Exemple #1
0
void
cgsrfs(trans_t trans, SuperMatrix *A, SuperMatrix *L, SuperMatrix *U,
       int *perm_r, int *perm_c, equed_t equed, float *R, float *C,
       SuperMatrix *B, SuperMatrix *X, float *ferr, float *berr,
       Gstat_t *Gstat, int *info)
{
/*
 * -- SuperLU MT routine (version 2.0) --
 * Lawrence Berkeley National Lab, Univ. of California Berkeley,
 * and Xerox Palo Alto Research Center.
 * September 10, 2007
 *
 *
 * Purpose
 * =======   
 *
 * cgsrfs improves the computed solution to a system of linear
 * equations and provides error bounds and backward error estimates for
 * the solution.
 *
 * 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**T * X = B  (Transpose)
 *         = CONJ:     A**H * X = B  (Conjugate transpose = 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 = NC, Dtype = _D, Mtype = 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 = SCP, Dtype = _D, Mtype = TRLU.
 *
 * U       (input) SuperMatrix*
 *         The factor U from the factorization Pr*A*Pc=L*U as computed by
 *         dgstrf(). Use column-wise storage scheme,
 *         i.e., U has types: Stype = NCP, Dtype = _D, Mtype = TRU.
 *
 * 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.
 *
 * 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.
 *
 * equed   (input) equed_t
 *         Specifies the form of equilibration that was done.
 *         = NOEQUIL: No equilibration.
 *         = ROW:  Row equilibration, i.e., A was premultiplied by diag(R).
 *         = COL:  Column equilibration, i.e., A was postmultiplied by
 *                 diag(C).
 *         = BOTH: Both row and column equilibration, i.e., A was replaced
 *                 by diag(R)*A*diag(C).
 *
 * R       (input) double*, dimension (A->nrow)
 *         The row scale factors for A.
 *         If equed = ROW or BOTH, A is premultiplied by diag(R).
 *         If equed = NOEQUIL or COL, R is not accessed.
 *
 * C       (input) double*, dimension (A->ncol)
 *         The column scale factors for A.
 *         If equed = COL or BOTH, A is postmultiplied by diag(C).
 *         If equed = NOEQUIL or ROW, C is not accessed.
 *
 * B       (input) SuperMatrix*
 *         B has types: Stype = DN, Dtype = _D, Mtype = GE.
 *         The right hand side matrix B.
 *
 * X       (input/output) SuperMatrix*
 *         X has types: Stype = DN, Dtype = _D, Mtype = GE.
 *         On entry, the solution matrix X, as computed by dgstrs().
 *         On exit, the improved solution matrix X.
 *
 * FERR    (output) double*, 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) double*, 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).
 *
 * 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.
 *
 */

#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;
    extern double slamch_(char *);
    extern int clacon_(int *, complex *, complex *, float *, 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_SCP || L->Dtype != SLU_C || L->Mtype != SLU_TRLU )
	*info = -3;
    else if ( U->nrow != U->ncol || U->nrow < 0 ||
 	      U->Stype != SLU_NCP || 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);
	xerbla_("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 = (equed == ROW) || (equed == BOTH);
    colequ = (equed == COL) || (equed == BOTH);
    
    /* Allocate working space */
    work = complexMalloc(2*A->nrow);
    rwork = (float *) SUPERLU_MALLOC( (size_t) A->nrow * sizeof(float) );
    iwork = intMalloc(A->nrow);
    if ( !work || !rwork || !iwork ) 
        SUPERLU_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    = slamch_("Epsilon");
    safmin = slamch_("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 ) SUPERLU_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_r, perm_c, &Bjcol, Gstat, 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 */

	/* 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 CLACON 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 {
	    clacon_(&A->nrow, &work[A->nrow], work,
		    &ferr[j], &kase);
	    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_r, perm_c, &Bjcol, Gstat, 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_r, perm_c, &Bjcol, Gstat, 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 */
Exemple #2
0
/*! \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 */
Exemple #3
0
int main(int argc, char *argv[])
{
    void cmatvec_mult(complex alpha, complex x[], complex beta, complex y[]);
    void cpsolve(int n, complex x[], complex y[]);
    extern int cfgmr( int n,
	void (*matvec_mult)(complex, complex [], complex, complex []),
	void (*psolve)(int n, complex [], complex[]),
	complex *rhs, complex *sol, double tol, int restrt, int *itmax,
	FILE *fits);
    extern int cfill_diag(int n, NCformat *Astore);

    char     equed[1] = {'B'};
    yes_no_t equil;
    trans_t  trans;
    SuperMatrix A, L, U;
    SuperMatrix B, X;
    NCformat *Astore;
    NCformat *Ustore;
    SCformat *Lstore;
    complex   *a;
    int      *asub, *xa;
    int      *etree;
    int      *perm_c; /* column permutation vector */
    int      *perm_r; /* row permutations from partial pivoting */
    int      nrhs, ldx, lwork, info, m, n, nnz;
    complex   *rhsb, *rhsx, *xact;
    complex   *work = NULL;
    float   *R, *C;
    float   u, rpg, rcond;
    complex zero = {0.0, 0.0};
    complex one = {1.0, 0.0};
    complex none = {-1.0, 0.0};
    mem_usage_t   mem_usage;
    superlu_options_t options;
    SuperLUStat_t stat;

    int restrt, iter, maxit, i;
    double resid;
    complex *x, *b;

