] + *nextai[k]; 4171 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4172 bnzi += nlnk; 4173 nextrow[k]++; nextai[k]++; 4174 } 4175 } 4176 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4177 4178 /* if free space is not available, make more free space */ 4179 if (current_space->local_remaining<bnzi) { 4180 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4181 nspacedouble++; 4182 } 4183 /* copy data into free space, then initialize lnk */ 4184 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4185 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4186 4187 current_space->array += bnzi; 4188 current_space->local_used += bnzi; 4189 current_space->local_remaining -= bnzi; 4190 4191 bi[i+1] = bi[i] + bnzi; 4192 } 4193 4194 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4195 4196 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4197 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4198 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4199 4200 /* create symbolic parallel matrix B_mpi */ 4201 /*---------------------------------------*/ 4202 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4203 if (n==PETSC_DECIDE) { 4204 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4205 } else { 4206 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4207 } 4208 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4209 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4210 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4211 4212 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 4213 B_mpi->assembled = PETSC_FALSE; 4214 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4215 merge->bi = bi; 4216 merge->bj = bj; 4217 merge->buf_ri = buf_ri; 4218 merge->buf_rj = buf_rj; 4219 merge->coi = PETSC_NULL; 4220 merge->coj = PETSC_NULL; 4221 merge->owners_co = PETSC_NULL; 4222 4223 /* attach the supporting struct to B_mpi for reuse */ 4224 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4225 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4226 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4227 *mpimat = B_mpi; 4228 4229 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4230 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4231 PetscFunctionReturn(0); 4232 } 4233 4234 #undef __FUNCT__ 4235 #define __FUNCT__ "MatMerge_SeqsToMPI" 4236 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4237 { 4238 PetscErrorCode ierr; 4239 4240 PetscFunctionBegin; 4241 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4242 if (scall == MAT_INITIAL_MATRIX){ 4243 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4244 } 4245 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4246 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4247 PetscFunctionReturn(0); 4248 } 4249 4250 #undef __FUNCT__ 4251 #define __FUNCT__ "MatGetLocalMat" 4252 /*@ 4253 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4254 4255 Not Collective 4256 4257 Input Parameters: 4258 + A - the matrix 4259 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4260 4261 Output Parameter: 4262 . A_loc - the local sequential matrix generated 4263 4264 Level: developer 4265 4266 @*/ 4267 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4268 { 4269 PetscErrorCode ierr; 4270 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4271 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4272 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4273 MatScalar *aa=a->a,*ba=b->a,*cam; 4274 PetscScalar *ca; 4275 PetscInt am=A->rmap.n,i,j,k,cstart=A->cmap.rstart; 4276 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4277 4278 PetscFunctionBegin; 4279 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4280 if (scall == MAT_INITIAL_MATRIX){ 4281 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4282 ci[0] = 0; 4283 for (i=0; i<am; i++){ 4284 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4285 } 4286 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4287 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4288 k = 0; 4289 for (i=0; i<am; i++) { 4290 ncols_o = bi[i+1] - bi[i]; 4291 ncols_d = ai[i+1] - ai[i]; 4292 /* off-diagonal portion of A */ 4293 for (jo=0; jo<ncols_o; jo++) { 4294 col = cmap[*bj]; 4295 if (col >= cstart) break; 4296 cj[k] = col; bj++; 4297 ca[k++] = *ba++; 4298 } 4299 /* diagonal portion of A */ 4300 for (j=0; j<ncols_d; j++) { 4301 cj[k] = cstart + *aj++; 4302 ca[k++] = *aa++; 4303 } 4304 /* off-diagonal portion of A */ 4305 for (j=jo; j<ncols_o; j++) { 4306 cj[k] = cmap[*bj++]; 4307 ca[k++] = *ba++; 4308 } 4309 } 4310 /* put together the new matrix */ 4311 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap.N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4312 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4313 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4314 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4315 mat->free_a = PETSC_TRUE; 4316 mat->free_ij = PETSC_TRUE; 4317 mat->nonew = 0; 4318 } else if (scall == MAT_REUSE_MATRIX){ 4319 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4320 ci = mat->i; cj = mat->j; cam = mat->a; 4321 for (i=0; i<am; i++) { 4322 /* off-diagonal portion of A */ 4323 ncols_o = bi[i+1] - bi[i]; 4324 for (jo=0; jo<ncols_o; jo++) { 4325 col = cmap[*bj]; 4326 if (col >= cstart) break; 4327 *cam++ = *ba++; bj++; 