A P P E N D I X A - Sun Performance Library Routines

A P P E N D I X A

Sun Performance Library Routines

This appendix lists the Sun Performance Library routines by library, routine name, and function.

For a description of the function and a listing of the Fortran and C interfaces, refer to the section 3P man pages for the individual routines. For example, to display the man page for the SBDSQR routine, type man -s 3P sbdsqr. The man page routine names use lowercase letters.

For many routines, separate routines exist that operate on different data types. Rather than list each routine separately, a lowercase x is used in a routine name to denote single, double, complex, and double complex data types. For example, the routine xBDSQR is available as four routines that operate with the following data types:

SBDSQR - Single data type

BBDSQR - Double data type

CBDSQR - Complex data type

ZBDSQR - Double complex data type

If a routine name is not available for S, B, C, and Z, the x prefix will not be used and each routine name will be listed.

LAPACK Routines

TABLE A-1 lists the Sun Performance Library LAPACK routines. (P) denotes routines that are parallelized..

TABLE A-1 LAPACK (Linear Algebra Package) Routines
Routine	Function
Bidiagonal Matrix
`SBDSDC` or `DBDSDC`	Computes the singular value decomposition (SVD) of a bidirectional matrix, using a divide and conquer method.
x`BDSQR`	Computes SVD of real upper or lower bidiagonal matrix, using the bidirectional QR algorithm.
Diagonal Matrix
`SDISNA` or `DDISNA`	Computes the reciprocal condition numbers for eigenvectors of real symmetric or complex Hermitian matrix.
General Band Matrix
x`GBBRD`	Reduces real or complex general band matrix to upper bidiagonal form.
x`GBCON`	Estimates the reciprocal of the condition number of general band matrix using LU factorization.
x`GBEQU`	Computes row and column scalings to equilibrate a general band matrix and reduce its condition number.
x`GBRFS`	Refines solution to general banded system of linear equations.
x`GBSV`	Solves a general banded system of linear equations (simple driver).
x`GBSVX`	Solves a general banded system of linear equations (expert driver).
x`GBTRF`	LU factorization of a general band matrix using partial pivoting with row interchanges.
x`GBTRS` (P)	Solves a general banded system of linear equations, using the factorization computed by x`GBTRF`.
General Matrix (Unsymmetric or Rectangular)
x`GEBAK`	Forms the right or left eigenvectors of a general matrix by backward transformation on the computed eigenvectors of the balanced matrix output by x`GEBAL.`
x`GEBAL`	Balances a general matrix.
x`GEBRD`	Reduces a general matrix to upper or lower bidiagonal form by an orthogonal transformation.
x`GECON`	Estimates the reciprocal of the condition number of a general matrix, using the factorization computed by x`GETRF`.
x`GEEQU`	Computes row and column scalings intended to equilibrate a general rectangular matrix and reduce its condition number.
x`GEES`	Computes the eigenvalues and Schur factorization of a general matrix (simple driver).
x`GEESX`	Computes the eigenvalues and Schur factorization of a general matrix (expert driver).
x`GEEV`	Computes the eigenvalues and left and right eigenvectors of a general matrix (simple driver).
x`GEEVX`	Computes the eigenvalues and left and right eigenvectors of a general matrix (expert driver).
x`GEGS`	Depreciated routine replaced by x`GGES`.
x`GEGV`	Depreciated routine replaced by x`GGEV`.
x`GEHRD`	Reduces a general matrix to upper Hessenberg form by an orthogonal similarity transformation.
x`GELQF` (P)	Computes LQ factorization of a general rectangular matrix.
x`GELS`	Computes the least squares solution to an over-determined system of linear equations using a QR or LQ factorization of A.
x`GELSD`	Computes the least squares solution to an over-determined system of linear equations using a divide and conquer method using a QR or LQ factorization of A.
x`GELSS`	Computes the minimum-norm solution to a linear least squares problem by using the SVD of a general rectangular matrix (simple driver).
x`GELSX`	Depreciated routine replaced by x`SELSY`.
x`GELSY`	Computes the minimum-norm solution to a linear least squares problem using a complete orthogonal factorization.
x`GEQLF` (P)	Computes QL factorization of a general rectangular matrix.
x`GEQP3`	Computes QR factorization of general rectangular matrix using Level 3 BLAS.
x`GEQPF`	Depreciated routine replaced by x`GEQP3`.
x`GEQRF` (P)	Computes QR factorization of a general rectangular matrix.
x`GERFS`	Refines solution to a system of linear equations.
x`GERQF` (P)	Computes RQ factorization of a general rectangular matrix.
x`GESDD`	Computes SVD of general rectangular matrix using a divide and conquer method.
x`GESV`	Solves a general system of linear equations (simple driver).
x`GESVX`	Solves a general system of linear equations (expert driver).
x`GESVD`	Computes SVD of general rectangular matrix.
x`GETRF` (P)	Computes an LU factorization of a general rectangular matrix using partial pivoting with row interchanges.
x`GETRI`	Computes inverse of a general matrix using the factorization computed by x`GETRF`.
x`GETRS` (P)	Solves a general system of linear equations using the factorization computed by x`GETRF.`
General Matrix-Generalized Problem (Pair of General Matrices)
x`GGBAK`	Forms the right or left eigenvectors of a generalized eigenvalue problem based on the output by x`GGBAL`.
