1 2 /* 3 Defines projective product routines where A is a SeqAIJ matrix 4 C = P^T * A * P 5 */ 6 7 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 8 #include <../src/mat/utils/freespace.h> 9 #include <petscbt.h> 10 #include <petsctime.h> 11 12 #if defined(PETSC_HAVE_HYPRE) 13 PETSC_INTERN PetscErrorCode MatPtAPSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat); 14 #endif 15 16 PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat C) 17 { 18 PetscErrorCode ierr; 19 Mat_Product *product = C->product; 20 Mat A=product->A,P=product->B; 21 MatProductAlgorithm alg=product->alg; 22 PetscReal fill=product->fill; 23 PetscBool flg; 24 Mat Pt; 25 26 PetscFunctionBegin; 27 /* "scalable" */ 28 ierr = PetscStrcmp(alg,"scalable",&flg);CHKERRQ(ierr); 29 if (flg) { 30 ierr = MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(A,P,fill,C);CHKERRQ(ierr); 31 C->ops->productnumeric = MatProductNumeric_PtAP; 32 PetscFunctionReturn(0); 33 } 34 35 /* "rap" */ 36 ierr = PetscStrcmp(alg,"rap",&flg);CHKERRQ(ierr); 37 if (flg) { 38 Mat_MatTransMatMult *atb; 39 40 ierr = PetscNew(&atb);CHKERRQ(ierr); 41 ierr = MatTranspose_SeqAIJ(P,MAT_INITIAL_MATRIX,&Pt);CHKERRQ(ierr); 42 ierr = MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Pt,A,P,fill,C);CHKERRQ(ierr); 43 44 atb->At = Pt; 45 atb->data = C->product->data; 46 atb->destroy = C->product->destroy; 47 C->product->data = atb; 48 C->product->destroy = MatDestroy_SeqAIJ_MatTransMatMult; 49 C->ops->ptapnumeric = MatPtAPNumeric_SeqAIJ_SeqAIJ; 50 C->ops->productnumeric = MatProductNumeric_PtAP; 51 PetscFunctionReturn(0); 52 } 53 54 /* hypre */ 55 #if defined(PETSC_HAVE_HYPRE) 56 ierr = PetscStrcmp(alg,"hypre",&flg);CHKERRQ(ierr); 57 if (flg) { 58 ierr = MatPtAPSymbolic_AIJ_AIJ_wHYPRE(A,P,fill,C);CHKERRQ(ierr); 59 PetscFunctionReturn(0); 60 } 61 #endif 62 63 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatProductType is not supported"); 64 } 65 66 PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat A,Mat P,PetscReal fill,Mat C) 67 { 68 PetscErrorCode ierr; 69 PetscFreeSpaceList free_space=NULL,current_space=NULL; 70 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*p = (Mat_SeqAIJ*)P->data,*c; 71 PetscInt *pti,*ptj,*ptJ,*ai=a->i,*aj=a->j,*ajj,*pi=p->i,*pj=p->j,*pjj; 72 PetscInt *ci,*cj,*ptadenserow,*ptasparserow,*ptaj,nspacedouble=0; 73 PetscInt an=A->cmap->N,am=A->rmap->N,pn=P->cmap->N,pm=P->rmap->N; 74 PetscInt i,j,k,ptnzi,arow,anzj,ptanzi,prow,pnzj,cnzi,nlnk,*lnk; 75 MatScalar *ca; 76 PetscBT lnkbt; 77 PetscReal afill; 78 79 PetscFunctionBegin; 80 /* Get ij structure of P^T */ 81 ierr = MatGetSymbolicTranspose_SeqAIJ(P,&pti,&ptj);CHKERRQ(ierr); 82 ptJ = ptj; 83 84 /* Allocate ci array, arrays for fill computation and */ 85 /* free space for accumulating nonzero column info */ 86 ierr = PetscMalloc1(pn+1,&ci);CHKERRQ(ierr); 87 ci[0] = 0; 88 89 ierr = PetscCalloc1(2*an+1,&ptadenserow);CHKERRQ(ierr); 90 ptasparserow = ptadenserow + an; 91 92 /* create and initialize a linked list */ 93 nlnk = pn+1; 94 ierr = PetscLLCreate(pn,pn,nlnk,lnk,lnkbt);CHKERRQ(ierr); 95 96 /* Set initial free space to be fill*(nnz(A)+ nnz(P)) */ 97 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,PetscIntSumTruncate(ai[am],pi[pm])),&free_space);CHKERRQ(ierr); 98 current_space = free_space; 99 100 /* Determine symbolic info for each row of C: */ 101 for (i=0; i<pn; i++) { 102 ptnzi = pti[i+1] - pti[i]; 103 ptanzi = 0; 104 /* Determine symbolic row of PtA: */ 105 for (j=0; j<ptnzi; j++) { 106 arow = *ptJ++; 107 anzj = ai[arow+1] - ai[arow]; 108 ajj = aj + ai[arow]; 109 for (k=0; k<anzj; k++) { 110 if (!ptadenserow[ajj[k]]) { 111 ptadenserow[ajj[k]] = -1; 112 ptasparserow[ptanzi++] = ajj[k]; 113 } 114 } 115 } 116 /* Using symbolic info for row of PtA, determine symbolic info for row of C: */ 117 ptaj = ptasparserow; 118 cnzi = 0; 119 for (j=0; j<ptanzi; j++) { 120 prow = *ptaj++; 121 pnzj = pi[prow+1] - pi[prow]; 122 pjj = pj + pi[prow]; 123 /* add non-zero cols of P into the sorted linked list lnk */ 124 ierr = PetscLLAddSorted(pnzj,pjj,pn,nlnk,lnk,lnkbt);CHKERRQ(ierr); 125 cnzi += nlnk; 126 } 127 128 /* If free space is not available, make more free space */ 129 /* Double the amount of total space in the list */ 130 if (current_space->local_remaining<cnzi) { 131 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(cnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 132 nspacedouble++; 133 } 134 135 /* Copy data into free space, and zero out denserows */ 136 ierr = PetscLLClean(pn,pn,cnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 137 138 current_space->array += cnzi; 139 current_space->local_used += cnzi; 140 current_space->local_remaining -= cnzi; 141 142 for (j=0; j<ptanzi; j++) ptadenserow[ptasparserow[j]] = 0; 143 144 /* Aside: Perhaps we should save the pta info for the numerical factorization. */ 145 /* For now, we will recompute what is needed. */ 146 ci[i+1] = ci[i] + cnzi; 147 } 148 /* nnz is now stored in ci[ptm], column indices are in the list of free space */ 149 /* Allocate space for cj, initialize cj, and */ 150 /* destroy list of free space and other temporary array(s) */ 151 ierr = PetscMalloc1(ci[pn]+1,&cj);CHKERRQ(ierr); 152 ierr = PetscFreeSpaceContiguous(&free_space,cj);CHKERRQ(ierr); 153 ierr = PetscFree(ptadenserow);CHKERRQ(ierr); 154 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 155 156 ierr = PetscCalloc1(ci[pn]+1,&ca);CHKERRQ(ierr); 157 158 /* put together the new matrix */ 159 ierr = MatSetSeqAIJWithArrays_private(PetscObjectComm((PetscObject)A),pn,pn,ci,cj,ca,((PetscObject)A)->type_name,C);CHKERRQ(ierr); 160 ierr = MatSetBlockSizes(C,PetscAbs(P->cmap->bs),PetscAbs(P->cmap->bs));CHKERRQ(ierr); 161 162 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 163 /* Since these are PETSc arrays, change flags to free them as necessary. */ 164 c = (Mat_SeqAIJ*)((C)->data); 165 c->free_a = PETSC_TRUE; 166 c->free_ij = PETSC_TRUE; 167 c->nonew = 0; 168 169 C->ops->ptapnumeric = MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy; 170 171 /* set MatInfo */ 172 afill = (PetscReal)ci[pn]/(ai[am]+pi[pm] + 1.e-5); 173 if (afill < 1.0) afill = 1.0; 174 c->maxnz = ci[pn]; 175 c->nz = ci[pn]; 176 C->info.mallocs = nspacedouble; 177 C->info.fill_ratio_given = fill; 178 C->info.fill_ratio_needed = afill; 179 180 /* Clean up. */ 181 ierr = MatRestoreSymbolicTranspose_SeqAIJ(P,&pti,&ptj);CHKERRQ(ierr); 182 #if defined(PETSC_USE_INFO) 183 if (ci[pn] != 0) { 184 ierr = PetscInfo3(C,"Reallocs %D; Fill ratio: given %g needed %g.\n",nspacedouble,(double)fill,(double)afill);CHKERRQ(ierr); 185 ierr = PetscInfo1(C,"Use MatPtAP(A,P,MatReuse,%g,&C) for best performance.