4328 } 4329 /* diagonal portion of A */ 4330 ncols_d = ai[i+1] - ai[i]; 4331 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4332 /* off-diagonal portion of A */ 4333 for (j=jo; j<ncols_o; j++) { 4334 *cam++ = *ba++; bj++; 4335 } 4336 } 4337 } else { 4338 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4339 } 4340 4341 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4342 PetscFunctionReturn(0); 4343 } 4344 4345 #undef __FUNCT__ 4346 #define __FUNCT__ "MatGetLocalMatCondensed" 4347 /*@C 4348 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4349 4350 Not Collective 4351 4352 Input Parameters: 4353 + A - the matrix 4354 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4355 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4356 4357 Output Parameter: 4358 . A_loc - the local sequential matrix generated 4359 4360 Level: developer 4361 4362 @*/ 4363 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4364 { 4365 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4366 PetscErrorCode ierr; 4367 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4368 IS isrowa,iscola; 4369 Mat *aloc; 4370 4371 PetscFunctionBegin; 4372 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4373 if (!row){ 4374 start = A->rmap.rstart; end = A->rmap.rend; 4375 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4376 } else { 4377 isrowa = *row; 4378 } 4379 if (!col){ 4380 start = A->cmap.rstart; 4381 cmap = a->garray; 4382 nzA = a->A->cmap.n; 4383 nzB = a->B->cmap.n; 4384 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4385 ncols = 0; 4386 for (i=0; i<nzB; i++) { 4387 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4388 else break; 4389 } 4390 imark = i; 4391 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4392 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4393 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4394 ierr = PetscFree(idx);CHKERRQ(ierr); 4395 } else { 4396 iscola = *col; 4397 } 4398 if (scall != MAT_INITIAL_MATRIX){ 4399 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4400 aloc[0] = *A_loc; 4401 } 4402 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4403 *A_loc = aloc[0]; 4404 ierr = PetscFree(aloc);CHKERRQ(ierr); 4405 if (!row){ 4406 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4407 } 4408 if (!col){ 4409 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4410 } 4411 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4412 PetscFunctionReturn(0); 4413 } 4414 4415 #undef __FUNCT__ 4416 #define __FUNCT__ "MatGetBrowsOfAcols" 4417 /*@C 4418 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4419 4420 Collective on Mat 4421 4422 Input Parameters: 4423 + A,B - the matrices in mpiaij format 4424 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4425 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4426 4427 Output Parameter: 4428 + rowb, colb - index sets of rows and columns of B to extract 4429 . brstart - row index of B_seq from which next B->rmap.n rows are taken from B's local rows 4430 - B_seq - the sequential matrix generated 4431 4432 Level: developer 4433 4434 @*/ 4435 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4436 { 4437 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4438 PetscErrorCode ierr; 4439 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4440 IS isrowb,iscolb; 4441 Mat *bseq; 4442 4443 PetscFunctionBegin; 4444 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4445 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap.rstart,A->cmap.rend,B->rmap.rstart,B->rmap.rend); 4446 } 4447 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4448 4449 if (scall == MAT_INITIAL_MATRIX){ 4450 start = A->cmap.rstart; 4451 cmap = a->garray; 4452 nzA = a->A->cmap.n; 4453 nzB = a->B->cmap.n; 4454 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4455 ncols = 0; 4456 for (i=0; i<nzB; i++) { /* row < local row index */ 4457 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4458 else break; 4459 } 4460 imark = i; 4461 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4462 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4463 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4464 ierr = PetscFree(idx);CHKERRQ(ierr); 4465 *brstart = imark; 4466 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap.N,0,1,&iscolb);CHKERRQ(ierr); 4467 } else { 4468 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4469 isrowb = *rowb; iscolb = *colb; 4470 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4471 bseq[0] = *B_seq; 4472 } 4473 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4474 *B_seq = bseq[0]; 4475 ierr = PetscFree(bseq);CHKERRQ(ierr); 4476 if (!rowb){ 4477 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4478 } else { 4479 *rowb = isrowb; 4480 } 4481 if (!colb){ 4482 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4483 } else { 4484 *colb = iscolb; 4485 } 4486 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4487 PetscFunctionReturn(0); 4488 } 4489 4490 #undef __FUNCT__ 4491 #define __FUNCT__ "MatGetBrowsOfAoCols" 4492 /*@C 4493 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4494 of the OFF-DIAGONAL portion of local A 4495 4496 Collective on Mat 4497 4498 Input Parameters: 4499 + A,B - the matrices in mpiaij format 4500 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4501 