x`GGBAL`	Balances a pair of general matrices for the generalized eigenvalue problem.
x`GGES`	Computes the generalized eigenvalues, Schur form, and left and/or right Schur vectors for two nonsymmetric matrices.
x`GGESX`	Computes the generalized eigenvalues, Schur form, and left and/or right Schur vectors.
x`GGEV`	Computes the generalized eigenvalues and the left and/or right generalized eigenvalues for two nonsymmetric matrices.
x`GGEVX`	Computes the generalized eigenvalues and the left and/or right generalized eigenvectors.
x`GGGLM`	Solves the GLM (Generalized Linear Regression Model) using the GQR (Generalized QR) factorization.
x`GGHRD`	Reduces two matrices to generalized upper Hessenberg form using orthogonal transformations.
x`GGLSE`	Solves the LSE (Constrained Linear Least Squares Problem) using the GRQ (Generalized RQ) factorization.
x`GGQRF`	Computes generalized QR factorization of two matrices.
x`GGRQF`	Computes generalized RQ factorization of two matrices.
x`GGSVD`	Computes the generalized singular value decomposition.
x`GGSVP`	Computes an orthogonal or unitary matrix as a preprocessing step for calculating the generalized singular value decomposition.
General Tridiagonal Matrix
x`GTCON`	Estimates the reciprocal of the condition number of a tridiagonal matrix, using the LU factorization as computed by x`GTTRF`.
x`GTRFS`	Refines solution to a general tridiagonal system of linear equations.
x`GTSV`	Solves a general tridiagonal system of linear equations (simple driver).
x`GTSVX`	Solves a general tridiagonal system of linear equations (expert driver).
x`GTTRF`	Computes an LU factorization of a general tridiagonal matrix using partial pivoting and row exchanges.
x`GTTRS` (P)	Solves general tridiagonal system of linear equations using the factorization computed by x.
Hermitian Band Matrix
`CHBEV` or `ZHBEV`	(Replacement with newer version `CHBEVD` or `ZHBEVD` suggested) Computes all eigenvalues and eigenvectors of a Hermitian band matrix.
`CHBEVD` or `ZHBEVD`	Computes all eigenvalues and eigenvectors of a Hermitian band matrix and uses a divide and conquer method to calculate eigenvectors.
`CHBEVX` or `ZHBEVX`	Computes selected eigenvalues and eigenvectors of a Hermitian band matrix.
`CHBGST` or `ZHBGST`	Reduces Hermitian-definite banded generalized eigenproblem to standard form.
`CHBGV` or `ZHBGV`	(Replacement with newer version `CHBGVD` or `ZHBGVD` suggested) Computes all eigenvalues and eigenvectors of a generalized Hermitian-definite banded eigenproblem.
`CHBGVD` or `ZHBGVD`	Computes all eigenvalues and eigenvectors of generalized Hermitian-definite banded eigenproblem and uses a divide and conquer method to calculate eigenvectors.
`CHBGVX` or `ZHBGVX`	Computes selected eigenvalues and eigenvectors of a generalized Hermitian-definite banded eigenproblem.
`CHBTRD` or `ZHBTRD`	Reduces Hermitian band matrix to real symmetric tridiagonal form by using a unitary similarity transform.
Hermitian Matrix
`CHECON` or `ZHECON`	Estimates the reciprocal of the condition number of a Hermitian matrix using the factorization computed by `CHETRF` or `ZHETRF`.
`CHEEV` or `ZHEEV`	(Replacement with newer version `CHEEVR` or `ZHEEVR` suggested) Computes all eigenvalues and eigenvectors of a Hermitian matrix (simple driver).
`CHEEVD` or `ZHEEVD`	(Replacement with newer version `CHEEVR` or `ZHEEVR` suggested) Computes all eigenvalues and eigenvectors of a Hermitian matrix and uses a divide and conquer method to calculate eigenvectors.
`CHEEVR` or `ZHEEVR`	Computes selected eigenvalues and the eigenvectors of a complex Hermitian matrix.
`CHEEVX` or `ZHEEVX`	Computes selected eigenvalues and eigenvectors of a Hermitian matrix (expert driver).
`CHEGST` or `ZHEGST`	Reduces a Hermitian-definite generalized eigenproblem to standard form using the factorization computed by `CPOTRF` or `ZPOTRF`.
`CHEGV` or `ZHEGV`	(Replacement with newer version `CHEGVD` or `ZHEGVD` suggested) Computes all the eigenvalues and eigenvectors of a complex generalized Hermitian-definite eigenproblem.
`CHEGVD` or `ZHEGVD`	Computes all the eigenvalues and eigenvectors of a complex generalized Hermitian-definite eigenproblem and uses a divide and conquer method to calculate eigenvectors.
`CHEGVX` or `ZHEGVX`	Computes selected eigenvalues and eigenvectors of a complex generalized Hermitian-definite eigenproblem.
`CHERFS` or `ZHERFS`	Improves the computed solution to a system of linear equations when the coefficient matrix is Hermitian indefinite.
`CHESV` or `ZHESV`	Solves a complex Hermitian indefinite system of linear equations (simple driver).
`CHESVX` or `ZHESVX`	Solves a complex Hermitian indefinite system of linear equations (simple driver).
`CHETRD` or `ZHETRD`	Reduces a Hermitian matrix to real symmetric tridiagonal form by using a unitary similarity transformation.
`CHETRF` or `ZHERTF`	Computes the factorization of a complex Hermitian indefinite matrix, using the diagonal pivoting method.
`CHETRI` or `ZHETRI`	Computes the inverse of a complex Hermitian indefinite matrix, using the factorization computed by `CHETRF` or `ZHETRF`.
`CHETRS` (P) or `ZHETRS` (P)	Solves a complex Hermitian indefinite matrix, using the factorization computed by `CHETRF` or `ZHETRF`.
Hermitian Matrix in Packed Storage
`CHPCON` or `ZHPCON`	Estimates the reciprocal of the condition number of a Hermitian indefinite matrix in packed storage using the factorization computed by `CHPTRF` or `ZHPTRF`.