#ifdef DEBUG
    extern int num_drop_L, num_drop_U;
#endif

#if ( DEBUGlevel>=1 )
    CHECK_MALLOC("Enter main()");
#endif

    /* Defaults */
    lwork = 0;
    nrhs  = 1;
    equil = YES;
    u	  = 0.1; /* u=1.0 for complete factorization */
    trans = NOTRANS;

    /* Set the default input options:
	options.Fact = DOFACT;
	options.Equil = YES;
	options.ColPerm = COLAMD;
	options.DiagPivotThresh = 0.1; //different from complete LU
	options.Trans = NOTRANS;
	options.IterRefine = NOREFINE;
	options.SymmetricMode = NO;
	options.PivotGrowth = NO;
	options.ConditionNumber = NO;
	options.PrintStat = YES;
	options.RowPerm = LargeDiag;
	options.ILU_DropTol = 1e-4;
	options.ILU_FillTol = 1e-2;
	options.ILU_FillFactor = 10.0;
	options.ILU_DropRule = DROP_BASIC | DROP_AREA;
	options.ILU_Norm = INF_NORM;
	options.ILU_MILU = SMILU_2;
     */
    ilu_set_default_options(&options);

    /* Modify the defaults. */
    options.PivotGrowth = YES;	  /* Compute reciprocal pivot growth */
    options.ConditionNumber = YES;/* Compute reciprocal condition number */

    if ( lwork > 0 ) {
	work = SUPERLU_MALLOC(lwork);
	if ( !work ) ABORT("Malloc fails for work[].");
    }

    /* Read matrix A from a file in Harwell-Boeing format.*/
    if (argc < 2)
    {
	printf("Usage:\n%s [OPTION] < [INPUT] > [OUTPUT]\nOPTION:\n"
		"-h -hb:\n\t[INPUT] is a Harwell-Boeing format matrix.\n"
		"-r -rb:\n\t[INPUT] is a Rutherford-Boeing format matrix.\n"
		"-t -triplet:\n\t[INPUT] is a triplet format matrix.\n",
		argv[0]);
	return 0;
    }
    else
    {
	switch (argv[1][1])
	{
	    case 'H':
	    case 'h':
		printf("Input a Harwell-Boeing format matrix:\n");
		creadhb(&m, &n, &nnz, &a, &asub, &xa);
		break;
	    case 'R':
	    case 'r':
		printf("Input a Rutherford-Boeing format matrix:\n");
		creadrb(&m, &n, &nnz, &a, &asub, &xa);
		break;
	    case 'T':
	    case 't':
		printf("Input a triplet format matrix:\n");
		creadtriple(&m, &n, &nnz, &a, &asub, &xa);
		break;
	    default:
		printf("Unrecognized format.\n");
		return 0;
	}
    }

    cCreate_CompCol_Matrix(&A, m, n, nnz, a, asub, xa, SLU_NC, SLU_C, SLU_GE);
    Astore = A.Store;
    cfill_diag(n, Astore);
    printf("Dimension %dx%d; # nonzeros %d\n", A.nrow, A.ncol, Astore->nnz);
    fflush(stdout);

    if ( !(rhsb = complexMalloc(m * nrhs)) ) ABORT("Malloc fails for rhsb[].");
    if ( !(rhsx = complexMalloc(m * nrhs)) ) ABORT("Malloc fails for rhsx[].");
    cCreate_Dense_Matrix(&B, m, nrhs, rhsb, m, SLU_DN, SLU_C, SLU_GE);
    cCreate_Dense_Matrix(&X, m, nrhs, rhsx, m, SLU_DN, SLU_C, SLU_GE);
    xact = complexMalloc(n * nrhs);
    ldx = n;
    cGenXtrue(n, nrhs, xact, ldx);
    cFillRHS(trans, nrhs, xact, ldx, &A, &B);

    if ( !(etree = intMalloc(n)) ) ABORT("Malloc fails for etree[].");
    if ( !(perm_r = intMalloc(m)) ) ABORT("Malloc fails for perm_r[].");
    if ( !(perm_c = intMalloc(n)) ) ABORT("Malloc fails for perm_c[].");
    if ( !(R = (float *) SUPERLU_MALLOC(A.nrow * sizeof(float))) )
	ABORT("SUPERLU_MALLOC fails for R[].");
    if ( !(C = (float *) SUPERLU_MALLOC(A.ncol * sizeof(float))) )
	ABORT("SUPERLU_MALLOC fails for C[].");

    info = 0;
#ifdef DEBUG
    num_drop_L = 0;
    num_drop_U = 0;
#endif

    /* Initialize the statistics variables. */
    StatInit(&stat);