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4502 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4503 4504 Output Parameter: 4505 + B_oth - the sequential matrix generated 4506 4507 Level: developer 4508 4509 @*/ 4510 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,MatScalar **bufa_ptr,Mat *B_oth) 4511 { 4512 VecScatter_MPI_General *gen_to,*gen_from; 4513 PetscErrorCode ierr; 4514 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4515 Mat_SeqAIJ *b_oth; 4516 VecScatter ctx=a->Mvctx; 4517 MPI_Comm comm=((PetscObject)ctx)->comm; 4518 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4519 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap.n,row,*b_othi,*b_othj; 4520 PetscScalar *rvalues,*svalues; 4521 MatScalar *b_otha,*bufa,*bufA; 4522 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4523 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4524 MPI_Status *sstatus,rstatus; 4525 PetscMPIInt jj; 4526 PetscInt *cols,sbs,rbs; 4527 PetscScalar *vals; 4528 4529 PetscFunctionBegin; 4530 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4531 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap.rstart,A->cmap.rend,B->rmap.rstart,B->rmap.rend); 4532 } 4533 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4534 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4535 4536 gen_to = (VecScatter_MPI_General*)ctx->todata; 4537 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4538 rvalues = gen_from->values; /* holds the length of receiving row */ 4539 svalues = gen_to->values; /* holds the length of sending row */ 4540 nrecvs = gen_from->n; 4541 nsends = gen_to->n; 4542 4543 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4544 srow = gen_to->indices; /* local row index to be sent */ 4545 sstarts = gen_to->starts; 4546 sprocs = gen_to->procs; 4547 sstatus = gen_to->sstatus; 4548 sbs = gen_to->bs; 4549 rstarts = gen_from->starts; 4550 rprocs = gen_from->procs; 4551 rbs = gen_from->bs; 4552 4553 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4554 if (scall == MAT_INITIAL_MATRIX){ 4555 /* i-array */ 4556 /*---------*/ 4557 /* post receives */ 4558 for (i=0; i<nrecvs; i++){ 4559 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4560 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4561 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4562 } 4563 4564 /* pack the outgoing message */ 4565 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4566 rstartsj = sstartsj + nsends +1; 4567 sstartsj[0] = 0; rstartsj[0] = 0; 4568 len = 0; /* total length of j or a array to be sent */ 4569 k = 0; 4570 for (i=0; i<nsends; i++){ 4571 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4572 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4573 for (j=0; j<nrows; j++) { 4574 row = srow[k] + B->rmap.range[rank]; /* global row idx */ 4575 for (l=0; l<sbs; l++){ 4576 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4577 rowlen[j*sbs+l] = ncols; 4578 len += ncols; 4579 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4580 } 4581 k++; 4582 } 4583 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4584 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4585 } 4586 /* recvs and sends of i-array are completed */ 4587 i = nrecvs; 4588 while (i--) { 4589 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4590 } 4591 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4592 4593 /* allocate buffers for sending j and a arrays */ 4594 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4595 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4596 4597 /* create i-array of B_oth */ 4598 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4599 b_othi[0] = 0; 4600 len = 0; /* total length of j or a array to be received */ 4601 k = 0; 4602 for (i=0; i<nrecvs; i++){ 4603 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4604 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4605 for (j=0; j<nrows; j++) { 4606 b_othi[k+1] = b_othi[k] + rowlen[j]; 4607 len += rowlen[j]; k++; 4608 } 4609 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4610 } 4611 4612 /* allocate space for j and a arrrays of B_oth */ 4613 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4614 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 4615 4616 /* j-array */ 4617 /*---------*/ 4618 /* post receives of j-array */ 4619 for (i=0; i<nrecvs; i++){ 4620 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4621 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4622 } 4623 4624 /* pack the outgoing message j-array */ 4625 k = 0; 4626 for (i=0; i<nsends; i++){ 4627 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4628 bufJ = bufj+sstartsj[i]; 4629 for (j=0; j<nrows; j++) { 4630 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4631 for (ll=0; ll<sbs; ll++){ 4632 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4633 for (l=0; l<ncols; l++){ 4634 *bufJ++ = cols[l]; 4635 } 4636 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4637 } 4638 } 4639 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4640 } 4641 4642 /* recvs and sends of j-array are completed */ 4643 i = nrecvs; 4644 while (i--) { 4645 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4646 } 4647 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4648 } else if (scall == MAT_REUSE_MATRIX){ 4649 sstartsj = *startsj; 4650 rstartsj = sstartsj + nsends +1; 4651 bufa = *bufa_ptr; 4652 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4653 b_otha = b_oth->a; 4654 } else { 4655 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4656 } 4657 4658 /* a-array */ 4659 /*---------*/ 4660 /* post receives of a-array */ 4661 for (i=0; i<nrecvs; i++){ 4662 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4663 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4664 } 4665 4666 /* pack the outgoing message a-array */ 4667 k = 0; 4668 for (i=0; i<nsends; i++){ 4669 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4670 bufA = bufa+sstartsj[i]; 4671 for (j=0; j<nrows; j++) { 4672 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4673 for (ll=0; ll<sbs; ll++){ 4674 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4675 for (l=0; l<ncols; l++){ 4676 *bufA++ = vals[l]; 4677 } 4678 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4679 } 4680 } 4681 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4682 } 4683 /* recvs and sends of a-array are completed */ 4684 i = nrecvs; 4685 while (i--) { 4686 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4687 } 4688 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4689 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4690 4691 if (scall == MAT_INITIAL_MATRIX){ 4692 /* put together the new matrix */ 4693 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap.N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4694 4695 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4696 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4697 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4698 b_oth->free_a = PETSC_TRUE; 4699 b_oth->free_ij = PETSC_TRUE; 4700 b_oth->nonew = 0; 4701 4702 ierr = PetscFree(bufj);CHKERRQ(ierr); 4703 if (!startsj || !bufa_ptr){ 4704 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4705 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4706 } else { 4707 *startsj = sstartsj; 4708 *bufa_ptr = bufa; 4709 } 4710 } 4711 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4712 PetscFunctionReturn(0); 4713 } 4714 4715 #undef __FUNCT__ 4716 #define __FUNCT__ "MatGetCommunicationStructs" 4717 /*@C 4718 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4719 4720 Not Collective 4721 4722 Input Parameters: 4723 . A - The matrix in mpiaij format 4724 4725 Output Parameter: 4726 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4727 . colmap - A map from global column index to local index into lvec 4728 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4729 4730 Level: developer 4731 4732 @*/ 4733 #if defined (PETSC_USE_CTABLE) 4734 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4735 #else 4736 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4737 #endif 4738 { 4739 Mat_MPIAIJ *a; 4740 4741 PetscFunctionBegin; 4742 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4743 PetscValidPointer(lvec, 2) 4744 PetscValidPointer(colmap, 3) 4745 PetscValidPointer(multScatter, 4) 4746 a = (Mat_MPIAIJ *) A->data; 4747 if (lvec) *lvec = a->lvec; 4748 if (colmap) *colmap = a->colmap; 4749 if (multScatter) *multScatter = a->Mvctx; 4750 PetscFunctionReturn(0); 4751 } 4752 4753 EXTERN_C_BEGIN 4754 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,MatType,MatReuse,Mat*); 4755 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,MatType,MatReuse,Mat*); 4756 EXTERN_C_END 4757 4758 #include "src/mat/impls/dense/mpi/mpidense.h" 4759 4760 #undef __FUNCT__ 4761 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4762 /* 4763 Computes (B'*A')' since computing B*A directly is untenable 4764 4765 n p p 4766 ( ) ( ) ( ) 4767 m ( A ) * n ( B ) = m ( C ) 4768 ( ) ( ) ( ) 4769 4770 */ 4771 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4772 { 4773 PetscErrorCode ierr; 4774 Mat At,Bt,Ct; 4775 4776 PetscFunctionBegin; 4777 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4778 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4779 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4780 ierr = MatDestroy(At);CHKERRQ(ierr); 4781 ierr = MatDestroy(Bt);CHKERRQ(ierr); 4782 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4783 ierr = MatDestroy(Ct);CHKERRQ(ierr); 4784 PetscFunctionReturn(0); 4785 } 4786 4787 #undef __FUNCT__ 4788 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4789 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4790 { 4791 PetscErrorCode ierr; 4792 PetscInt m=A->rmap.n,n=B->cmap.n; 4793 Mat Cmat; 4794 4795 PetscFunctionBegin; 4796 if (A->cmap.n != B->rmap.n) SETERRQ2(PETSC_ERR_ARG_SIZ,"A->cmap.n %d != B->rmap.n %d\n",A->cmap.n,B->rmap.n); 4797 ierr = MatCreate(A->hdr.comm,&Cmat);CHKERRQ(ierr); 4798 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4799 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4800 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 4801 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4802 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4803 *C = Cmat; 4804 PetscFunctionReturn(0); 4805 } 4806 4807 /* ----------------------------------------------------------------*/ 4808 #undef __FUNCT__ 4809 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4810 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4811 { 4812 PetscErrorCode ierr; 4813 4814 PetscFunctionBegin; 