`CHPEV` or `ZHPEV`	(Replacement with newer version `CHPEVD` or `ZHPEVD` suggested) Computes all the eigenvalues and eigenvectors of a Hermitian matrix in packed storage (simple driver).
`CHPEVX` or `ZHPEVX`	Computes selected eigenvalues and eigenvectors of a Hermitian matrix in packed storage (expert driver).
`CHPEVD` or `ZHPEVD`	Computes all the eigenvalues and eigenvectors of a Hermitian matrix in packed storage and uses a divide and conquer method to calculate eigenvectors.
`CHPGST` or `ZHPGST`	Reduces a Hermitian-definite generalized eigenproblem to standard form where the coefficient matrices are in packed storage and uses the factorization computed by `CPPTRF` or `ZPPTRF`.
`CHPGV` or `ZHPGV`	(Replacement with newer version `CHPGVD` or `ZHPGVD` suggested) Computes all the eigenvalues and eigenvectors of a generalized Hermitian-definite eigenproblem where the coefficient matrices are in packed storage (simple driver).
`CHPGVX` or `ZHPGVX`	Computes selected eigenvalues and eigenvectors of a generalized Hermitian-definite eigenproblem where the coefficient matrices are in packed storage (expert driver).
`CHPGVD` or `ZHPGVD`	Computes all the eigenvalues and eigenvectors of a generalized Hermitian-definite eigenproblem where the coefficient matrices are in packed storage, and uses a divide and conquer method to calculate eigenvectors.
`CHPRFS` or `ZHPRFS`	Improves the computed solution to a system of linear equations when the coefficient matrix is Hermitian indefinite in packed storage.
`CHPSV` or `ZHPSV`	Computes the solution to a complex system of linear equations where the coefficient matrix is Hermitian in packed storage (simple driver).
`CHPSVX` or `ZHPSVX`	Uses the diagonal pivoting factorization to compute the solution to a complex system of linear equations where the coefficient matrix is Hermitian in packed storage (expert driver).
`CHPTRD` or `ZHPTRD`	Reduces a complex Hermitian matrix stored in packed form to real symmetric tridiagonal form.
`CHPTRF` or `ZHPTRF`	Computes the factorization of a complex Hermitian indefinite matrix in packed storage, using the diagonal pivoting method.
`CHPTRI` or `ZHPTRI`	Computes the inverse of a complex Hermitian indefinite matrix in packed storage using the factorization computed by `CHPTRF` or `ZHPTRF`.
`CHPTRS` (P) or `ZHPTRS` (P)	Solves a complex Hermitian indefinite matrix in packed storage, using the factorization computed by `CHPTRF` or `ZHPTRF`.
Upper Hessenberg Matrix
x`HSEIN`	Computes right and/or left eigenvectors of upper Hessenberg matrix using inverse iteration.
x`HSEQR`	Computes eigenvectors and Shur factorization of upper Hessenberg matrix using multishift QR algorithm.
Upper Hessenberg Matrix-Generalized Problem (Hessenberg and Triangular Matrix)
x`HGEQZ`	Implements single-/double-shift version of QZ method for finding the generalized eigenvalues of the equation det(A - w(i) * B) = 0.
Real Orthogonal Matrix in Packed Storage
`SOPGTR` or `DOPGTR`	Generates an orthogonal transformation matrix from a tridiagonal matrix determined by `SSPTRD` or `DSPTRD`.
`SOPMTR` or `DOPMTR`	Multiplies a general matrix by the orthogonal transformation matrix reduced to tridiagonal form by `SSPTRD` or `DSPTRD`.
Real Orthogonal Matrix
`SORGBR` or `DORGBR`	Generates the orthogonal transformation matrices from reduction to bidiagonal form, as determined by `SGEBRD` or `DGEBRD`.
`SORGHR` or `DORGHR`	Generates the orthogonal transformation matrix reduced to Hessenberg form, as determined by `SGEHRD` or `DGEHRD`.
`SORGLQ` or `DORGLQ`	Generates an orthogonal matrix Q from an LQ factorization, as returned by `SGELQF` or `DGELQF`.
`SORGQL` or `DORGQL`	Generates an orthogonal matrix Q from a QL factorization, as returned by `SGEQLF` or `DGEQLF`.
`SORGQR` or `DORGQR`	Generates an orthogonal matrix Q from a QR factorization, as returned by `SGEQRF` or `DGEQRF`.
`SORGRQ` or `DORGRQ`	Generates orthogonal matrix Q from an RQ factorization, as returned by `SGERQF` or `DGERQF`.
`SORGTR` or `DORGTR`	Generates an orthogonal matrix reduced to tridiagonal form by `SSYTRD` or `DSYTRD`.
`SORMBR` or `DORMBR`	Multiplies a general matrix with the orthogonal matrix reduced to bidiagonal form, as determined by `SGEBRD` or `DGEBRD`.
`SORMHR` or `DORMHR`	Multiplies a general matrix by the orthogonal matrix reduced to Hessenberg form by `SGEHRD` or `DGEHRD`.
`SORMLQ` (P) or `DORMLQ` (P)	Multiplies a general matrix by the orthogonal matrix from an LQ factorization, as returned by `SGELQF` or `DGELQF`.
`SORMQL` (P) or `DORMQL` (P)	Multiplies a general matrix by the orthogonal matrix from a QL factorization, as returned by `SGEQLF` or `DGEQLF`.
`SORMQR` (P) or `DORMQR` (P)	Multiplies a general matrix by the orthogonal matrix from a QR factorization, as returned by `SGEQRF` or `DGEQRF`.
`SORMR3` or `DORMR3`	Multiplies a general matrix by the orthogonal matrix returned by `STZRZF` or `DTZRZF`.
`SORMRQ` (P) or `DORMRQ` (P)	Multiplies a general matrix by the orthogonal matrix from an RQ factorization returned by `SGERQF` or `DGERQF`.
`SORMRZ` or `DORMRZ`	Multiplies a general matrix by the orthogonal matrix from an RZ factorization, as returned by `STZRZF` or `DTZRZF`.
`SORMTR` or `DORMTR`	Multiplies a general matrix by the orthogonal transformation matrix reduced to tridiagonal form by `SSYTRD` or `DSYTRD`.
Symmetric or Hermitian Positive Definite Band Matrix
x`PBCON`	Estimates the reciprocal of the condition number of a symmetric or Hermitian positive definite band matrix, using the Cholesky factorization returned by x`PBTRF`.