    /* Compute the incomplete factorization and compute the condition number
       and pivot growth using dgsisx. */
    cgsisx(&options, &A, perm_c, perm_r, etree, equed, R, C, &L, &U, work,
	   lwork, &B, &X, &rpg, &rcond, &mem_usage, &stat, &info);

    Lstore = (SCformat *) L.Store;
    Ustore = (NCformat *) U.Store;
    printf("cgsisx(): info %d\n", info);
    if (info > 0 || rcond < 1e-8 || rpg > 1e8)
	printf("WARNING: This preconditioner might be unstable.\n");

    if ( info == 0 || info == n+1 ) {

	if ( options.PivotGrowth == YES )
	    printf("Recip. pivot growth = %e\n", rpg);
	if ( options.ConditionNumber == YES )
	    printf("Recip. condition number = %e\n", rcond);

    } else if ( info > 0 && lwork == -1 ) {
	printf("** Estimated memory: %d bytes\n", info - n);
    }
    printf("n(A) = %d, nnz(A) = %d\n", n, Astore->nnz);
    printf("No of nonzeros in factor L = %d\n", Lstore->nnz);
    printf("No of nonzeros in factor U = %d\n", Ustore->nnz);
    printf("No of nonzeros in L+U = %d\n", Lstore->nnz + Ustore->nnz - n);
    printf("Fill ratio: nnz(F)/nnz(A) = %.3f\n",
	    ((double)(Lstore->nnz) + (double)(Ustore->nnz) - (double)n)
	    / (double)Astore->nnz);
    printf("L\\U MB %.3f\ttotal MB needed %.3f\n",
	   mem_usage.for_lu/1e6, mem_usage.total_needed/1e6);
    fflush(stdout);

    /* Set the global variables. */
    GLOBAL_A = &A;
    GLOBAL_L = &L;
    GLOBAL_U = &U;
    GLOBAL_STAT = &stat;
    GLOBAL_PERM_C = perm_c;
    GLOBAL_PERM_R = perm_r;

    /* Set the variables used by GMRES. */
    restrt = SUPERLU_MIN(n / 3 + 1, 50);
    maxit = 1000;
    iter = maxit;
    resid = 1e-8;
    if (!(b = complexMalloc(m))) ABORT("Malloc fails for b[].");
    if (!(x = complexMalloc(n))) ABORT("Malloc fails for x[].");
    sp_cgemv("N", one, &A, xact, 1, zero, b, 1);

    if (info <= n + 1)
    {
	int i_1 = 1;
	double maxferr = 0.0, nrmA, nrmB, res, t;
        complex temp;
	extern float scnrm2_(int *, complex [], int *);
	extern void caxpy_(int *, complex *, complex [], int *, complex [], int *);

	/* Call GMRES. */
	/*double *sol = (double*) ((DNformat*) X.Store)->nzval;
	for (i = 0; i < n; i++) x[i] = sol[i];*/
	for (i = 0; i < n; i++) x[i] = zero;

	t = SuperLU_timer_();

	cfgmr(n, cmatvec_mult, cpsolve, b, x, resid, restrt, &iter, stdout);

	t = SuperLU_timer_() - t;

	/* Output the result. */
	nrmA = scnrm2_(&(Astore->nnz), (complex *)((DNformat *)A.Store)->nzval,
		&i_1);
	nrmB = scnrm2_(&m, b, &i_1);
	sp_cgemv("N", none, &A, x, 1, one, b, 1);
	res = scnrm2_(&m, b, &i_1);
	resid = res / nrmB;
	printf("||A||_F = %.1e, ||B||_2 = %.1e, ||B-A*X||_2 = %.1e, "
		"relres = %.1e\n", nrmA, nrmB, res, resid);

	if (iter >= maxit)
	{
	    if (resid >= 1.0) iter = -180;
	    else if (resid > 1e-8) iter = -111;
	}
	printf("iteration: %d\nresidual: %.1e\nGMRES time: %.2f seconds.\n",
		iter, resid, t);

	for (i = 0; i < m; i++)
            c_sub(&temp, &x[i], &xact[i]);
            maxferr = SUPERLU_MAX(maxferr, c_abs1(&temp));
	printf("||X-X_true||_oo = %.1e\n", maxferr);
    }
#ifdef DEBUG
    printf("%d entries in L and %d entries in U dropped.\n",
	    num_drop_L, num_drop_U);
#endif
    fflush(stdout);

    if ( options.PrintStat ) StatPrint(&stat);
    StatFree(&stat);

