/*! \brief * * <pre> * Purpose * ======= * * CGSRFS improves the computed solution to a system of linear * equations and provides error bounds and backward error estimates for * the solution. * * If equilibration was performed, the system becomes: * (diag(R)*A_original*diag(C)) * X = diag(R)*B_original. * * See supermatrix.h for the definition of 'SuperMatrix' structure. * * Arguments * ========= * * trans (input) trans_t * Specifies the form of the system of equations: * = NOTRANS: A * X = B (No transpose) * = TRANS: A'* X = B (Transpose) * = CONJ: A**H * X = B (Conjugate transpose) * * A (input) SuperMatrix* * The original matrix A in the system, or the scaled A if * equilibration was done. The type of A can be: * Stype = SLU_NC, Dtype = SLU_C, Mtype = SLU_GE. * * L (input) SuperMatrix* * The factor L from the factorization Pr*A*Pc=L*U. Use * compressed row subscripts storage for supernodes, * i.e., L has types: Stype = SLU_SC, Dtype = SLU_C, Mtype = SLU_TRLU. * * U (input) SuperMatrix* * The factor U from the factorization Pr*A*Pc=L*U as computed by * cgstrf(). Use column-wise storage scheme, * i.e., U has types: Stype = SLU_NC, Dtype = SLU_C, Mtype = SLU_TRU. * * perm_c (input) int*, dimension (A->ncol) * Column permutation vector, which defines the * permutation matrix Pc; perm_c[i] = j means column i of A is * in position j in A*Pc. * * perm_r (input) int*, dimension (A->nrow) * Row permutation vector, which defines the permutation matrix Pr; * perm_r[i] = j means row i of A is in position j in Pr*A. * * equed (input) Specifies the form of equilibration that was done. * = 'N': No equilibration. * = 'R': Row equilibration, i.e., A was premultiplied by diag(R). * = 'C': Column equilibration, i.e., A was postmultiplied by * diag(C). * = 'B': Both row and column equilibration, i.e., A was replaced * by diag(R)*A*diag(C). * * R (input) float*, dimension (A->nrow) * The row scale factors for A. * If equed = 'R' or 'B', A is premultiplied by diag(R). * If equed = 'N' or 'C', R is not accessed. * * C (input) float*, dimension (A->ncol) * The column scale factors for A. * If equed = 'C' or 'B', A is postmultiplied by diag(C). * If equed = 'N' or 'R', C is not accessed. * * B (input) SuperMatrix* * B has types: Stype = SLU_DN, Dtype = SLU_C, Mtype = SLU_GE. * The right hand side matrix B. * if equed = 'R' or 'B', B is premultiplied by diag(R). * * X (input/output) SuperMatrix* * X has types: Stype = SLU_DN, Dtype = SLU_C, Mtype = SLU_GE. * On entry, the solution matrix X, as computed by cgstrs(). * On exit, the improved solution matrix X. * if *equed = 'C' or 'B', X should be premultiplied by diag(C) * in order to obtain the solution to the original system. * * FERR (output) float*, dimension (B->ncol) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) float*, dimension (B->ncol) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * stat (output) SuperLUStat_t* * Record the statistics on runtime and floating-point operation count. * See util.h for the definition of 'SuperLUStat_t'. * * info (output) int* * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Internal Parameters * =================== * * ITMAX is the maximum number of steps of iterative refinement. * * </pre> */ void cgsrfs(trans_t trans, SuperMatrix *A, SuperMatrix *L, SuperMatrix *U, int *perm_c, int *perm_r, char *equed, float *R, float *C, SuperMatrix *B, SuperMatrix *X, float *ferr, float *berr, SuperLUStat_t *stat, int *info) { #define ITMAX 5 /* Table of constant values */ int ione = 1; complex ndone = {-1., 0.