      SUBROUTINE SCHKBD( NSIZES, MVAL, NVAL, NTYPES, DOTYPE, NRHS,
     $                   ISEED, THRESH, A, LDA, BD, BE, S1, S2, X, LDX,
     $                   Y, Z, Q, LDQ, PT, LDPT, U, VT, WORK, LWORK,
     $                   IWORK, NOUT, INFO )
*
*  -- LAPACK test routine (version 3.1) --
*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
*     November 2006
*
*     .. Scalar Arguments ..
      INTEGER            INFO, LDA, LDPT, LDQ, LDX, LWORK, NOUT, NRHS,
     $                   NSIZES, NTYPES
      REAL               THRESH
*     ..
*     .. Array Arguments ..
      LOGICAL            DOTYPE( * )
      INTEGER            ISEED( 4 ), IWORK( * ), MVAL( * ), NVAL( * )
      REAL               A( LDA, * ), BD( * ), BE( * ), PT( LDPT, * ),
     $                   Q( LDQ, * ), S1( * ), S2( * ), U( LDPT, * ),
     $                   VT( LDPT, * ), WORK( * ), X( LDX, * ),
     $                   Y( LDX, * ), Z( LDX, * )
*     ..
*
*  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) )
*
* ======================================================================
*
*     .. Parameters ..
      REAL               ZERO, ONE, TWO, HALF
      PARAMETER          ( ZERO = 0.0E0, ONE = 1.0E0, TWO = 2.0E0,
     $                   HALF = 0.5E0 )
      INTEGER            MAXTYP
      PARAMETER          ( MAXTYP = 16 )
*     ..
*     .. Local Scalars ..
      LOGICAL            BADMM, BADNN, BIDIAG
      CHARACTER          UPLO
      CHARACTER*3        PATH
      INTEGER            I, IINFO, IMODE, ITYPE, J, JCOL, JSIZE, JTYPE,
     $                   LOG2UI, M, MINWRK, MMAX, MNMAX, MNMIN, MQ,
     $                   MTYPES, N, NFAIL, NMAX, NTEST
      REAL               AMNINV, ANORM, COND, OVFL, RTOVFL, RTUNFL,
     $                   TEMP1, TEMP2, ULP, ULPINV, UNFL
*     ..
*     .. Local Arrays ..
      INTEGER            IDUM( 1 ), IOLDSD( 4 ), KMAGN( MAXTYP ),
     $                   KMODE( MAXTYP ), KTYPE( MAXTYP )
      REAL               DUM( 1 ), DUMMA( 1 ), RESULT( 19 )
*     ..
*     .. External Functions ..
      REAL               SLAMCH, SLARND
      EXTERNAL           SLAMCH, SLARND
*     ..
*     .. External Subroutines ..
      EXTERNAL           ALASUM, SBDSDC, SBDSQR, SBDT01, SBDT02, SBDT03,
     $                   SCOPY, SGEBRD, SGEMM, SLABAD, SLACPY, SLAHD2,
     $                   SLASET, SLATMR, SLATMS, SORGBR, SORT01, XERBLA
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          ABS, EXP, INT, LOG, MAX, MIN, SQRT
*     ..
*     .. Scalars in Common ..
      LOGICAL            LERR, OK
      CHARACTER*6        SRNAMT
      INTEGER            INFOT, NUNIT
*     ..
*     .. Common blocks ..
      COMMON             / INFOC / INFOT, NUNIT, OK, LERR
      COMMON             / SRNAMC / SRNAMT
*     ..
*     .. Data statements ..
      DATA               KTYPE / 1, 2, 5*4, 5*6, 3*9, 10 /
      DATA               KMAGN / 2*1, 3*1, 2, 3, 3*1, 2, 3, 1, 2, 3, 0 /
      DATA               KMODE / 2*0, 4, 3, 1, 4, 4, 4, 3, 1, 4, 4, 0,
     $                   0, 0, 0 /
*     ..
*     .. Executable Statements ..
*
*     Check for errors
*
      INFO = 0
*
      BADMM = .FALSE.
      BADNN = .FALSE.
      MMAX = 1
      NMAX = 1
      MNMAX = 1
      MINWRK = 1
      DO 10 J = 1, NSIZES
         MMAX = MAX( MMAX, MVAL( J ) )
         IF( MVAL( J ).LT.0 )
     $      BADMM = .TRUE.
