/* Subroutine */ int sgelss_(integer *m, integer *n, integer *nrhs, real *a,
integer *lda, real *b, integer *ldb, real *s, real *rcond, integer *
rank, real *work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2, i__3, i__4;
real r__1;
/* Local variables */
static real anrm, bnrm;
static integer itau;
static real vdum[1];
static integer i__, iascl, ibscl, chunk;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static real sfmin;
static integer minmn, maxmn;
extern /* Subroutine */ int sgemv_(char *, integer *, integer *, real *,
real *, integer *, real *, integer *, real *, real *, integer *);
static integer itaup, itauq;
extern /* Subroutine */ int srscl_(integer *, real *, real *, integer *);
static integer mnthr, iwork;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
static integer bl, ie, il;
extern /* Subroutine */ int slabad_(real *, real *);
static integer mm, bdspac;
extern /* Subroutine */ int sgebrd_(integer *, integer *, real *, integer
*, real *, real *, real *, real *, real *, integer *, integer *);
extern doublereal slamch_(char *), slange_(char *, integer *,
integer *, real *, integer *, real *);
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static real bignum;
extern /* Subroutine */ int sgelqf_(integer *, integer *, real *, integer
*, real *, real *, integer *, integer *), slascl_(char *, integer
*, integer *, real *, real *, integer *, integer *, real *,
integer *, integer *), sgeqrf_(integer *, integer *, real
*, integer *, real *, real *, integer *, integer *), slacpy_(char
*, integer *, integer *, real *, integer *, real *, integer *), slaset_(char *, integer *, integer *, real *, real *,
real *, integer *), sbdsqr_(char *, integer *, integer *,
integer *, integer *, real *, real *, real *, integer *, real *,
integer *, real *, integer *, real *, integer *), sorgbr_(
char *, integer *, integer *, integer *, real *, integer *, real *
, real *, integer *, integer *);
static integer ldwork;
extern /* Subroutine */ int sormbr_(char *, char *, char *, integer *,
integer *, integer *, real *, integer *, real *, real *, integer *
, real *, integer *, integer *);
static integer minwrk, maxwrk;
static real smlnum;
extern /* Subroutine */ int sormlq_(char *, char *, integer *, integer *,
integer *, real *, integer *, real *, real *, integer *, real *,
integer *, integer *);
static logical lquery;
extern /* Subroutine */ int sormqr_(char *, char *, integer *, integer *,
integer *, real *, integer *, real *, real *, integer *, real *,
integer *, integer *);
static real eps, thr;
#define a_ref(a_1,a_2) a[(a_2)*a_dim1 + a_1]
#define b_ref(a_1,a_2) b[(a_2)*b_dim1 + a_1]
/* -- LAPACK driver routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
October 31, 1999
Purpose
=======
SGELSS computes the minimum norm solution to a real linear least
squares problem:
Minimize 2-norm(| b - A*x |).
using the singular value decomposition (SVD) of A. A is an M-by-N
matrix which may be rank-deficient.
Several right hand side vectors b and solution vectors x can be
handled in a single call; they are stored as the columns of the
M-by-NRHS right hand side matrix B and the N-by-NRHS solution matrix
X.
The effective rank of A is determined by treating as zero those
singular values which are less than RCOND times the largest singular
value.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrices B and X. NRHS >= 0.
A (input/output) REAL array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit, the first min(m,n) rows of A are overwritten with
its right singular vectors, stored rowwise.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
B (input/output) REAL array, dimension (LDB,NRHS)
On entry, the M-by-NRHS right hand side matrix B.
On exit, B is overwritten by the N-by-NRHS solution
matrix X. If m >= n and RANK = n, the residual
sum-of-squares for the solution in the i-th column is given
by the sum of squares of elements n+1:m in that column.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,max(M,N)).
S (output) REAL array, dimension (min(M,N))
The singular values of A in decreasing order.
The condition number of A in the 2-norm = S(1)/S(min(m,n)).
RCOND (input) REAL
RCOND is used to determine the effective rank of A.
Singular values S(i) <= RCOND*S(1) are treated as zero.
If RCOND < 0, machine precision is used instead.
RANK (output) INTEGER
The effective rank of A, i.e., the number of singular values
which are greater than RCOND*S(1).
WORK (workspace/output) REAL array, dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= 1, and also:
LWORK >= 3*min(M,N) + max( 2*min(M,N), max(M,N), NRHS )
For good performance, LWORK should generally be larger.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: the algorithm for computing the SVD failed to converge;
if INFO = i, i off-diagonal elements of an intermediate
bidiagonal form did not converge to zero.
=====================================================================
Test the input arguments
Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1 * 1;
b -= b_offset;
--s;
--work;
/* Function Body */
*info = 0;
minmn = min(*m,*n);
maxmn = max(*m,*n);
mnthr = ilaenv_(&c__6, "SGELSS", " ", m, n, nrhs, &c_n1, (ftnlen)6, (
ftnlen)1);
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*nrhs < 0) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
} else if (*ldb < max(1,maxmn)) {
*info = -7;
}
/* Compute workspace
(Note: Comments in the code beginning "Workspace:" describe the
minimal amount of workspace needed at that point in the code,
as well as the preferred amount for good performance.
NB refers to the optimal block size for the immediately
following subroutine, as returned by ILAENV.) */
minwrk = 1;
if (*info == 0 && (*lwork >= 1 || lquery)) {
maxwrk = 0;
mm = *m;
if (*m >= *n && *m >= mnthr) {
/* Path 1a - overdetermined, with many more rows than columns */
mm = *n;
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + *n * ilaenv_(&c__1, "SGEQRF", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + *nrhs * ilaenv_(&c__1, "SORMQR", "LT",
m, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)2);
maxwrk = max(i__1,i__2);
}
if (*m >= *n) {
/* Path 1 - overdetermined or exactly determined
Compute workspace needed for SBDSQR
Computing MAX */
i__1 = 1, i__2 = *n * 5;
bdspac = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + (mm + *n) * ilaenv_(&c__1, "SGEBRD"
, " ", &mm, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + *nrhs * ilaenv_(&c__1, "SORMBR",
"QLT", &mm, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + (*n - 1) * ilaenv_(&c__1, "SORGBR",
"P", n, n, n, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
maxwrk = max(maxwrk,bdspac);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * *nrhs;
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = *n * 3 + mm, i__2 = *n * 3 + *nrhs, i__1 = max(i__1,i__2);
minwrk = max(i__1,bdspac);
maxwrk = max(minwrk,maxwrk);
}
if (*n > *m) {
/* Compute workspace needed for SBDSQR
Computing MAX */
i__1 = 1, i__2 = *m * 5;
bdspac = max(i__1,i__2);
/* Computing MAX */
i__1 = *m * 3 + *nrhs, i__2 = *m * 3 + *n, i__1 = max(i__1,i__2);
minwrk = max(i__1,bdspac);
if (*n >= mnthr) {
/* Path 2a - underdetermined, with many more columns
than rows */
maxwrk = *m + *m * ilaenv_(&c__1, "SGELQF", " ", m, n, &c_n1,
&c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + (*m << 1) *
ilaenv_(&c__1, "SGEBRD", " ", m, m, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + *nrhs * ilaenv_(&
c__1, "SORMBR", "QLT", m, nrhs, m, &c_n1, (ftnlen)6, (
ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + (*m - 1) *
ilaenv_(&c__1, "SORGBR", "P", m, m, m, &c_n1, (ftnlen)
6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + *m + bdspac;
maxwrk = max(i__1,i__2);
if (*nrhs > 1) {
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + *m + *m * *nrhs;
maxwrk = max(i__1,i__2);
} else {
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 1);
maxwrk = max(i__1,i__2);
}
/* Computing MAX */
i__1 = maxwrk, i__2 = *m + *nrhs * ilaenv_(&c__1, "SORMLQ",
"LT", n, nrhs, m, &c_n1, (ftnlen)6, (ftnlen)2);
maxwrk = max(i__1,i__2);
} else {
/* Path 2 - underdetermined */
maxwrk = *m * 3 + (*n + *m) * ilaenv_(&c__1, "SGEBRD", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * 3 + *nrhs * ilaenv_(&c__1, "SORMBR"
, "QLT", m, nrhs, m, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * 3 + *m * ilaenv_(&c__1, "SORGBR",
"P", m, n, m, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
maxwrk = max(maxwrk,bdspac);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * *nrhs;
maxwrk = max(i__1,i__2);
}
}
maxwrk = max(minwrk,maxwrk);
work[1] = (real) maxwrk;
}
minwrk = max(minwrk,1);
if (*lwork < minwrk && ! lquery) {
*info = -12;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SGELSS", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
*rank = 0;
return 0;
}
/* Get machine parameters */
eps = slamch_("P");
sfmin = slamch_("S");
smlnum = sfmin / eps;
bignum = 1.f / smlnum;
slabad_(&smlnum, &bignum);
/* Scale A if max element outside range [SMLNUM,BIGNUM] */
anrm = slange_("M", m, n, &a[a_offset], lda, &work[1]);
iascl = 0;
if (anrm > 0.f && anrm < smlnum) {
/* Scale matrix norm up to SMLNUM */
slascl_("G", &c__0, &c__0, &anrm, &smlnum, m, n, &a[a_offset], lda,
info);
iascl = 1;
} else if (anrm > bignum) {
/* Scale matrix norm down to BIGNUM */
slascl_("G", &c__0, &c__0, &anrm, &bignum, m, n, &a[a_offset], lda,
info);
iascl = 2;
} else if (anrm == 0.f) {
/* Matrix all zero. Return zero solution. */
i__1 = max(*m,*n);
slaset_("F", &i__1, nrhs, &c_b74, &c_b74, &b[b_offset], ldb);
slaset_("F", &minmn, &c__1, &c_b74, &c_b74, &s[1], &c__1);
*rank = 0;
goto L70;
}
/* Scale B if max element outside range [SMLNUM,BIGNUM] */
bnrm = slange_("M", m, nrhs, &b[b_offset], ldb, &work[1]);
ibscl = 0;
if (bnrm > 0.f && bnrm < smlnum) {
/* Scale matrix norm up to SMLNUM */
slascl_("G", &c__0, &c__0, &bnrm, &smlnum, m, nrhs, &b[b_offset], ldb,
info);
ibscl = 1;
} else if (bnrm > bignum) {
/* Scale matrix norm down to BIGNUM */
slascl_("G", &c__0, &c__0, &bnrm, &bignum, m, nrhs, &b[b_offset], ldb,
info);
ibscl = 2;
}
/* Overdetermined case */
if (*m >= *n) {
/* Path 1 - overdetermined or exactly determined */
mm = *m;
if (*m >= mnthr) {
/* Path 1a - overdetermined, with many more rows than columns */
mm = *n;
itau = 1;
iwork = itau + *n;
/* Compute A=Q*R
(Workspace: need 2*N, prefer N+N*NB) */
i__1 = *lwork - iwork + 1;
sgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[iwork], &i__1,
info);
/* Multiply B by transpose(Q)
(Workspace: need N+NRHS, prefer N+NRHS*NB) */
i__1 = *lwork - iwork + 1;
sormqr_("L", "T", m, nrhs, n, &a[a_offset], lda, &work[itau], &b[
b_offset], ldb, &work[iwork], &i__1, info);
/* Zero out below R */
if (*n > 1) {
i__1 = *n - 1;
i__2 = *n - 1;
slaset_("L", &i__1, &i__2, &c_b74, &c_b74, &a_ref(2, 1), lda);
}
}
ie = 1;
itauq = ie + *n;
itaup = itauq + *n;
iwork = itaup + *n;
/* Bidiagonalize R in A
(Workspace: need 3*N+MM, prefer 3*N+(MM+N)*NB) */
i__1 = *lwork - iwork + 1;
sgebrd_(&mm, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[iwork], &i__1, info);
/* Multiply B by transpose of left bidiagonalizing vectors of R
(Workspace: need 3*N+NRHS, prefer 3*N+NRHS*NB) */
i__1 = *lwork - iwork + 1;
sormbr_("Q", "L", "T", &mm, nrhs, n, &a[a_offset], lda, &work[itauq],
&b[b_offset], ldb, &work[iwork], &i__1, info);
/* Generate right bidiagonalizing vectors of R in A
(Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) */
i__1 = *lwork - iwork + 1;
sorgbr_("P", n, n, n, &a[a_offset], lda, &work[itaup], &work[iwork], &
i__1, info);
iwork = ie + *n;
/* Perform bidiagonal QR iteration
multiply B by transpose of left singular vectors
compute right singular vectors in A
(Workspace: need BDSPAC) */
sbdsqr_("U", n, n, &c__0, nrhs, &s[1], &work[ie], &a[a_offset], lda,
vdum, &c__1, &b[b_offset], ldb, &work[iwork], info)
;
if (*info != 0) {
goto L70;
}
/* Multiply B by reciprocals of singular values
Computing MAX */
r__1 = *rcond * s[1];
thr = dmax(r__1,sfmin);
if (*rcond < 0.f) {
/* Computing MAX */
r__1 = eps * s[1];
thr = dmax(r__1,sfmin);
}
*rank = 0;
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (s[i__] > thr) {
srscl_(nrhs, &s[i__], &b_ref(i__, 1), ldb);
++(*rank);
} else {
slaset_("F", &c__1, nrhs, &c_b74, &c_b74, &b_ref(i__, 1), ldb);
}
/* L10: */
}
/* Multiply B by right singular vectors
(Workspace: need N, prefer N*NRHS) */
if (*lwork >= *ldb * *nrhs && *nrhs > 1) {
sgemm_("T", "N", n, nrhs, n, &c_b108, &a[a_offset], lda, &b[
b_offset], ldb, &c_b74, &work[1], ldb);
slacpy_("G", n, nrhs, &work[1], ldb, &b[b_offset], ldb)
;
} else if (*nrhs > 1) {
chunk = *lwork / *n;
i__1 = *nrhs;
i__2 = chunk;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = *nrhs - i__ + 1;
bl = min(i__3,chunk);
sgemm_("T", "N", n, &bl, n, &c_b108, &a[a_offset], lda, &
b_ref(1, i__), ldb, &c_b74, &work[1], n);
slacpy_("G", n, &bl, &work[1], n, &b_ref(1, i__), ldb);
/* L20: */
}
} else {
sgemv_("T", n, n, &c_b108, &a[a_offset], lda, &b[b_offset], &c__1,
&c_b74, &work[1], &c__1);
scopy_(n, &work[1], &c__1, &b[b_offset], &c__1);
}
} else /* if(complicated condition) */ {
/* Computing MAX */
i__2 = *m, i__1 = (*m << 1) - 4, i__2 = max(i__2,i__1), i__2 = max(
i__2,*nrhs), i__1 = *n - *m * 3;
if (*n >= mnthr && *lwork >= (*m << 2) + *m * *m + max(i__2,i__1)) {
/* Path 2a - underdetermined, with many more columns than rows
and sufficient workspace for an efficient algorithm */
ldwork = *m;
/* Computing MAX
Computing MAX */
i__3 = *m, i__4 = (*m << 1) - 4, i__3 = max(i__3,i__4), i__3 =
max(i__3,*nrhs), i__4 = *n - *m * 3;
i__2 = (*m << 2) + *m * *lda + max(i__3,i__4), i__1 = *m * *lda +
*m + *m * *nrhs;
if (*lwork >= max(i__2,i__1)) {
ldwork = *lda;
}
itau = 1;
iwork = *m + 1;
/* Compute A=L*Q
(Workspace: need 2*M, prefer M+M*NB) */
i__2 = *lwork - iwork + 1;
sgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[iwork], &i__2,
info);
il = iwork;
/* Copy L to WORK(IL), zeroing out above it */
slacpy_("L", m, m, &a[a_offset], lda, &work[il], &ldwork);
i__2 = *m - 1;
i__1 = *m - 1;
slaset_("U", &i__2, &i__1, &c_b74, &c_b74, &work[il + ldwork], &
ldwork);
ie = il + ldwork * *m;
itauq = ie + *m;
itaup = itauq + *m;
iwork = itaup + *m;
/* Bidiagonalize L in WORK(IL)
(Workspace: need M*M+5*M, prefer M*M+4*M+2*M*NB) */
i__2 = *lwork - iwork + 1;
sgebrd_(m, m, &work[il], &ldwork, &s[1], &work[ie], &work[itauq],
&work[itaup], &work[iwork], &i__2, info);
/* Multiply B by transpose of left bidiagonalizing vectors of L
(Workspace: need M*M+4*M+NRHS, prefer M*M+4*M+NRHS*NB) */
i__2 = *lwork - iwork + 1;
sormbr_("Q", "L", "T", m, nrhs, m, &work[il], &ldwork, &work[
itauq], &b[b_offset], ldb, &work[iwork], &i__2, info);
/* Generate right bidiagonalizing vectors of R in WORK(IL)
(Workspace: need M*M+5*M-1, prefer M*M+4*M+(M-1)*NB) */
i__2 = *lwork - iwork + 1;
sorgbr_("P", m, m, m, &work[il], &ldwork, &work[itaup], &work[
iwork], &i__2, info);
iwork = ie + *m;
/* Perform bidiagonal QR iteration,
computing right singular vectors of L in WORK(IL) and
multiplying B by transpose of left singular vectors
(Workspace: need M*M+M+BDSPAC) */
sbdsqr_("U", m, m, &c__0, nrhs, &s[1], &work[ie], &work[il], &
ldwork, &a[a_offset], lda, &b[b_offset], ldb, &work[iwork]
, info);
if (*info != 0) {
goto L70;
}
/* Multiply B by reciprocals of singular values
Computing MAX */
r__1 = *rcond * s[1];
thr = dmax(r__1,sfmin);
if (*rcond < 0.f) {
/* Computing MAX */
r__1 = eps * s[1];
thr = dmax(r__1,sfmin);
}
*rank = 0;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
if (s[i__] > thr) {
srscl_(nrhs, &s[i__], &b_ref(i__, 1), ldb);
++(*rank);
} else {
slaset_("F", &c__1, nrhs, &c_b74, &c_b74, &b_ref(i__, 1),
ldb);
}
/* L30: */
}
iwork = ie;
/* Multiply B by right singular vectors of L in WORK(IL)
(Workspace: need M*M+2*M, prefer M*M+M+M*NRHS) */
if (*lwork >= *ldb * *nrhs + iwork - 1 && *nrhs > 1) {
sgemm_("T", "N", m, nrhs, m, &c_b108, &work[il], &ldwork, &b[
b_offset], ldb, &c_b74, &work[iwork], ldb);
slacpy_("G", m, nrhs, &work[iwork], ldb, &b[b_offset], ldb);
} else if (*nrhs > 1) {
chunk = (*lwork - iwork + 1) / *m;
i__2 = *nrhs;
i__1 = chunk;
for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ +=
i__1) {
/* Computing MIN */
i__3 = *nrhs - i__ + 1;
bl = min(i__3,chunk);
sgemm_("T", "N", m, &bl, m, &c_b108, &work[il], &ldwork, &
b_ref(1, i__), ldb, &c_b74, &work[iwork], n);
slacpy_("G", m, &bl, &work[iwork], n, &b_ref(1, i__), ldb);
/* L40: */
}
} else {
sgemv_("T", m, m, &c_b108, &work[il], &ldwork, &b_ref(1, 1), &
c__1, &c_b74, &work[iwork], &c__1);
scopy_(m, &work[iwork], &c__1, &b_ref(1, 1), &c__1);
}
/* Zero out below first M rows of B */
i__1 = *n - *m;
slaset_("F", &i__1, nrhs, &c_b74, &c_b74, &b_ref(*m + 1, 1), ldb);
iwork = itau + *m;
/* Multiply transpose(Q) by B
(Workspace: need M+NRHS, prefer M+NRHS*NB) */
i__1 = *lwork - iwork + 1;
sormlq_("L", "T", n, nrhs, m, &a[a_offset], lda, &work[itau], &b[
b_offset], ldb, &work[iwork], &i__1, info);
} else {
/* Path 2 - remaining underdetermined cases */
ie = 1;
itauq = ie + *m;
itaup = itauq + *m;
iwork = itaup + *m;
/* Bidiagonalize A
(Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) */
i__1 = *lwork - iwork + 1;
sgebrd_(m, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[iwork], &i__1, info);
/* Multiply B by transpose of left bidiagonalizing vectors
(Workspace: need 3*M+NRHS, prefer 3*M+NRHS*NB) */
i__1 = *lwork - iwork + 1;
sormbr_("Q", "L", "T", m, nrhs, n, &a[a_offset], lda, &work[itauq]
, &b[b_offset], ldb, &work[iwork], &i__1, info);
/* Generate right bidiagonalizing vectors in A
(Workspace: need 4*M, prefer 3*M+M*NB) */
i__1 = *lwork - iwork + 1;
sorgbr_("P", m, n, m, &a[a_offset], lda, &work[itaup], &work[
iwork], &i__1, info);
iwork = ie + *m;
/* Perform bidiagonal QR iteration,
computing right singular vectors of A in A and
multiplying B by transpose of left singular vectors
(Workspace: need BDSPAC) */
sbdsqr_("L", m, n, &c__0, nrhs, &s[1], &work[ie], &a[a_offset],
lda, vdum, &c__1, &b[b_offset], ldb, &work[iwork], info);
if (*info != 0) {
goto L70;
}
/* Multiply B by reciprocals of singular values
Computing MAX */
r__1 = *rcond * s[1];
thr = dmax(r__1,sfmin);
if (*rcond < 0.f) {
/* Computing MAX */
r__1 = eps * s[1];
thr = dmax(r__1,sfmin);
}
*rank = 0;
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
if (s[i__] > thr) {
srscl_(nrhs, &s[i__], &b_ref(i__, 1), ldb);
++(*rank);
} else {
slaset_("F", &c__1, nrhs, &c_b74, &c_b74, &b_ref(i__, 1),
ldb);
}
/* L50: */
}
/* Multiply B by right singular vectors of A
(Workspace: need N, prefer N*NRHS) */
if (*lwork >= *ldb * *nrhs && *nrhs > 1) {
sgemm_("T", "N", n, nrhs, m, &c_b108, &a[a_offset], lda, &b[
b_offset], ldb, &c_b74, &work[1], ldb);
slacpy_("F", n, nrhs, &work[1], ldb, &b[b_offset], ldb);
} else if (*nrhs > 1) {
chunk = *lwork / *n;
i__1 = *nrhs;
i__2 = chunk;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ +=
i__2) {
/* Computing MIN */
i__3 = *nrhs - i__ + 1;
bl = min(i__3,chunk);
sgemm_("T", "N", n, &bl, m, &c_b108, &a[a_offset], lda, &
b_ref(1, i__), ldb, &c_b74, &work[1], n);
slacpy_("F", n, &bl, &work[1], n, &b_ref(1, i__), ldb);
/* L60: */
}
} else {
sgemv_("T", m, n, &c_b108, &a[a_offset], lda, &b[b_offset], &
c__1, &c_b74, &work[1], &c__1);
scopy_(n, &work[1], &c__1, &b[b_offset], &c__1);
}
}
}
/* Undo scaling */
if (iascl == 1) {
slascl_("G", &c__0, &c__0, &anrm, &smlnum, n, nrhs, &b[b_offset], ldb,
info);
slascl_("G", &c__0, &c__0, &smlnum, &anrm, &minmn, &c__1, &s[1], &
minmn, info);
} else if (iascl == 2) {
slascl_("G", &c__0, &c__0, &anrm, &bignum, n, nrhs, &b[b_offset], ldb,
info);
slascl_("G", &c__0, &c__0, &bignum, &anrm, &minmn, &c__1, &s[1], &
minmn, info);
}
if (ibscl == 1) {
slascl_("G", &c__0, &c__0, &smlnum, &bnrm, n, nrhs, &b[b_offset], ldb,
info);
} else if (ibscl == 2) {
slascl_("G", &c__0, &c__0, &bignum, &bnrm, n, nrhs, &b[b_offset], ldb,
info);
}
L70:
work[1] = (real) maxwrk;
return 0;
/* End of SGELSS */
} /* sgelss_ */
/* Subroutine */ int spotrf_(char *uplo, integer *n, real *a, integer *lda,
integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
integer j, jb, nb;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
logical upper;
extern /* Subroutine */ int strsm_(char *, char *, char *, char *,
integer *, integer *, real *, real *, integer *, real *, integer *
), ssyrk_(char *, char *, integer
*, integer *, real *, real *, integer *, real *, real *, integer *
), spotf2_(char *, integer *, real *, integer *,
integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *);
/* -- LAPACK routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SPOTRF computes the Cholesky factorization of a real symmetric */
/* positive definite matrix A. */
/* The factorization has the form */
/* A = U**T * U, if UPLO = 'U', or */
/* A = L * L**T, if UPLO = 'L', */
/* where U is an upper triangular matrix and L is lower triangular. */
/* This is the block version of the algorithm, calling Level 3 BLAS. */
/* Arguments */
/* ========= */
/* UPLO (input) CHARACTER*1 */
/* = 'U': Upper triangle of A is stored; */
/* = 'L': Lower triangle of A is stored. */
/* N (input) INTEGER */
/* The order of the matrix A. N >= 0. */
/* A (input/output) REAL array, dimension (LDA,N) */
/* On entry, the symmetric matrix A. If UPLO = 'U', the leading */
/* N-by-N upper triangular part of A contains the upper */
/* triangular part of the matrix A, and the strictly lower */
/* triangular part of A is not referenced. If UPLO = 'L', the */
/* leading N-by-N lower triangular part of A contains the lower */
/* triangular part of the matrix A, and the strictly upper */
/* triangular part of A is not referenced. */
/* On exit, if INFO = 0, the factor U or L from the Cholesky */
/* factorization A = U**T*U or A = L*L**T. */
/* LDA (input) INTEGER */
/* The leading dimension of the array A. LDA >= max(1,N). */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: if INFO = i, the leading minor of order i is not */
/* positive definite, and the factorization could not be */
/* completed. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SPOTRF", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "SPOTRF", uplo, n, &c_n1, &c_n1, &c_n1);
if (nb <= 1 || nb >= *n) {
/* Use unblocked code. */
spotf2_(uplo, n, &a[a_offset], lda, info);
} else {
/* Use blocked code. */
if (upper) {
/* Compute the Cholesky factorization A = U'*U. */
i__1 = *n;
i__2 = nb;
for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) {
/* Update and factorize the current diagonal block and test */
/* for non-positive-definiteness. */
/* Computing MIN */
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
ssyrk_("Upper", "Transpose", &jb, &i__3, &c_b13, &a[j *
a_dim1 + 1], lda, &c_b14, &a[j + j * a_dim1], lda);
spotf2_("Upper", &jb, &a[j + j * a_dim1], lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block row. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
sgemm_("Transpose", "No transpose", &jb, &i__3, &i__4, &
c_b13, &a[j * a_dim1 + 1], lda, &a[(j + jb) *
a_dim1 + 1], lda, &c_b14, &a[j + (j + jb) *
a_dim1], lda);
i__3 = *n - j - jb + 1;
strsm_("Left", "Upper", "Transpose", "Non-unit", &jb, &
i__3, &c_b14, &a[j + j * a_dim1], lda, &a[j + (j
+ jb) * a_dim1], lda);
}
/* L10: */
}
} else {
/* Compute the Cholesky factorization A = L*L'. */
i__2 = *n;
i__1 = nb;
for (j = 1; i__1 < 0 ? j >= i__2 : j <= i__2; j += i__1) {
/* Update and factorize the current diagonal block and test */
/* for non-positive-definiteness. */
/* Computing MIN */
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
ssyrk_("Lower", "No transpose", &jb, &i__3, &c_b13, &a[j +
a_dim1], lda, &c_b14, &a[j + j * a_dim1], lda);
spotf2_("Lower", &jb, &a[j + j * a_dim1], lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block column. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
sgemm_("No transpose", "Transpose", &i__3, &jb, &i__4, &
c_b13, &a[j + jb + a_dim1], lda, &a[j + a_dim1],
lda, &c_b14, &a[j + jb + j * a_dim1], lda);
i__3 = *n - j - jb + 1;
strsm_("Right", "Lower", "Transpose", "Non-unit", &i__3, &
jb, &c_b14, &a[j + j * a_dim1], lda, &a[j + jb +
j * a_dim1], lda);
}
/* L20: */
}
}
}
goto L40;
L30:
*info = *info + j - 1;
L40:
return 0;
/* End of SPOTRF */
} /* spotrf_ */
/* Subroutine */ int spotrf_(char *uplo, integer *n, real *a, integer *lda,
integer *info)
{
/* -- LAPACK routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
March 31, 1993
Purpose
=======
SPOTRF computes the Cholesky factorization of a real symmetric
positive definite matrix A.
