1 #define PETSCMAT_DLL 2 3 /* 4 Defines matrix-matrix product routines for pairs of SeqAIJ matrices 5 C = A * B 6 */ 7 8 #include "src/mat/impls/aij/seq/aij.h" /*I "petscmat.h" I*/ 9 #include "src/mat/utils/freespace.h" 10 #include "petscbt.h" 11 12 13 #undef __FUNCT__ 14 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqAIJ" 15 PetscErrorCode MatMatMult_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 16 { 17 PetscErrorCode ierr; 18 19 PetscFunctionBegin; 20 if (scall == MAT_INITIAL_MATRIX){ 21 ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 22 } 23 ierr = MatMatMultNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr); 24 PetscFunctionReturn(0); 25 } 26 27 28 #undef __FUNCT__ 29 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqAIJ" 30 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 31 { 32 PetscErrorCode ierr; 33 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 34 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c; 35 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci,*cj; 36 PetscInt am=A->rmap.N,bn=B->cmap.N,bm=B->rmap.N; 37 PetscInt i,j,anzi,brow,bnzj,cnzi,nlnk,*lnk,nspacedouble=0; 38 MatScalar *ca; 39 PetscBT lnkbt; 40 41 PetscFunctionBegin; 42 /* Set up */ 43 /* Allocate ci array, arrays for fill computation and */ 44 /* free space for accumulating nonzero column info */ 45 ierr = PetscMalloc(((am+1)+1)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 46 ci[0] = 0; 47 48 /* create and initialize a linked list */ 49 nlnk = bn+1; 50 ierr = PetscLLCreate(bn,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr); 51 52 /* Initial FreeSpace size is fill*(nnz(A)+nnz(B)) */ 53 if (fill < 1.0) fill = 1.0; /* In case user input a wrong fill, reset it to 1.0 */ 54 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+bi[bm])),&free_space);CHKERRQ(ierr); 55 current_space = free_space; 56 57 /* Determine symbolic info for each row of the product: */ 58 for (i=0;i<am;i++) { 59 anzi = ai[i+1] - ai[i]; 60 cnzi = 0; 61 j = anzi; 62 aj = a->j + ai[i]; 63 while (j){/* assume cols are almost in increasing order, starting from its end saves computation */ 64 j--; 65 brow = *(aj + j); 66 bnzj = bi[brow+1] - bi[brow]; 67 bjj = bj + bi[brow]; 68 /* add non-zero cols of B into the sorted linked list lnk */ 69 ierr = PetscLLAdd(bnzj,bjj,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr); 70 cnzi += nlnk; 71 } 72 73 /* If free space is not available, make more free space */ 74 /* Double the amount of total space in the list */ 75 if (current_space->local_remaining<cnzi) { 76 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 77 nspacedouble++; 78 } 79 80 /* Copy data into free space, then initialize lnk */ 81 ierr = PetscLLClean(bn,bn,cnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 82 current_space->array += cnzi; 83 current_space->local_used += cnzi; 84 current_space->local_remaining -= cnzi; 85 86 ci[i+1] = ci[i] + cnzi; 87 } 88 89 /* Column indices are in the list of free space */ 90 /* Allocate space for cj, initialize cj, and */ 91 /* destroy list of free space and other temporary array(s) */ 92 ierr = PetscMalloc((ci[am]+1)*sizeof(PetscInt),&cj);CHKERRQ(ierr); 93 ierr = PetscFreeSpaceContiguous(&free_space,cj);CHKERRQ(ierr); 94 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 95 96 /* Allocate space for ca */ 97 ierr = PetscMalloc((ci[am]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr); 98 ierr = PetscMemzero(ca,(ci[am]+1)*sizeof(MatScalar));CHKERRQ(ierr); 99 100 /* put together the new symbolic matrix */ 101 ierr = MatCreateSeqAIJWithArrays(A->comm,am,bn,ci,cj,ca,C);CHKERRQ(ierr); 102 103 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 104 /* These are PETSc arrays, so change flags so arrays can be deleted by PETSc */ 105 c = (Mat_SeqAIJ *)((*C)->data); 106 c->freedata = PETSC_TRUE; 107 c->nonew = 0; 108 109 if (nspacedouble){ 110 ierr = PetscInfo5((*C),"nspacedouble:%D, nnz(A):%D, nnz(B):%D, fill:%G, nnz(C):%D\n",nspacedouble,ai[am],bi[bm],fill,ci[am]);CHKERRQ(ierr); 111 } 112 PetscFunctionReturn(0); 113 } 114 115 116 #undef __FUNCT__ 117 