         NMAX = MAX( NMAX, NVAL( J ) )
         IF( NVAL( J ).LT.0 )
     $      BADNN = .TRUE.
         MNMAX = MAX( MNMAX, MIN( MVAL( J ), NVAL( J ) ) )
         MINWRK = MAX( MINWRK, 3*( MVAL( J )+NVAL( J ) ),
     $            MVAL( J )*( MVAL( J )+MAX( MVAL( J ), NVAL( J ),
     $            NRHS )+1 )+NVAL( J )*MIN( NVAL( J ), MVAL( J ) ) )
   10 CONTINUE
*
*     Check for errors
*
      IF( NSIZES.LT.0 ) THEN
         INFO = -1
      ELSE IF( BADMM ) THEN
         INFO = -2
      ELSE IF( BADNN ) THEN
         INFO = -3
      ELSE IF( NTYPES.LT.0 ) THEN
         INFO = -4
      ELSE IF( NRHS.LT.0 ) THEN
         INFO = -6
      ELSE IF( LDA.LT.MMAX ) THEN
         INFO = -11
      ELSE IF( LDX.LT.MMAX ) THEN
         INFO = -17
      ELSE IF( LDQ.LT.MMAX ) THEN
         INFO = -21
      ELSE IF( LDPT.LT.MNMAX ) THEN
         INFO = -23
      ELSE IF( MINWRK.GT.LWORK ) THEN
         INFO = -27
      END IF
*
      IF( INFO.NE.0 ) THEN
         CALL XERBLA( 'SCHKBD', -INFO )
         RETURN
      END IF
*
*     Initialize constants
*
      PATH( 1: 1 ) = 'Single precision'
      PATH( 2: 3 ) = 'BD'
      NFAIL = 0
      NTEST = 0
      UNFL = SLAMCH( 'Safe minimum' )
      OVFL = SLAMCH( 'Overflow' )
      CALL SLABAD( UNFL, OVFL )
      ULP = SLAMCH( 'Precision' )
      ULPINV = ONE / ULP
      LOG2UI = INT( LOG( ULPINV ) / LOG( TWO ) )
      RTUNFL = SQRT( UNFL )
      RTOVFL = SQRT( OVFL )
      INFOT = 0
*
*     Loop over sizes, types
*
      DO 200 JSIZE = 1, NSIZES
         M = MVAL( JSIZE )
         N = NVAL( JSIZE )
         MNMIN = MIN( M, N )
         AMNINV = ONE / MAX( M, N, 1 )
*
         IF( NSIZES.NE.1 ) THEN
            MTYPES = MIN( MAXTYP, NTYPES )
         ELSE
            MTYPES = MIN( MAXTYP+1, NTYPES )
         END IF
*
         DO 190 JTYPE = 1, MTYPES
            IF( .NOT.DOTYPE( JTYPE ) )
     $         GO TO 190
*
            DO 20 J = 1, 4
               IOLDSD( J ) = ISEED( J )
   20       CONTINUE
*
            DO 30 J = 1, 14
               RESULT( J ) = -ONE
   30       CONTINUE
*
            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.GT.MAXTYP )
     $         GO TO 100
*
            ITYPE = KTYPE( JTYPE )
            IMODE = KMODE( JTYPE )
*
*           Compute norm
*
            GO TO ( 40, 50, 60 )KMAGN( JTYPE )
*
   40       CONTINUE
            ANORM = ONE
            GO TO 70
*
   50       CONTINUE
            ANORM = ( RTOVFL*ULP )*AMNINV
            GO TO 70
*
   60       CONTINUE
            ANORM = RTUNFL*MAX( M, N )*ULPINV
            GO TO 70
*
   70       CONTINUE
*
            CALL SLASET( 'Full', LDA, N, ZERO, ZERO, A, LDA )
            IINFO = 0
            COND = ULPINV
*
            BIDIAG = .FALSE.