The factorization has the form
A = U**T * U, if UPLO = 'U', or
A = L * L**T, if UPLO = 'L',
where U is an upper triangular matrix and L is lower triangular.
This is the block version of the algorithm, calling Level 3 BLAS.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) REAL array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
N-by-N upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading N-by-N lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if INFO = 0, the factor U or L from the Cholesky
factorization A = U**T*U or A = L*L**T.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, the leading minor of order i is not
positive definite, and the factorization could not be
completed.
=====================================================================
Test the input parameters.
Parameter adjustments */
/* Table of constant values */
static integer c__1 = 1;
static integer c_n1 = -1;
static real c_b13 = -1.f;
static real c_b14 = 1.f;
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer j;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static logical upper;
extern /* Subroutine */ int strsm_(char *, char *, char *, char *,
integer *, integer *, real *, real *, integer *, real *, integer *
), ssyrk_(char *, char *, integer
*, integer *, real *, real *, integer *, real *, real *, integer *
);
static integer jb;
extern /* Subroutine */ int spotf2_(char *, integer *, real *, integer *,
integer *);
static integer nb;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
#define a_ref(a_1,a_2) a[(a_2)*a_dim1 + a_1]
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SPOTRF", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "SPOTRF", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
if (nb <= 1 || nb >= *n) {
/* Use unblocked code. */
spotf2_(uplo, n, &a[a_offset], lda, info);
} else {
/* Use blocked code. */
if (upper) {
/* Compute the Cholesky factorization A = U'*U. */
i__1 = *n;
i__2 = nb;
for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) {
/* Update and factorize the current diagonal block and test
for non-positive-definiteness.
Computing MIN */
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
ssyrk_("Upper", "Transpose", &jb, &i__3, &c_b13, &a_ref(1, j),
lda, &c_b14, &a_ref(j, j), lda)
;
spotf2_("Upper", &jb, &a_ref(j, j), lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block row. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
sgemm_("Transpose", "No transpose", &jb, &i__3, &i__4, &
c_b13, &a_ref(1, j), lda, &a_ref(1, j + jb), lda,
&c_b14, &a_ref(j, j + jb), lda);
i__3 = *n - j - jb + 1;
strsm_("Left", "Upper", "Transpose", "Non-unit", &jb, &
i__3, &c_b14, &a_ref(j, j), lda, &a_ref(j, j + jb)
, lda)
;
}
/* L10: */
}
} else {
/* Compute the Cholesky factorization A = L*L'. */
i__2 = *n;
i__1 = nb;
for (j = 1; i__1 < 0 ? j >= i__2 : j <= i__2; j += i__1) {
/* Update and factorize the current diagonal block and test
for non-positive-definiteness.
Computing MIN */
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
ssyrk_("Lower", "No transpose", &jb, &i__3, &c_b13, &a_ref(j,
1), lda, &c_b14, &a_ref(j, j), lda);
spotf2_("Lower", &jb, &a_ref(j, j), lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block column. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
sgemm_("No transpose", "Transpose", &i__3, &jb, &i__4, &
c_b13, &a_ref(j + jb, 1), lda, &a_ref(j, 1), lda,
&c_b14, &a_ref(j + jb, j), lda);
i__3 = *n - j - jb + 1;
strsm_("Right", "Lower", "Transpose", "Non-unit", &i__3, &
jb, &c_b14, &a_ref(j, j), lda, &a_ref(j + jb, j),
lda);
}
/* L20: */
}
}
}
goto L40;
L30:
*info = *info + j - 1;
L40:
return 0;
/* End of SPOTRF */
} /* spotrf_ */
/* Subroutine */ int schkbd_(integer *nsizes, integer *mval, integer *nval,
integer *ntypes, logical *dotype, integer *nrhs, integer *iseed, real
*thresh, real *a, integer *lda, real *bd, real *be, real *s1, real *
s2, real *x, integer *ldx, real *y, real *z__, real *q, integer *ldq,
real *pt, integer *ldpt, real *u, real *vt, real *work, integer *
lwork, integer *iwork, integer *nout, integer *info)
{
/* Initialized data */
static integer ktype[16] = { 1,2,4,4,4,4,4,6,6,6,6,6,9,9,9,10 };
static integer kmagn[16] = { 1,1,1,1,1,2,3,1,1,1,2,3,1,2,3,0 };
static integer kmode[16] = { 0,0,4,3,1,4,4,4,3,1,4,4,0,0,0,0 };
/* Format strings */
static char fmt_9998[] = "(\002 SCHKBD: \002,a,\002 returned INFO=\002,i"
"6,\002.\002,/9x,\002M=\002,i6,\002, N=\002,i6,\002, JTYPE=\002,i"
"6,\002, ISEED=(\002,3(i5,\002,\002),i5,\002)\002)";
static char fmt_9999[] = "(\002 M=\002,i5,\002, N=\002,i5,\002, type "
"\002,i2,\002, seed=\002,4(i4,\002,\002),\002 test(\002,i2,\002)"
"=\002,g11.4)";
/* System generated locals */
integer a_dim1, a_offset, pt_dim1, pt_offset, q_dim1, q_offset, u_dim1,
u_offset, vt_dim1, vt_offset, x_dim1, x_offset, y_dim1, y_offset,
z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5, i__6, i__7;
real r__1, r__2, r__3, r__4, r__5, r__6, r__7;
/* Builtin functions
Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen);
double log(doublereal), sqrt(doublereal), exp(doublereal);
integer s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void);
/* Local variables */
static real cond;
static integer jcol;
static char path[3];
static integer idum[1], mmax, nmax;
static real unfl, ovfl;
static char uplo[1];
static real temp1, temp2;
static integer i__, j, m, n;
static logical badmm, badnn;
static integer nfail, imode;
extern /* Subroutine */ int sbdt01_(integer *, integer *, integer *, real
*, integer *, real *, integer *, real *, real *, real *, integer *
, real *, real *), sbdt02_(integer *, integer *, real *, integer *
, real *, integer *, real *, integer *, real *, real *), sbdt03_(
char *, integer *, integer *, real *, real *, real *, integer *,
real *, real *, integer *, real *, real *);
static real dumma[1];
static integer iinfo;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static real anorm;
static integer mnmin, mnmax, jsize;
extern /* Subroutine */ int sort01_(char *, integer *, integer *, real *,
integer *, real *, integer *, real *);
static integer itype, jtype, ntest;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *), slahd2_(integer *, char *);
static integer log2ui;
static logical bidiag;
extern /* Subroutine */ int slabad_(real *, real *);
static integer mq;
extern /* Subroutine */ int sbdsdc_(char *, char *, integer *, real *,
real *, real *, integer *, real *, integer *, real *, integer *,
real *, integer *, integer *), sgebrd_(integer *,
integer *, real *, integer *, real *, real *, real *, real *,
real *, integer *, integer *);
extern doublereal slamch_(char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static integer ioldsd[4];
extern /* Subroutine */ int alasum_(char *, integer *, integer *, integer
*, integer *);
extern doublereal slarnd_(integer *, integer *);
static real amninv;
extern /* Subroutine */ int slacpy_(char *, integer *, integer *, real *,
integer *, real *, integer *), slaset_(char *, integer *,
integer *, real *, real *, real *, integer *), sbdsqr_(
char *, integer *, integer *, integer *, integer *, real *, real *
, real *, integer *, real *, integer *, real *, integer *, real *,
integer *), sorgbr_(char *, integer *, integer *,
integer *, real *, integer *, real *, real *, integer *, integer *
), slatmr_(integer *, integer *, char *, integer *, char *
, real *, integer *, real *, real *, char *, char *, real *,
integer *, real *, real *, integer *, real *, char *, integer *,
integer *, integer *, real *, real *, char *, real *, integer *,
integer *, integer *), slatms_(integer *, integer *, char *, integer *, char *,
real *, integer *, real *, real *, integer *, integer *, char *,
real *, integer *, real *, integer *);
static integer minwrk;
static real rtunfl, rtovfl, ulpinv, result[19];
static integer mtypes;
static real dum[1], ulp;
/* Fortran I/O blocks */
static cilist io___39 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___40 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___42 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___43 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___44 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___45 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___51 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___52 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___53 = { 0, 0, 0, fmt_9999, 0 };
#define a_ref(a_1,a_2) a[(a_2)*a_dim1 + a_1]
/* -- LAPACK test routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Purpose
=======
SCHKBD checks the singular value decomposition (SVD) routines.
SGEBRD reduces a real general m by n matrix A to upper or lower
bidiagonal form B by an orthogonal transformation: Q' * A * P = B
(or A = Q * B * P'). The matrix B is upper bidiagonal if m >= n
and lower bidiagonal if m < n.
SORGBR generates the orthogonal matrices Q and P' from SGEBRD.
Note that Q and P are not necessarily square.
SBDSQR computes the singular value decomposition of the bidiagonal
matrix B as B = U S V'. It is called three times to compute
1) B = U S1 V', where S1 is the diagonal matrix of singular
values and the columns of the matrices U and V are the left
and right singular vectors, respectively, of B.
2) Same as 1), but the singular values are stored in S2 and the
singular vectors are not computed.
3) A = (UQ) S (P'V'), the SVD of the original matrix A.
In addition, SBDSQR has an option to apply the left orthogonal matrix
U to a matrix X, useful in least squares applications.
SBDSDC computes the singular value decomposition of the bidiagonal
matrix B as B = U S V' using divide-and-conquer. It is called twice
to compute
1) B = U S1 V', where S1 is the diagonal matrix of singular
values and the columns of the matrices U and V are the left
and right singular vectors, respectively, of B.
2) Same as 1), but the singular values are stored in S2 and the
singular vectors are not computed.
For each pair of matrix dimensions (M,N) and each selected matrix
type, an M by N matrix A and an M by NRHS matrix X are generated.
The problem dimensions are as follows
A: M x N
Q: M x min(M,N) (but M x M if NRHS > 0)
P: min(M,N) x N
B: min(M,N) x min(M,N)
U, V: min(M,N) x min(M,N)
S1, S2 diagonal, order min(M,N)
X: M x NRHS
For each generated matrix, 14 tests are performed:
Test SGEBRD and SORGBR
(1) | A - Q B PT | / ( |A| max(M,N) ulp ), PT = P'
(2) | I - Q' Q | / ( M ulp )
(3) | I - PT PT' | / ( N ulp )
Test SBDSQR on bidiagonal matrix B
(4) | B - U S1 VT | / ( |B| min(M,N) ulp ), VT = V'
(5) | Y - U Z | / ( |Y| max(min(M,N),k) ulp ), where Y = Q' X
and Z = U' Y.
(6) | I - U' U | / ( min(M,N) ulp )
(7) | I - VT VT' | / ( min(M,N) ulp )
(8) S1 contains min(M,N) nonnegative values in decreasing order.
(Return 0 if true, 1/ULP if false.)
(9) | S1 - S2 | / ( |S1| ulp ), where S2 is computed without
computing U and V.
(10) 0 if the true singular values of B are within THRESH of
those in S1. 2*THRESH if they are not. (Tested using
SSVDCH)
Test SBDSQR on matrix A
(11) | A - (QU) S (VT PT) | / ( |A| max(M,N) ulp )
(12) | X - (QU) Z | / ( |X| max(M,k) ulp )
(13) | I - (QU)'(QU) | / ( M ulp )
(14) | I - (VT PT) (PT'VT') | / ( N ulp )
Test SBDSDC on bidiagonal matrix B
(15) | B - U S1 VT | / ( |B| min(M,N) ulp ), VT = V'
(16) | I - U' U | / ( min(M,N) ulp )
(17) | I - VT VT' | / ( min(M,N) ulp )
(18) S1 contains min(M,N) nonnegative values in decreasing order.
(Return 0 if true, 1/ULP if false.)
(19) | S1 - S2 | / ( |S1| ulp ), where S2 is computed without
computing U and V.
The possible matrix types are
(1) The zero matrix.
(2) The identity matrix.
(3) A diagonal matrix with evenly spaced entries
1, ..., ULP and random signs.
(ULP = (first number larger than 1) - 1 )
(4) A diagonal matrix with geometrically spaced entries
1, ..., ULP and random signs.
(5) A diagonal matrix with "clustered" entries 1, ULP, ..., ULP
and random signs.
(6) Same as (3), but multiplied by SQRT( overflow threshold )
(7) Same as (3), but multiplied by SQRT( underflow threshold )
(8) A matrix of the form U D V, where U and V are orthogonal and
D has evenly spaced entries 1, ..., ULP with random signs
on the diagonal.
(9) A matrix of the form U D V, where U and V are orthogonal and
D has geometrically spaced entries 1, ..., ULP with random
signs on the diagonal.
(10) A matrix of the form U D V, where U and V are orthogonal and
D has "clustered" entries 1, ULP,..., ULP with random
signs on the diagonal.
(11) Same as (8), but multiplied by SQRT( overflow threshold )
(12) Same as (8), but multiplied by SQRT( underflow threshold )
(13) Rectangular matrix with random entries chosen from (-1,1).
(14) Same as (13), but multiplied by SQRT( overflow threshold )
(15) Same as (13), but multiplied by SQRT( underflow threshold )
Special case:
(16) A bidiagonal matrix with random entries chosen from a
logarithmic distribution on [ulp^2,ulp^(-2)] (I.e., each
entry is e^x, where x is chosen uniformly on
[ 2 log(ulp), -2 log(ulp) ] .) For *this* type:
(a) SGEBRD is not called to reduce it to bidiagonal form.
(b) the bidiagonal is min(M,N) x min(M,N); if M<N, the
matrix will be lower bidiagonal, otherwise upper.
(c) only tests 5--8 and 14 are performed.
A subset of the full set of matrix types may be selected through
the logical array DOTYPE.
Arguments
==========
NSIZES (input) INTEGER
The number of values of M and N contained in the vectors
MVAL and NVAL. The matrix sizes are used in pairs (M,N).
MVAL (input) INTEGER array, dimension (NM)
The values of the matrix row dimension M.
NVAL (input) INTEGER array, dimension (NM)
The values of the matrix column dimension N.
NTYPES (input) INTEGER
The number of elements in DOTYPE. If it is zero, SCHKBD
does nothing. It must be at least zero. If it is MAXTYP+1
and NSIZES is 1, then an additional type, MAXTYP+1 is
defined, which is to use whatever matrices are in A and B.
This is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
DOTYPE(MAXTYP+1) is .TRUE. .
DOTYPE (input) LOGICAL array, dimension (NTYPES)
If DOTYPE(j) is .TRUE., then for each size (m,n), a matrix
of type j will be generated. If NTYPES is smaller than the
maximum number of types defined (PARAMETER MAXTYP), then
types NTYPES+1 through MAXTYP will not be generated. If
NTYPES is larger than MAXTYP, DOTYPE(MAXTYP+1) through
DOTYPE(NTYPES) will be ignored.
NRHS (input) INTEGER
The number of columns in the "right-hand side" matrices X, Y,
and Z, used in testing SBDSQR. If NRHS = 0, then the
operations on the right-hand side will not be tested.
NRHS must be at least 0.
ISEED (input/output) INTEGER array, dimension (4)
On entry ISEED specifies the seed of the random number
generator. The array elements should be between 0 and 4095;
if not they will be reduced mod 4096. Also, ISEED(4) must
be odd. The values of ISEED are changed on exit, and can be
used in the next call to SCHKBD to continue the same random
number sequence.
THRESH (input) REAL
The threshold value for the test ratios. A result is
included in the output file if RESULT >= THRESH. To have
every test ratio printed, use THRESH = 0. Note that the
expected value of the test ratios is O(1), so THRESH should
be a reasonably small multiple of 1, e.g., 10 or 100.
A (workspace) REAL array, dimension (LDA,NMAX)
where NMAX is the maximum value of N in NVAL.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,MMAX),
where MMAX is the maximum value of M in MVAL.
BD (workspace) REAL array, dimension
(max(min(MVAL(j),NVAL(j))))
BE (workspace) REAL array, dimension
(max(min(MVAL(j),NVAL(j))))
S1 (workspace) REAL array, dimension
(max(min(MVAL(j),NVAL(j))))
S2 (workspace) REAL array, dimension
(max(min(MVAL(j),NVAL(j))))
X (workspace) REAL array, dimension (LDX,NRHS)
LDX (input) INTEGER
The leading dimension of the arrays X, Y, and Z.
LDX >= max(1,MMAX)
Y (workspace) REAL array, dimension (LDX,NRHS)
Z (workspace) REAL array, dimension (LDX,NRHS)
Q (workspace) REAL array, dimension (LDQ,MMAX)
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,MMAX).
PT (workspace) REAL array, dimension (LDPT,NMAX)
LDPT (input) INTEGER
The leading dimension of the arrays PT, U, and V.
LDPT >= max(1, max(min(MVAL(j),NVAL(j)))).
U (workspace) REAL array, dimension
(LDPT,max(min(MVAL(j),NVAL(j))))
V (workspace) REAL array, dimension
(LDPT,max(min(MVAL(j),NVAL(j))))
WORK (workspace) REAL array, dimension (LWORK)
LWORK (input) INTEGER
The number of entries in WORK. This must be at least
3(M+N) and M(M + max(M,N,k) + 1) + N*min(M,N) for all
pairs (M,N)=(MM(j),NN(j))
IWORK (workspace) INTEGER array, dimension at least 8*min(M,N)
NOUT (input) INTEGER
The FORTRAN unit number for printing out error messages
(e.g., if a routine returns IINFO not equal to 0.)
INFO (output) INTEGER
If 0, then everything ran OK.
-1: NSIZES < 0
-2: Some MM(j) < 0
-3: Some NN(j) < 0
-4: NTYPES < 0
-6: NRHS < 0
-8: THRESH < 0
-11: LDA < 1 or LDA < MMAX, where MMAX is max( MM(j) ).
-17: LDB < 1 or LDB < MMAX.
-21: LDQ < 1 or LDQ < MMAX.
-23: LDPT< 1 or LDPT< MNMAX.
-27: LWORK too small.
If SLATMR, SLATMS, SGEBRD, SORGBR, or SBDSQR,
returns an error code, the
absolute value of it is returned.
-----------------------------------------------------------------------
Some Local Variables and Parameters:
---- ----- --------- --- ----------
ZERO, ONE Real 0 and 1.
MAXTYP The number of types defined.
NTEST The number of tests performed, or which can
be performed so far, for the current matrix.
MMAX Largest value in NN.
NMAX Largest value in NN.
MNMIN min(MM(j), NN(j)) (the dimension of the bidiagonal
matrix.)
MNMAX The maximum value of MNMIN for j=1,...,NSIZES.
NFAIL The number of tests which have exceeded THRESH
COND, IMODE Values to be passed to the matrix generators.
ANORM Norm of A; passed to matrix generators.
OVFL, UNFL Overflow and underflow thresholds.
RTOVFL, RTUNFL Square roots of the previous 2 values.
ULP, ULPINV Finest relative precision and its inverse.
The following four arrays decode JTYPE:
KTYPE(j) The general type (1-10) for type "j".
KMODE(j) The MODE value to be passed to the matrix
generator for type "j".