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqAIJ" 118 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C) 119 { 120 PetscErrorCode ierr; 121 PetscInt flops=0; 122 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data; 123 Mat_SeqAIJ *b = (Mat_SeqAIJ *)B->data; 124 Mat_SeqAIJ *c = (Mat_SeqAIJ *)C->data; 125 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci=c->i,*cj=c->j; 126 PetscInt am=A->rmap.N,cm=C->rmap.N; 127 PetscInt i,j,k,anzi,bnzi,cnzi,brow,nextb; 128 MatScalar *aa=a->a,*ba=b->a,*baj,*ca=c->a; 129 130 PetscFunctionBegin; 131 /* clean old values in C */ 132 ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr); 133 /* Traverse A row-wise. */ 134 /* Build the ith row in C by summing over nonzero columns in A, */ 135 /* the rows of B corresponding to nonzeros of A. */ 136 for (i=0;i<am;i++) { 137 anzi = ai[i+1] - ai[i]; 138 for (j=0;j<anzi;j++) { 139 brow = *aj++; 140 bnzi = bi[brow+1] - bi[brow]; 141 bjj = bj + bi[brow]; 142 baj = ba + bi[brow]; 143 nextb = 0; 144 for (k=0; nextb<bnzi; k++) { 145 if (cj[k] == bjj[nextb]){ /* ccol == bcol */ 146 ca[k] += (*aa)*baj[nextb++]; 147 } 148 } 149 flops += 2*bnzi; 150 aa++; 151 } 152 cnzi = ci[i+1] - ci[i]; 153 ca += cnzi; 154 cj += cnzi; 155 } 156 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 157 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 158 159 ierr = PetscLogFlops(flops);CHKERRQ(ierr); 160 PetscFunctionReturn(0); 161 } 162 163 164 #undef __FUNCT__ 165 #define __FUNCT__ "MatMatMultTranspose_SeqAIJ_SeqAIJ" 166 PetscErrorCode MatMatMultTranspose_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) { 167 PetscErrorCode ierr; 168 169 PetscFunctionBegin; 170 if (scall == MAT_INITIAL_MATRIX){ 171 ierr = MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 172 } 173 ierr = MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr); 174 PetscFunctionReturn(0); 175 } 176 177 #undef __FUNCT__ 178 #define __FUNCT__ "MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ" 179 PetscErrorCode MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 180 { 181 PetscErrorCode ierr; 182 Mat At; 183 PetscInt *ati,*atj; 184 185 PetscFunctionBegin; 186 /* create symbolic At */ 187 ierr = MatGetSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr); 188 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,A->cmap.n,A->rmap.n,ati,atj,PETSC_NULL,&At);CHKERRQ(ierr); 189 190 /* get symbolic C=At*B */ 191 ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(At,B,fill,C);CHKERRQ(ierr); 192 193 /* clean up */ 194 ierr = MatDestroy(At);CHKERRQ(ierr); 195 ierr = MatRestoreSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr); 196 197 PetscFunctionReturn(0); 198 } 199 200 #undef __FUNCT__ 201 #define __FUNCT__ "MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ" 202 PetscErrorCode MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C) 203 { 204 PetscErrorCode ierr; 205 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c=(Mat_SeqAIJ*)C->data; 206 PetscInt am=A->rmap.n,anzi,*ai=a->i,*aj=a->j,*bi=b->i,*bj,bnzi,nextb; 207 PetscInt cm=C->rmap.n,*ci=c->i,*cj=c->j,crow,*cjj,i,j,k,flops=0; 208 MatScalar *aa=a->a,*ba,*ca=c->a,*caj; 209 210 PetscFunctionBegin; 211 /* clear old values in C */ 212 ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr); 213 214 /* compute A^T*B using outer product (A^T)[:,i]*B[i,:] */ 215 for (i=0;i<am;i++) { 216 bj = b->j + bi[i]; 217 ba = b->a + bi[i]; 218 bnzi = bi[i+1] - bi[i]; 219 anzi = ai[i+1] - ai[i]; 220 for (j=0; j<anzi; j++) { 221 nextb = 0; 222 crow = *aj++; 223 cjj = cj + ci[crow]; 224 caj = ca + ci[crow]; 225 /* perform sparse axpy operation. Note cjj includes bj. */ 226 for (k=0; nextb<bnzi; k++) { 227 if (cjj[k] == *(bj+nextb)) { /* ccol == bcol */ 228 caj[k] += (*aa)*(*(ba+nextb)); 229 nextb++; 230 } 231 } 232 flops += 2*bnzi; 233 aa++; 234 } 235 } 236 237 /* Assemble the final matrix and clean up */ 238 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 239 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 240 ierr = PetscLogFlops(flops);CHKERRQ(ierr); 241 PetscFunctionReturn(0); 242 } 243