ctorization of a symmetric matrix A in packed storage.  It is typical to follow a call to xSPFA with a call to xSPSL to solve Ax = b or to xSPDI to compute the determinant, inverse, and inertia of A.
sspgst		sspgst (3p)	- reduce a real symmetric-definite generalized eigenproblem to standard form, using packed storage
sspgv		sspgv (3p)	- compute all the eigenvalues and, optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
sspmv		sspmv (3p)	- perform the matrix-vector operation	y := alpha*A*x + beta*y
sspr		sspr (3p)	- perform the symmetric rank 1 operation   A := alpha*x*x' + A
sspr2		sspr2 (3p)	- perform the symmetric rank 2 operation   A := alpha*x*y' + alpha*y*x' + A
ssprfs		ssprfs (3p)	- improve the computed solution to a system of linear equations when the coefficient matrix is symmetric indefinite and packed, and provides error bounds and backward error estimates for the solution
sspsl		sspsl (3p)	- solve the linear system Ax = b for a symmetric matrix A in packed storage, which has been UDU-factored by xSPCO or xSPFA, and vectors b and x.
sspsv		sspsv (3p)	- compute the solution to a real system of linear equations  A * X = B,
sspsvx		sspsvx (3p)	- use the diagonal pivoting factorization A = U*D*U**T or A = L*D*L**T to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N symmetric matrix stored in packed format and X and B are N-by-NRHS matrices
ssptrd		ssptrd (3p)	- reduce a real symmetric matrix A stored in packed form to symmetric tridiagonal form T by an orthogonal similarity transformation
ssptrf		ssptrf (3p)	- compute the factorization of a real symmetric matrix A stored in packed format using the Bunch-Kaufman diagonal pivoting method
ssptri		ssptri (3p)	- compute the inverse of a real symmetric indefinite matrix A in packed storage using the factorization A = U*D*U**T or A = L*D*L**T computed by SSPTRF
ssptrs		ssptrs (3p)	- solve a system of linear equations A*X = B with a real symmetric matrix A stored in packed format using the factorization A = U*D*U**T or A = L*D*L**T computed by SSPTRF
sstebz		sstebz (3p)	- compute the eigenvalues of a symmetric tridiagonal matrix T
sstedc		sstedc (3p)	- compute all eigenvalues and, optionally, eigenvectors of a symmetric tridiagonal matrix using the divide and conquer method
sstein		sstein (3p)	- compute the eigenvectors of a real symmetric tridiagonal matrix T corresponding to specified eigenvalues, using inverse iteration
ssteqr		ssteqr (3p)	- compute all eigenvalues and, optionally, eigenvectors of a symmetric tridiagonal matrix using the implicit QL or QR method
ssterf		ssterf (3p)	- compute all eigenvalues of a symmetric tridiagonal matrix using the Pal-Walker-Kahan variant of the QL or QR algorithm
sstev		sstev (3p)	- compute all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix A
sstevd		sstevd (3p)	- compute all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix
sstevx		sstevx (3p)	- compute selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix A
ssvdc		ssvdc (3p)	- compute the singular value decomposition of a general matrix A.
sswap		sswap (3p)	- Exchange vectors x and y.
ssycon		ssycon (3p)	- estimate the reciprocal of the condition number (in the 1-norm) of a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
ssyev		ssyev (3p)	- compute all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A
ssyevd		ssyevd (3p)	- compute all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A
ssyevx		ssyevx (3p)	- compute selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix A
ssygs2		ssygs2 (3p)	- reduce a real symmetric-definite generalized eigenproblem to standard form
ssygst		ssygst (3p)	- reduce a real symmetric-definite generalized eigenproblem to standard form
ssygv		ssygv (3p)	- compute all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
ssymm		ssymm (3p)	- perform one of the matrix-matrix operations	C := alpha*A*B + beta*C or C := alpha*B*A + beta*C
ssymv		ssymv (3p)	- perform the matrix-vector operation	y := alpha*A*x + beta*y
ssyr		ssyr (3p)	- perform the symmetric rank 1 operation   A := alpha*x*x' + A
ssyr2		ssyr2 (3p)	- perform the symmetric rank 2 operation   A := alpha*x*y' + alpha*y*x' + A
ssyr2k		ssyr2k (3p)	- perform one of the symmetric rank 2k operations   C := alpha*A*B' + alpha*B*A' + beta*C or C := alpha*A'*B + alpha*B'*A + beta*C
ssyrfs		ssyrfs (3p)	- improve the computed solution to a system of linear equations when the coefficient matrix is symmetric indefinite, and provides error bounds and backward error estimates for the solution
ssyrk		ssyrk (3p)	- perform one of the symmetric rank k operations   C := alpha*A*A' + beta*C or C := alpha*A'*A + beta*C
ssysv		ssysv (3p)	- compute the solution to a real system of linear equations  A * X = B,
ssysvx		ssysvx (3p)	- use the diagonal pivoting factorization to compute the solution to a real system of linear equations A * X = B,
ssytd2		ssytd2 (3p)	- reduce a real symmetric matrix A to symmetric tridiagonal form T by an orthogonal similarity transformation
ssytf2		ssytf2 (3p)	- compute the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
ssytrd		ssytrd (3p)	- reduce a real symmetric matrix A to real symmetric tridiagonal form T by an orthogonal similarity transformation
ssytrf		ssytrf (3p)	- compute the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
ssytri		ssytri (3p)	- compute the inverse of a real symmetric indefinite matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
ssytrs		ssytrs (3p)	- solve a system of linear equations A*X = B with a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
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