            IF( ITYPE.EQ.1 ) THEN
*
*              Zero matrix
*
               IINFO = 0
*
            ELSE IF( ITYPE.EQ.2 ) THEN
*
*              Identity
*
               DO 80 JCOL = 1, MNMIN
                  A( JCOL, JCOL ) = ANORM
   80          CONTINUE
*
            ELSE IF( ITYPE.EQ.4 ) THEN
*
*              Diagonal Matrix, [Eigen]values Specified
*
               CALL SLATMS( MNMIN, MNMIN, 'S', ISEED, 'N', WORK, IMODE,
     $                      COND, ANORM, 0, 0, 'N', A, LDA,
     $                      WORK( MNMIN+1 ), IINFO )
*
            ELSE IF( ITYPE.EQ.5 ) THEN
*
*              Symmetric, eigenvalues specified
*
               CALL SLATMS( MNMIN, MNMIN, 'S', ISEED, 'S', WORK, IMODE,
     $                      COND, ANORM, M, N, 'N', A, LDA,
     $                      WORK( MNMIN+1 ), IINFO )
*
            ELSE IF( ITYPE.EQ.6 ) THEN
*
*              Nonsymmetric, singular values specified
*
               CALL SLATMS( M, N, 'S', ISEED, 'N', WORK, IMODE, COND,
     $                      ANORM, M, N, 'N', A, LDA, WORK( MNMIN+1 ),
     $                      IINFO )
*
            ELSE IF( ITYPE.EQ.7 ) THEN
*
*              Diagonal, random entries
*
               CALL SLATMR( MNMIN, MNMIN, 'S', ISEED, 'N', WORK, 6, ONE,
     $                      ONE, 'T', 'N', WORK( MNMIN+1 ), 1, ONE,
     $                      WORK( 2*MNMIN+1 ), 1, ONE, 'N', IWORK, 0, 0,
     $                      ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
*
            ELSE IF( ITYPE.EQ.8 ) THEN
*
*              Symmetric, random entries
*
               CALL SLATMR( MNMIN, MNMIN, 'S', ISEED, 'S', WORK, 6, ONE,
     $                      ONE, 'T', 'N', WORK( MNMIN+1 ), 1, ONE,
     $                      WORK( M+MNMIN+1 ), 1, ONE, 'N', IWORK, M, N,
     $                      ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
*
            ELSE IF( ITYPE.EQ.9 ) THEN
*
*              Nonsymmetric, random entries
*
               CALL SLATMR( M, N, 'S', ISEED, 'N', WORK, 6, ONE, ONE,
     $                      'T', 'N', WORK( MNMIN+1 ), 1, ONE,
     $                      WORK( M+MNMIN+1 ), 1, ONE, 'N', IWORK, M, N,
     $                      ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
*
            ELSE IF( ITYPE.EQ.10 ) THEN
*
*              Bidiagonal, random entries
*
               TEMP1 = -TWO*LOG( ULP )
               DO 90 J = 1, MNMIN
                  BD( J ) = EXP( TEMP1*SLARND( 2, ISEED ) )
                  IF( J.LT.MNMIN )
     $               BE( J ) = EXP( TEMP1*SLARND( 2, ISEED ) )
   90          CONTINUE
*
               IINFO = 0
               BIDIAG = .TRUE.
               IF( M.GE.N ) THEN
                  UPLO = 'U'
               ELSE
                  UPLO = 'L'
               END IF
            ELSE
               IINFO = 1
            END IF
*
            IF( IINFO.EQ.0 ) THEN
*
*              Generate Right-Hand Side
*
               IF( BIDIAG ) THEN
                  CALL SLATMR( MNMIN, NRHS, 'S', ISEED, 'N', WORK, 6,
     $                         ONE, ONE, 'T', 'N', WORK( MNMIN+1 ), 1,
     $                         ONE, WORK( 2*MNMIN+1 ), 1, ONE, 'N',
     $                         IWORK, MNMIN, NRHS, ZERO, ONE, 'NO', Y,
     $                         LDX, IWORK, IINFO )
               ELSE
                  CALL SLATMR( M, NRHS, 'S', ISEED, 'N', WORK, 6, ONE,
     $                         ONE, 'T', 'N', WORK( M+1 ), 1, ONE,
     $                         WORK( 2*M+1 ), 1, ONE, 'N', IWORK, M,
     $                         NRHS, ZERO, ONE, 'NO', X, LDX, IWORK,
     $                         IINFO )
               END IF
            END IF
*
*           Error Exit
*
            IF( IINFO.NE.0 ) THEN
               WRITE( NOUT, FMT = 9998 )'Generator', IINFO, M, N,
     $            JTYPE, IOLDSD
               INFO = ABS( IINFO )
               RETURN
            END IF
*
  100       CONTINUE
*
*           Call SGEBRD and SORGBR to compute B, Q, and P, do tests.
*
            IF( .NOT.BIDIAG ) THEN
*
*              Compute transformations to reduce A to bidiagonal form:
*              B := Q' * A * P.