}; complex done = {1., 0.}; /* Local variables */ NCformat *Astore; complex *Aval; SuperMatrix Bjcol; DNformat *Bstore, *Xstore, *Bjcol_store; complex *Bmat, *Xmat, *Bptr, *Xptr; int kase; float safe1, safe2; int i, j, k, irow, nz, count, notran, rowequ, colequ; int ldb, ldx, nrhs; float s, xk, lstres, eps, safmin; char transc[1]; trans_t transt; complex *work; float *rwork; int *iwork; int isave[3]; extern int clacon2_(int *, complex *, complex *, float *, int *, int []); #ifdef _CRAY extern int CCOPY(int *, complex *, int *, complex *, int *); extern int CSAXPY(int *, complex *, complex *, int *, complex *, int *); #else extern int ccopy_(int *, complex *, int *, complex *, int *); extern int caxpy_(int *, complex *, complex *, int *, complex *, int *); #endif Astore = A->Store; Aval = Astore->nzval; Bstore = B->Store; Xstore = X->Store; Bmat = Bstore->nzval; Xmat = Xstore->nzval; ldb = Bstore->lda; ldx = Xstore->lda; nrhs = B->ncol; /* Test the input parameters */ *info = 0; notran = (trans == NOTRANS); if ( !notran && trans != TRANS && trans != CONJ ) *info = -1; else if ( A->nrow != A->ncol || A->nrow < 0 || A->Stype != SLU_NC || A->Dtype != SLU_C || A->Mtype != SLU_GE ) *info = -2; else if ( L->nrow != L->ncol || L->nrow < 0 || L->Stype != SLU_SC || L->Dtype != SLU_C || L->Mtype != SLU_TRLU ) *info = -3; else if ( U->nrow != U->ncol || U->nrow < 0 || U->Stype != SLU_NC || U->Dtype != SLU_C || U->Mtype != SLU_TRU ) *info = -4; else if ( ldb < SUPERLU_MAX(0, A->nrow) || B->Stype != SLU_DN || B->Dtype != SLU_C || B->Mtype != SLU_GE ) *info = -10; else if ( ldx < SUPERLU_MAX(0, A->nrow) || X->Stype != SLU_DN || X->Dtype != SLU_C || X->Mtype != SLU_GE ) *info = -11; if (*info != 0) { i = -(*info); input_error("cgsrfs", &i); return; } /* Quick return if possible */ if ( A->nrow == 0 || nrhs == 0) { for (j = 0; j < nrhs; ++j) { ferr[j] = 0.; berr[j] = 0.; } return; } rowequ = lsame_(equed, "R") || lsame_(equed, "B"); colequ = lsame_(equed, "C") || lsame_(equed, "B"); /* Allocate working space */ work = complexMalloc(2*A->nrow); rwork = (float *) SUPERLU_MALLOC( A->nrow * sizeof(float) ); iwork = intMalloc(A->nrow); if ( !work || !rwork || !iwork ) ABORT("Malloc fails for work/rwork/iwork."); if ( notran ) { *(unsigned char *)transc = 'N'; transt = TRANS; } else { *(unsigned char *)transc = 'T'; transt = NOTRANS; } /* NZ = maximum number of nonzero elements in each row of A, plus 1 */ nz = A->ncol + 1; eps = smach("Epsilon"); safmin = smach("Safe minimum"); /* Set SAFE1 essentially to be the underflow threshold times the number of additions in each row. */ safe1 = nz * safmin; safe2 = safe1 / eps; /* Compute the number of nonzeros in each row (or column) of A */ for (i = 0; i < A->nrow; ++i) iwork[i] = 0; if ( notran ) { for (k = 0; k < A->ncol; ++k) for (i = Astore->colptr[k]; i < Astore->colptr[k+1]; ++i) ++iwork[Astore->rowind[i]]; } else { for (k = 0; k < A->ncol; ++k) iwork[k] = Astore->colptr[k+1] - Astore->colptr[k]; } /* Copy one column of RHS B into Bjcol. */ Bjcol.Stype = B->Stype; Bjcol.Dtype = B->Dtype; Bjcol.Mtype = B->Mtype; Bjcol.nrow = B->nrow; Bjcol.ncol = 1; Bjcol.Store = (void *) SUPERLU_MALLOC( sizeof(DNformat) ); if ( !Bjcol.Store ) ABORT("SUPERLU_MALLOC fails for Bjcol.Store"); Bjcol_store = Bjcol.Store; Bjcol_store->lda = ldb; Bjcol_store->nzval = work; /* address aliasing */ /* Do for each right hand side ... */ for (j = 0; j < nrhs; ++j) { count = 0; lstres = 3.; Bptr = &Bmat[j*ldb]; Xptr = &Xmat[j*ldx]; while (1) { /* Loop until stopping criterion is satisfied. */ /* Compute residual R = B - op(A) * X, where op(A) = A, A**T, or A**H, depending on TRANS. */ #ifdef _CRAY CCOPY(&A->nrow, Bptr, &ione, work, &ione); #else ccopy_(&A->nrow, Bptr, &ione, work, &ione); #endif sp_cgemv(transc, ndone, A, Xptr, ione, done, work, ione); /* Compute componentwise relative backward error from formula max(i) ( abs(R(i)) / ( abs(op(A))*abs(X) + abs(B) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z. If the i-th component of the denominator is less than SAFE2, then SAFE1 is added to the i-th component of the numerator before dividing. */ for (i = 0; i < A->nrow; ++i) rwork[i] = c_abs1( &Bptr[i] ); /* Compute abs(op(A))*abs(X) + abs(B). */ if (notran) { for (k = 0; k < A->ncol; ++k) { xk = c_abs1( &Xptr[k] ); for (i = Astore->colptr[k]; i < Astore->colptr[k+1]; ++i) rwork[Astore->rowind[i]] += c_abs1(&Aval[i]) * xk; } } else { for (k = 0; k < A->ncol; ++k) { s = 0.; for (i = Astore->colptr[k]; i < Astore->colptr[k+1]; ++i) { irow = Astore->rowind[i]; s += c_abs1(&Aval[i]) * c_abs1(&Xptr[irow]); } rwork[k] += s; } } s = 0.; for (i = 0; i < A->nrow; ++i) { if (rwork[i] > safe2) { s = SUPERLU_MAX( s, c_abs1(&work[i]) / rwork[i] ); } else if ( rwork[i] != 0.0 ) { s = SUPERLU_MAX( s, (c_abs1(&work[i]) + safe1) / rwork[i] ); } /* If rwork[i] is exactly 0.0, then we know the true residual also must be exactly 0.0. */ } berr[j] = s; /* Test stopping criterion. Continue iterating if 1) The residual BERR(J) is larger than machine epsilon, and 2) BERR(J) decreased by at least a factor of 2 during the last iteration, and 3) At most ITMAX iterations tried. */ if (berr[j] > eps && berr[j] * 2. <= lstres && count < ITMAX) { /* Update solution and try again. */ cgstrs (trans, L, U, perm_c, perm_r, &Bjcol, stat, info); #ifdef _CRAY CAXPY(&A->nrow, &done, work, &ione, &Xmat[j*ldx], &ione); #else caxpy_(&A->nrow, &done, work, &ione, &Xmat[j*ldx], &ione); #endif lstres = berr[j]; ++count; } else { break; } } /* end while */ stat->RefineSteps = count; /* Bound error from formula: norm(X - XTRUE) / norm(X) .le. FERR = norm( abs(inv(op(A)))* ( abs(R) + NZ*EPS*( abs(op(A))*abs(X)+abs(B) ))) / norm(X) where norm(Z) is the magnitude of the largest component of Z inv(op(A)) is the inverse of op(A) abs(Z) is the componentwise absolute value of the matrix or vector Z NZ is the maximum number of nonzeros in any row of A, plus 1 EPS is machine epsilon The i-th component of abs(R)+NZ*EPS*(abs(op(A))*abs(X)+abs(B)) is incremented by SAFE1 if the i-th component of abs(op(A))*abs(X) + abs(B) is less than SAFE2. Use CLACON2 to estimate the infinity-norm of the matrix inv(op(A)) * diag(W), where W = abs(R) + NZ*EPS*( abs(op(A))*abs(X)+abs(B) ))) */ for (i = 0; i < A->nrow; ++i) rwork[i] = c_abs1( &Bptr[i] ); /* Compute abs(op(A))*abs(X) + abs(B). */ if ( notran ) { for (k = 0; k < A->ncol; ++k) { xk = c_abs1( &Xptr[k] ); for (i = Astore->colptr[k]; i < Astore->colptr[k+1]; ++i) rwork[Astore->rowind[i]] += c_abs1(&Aval[i]) * xk; } } else { for (k = 0; k < A->ncol; ++k) { s = 0.; for (i = Astore->colptr[k]; i < Astore->colptr[k+1]; ++i) { irow = Astore->rowind[i]; xk = c_abs1( &Xptr[irow] ); s += c_abs1(&Aval[i]) * xk; } rwork[k] += s; } } for (i = 0; i < A->nrow; ++i) if (rwork[i] > safe2) rwork[i] = c_abs(&work[i]) + (iwork[i]+1)*eps*rwork[i]; else rwork[i] = c_abs(&work[i])+(iwork[i]+1)*eps*rwork[i]+safe1; kase = 0; do { clacon2_(&A->nrow, &work[A->nrow], work, &ferr[j], &kase, isave); if (kase == 0) break; if (kase == 1) { /* Multiply by diag(W)*inv(op(A)**T)*(diag(C) or diag(R)). */ if ( notran && colequ ) for (i = 0; i < A->ncol; ++i) { cs_mult(&work[i], &work[i], C[i]); } else if ( !notran && rowequ ) for (i = 0; i < A->nrow; ++i) { cs_mult(&work[i], &work[i], R[i]); } cgstrs (transt, L, U, perm_c, perm_r, &Bjcol, stat, info); for (i = 0; i < A->nrow; ++i) { cs_mult(&work[i], &work[i], rwork[i]); } } else { /* Multiply by (diag(C) or diag(R))*inv(op(A))*diag(W). */ for (i = 0; i < A->nrow; ++i) { cs_mult(&work[i], &work[i], rwork[i]); } cgstrs (trans, L, U, perm_c, perm_r, &Bjcol, stat, info); if ( notran && colequ ) for (i = 0; i < A->ncol; ++i) { cs_mult(&work[i], &work[i], C[i]); } else if ( !notran && rowequ ) for (i = 0; i < A->ncol; ++i) { cs_mult(&work[i], &work[i], R[i]); } } } while ( kase != 0 ); /* Normalize error. */ lstres = 0.; if ( notran && colequ ) { for (i = 0; i < A->nrow; ++i) lstres = SUPERLU_MAX( lstres, C[i] * c_abs1( &Xptr[i]) ); } else if ( !notran && rowequ ) { for (i = 0; i < A->nrow; ++i) lstres = SUPERLU_MAX( lstres, R[i] * c_abs1( &Xptr[i]) ); } else { for (i = 0; i < A->nrow; ++i) lstres = SUPERLU_MAX( lstres, c_abs1( &Xptr[i]) ); } if ( lstres != 0. ) ferr[j] /= lstres; } /* for each RHS j ... */ SUPERLU_FREE(work); SUPERLU_FREE(rwork); SUPERLU_FREE(iwork); SUPERLU_FREE(Bjcol.Store); return; } /* cgsrfs */
void cgscon(char *norm, SuperMatrix *L, SuperMatrix *U, float anorm, float *rcond, SuperLUStat_t *stat, int *info) { /* Local variables */ int kase, kase1, onenrm, i; float ainvnm; complex *work; int isave[3]; extern int crscl_(int *, complex *, complex *, int *); extern int clacon2_(int *, complex *, complex *, float *, int *, int []); /* Test the input parameters. */ *info = 0; onenrm = *(unsigned char *)norm == '1' || strncmp(norm, "O", 1)==0; if (! onenrm && ! strncmp(norm, "I", 1)==0) *info = -1; else if (L->nrow < 0 || L->nrow != L->ncol || L->Stype != SLU_SC || L->Dtype != SLU_C || L->Mtype != SLU_TRLU) *info = -2; else if (U->nrow < 0 || U->nrow != U->ncol || U->Stype != SLU_NC || U->Dtype != SLU_C || U->Mtype != SLU_TRU) *info = -3; if (*info != 0) { i = -(*info); input_error("cgscon", &i); return; } /* Quick return if possible */ *rcond = 0.; if ( L->nrow == 0 || U->nrow == 0) { *rcond = 1.; return; } work = complexCalloc( 3*L->nrow ); if ( !work ) ABORT("Malloc fails for work arrays in cgscon."); /* Estimate the norm of inv(A). */ ainvnm = 0.; if ( onenrm ) kase1 = 1; else kase1 = 2; kase = 0; do { clacon2_(&L->nrow, &work[L->nrow], &work[0], &ainvnm, &kase, isave); if (kase == 0) break; if (kase == kase1) { /* Multiply by inv(L). */ sp_ctrsv("L", "No trans", "Unit", L, U, &work[0], stat, info); /* Multiply by inv(U). */ sp_ctrsv("U", "No trans", "Non-unit", L, U, &work[0], stat, info); } else { /* Multiply by inv(U'). */ sp_ctrsv("U", "Transpose", "Non-unit", L, U, &work[0], stat, info); /* Multiply by inv(L'). */ sp_ctrsv("L", "Transpose", "Unit", L, U, &work[0], stat, info); } } while ( kase != 0 ); /* Compute the estimate of the reciprocal condition number. */ if (ainvnm != 0.) *rcond = (1. / ainvnm) / anorm; SUPERLU_FREE (work); return; } /* cgscon */