4815 if (scall == MAT_INITIAL_MATRIX){ 4816 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 4817 } 4818 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 4819 PetscFunctionReturn(0); 4820 } 4821 4822 /*MC 4823 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4824 4825 Options Database Keys: 4826 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4827 4828 Level: beginner 4829 4830 .seealso: MatCreateMPIAIJ() 4831 M*/ 4832 4833 EXTERN_C_BEGIN 4834 #undef __FUNCT__ 4835 #define __FUNCT__ "MatCreate_MPIAIJ" 4836 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4837 { 4838 Mat_MPIAIJ *b; 4839 PetscErrorCode ierr; 4840 PetscMPIInt size; 4841 4842 PetscFunctionBegin; 4843 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4844 4845 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4846 B->data = (void*)b; 4847 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4848 B->factor = 0; 4849 B->rmap.bs = 1; 4850 B->assembled = PETSC_FALSE; 4851 B->mapping = 0; 4852 4853 B->insertmode = NOT_SET_VALUES; 4854 b->size = size; 4855 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4856 4857 /* build cache for off array entries formed */ 4858 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4859 b->donotstash = PETSC_FALSE; 4860 b->colmap = 0; 4861 b->garray = 0; 4862 b->roworiented = PETSC_TRUE; 4863 4864 /* stuff used for matrix vector multiply */ 4865 b->lvec = PETSC_NULL; 4866 b->Mvctx = PETSC_NULL; 4867 4868 /* stuff for MatGetRow() */ 4869 b->rowindices = 0; 4870 b->rowvalues = 0; 4871 b->getrowactive = PETSC_FALSE; 4872 4873 4874 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4875 "MatStoreValues_MPIAIJ", 4876 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4877 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4878 "MatRetrieveValues_MPIAIJ", 4879 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4880 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4881 "MatGetDiagonalBlock_MPIAIJ", 4882 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4883 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4884 "MatIsTranspose_MPIAIJ", 4885 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4886 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4887 "MatMPIAIJSetPreallocation_MPIAIJ", 4888 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4889 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4890 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4891 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4892 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4893 "MatDiagonalScaleLocal_MPIAIJ", 4894 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4895 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 4896 "MatConvert_MPIAIJ_MPICSRPERM", 4897 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 4898 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 4899 "MatConvert_MPIAIJ_MPICRL", 4900 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 4901 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 4902 "MatMatMult_MPIDense_MPIAIJ", 4903 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 4904 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 4905 "MatMatMultSymbolic_MPIDense_MPIAIJ", 4906 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 4907 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 4908 "MatMatMultNumeric_MPIDense_MPIAIJ", 4909 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 4910 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 4911 PetscFunctionReturn(0); 4912 } 4913 EXTERN_C_END 4914 4915 #undef __FUNCT__ 4916 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 4917 /*@ 4918 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 4919 and "off-diagonal" part of the matrix in CSR format. 4920 4921 Collective on MPI_Comm 4922 4923 Input Parameters: 4924 + comm - MPI communicator 4925 . m - number of local rows (Cannot be PETSC_DECIDE) 4926 . n - This value should be the same as the local size used in creating the 4927 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4928 calculated if N is given) For square matrices n is almost always m. 4929 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4930 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4931 . i - row indices for "diagonal" portion of matrix 4932 . j - column indices 4933 . a - matrix values 4934 . oi - row indices for "off-diagonal" portion of matrix 4935 . oj - column indices 4936 - oa - matrix values 4937 4938 Output Parameter: 4939 . mat - the matrix 4940 4941 Level: advanced 4942 4943 Notes: 4944 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 4945 4946 The i and j indices are 0 based 4947 4948 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 4949 4950 4951 .keywords: matrix, aij, compressed row, sparse, parallel 4952 4953 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4954 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 4955 @*/ 4956 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 4957 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 4958 { 4959 PetscErrorCode ierr; 4960 Mat_MPIAIJ *maij; 4961 4962 PetscFunctionBegin; 4963 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4964 if (i[0]) { 4965 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4966 } 4967 if (oi[0]) { 4968 