x`PBEQU`	Computes equilibration scale factors for a symmetric or Hermitian positive definite band matrix.
x`PBRFS`	Refines solution to a symmetric or Hermitian positive definite banded system of linear equations.
x`PBSTF`	Computes a split Cholesky factorization of a real symmetric positive definite band matrix.
x`PBSV`	Solves a symmetric or Hermitian positive definite banded system of linear equations (simple driver).
x`PBSVX`	Solves a symmetric or Hermitian positive definite banded system of linear equations (expert driver).
x`PBTRF`	Computes Cholesky factorization of a symmetric or Hermitian positive definite band matrix.
x`PBTRS` (P)	Solves symmetric positive definite banded matrix, using the Cholesky factorization computed by x`PBTRF`.
Symmetric or Hermitian Positive Definite Matrix
x`POCON`	Estimates the reciprocal of the condition number of a symmetric or Hermitian positive definite matrix, using the Cholesky factorization returned by x`POTRF`.
x`POEQU`	Computes equilibration scale factors for a symmetric or Hermitian positive definite matrix.
x`PORFS`	Refines solution to a linear system in a Cholesky-factored symmetric or Hermitian positive definite matrix.
x`POSV`	Solves a symmetric or Hermitian positive definite system of linear equations (simple driver).
x`POSVX`	Solves a symmetric or Hermitian positive definite system of linear equations (expert driver).
x`POTRF` (P)	Computes Cholesky factorization of a symmetric or Hermitian positive definite matrix.
x`POTRI`	Computes the inverse of a symmetric or Hermitian positive definite matrix using the Cholesky-factorization returned by x`POTRF`.
x`POTRS` (P)	Solves a symmetric or Hermitian positive definite system of linear equations, using the Cholesky factorization returned by x`POTRF`.
Symmetric or Hermitian Positive Definite Matrix in Packed Storage
x`PPCON`	Reciprocal condition number of a Cholesky-factored symmetric positive definite matrix in packed storage.
x`PPEQU`	Computes equilibration scale factors for a symmetric or Hermitian positive definite matrix in packed storage.
x`PPRFS`	Refines solution to a linear system in a Cholesky-factored symmetric or Hermitian positive definite matrix in packed storage.
x`PPSV`	Solves a linear system in a symmetric or Hermitian positive definite matrix in packed storage (simple driver).
x`PPSVX`	Solves a linear system in a symmetric or Hermitian positive definite matrix in packed storage (expert driver).
x`PPTRF`	Computes Cholesky factorization of a symmetric or Hermitian positive definite matrix in packed storage.
x`PPTRI`	Computes the inverse of a symmetric or Hermitian positive definite matrix in packed storage using the Cholesky-factorization returned by x`PPTRF`.
x`PPTRS` (P)	Solves a symmetric or Hermitian positive definite system of linear equations where the coefficient matrix is in packed storage, using the Cholesky factorization returned by x`PPTRF`.
Symmetric or Hermitian Positive Definite Tridiagonal Matrix
x`PTCON`	Estimates the reciprocal of the condition number of a symmetric or Hermitian positive definite tridiagonal matrix using the Cholesky factorization returned by x`PTTRF`.
x`PTEQR`	Computes all eigenvectors and eigenvalues of a real symmetric or Hermitian positive definite system of linear equations.
x`PTRFS`	Refines solution to a symmetric or Hermitian positive definite tridiagonal system of linear equations.
x`PTSV`	Solves a symmetric or Hermitian positive definite tridiagonal system of linear equations (simple driver).
x`PTSVX`	Solves a symmetric or Hermitian positive definite tridiagonal system of linear equations (expert driver).
x`PTTRF`	Computes the LDL^H factorization of a symmetric or Hermitian positive definite tridiagonal matrix.
x`PTTRS` (P)	Solves a symmetric or Hermitian positive definite tridiagonal system of linear equations using the LDL^H factorization returned by x`PTTRF`.
Real Symmetric Band Matrix
`SSBEV` or `DSBEV`	(Replacement with newer version `SSBEVD` or `DSBEVD` suggested) Computes all eigenvalues and eigenvectors of a symmetric band matrix.
`SSBEVD` or `DSBEVD`	Computes all eigenvalues and eigenvectors of a symmetric band matrix and uses a divide and conquer method to calculate eigenvectors.
`SSBEVX` or `DSBEVX`	Computes selected eigenvalues and eigenvectors of a symmetric band matrix.
`SSBGST` or `DSBGST`	Reduces symmetric-definite banded generalized eigenproblem to standard form.
`SSBGV` or `DSBGV`	(Replacement with newer version `SSBGVD` or `DSBGVD` suggested) Computes all eigenvalues and eigenvectors of a generalized symmetric-definite banded eigenproblem.
`SSBGVD` or `DSBGVD`	Computes all eigenvalues and eigenvectors of generalized symmetric-definite banded eigenproblem and uses a divide and conquer method to calculate eigenvectors.
`SSBGVX` or `DSBGVX`	Computes selected eigenvalues and eigenvectors of a generalized symmetric-definite banded eigenproblem.
`SSBTRD` or `DSBTRD`	Reduces symmetric band matrix to real symmetric tridiagonal form by using an orthogonal similarity transform.
Symmetric Matrix in Packed Storage
x`SPCON`	Estimates the reciprocal of the condition number of a symmetric packed matrix using the factorization computed by x`SPTRF`.
`SSPEV` or `DSPEV`	(Replacement with newer version `SSPEVD` or `DSPEVD` suggested) Computes all the eigenvalues and eigenvectors of a symmetric matrix in packed storage (simple driver).