    SUPERLU_FREE (rhsb);
    SUPERLU_FREE (rhsx);
    SUPERLU_FREE (xact);
    SUPERLU_FREE (etree);
    SUPERLU_FREE (perm_r);
    SUPERLU_FREE (perm_c);
    SUPERLU_FREE (R);
    SUPERLU_FREE (C);
    Destroy_CompCol_Matrix(&A);
    Destroy_SuperMatrix_Store(&B);
    Destroy_SuperMatrix_Store(&X);
    if ( lwork >= 0 ) {
	Destroy_SuperNode_Matrix(&L);
	Destroy_CompCol_Matrix(&U);
    }
    SUPERLU_FREE(b);
    SUPERLU_FREE(x);

#if ( DEBUGlevel>=1 )
    CHECK_MALLOC("Exit main()");
#endif

    return 0;
}
int
sp_cgemm(char *trans, int m, int n, int k, 
         complex alpha, SuperMatrix *A, complex *b, int ldb, 
         complex beta, complex *c, int ldc)
{
/*  Purpose   
    =======   

    sp_c performs one of the matrix-matrix operations   

       C := alpha*op( A )*op( B ) + beta*C,   

    where  op( X ) is one of 

       op( X ) = X   or   op( X ) = X'   or   op( X ) = conjg( X' ),

    alpha and beta are scalars, and A, B and C are matrices, with op( A ) 
    an m by k matrix,  op( B )  a  k by n matrix and  C an m by n matrix. 
  

    Parameters   
    ==========   

    TRANS  - (input) char*
             On entry, TRANS specifies the operation to be performed as
             follows:
                TRANS = 'N' or 'n'   y := alpha*A*x + beta*y.
                TRANS = 'T' or 't'   y := alpha*A'*x + beta*y.
                TRANS = 'C' or 'c'   y := alpha*A'*x + beta*y.

    M      - (input) int   
             On entry,  M  specifies  the number of rows of the matrix 
	     op( A ) and of the matrix C.  M must be at least zero. 
	     Unchanged on exit.   

    N      - (input) int
             On entry,  N specifies the number of columns of the matrix 
	     op( B ) and the number of columns of the matrix C. N must be 
	     at least zero.
	     Unchanged on exit.   

    K      - (input) int
             On entry, K specifies the number of columns of the matrix 
	     op( A ) and the number of rows of the matrix op( B ). K must 
	     be at least  zero.   
             Unchanged on exit.
	     
    ALPHA  - (input) complex
             On entry, ALPHA specifies the scalar alpha.   

    A      - (input) SuperMatrix*
             Matrix A with a sparse format, of dimension (A->nrow, A->ncol).
             Currently, the type of A can be:
                 Stype = NC or NCP; Dtype = SLU_C; Mtype = GE. 
             In the future, more general A can be handled.

    B      - COMPLEX PRECISION array of DIMENSION ( LDB, kb ), where kb is 
             n when TRANSB = 'N' or 'n',  and is  k otherwise.   
             Before entry with  TRANSB = 'N' or 'n',  the leading k by n 
             part of the array B must contain the matrix B, otherwise 
             the leading n by k part of the array B must contain the 
             matrix B.   
             Unchanged on exit.   

    LDB    - (input) int
             On entry, LDB specifies the first dimension of B as declared 
             in the calling (sub) program. LDB must be at least max( 1, n ).  
             Unchanged on exit.   

    BETA   - (input) complex
             On entry, BETA specifies the scalar beta. When BETA is   
             supplied as zero then C need not be set on input.   

    C      - COMPLEX PRECISION array of DIMENSION ( LDC, n ).   
             Before entry, the leading m by n part of the array C must 
             contain the matrix C,  except when beta is zero, in which 
             case C need not be set on entry.   
             On exit, the array C is overwritten by the m by n matrix 
	     ( alpha*op( A )*B + beta*C ).   

    LDC    - (input) int
             On entry, LDC specifies the first dimension of C as declared 
             in the calling (sub)program. LDC must be at least max(1,m).   
             Unchanged on exit.   

    ==== Sparse Level 3 Blas routine.   
*/
    int    incx = 1, incy = 1;
    int    j;

    for (j = 0; j < n; ++j) {
	sp_cgemv(trans, alpha, A, &b[ldb*j], incx, beta, &c[ldc*j], incy);
    }
    return 0;    
}
Exemple #5
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void cmatvec_mult(complex alpha, complex x[], complex beta, complex y[])
{
    SuperMatrix *A = GLOBAL_A;

    sp_cgemv("N", alpha, A, x, 1, beta, y, 1);
}