KMAGN(j) The order of magnitude ( O(1),
O(overflow^(1/2) ), O(underflow^(1/2) )
======================================================================
Parameter adjustments */
--mval;
--nval;
--dotype;
--iseed;
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
--bd;
--be;
--s1;
--s2;
z_dim1 = *ldx;
z_offset = 1 + z_dim1 * 1;
z__ -= z_offset;
y_dim1 = *ldx;
y_offset = 1 + y_dim1 * 1;
y -= y_offset;
x_dim1 = *ldx;
x_offset = 1 + x_dim1 * 1;
x -= x_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1 * 1;
q -= q_offset;
vt_dim1 = *ldpt;
vt_offset = 1 + vt_dim1 * 1;
vt -= vt_offset;
u_dim1 = *ldpt;
u_offset = 1 + u_dim1 * 1;
u -= u_offset;
pt_dim1 = *ldpt;
pt_offset = 1 + pt_dim1 * 1;
pt -= pt_offset;
--work;
--iwork;
/* Function Body
Check for errors */
*info = 0;
badmm = FALSE_;
badnn = FALSE_;
mmax = 1;
nmax = 1;
mnmax = 1;
minwrk = 1;
i__1 = *nsizes;
for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
i__2 = mmax, i__3 = mval[j];
mmax = max(i__2,i__3);
if (mval[j] < 0) {
badmm = TRUE_;
}
/* Computing MAX */
i__2 = nmax, i__3 = nval[j];
nmax = max(i__2,i__3);
if (nval[j] < 0) {
badnn = TRUE_;
}
/* Computing MAX
Computing MIN */
i__4 = mval[j], i__5 = nval[j];
i__2 = mnmax, i__3 = min(i__4,i__5);
mnmax = max(i__2,i__3);
/* Computing MAX
Computing MAX */
i__4 = mval[j], i__5 = nval[j], i__4 = max(i__4,i__5);
/* Computing MIN */
i__6 = nval[j], i__7 = mval[j];
i__2 = minwrk, i__3 = (mval[j] + nval[j]) * 3, i__2 = max(i__2,i__3),
i__3 = mval[j] * (mval[j] + max(i__4,*nrhs) + 1) + nval[j] *
min(i__6,i__7);
minwrk = max(i__2,i__3);
/* L10: */
}
/* Check for errors */
if (*nsizes < 0) {
*info = -1;
} else if (badmm) {
*info = -2;
} else if (badnn) {
*info = -3;
} else if (*ntypes < 0) {
*info = -4;
} else if (*nrhs < 0) {
*info = -6;
} else if (*lda < mmax) {
*info = -11;
} else if (*ldx < mmax) {
*info = -17;
} else if (*ldq < mmax) {
*info = -21;
} else if (*ldpt < mnmax) {
*info = -23;
} else if (minwrk > *lwork) {
*info = -27;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SCHKBD", &i__1);
return 0;
}
/* Initialize constants */
s_copy(path, "Single precision", (ftnlen)1, (ftnlen)16);
s_copy(path + 1, "BD", (ftnlen)2, (ftnlen)2);
nfail = 0;
ntest = 0;
unfl = slamch_("Safe minimum");
ovfl = slamch_("Overflow");
slabad_(&unfl, &ovfl);
ulp = slamch_("Precision");
ulpinv = 1.f / ulp;
log2ui = (integer) (log(ulpinv) / log(2.f));
rtunfl = sqrt(unfl);
rtovfl = sqrt(ovfl);
infoc_1.infot = 0;
/* Loop over sizes, types */
i__1 = *nsizes;
for (jsize = 1; jsize <= i__1; ++jsize) {
m = mval[jsize];
n = nval[jsize];
mnmin = min(m,n);
/* Computing MAX */
i__2 = max(m,n);
amninv = 1.f / max(i__2,1);
if (*nsizes != 1) {
mtypes = min(16,*ntypes);
} else {
mtypes = min(17,*ntypes);
}
i__2 = mtypes;
for (jtype = 1; jtype <= i__2; ++jtype) {
if (! dotype[jtype]) {
goto L190;
}
for (j = 1; j <= 4; ++j) {
ioldsd[j - 1] = iseed[j];
/* L20: */
}
for (j = 1; j <= 14; ++j) {
result[j - 1] = -1.f;
/* L30: */
}
*(unsigned char *)uplo = ' ';
/* Compute "A"
Control parameters:
KMAGN KMODE KTYPE
=1 O(1) clustered 1 zero
=2 large clustered 2 identity
=3 small exponential (none)
=4 arithmetic diagonal, (w/ eigenvalues)
=5 random symmetric, w/ eigenvalues
=6 nonsymmetric, w/ singular values
=7 random diagonal
=8 random symmetric
=9 random nonsymmetric
=10 random bidiagonal (log. distrib.) */
if (mtypes > 16) {
goto L100;
}
itype = ktype[jtype - 1];
imode = kmode[jtype - 1];
/* Compute norm */
switch (kmagn[jtype - 1]) {
case 1: goto L40;
case 2: goto L50;
case 3: goto L60;
}
L40:
anorm = 1.f;
goto L70;
L50:
anorm = rtovfl * ulp * amninv;
goto L70;
L60:
anorm = rtunfl * max(m,n) * ulpinv;
goto L70;
L70:
slaset_("Full", lda, &n, &c_b20, &c_b20, &a[a_offset], lda);
iinfo = 0;
cond = ulpinv;
bidiag = FALSE_;
if (itype == 1) {
/* Zero matrix */
iinfo = 0;
} else if (itype == 2) {
/* Identity */
i__3 = mnmin;
for (jcol = 1; jcol <= i__3; ++jcol) {
a_ref(jcol, jcol) = anorm;
/* L80: */
}
} else if (itype == 4) {
/* Diagonal Matrix, [Eigen]values Specified */
slatms_(&mnmin, &mnmin, "S", &iseed[1], "N", &work[1], &imode,
&cond, &anorm, &c__0, &c__0, "N", &a[a_offset], lda,
&work[mnmin + 1], &iinfo);
} else if (itype == 5) {
/* Symmetric, eigenvalues specified */
slatms_(&mnmin, &mnmin, "S", &iseed[1], "S", &work[1], &imode,
&cond, &anorm, &m, &n, "N", &a[a_offset], lda, &work[
mnmin + 1], &iinfo);
} else if (itype == 6) {
/* Nonsymmetric, singular values specified */
slatms_(&m, &n, "S", &iseed[1], "N", &work[1], &imode, &cond,
&anorm, &m, &n, "N", &a[a_offset], lda, &work[mnmin +
1], &iinfo);
} else if (itype == 7) {
/* Diagonal, random entries */
slatmr_(&mnmin, &mnmin, "S", &iseed[1], "N", &work[1], &c__6,
&c_b37, &c_b37, "T", "N", &work[mnmin + 1], &c__1, &
c_b37, &work[(mnmin << 1) + 1], &c__1, &c_b37, "N", &
iwork[1], &c__0, &c__0, &c_b20, &anorm, "NO", &a[
a_offset], lda, &iwork[1], &iinfo);
} else if (itype == 8) {
/* Symmetric, random entries */
slatmr_(&mnmin, &mnmin, "S", &iseed[1], "S", &work[1], &c__6,
&c_b37, &c_b37, "T", "N", &work[mnmin + 1], &c__1, &
c_b37, &work[m + mnmin + 1], &c__1, &c_b37, "N", &
iwork[1], &m, &n, &c_b20, &anorm, "NO", &a[a_offset],
lda, &iwork[1], &iinfo);
} else if (itype == 9) {
/* Nonsymmetric, random entries */
slatmr_(&m, &n, "S", &iseed[1], "N", &work[1], &c__6, &c_b37,
&c_b37, "T", "N", &work[mnmin + 1], &c__1, &c_b37, &
work[m + mnmin + 1], &c__1, &c_b37, "N", &iwork[1], &
m, &n, &c_b20, &anorm, "NO", &a[a_offset], lda, &
iwork[1], &iinfo);
} else if (itype == 10) {
/* Bidiagonal, random entries */
temp1 = log(ulp) * -2.f;
i__3 = mnmin;
for (j = 1; j <= i__3; ++j) {
bd[j] = exp(temp1 * slarnd_(&c__2, &iseed[1]));
if (j < mnmin) {
be[j] = exp(temp1 * slarnd_(&c__2, &iseed[1]));
}
/* L90: */
}
iinfo = 0;
bidiag = TRUE_;
if (m >= n) {
*(unsigned char *)uplo = 'U';
} else {
*(unsigned char *)uplo = 'L';
}
} else {
iinfo = 1;
}
if (iinfo == 0) {
/* Generate Right-Hand Side */
if (bidiag) {
slatmr_(&mnmin, nrhs, "S", &iseed[1], "N", &work[1], &
c__6, &c_b37, &c_b37, "T", "N", &work[mnmin + 1],
&c__1, &c_b37, &work[(mnmin << 1) + 1], &c__1, &
c_b37, "N", &iwork[1], &mnmin, nrhs, &c_b20, &
c_b37, "NO", &y[y_offset], ldx, &iwork[1], &iinfo);
} else {
slatmr_(&m, nrhs, "S", &iseed[1], "N", &work[1], &c__6, &
c_b37, &c_b37, "T", "N", &work[m + 1], &c__1, &
c_b37, &work[(m << 1) + 1], &c__1, &c_b37, "N", &
iwork[1], &m, nrhs, &c_b20, &c_b37, "NO", &x[
x_offset], ldx, &iwork[1], &iinfo);
}
}
/* Error Exit */
if (iinfo != 0) {
io___39.ciunit = *nout;
s_wsfe(&io___39);
do_fio(&c__1, "Generator", (ftnlen)9);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
return 0;
}
L100:
/* Call SGEBRD and SORGBR to compute B, Q, and P, do tests. */
if (! bidiag) {
/* Compute transformations to reduce A to bidiagonal form:
B := Q' * A * P. */
slacpy_(" ", &m, &n, &a[a_offset], lda, &q[q_offset], ldq);
i__3 = *lwork - (mnmin << 1);
sgebrd_(&m, &n, &q[q_offset], ldq, &bd[1], &be[1], &work[1], &
work[mnmin + 1], &work[(mnmin << 1) + 1], &i__3, &
iinfo);
/* Check error code from SGEBRD. */
if (iinfo != 0) {
io___40.ciunit = *nout;
s_wsfe(&io___40);
do_fio(&c__1, "SGEBRD", (ftnlen)6);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer))
;
e_wsfe();
*info = abs(iinfo);
return 0;
}
slacpy_(" ", &m, &n, &q[q_offset], ldq, &pt[pt_offset], ldpt);
if (m >= n) {
*(unsigned char *)uplo = 'U';
} else {
*(unsigned char *)uplo = 'L';
}
/* Generate Q */
mq = m;
if (*nrhs <= 0) {
mq = mnmin;
}
i__3 = *lwork - (mnmin << 1);
sorgbr_("Q", &m, &mq, &n, &q[q_offset], ldq, &work[1], &work[(
mnmin << 1) + 1], &i__3, &iinfo);
/* Check error code from SORGBR. */
if (iinfo != 0) {
io___42.ciunit = *nout;
s_wsfe(&io___42);
do_fio(&c__1, "SORGBR(Q)", (ftnlen)9);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer))
;
e_wsfe();
*info = abs(iinfo);
return 0;
}
/* Generate P' */
i__3 = *lwork - (mnmin << 1);
sorgbr_("P", &mnmin, &n, &m, &pt[pt_offset], ldpt, &work[
mnmin + 1], &work[(mnmin << 1) + 1], &i__3, &iinfo);
/* Check error code from SORGBR. */
if (iinfo != 0) {
io___43.ciunit = *nout;
s_wsfe(&io___43);
do_fio(&c__1, "SORGBR(P)", (ftnlen)9);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer))
;
e_wsfe();
*info = abs(iinfo);
return 0;
}
/* Apply Q' to an M by NRHS matrix X: Y := Q' * X. */
sgemm_("Transpose", "No transpose", &m, nrhs, &m, &c_b37, &q[
q_offset], ldq, &x[x_offset], ldx, &c_b20, &y[
y_offset], ldx);
/* Test 1: Check the decomposition A := Q * B * PT
2: Check the orthogonality of Q
3: Check the orthogonality of PT */
sbdt01_(&m, &n, &c__1, &a[a_offset], lda, &q[q_offset], ldq, &
bd[1], &be[1], &pt[pt_offset], ldpt, &work[1], result)
;
sort01_("Columns", &m, &mq, &q[q_offset], ldq, &work[1],
lwork, &result[1]);
sort01_("Rows", &mnmin, &n, &pt[pt_offset], ldpt, &work[1],
lwork, &result[2]);
}
/* Use SBDSQR to form the SVD of the bidiagonal matrix B:
B := U * S1 * VT, and compute Z = U' * Y. */
scopy_(&mnmin, &bd[1], &c__1, &s1[1], &c__1);
if (mnmin > 0) {
i__3 = mnmin - 1;
scopy_(&i__3, &be[1], &c__1, &work[1], &c__1);
}
slacpy_(" ", &m, nrhs, &y[y_offset], ldx, &z__[z_offset], ldx);
slaset_("Full", &mnmin, &mnmin, &c_b20, &c_b37, &u[u_offset],
ldpt);
slaset_("Full", &mnmin, &mnmin, &c_b20, &c_b37, &vt[vt_offset],
ldpt);
sbdsqr_(uplo, &mnmin, &mnmin, &mnmin, nrhs, &s1[1], &work[1], &vt[
vt_offset], ldpt, &u[u_offset], ldpt, &z__[z_offset], ldx,
&work[mnmin + 1], &iinfo);
/* Check error code from SBDSQR. */
if (iinfo != 0) {
io___44.ciunit = *nout;
s_wsfe(&io___44);
do_fio(&c__1, "SBDSQR(vects)", (ftnlen)13);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
if (iinfo < 0) {
return 0;
} else {
result[3] = ulpinv;
goto L170;
}
}
/* Use SBDSQR to compute only the singular values of the
bidiagonal matrix B; U, VT, and Z should not be modified. */
scopy_(&mnmin, &bd[1], &c__1, &s2[1], &c__1);
if (mnmin > 0) {
i__3 = mnmin - 1;
scopy_(&i__3, &be[1], &c__1, &work[1], &c__1);
}
sbdsqr_(uplo, &mnmin, &c__0, &c__0, &c__0, &s2[1], &work[1], &vt[
vt_offset], ldpt, &u[u_offset], ldpt, &z__[z_offset], ldx,
&work[mnmin + 1], &iinfo);
/* Check error code from SBDSQR. */
if (iinfo != 0) {
io___45.ciunit = *nout;
s_wsfe(&io___45);
do_fio(&c__1, "SBDSQR(values)", (ftnlen)14);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
if (iinfo < 0) {
return 0;
} else {
result[8] = ulpinv;
goto L170;
}
}
/* Test 4: Check the decomposition B := U * S1 * VT
5: Check the computation Z := U' * Y
6: Check the orthogonality of U
7: Check the orthogonality of VT */
sbdt03_(uplo, &mnmin, &c__1, &bd[1], &be[1], &u[u_offset], ldpt, &
s1[1], &vt[vt_offset], ldpt, &work[1], &result[3]);
sbdt02_(&mnmin, nrhs, &y[y_offset], ldx, &z__[z_offset], ldx, &u[
u_offset], ldpt, &work[1], &result[4]);
sort01_("Columns", &mnmin, &mnmin, &u[u_offset], ldpt, &work[1],
lwork, &result[5]);
sort01_("Rows", &mnmin, &mnmin, &vt[vt_offset], ldpt, &work[1],
lwork, &result[6]);
/* Test 8: Check that the singular values are sorted in
non-increasing order and are non-negative */
result[7] = 0.f;
i__3 = mnmin - 1;
for (i__ = 1; i__ <= i__3; ++i__) {
if (s1[i__] < s1[i__ + 1]) {
result[7] = ulpinv;
}
if (s1[i__] < 0.f) {
result[7] = ulpinv;
}
/* L110: */
}
if (mnmin >= 1) {
if (s1[mnmin] < 0.f) {
result[7] = ulpinv;
}
}
/* Test 9: Compare SBDSQR with and without singular vectors */
temp2 = 0.f;
i__3 = mnmin;
for (j = 1; j <= i__3; ++j) {
/* Computing MAX
Computing MAX */
r__6 = (r__1 = s1[j], dabs(r__1)), r__7 = (r__2 = s2[j], dabs(
r__2));
r__4 = sqrt(unfl) * dmax(s1[1],1.f), r__5 = ulp * dmax(r__6,
r__7);
temp1 = (r__3 = s1[j] - s2[j], dabs(r__3)) / dmax(r__4,r__5);
temp2 = dmax(temp1,temp2);
/* L120: */
}
result[8] = temp2;
/* Test 10: Sturm sequence test of singular values
Go up by factors of two until it succeeds */
temp1 = *thresh * (.5f - ulp);
i__3 = log2ui;
for (j = 0; j <= i__3; ++j) {
/* CALL SSVDCH( MNMIN, BD, BE, S1, TEMP1, IINFO ) */
if (iinfo == 0) {
goto L140;
}
temp1 *= 2.f;
/* L130: */
}
L140:
result[9] = temp1;
/* Use SBDSQR to form the decomposition A := (QU) S (VT PT)
from the bidiagonal form A := Q B PT. */
if (! bidiag) {
scopy_(&mnmin, &bd[1], &c__1, &s2[1], &c__1);
if (mnmin > 0) {
i__3 = mnmin - 1;
scopy_(&i__3, &be[1], &c__1, &work[1], &c__1);
}
sbdsqr_(uplo, &mnmin, &n, &m, nrhs, &s2[1], &work[1], &pt[
pt_offset], ldpt, &q[q_offset], ldq, &y[y_offset],
ldx, &work[mnmin + 1], &iinfo);
/* Test 11: Check the decomposition A := Q*U * S2 * VT*PT
12: Check the computation Z := U' * Q' * X
13: Check the orthogonality of Q*U
14: Check the orthogonality of VT*PT */
sbdt01_(&m, &n, &c__0, &a[a_offset], lda, &q[q_offset], ldq, &
s2[1], dumma, &pt[pt_offset], ldpt, &work[1], &result[
10]);
sbdt02_(&m, nrhs, &x[x_offset], ldx, &y[y_offset], ldx, &q[
q_offset], ldq, &work[1], &result[11]);
sort01_("Columns", &m, &mq, &q[q_offset], ldq, &work[1],
lwork, &result[12]);
sort01_("Rows", &mnmin, &n, &pt[pt_offset], ldpt, &work[1],
lwork, &result[13]);
}
/* Use SBDSDC to form the SVD of the bidiagonal matrix B:
B := U * S1 * VT */
scopy_(&mnmin, &bd[1], &c__1, &s1[1], &c__1);
if (mnmin > 0) {
i__3 = mnmin - 1;
scopy_(&i__3, &be[1], &c__1, &work[1], &c__1);
}
slaset_("Full", &mnmin, &mnmin, &c_b20, &c_b37, &u[u_offset],
ldpt);
slaset_("Full", &mnmin, &mnmin, &c_b20, &c_b37, &vt[vt_offset],
ldpt);
sbdsdc_(uplo, "I", &mnmin, &s1[1], &work[1], &u[u_offset], ldpt, &
vt[vt_offset], ldpt, dum, idum, &work[mnmin + 1], &iwork[
1], &iinfo);
/* Check error code from SBDSDC. */
if (iinfo != 0) {
io___51.ciunit = *nout;
s_wsfe(&io___51);
do_fio(&c__1, "SBDSDC(vects)", (ftnlen)13);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
if (iinfo < 0) {
return 0;
} else {
result[14] = ulpinv;
goto L170;
}
}
/* Use SBDSDC to compute only the singular values of the
bidiagonal matrix B; U and VT should not be modified. */
scopy_(&mnmin, &bd[1], &c__1, &s2[1], &c__1);
if (mnmin > 0) {
i__3 = mnmin - 1;
scopy_(&i__3, &be[1], &c__1, &work[1], &c__1);
}
sbdsdc_(uplo, "N", &mnmin, &s2[1], &work[1], dum, &c__1, dum, &
c__1, dum, idum, &work[mnmin + 1], &iwork[1], &iinfo);
/* Check error code from SBDSDC. */
if (iinfo != 0) {
io___52.ciunit = *nout;
s_wsfe(&io___52);
do_fio(&c__1, "SBDSDC(values)", (ftnlen)14);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
if (iinfo < 0) {
return 0;
} else {
result[17] = ulpinv;
goto L170;
}
}
/* Test 15: Check the decomposition B := U * S1 * VT
16: Check the orthogonality of U
17: Check the orthogonality of VT */
sbdt03_(uplo, &mnmin, &c__1, &bd[1], &be[1], &u[u_offset], ldpt, &
s1[1], &vt[vt_offset], ldpt, &work[1], &result[14]);
sort01_("Columns", &mnmin, &mnmin, &u[u_offset], ldpt, &work[1],
lwork, &result[15]);
sort01_("Rows", &mnmin, &mnmin, &vt[vt_offset], ldpt, &work[1],
lwork, &result[16]);
/* Test 18: Check that the singular values are sorted in
non-increasing order and are non-negative */
result[17] = 0.f;
i__3 = mnmin - 1;
for (i__ = 1; i__ <= i__3; ++i__) {
if (s1[i__] < s1[i__ + 1]) {
result[17] = ulpinv;
}
if (s1[i__] < 0.f) {
result[17] = ulpinv;
}
/* L150: */
}
if (mnmin >= 1) {
if (s1[mnmin] < 0.f) {
result[17] = ulpinv;
}
}
/* Test 19: Compare SBDSQR with and without singular vectors */
temp2 = 0.f;
i__3 = mnmin;
for (j = 1; j <= i__3; ++j) {
/* Computing MAX
Computing MAX */
r__4 = dabs(s1[1]), r__5 = dabs(s2[1]);
r__2 = sqrt(unfl) * dmax(s1[1],1.f), r__3 = ulp * dmax(r__4,
r__5);
temp1 = (r__1 = s1[j] - s2[j], dabs(r__1)) / dmax(r__2,r__3);
temp2 = dmax(temp1,temp2);
/* L160: */
}
result[18] = temp2;
/* End of Loop -- Check for RESULT(j) > THRESH */
L170:
for (j = 1; j <= 19; ++j) {
if (result[j - 1] >= *thresh) {
if (nfail == 0) {
slahd2_(nout, path);
}
io___53.ciunit = *nout;
s_wsfe(&io___53);
do_fio(&c__1, (char *)&m, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer))
;
do_fio(&c__1, (char *)&j, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&result[j - 1], (ftnlen)sizeof(real)
);
e_wsfe();
++nfail;
}
/* L180: */
}
if (! bidiag) {
ntest += 19;
} else {
ntest += 5;
}
L190:
;
}
/* L200: */
}
/* Summary */
alasum_(path, nout, &nfail, &ntest, &c__0);
return 0;
/* End of SCHKBD */
} /* schkbd_ */
int main( int argc, char** argv )
{
obj_t a, b, c;
obj_t c_save;
obj_t alpha, beta;
dim_t m, n, k;
dim_t p;
dim_t p_begin, p_end, p_inc;
int m_input, n_input, k_input;
num_t dt;
int r, n_repeats;
trans_t transa;
trans_t transb;
f77_char f77_transa;
f77_char f77_transb;
double dtime;
double dtime_save;
double gflops;
bli_init();
//bli_error_checking_level_set( BLIS_NO_ERROR_CHECKING );
n_repeats = 3;
#ifndef PRINT
p_begin = 200;
p_end = 2000;
p_inc = 200;
m_input = -1;
n_input = -1;
k_input = -1;
#else
p_begin = 16;
p_end = 16;
p_inc = 1;
m_input = 5;
k_input = 6;
n_input = 4;
#endif
#if 1
//dt = BLIS_FLOAT;
dt = BLIS_DOUBLE;
#else
//dt = BLIS_SCOMPLEX;
dt = BLIS_DCOMPLEX;
#endif
transa = BLIS_NO_TRANSPOSE;
transb = BLIS_NO_TRANSPOSE;
bli_param_map_blis_to_netlib_trans( transa, &f77_transa );
bli_param_map_blis_to_netlib_trans( transb, &f77_transb );
for ( p = p_begin; p <= p_end; p += p_inc )
{
if ( m_input < 0 ) m = p * ( dim_t )abs(m_input);
else m = ( dim_t ) m_input;
if ( n_input < 0 ) n = p * ( dim_t )abs(n_input);
else n = ( dim_t ) n_input;
if ( k_input < 0 ) k = p * ( dim_t )abs(k_input);
else k = ( dim_t ) k_input;
bli_obj_create( dt, 1, 1, 0, 0, &alpha );
bli_obj_create( dt, 1, 1, 0, 0, &beta );
bli_obj_create( dt, m, k, 0, 0, &a );
bli_obj_create( dt, k, n, 0, 0, &b );
bli_obj_create( dt, m, n, 0, 0, &c );
bli_obj_create( dt, m, n, 0, 0, &c_save );
bli_randm( &a );
bli_randm( &b );
bli_randm( &c );
bli_obj_set_conjtrans( transa, a );
bli_obj_set_conjtrans( transb, b );
bli_setsc( (0.9/1.0), 0.2, &alpha );
bli_setsc( -(1.1/1.0), 0.3, &beta );
bli_copym( &c, &c_save );
dtime_save = DBL_MAX;
for ( r = 0; r < n_repeats; ++r )
{
bli_copym( &c_save, &c );
dtime = bli_clock();
#ifdef PRINT
bli_printm( "a", &a, "%4.1f", "" );
bli_printm( "b", &b, "%4.1f", "" );
bli_printm( "c", &c, "%4.1f", "" );
#endif
#ifdef BLIS
bli_gemm( &alpha,
&a,
&b,
&beta,
&c );
#else
if ( bli_is_float( dt ) )
{
f77_int mm = bli_obj_length( c );
f77_int kk = bli_obj_width_after_trans( a );
f77_int nn = bli_obj_width( c );
f77_int lda = bli_obj_col_stride( a );
f77_int ldb = bli_obj_col_stride( b );
f77_int ldc = bli_obj_col_stride( c );
float* alphap = bli_obj_buffer( alpha );
float* ap = bli_obj_buffer( a );
float* bp = bli_obj_buffer( b );
float* betap = bli_obj_buffer( beta );
float* cp = bli_obj_buffer( c );
sgemm_( &f77_transa,
&f77_transb,
&mm,
&nn,
&kk,
alphap,
ap, &lda,
bp, &ldb,
betap,
cp, &ldc );
}
else if ( bli_is_double( dt ) )
{
f77_int mm = bli_obj_length( c );
f77_int kk = bli_obj_width_after_trans( a );
f77_int nn = bli_obj_width( c );
f77_int lda = bli_obj_col_stride( a );
f77_int ldb = bli_obj_col_stride( b );
f77_int ldc = bli_obj_col_stride( c );
double* alphap = bli_obj_buffer( alpha );
double* ap = bli_obj_buffer( a );
double* bp = bli_obj_buffer( b );
double* betap = bli_obj_buffer( beta );
double* cp = bli_obj_buffer( c );
dgemm_( &f77_transa,
&f77_transb,
&mm,
&nn,
&kk,
alphap,
ap, &lda,
bp, &ldb,
betap,
cp, &ldc );
}
else if ( bli_is_scomplex( dt ) )
{
f77_int mm = bli_obj_length( c );
f77_int kk = bli_obj_width_after_trans( a );
f77_int nn = bli_obj_width( c );
f77_int lda = bli_obj_col_stride( a );
f77_int ldb = bli_obj_col_stride( b );
f77_int ldc = bli_obj_col_stride( c );
scomplex* alphap = bli_obj_buffer( alpha );
scomplex* ap = bli_obj_buffer( a );
scomplex* bp = bli_obj_buffer( b );
scomplex* betap = bli_obj_buffer( beta );
scomplex* cp = bli_obj_buffer( c );
cgemm_( &f77_transa,
&f77_transb,
&mm,
&nn,
&kk,
alphap,
ap, &lda,
bp, &ldb,
betap,
cp, &ldc );
}
else if ( bli_is_dcomplex( dt ) )
{
f77_int mm = bli_obj_length( c );
f77_int kk = bli_obj_width_after_trans( a );
f77_int nn = bli_obj_width( c );
f77_int lda = bli_obj_col_stride( a );
f77_int ldb = bli_obj_col_stride( b );
f77_int ldc = bli_obj_col_stride( c );
dcomplex* alphap = bli_obj_buffer( alpha );
dcomplex* ap = bli_obj_buffer( a );
dcomplex* bp = bli_obj_buffer( b );
dcomplex* betap = bli_obj_buffer( beta );
dcomplex* cp = bli_obj_buffer( c );
zgemm_( &f77_transa,
&f77_transb,
&mm,
&nn,
&kk,
alphap,
ap, &lda,
bp, &ldb,
betap,
cp, &ldc );
}
#endif
#ifdef PRINT
bli_printm( "c after", &c, "%4.1f", "" );
exit(1);
#endif
dtime_save = bli_clock_min_diff( dtime_save, dtime );
}
gflops = ( 2.0 * m * k * n ) / ( dtime_save * 1.0e9 );