*
               CALL SLACPY( ' ', M, N, A, LDA, Q, LDQ )
               CALL SGEBRD( M, N, Q, LDQ, BD, BE, WORK, WORK( MNMIN+1 ),
     $                      WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
*
*              Check error code from SGEBRD.
*
               IF( IINFO.NE.0 ) THEN
                  WRITE( NOUT, FMT = 9998 )'SGEBRD', IINFO, M, N,
     $               JTYPE, IOLDSD
                  INFO = ABS( IINFO )
                  RETURN
               END IF
*
               CALL SLACPY( ' ', M, N, Q, LDQ, PT, LDPT )
               IF( M.GE.N ) THEN
                  UPLO = 'U'
               ELSE
                  UPLO = 'L'
               END IF
*
*              Generate Q
*
               MQ = M
               IF( NRHS.LE.0 )
     $            MQ = MNMIN
               CALL SORGBR( 'Q', M, MQ, N, Q, LDQ, WORK,
     $                      WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
*
*              Check error code from SORGBR.
*
               IF( IINFO.NE.0 ) THEN
                  WRITE( NOUT, FMT = 9998 )'SORGBR(Q)', IINFO, M, N,
     $               JTYPE, IOLDSD
                  INFO = ABS( IINFO )
                  RETURN
               END IF
*
*              Generate P'
*
               CALL SORGBR( 'P', MNMIN, N, M, PT, LDPT, WORK( MNMIN+1 ),
     $                      WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
*
*              Check error code from SORGBR.
*
               IF( IINFO.NE.0 ) THEN
                  WRITE( NOUT, FMT = 9998 )'SORGBR(P)', IINFO, M, N,
     $               JTYPE, IOLDSD
                  INFO = ABS( IINFO )
                  RETURN
               END IF
*
*              Apply Q' to an M by NRHS matrix X:  Y := Q' * X.
*
               CALL SGEMM( 'Transpose', 'No transpose', M, NRHS, M, ONE,
     $                     Q, LDQ, X, LDX, ZERO, Y, LDX )
*
*              Test 1:  Check the decomposition A := Q * B * PT
*                   2:  Check the orthogonality of Q
*                   3:  Check the orthogonality of PT
*
               CALL SBDT01( M, N, 1, A, LDA, Q, LDQ, BD, BE, PT, LDPT,
     $                      WORK, RESULT( 1 ) )
               CALL SORT01( 'Columns', M, MQ, Q, LDQ, WORK, LWORK,
     $                      RESULT( 2 ) )
               CALL SORT01( 'Rows', MNMIN, N, PT, LDPT, WORK, LWORK,
     $                      RESULT( 3 ) )
            END IF
*
*           Use SBDSQR to form the SVD of the bidiagonal matrix B:
*           B := U * S1 * VT, and compute Z = U' * Y.
*
            CALL SCOPY( MNMIN, BD, 1, S1, 1 )
            IF( MNMIN.GT.0 )
     $         CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
            CALL SLACPY( ' ', M, NRHS, Y, LDX, Z, LDX )
            CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, U, LDPT )
            CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, VT, LDPT )
*
            CALL SBDSQR( UPLO, MNMIN, MNMIN, MNMIN, NRHS, S1, WORK, VT,
     $                   LDPT, U, LDPT, Z, LDX, WORK( MNMIN+1 ), IINFO )
*
*           Check error code from SBDSQR.
*
            IF( IINFO.NE.0 ) THEN
               WRITE( NOUT, FMT = 9998 )'SBDSQR(vects)', IINFO, M, N,
     $            JTYPE, IOLDSD
               INFO = ABS( IINFO )
               IF( IINFO.LT.0 ) THEN
                  RETURN
               ELSE
                  RESULT( 4 ) = ULPINV
                  GO TO 170
               END IF
            END IF
*
*           Use SBDSQR to compute only the singular values of the
*           bidiagonal matrix B;  U, VT, and Z should not be modified.
*
            CALL SCOPY( MNMIN, BD, 1, S2, 1 )
            IF( MNMIN.GT.0 )
     $         CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
*
            CALL SBDSQR( UPLO, MNMIN, 0, 0, 0, S2, WORK, VT, LDPT, U,
     $                   LDPT, Z, LDX, WORK( MNMIN+1 ), IINFO )
*
*           Check error code from SBDSQR.