\n",(double)afill);CHKERRQ(ierr); 186 } else { 187 ierr = PetscInfo(C,"Empty matrix product\n");CHKERRQ(ierr); 188 } 189 #endif 190 PetscFunctionReturn(0); 191 } 192 193 PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat A,Mat P,Mat C) 194 { 195 PetscErrorCode ierr; 196 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 197 Mat_SeqAIJ *p = (Mat_SeqAIJ*) P->data; 198 Mat_SeqAIJ *c = (Mat_SeqAIJ*) C->data; 199 PetscInt *ai=a->i,*aj=a->j,*apj,*apjdense,*pi=p->i,*pj=p->j,*pJ=p->j,*pjj; 200 PetscInt *ci=c->i,*cj=c->j,*cjj; 201 PetscInt am =A->rmap->N,cn=C->cmap->N,cm=C->rmap->N; 202 PetscInt i,j,k,anzi,pnzi,apnzj,nextap,pnzj,prow,crow; 203 MatScalar *aa=a->a,*apa,*pa=p->a,*pA=p->a,*paj,*ca=c->a,*caj; 204 205 PetscFunctionBegin; 206 /* Allocate temporary array for storage of one row of A*P (cn: non-scalable) */ 207 ierr = PetscCalloc2(cn,&apa,cn,&apjdense);CHKERRQ(ierr); 208 ierr = PetscMalloc1(cn,&apj);CHKERRQ(ierr); 209 210 /* Clear old values in C */ 211 ierr = PetscArrayzero(ca,ci[cm]);CHKERRQ(ierr); 212 213 for (i=0; i<am; i++) { 214 /* Form sparse row of A*P */ 215 anzi = ai[i+1] - ai[i]; 216 apnzj = 0; 217 for (j=0; j<anzi; j++) { 218 prow = *aj++; 219 pnzj = pi[prow+1] - pi[prow]; 220 pjj = pj + pi[prow]; 221 paj = pa + pi[prow]; 222 for (k=0; k<pnzj; k++) { 223 if (!apjdense[pjj[k]]) { 224 apjdense[pjj[k]] = -1; 225 apj[apnzj++] = pjj[k]; 226 } 227 apa[pjj[k]] += (*aa)*paj[k]; 228 } 229 ierr = PetscLogFlops(2.0*pnzj);CHKERRQ(ierr); 230 aa++; 231 } 232 233 /* Sort the j index array for quick sparse axpy. */ 234 /* Note: a array does not need sorting as it is in dense storage locations. */ 235 ierr = PetscSortInt(apnzj,apj);CHKERRQ(ierr); 236 237 /* Compute P^T*A*P using outer product (P^T)[:,j]*(A*P)[j,:]. */ 238 pnzi = pi[i+1] - pi[i]; 239 for (j=0; j<pnzi; j++) { 240 nextap = 0; 241 crow = *pJ++; 242 cjj = cj + ci[crow]; 243 caj = ca + ci[crow]; 244 /* Perform sparse axpy operation. Note cjj includes apj. */ 245 for (k=0; nextap<apnzj; k++) { 246 if (PetscUnlikelyDebug(k >= ci[crow+1] - ci[crow])) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"k too large k %d, crow %d",k,crow); 247 if (cjj[k]==apj[nextap]) { 248 caj[k] += (*pA)*apa[apj[nextap++]]; 249 } 250 } 251 ierr = PetscLogFlops(2.0*apnzj);CHKERRQ(ierr); 252 pA++; 253 } 254 255 /* Zero the current row info for A*P */ 256 for (j=0; j<apnzj; j++) { 257 apa[apj[j]] = 0.; 258 apjdense[apj[j]] = 0; 259 } 260 } 261 262 /* Assemble the final matrix and clean up */ 263 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 264 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 265 266 ierr = PetscFree2(apa,apjdense);CHKERRQ(ierr); 267 ierr = PetscFree(apj);CHKERRQ(ierr); 268 PetscFunctionReturn(0); 269 } 270 271 PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat A,Mat P,Mat C) 272 { 273 PetscErrorCode ierr; 274 Mat_MatTransMatMult *atb; 275 276 PetscFunctionBegin; 277 MatCheckProduct(C,3); 278 atb = (Mat_MatTransMatMult*)C->product->data; 279 if (!atb) SETERRQ(PetscObjectComm((PetscObject)C),PETSC_ERR_PLIB,"Missing data structure"); 280 ierr = MatTranspose_SeqAIJ(P,MAT_REUSE_MATRIX,&atb->At);CHKERRQ(ierr); 281 if (!C->ops->matmultnumeric) SETERRQ(PetscObjectComm((PetscObject)C),PETSC_ERR_PLIB,"Missing numeric operation"); 282 /* when using rap, MatMatMatMultSymbolic used a different data */ 283 if (atb->data) C->product->data = atb->data; 284 ierr = (*C->ops->matmatmultnumeric)(atb->At,A,P,C);CHKERRQ(ierr); 285 C->product->data = atb; 286 PetscFunctionReturn(0); 287 } 288