if ( bli_is_complex( dt ) ) gflops *= 4.0;
#ifdef BLIS
printf( "data_gemm_blis" );
#else
printf( "data_gemm_%s", BLAS );
#endif
printf( "( %2lu, 1:5 ) = [ %4lu %4lu %4lu %10.3e %6.3f ];\n",
( unsigned long )(p - p_begin + 1)/p_inc + 1,
( unsigned long )m,
( unsigned long )k,
( unsigned long )n, dtime_save, gflops );
bli_obj_free( &alpha );
bli_obj_free( &beta );
bli_obj_free( &a );
bli_obj_free( &b );
bli_obj_free( &c );
bli_obj_free( &c_save );
}
bli_finalize();
return 0;
}
/* Subroutine */ int slalsd_(char *uplo, integer *smlsiz, integer *n, integer
*nrhs, real *d__, real *e, real *b, integer *ldb, real *rcond,
integer *rank, real *work, integer *iwork, integer *info)
{
/* System generated locals */
integer b_dim1, b_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double log(doublereal), r_sign(real *, real *);
/* Local variables */
integer c__, i__, j, k;
real r__;
integer s, u, z__;
real cs;
integer bx;
real sn;
integer st, vt, nm1, st1;
real eps;
integer iwk;
real tol;
integer difl, difr;
real rcnd;
integer perm, nsub, nlvl, sqre, bxst;
extern /* Subroutine */ int srot_(integer *, real *, integer *, real *,
integer *, real *, real *), sgemm_(char *, char *, integer *,
integer *, integer *, real *, real *, integer *, real *, integer *
, real *, real *, integer *);
integer poles, sizei, nsize;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
integer nwork, icmpq1, icmpq2;
extern doublereal slamch_(char *);
extern /* Subroutine */ int slasda_(integer *, integer *, integer *,
integer *, real *, real *, real *, integer *, real *, integer *,
real *, real *, real *, real *, integer *, integer *, integer *,
integer *, real *, real *, real *, real *, integer *, integer *),
xerbla_(char *, integer *), slalsa_(integer *, integer *,
integer *, integer *, real *, integer *, real *, integer *, real *
, integer *, real *, integer *, real *, real *, real *, real *,
integer *, integer *, integer *, integer *, real *, real *, real *
, real *, integer *, integer *), slascl_(char *, integer *,
integer *, real *, real *, integer *, integer *, real *, integer *
, integer *);
integer givcol;
extern integer isamax_(integer *, real *, integer *);
extern /* Subroutine */ int slasdq_(char *, integer *, integer *, integer
*, integer *, integer *, real *, real *, real *, integer *, real *
, integer *, real *, integer *, real *, integer *),
slacpy_(char *, integer *, integer *, real *, integer *, real *,
integer *), slartg_(real *, real *, real *, real *, real *
), slaset_(char *, integer *, integer *, real *, real *, real *,
integer *);
real orgnrm;
integer givnum;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *);
integer givptr, smlszp;
/* -- LAPACK routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SLALSD uses the singular value decomposition of A to solve the least */
/* squares problem of finding X to minimize the Euclidean norm of each */
/* column of A*X-B, where A is N-by-N upper bidiagonal, and X and B */
/* are N-by-NRHS. The solution X overwrites B. */
/* The singular values of A smaller than RCOND times the largest */
/* singular value are treated as zero in solving the least squares */
/* problem; in this case a minimum norm solution is returned. */
/* The actual singular values are returned in D in ascending order. */
/* This code makes very mild assumptions about floating point */
/* arithmetic. It will work on machines with a guard digit in */
/* add/subtract, or on those binary machines without guard digits */
/* which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2. */
/* It could conceivably fail on hexadecimal or decimal machines */
/* without guard digits, but we know of none. */
/* Arguments */
/* ========= */
/* UPLO (input) CHARACTER*1 */
/* = 'U': D and E define an upper bidiagonal matrix. */
/* = 'L': D and E define a lower bidiagonal matrix. */
/* SMLSIZ (input) INTEGER */
/* The maximum size of the subproblems at the bottom of the */
/* computation tree. */
/* N (input) INTEGER */
/* The dimension of the bidiagonal matrix. N >= 0. */
/* NRHS (input) INTEGER */
/* The number of columns of B. NRHS must be at least 1. */
/* D (input/output) REAL array, dimension (N) */
/* On entry D contains the main diagonal of the bidiagonal */
/* matrix. On exit, if INFO = 0, D contains its singular values. */
/* E (input/output) REAL array, dimension (N-1) */
/* Contains the super-diagonal entries of the bidiagonal matrix. */
/* On exit, E has been destroyed. */
/* B (input/output) REAL array, dimension (LDB,NRHS) */
/* On input, B contains the right hand sides of the least */
/* squares problem. On output, B contains the solution X. */
/* LDB (input) INTEGER */
/* The leading dimension of B in the calling subprogram. */
/* LDB must be at least max(1,N). */
/* RCOND (input) REAL */
/* The singular values of A less than or equal to RCOND times */
/* the largest singular value are treated as zero in solving */
/* the least squares problem. If RCOND is negative, */
/* machine precision is used instead. */
/* For example, if diag(S)*X=B were the least squares problem, */
/* where diag(S) is a diagonal matrix of singular values, the */
/* solution would be X(i) = B(i) / S(i) if S(i) is greater than */
/* RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to */
/* RCOND*max(S). */
/* RANK (output) INTEGER */
/* The number of singular values of A greater than RCOND times */
/* the largest singular value. */
/* WORK (workspace) REAL array, dimension at least */
/* (9*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2), */
/* where NLVL = max(0, INT(log_2 (N/(SMLSIZ+1))) + 1). */
/* IWORK (workspace) INTEGER array, dimension at least */
/* (3*N*NLVL + 11*N) */
/* INFO (output) INTEGER */
/* = 0: successful exit. */
/* < 0: if INFO = -i, the i-th argument had an illegal value. */
/* > 0: The algorithm failed to compute an singular value while */
/* working on the submatrix lying in rows and columns */
/* INFO/(N+1) through MOD(INFO,N+1). */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Ming Gu and Ren-Cang Li, Computer Science Division, University of */
/* California at Berkeley, USA */
/* Osni Marques, LBNL/NERSC, USA */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -3;
} else if (*nrhs < 1) {
*info = -4;
} else if (*ldb < 1 || *ldb < *n) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SLALSD", &i__1);
return 0;
}
eps = slamch_("Epsilon");
/* Set up the tolerance. */
if (*rcond <= 0.f || *rcond >= 1.f) {
rcnd = eps;
} else {
rcnd = *rcond;
}
*rank = 0;
/* Quick return if possible. */
if (*n == 0) {
return 0;
} else if (*n == 1) {
if (d__[1] == 0.f) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &b[b_offset], ldb);
} else {
*rank = 1;
slascl_("G", &c__0, &c__0, &d__[1], &c_b11, &c__1, nrhs, &b[
b_offset], ldb, info);
d__[1] = dabs(d__[1]);
}
return 0;
}
/* Rotate the matrix if it is lower bidiagonal. */
if (*(unsigned char *)uplo == 'L') {
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
slartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
d__[i__] = r__;
e[i__] = sn * d__[i__ + 1];
d__[i__ + 1] = cs * d__[i__ + 1];
if (*nrhs == 1) {
srot_(&c__1, &b[i__ + b_dim1], &c__1, &b[i__ + 1 + b_dim1], &
c__1, &cs, &sn);
} else {
work[(i__ << 1) - 1] = cs;
work[i__ * 2] = sn;
}
/* L10: */
}
if (*nrhs > 1) {
i__1 = *nrhs;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *n - 1;
for (j = 1; j <= i__2; ++j) {
cs = work[(j << 1) - 1];
sn = work[j * 2];
srot_(&c__1, &b[j + i__ * b_dim1], &c__1, &b[j + 1 + i__ *
b_dim1], &c__1, &cs, &sn);
/* L20: */
}
/* L30: */
}
}
}
/* Scale. */
nm1 = *n - 1;
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
slaset_("A", n, nrhs, &c_b6, &c_b6, &b[b_offset], ldb);
return 0;
}
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, &c__1, &d__[1], n, info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, &nm1, &c__1, &e[1], &nm1,
info);
/* If N is smaller than the minimum divide size SMLSIZ, then solve */
/* the problem with another solver. */
if (*n <= *smlsiz) {
nwork = *n * *n + 1;
slaset_("A", n, n, &c_b6, &c_b11, &work[1], n);
slasdq_("U", &c__0, n, n, &c__0, nrhs, &d__[1], &e[1], &work[1], n, &
work[1], n, &b[b_offset], ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
tol = rcnd * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (d__[i__] <= tol) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &b[i__ + b_dim1], ldb);
} else {
slascl_("G", &c__0, &c__0, &d__[i__], &c_b11, &c__1, nrhs, &b[
i__ + b_dim1], ldb, info);
++(*rank);
}
/* L40: */
}
sgemm_("T", "N", n, nrhs, n, &c_b11, &work[1], n, &b[b_offset], ldb, &
c_b6, &work[nwork], n);
slacpy_("A", n, nrhs, &work[nwork], n, &b[b_offset], ldb);
/* Unscale. */
slascl_("G", &c__0, &c__0, &c_b11, &orgnrm, n, &c__1, &d__[1], n,
info);
slasrt_("D", n, &d__[1], info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, nrhs, &b[b_offset],
ldb, info);
return 0;
}
/* Book-keeping and setting up some constants. */
nlvl = (integer) (log((real) (*n) / (real) (*smlsiz + 1)) / log(2.f)) + 1;
smlszp = *smlsiz + 1;
u = 1;
vt = *smlsiz * *n + 1;
difl = vt + smlszp * *n;
difr = difl + nlvl * *n;
z__ = difr + (nlvl * *n << 1);
c__ = z__ + nlvl * *n;
s = c__ + *n;
poles = s + *n;
givnum = poles + (nlvl << 1) * *n;
bx = givnum + (nlvl << 1) * *n;
nwork = bx + *n * *nrhs;
sizei = *n + 1;
k = sizei + *n;
givptr = k + *n;
perm = givptr + *n;
givcol = perm + nlvl * *n;
iwk = givcol + (nlvl * *n << 1);
st = 1;
sqre = 0;
icmpq1 = 1;
icmpq2 = 0;
nsub = 0;
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = d__[i__], dabs(r__1)) < eps) {
d__[i__] = r_sign(&eps, &d__[i__]);
}
/* L50: */
}
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = e[i__], dabs(r__1)) < eps || i__ == nm1) {
++nsub;
iwork[nsub] = st;
/* Subproblem found. First determine its size and then */
/* apply divide and conquer on it. */
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else if ((r__1 = e[i__], dabs(r__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else {
/* A subproblem with E(NM1) small. This implies an */
/* 1-by-1 subproblem at D(N), which is not solved */
/* explicitly. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
++nsub;
iwork[nsub] = *n;
iwork[sizei + nsub - 1] = 1;
scopy_(nrhs, &b[*n + b_dim1], ldb, &work[bx + nm1], n);
}
st1 = st - 1;
if (nsize == 1) {
/* This is a 1-by-1 subproblem and is not solved */
/* explicitly. */
scopy_(nrhs, &b[st + b_dim1], ldb, &work[bx + st1], n);
} else if (nsize <= *smlsiz) {
/* This is a small subproblem and is solved by SLASDQ. */
slaset_("A", &nsize, &nsize, &c_b6, &c_b11, &work[vt + st1],
n);
slasdq_("U", &c__0, &nsize, &nsize, &c__0, nrhs, &d__[st], &e[
st], &work[vt + st1], n, &work[nwork], n, &b[st +
b_dim1], ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
slacpy_("A", &nsize, nrhs, &b[st + b_dim1], ldb, &work[bx +
st1], n);
} else {
/* A large problem. Solve it using divide and conquer. */
slasda_(&icmpq1, smlsiz, &nsize, &sqre, &d__[st], &e[st], &
work[u + st1], n, &work[vt + st1], &iwork[k + st1], &
work[difl + st1], &work[difr + st1], &work[z__ + st1],
&work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum +
st1], &work[c__ + st1], &work[s + st1], &work[nwork],
&iwork[iwk], info);
if (*info != 0) {
return 0;
}
bxst = bx + st1;
slalsa_(&icmpq2, smlsiz, &nsize, nrhs, &b[st + b_dim1], ldb, &
work[bxst], n, &work[u + st1], n, &work[vt + st1], &
iwork[k + st1], &work[difl + st1], &work[difr + st1],
&work[z__ + st1], &work[poles + st1], &iwork[givptr +
st1], &iwork[givcol + st1], n, &iwork[perm + st1], &
work[givnum + st1], &work[c__ + st1], &work[s + st1],
&work[nwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
}
st = i__ + 1;
}
/* L60: */
}
/* Apply the singular values and treat the tiny ones as zero. */
tol = rcnd * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Some of the elements in D can be negative because 1-by-1 */
/* subproblems were not solved explicitly. */
if ((r__1 = d__[i__], dabs(r__1)) <= tol) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &work[bx + i__ - 1], n);
} else {
++(*rank);
slascl_("G", &c__0, &c__0, &d__[i__], &c_b11, &c__1, nrhs, &work[
bx + i__ - 1], n, info);
}
d__[i__] = (r__1 = d__[i__], dabs(r__1));
/* L70: */
}
/* Now apply back the right singular vectors. */
icmpq2 = 1;
i__1 = nsub;
for (i__ = 1; i__ <= i__1; ++i__) {
st = iwork[i__];
st1 = st - 1;
nsize = iwork[sizei + i__ - 1];
bxst = bx + st1;
if (nsize == 1) {
scopy_(nrhs, &work[bxst], n, &b[st + b_dim1], ldb);
} else if (nsize <= *smlsiz) {
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b11, &work[vt + st1], n,
&work[bxst], n, &c_b6, &b[st + b_dim1], ldb);
} else {
slalsa_(&icmpq2, smlsiz, &nsize, nrhs, &work[bxst], n, &b[st +
b_dim1], ldb, &work[u + st1], n, &work[vt + st1], &iwork[
k + st1], &work[difl + st1], &work[difr + st1], &work[z__
+ st1], &work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum + st1],
&work[c__ + st1], &work[s + st1], &work[nwork], &iwork[
iwk], info);
if (*info != 0) {
return 0;
}
}
/* L80: */
}
/* Unscale and sort the singular values. */
slascl_("G", &c__0, &c__0, &c_b11, &orgnrm, n, &c__1, &d__[1], n, info);
slasrt_("D", n, &d__[1], info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, nrhs, &b[b_offset], ldb,
info);
return 0;
/* End of SLALSD */
} /* slalsd_ */
/* Subroutine */ int sstt22_(integer *n, integer *m, integer *kband, real *ad,
real *ae, real *sd, real *se, real *u, integer *ldu, real *work,
integer *ldwork, real *result)
{
/* System generated locals */
integer u_dim1, u_offset, work_dim1, work_offset, i__1, i__2, i__3;
real r__1, r__2, r__3, r__4, r__5;
/* Local variables */
integer i__, j, k;
real ulp, aukj, unfl;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
real anorm, wnorm;
extern doublereal slamch_(char *), slange_(char *, integer *,
integer *, real *, integer *, real *), slansy_(char *,
char *, integer *, real *, integer *, real *);
/* -- LAPACK test routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTT22 checks a set of M eigenvalues and eigenvectors, */
/* A U = U S */
/* where A is symmetric tridiagonal, the columns of U are orthogonal, */
/* and S is diagonal (if KBAND=0) or symmetric tridiagonal (if KBAND=1). */
/* Two tests are performed: */
/* RESULT(1) = | U' A U - S | / ( |A| m ulp ) */
/* RESULT(2) = | I - U'U | / ( m ulp ) */
/* Arguments */
/* ========= */
/* N (input) INTEGER */
/* The size of the matrix. If it is zero, SSTT22 does nothing. */
/* It must be at least zero. */
/* M (input) INTEGER */
/* The number of eigenpairs to check. If it is zero, SSTT22 */
/* does nothing. It must be at least zero. */
/* KBAND (input) INTEGER */
/* The bandwidth of the matrix S. It may only be zero or one. */
/* If zero, then S is diagonal, and SE is not referenced. If */
/* one, then S is symmetric tri-diagonal. */
/* AD (input) REAL array, dimension (N) */
/* The diagonal of the original (unfactored) matrix A. A is */
/* assumed to be symmetric tridiagonal. */
/* AE (input) REAL array, dimension (N) */
/* The off-diagonal of the original (unfactored) matrix A. A */
/* is assumed to be symmetric tridiagonal. AE(1) is ignored, */
/* AE(2) is the (1,2) and (2,1) element, etc. */
/* SD (input) REAL array, dimension (N) */
/* The diagonal of the (symmetric tri-) diagonal matrix S. */
/* SE (input) REAL array, dimension (N) */
/* The off-diagonal of the (symmetric tri-) diagonal matrix S. */
/* Not referenced if KBSND=0. If KBAND=1, then AE(1) is */
/* ignored, SE(2) is the (1,2) and (2,1) element, etc. */
/* U (input) REAL array, dimension (LDU, N) */
/* The orthogonal matrix in the decomposition. */
/* LDU (input) INTEGER */
/* The leading dimension of U. LDU must be at least N. */
/* WORK (workspace) REAL array, dimension (LDWORK, M+1) */
/* LDWORK (input) INTEGER */
/* The leading dimension of WORK. LDWORK must be at least */
/* max(1,M). */
/* RESULT (output) REAL array, dimension (2) */
/* The values computed by the two tests described above. The */
/* values are currently limited to 1/ulp, to avoid overflow. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Parameter adjustments */
--ad;
--ae;
--sd;
--se;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
work_dim1 = *ldwork;
work_offset = 1 + work_dim1;
work -= work_offset;
--result;
/* Function Body */
result[1] = 0.f;
result[2] = 0.f;
if (*n <= 0 || *m <= 0) {
return 0;
}
unfl = slamch_("Safe minimum");
ulp = slamch_("Epsilon");
/* Do Test 1 */
/* Compute the 1-norm of A. */
if (*n > 1) {
anorm = dabs(ad[1]) + dabs(ae[1]);
i__1 = *n - 1;
for (j = 2; j <= i__1; ++j) {
/* Computing MAX */
r__4 = anorm, r__5 = (r__1 = ad[j], dabs(r__1)) + (r__2 = ae[j],
dabs(r__2)) + (r__3 = ae[j - 1], dabs(r__3));
anorm = dmax(r__4,r__5);
/* L10: */
}
/* Computing MAX */
r__3 = anorm, r__4 = (r__1 = ad[*n], dabs(r__1)) + (r__2 = ae[*n - 1],
dabs(r__2));
anorm = dmax(r__3,r__4);
} else {
anorm = dabs(ad[1]);
}
anorm = dmax(anorm,unfl);
/* Norm of U'AU - S */
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *m;
for (j = 1; j <= i__2; ++j) {
work[i__ + j * work_dim1] = 0.f;
i__3 = *n;
for (k = 1; k <= i__3; ++k) {
aukj = ad[k] * u[k + j * u_dim1];
if (k != *n) {
aukj += ae[k] * u[k + 1 + j * u_dim1];
}
if (k != 1) {
aukj += ae[k - 1] * u[k - 1 + j * u_dim1];
}
work[i__ + j * work_dim1] += u[k + i__ * u_dim1] * aukj;
/* L20: */
}
/* L30: */
}
work[i__ + i__ * work_dim1] -= sd[i__];
if (*kband == 1) {
if (i__ != 1) {
work[i__ + (i__ - 1) * work_dim1] -= se[i__ - 1];
}
if (i__ != *n) {
work[i__ + (i__ + 1) * work_dim1] -= se[i__];
}
}
/* L40: */
}
wnorm = slansy_("1", "L", m, &work[work_offset], m, &work[(*m + 1) *
work_dim1 + 1]);
if (anorm > wnorm) {
result[1] = wnorm / anorm / (*m * ulp);
} else {
if (anorm < 1.f) {
/* Computing MIN */
r__1 = wnorm, r__2 = *m * anorm;
result[1] = dmin(r__1,r__2) / anorm / (*m * ulp);
} else {
/* Computing MIN */
r__1 = wnorm / anorm, r__2 = (real) (*m);
result[1] = dmin(r__1,r__2) / (*m * ulp);
}
}
/* Do Test 2 */
/* Compute U'U - I */
sgemm_("T", "N", m, m, n, &c_b12, &u[u_offset], ldu, &u[u_offset], ldu, &
c_b13, &work[work_offset], m);
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
work[j + j * work_dim1] += -1.f;
/* L50: */
}
/* Computing MIN */
r__1 = (real) (*m), r__2 = slange_("1", m, m, &work[work_offset], m, &
work[(*m + 1) * work_dim1 + 1]);
result[2] = dmin(r__1,r__2) / (*m * ulp);
return 0;
/* End of SSTT22 */
} /* sstt22_ */
/* Subroutine */ int slaed0_(integer *icompq, integer *qsiz, integer *n, real
*d__, real *e, real *q, integer *ldq, real *qstore, integer *ldqs,
real *work, integer *iwork, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, qstore_dim1, qstore_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double log(doublereal);
integer pow_ii(integer *, integer *);
/* Local variables */
static real temp;
static integer curr, i__, j, k;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static integer iperm, indxq, iwrem;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
static integer iqptr, tlvls;
extern /* Subroutine */ int slaed1_(integer *, real *, real *, integer *,
integer *, real *, integer *, real *, integer *, integer *),
slaed7_(integer *, integer *, integer *, integer *, integer *,
integer *, real *, real *, integer *, integer *, real *, integer *
, real *, integer *, integer *, integer *, integer *, integer *,
real *, real *, integer *, integer *);
static integer iq, igivcl;
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *);
static integer igivnm, submat;
extern /* Subroutine */ int slacpy_(char *, integer *, integer *, real *,
integer *, real *, integer *);
static integer curprb, subpbs, igivpt, curlvl, matsiz, iprmpt, smlsiz;
extern /* Subroutine */ int ssteqr_(char *, integer *, real *, real *,
real *, integer *, real *, integer *);
static integer lgn, msd2, smm1, spm1, spm2;
#define q_ref(a_1,a_2) q[(a_2)*q_dim1 + a_1]
#define qstore_ref(a_1,a_2) qstore[(a_2)*qstore_dim1 + a_1]
/* -- LAPACK routine (instrumented to count operations, version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Common block to return operation count and iteration count
ITCNT is unchanged, OPS is only incremented
Purpose
=======
SLAED0 computes all eigenvalues and corresponding eigenvectors of a
symmetric tridiagonal matrix using the divide and conquer method.