*
            IF( IINFO.NE.0 ) THEN
               WRITE( NOUT, FMT = 9998 )'SBDSQR(values)', IINFO, M, N,
     $            JTYPE, IOLDSD
               INFO = ABS( IINFO )
               IF( IINFO.LT.0 ) THEN
                  RETURN
               ELSE
                  RESULT( 9 ) = ULPINV
                  GO TO 170
               END IF
            END IF
*
*           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
*
            CALL SBDT03( UPLO, MNMIN, 1, BD, BE, U, LDPT, S1, VT, LDPT,
     $                   WORK, RESULT( 4 ) )
            CALL SBDT02( MNMIN, NRHS, Y, LDX, Z, LDX, U, LDPT, WORK,
     $                   RESULT( 5 ) )
            CALL SORT01( 'Columns', MNMIN, MNMIN, U, LDPT, WORK, LWORK,
     $                   RESULT( 6 ) )
            CALL SORT01( 'Rows', MNMIN, MNMIN, VT, LDPT, WORK, LWORK,
     $                   RESULT( 7 ) )
*
*           Test 8:  Check that the singular values are sorted in
*                    non-increasing order and are non-negative
*
            RESULT( 8 ) = ZERO
            DO 110 I = 1, MNMIN - 1
               IF( S1( I ).LT.S1( I+1 ) )
     $            RESULT( 8 ) = ULPINV
               IF( S1( I ).LT.ZERO )
     $            RESULT( 8 ) = ULPINV
  110       CONTINUE
            IF( MNMIN.GE.1 ) THEN
               IF( S1( MNMIN ).LT.ZERO )
     $            RESULT( 8 ) = ULPINV
            END IF
*
*           Test 9:  Compare SBDSQR with and without singular vectors
*
            TEMP2 = ZERO
*
            DO 120 J = 1, MNMIN
               TEMP1 = ABS( S1( J )-S2( J ) ) /
     $                 MAX( SQRT( UNFL )*MAX( S1( 1 ), ONE ),
     $                 ULP*MAX( ABS( S1( J ) ), ABS( S2( J ) ) ) )
               TEMP2 = MAX( TEMP1, TEMP2 )
  120       CONTINUE
*
            RESULT( 9 ) = TEMP2
*
*           Test 10:  Sturm sequence test of singular values
*                     Go up by factors of two until it succeeds
*
            TEMP1 = THRESH*( HALF-ULP )
*
            DO 130 J = 0, LOG2UI
*               CALL SSVDCH( MNMIN, BD, BE, S1, TEMP1, IINFO )
               IF( IINFO.EQ.0 )
     $            GO TO 140
               TEMP1 = TEMP1*TWO
  130       CONTINUE
*
  140       CONTINUE
            RESULT( 10 ) = TEMP1
*
*           Use SBDSQR to form the decomposition A := (QU) S (VT PT)
*           from the bidiagonal form A := Q B PT.
*
            IF( .NOT.BIDIAG ) THEN
               CALL SCOPY( MNMIN, BD, 1, S2, 1 )
               IF( MNMIN.GT.0 )
     $            CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
*
               CALL SBDSQR( UPLO, MNMIN, N, M, NRHS, S2, WORK, PT, LDPT,
     $                      Q, LDQ, Y, 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
*
               CALL SBDT01( M, N, 0, A, LDA, Q, LDQ, S2, DUMMA, PT,
     $                      LDPT, WORK, RESULT( 11 ) )
               CALL SBDT02( M, NRHS, X, LDX, Y, LDX, Q, LDQ, WORK,
     $                      RESULT( 12 ) )
               CALL SORT01( 'Columns', M, MQ, Q, LDQ, WORK, LWORK,
     $                      RESULT( 13 ) )
               CALL SORT01( 'Rows', MNMIN, N, PT, LDPT, WORK, LWORK,
     $                      RESULT( 14 ) )
            END IF
*
*           Use SBDSDC to form the SVD of the bidiagonal matrix B:
*           B := U * S1 * VT
*
            CALL SCOPY( MNMIN, BD, 1, S1, 1 )
            IF( MNMIN.GT.0 )
     $         CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
            CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, U, LDPT )
            CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, VT, LDPT )
*
            CALL SBDSDC( UPLO, 'I', MNMIN, S1, WORK, U, LDPT, VT, LDPT,
     $                   DUM, IDUM, WORK( MNMIN+1 ), IWORK, IINFO )
*
*           Check error code from SBDSDC.