`SSPEVX` or `DSPEVX`	Computes selected eigenvalues and eigenvectors of a symmetric matrix in packed storage (expert driver).
`SSPEVD` or `DSPEVD`	Computes all the eigenvalues and eigenvectors of a symmetric matrix in packed storage and uses a divide and conquer method to calculate eigenvectors.
`SSPGST` or `DSPGST`	Reduces a real symmetric-definite generalized eigenproblem to standard form where the coefficient matrices are in packed storage and uses the factorization computed by `SPPTRF` or `DPPTRF`.
`SSPGVD` or `DSPGVD`	Computes all the eigenvalues and eigenvectors of a real generalized symmetric-definite eigenproblem where the coefficient matrices are in packed storage, and uses a divide and conquer method to calculate eigenvectors.
`SSPGV` or `DSPGV`	(Replacement with newer version `SSPGVD` or `DSPGVD` suggested) Computes all the eigenvalues and eigenvectors of a real generalized symmetric-definite eigenproblem where the coefficient matrices are in packed storage (simple driver).
`SSPGVX` or `DSPGVX`	Computes selected eigenvalues and eigenvectors of a real generalized symmetric-definite eigenproblem where the coefficient matrices are in packed storage (expert driver).
x`SPRFS`	Improves the computed solution to a system of linear equations when the coefficient matrix is symmetric indefinite in packed storage.
x`SPSV`	Computes the solution to a system of linear equations where the coefficient matrix is a symmetric matrix in packed storage (simple driver).
x`SPSVX`	Uses the diagonal pivoting factorization to compute the solution to a system of linear equations where the coefficient matrix is a symmetric matrix in packed storage (expert driver).
`SSPTRD` or `DSPTRD`	Reduces a real symmetric matrix stored in packed form to real symmetric tridiagonal form using an orthogonal similarity transform.
x`SPTRF`	Computes the factorization of a symmetric packed matrix using the Bunch-Kaufman diagonal pivoting method.
x`SPTRI`	Computes the inverse of a symmetric indefinite matrix in packed storage using the factorization computed by `xSPTRF`.
x`SPTRS` (P)	Solves a system of linear equations by the symmetric matrix stored in packed format using the factorization computed by `xSPTRF`.
Real Symmetric Tridiagonal Matrix
`SSTEBZ` or `DSTEBZ`	Computes the eigenvalues of a real symmetric tridiagonal matrix.
x`STEDC`	Computes all the eigenvalues and eigenvectors of a symmetric tridiagonal matrix using a divide and conquer method.
x`STEGR`	Computes selected eigenvalues and eigenvectors of a real symmetric tridiagonal matrix using Relatively Robust Representations.
x`STEIN`	Computes selected eigenvectors of a real symmetric tridiagonal matrix using inverse iteration.
x`STEQR`	Computes all the eigenvalues and eigenvectors of a real symmetric tridiagonal matrix using the implicit QL or QR algorithm.
`SSTERF` or `DSTERF`	Computes all the eigenvalues and eigenvectors of a real symmetric tridiagonal matrix using a root-free QL or QR algorithm variant.
`SSTEV` or `DSTEV`	(Replacement with newer version `SSTEVR` or `DSTEVR` suggested) Computes all eigenvalues and eigenvectors of a real symmetric tridiagonal matrix (simple driver).
`SSTEVX` or `DSTEVX`	Computes selected eigenvalues and eigenvectors of a real symmetric tridiagonal matrix (expert driver).
`SSTEVD` or `DSTEVD`	(Replacement with newer version `SSTEVR` or `DSTEVR` suggested) Computes all the eigenvalues and eigenvectors of a real symmetric tridiagonal matrix using a divide and conquer method.
`SSTEVR` or `DSTEVR`	Computes selected eigenvalues and eigenvectors of a real symmetric tridiagonal matrix using Relatively Robust Representations.
x`STSV`	Computes the solution to a system of linear equations where the coefficient matrix is a symmetric tridiagonal matrix.
x`STTRF`	Computes the factorization of a symmetric tridiagonal matrix.
x`STTRS` (P)	Computes the solution to a system of linear equations where the coefficient matrix is a symmetric tridiagonal matrix.
Symmetric Matrix
x`SYCON`	Estimates the reciprocal of the condition number of a symmetric matrix using the factorization computed by `SSYTRF` or `DSYTRF`.
`SSYEV` or `DSYEV`	(Replacement with newer version `SSYEVR` or `DSYEVR` suggested) Computes all eigenvalues and eigenvectors of a symmetric matrix.
`SSYEVX` or `DSYEVX`	Computes eigenvalues and eigenvectors of a symmetric matrix (expert driver).
`SSYEVD` or `DSYEVD`	(Replacement with newer version `SSYEVR` or `DSYEVR` suggested) Computes all eigenvalues and eigenvectors of a symmetric matrix and uses a divide and conquer method to calculate eigenvectors.
`SSYEVR` or `DSYEVR`	Computes selected eigenvalues and eigenvectors of a symmetric tridiagonal matrix.
`SSYGST` or `DSYGST`	Reduces a symmetric-definite generalized eigenproblem to standard form using the factorization computed by `SPOTRF` or `DPOTRF`.
`SSYGV` or `DSYGV`	(Replacement with newer version `SSYGVD` or `DSYGVD` suggested) Computes all the eigenvalues and eigenvectors of a generalized symmetric-definite eigenproblem.
`SSYGVX` or `DSYGVX`	Computes selected eigenvalues and eigenvectors of a generalized symmetric-definite eigenproblem.
`SSYGVD` or `DSYGVD`	Computes all the eigenvalues and eigenvectors of a generalized symmetric-definite eigenproblem and uses a divide and conquer method to calculate eigenvectors.
x`SYRFS`	Improves the computed solution to a system of linear equations when the coefficient matrix is symmetric indefinite.
x`SYSV`	Solves a real symmetric indefinite system of linear equations (simple driver).