Arguments
=========
ICOMPQ (input) INTEGER
= 0: Compute eigenvalues only.
= 1: Compute eigenvectors of original dense symmetric matrix
also. On entry, Q contains the orthogonal matrix used
to reduce the original matrix to tridiagonal form.
= 2: Compute eigenvalues and eigenvectors of tridiagonal
matrix.
QSIZ (input) INTEGER
The dimension of the orthogonal matrix used to reduce
the full matrix to tridiagonal form. QSIZ >= N if ICOMPQ = 1.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
D (input/output) REAL array, dimension (N)
On entry, the main diagonal of the tridiagonal matrix.
On exit, its eigenvalues.
E (input) REAL array, dimension (N-1)
The off-diagonal elements of the tridiagonal matrix.
On exit, E has been destroyed.
Q (input/output) REAL array, dimension (LDQ, N)
On entry, Q must contain an N-by-N orthogonal matrix.
If ICOMPQ = 0 Q is not referenced.
If ICOMPQ = 1 On entry, Q is a subset of the columns of the
orthogonal matrix used to reduce the full
matrix to tridiagonal form corresponding to
the subset of the full matrix which is being
decomposed at this time.
If ICOMPQ = 2 On entry, Q will be the identity matrix.
On exit, Q contains the eigenvectors of the
tridiagonal matrix.
LDQ (input) INTEGER
The leading dimension of the array Q. If eigenvectors are
desired, then LDQ >= max(1,N). In any case, LDQ >= 1.
QSTORE (workspace) REAL array, dimension (LDQS, N)
Referenced only when ICOMPQ = 1. Used to store parts of
the eigenvector matrix when the updating matrix multiplies
take place.
LDQS (input) INTEGER
The leading dimension of the array QSTORE. If ICOMPQ = 1,
then LDQS >= max(1,N). In any case, LDQS >= 1.
WORK (workspace) REAL array,
If ICOMPQ = 0 or 1, the dimension of WORK must be at least
1 + 3*N + 2*N*lg N + 2*N**2
( lg( N ) = smallest integer k
such that 2^k >= N )
If ICOMPQ = 2, the dimension of WORK must be at least
4*N + N**2.
IWORK (workspace) INTEGER array,
If ICOMPQ = 0 or 1, the dimension of IWORK must be at least
6 + 6*N + 5*N*lg N.
( lg( N ) = smallest integer k
such that 2^k >= N )
If ICOMPQ = 2, the dimension of IWORK must be at least
3 + 5*N.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an eigenvalue while
working on the submatrix lying in rows and columns
INFO/(N+1) through mod(INFO,N+1).
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
Parameter adjustments */
--d__;
--e;
q_dim1 = *ldq;
q_offset = 1 + q_dim1 * 1;
q -= q_offset;
qstore_dim1 = *ldqs;
qstore_offset = 1 + qstore_dim1 * 1;
qstore -= qstore_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 2) {
*info = -1;
} else if (*icompq == 1 && *qsiz < max(0,*n)) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ldq < max(1,*n)) {
*info = -7;
} else if (*ldqs < max(1,*n)) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SLAED0", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
smlsiz = ilaenv_(&c__9, "SLAED0", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
/* Determine the size and placement of the submatrices, and save in
the leading elements of IWORK. */
iwork[1] = *n;
subpbs = 1;
tlvls = 0;
L10:
if (iwork[subpbs] > smlsiz) {
for (j = subpbs; j >= 1; --j) {
iwork[j * 2] = (iwork[j] + 1) / 2;
iwork[(j << 1) - 1] = iwork[j] / 2;
/* L20: */
}
++tlvls;
subpbs <<= 1;
goto L10;
}
i__1 = subpbs;
for (j = 2; j <= i__1; ++j) {
iwork[j] += iwork[j - 1];
/* L30: */
}
/* Divide the matrix into SUBPBS submatrices of size at most SMLSIZ+1
using rank-1 modifications (cuts). */
spm1 = subpbs - 1;
latime_1.ops += spm1 << 1;
i__1 = spm1;
for (i__ = 1; i__ <= i__1; ++i__) {
submat = iwork[i__] + 1;
smm1 = submat - 1;
d__[smm1] -= (r__1 = e[smm1], dabs(r__1));
d__[submat] -= (r__1 = e[smm1], dabs(r__1));
/* L40: */
}
indxq = (*n << 2) + 3;
if (*icompq != 2) {
/* Set up workspaces for eigenvalues only/accumulate new vectors
routine */
latime_1.ops += 3;
temp = log((real) (*n)) / log(2.f);
lgn = (integer) temp;
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
iprmpt = indxq + *n + 1;
iperm = iprmpt + *n * lgn;
iqptr = iperm + *n * lgn;
igivpt = iqptr + *n + 2;
igivcl = igivpt + *n * lgn;
igivnm = 1;
iq = igivnm + (*n << 1) * lgn;
/* Computing 2nd power */
i__1 = *n;
iwrem = iq + i__1 * i__1 + 1;
/* Initialize pointers */
i__1 = subpbs;
for (i__ = 0; i__ <= i__1; ++i__) {
iwork[iprmpt + i__] = 1;
iwork[igivpt + i__] = 1;
/* L50: */
}
iwork[iqptr] = 1;
}
/* Solve each submatrix eigenproblem at the bottom of the divide and
conquer tree. */
curr = 0;
i__1 = spm1;
for (i__ = 0; i__ <= i__1; ++i__) {
if (i__ == 0) {
submat = 1;
matsiz = iwork[1];
} else {
submat = iwork[i__] + 1;
matsiz = iwork[i__ + 1] - iwork[i__];
}
if (*icompq == 2) {
ssteqr_("I", &matsiz, &d__[submat], &e[submat], &q_ref(submat,
submat), ldq, &work[1], info);
if (*info != 0) {
goto L130;
}
} else {
ssteqr_("I", &matsiz, &d__[submat], &e[submat], &work[iq - 1 +
iwork[iqptr + curr]], &matsiz, &work[1], info);
if (*info != 0) {
goto L130;
}
if (*icompq == 1) {
latime_1.ops += (real) (*qsiz) * 2 * matsiz * matsiz;
sgemm_("N", "N", qsiz, &matsiz, &matsiz, &c_b23, &q_ref(1,
submat), ldq, &work[iq - 1 + iwork[iqptr + curr]], &
matsiz, &c_b24, &qstore_ref(1, submat), ldqs);
}
/* Computing 2nd power */
i__2 = matsiz;
iwork[iqptr + curr + 1] = iwork[iqptr + curr] + i__2 * i__2;
++curr;
}
k = 1;
i__2 = iwork[i__ + 1];
for (j = submat; j <= i__2; ++j) {
iwork[indxq + j] = k;
++k;
/* L60: */
}
/* L70: */
}
/* Successively merge eigensystems of adjacent submatrices
into eigensystem for the corresponding larger matrix.
while ( SUBPBS > 1 ) */
curlvl = 1;
L80:
if (subpbs > 1) {
spm2 = subpbs - 2;
i__1 = spm2;
for (i__ = 0; i__ <= i__1; i__ += 2) {
if (i__ == 0) {
submat = 1;
matsiz = iwork[2];
msd2 = iwork[1];
curprb = 0;
} else {
submat = iwork[i__] + 1;
matsiz = iwork[i__ + 2] - iwork[i__];
msd2 = matsiz / 2;
++curprb;
}
/* Merge lower order eigensystems (of size MSD2 and MATSIZ - MSD2)
into an eigensystem of size MATSIZ.
SLAED1 is used only for the full eigensystem of a tridiagonal
matrix.
SLAED7 handles the cases in which eigenvalues only or eigenvalues
and eigenvectors of a full symmetric matrix (which was reduced to
tridiagonal form) are desired. */
if (*icompq == 2) {
slaed1_(&matsiz, &d__[submat], &q_ref(submat, submat), ldq, &
iwork[indxq + submat], &e[submat + msd2 - 1], &msd2, &
work[1], &iwork[subpbs + 1], info);
} else {
slaed7_(icompq, &matsiz, qsiz, &tlvls, &curlvl, &curprb, &d__[
submat], &qstore_ref(1, submat), ldqs, &iwork[indxq +
submat], &e[submat + msd2 - 1], &msd2, &work[iq], &
iwork[iqptr], &iwork[iprmpt], &iwork[iperm], &iwork[
igivpt], &iwork[igivcl], &work[igivnm], &work[iwrem],
&iwork[subpbs + 1], info);
}
if (*info != 0) {
goto L130;
}
iwork[i__ / 2 + 1] = iwork[i__ + 2];
/* L90: */
}
subpbs /= 2;
++curlvl;
goto L80;
}
/* end while
Re-merge the eigenvalues/vectors which were deflated at the final
merge step. */
if (*icompq == 1) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
scopy_(qsiz, &qstore_ref(1, j), &c__1, &q_ref(1, i__), &c__1);
/* L100: */
}
scopy_(n, &work[1], &c__1, &d__[1], &c__1);
} else if (*icompq == 2) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
scopy_(n, &q_ref(1, j), &c__1, &work[*n * i__ + 1], &c__1);
/* L110: */
}
scopy_(n, &work[1], &c__1, &d__[1], &c__1);
slacpy_("A", n, n, &work[*n + 1], n, &q[q_offset], ldq);
} else {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
/* L120: */
}
scopy_(n, &work[1], &c__1, &d__[1], &c__1);
}
goto L140;
L130:
*info = submat * (*n + 1) + submat + matsiz - 1;
L140:
return 0;
/* End of SLAED0 */
} /* slaed0_ */
/* Subroutine */ int slahr2_(integer *n, integer *k, integer *nb, real *a,
integer *lda, real *tau, real *t, integer *ldt, real *y, integer *ldy)
{
/* System generated locals */
integer a_dim1, a_offset, t_dim1, t_offset, y_dim1, y_offset, i__1, i__2,
i__3;
real r__1;
/* Local variables */
integer i__;
real ei;
/* -- LAPACK auxiliary routine (version 3.2) -- */
/* November 2006 */
/* Purpose */
/* ======= */
/* SLAHR2 reduces the first NB columns of A real general n-BY-(n-k+1) */
/* matrix A so that elements below the k-th subdiagonal are zero. The */
/* reduction is performed by an orthogonal similarity transformation */
/* Q' * A * Q. The routine returns the matrices V and T which determine */
/* Q as a block reflector I - V*T*V', and also the matrix Y = A * V * T. */
/* This is an auxiliary routine called by SGEHRD. */
/* Arguments */
/* ========= */
/* N (input) INTEGER */
/* The order of the matrix A. */
/* K (input) INTEGER */
/* The offset for the reduction. Elements below the k-th */
/* subdiagonal in the first NB columns are reduced to zero. */
/* K < N. */
/* NB (input) INTEGER */
/* The number of columns to be reduced. */
/* A (input/output) REAL array, dimension (LDA,N-K+1) */
/* On entry, the n-by-(n-k+1) general matrix A. */
/* On exit, the elements on and above the k-th subdiagonal in */
/* the first NB columns are overwritten with the corresponding */
/* elements of the reduced matrix; the elements below the k-th */
/* subdiagonal, with the array TAU, represent the matrix Q as a */
/* product of elementary reflectors. The other columns of A are */
/* unchanged. See Further Details. */
/* LDA (input) INTEGER */
/* The leading dimension of the array A. LDA >= max(1,N). */
/* TAU (output) REAL array, dimension (NB) */
/* The scalar factors of the elementary reflectors. See Further */
/* Details. */
/* T (output) REAL array, dimension (LDT,NB) */
/* The upper triangular matrix T. */
/* LDT (input) INTEGER */
/* The leading dimension of the array T. LDT >= NB. */
/* Y (output) REAL array, dimension (LDY,NB) */
/* The n-by-nb matrix Y. */
/* LDY (input) INTEGER */
/* The leading dimension of the array Y. LDY >= N. */
/* Further Details */
/* =============== */
/* The matrix Q is represented as a product of nb elementary reflectors */
/* Q = H(1) H(2) . . . H(nb). */
/* Each H(i) has the form */
/* H(i) = I - tau * v * v' */
/* where tau is a real scalar, and v is a real vector with */
/* v(1:i+k-1) = 0, v(i+k) = 1; v(i+k+1:n) is stored on exit in */
/* A(i+k+1:n,i), and tau in TAU(i). */
/* The elements of the vectors v together form the (n-k+1)-by-nb matrix */
/* V which is needed, with T and Y, to apply the transformation to the */
/* unreduced part of the matrix, using an update of the form: */
/* A := (I - V*T*V') * (A - Y*V'). */
/* The contents of A on exit are illustrated by the following example */
/* with n = 7, k = 3 and nb = 2: */
/* ( a a a a a ) */
/* ( a a a a a ) */
/* ( a a a a a ) */
/* ( h h a a a ) */
/* ( v1 h a a a ) */
/* ( v1 v2 a a a ) */
/* ( v1 v2 a a a ) */
/* where a denotes an element of the original matrix A, h denotes a */
/* modified element of the upper Hessenberg matrix H, and vi denotes an */
/* element of the vector defining H(i). */
/* This file is a slight modification of LAPACK-3.0's SLAHRD */
/* incorporating improvements proposed by Quintana-Orti and Van de */
/* Gejin. Note that the entries of A(1:K,2:NB) differ from those */
/* returned by the original LAPACK routine. This function is */
/* not backward compatible with LAPACK3.0. */
/* ===================================================================== */
/* Quick return if possible */
/* Parameter adjustments */
--tau;
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
y_dim1 = *ldy;
y_offset = 1 + y_dim1;
y -= y_offset;
/* Function Body */
if (*n <= 1) {
return 0;
}
i__1 = *nb;
for (i__ = 1; i__ <= i__1; ++i__) {
if (i__ > 1) {
/* Update A(K+1:N,I) */
/* Update I-th column of A - Y * V' */
i__2 = *n - *k;
i__3 = i__ - 1;
sgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &y[*k + 1 + y_dim1],
ldy, &a[*k + i__ - 1 + a_dim1], lda, &c_b5, &a[*k + 1 +
i__ * a_dim1], &c__1);
/* Apply I - V * T' * V' to this column (call it b) from the */
/* left, using the last column of T as workspace */
/* Let V = ( V1 ) and b = ( b1 ) (first I-1 rows) */
/* ( V2 ) ( b2 ) */
/* where V1 is unit lower triangular */
/* w := V1' * b1 */
i__2 = i__ - 1;
scopy_(&i__2, &a[*k + 1 + i__ * a_dim1], &c__1, &t[*nb * t_dim1 +
1], &c__1);
i__2 = i__ - 1;
strmv_("Lower", "Transpose", "UNIT", &i__2, &a[*k + 1 + a_dim1],
lda, &t[*nb * t_dim1 + 1], &c__1);
/* w := w + V2'*b2 */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
sgemv_("Transpose", &i__2, &i__3, &c_b5, &a[*k + i__ + a_dim1],
lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b5, &t[*nb *
t_dim1 + 1], &c__1);
/* w := T'*w */
i__2 = i__ - 1;
strmv_("Upper", "Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt,
&t[*nb * t_dim1 + 1], &c__1);
/* b2 := b2 - V2*w */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
sgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &a[*k + i__ + a_dim1],
lda, &t[*nb * t_dim1 + 1], &c__1, &c_b5, &a[*k + i__ +
i__ * a_dim1], &c__1);
/* b1 := b1 - V1*w */
i__2 = i__ - 1;
strmv_("Lower", "NO TRANSPOSE", "UNIT", &i__2, &a[*k + 1 + a_dim1]
, lda, &t[*nb * t_dim1 + 1], &c__1);
i__2 = i__ - 1;
saxpy_(&i__2, &c_b4, &t[*nb * t_dim1 + 1], &c__1, &a[*k + 1 + i__
* a_dim1], &c__1);
a[*k + i__ - 1 + (i__ - 1) * a_dim1] = ei;
}
/* Generate the elementary reflector H(I) to annihilate */
/* A(K+I+1:N,I) */
i__2 = *n - *k - i__ + 1;
/* Computing MIN */
i__3 = *k + i__ + 1;
slarfg_(&i__2, &a[*k + i__ + i__ * a_dim1], &a[min(i__3, *n)+ i__ *
a_dim1], &c__1, &tau[i__]);
ei = a[*k + i__ + i__ * a_dim1];
a[*k + i__ + i__ * a_dim1] = 1.f;
/* Compute Y(K+1:N,I) */
i__2 = *n - *k;
i__3 = *n - *k - i__ + 1;
sgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b5, &a[*k + 1 + (i__ + 1) *
a_dim1], lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b38, &y[*
k + 1 + i__ * y_dim1], &c__1);
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
sgemv_("Transpose", &i__2, &i__3, &c_b5, &a[*k + i__ + a_dim1], lda, &
a[*k + i__ + i__ * a_dim1], &c__1, &c_b38, &t[i__ * t_dim1 +
1], &c__1);
i__2 = *n - *k;
i__3 = i__ - 1;
sgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &y[*k + 1 + y_dim1], ldy,
&t[i__ * t_dim1 + 1], &c__1, &c_b5, &y[*k + 1 + i__ * y_dim1],
&c__1);
i__2 = *n - *k;
sscal_(&i__2, &tau[i__], &y[*k + 1 + i__ * y_dim1], &c__1);
/* Compute T(1:I,I) */
i__2 = i__ - 1;
r__1 = -tau[i__];
sscal_(&i__2, &r__1, &t[i__ * t_dim1 + 1], &c__1);
i__2 = i__ - 1;
strmv_("Upper", "No Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt,
&t[i__ * t_dim1 + 1], &c__1)
;
t[i__ + i__ * t_dim1] = tau[i__];
}
a[*k + *nb + *nb * a_dim1] = ei;
/* Compute Y(1:K,1:NB) */
slacpy_("ALL", k, nb, &a[(a_dim1 << 1) + 1], lda, &y[y_offset], ldy);
strmm_("RIGHT", "Lower", "NO TRANSPOSE", "UNIT", k, nb, &c_b5, &a[*k + 1
+ a_dim1], lda, &y[y_offset], ldy);
if (*n > *k + *nb) {
i__1 = *n - *k - *nb;
sgemm_("NO TRANSPOSE", "NO TRANSPOSE", k, nb, &i__1, &c_b5, &a[(*nb +
2) * a_dim1 + 1], lda, &a[*k + 1 + *nb + a_dim1], lda, &c_b5,
&y[y_offset], ldy);
}
strmm_("RIGHT", "Upper", "NO TRANSPOSE", "NON-UNIT", k, nb, &c_b5, &t[
t_offset], ldt, &y[y_offset], ldy);
return 0;
/* End of SLAHR2 */
} /* slahr2_ */
/* Subroutine */ int sqlt02_(integer *m, integer *n, integer *k, real *a,
real *af, real *q, real *l, integer *lda, real *tau, real *work,
integer *lwork, real *rwork, real *result)
{
/* System generated locals */
integer a_dim1, a_offset, af_dim1, af_offset, l_dim1, l_offset, q_dim1,
q_offset, i__1, i__2;
/* Builtin functions */
/* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen);
/* Local variables */
real eps;
integer info;
real resid;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
real anorm;
extern /* Subroutine */ int ssyrk_(char *, char *, integer *, integer *,
real *, real *, integer *, real *, real *, integer *);
extern doublereal slamch_(char *), slange_(char *, integer *,
integer *, real *, integer *, real *);
extern /* Subroutine */ int slacpy_(char *, integer *, integer *, real *,
integer *, real *, integer *), slaset_(char *, integer *,
integer *, real *, real *, real *, integer *), sorgql_(
integer *, integer *, integer *, real *, integer *, real *, real *
, integer *, integer *);
extern doublereal slansy_(char *, char *, integer *, real *, integer *,
real *);
/* -- LAPACK test routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SQLT02 tests SORGQL, which generates an m-by-n matrix Q with */
/* orthonornmal columns that is defined as the product of k elementary */
/* reflectors. */
/* Given the QL factorization of an m-by-n matrix A, SQLT02 generates */
/* the orthogonal matrix Q defined by the factorization of the last k */
/* columns of A; it compares L(m-n+1:m,n-k+1:n) with */
/* Q(1:m,m-n+1:m)'*A(1:m,n-k+1:n), and checks that the columns of Q are */
/* orthonormal. */
/* Arguments */
/* ========= */
/* M (input) INTEGER */
/* The number of rows of the matrix Q to be generated. M >= 0. */
/* N (input) INTEGER */
/* The number of columns of the matrix Q to be generated. */
/* M >= N >= 0. */
/* K (input) INTEGER */
/* The number of elementary reflectors whose product defines the */
/* matrix Q. N >= K >= 0. */
/* A (input) REAL array, dimension (LDA,N) */
/* The m-by-n matrix A which was factorized by SQLT01. */
/* AF (input) REAL array, dimension (LDA,N) */
/* Details of the QL factorization of A, as returned by SGEQLF. */
/* See SGEQLF for further details. */
/* Q (workspace) REAL array, dimension (LDA,N) */
/* L (workspace) REAL array, dimension (LDA,N) */
/* LDA (input) INTEGER */
/* The leading dimension of the arrays A, AF, Q and L. LDA >= M. */
/* TAU (input) REAL array, dimension (N) */
/* The scalar factors of the elementary reflectors corresponding */
/* to the QL factorization in AF. */
/* WORK (workspace) REAL array, dimension (LWORK) */
/* LWORK (input) INTEGER */
/* The dimension of the array WORK. */
/* RWORK (workspace) REAL array, dimension (M) */
/* RESULT (output) REAL array, dimension (2) */
/* The test ratios: */
/* RESULT(1) = norm( L - Q'*A ) / ( M * norm(A) * EPS ) */
/* RESULT(2) = norm( I - Q'*Q ) / ( M * EPS ) */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Scalars in Common .. */
/* .. */
/* .. Common blocks .. */
/* .. */
/* .. Executable Statements .. */
/* Quick return if possible */
/* Parameter adjustments */
l_dim1 = *lda;
l_offset = 1 + l_dim1;
l -= l_offset;
q_dim1 = *lda;
q_offset = 1 + q_dim1;
q -= q_offset;
af_dim1 = *lda;
af_offset = 1 + af_dim1;
af -= af_offset;
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
--rwork;