*
            IF( IINFO.NE.0 ) THEN
               WRITE( NOUT, FMT = 9998 )'SBDSDC(vects)', IINFO, M, N,
     $            JTYPE, IOLDSD
               INFO = ABS( IINFO )
               IF( IINFO.LT.0 ) THEN
                  RETURN
               ELSE
                  RESULT( 15 ) = ULPINV
                  GO TO 170
               END IF
            END IF
*
*           Use SBDSDC to compute only the singular values of the
*           bidiagonal matrix B;  U and VT should not be modified.
*
            CALL SCOPY( MNMIN, BD, 1, S2, 1 )
            IF( MNMIN.GT.0 )
     $         CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
*
            CALL SBDSDC( UPLO, 'N', MNMIN, S2, WORK, DUM, 1, DUM, 1,
     $                   DUM, IDUM, WORK( MNMIN+1 ), IWORK, IINFO )
*
*           Check error code from SBDSDC.
*
            IF( IINFO.NE.0 ) THEN
               WRITE( NOUT, FMT = 9998 )'SBDSDC(values)', IINFO, M, N,
     $            JTYPE, IOLDSD
               INFO = ABS( IINFO )
               IF( IINFO.LT.0 ) THEN
                  RETURN
               ELSE
                  RESULT( 18 ) = ULPINV
                  GO TO 170
               END IF
            END IF
*
*           Test 15:  Check the decomposition B := U * S1 * VT
*                16:  Check the orthogonality of U
*                17:  Check the orthogonality of VT
*
            CALL SBDT03( UPLO, MNMIN, 1, BD, BE, U, LDPT, S1, VT, LDPT,
     $                   WORK, RESULT( 15 ) )
            CALL SORT01( 'Columns', MNMIN, MNMIN, U, LDPT, WORK, LWORK,
     $                   RESULT( 16 ) )
            CALL SORT01( 'Rows', MNMIN, MNMIN, VT, LDPT, WORK, LWORK,
     $                   RESULT( 17 ) )
*
*           Test 18:  Check that the singular values are sorted in
*                     non-increasing order and are non-negative
*
            RESULT( 18 ) = ZERO
            DO 150 I = 1, MNMIN - 1
               IF( S1( I ).LT.S1( I+1 ) )
     $            RESULT( 18 ) = ULPINV
               IF( S1( I ).LT.ZERO )
     $            RESULT( 18 ) = ULPINV
  150       CONTINUE
            IF( MNMIN.GE.1 ) THEN
               IF( S1( MNMIN ).LT.ZERO )
     $            RESULT( 18 ) = ULPINV
            END IF
*
*           Test 19:  Compare SBDSQR with and without singular vectors
*
            TEMP2 = ZERO
*
            DO 160 J = 1, MNMIN
               TEMP1 = ABS( S1( J )-S2( J ) ) /
     $                 MAX( SQRT( UNFL )*MAX( S1( 1 ), ONE ),
     $                 ULP*MAX( ABS( S1( 1 ) ), ABS( S2( 1 ) ) ) )
               TEMP2 = MAX( TEMP1, TEMP2 )
  160       CONTINUE
*
            RESULT( 19 ) = TEMP2
*
*           End of Loop -- Check for RESULT(j) > THRESH
*
  170       CONTINUE
            DO 180 J = 1, 19
               IF( RESULT( J ).GE.THRESH ) THEN
                  IF( NFAIL.EQ.0 )
     $               CALL SLAHD2( NOUT, PATH )
                  WRITE( NOUT, FMT = 9999 )M, N, JTYPE, IOLDSD, J,
     $               RESULT( J )
                  NFAIL = NFAIL + 1
               END IF
  180       CONTINUE
            IF( .NOT.BIDIAG ) THEN
               NTEST = NTEST + 19
            ELSE
               NTEST = NTEST + 5
            END IF
*
  190    CONTINUE
  200 CONTINUE
*
*     Summary
*
      CALL ALASUM( PATH, NOUT, NFAIL, NTEST, 0 )
*
      RETURN
*
*     End of SCHKBD
*
 9999 FORMAT( ' M=', I5, ', N=', I5, ', type ', I2, ', seed=',
     $      4( I4, ',' ), ' test(', I2, ')=', G11.4 )
 9998 FORMAT( ' SCHKBD: ', A, ' returned INFO=', I6, '.', / 9X, 'M=',
     $      I6, ', N=', I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ),
     $      I5, ')' )
*
      END