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 4969 } 4970 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4971 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4972 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4973 maij = (Mat_MPIAIJ*) (*mat)->data; 4974 maij->donotstash = PETSC_TRUE; 4975 (*mat)->preallocated = PETSC_TRUE; 4976 4977 (*mat)->rmap.bs = (*mat)->cmap.bs = 1; 4978 ierr = PetscMapSetUp(&(*mat)->rmap);CHKERRQ(ierr); 4979 ierr = PetscMapSetUp(&(*mat)->cmap);CHKERRQ(ierr); 4980 4981 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 4982 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap.N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 4983 4984 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4985 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4986 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4987 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4988 4989 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4990 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4991 PetscFunctionReturn(0); 4992 } 4993 4994 /* 4995 Special version for direct calls from Fortran 4996 */ 4997 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4998 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 4999 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5000 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5001 #endif 5002 5003 /* Change these macros so can be used in void function */ 5004 #undef CHKERRQ 5005 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5006 #undef SETERRQ2 5007 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5008 #undef SETERRQ 5009 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5010 5011 EXTERN_C_BEGIN 5012 #undef __FUNCT__ 5013 #define __FUNCT__ "matsetvaluesmpiaij_" 5014 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5015 { 5016 Mat mat = *mmat; 5017 PetscInt m = *mm, n = *mn; 5018 InsertMode addv = *maddv; 5019 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5020 PetscScalar value; 5021 PetscErrorCode ierr; 5022 5023 MatPreallocated(mat); 5024 if (mat->insertmode == NOT_SET_VALUES) { 5025 mat->insertmode = addv; 5026 } 5027 #if defined(PETSC_USE_DEBUG) 5028 else if (mat->insertmode != addv) { 5029 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5030 } 5031 #endif 5032 { 5033 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 5034 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 5035 PetscTruth roworiented = aij->roworiented; 5036 5037 /* Some Variables required in the macro */ 5038 Mat A = aij->A; 5039 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5040 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5041 MatScalar *aa = a->a; 5042 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5043 Mat B = aij->B; 5044 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5045 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 5046 MatScalar *ba = b->a; 5047 5048 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5049 PetscInt nonew = a->nonew; 5050 MatScalar *ap1,*ap2; 5051 5052 PetscFunctionBegin; 5053 for (i=0; i<m; i++) { 5054 if (im[i] < 0) continue; 5055 #if defined(PETSC_USE_DEBUG) 5056 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 5057 #endif 5058 if (im[i] >= rstart && im[i] < rend) { 5059 row = im[i] - rstart; 5060 lastcol1 = -1; 5061 rp1 = aj + ai[row]; 5062 ap1 = aa + ai[row]; 5063 rmax1 = aimax[row]; 5064 nrow1 = ailen[row]; 5065 low1 = 0; 5066 high1 = nrow1; 5067 lastcol2 = -1; 5068 rp2 = bj + bi[row]; 5069 ap2 = ba + bi[row]; 5070 rmax2 = bimax[row]; 5071 nrow2 = bilen[row]; 5072 low2 = 0; 5073 high2 = nrow2; 5074 5075 for (j=0; j<n; j++) { 5076 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5077 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5078 if (in[j] >= cstart && in[j] < cend){ 5079 col = in[j] - cstart; 5080 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5081 } else if (in[j] < 0) continue; 5082 #if defined(PETSC_USE_DEBUG) 5083 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);} 5084 #endif 5085 else { 5086 if (mat->was_assembled) { 5087 if (!aij->colmap) { 5088 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5089 } 5090 #if defined (PETSC_USE_CTABLE) 5091 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5092 col--; 5093 #else 5094 col = aij->colmap[in[j]] - 1; 5095 #endif 5096 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5097 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5098 col = in[j]; 5099 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5100 B = aij->B; 5101 b = (Mat_SeqAIJ*)B->data; 5102 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5103 rp2 = bj + bi[row]; 5104 ap2 = ba + bi[row]; 5105 rmax2 = bimax[row]; 5106 nrow2 = bilen[row]; 5107 low2 = 0; 5108 high2 = nrow2; 5109 bm = aij->B->rmap.n; 5110 ba = b->a; 5111 } 5112 } else col = in[j]; 5113 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5114 } 5115 } 5116 } else { 5117 if (!aij->donotstash) { 5118 if (roworiented) { 5119 if (ignorezeroentries && v[i*n] == 0.0) continue; 5120 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 5121 } else { 5122 if (ignorezeroentries && v[i] == 0.0) continue; 5123 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 5124 } 5125 } 5126 } 5127 }} 5128 PetscFunctionReturnVoid(); 5129 } 5130 EXTERN_C_END 5131 5132