--result;
/* Function Body */
if (*m == 0 || *n == 0 || *k == 0) {
result[1] = 0.f;
result[2] = 0.f;
return 0;
}
eps = slamch_("Epsilon");
/* Copy the last k columns of the factorization to the array Q */
slaset_("Full", m, n, &c_b4, &c_b4, &q[q_offset], lda);
if (*k < *m) {
i__1 = *m - *k;
slacpy_("Full", &i__1, k, &af[(*n - *k + 1) * af_dim1 + 1], lda, &q[(*
n - *k + 1) * q_dim1 + 1], lda);
}
if (*k > 1) {
i__1 = *k - 1;
i__2 = *k - 1;
slacpy_("Upper", &i__1, &i__2, &af[*m - *k + 1 + (*n - *k + 2) *
af_dim1], lda, &q[*m - *k + 1 + (*n - *k + 2) * q_dim1], lda);
}
/* Generate the last n columns of the matrix Q */
s_copy(srnamc_1.srnamt, "SORGQL", (ftnlen)6, (ftnlen)6);
sorgql_(m, n, k, &q[q_offset], lda, &tau[*n - *k + 1], &work[1], lwork, &
info);
/* Copy L(m-n+1:m,n-k+1:n) */
slaset_("Full", n, k, &c_b10, &c_b10, &l[*m - *n + 1 + (*n - *k + 1) *
l_dim1], lda);
slacpy_("Lower", k, k, &af[*m - *k + 1 + (*n - *k + 1) * af_dim1], lda, &
l[*m - *k + 1 + (*n - *k + 1) * l_dim1], lda);
/* Compute L(m-n+1:m,n-k+1:n) - Q(1:m,m-n+1:m)' * A(1:m,n-k+1:n) */
sgemm_("Transpose", "No transpose", n, k, m, &c_b15, &q[q_offset], lda, &
a[(*n - *k + 1) * a_dim1 + 1], lda, &c_b16, &l[*m - *n + 1 + (*n
- *k + 1) * l_dim1], lda);
/* Compute norm( L - Q'*A ) / ( M * norm(A) * EPS ) . */
anorm = slange_("1", m, k, &a[(*n - *k + 1) * a_dim1 + 1], lda, &rwork[1]);
resid = slange_("1", n, k, &l[*m - *n + 1 + (*n - *k + 1) * l_dim1], lda,
&rwork[1]);
if (anorm > 0.f) {
result[1] = resid / (real) max(1,*m) / anorm / eps;
} else {
result[1] = 0.f;
}
/* Compute I - Q'*Q */
slaset_("Full", n, n, &c_b10, &c_b16, &l[l_offset], lda);
ssyrk_("Upper", "Transpose", n, m, &c_b15, &q[q_offset], lda, &c_b16, &l[
l_offset], lda);
/* Compute norm( I - Q'*Q ) / ( M * EPS ) . */
resid = slansy_("1", "Upper", n, &l[l_offset], lda, &rwork[1]);
result[2] = resid / (real) max(1,*m) / eps;
return 0;
/* End of SQLT02 */
} /* sqlt02_ */
int ssbgvd_(char *jobz, char *uplo, int *n, int *ka,
int *kb, float *ab, int *ldab, float *bb, int *ldbb, float *
w, float *z__, int *ldz, float *work, int *lwork, int *
iwork, int *liwork, int *info)
{
/* System generated locals */
int ab_dim1, ab_offset, bb_dim1, bb_offset, z_dim1, z_offset, i__1;
/* Local variables */
int inde;
char vect[1];
extern int lsame_(char *, char *);
int iinfo;
extern int sgemm_(char *, char *, int *, int *,
int *, float *, float *, int *, float *, int *, float *,
float *, int *);
int lwmin;
int upper, wantz;
int indwk2, llwrk2;
extern int xerbla_(char *, int *), sstedc_(
char *, int *, float *, float *, float *, int *, float *,
int *, int *, int *, int *), slacpy_(char
*, int *, int *, float *, int *, float *, int *);
int indwrk, liwmin;
extern int spbstf_(char *, int *, int *, float *,
int *, int *), ssbtrd_(char *, char *, int *,
int *, float *, int *, float *, float *, float *, int *,
float *, int *), ssbgst_(char *, char *,
int *, int *, int *, float *, int *, float *,
int *, float *, int *, float *, int *),
ssterf_(int *, float *, float *, int *);
int lquery;
/* -- LAPACK driver routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSBGVD computes all the eigenvalues, and optionally, the eigenvectors */
/* of a float generalized symmetric-definite banded eigenproblem, of the */
/* form A*x=(lambda)*B*x. Here A and B are assumed to be symmetric and */
/* banded, and B is also positive definite. If eigenvectors are */
/* desired, it uses a divide and conquer algorithm. */
/* The divide and conquer algorithm makes very mild assumptions about */
/* floating point arithmetic. It will work on machines with a guard */
/* digit in add/subtract, or on those binary machines without guard */
/* digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or */
/* Cray-2. It could conceivably fail on hexadecimal or decimal machines */
/* without guard digits, but we know of none. */
/* Arguments */
/* ========= */
/* JOBZ (input) CHARACTER*1 */
/* = 'N': Compute eigenvalues only; */
/* = 'V': Compute eigenvalues and eigenvectors. */
/* UPLO (input) CHARACTER*1 */
/* = 'U': Upper triangles of A and B are stored; */
/* = 'L': Lower triangles of A and B are stored. */
/* N (input) INTEGER */
/* The order of the matrices A and B. N >= 0. */
/* KA (input) INTEGER */
/* The number of superdiagonals of the matrix A if UPLO = 'U', */
/* or the number of subdiagonals if UPLO = 'L'. KA >= 0. */
/* KB (input) INTEGER */
/* The number of superdiagonals of the matrix B if UPLO = 'U', */
/* or the number of subdiagonals if UPLO = 'L'. KB >= 0. */
/* AB (input/output) REAL array, dimension (LDAB, N) */
/* On entry, the upper or lower triangle of the symmetric band */
/* matrix A, stored in the first ka+1 rows of the array. The */
/* j-th column of A is stored in the j-th column of the array AB */
/* as follows: */
/* if UPLO = 'U', AB(ka+1+i-j,j) = A(i,j) for MAX(1,j-ka)<=i<=j; */
/* if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=MIN(n,j+ka). */
/* On exit, the contents of AB are destroyed. */
/* LDAB (input) INTEGER */
/* The leading dimension of the array AB. LDAB >= KA+1. */
/* BB (input/output) REAL array, dimension (LDBB, N) */
/* On entry, the upper or lower triangle of the symmetric band */
/* matrix B, stored in the first kb+1 rows of the array. The */
/* j-th column of B is stored in the j-th column of the array BB */
/* as follows: */
/* if UPLO = 'U', BB(ka+1+i-j,j) = B(i,j) for MAX(1,j-kb)<=i<=j; */
/* if UPLO = 'L', BB(1+i-j,j) = B(i,j) for j<=i<=MIN(n,j+kb). */
/* On exit, the factor S from the split Cholesky factorization */
/* B = S**T*S, as returned by SPBSTF. */
/* LDBB (input) INTEGER */
/* The leading dimension of the array BB. LDBB >= KB+1. */
/* W (output) REAL array, dimension (N) */
/* If INFO = 0, the eigenvalues in ascending order. */
/* Z (output) REAL array, dimension (LDZ, N) */
/* If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of */
/* eigenvectors, with the i-th column of Z holding the */
/* eigenvector associated with W(i). The eigenvectors are */
/* normalized so Z**T*B*Z = I. */
/* If JOBZ = 'N', then Z is not referenced. */
/* LDZ (input) INTEGER */
/* The leading dimension of the array Z. LDZ >= 1, and if */
/* JOBZ = 'V', LDZ >= MAX(1,N). */
/* WORK (workspace/output) REAL array, dimension (MAX(1,LWORK)) */
/* On exit, if INFO = 0, WORK(1) returns the optimal LWORK. */
/* LWORK (input) INTEGER */
/* The dimension of the array WORK. */
/* If N <= 1, LWORK >= 1. */
/* If JOBZ = 'N' and N > 1, LWORK >= 3*N. */
/* If JOBZ = 'V' and N > 1, LWORK >= 1 + 5*N + 2*N**2. */
/* If LWORK = -1, then a workspace query is assumed; the routine */
/* only calculates the optimal sizes of the WORK and IWORK */
/* arrays, returns these values as the first entries of the WORK */
/* and IWORK arrays, and no error message related to LWORK or */
/* LIWORK is issued by XERBLA. */
/* IWORK (workspace/output) INTEGER array, dimension (MAX(1,LIWORK)) */
/* On exit, if LIWORK > 0, IWORK(1) returns the optimal LIWORK. */
/* LIWORK (input) INTEGER */
/* The dimension of the array IWORK. */
/* If JOBZ = 'N' or N <= 1, LIWORK >= 1. */
/* If JOBZ = 'V' and N > 1, LIWORK >= 3 + 5*N. */
/* If LIWORK = -1, then a workspace query is assumed; the */
/* routine only calculates the optimal sizes of the WORK and */
/* IWORK arrays, returns these values as the first entries of */
/* the WORK and IWORK arrays, and no error message related to */
/* LWORK or LIWORK is issued by XERBLA. */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: if INFO = i, and i is: */
/* <= N: the algorithm failed to converge: */
/* i off-diagonal elements of an intermediate */
/* tridiagonal form did not converge to zero; */
/* > N: if INFO = N + i, for 1 <= i <= N, then SPBSTF */
/* returned INFO = i: B is not positive definite. */
/* The factorization of B could not be completed and */
/* no eigenvalues or eigenvectors were computed. */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
ab_dim1 = *ldab;
ab_offset = 1 + ab_dim1;
ab -= ab_offset;
bb_dim1 = *ldbb;
bb_offset = 1 + bb_dim1;
bb -= bb_offset;
--w;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
--iwork;
/* Function Body */
wantz = lsame_(jobz, "V");
upper = lsame_(uplo, "U");
lquery = *lwork == -1 || *liwork == -1;
*info = 0;
if (*n <= 1) {
liwmin = 1;
lwmin = 1;
} else if (wantz) {
liwmin = *n * 5 + 3;
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 5 + 1 + (i__1 * i__1 << 1);
} else {
liwmin = 1;
lwmin = *n << 1;
}
if (! (wantz || lsame_(jobz, "N"))) {
*info = -1;
} else if (! (upper || lsame_(uplo, "L"))) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ka < 0) {
*info = -4;
} else if (*kb < 0 || *kb > *ka) {
*info = -5;
} else if (*ldab < *ka + 1) {
*info = -7;
} else if (*ldbb < *kb + 1) {
*info = -9;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -12;
}
if (*info == 0) {
work[1] = (float) lwmin;
iwork[1] = liwmin;
if (*lwork < lwmin && ! lquery) {
*info = -14;
} else if (*liwork < liwmin && ! lquery) {
*info = -16;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSBGVD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Form a split Cholesky factorization of B. */
spbstf_(uplo, n, kb, &bb[bb_offset], ldbb, info);
if (*info != 0) {
*info = *n + *info;
return 0;
}
/* Transform problem to standard eigenvalue problem. */
inde = 1;
indwrk = inde + *n;
indwk2 = indwrk + *n * *n;
llwrk2 = *lwork - indwk2 + 1;
ssbgst_(jobz, uplo, n, ka, kb, &ab[ab_offset], ldab, &bb[bb_offset], ldbb,
&z__[z_offset], ldz, &work[indwrk], &iinfo)
;
/* Reduce to tridiagonal form. */
if (wantz) {
*(unsigned char *)vect = 'U';
} else {
*(unsigned char *)vect = 'N';
}
ssbtrd_(vect, uplo, n, ka, &ab[ab_offset], ldab, &w[1], &work[inde], &z__[
z_offset], ldz, &work[indwrk], &iinfo);
/* For eigenvalues only, call SSTERF. For eigenvectors, call SSTEDC. */
if (! wantz) {
ssterf_(n, &w[1], &work[inde], info);
} else {
sstedc_("I", n, &w[1], &work[inde], &work[indwrk], n, &work[indwk2], &
llwrk2, &iwork[1], liwork, info);
sgemm_("N", "N", n, n, n, &c_b12, &z__[z_offset], ldz, &work[indwrk],
n, &c_b13, &work[indwk2], n);
slacpy_("A", n, n, &work[indwk2], n, &z__[z_offset], ldz);
}
work[1] = (float) lwmin;
iwork[1] = liwmin;
return 0;
/* End of SSBGVD */
} /* ssbgvd_ */
int slaqr5_(int *wantt, int *wantz, int *kacc22,
int *n, int *ktop, int *kbot, int *nshfts, float *sr,
float *si, float *h__, int *ldh, int *iloz, int *ihiz, float
*z__, int *ldz, float *v, int *ldv, float *u, int *ldu,
int *nv, float *wv, int *ldwv, int *nh, float *wh, int *
ldwh)
{
/* System generated locals */
int h_dim1, h_offset, u_dim1, u_offset, v_dim1, v_offset, wh_dim1,
wh_offset, wv_dim1, wv_offset, z_dim1, z_offset, i__1, i__2, i__3,
i__4, i__5, i__6, i__7;
float r__1, r__2, r__3, r__4, r__5;
/* Local variables */
int i__, j, k, m, i2, j2, i4, j4, k1;
float h11, h12, h21, h22;
int m22, ns, nu;
float vt[3], scl;
int kdu, kms;
float ulp;
int knz, kzs;
float tst1, tst2, beta;
int blk22, bmp22;
int mend, jcol, jlen, jbot, mbot;
float swap;
int jtop, jrow, mtop;
float alpha;
int accum;
int ndcol, incol;
extern int sgemm_(char *, char *, int *, int *,
int *, float *, float *, int *, float *, int *, float *,
float *, int *);
int krcol, nbmps;
extern int strmm_(char *, char *, char *, char *,
int *, int *, float *, float *, int *, float *, int *
), slaqr1_(int *, float *,
int *, float *, float *, float *, float *, float *), slabad_(float *
, float *);
extern double slamch_(char *);
float safmin;
extern int slarfg_(int *, float *, float *, int *,
float *);
float safmax;
extern int slacpy_(char *, int *, int *, float *,
int *, float *, int *), slaset_(char *, int *,
int *, float *, float *, float *, int *);
float refsum;
int mstart;
float smlnum;
/* -- LAPACK auxiliary routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* This auxiliary subroutine called by SLAQR0 performs a */
/* single small-bulge multi-shift QR sweep. */
/* WANTT (input) int scalar */
/* WANTT = .true. if the quasi-triangular Schur factor */
/* is being computed. WANTT is set to .false. otherwise. */
/* WANTZ (input) int scalar */
/* WANTZ = .true. if the orthogonal Schur factor is being */
/* computed. WANTZ is set to .false. otherwise. */
/* KACC22 (input) int with value 0, 1, or 2. */
/* Specifies the computation mode of far-from-diagonal */
/* orthogonal updates. */
/* = 0: SLAQR5 does not accumulate reflections and does not */
/* use matrix-matrix multiply to update far-from-diagonal */
/* matrix entries. */
/* = 1: SLAQR5 accumulates reflections and uses matrix-matrix */
/* multiply to update the far-from-diagonal matrix entries. */
/* = 2: SLAQR5 accumulates reflections, uses matrix-matrix */
/* multiply to update the far-from-diagonal matrix entries, */
/* and takes advantage of 2-by-2 block structure during */
/* matrix multiplies. */
/* N (input) int scalar */
/* N is the order of the Hessenberg matrix H upon which this */
/* subroutine operates. */
/* KTOP (input) int scalar */
/* KBOT (input) int scalar */
/* These are the first and last rows and columns of an */
/* isolated diagonal block upon which the QR sweep is to be */
/* applied. It is assumed without a check that */
/* either KTOP = 1 or H(KTOP,KTOP-1) = 0 */
/* and */
/* either KBOT = N or H(KBOT+1,KBOT) = 0. */
/* NSHFTS (input) int scalar */
/* NSHFTS gives the number of simultaneous shifts. NSHFTS */
/* must be positive and even. */
/* SR (input/output) REAL array of size (NSHFTS) */
/* SI (input/output) REAL array of size (NSHFTS) */
/* SR contains the float parts and SI contains the imaginary */
/* parts of the NSHFTS shifts of origin that define the */
/* multi-shift QR sweep. On output SR and SI may be */
/* reordered. */
/* H (input/output) REAL array of size (LDH,N) */
/* On input H contains a Hessenberg matrix. On output a */
/* multi-shift QR sweep with shifts SR(J)+i*SI(J) is applied */
/* to the isolated diagonal block in rows and columns KTOP */
/* through KBOT. */
/* LDH (input) int scalar */
/* LDH is the leading dimension of H just as declared in the */
/* calling procedure. LDH.GE.MAX(1,N). */
/* ILOZ (input) INTEGER */
/* IHIZ (input) INTEGER */
/* Specify the rows of Z to which transformations must be */
/* applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N */
/* Z (input/output) REAL array of size (LDZ,IHI) */
/* If WANTZ = .TRUE., then the QR Sweep orthogonal */
/* similarity transformation is accumulated into */
/* Z(ILOZ:IHIZ,ILO:IHI) from the right. */
/* If WANTZ = .FALSE., then Z is unreferenced. */
/* LDZ (input) int scalar */
/* LDA is the leading dimension of Z just as declared in */
/* the calling procedure. LDZ.GE.N. */
/* V (workspace) REAL array of size (LDV,NSHFTS/2) */
/* LDV (input) int scalar */
/* LDV is the leading dimension of V as declared in the */
/* calling procedure. LDV.GE.3. */
/* U (workspace) REAL array of size */
/* (LDU,3*NSHFTS-3) */
/* LDU (input) int scalar */
/* LDU is the leading dimension of U just as declared in the */
/* in the calling subroutine. LDU.GE.3*NSHFTS-3. */
/* NH (input) int scalar */
/* NH is the number of columns in array WH available for */
/* workspace. NH.GE.1. */
/* WH (workspace) REAL array of size (LDWH,NH) */
/* LDWH (input) int scalar */
/* Leading dimension of WH just as declared in the */
/* calling procedure. LDWH.GE.3*NSHFTS-3. */
/* NV (input) int scalar */
/* NV is the number of rows in WV agailable for workspace. */
/* NV.GE.1. */
/* WV (workspace) REAL array of size */
/* (LDWV,3*NSHFTS-3) */
/* LDWV (input) int scalar */
/* LDWV is the leading dimension of WV as declared in the */
/* in the calling subroutine. LDWV.GE.NV. */
/* ================================================================ */
/* Based on contributions by */
/* Karen Braman and Ralph Byers, Department of Mathematics, */
/* University of Kansas, USA */
/* ================================================================ */
/* Reference: */
/* K. Braman, R. Byers and R. Mathias, The Multi-Shift QR */
/* Algorithm Part I: Maintaining Well Focused Shifts, and */
/* Level 3 Performance, SIAM Journal of Matrix Analysis, */
/* volume 23, pages 929--947, 2002. */
/* ================================================================ */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Local Arrays .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Executable Statements .. */
/* ==== If there are no shifts, then there is nothing to do. ==== */
/* Parameter adjustments */
--sr;
--si;
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
wv_dim1 = *ldwv;
wv_offset = 1 + wv_dim1;
wv -= wv_offset;
wh_dim1 = *ldwh;
wh_offset = 1 + wh_dim1;
wh -= wh_offset;
/* Function Body */
if (*nshfts < 2) {
return 0;
}
/* ==== If the active block is empty or 1-by-1, then there */
/* . is nothing to do. ==== */
if (*ktop >= *kbot) {
return 0;
}
/* ==== Shuffle shifts into pairs of float shifts and pairs */
/* . of complex conjugate shifts assuming complex */
/* . conjugate shifts are already adjacent to one */
/* . another. ==== */
i__1 = *nshfts - 2;
for (i__ = 1; i__ <= i__1; i__ += 2) {
if (si[i__] != -si[i__ + 1]) {
swap = sr[i__];
sr[i__] = sr[i__ + 1];
sr[i__ + 1] = sr[i__ + 2];
sr[i__ + 2] = swap;
swap = si[i__];
si[i__] = si[i__ + 1];
si[i__ + 1] = si[i__ + 2];
si[i__ + 2] = swap;
}
/* L10: */
}
/* ==== NSHFTS is supposed to be even, but if it is odd, */
/* . then simply reduce it by one. The shuffle above */
/* . ensures that the dropped shift is float and that */
/* . the remaining shifts are paired. ==== */
ns = *nshfts - *nshfts % 2;
/* ==== Machine constants for deflation ==== */
safmin = slamch_("SAFE MINIMUM");
safmax = 1.f / safmin;
slabad_(&safmin, &safmax);
ulp = slamch_("PRECISION");
smlnum = safmin * ((float) (*n) / ulp);
/* ==== Use accumulated reflections to update far-from-diagonal */
/* . entries ? ==== */
accum = *kacc22 == 1 || *kacc22 == 2;
/* ==== If so, exploit the 2-by-2 block structure? ==== */
blk22 = ns > 2 && *kacc22 == 2;
/* ==== clear trash ==== */
if (*ktop + 2 <= *kbot) {
h__[*ktop + 2 + *ktop * h_dim1] = 0.f;
}
/* ==== NBMPS = number of 2-shift bulges in the chain ==== */
nbmps = ns / 2;
/* ==== KDU = width of slab ==== */
kdu = nbmps * 6 - 3;
/* ==== Create and chase chains of NBMPS bulges ==== */
i__1 = *kbot - 2;
i__2 = nbmps * 3 - 2;
for (incol = (1 - nbmps) * 3 + *ktop - 1; i__2 < 0 ? incol >= i__1 :