x`SYSVX`	Solves a real symmetric indefinite system of linear equations (expert driver).
`SSYTRD` or `DSYTRD`	Reduces a symmetric matrix to real symmetric tridiagonal form by using a orthogonal similarity transformation.
x`SYTRF`	Computes the factorization of a real symmetric indefinite matrix using the diagonal pivoting method.
x`SYTRI`	Computes the inverse of a symmetric indefinite matrix using the factorization computed by x`SYTRF`.
x`SYTRS` (P)	Solves a system of linear equations by the symmetric matrix using the factorization computed by x`SYTRF`.
Triangular Band Matrix
x`TBCON`	Estimates the reciprocal condition number of a triangular band matrix.
x`TBRFS`	Determines error bounds and estimates for solving a triangular banded system of linear equations.
x`TBTRS` (P)	Solves a triangular banded system of linear equations.
Triangular Matrix-Generalized Problem (Pair of Triangular Matrices)
x`TGEVC`	Computes right and/or left generalized eigenvectors of two upper triangular matrices.
x`TGEXC`	Reorders the generalized Schur decomposition of a real or complex matrix pair using an orthogonal or unitary equivalence transformation.
x`TGSEN`	Reorders the generalized real-Schur or Schur decomposition of two matrixes and computes the generalized eigenvalues.
x`TGSJA`	Computes the generalized SVD from two upper triangular matrices obtained from x`GGSVP`.
x`TGSNA`	Estimates reciprocal condition numbers for specified eigenvalues and eigenvectors of two matrices in real-Schur or Schur canonical form.
x`TGSYL`	Solves the generalized Sylvester equation.
Triangular Matrix in Packed Storage
x`TPCON`	Estimates the reciprocal or the condition number of a triangular matrix in packed storage.
x`TPRFS`	Determines error bounds and estimates for solving a triangular system of linear equations where the coefficient matrix is in packed storage.
x`TPTRI`	Computes the inverse of a triangular matrix in packed storage.
x`TPTRS` (P)	Solves a triangular system of linear equations where the coefficient matrix is in packed storage.
Triangular Matrix
x`TRCON`	Estimates the reciprocal or the condition number of a triangular matrix.
x`TREVC`	Computes right and/or left eigenvectors of an upper triangular matrix.
x`TREXC`	Reorders Schur factorization of matrix using an orthogonal or unitary similarity transformation.
x`TRRFS`	Determines error bounds and estimates for triangular system of a linear equations.
x`TRSEN`	Reorders Schur factorization of matrix to group selected cluster of eigenvalues in the leading positions on the diagonal of the upper triangular matrix T and the leading columns of Q form an orthonormal basis of the corresponding right invariant subspace.
x`TRSNA`	Estimates the reciprocal condition numbers of selected eigenvalues and eigenvectors of an upper quasi-triangular matrix.
x`TRSYL`	Solves Sylvester matrix equation.
x`TRTRI`	Computes the inverse of a triangular matrix.
x`TRTRS` (P)	Solves a triangular system of linear equations.
Trapezoidal Matrix
x`TZRQF`	Depreciated routine replaced by routine x`TZRZF`.
x`TZRZF`	Reduces a rectangular upper trapezoidal matrix to upper triangular form by means of orthogonal transformations.
Unitary Matrix
`CUNGBR` or `ZUNGBR`	Generates the unitary transformation matrices from reduction to bidiagonal form, as determined by `CGEBRD` or `ZGEBRD`.
`CUNGHR` or `ZUNGHR`	Generates the orthogonal transformation matrix reduced to Hessenberg form, as determined by `CGEHRD` or `ZGEHRD`.
`CUNGLQ` or `ZUNGLQ`	Generates a unitary matrix Q from an LQ factorization, as returned by `CGELQF` or `ZGELQF`.
`CUNGQL` or `ZUNGQL`	Generates a unitary matrix Q from a QL factorization, as returned by `CGEQLF` or `ZGEQLF`.
`CUNGQR` or `ZUNGQR`	Generates a unitary matrix Q from a QR factorization, as returned by `CGEQRF` or `ZGEQRF`.
`CUNGRQ` or `ZUNGRQ`	Generates a unitary matrix Q from an RQ factorization, as returned by `CGERQF` or `ZGERQF`.
`CUNGTR` or `ZUNGTR`	Generates a unitary matrix reduced to tridiagonal form, by `CHETRD` or `ZHETRD`.
`CUNMBR` or `ZUNMBR`	Multiplies a general matrix with the unitary transformation matrix reduced to bidiagonal form, as determined by `CGEBRD` or `ZGEBRD`.
`CUNMHR` or `ZUNMHR`	Multiplies a general matrix by the unitary matrix reduced to Hessenberg form by `CGEHRD` or `ZGEHRD`.
`CUNMLQ` (P) or `ZUNMLQ` (P)	Multiplies a general matrix by the unitary matrix from an LQ factorization, as returned by `CGELQF` or `ZGELQF`.
`CUNMQL` (P) or `ZUNMQL` (P)	Multiplies a general matrix by the unitary matrix from a QL factorization, as returned by `CGEQLF` or `ZGEQLF`.
`CUNMQR` (P) or `ZUNMQR` (P)	Multiplies a general matrix by the unitary matrix from a QR factorization, as returned by `CGEQRF` or `ZGEQRF`.
`CUNMRQ` (P) or `ZUNMRQ` (P)	Multiplies a general matrix by the unitary matrix from an RQ factorization, as returned by `CGERQF` or `ZGERQF`.
`CUNMRZ` or `ZUNMRZ`	Multiplies a general matrix by the unitary matrix from an RZ factorization, as returned by `CTZRZF` or `ZTZRZF`.
`CUNMTR` or `ZUNMTR`	Multiplies a general matrix by the unitary transformation matrix reduced to tridiagonal form by `CHETRD` or `ZHETRD`.
Unitary Matrix in Packed Storage
`CUPGTR` or `ZUPGTR`	Generates the unitary transformation matrix from a tridiagonal matrix determined by `CHPTRD` or `ZHPTRD`.
`CUPMTR` or `ZUPMTR`	Multiplies a general matrix by the unitary transformation matrix reduced to tridiagonal form by `CHPTRD` or `ZHPTRD`.