incol <= i__1; incol += i__2) {
ndcol = incol + kdu;
if (accum) {
slaset_("ALL", &kdu, &kdu, &c_b7, &c_b8, &u[u_offset], ldu);
}
/* ==== Near-the-diagonal bulge chase. The following loop */
/* . performs the near-the-diagonal part of a small bulge */
/* . multi-shift QR sweep. Each 6*NBMPS-2 column diagonal */
/* . chunk extends from column INCOL to column NDCOL */
/* . (including both column INCOL and column NDCOL). The */
/* . following loop chases a 3*NBMPS column long chain of */
/* . NBMPS bulges 3*NBMPS-2 columns to the right. (INCOL */
/* . may be less than KTOP and and NDCOL may be greater than */
/* . KBOT indicating phantom columns from which to chase */
/* . bulges before they are actually introduced or to which */
/* . to chase bulges beyond column KBOT.) ==== */
/* Computing MIN */
i__4 = incol + nbmps * 3 - 3, i__5 = *kbot - 2;
i__3 = MIN(i__4,i__5);
for (krcol = incol; krcol <= i__3; ++krcol) {
/* ==== Bulges number MTOP to MBOT are active double implicit */
/* . shift bulges. There may or may not also be small */
/* . 2-by-2 bulge, if there is room. The inactive bulges */
/* . (if any) must wait until the active bulges have moved */
/* . down the diagonal to make room. The phantom matrix */
/* . paradigm described above helps keep track. ==== */
/* Computing MAX */
i__4 = 1, i__5 = (*ktop - 1 - krcol + 2) / 3 + 1;
mtop = MAX(i__4,i__5);
/* Computing MIN */
i__4 = nbmps, i__5 = (*kbot - krcol) / 3;
mbot = MIN(i__4,i__5);
m22 = mbot + 1;
bmp22 = mbot < nbmps && krcol + (m22 - 1) * 3 == *kbot - 2;
/* ==== Generate reflections to chase the chain right */
/* . one column. (The minimum value of K is KTOP-1.) ==== */
i__4 = mbot;
for (m = mtop; m <= i__4; ++m) {
k = krcol + (m - 1) * 3;
if (k == *ktop - 1) {
slaqr1_(&c__3, &h__[*ktop + *ktop * h_dim1], ldh, &sr[(m
<< 1) - 1], &si[(m << 1) - 1], &sr[m * 2], &si[m *
2], &v[m * v_dim1 + 1]);
alpha = v[m * v_dim1 + 1];
slarfg_(&c__3, &alpha, &v[m * v_dim1 + 2], &c__1, &v[m *
v_dim1 + 1]);
} else {
beta = h__[k + 1 + k * h_dim1];
v[m * v_dim1 + 2] = h__[k + 2 + k * h_dim1];
v[m * v_dim1 + 3] = h__[k + 3 + k * h_dim1];
slarfg_(&c__3, &beta, &v[m * v_dim1 + 2], &c__1, &v[m *
v_dim1 + 1]);
/* ==== A Bulge may collapse because of vigilant */
/* . deflation or destructive underflow. In the */
/* . underflow case, try the two-small-subdiagonals */
/* . trick to try to reinflate the bulge. ==== */
if (h__[k + 3 + k * h_dim1] != 0.f || h__[k + 3 + (k + 1)
* h_dim1] != 0.f || h__[k + 3 + (k + 2) * h_dim1]
== 0.f) {
/* ==== Typical case: not collapsed (yet). ==== */
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.f;
h__[k + 3 + k * h_dim1] = 0.f;
} else {
/* ==== Atypical case: collapsed. Attempt to */
/* . reintroduce ignoring H(K+1,K) and H(K+2,K). */
/* . If the fill resulting from the new */
/* . reflector is too large, then abandon it. */
/* . Otherwise, use the new one. ==== */
slaqr1_(&c__3, &h__[k + 1 + (k + 1) * h_dim1], ldh, &
sr[(m << 1) - 1], &si[(m << 1) - 1], &sr[m *
2], &si[m * 2], vt);
alpha = vt[0];
slarfg_(&c__3, &alpha, &vt[1], &c__1, vt);
refsum = vt[0] * (h__[k + 1 + k * h_dim1] + vt[1] *
h__[k + 2 + k * h_dim1]);
if ((r__1 = h__[k + 2 + k * h_dim1] - refsum * vt[1],
ABS(r__1)) + (r__2 = refsum * vt[2], ABS(
r__2)) > ulp * ((r__3 = h__[k + k * h_dim1],
ABS(r__3)) + (r__4 = h__[k + 1 + (k + 1) *
h_dim1], ABS(r__4)) + (r__5 = h__[k + 2 + (k
+ 2) * h_dim1], ABS(r__5)))) {
/* ==== Starting a new bulge here would */
/* . create non-negligible fill. Use */
/* . the old one with trepidation. ==== */
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.f;
h__[k + 3 + k * h_dim1] = 0.f;
} else {
/* ==== Stating a new bulge here would */
/* . create only negligible fill. */
/* . Replace the old reflector with */
/* . the new one. ==== */
h__[k + 1 + k * h_dim1] -= refsum;
h__[k + 2 + k * h_dim1] = 0.f;
h__[k + 3 + k * h_dim1] = 0.f;
v[m * v_dim1 + 1] = vt[0];
v[m * v_dim1 + 2] = vt[1];
v[m * v_dim1 + 3] = vt[2];
}
}
}
/* L20: */
}
/* ==== Generate a 2-by-2 reflection, if needed. ==== */
k = krcol + (m22 - 1) * 3;
if (bmp22) {
if (k == *ktop - 1) {
slaqr1_(&c__2, &h__[k + 1 + (k + 1) * h_dim1], ldh, &sr[(
m22 << 1) - 1], &si[(m22 << 1) - 1], &sr[m22 * 2],
&si[m22 * 2], &v[m22 * v_dim1 + 1]);
beta = v[m22 * v_dim1 + 1];
slarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22
* v_dim1 + 1]);
} else {
beta = h__[k + 1 + k * h_dim1];
v[m22 * v_dim1 + 2] = h__[k + 2 + k * h_dim1];
slarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22
* v_dim1 + 1]);
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.f;
}
}
/* ==== Multiply H by reflections from the left ==== */
if (accum) {
jbot = MIN(ndcol,*kbot);
} else if (*wantt) {
jbot = *n;
} else {
jbot = *kbot;
}
i__4 = jbot;
for (j = MAX(*ktop,krcol); j <= i__4; ++j) {
/* Computing MIN */
i__5 = mbot, i__6 = (j - krcol + 2) / 3;
mend = MIN(i__5,i__6);
i__5 = mend;
for (m = mtop; m <= i__5; ++m) {
k = krcol + (m - 1) * 3;
refsum = v[m * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] + v[
m * v_dim1 + 2] * h__[k + 2 + j * h_dim1] + v[m *
v_dim1 + 3] * h__[k + 3 + j * h_dim1]);
h__[k + 1 + j * h_dim1] -= refsum;
h__[k + 2 + j * h_dim1] -= refsum * v[m * v_dim1 + 2];
h__[k + 3 + j * h_dim1] -= refsum * v[m * v_dim1 + 3];
/* L30: */
}
/* L40: */
}
if (bmp22) {
k = krcol + (m22 - 1) * 3;
/* Computing MAX */
i__4 = k + 1;
i__5 = jbot;
for (j = MAX(i__4,*ktop); j <= i__5; ++j) {
refsum = v[m22 * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] +
v[m22 * v_dim1 + 2] * h__[k + 2 + j * h_dim1]);
h__[k + 1 + j * h_dim1] -= refsum;
h__[k + 2 + j * h_dim1] -= refsum * v[m22 * v_dim1 + 2];
/* L50: */
}
}
/* ==== Multiply H by reflections from the right. */
/* . Delay filling in the last row until the */
/* . vigilant deflation check is complete. ==== */
if (accum) {
jtop = MAX(*ktop,incol);
} else if (*wantt) {
jtop = 1;
} else {
jtop = *ktop;
}
i__5 = mbot;
for (m = mtop; m <= i__5; ++m) {
if (v[m * v_dim1 + 1] != 0.f) {
k = krcol + (m - 1) * 3;
/* Computing MIN */
i__6 = *kbot, i__7 = k + 3;
i__4 = MIN(i__6,i__7);
for (j = jtop; j <= i__4; ++j) {
refsum = v[m * v_dim1 + 1] * (h__[j + (k + 1) *
h_dim1] + v[m * v_dim1 + 2] * h__[j + (k + 2)
* h_dim1] + v[m * v_dim1 + 3] * h__[j + (k +
3) * h_dim1]);
h__[j + (k + 1) * h_dim1] -= refsum;
h__[j + (k + 2) * h_dim1] -= refsum * v[m * v_dim1 +
2];
h__[j + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 +
3];
/* L60: */
}
if (accum) {
/* ==== Accumulate U. (If necessary, update Z later */
/* . with with an efficient matrix-matrix */
/* . multiply.) ==== */
kms = k - incol;
/* Computing MAX */
i__4 = 1, i__6 = *ktop - incol;
i__7 = kdu;
for (j = MAX(i__4,i__6); j <= i__7; ++j) {
refsum = v[m * v_dim1 + 1] * (u[j + (kms + 1) *
u_dim1] + v[m * v_dim1 + 2] * u[j + (kms
+ 2) * u_dim1] + v[m * v_dim1 + 3] * u[j
+ (kms + 3) * u_dim1]);
u[j + (kms + 1) * u_dim1] -= refsum;
u[j + (kms + 2) * u_dim1] -= refsum * v[m *
v_dim1 + 2];
u[j + (kms + 3) * u_dim1] -= refsum * v[m *
v_dim1 + 3];
/* L70: */
}
} else if (*wantz) {
/* ==== U is not accumulated, so update Z */
/* . now by multiplying by reflections */
/* . from the right. ==== */
i__7 = *ihiz;
for (j = *iloz; j <= i__7; ++j) {
refsum = v[m * v_dim1 + 1] * (z__[j + (k + 1) *
z_dim1] + v[m * v_dim1 + 2] * z__[j + (k
+ 2) * z_dim1] + v[m * v_dim1 + 3] * z__[
j + (k + 3) * z_dim1]);
z__[j + (k + 1) * z_dim1] -= refsum;
z__[j + (k + 2) * z_dim1] -= refsum * v[m *
v_dim1 + 2];
z__[j + (k + 3) * z_dim1] -= refsum * v[m *
v_dim1 + 3];
/* L80: */
}
}
}
/* L90: */
}
/* ==== Special case: 2-by-2 reflection (if needed) ==== */
k = krcol + (m22 - 1) * 3;
if (bmp22 && v[m22 * v_dim1 + 1] != 0.f) {
/* Computing MIN */
i__7 = *kbot, i__4 = k + 3;
i__5 = MIN(i__7,i__4);
for (j = jtop; j <= i__5; ++j) {
refsum = v[m22 * v_dim1 + 1] * (h__[j + (k + 1) * h_dim1]
+ v[m22 * v_dim1 + 2] * h__[j + (k + 2) * h_dim1])
;
h__[j + (k + 1) * h_dim1] -= refsum;
h__[j + (k + 2) * h_dim1] -= refsum * v[m22 * v_dim1 + 2];
/* L100: */
}
if (accum) {
kms = k - incol;
/* Computing MAX */
i__5 = 1, i__7 = *ktop - incol;
i__4 = kdu;
for (j = MAX(i__5,i__7); j <= i__4; ++j) {
refsum = v[m22 * v_dim1 + 1] * (u[j + (kms + 1) *
u_dim1] + v[m22 * v_dim1 + 2] * u[j + (kms +
2) * u_dim1]);
u[j + (kms + 1) * u_dim1] -= refsum;
u[j + (kms + 2) * u_dim1] -= refsum * v[m22 * v_dim1
+ 2];
/* L110: */
}
} else if (*wantz) {
i__4 = *ihiz;
for (j = *iloz; j <= i__4; ++j) {
refsum = v[m22 * v_dim1 + 1] * (z__[j + (k + 1) *
z_dim1] + v[m22 * v_dim1 + 2] * z__[j + (k +
2) * z_dim1]);
z__[j + (k + 1) * z_dim1] -= refsum;
z__[j + (k + 2) * z_dim1] -= refsum * v[m22 * v_dim1
+ 2];
/* L120: */
}
}
}
/* ==== Vigilant deflation check ==== */
mstart = mtop;
if (krcol + (mstart - 1) * 3 < *ktop) {
++mstart;
}
mend = mbot;
if (bmp22) {
++mend;
}
if (krcol == *kbot - 2) {
++mend;
}
i__4 = mend;
for (m = mstart; m <= i__4; ++m) {
/* Computing MIN */
i__5 = *kbot - 1, i__7 = krcol + (m - 1) * 3;
k = MIN(i__5,i__7);
/* ==== The following convergence test requires that */
/* . the tradition small-compared-to-nearby-diagonals */
/* . criterion and the Ahues & Tisseur (LAWN 122, 1997) */
/* . criteria both be satisfied. The latter improves */
/* . accuracy in some examples. Falling back on an */
/* . alternate convergence criterion when TST1 or TST2 */
/* . is zero (as done here) is traditional but probably */
/* . unnecessary. ==== */
if (h__[k + 1 + k * h_dim1] != 0.f) {
tst1 = (r__1 = h__[k + k * h_dim1], ABS(r__1)) + (r__2 =
h__[k + 1 + (k + 1) * h_dim1], ABS(r__2));
if (tst1 == 0.f) {
if (k >= *ktop + 1) {
tst1 += (r__1 = h__[k + (k - 1) * h_dim1], ABS(
r__1));
}
if (k >= *ktop + 2) {
tst1 += (r__1 = h__[k + (k - 2) * h_dim1], ABS(
r__1));
}
if (k >= *ktop + 3) {
tst1 += (r__1 = h__[k + (k - 3) * h_dim1], ABS(
r__1));
}
if (k <= *kbot - 2) {
tst1 += (r__1 = h__[k + 2 + (k + 1) * h_dim1],
ABS(r__1));
}
if (k <= *kbot - 3) {
tst1 += (r__1 = h__[k + 3 + (k + 1) * h_dim1],
ABS(r__1));
}
if (k <= *kbot - 4) {
tst1 += (r__1 = h__[k + 4 + (k + 1) * h_dim1],
ABS(r__1));
}
}
/* Computing MAX */
r__2 = smlnum, r__3 = ulp * tst1;
if ((r__1 = h__[k + 1 + k * h_dim1], ABS(r__1)) <= MAX(
r__2,r__3)) {
/* Computing MAX */
r__3 = (r__1 = h__[k + 1 + k * h_dim1], ABS(r__1)),
r__4 = (r__2 = h__[k + (k + 1) * h_dim1],
ABS(r__2));
h12 = MAX(r__3,r__4);
/* Computing MIN */
r__3 = (r__1 = h__[k + 1 + k * h_dim1], ABS(r__1)),
r__4 = (r__2 = h__[k + (k + 1) * h_dim1],
ABS(r__2));
h21 = MIN(r__3,r__4);
/* Computing MAX */
r__3 = (r__1 = h__[k + 1 + (k + 1) * h_dim1], ABS(
r__1)), r__4 = (r__2 = h__[k + k * h_dim1] -
h__[k + 1 + (k + 1) * h_dim1], ABS(r__2));
h11 = MAX(r__3,r__4);
/* Computing MIN */
r__3 = (r__1 = h__[k + 1 + (k + 1) * h_dim1], ABS(
r__1)), r__4 = (r__2 = h__[k + k * h_dim1] -
h__[k + 1 + (k + 1) * h_dim1], ABS(r__2));
h22 = MIN(r__3,r__4);
scl = h11 + h12;
tst2 = h22 * (h11 / scl);
/* Computing MAX */
r__1 = smlnum, r__2 = ulp * tst2;
if (tst2 == 0.f || h21 * (h12 / scl) <= MAX(r__1,
r__2)) {
h__[k + 1 + k * h_dim1] = 0.f;
}
}
}
/* L130: */
}
/* ==== Fill in the last row of each bulge. ==== */
/* Computing MIN */
i__4 = nbmps, i__5 = (*kbot - krcol - 1) / 3;
mend = MIN(i__4,i__5);
i__4 = mend;
for (m = mtop; m <= i__4; ++m) {
k = krcol + (m - 1) * 3;
refsum = v[m * v_dim1 + 1] * v[m * v_dim1 + 3] * h__[k + 4 + (
k + 3) * h_dim1];
h__[k + 4 + (k + 1) * h_dim1] = -refsum;
h__[k + 4 + (k + 2) * h_dim1] = -refsum * v[m * v_dim1 + 2];
h__[k + 4 + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 + 3];
/* L140: */
}
/* ==== End of near-the-diagonal bulge chase. ==== */
/* L150: */
}
/* ==== Use U (if accumulated) to update far-from-diagonal */
/* . entries in H. If required, use U to update Z as */
/* . well. ==== */
if (accum) {
if (*wantt) {
jtop = 1;
jbot = *n;
} else {
jtop = *ktop;
jbot = *kbot;
}
if (! blk22 || incol < *ktop || ndcol > *kbot || ns <= 2) {
/* ==== Updates not exploiting the 2-by-2 block */
/* . structure of U. K1 and NU keep track of */
/* . the location and size of U in the special */
/* . cases of introducing bulges and chasing */
/* . bulges off the bottom. In these special */
/* . cases and in case the number of shifts */
/* . is NS = 2, there is no 2-by-2 block */
/* . structure to exploit. ==== */
/* Computing MAX */
i__3 = 1, i__4 = *ktop - incol;
k1 = MAX(i__3,i__4);
/* Computing MAX */
i__3 = 0, i__4 = ndcol - *kbot;
nu = kdu - MAX(i__3,i__4) - k1 + 1;
/* ==== Horizontal Multiply ==== */
i__3 = jbot;
i__4 = *nh;
for (jcol = MIN(ndcol,*kbot) + 1; i__4 < 0 ? jcol >= i__3 :
jcol <= i__3; jcol += i__4) {
/* Computing MIN */
i__5 = *nh, i__7 = jbot - jcol + 1;
jlen = MIN(i__5,i__7);
sgemm_("C", "N", &nu, &jlen, &nu, &c_b8, &u[k1 + k1 *
u_dim1], ldu, &h__[incol + k1 + jcol * h_dim1],
ldh, &c_b7, &wh[wh_offset], ldwh);
slacpy_("ALL", &nu, &jlen, &wh[wh_offset], ldwh, &h__[
incol + k1 + jcol * h_dim1], ldh);
/* L160: */
}
/* ==== Vertical multiply ==== */
i__4 = MAX(*ktop,incol) - 1;
i__3 = *nv;
for (jrow = jtop; i__3 < 0 ? jrow >= i__4 : jrow <= i__4;
jrow += i__3) {
/* Computing MIN */
i__5 = *nv, i__7 = MAX(*ktop,incol) - jrow;
jlen = MIN(i__5,i__7);
sgemm_("N", "N", &jlen, &nu, &nu, &c_b8, &h__[jrow + (
incol + k1) * h_dim1], ldh, &u[k1 + k1 * u_dim1],
ldu, &c_b7, &wv[wv_offset], ldwv);
slacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &h__[
jrow + (incol + k1) * h_dim1], ldh);
/* L170: */
}
/* ==== Z multiply (also vertical) ==== */
if (*wantz) {
i__3 = *ihiz;
i__4 = *nv;
for (jrow = *iloz; i__4 < 0 ? jrow >= i__3 : jrow <= i__3;
jrow += i__4) {
/* Computing MIN */
i__5 = *nv, i__7 = *ihiz - jrow + 1;
jlen = MIN(i__5,i__7);
sgemm_("N", "N", &jlen, &nu, &nu, &c_b8, &z__[jrow + (
incol + k1) * z_dim1], ldz, &u[k1 + k1 *
u_dim1], ldu, &c_b7, &wv[wv_offset], ldwv);
slacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &z__[
jrow + (incol + k1) * z_dim1], ldz)
;
/* L180: */
}
}
} else {
/* ==== Updates exploiting U's 2-by-2 block structure. */
/* . (I2, I4, J2, J4 are the last rows and columns */
/* . of the blocks.) ==== */
i2 = (kdu + 1) / 2;
i4 = kdu;
j2 = i4 - i2;
j4 = kdu;
/* ==== KZS and KNZ deal with the band of zeros */
/* . along the diagonal of one of the triangular */
/* . blocks. ==== */
kzs = j4 - j2 - (ns + 1);
knz = ns + 1;
/* ==== Horizontal multiply ==== */
i__4 = jbot;
i__3 = *nh;
for (jcol = MIN(ndcol,*kbot) + 1; i__3 < 0 ? jcol >= i__4 :
jcol <= i__4; jcol += i__3) {
/* Computing MIN */
i__5 = *nh, i__7 = jbot - jcol + 1;
jlen = MIN(i__5,i__7);
/* ==== Copy bottom of H to top+KZS of scratch ==== */
/* (The first KZS rows get multiplied by zero.) ==== */
slacpy_("ALL", &knz, &jlen, &h__[incol + 1 + j2 + jcol *
h_dim1], ldh, &wh[kzs + 1 + wh_dim1], ldwh);
/* ==== Multiply by U21' ==== */
slaset_("ALL", &kzs, &jlen, &c_b7, &c_b7, &wh[wh_offset],
ldwh);
strmm_("L", "U", "C", "N", &knz, &jlen, &c_b8, &u[j2 + 1
+ (kzs + 1) * u_dim1], ldu, &wh[kzs + 1 + wh_dim1]
, ldwh);
/* ==== Multiply top of H by U11' ==== */
sgemm_("C", "N", &i2, &jlen, &j2, &c_b8, &u[u_offset],
ldu, &h__[incol + 1 + jcol * h_dim1], ldh, &c_b8,
&wh[wh_offset], ldwh);
/* ==== Copy top of H to bottom of WH ==== */
slacpy_("ALL", &j2, &jlen, &h__[incol + 1 + jcol * h_dim1]
, ldh, &wh[i2 + 1 + wh_dim1], ldwh);
/* ==== Multiply by U21' ==== */
strmm_("L", "L", "C", "N", &j2, &jlen, &c_b8, &u[(i2 + 1)
* u_dim1 + 1], ldu, &wh[i2 + 1 + wh_dim1], ldwh);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
sgemm_("C", "N", &i__5, &jlen, &i__7, &c_b8, &u[j2 + 1 + (
i2 + 1) * u_dim1], ldu, &h__[incol + 1 + j2 +
jcol * h_dim1], ldh, &c_b8, &wh[i2 + 1 + wh_dim1],
ldwh);
/* ==== Copy it back ==== */
slacpy_("ALL", &kdu, &jlen, &wh[wh_offset], ldwh, &h__[
incol + 1 + jcol * h_dim1], ldh);
/* L190: */
}
/* ==== Vertical multiply ==== */
i__3 = MAX(incol,*ktop) - 1;
i__4 = *nv;
for (jrow = jtop; i__4 < 0 ? jrow >= i__3 : jrow <= i__3;
jrow += i__4) {
/* Computing MIN */
i__5 = *nv, i__7 = MAX(incol,*ktop) - jrow;
jlen = MIN(i__5,i__7);
/* ==== Copy right of H to scratch (the first KZS */
/* . columns get multiplied by zero) ==== */
slacpy_("ALL", &jlen, &knz, &h__[jrow + (incol + 1 + j2) *
h_dim1], ldh, &wv[(kzs + 1) * wv_dim1 + 1], ldwv);
/* ==== Multiply by U21 ==== */
slaset_("ALL", &jlen, &kzs, &c_b7, &c_b7, &wv[wv_offset],
ldwv);
strmm_("R", "U", "N", "N", &jlen, &knz, &c_b8, &u[j2 + 1
+ (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1) *
wv_dim1 + 1], ldwv);
/* ==== Multiply by U11 ==== */
sgemm_("N", "N", &jlen, &i2, &j2, &c_b8, &h__[jrow + (
incol + 1) * h_dim1], ldh, &u[u_offset], ldu, &
c_b8, &wv[wv_offset], ldwv);
/* ==== Copy left of H to right of scratch ==== */
slacpy_("ALL", &jlen, &j2, &h__[jrow + (incol + 1) *
h_dim1], ldh, &wv[(i2 + 1) * wv_dim1 + 1], ldwv);
/* ==== Multiply by U21 ==== */
i__5 = i4 - i2;
strmm_("R", "L", "N", "N", &jlen, &i__5, &c_b8, &u[(i2 +
1) * u_dim1 + 1], ldu, &wv[(i2 + 1) * wv_dim1 + 1]
, ldwv);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
sgemm_("N", "N", &jlen, &i__5, &i__7, &c_b8, &h__[jrow + (
incol + 1 + j2) * h_dim1], ldh, &u[j2 + 1 + (i2 +
1) * u_dim1], ldu, &c_b8, &wv[(i2 + 1) * wv_dim1
+ 1], ldwv);
/* ==== Copy it back ==== */
slacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, &h__[
jrow + (incol + 1) * h_dim1], ldh);
/* L200: */
}
/* ==== Multiply Z (also vertical) ==== */
if (*wantz) {
i__4 = *ihiz;
i__3 = *nv;
for (jrow = *iloz; i__3 < 0 ? jrow >= i__4 : jrow <= i__4;
jrow += i__3) {
/* Computing MIN */
i__5 = *nv, i__7 = *ihiz - jrow + 1;
jlen = MIN(i__5,i__7);
/* ==== Copy right of Z to left of scratch (first */
/* . KZS columns get multiplied by zero) ==== */
slacpy_("ALL", &jlen, &knz, &z__[jrow + (incol + 1 +
j2) * z_dim1], ldz, &wv[(kzs + 1) * wv_dim1 +
1], ldwv);
/* ==== Multiply by U12 ==== */
slaset_("ALL", &jlen, &kzs, &c_b7, &c_b7, &wv[
wv_offset], ldwv);
strmm_("R", "U", "N", "N", &jlen, &knz, &c_b8, &u[j2
+ 1 + (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1)
* wv_dim1 + 1], ldwv);
/* ==== Multiply by U11 ==== */
sgemm_("N", "N", &jlen, &i2, &j2, &c_b8, &z__[jrow + (
incol + 1) * z_dim1], ldz, &u[u_offset], ldu,
&c_b8, &wv[wv_offset], ldwv);
/* ==== Copy left of Z to right of scratch ==== */
slacpy_("ALL", &jlen, &j2, &z__[jrow + (incol + 1) *
z_dim1], ldz, &wv[(i2 + 1) * wv_dim1 + 1],
ldwv);
/* ==== Multiply by U21 ==== */
i__5 = i4 - i2;