BLAS1 Routines

TABLE A-2 lists the Sun Performance Library BLAS1 routines. No Sun Performance Library BLAS1 routines are currently parallelized.

TABLE A-2 BLAS1 (Basic Linear Algebra Subprograms, Level 1) Routines
Routine	Function
`SASUM`, `DASUM`, `SCASUM`, `DZASUM`	Sum of the absolute values of a vector
x`AXPY`	Product of a scalar and vector plus a vector
x`COPY`	Copy a vector
`SDOT`, `DDOT`, `DSDOT`, `SDSDOT`, `CDOTU`, `ZDOTU`, `DQDOTA`, `DQDOTI`	Dot product (inner product)
`CDOTC`, `ZDOTC`	Dot product conjugating first vector
`SNRM2`, `DNRM2`, `SCNRM2`, `DZNRM2`	Euclidean norm of a vector
x`ROTG`	Set up Givens plane rotation
x`ROT`, `CSROT`, `ZDROT`	Apply Given's plane rotation
`SROTMG`, `DROTMG`	Set up modified Given's plane rotation
`SROTM`, `DROTM`	Apply modified Given's rotation
`ISAMAX`, `DAMAX`, `ICAMAX`, `IZAMAX`	Index of element with maximum absolute value
x`SCAL`, `CSSCAL`, `ZDSCAL`	Scale a vector
x`SWAP`	Swap two vectors
`CVMUL`, `ZVMUL`	Compute scaled product of complex vectors

BLAS2 Routines

TABLE A-3 lists the Sun Performance Library BLAS2 routines. (P) denotes routines that are parallelized.

TABLE A-3 BLAS2 (Basic Linear Algebra Subprograms, Level 2) Routines
Routine	Function
x`GBMV`	Product of a matrix in banded storage and a vector
x`GEMV` (P)	Product of a general matrix and a vector
`SGER` (P), `DGER` (P), `CGERC` (P), `ZGERC` (P), `CGERU` (P), `ZGERU` (P)	Rank-1 update to a general matrix
`CHBMV`, `ZHBMV`	Product of a Hermitian matrix in banded storage and a vector
`CHEMV` (P), `ZHEMV` (P)	Product of a Hermitian matrix and a vector
`CHER` (P), `ZHER` (P)	Rank-1 update to a Hermitian matrix
`CHER2`, `ZHER2`	Rank-2 update to a Hermitian matrix
`CHPMV` (P), `ZHPMV` (P)	Product of a Hermitian matrix in packed storage and a vector
`CHPR`, `ZHPR`	Rank-1 update to a Hermitian matrix in packed storage
`CHPR2`, `ZHPR2`	Rank-2 update to a Hermitian matrix in packed storage
`SSBMV`, `DSBMV`	Product of a symmetric matrix in banded storage and a vector
`SSPMV` (P), `DSPMV` (P)	Product of a Symmetric matrix in packed storage and a vector
`SSPR`, `DSPR`	Rank-1 update to a real symmetric matrix in packed storage
`SSPR2` (P), `DSPR2` (P)	Rank-2 update to a real symmetric matrix in packed storage
`SSYMV`, (P) `DSYMV` (P)	Product of a symmetric matrix and a vector
`SSYR` (P), `DSYR` (P)	Rank-1 update to a real symmetric matrix
`SSYR2` (P), `DSYR2` (P)	Rank-2 update to a real symmetric matrix
x`TBMV`	Product of a triangular matrix in banded storage and a vector
x`TBSV`	Solution to a triangular system in banded storage of linear equations
x`TPMV`	Product of a triangular matrix in packed storage and a vector
x`TPSV`	Solution to a triangular system of linear equations in packed storage
x`TRMV` (P)	Product of a triangular matrix and a vector
x`TRSV` (P)	Solution to a triangular system of linear equations

BLAS3 Routines

TABLE A-4 lists the Sun Performance Library BLAS3 routines. (P) denotes routines that are parallelized.

TABLE A-4 BLAS3 (Basic Linear Algebra Subprograms, Level 3) Routines
Routine	Function
x`GEMM` (P)	Product of two general matrices
`CHEMM` (P) or `ZHEMM` (P)	Product of a Hermitian matrix and a general matrix
`CHERK` (P) or `ZHERK` (P)	Rank-k update of a Hermitian matrix
`CHER2K` (P) or `ZHER2K` (P)	Rank-2k update of a Hermitian matrix
x`SYMM` (P)	Product of a symmetric matrix and a general matrix
x`SYRK` (P)	Rank-k update of a symmetric matrix
x`SYR2K` (P)	Rank-2k update of a symmetric matrix
x`TRMM` (P)	Product of a triangular matrix and a general matrix
x`TRSM` (P)	Solution for a triangular system of equations

Sparse BLAS Routines

TABLE A-5 lists the Sun Performance Library sparse BLAS routines. (P) denotes routines that are parallelized.

TABLE A-5 Sparse BLAS Routines
Routines	Function
x`AXPYI`	Adds a scalar multiple of a sparse vector X to a full vector Y.
x`BCOMM` (P)	Block coordinate matrix-matrix multiply.
x`BDIMM` (P)	Block diagonal format matrix-matrix multiply.
x`BDISM` (P)	Block Diagonal format triangular solve.
x`BELMM` (P)	Block Ellpack format matrix-matrix multiply.
x`BELSM` (P)	Block Ellpack format triangular solve.
x`BSCMM` (P)	Block compressed sparse column format matrix-matrix multiply.
x`BSCSM` (P)	Block compressed sparse column format triangular solve.
x`BSRMM` (P)	Block compressed sparse row format matrix-matrix multiply.
x`BSRSM` (P)	Block compressed sparse row format triangular solve.
x`COOMM` (P)	Coordinate format matrix-matrix multiply.
x`CSCMM` (P)	Compressed sparse column format matrix-matrix multiply
x`CSCSM` (P)	Compressed sparse column format triangular solve
x`CSRMM` (P)	Compressed sparse row format matrix-matrix multiply.
x`CSRSM` (P)	Compressed sparse row format triangular solve.
x`DIAMM` (P)	Diagonal format matrix-matrix multiply.
x`DIASM` (P)	Diagonal format triangular solve.
`SDOTI`, `DDOTI, CDOTUI`, or `ZDOTUI`	Computes the dot product of a sparse vector and a full vector.
`CDOTCI`, or `ZDOTCI`	Computes the conjugate dot product of a sparse vector and a full vector.
x`ELLMM` (P)	Ellpack format matrix-matrix multiply.
x`ELLSM` (P)	Ellpack format triangular solve.
x`CGTHR`	Given a full vector, creates a sparse vector and corresponding index vector.
x`CGTHRZ`	Given a full vector, creates a sparse vector and corresponding index vector and zeros the full vector.
x`JADMM` (P)	Jagged diagonal matrix-matrix multiply.
`SJADRP` or `DJADRP`	Right permutation of a jagged diagonal matrix.
x`JADSM` (P)	Jagged diagonal triangular solve.
`SROTI` or `DROTI`	Applies a Givens rotation to a sparse vector and a full vector.
x`CSCTR`	Given a sparse vector and corresponding index vector, puts those elements into a full vector.
x`SKYMM` (P)	Skyline format matrix-matrix multiply.
x`SKYSM` (P)	Skyline format triangular solve.
x`VBRMM` (P)	Variable block sparse row format matrix-matrix multiply.
x`VBRSM` (P)	Variable block sparse row format triangular solve.