strmm_("R", "L", "N", "N", &jlen, &i__5, &c_b8, &u[(
i2 + 1) * u_dim1 + 1], ldu, &wv[(i2 + 1) *
wv_dim1 + 1], ldwv);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
sgemm_("N", "N", &jlen, &i__5, &i__7, &c_b8, &z__[
jrow + (incol + 1 + j2) * z_dim1], ldz, &u[j2
+ 1 + (i2 + 1) * u_dim1], ldu, &c_b8, &wv[(i2
+ 1) * wv_dim1 + 1], ldwv);
/* ==== Copy the result back to Z ==== */
slacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, &
z__[jrow + (incol + 1) * z_dim1], ldz);
/* L210: */
}
}
}
}
/* L220: */
}
/* ==== End of SLAQR5 ==== */
return 0;
} /* slaqr5_ */
/* Subroutine */ int sgehrd_(integer *n, integer *ilo, integer *ihi, real *a,
integer *lda, real *tau, real *work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
integer i__, j;
#ifdef LAPACK_DISABLE_MEMORY_HOGS
real t[1] /* was [65][64] */;
/** This function uses too much memory, so we stopped allocating the memory
* above and assert false here. */
assert(0 && "sgehrd_ was called. This function allocates too much"
" memory and has been disabled.");
#else
real t[4160] /* was [65][64] */;
#endif
integer ib;
real ei;
integer nb, nh, nx, iws, nbmin, iinfo;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *), strmm_(char *, char *, char *,
char *, integer *, integer *, real *, real *, integer *, real *,
integer *), saxpy_(integer *,
real *, real *, integer *, real *, integer *), sgehd2_(integer *,
integer *, integer *, real *, integer *, real *, real *, integer *
), slahr2_(integer *, integer *, integer *, real *, integer *,
real *, real *, integer *, real *, integer *), slarfb_(char *,
char *, char *, char *, integer *, integer *, integer *, real *,
integer *, real *, integer *, real *, integer *, real *, integer *
), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *);
integer ldwork, lwkopt;
logical lquery;
/* -- LAPACK routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SGEHRD reduces a real general matrix A to upper Hessenberg form H by */
/* an orthogonal similarity transformation: Q' * A * Q = H . */
/* Arguments */
/* ========= */
/* N (input) INTEGER */
/* The order of the matrix A. N >= 0. */
/* ILO (input) INTEGER */
/* IHI (input) INTEGER */
/* It is assumed that A is already upper triangular in rows */
/* and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally */
/* set by a previous call to SGEBAL; otherwise they should be */
/* set to 1 and N respectively. See Further Details. */
/* 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. */
/* A (input/output) REAL array, dimension (LDA,N) */
/* On entry, the N-by-N general matrix to be reduced. */
/* On exit, the upper triangle and the first subdiagonal of A */
/* are overwritten with the upper Hessenberg matrix H, and the */
/* elements below the first subdiagonal, with the array TAU, */
/* represent the orthogonal matrix Q as a product of elementary */
/* reflectors. See Further Details. */
/* LDA (input) INTEGER */
/* The leading dimension of the array A. LDA >= max(1,N). */
/* TAU (output) REAL array, dimension (N-1) */
/* The scalar factors of the elementary reflectors (see Further */
/* Details). Elements 1:ILO-1 and IHI:N-1 of TAU are set to */
/* zero. */
/* WORK (workspace/output) REAL array, dimension (LWORK) */
/* On exit, if INFO = 0, WORK(1) returns the optimal LWORK. */
/* LWORK (input) INTEGER */
/* The length of the array WORK. LWORK >= max(1,N). */
/* For optimum performance LWORK >= N*NB, where NB is the */
/* optimal blocksize. */
/* If LWORK = -1, then a workspace query is assumed; the routine */
/* only calculates the optimal size of the WORK array, returns */
/* this value as the first entry of the WORK array, and no error */
/* message related to LWORK is issued by XERBLA. */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value. */
/* Further Details */
/* =============== */
/* The matrix Q is represented as a product of (ihi-ilo) elementary */
/* reflectors */
/* Q = H(ilo) H(ilo+1) . . . H(ihi-1). */
/* Each H(i) has the form */
/* H(i) = I - tau * v * v' */
/* where tau is a real scalar, and v is a real vector with */
/* v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on */
/* exit in A(i+2:ihi,i), and tau in TAU(i). */
/* The contents of A are illustrated by the following example, with */
/* n = 7, ilo = 2 and ihi = 6: */
/* on entry, on exit, */
/* ( a a a a a a a ) ( a a h h h h a ) */
/* ( a a a a a a ) ( a h h h h a ) */
/* ( a a a a a a ) ( h h h h h h ) */
/* ( a a a a a a ) ( v2 h h h h h ) */
/* ( a a a a a a ) ( v2 v3 h h h h ) */
/* ( a a a a a a ) ( v2 v3 v4 h h h ) */
/* ( a ) ( a ) */
/* where a denotes an element of the original matrix A, h denotes a */
/* modified element of the upper Hessenberg matrix H, and vi denotes an */
/* element of the vector defining H(i). */
/* This file is a slight modification of LAPACK-3.0's SGEHRD */
/* subroutine incorporating improvements proposed by Quintana-Orti and */
/* Van de Geijn (2005). */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. Local Arrays .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters */
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
/* Computing MIN */
i__1 = 64, i__2 = ilaenv_(&c__1, "SGEHRD", " ", n, ilo, ihi, &c_n1);
nb = min(i__1,i__2);
lwkopt = *n * nb;
work[1] = (real) lwkopt;
lquery = *lwork == -1;
if (*n < 0) {
*info = -1;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -2;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*lwork < max(1,*n) && ! lquery) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SGEHRD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Set elements 1:ILO-1 and IHI:N-1 of TAU to zero */
i__1 = *ilo - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
tau[i__] = 0.f;
/* L10: */
}
i__1 = *n - 1;
for (i__ = max(1,*ihi); i__ <= i__1; ++i__) {
tau[i__] = 0.f;
/* L20: */
}
/* Quick return if possible */
nh = *ihi - *ilo + 1;
if (nh <= 1) {
work[1] = 1.f;
return 0;
}
/* Determine the block size */
/* Computing MIN */
i__1 = 64, i__2 = ilaenv_(&c__1, "SGEHRD", " ", n, ilo, ihi, &c_n1);
nb = min(i__1,i__2);
nbmin = 2;
iws = 1;
if (nb > 1 && nb < nh) {
/* Determine when to cross over from blocked to unblocked code */
/* (last block is always handled by unblocked code) */
/* Computing MAX */
i__1 = nb, i__2 = ilaenv_(&c__3, "SGEHRD", " ", n, ilo, ihi, &c_n1);
nx = max(i__1,i__2);
if (nx < nh) {
/* Determine if workspace is large enough for blocked code */
iws = *n * nb;
if (*lwork < iws) {
/* Not enough workspace to use optimal NB: determine the */
/* minimum value of NB, and reduce NB or force use of */
/* unblocked code */
/* Computing MAX */
i__1 = 2, i__2 = ilaenv_(&c__2, "SGEHRD", " ", n, ilo, ihi, &
c_n1);
nbmin = max(i__1,i__2);
if (*lwork >= *n * nbmin) {
nb = *lwork / *n;
} else {
nb = 1;
}
}
}
}
ldwork = *n;
if (nb < nbmin || nb >= nh) {
/* Use unblocked code below */
i__ = *ilo;
} else {
/* Use blocked code */
i__1 = *ihi - 1 - nx;
i__2 = nb;
for (i__ = *ilo; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = nb, i__4 = *ihi - i__;
ib = min(i__3,i__4);
/* Reduce columns i:i+ib-1 to Hessenberg form, returning the */
/* matrices V and T of the block reflector H = I - V*T*V' */
/* which performs the reduction, and also the matrix Y = A*V*T */
slahr2_(ihi, &i__, &ib, &a[i__ * a_dim1 + 1], lda, &tau[i__], t, &
c__65, &work[1], &ldwork);
/* Apply the block reflector H to A(1:ihi,i+ib:ihi) from the */
/* right, computing A := A - Y * V'. V(i+ib,ib-1) must be set */
/* to 1 */
ei = a[i__ + ib + (i__ + ib - 1) * a_dim1];
a[i__ + ib + (i__ + ib - 1) * a_dim1] = 1.f;
i__3 = *ihi - i__ - ib + 1;
sgemm_("No transpose", "Transpose", ihi, &i__3, &ib, &c_b25, &
work[1], &ldwork, &a[i__ + ib + i__ * a_dim1], lda, &
c_b26, &a[(i__ + ib) * a_dim1 + 1], lda);
a[i__ + ib + (i__ + ib - 1) * a_dim1] = ei;
/* Apply the block reflector H to A(1:i,i+1:i+ib-1) from the */
/* right */
i__3 = ib - 1;
strmm_("Right", "Lower", "Transpose", "Unit", &i__, &i__3, &c_b26,
&a[i__ + 1 + i__ * a_dim1], lda, &work[1], &ldwork);
i__3 = ib - 2;
for (j = 0; j <= i__3; ++j) {
saxpy_(&i__, &c_b25, &work[ldwork * j + 1], &c__1, &a[(i__ +
j + 1) * a_dim1 + 1], &c__1);
/* L30: */
}
/* Apply the block reflector H to A(i+1:ihi,i+ib:n) from the */
/* left */
i__3 = *ihi - i__;
i__4 = *n - i__ - ib + 1;
slarfb_("Left", "Transpose", "Forward", "Columnwise", &i__3, &
i__4, &ib, &a[i__ + 1 + i__ * a_dim1], lda, t, &c__65, &a[
i__ + 1 + (i__ + ib) * a_dim1], lda, &work[1], &ldwork);
/* L40: */
}
}
/* Use unblocked code to reduce the rest of the matrix */
sgehd2_(n, &i__, ihi, &a[a_offset], lda, &tau[1], &work[1], &iinfo);
work[1] = (real) iws;
return 0;
/* End of SGEHRD */
} /* sgehrd_ */
/* Main */
int main(int argc, char** argv)
{
if (argc!=5){
fprintf (stderr, "Usage: %s <sizeM> <sizeN> <sizeK> <Nb iter>\n",argv[0]);
exit(0);
}
const int M=strtol(argv[1],0,0);
const int N=strtol(argv[2],0,0);
const int K=strtol(argv[3],0,0);
const int NBITER=strtol(argv[4],0,0);
const int NA= M * K;
const int NB= K * N;
const int NC= M * N;
real* h_A;
real* h_B;
real* h_C;
const real alpha = 1.0f;
const real beta = 0.0f;
#ifdef NVIDIA
cublasStatus status;
real* d_A = 0;
real* d_B = 0;
real* d_C = 0;
#endif
#ifdef COMPARE
real* h_C_ref;
real error_norm;
real ref_norm;
real diff;
#endif
/* Allocate host memory for the matrices */
h_A = (real*)malloc(NA * sizeof(h_A[0]));
if (h_A == 0) {
fprintf (stderr, "!!!! host memory allocation error (A)\n");
return EXIT_FAILURE;
}
h_B = (real*)malloc(NB * sizeof(h_B[0]));
if (h_B == 0) {
fprintf (stderr, "!!!! host memory allocation error (B)\n");
return EXIT_FAILURE;
}
h_C = (real*)malloc(NC * sizeof(h_C[0]));
if (h_C == 0) {
fprintf (stderr, "!!!! host memory allocation error (C)\n");
return EXIT_FAILURE;
}
for (int i = 0; i < NA; ++i) h_A[i] = M_PI+(real)i;
for (int i = 0; i < NB; ++i) h_B[i] = M_PI+(real)i;
#ifdef NVIDIA
/* Initialize CUBLAS */
status = cublasInit();
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! CUBLAS initialization error\n");
return EXIT_FAILURE;
}
/* Allocate device memory for the matrices */
status = cublasAlloc(NA, sizeof(d_A[0]), (void**)&d_A);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device memory allocation error (A)\n");
return EXIT_FAILURE;
}
status = cublasAlloc(NB, sizeof(d_B[0]), (void**)&d_B);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device memory allocation error (B)\n");
return EXIT_FAILURE;
}
status = cublasAlloc(NC, sizeof(d_C[0]), (void**)&d_C);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device memory allocation error (C)\n");
return EXIT_FAILURE;
}
/* Initialize the device matrices with the host matrices */
status = cublasSetVector(NA, sizeof(h_A[0]), h_A, 1, d_A, 1);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device access error (write A)\n");
return EXIT_FAILURE;
}
status = cublasSetVector(NB, sizeof(h_B[0]), h_B, 1, d_B, 1);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device access error (write B)\n");
return EXIT_FAILURE;
}
status = cublasSetVector(NC, sizeof(h_C[0]), h_C, 1, d_C, 1);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device access error (write C)\n");
return EXIT_FAILURE;
}
/* Clear last error */
cublasGetError();
#endif
#ifdef COMPARE
/* Performs operation using plain C code */
for (int i=0;i<NBITER;i++)
c_xgemm(M,N,K, alpha, h_A, h_B, beta, h_C);
h_C_ref = h_C;
/* Allocate host memory for reading back the result from device memory */
h_C = (real*)malloc(NC * sizeof(h_C[0]));
if (h_C == 0) {
fprintf (stderr, "!!!! host memory allocation error (C)\n");
return EXIT_FAILURE;
}
#endif
#ifdef NVIDIA
/* Performs operation using cublas */
for (int i=0;i<NBITER;i++)
//We must Change the order of the parameter as cublas take
//matrix as colomn major and C matrix is row major
cublasSgemm('n', 'n', N, M, K, alpha, d_B, N, d_A, K, beta, d_C, N);
status = cublasGetError();
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! kernel execution error.\n");
return EXIT_FAILURE;
}
/* Read the result back */
status = cublasGetVector(NC, sizeof(h_C[0]), d_C, 1, h_C, 1);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device access error (read C)\n");
return EXIT_FAILURE;
}
#elif defined( CXGEMM )
for (int i=0;i<NBITER;i++)
c_xgemm(M,N,K, alpha, h_A, h_B, beta, h_C);
#else
char transa='N', transb='N';
for (int i=0;i<NBITER;i++)
sgemm_(&transb, &transa, &N, &M, &K, &alpha, h_B, &N, h_A, &K, &beta, h_C, &N);
#endif
#ifdef COMPARE
/* Check result against reference */
error_norm = 0;
ref_norm = 0;
for (int i = 0; i < NC; ++i) {
diff = h_C_ref[i] - h_C[i];
error_norm += diff * diff;
ref_norm += h_C_ref[i] * h_C_ref[i];
}
error_norm = (float)sqrt((double)error_norm);
ref_norm = (float)sqrt((double)ref_norm);
if (fabs(ref_norm) < 1e-7) {
fprintf (stderr, "!!!! reference norm is 0\n");
return EXIT_FAILURE;
}
printf( "Test %s\n", (error_norm / ref_norm < 1e-6f) ? "PASSED" : "FAILED");
#endif
/* Memory clean up */
free(h_A);
free(h_B);
free(h_C);
#ifdef NVIDIA
status = cublasFree(d_A);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! memory free error (A)\n");
return EXIT_FAILURE;
}
status = cublasFree(d_B);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! memory free error (B)\n");
return EXIT_FAILURE;
}
status = cublasFree(d_C);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! memory free error (C)\n");
return EXIT_FAILURE;
}
/* Shutdown */
status = cublasShutdown();
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! shutdown error (A)\n");
return EXIT_FAILURE;
}
#endif
// if (argc <= 1 || strcmp(argv[1], "-noprompt")) {
// printf("\nPress ENTER to exit...\n");
// getchar();
// }
return EXIT_SUCCESS;
}
/* Subroutine */ int sgetrf_(integer *m, integer *n, real *a, integer *lda,
integer *ipiv, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5, i__6;
/* Local variables */
integer i__, j, k, jb, nb, iinfo;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *), strsm_(char *, char *, char *,
char *, integer *, integer *, real *, real *, integer *, real *,
integer *), sgetf2_(integer *,
integer *, real *, integer *, integer *, integer *), xerbla_(char
*, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *);
extern /* Subroutine */ int slaswp_(integer *, real *, integer *, integer
*, integer *, integer *, integer *);
/* -- LAPACK routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* March 2008 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SGETRF computes an LU factorization of a general M-by-N matrix A */
/* using partial pivoting with row interchanges. */
/* The factorization has the form */
/* A = P * L * U */
/* where P is a permutation matrix, L is lower triangular with unit */
/* diagonal elements (lower trapezoidal if m > n), and U is upper */
/* triangular (upper trapezoidal if m < n). */
/* This is the left-looking Level 3 BLAS version of the algorithm. */
/* Arguments */
/* ========= */
/* M (input) INTEGER */
/* The number of rows of the matrix A. M >= 0. */
/* N (input) INTEGER */
/* The number of columns of the matrix A. N >= 0. */
/* A (input/output) REAL array, dimension (LDA,N) */
/* On entry, the M-by-N matrix to be factored. */
/* On exit, the factors L and U from the factorization */
/* A = P*L*U; the unit diagonal elements of L are not stored. */
/* LDA (input) INTEGER */
/* The leading dimension of the array A. LDA >= max(1,M). */
/* IPIV (output) INTEGER array, dimension (min(M,N)) */
/* The pivot indices; for 1 <= i <= min(M,N), row i of the */
/* matrix was interchanged with row IPIV(i). */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: if INFO = i, U(i,i) is exactly zero. The factorization */
/* has been completed, but the factor U is exactly */
/* singular, and division by zero will occur if it is used */
/* to solve a system of equations. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SGETRF", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "SGETRF", " ", m, n, &c_n1, &c_n1);
if (nb <= 1 || nb >= min(*m,*n)) {
/* Use unblocked code. */
sgetf2_(m, n, &a[a_offset], lda, &ipiv[1], info);
} else {
/* Use blocked code. */
i__1 = min(*m,*n);
i__2 = nb;
for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) {
/* Computing MIN */
i__3 = min(*m,*n) - j + 1;
jb = min(i__3,nb);
/* Update before factoring the current panel */
i__3 = j - nb;
i__4 = nb;
for (k = 1; i__4 < 0 ? k >= i__3 : k <= i__3; k += i__4) {
/* Apply interchanges to rows K:K+NB-1. */
i__5 = k + nb - 1;
slaswp_(&jb, &a[j * a_dim1 + 1], lda, &k, &i__5, &ipiv[1], &
c__1);
/* Compute block row of U. */
strsm_("Left", "Lower", "No transpose", "Unit", &nb, &jb, &
c_b15, &a[k + k * a_dim1], lda, &a[k + j * a_dim1],
lda);
/* Update trailing submatrix. */
i__5 = *m - k - nb + 1;
sgemm_("No transpose", "No transpose", &i__5, &jb, &nb, &
c_b18, &a[k + nb + k * a_dim1], lda, &a[k + j *
a_dim1], lda, &c_b15, &a[k + nb + j * a_dim1], lda);
/* L30: */
}
/* Factor diagonal and subdiagonal blocks and test for exact */
/* singularity. */
i__4 = *m - j + 1;
sgetf2_(&i__4, &jb, &a[j + j * a_dim1], lda, &ipiv[j], &iinfo);
/* Adjust INFO and the pivot indices. */
if (*info == 0 && iinfo > 0) {
*info = iinfo + j - 1;
}
/* Computing MIN */
i__3 = *m, i__5 = j + jb - 1;
i__4 = min(i__3,i__5);
for (i__ = j; i__ <= i__4; ++i__) {
ipiv[i__] = j - 1 + ipiv[i__];
/* L10: */
}
/* L20: */
}
/* Apply interchanges to the left-overs */
i__2 = min(*m,*n);
i__1 = nb;
for (k = 1; i__1 < 0 ? k >= i__2 : k <= i__2; k += i__1) {
i__4 = k - 1;
/* Computing MIN */
i__5 = k + nb - 1, i__6 = min(*m,*n);
i__3 = min(i__5,i__6);
slaswp_(&i__4, &a[a_dim1 + 1], lda, &k, &i__3, &ipiv[1], &c__1);
/* L40: */
}
/* Apply update to the M+1:N columns when N > M */
if (*n > *m) {
i__1 = *n - *m;
slaswp_(&i__1, &a[(*m + 1) * a_dim1 + 1], lda, &c__1, m, &ipiv[1],
&c__1);
i__1 = *m;
i__2 = nb;
for (k = 1; i__2 < 0 ? k >= i__1 : k <= i__1; k += i__2) {
/* Computing MIN */
i__4 = *m - k + 1;
jb = min(i__4,nb);
i__4 = *n - *m;
strsm_("Left", "Lower", "No transpose", "Unit", &jb, &i__4, &
c_b15, &a[k + k * a_dim1], lda, &a[k + (*m + 1) *
a_dim1], lda);
if (k + nb <= *m) {
i__4 = *m - k - nb + 1;
i__3 = *n - *m;
sgemm_("No transpose", "No transpose", &i__4, &i__3, &nb,
&c_b18, &a[k + nb + k * a_dim1], lda, &a[k + (*m
+ 1) * a_dim1], lda, &c_b15, &a[k + nb + (*m + 1)
* a_dim1], lda);
}
/* L50: */
}
}
}
return 0;
/* End of SGETRF */
} /* sgetrf_ */