Sparse Solver Routines

TABLE A-6 lists the Sun Performance Library sparse solver routines. (P) denotes routines that are parallelized.

TABLE A-6 Sparse Solver Routines
Routines	Function
`SGSSFS` (P), `DGSSFS` (P), `CGSSFS` (P), or `ZGSSFS` (P)	One call interface to sparse solver.
`SGSSIN`, `DGSSIN`, `CGSSIN`, or `ZGSSIN`	Sparse solver initialization.
`SGSSOR`, `DGSSOR`, `CGSSOR`, or `ZGSSOR`	Fill reducing ordering and symbolic factorization.
`SGSSFA` (P), `DGSSFA` (P), `CGSSFA` (P), or `ZGSSFA` (P)	Matrix value input and numeric factorization.
`SGSSSL`, `DGSSSL`, `CGSSSL`, or `ZGSSSL`	Triangular solve.
`SGSSUO`, `DGSSUO`, C`GSSUO`, or `ZGSSUO`	Sets user-specified ordering permutation.
`SGSSRP`, `DGSSRP`, C`GSSRP`, or Z`GSSRP`	Returns permutation used by solver.
`SGSSCO`, `DGSSCO`, `CGSSCO`, or `ZGSSCO`	Returns condition number estimate of coefficient matrix.
`SGSSDA`, `DGSSDA`, `CGSSDA`, or `ZGSSDA`	De-allocates sparse solver.
`SGSSPS`, `DGSSPS`, `CGSSPS`, or `ZGSSPS`	Prints solver statistics.

Signal Processing Library Routines

Sun Performance Library contains routines for computing the fast Fourier transform, sine and cosine transforms, and convolution and correlation.

FFT Routines

Sun Performance Library provides a set of FFT interfaces that supersedes a subset of the FFTPACK and VFFTPACK routines provided in earlier Sun Performance Library releases. The legacy FFT routines and man pages for the routines are still included to maintain compatibility with existing codes, but the routines are no longer supported. For information on using the legacy FFT routines, see the section 3P man pages.

TABLE A-7 shows the mapping between the Sun Performance Library FFT routines and the corresponding FFTPACK and VFFTPACK routines. (P) denotes routines that are parallelized.

TABLE A-7 FFT Routines
Routine	Replaces	Function
`CFFTC` (P)	`CFFTI` `CFFTF` (P) `CFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward or inverse FFT of a complex sequence.
`CFFTC2` (P)	`CFFT2I` `CFFT2F` (P) `CFFT2B` (P)	Initialize the trigonometric weight and factor tables or compute the two-dimensional forward or inverse FFT of a two-dimensional complex array.
`CFFTC3` (P)	`CFFT3I` `CFFT3F` (P) `CFFT3B` (P)	Initialize the trigonometric weight and factor tables or compute the three-dimensional forward or inverse FFT of three-dimensional complex array.
`CFFTCM` (P)	`VCFFTI` `VCFFTF` (P) `VCFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward or inverse FFT of a set of data sequences stored in a two-dimensional complex array.
`CFFTS`	`RFFTI`, `RFFTB` `EZFFTI`, `EZFFTB`	Initialize the trigonometric weight and factor tables or compute the one-dimensional inverse FFT of a complex sequence.
`CFFTS2`	`RFFT2I` `RFFT2B`	Initialize the trigonometric weight and factor tables or compute the two-dimensional inverse FFT of a two-dimensional complex array.
`CFFTS3` (P)	`RFFT3I` `RFFT3B`	Initialize the trigonometric weight and factor tables or compute the three-dimensional inverse FFT of three-dimensional complex array.
`CFFTSM`	`VRFFTI` `VRFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional inverse FFT of a set of data sequences stored in a two-dimensional complex array.
`DFFTZ`	`DFFTI`, `DFFTF` `DEZFFTI`, `DEZFFTF`	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward FFT of a double precision sequence.
`DFFTZ2`	`DFFT2I` `DFFT2F`	Initialize the trigonometric weight and factor tables or compute the two-dimensional forward FFT of a two-dimensional double precision array.
`DFFTZ3` (P)	`DFFT3I` `DFFT3F`	Initialize the trigonometric weight and factor tables or compute the three-dimensional forward FFT of three-dimensional double precision array.
`DFFTZM`	`VDFFTI` `VDFFTF` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward FFT of a set of data sequences stored in a two-dimensional double precision array.
`SFFTC`	`RFFTI`, `RFFTF` `EZFFTI`, `EZFFTF`	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward FFT of a real sequence.
`SFFTC2`	`RFFT2I` `RFFT2F`	Initialize the trigonometric weight and factor tables or compute the two-dimensional forward FFT of a two-dimensional real array.
`SFFTC3` (P)	`RFFT3I` `RFFT3F`	Initialize the trigonometric weight and factor tables or compute the three-dimensional forward FFT of three-dimensional real array.
`SFFTCM`	`VRFFTI` `VRFFTF` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward FFT of a set of data sequences stored in a two-dimensional real array.
`ZFFTD`	`DFFTI`, `DFFTB` `DEZFFTI`, `DEZFFTB`	Initialize the trigonometric weight and factor tables or compute the one-dimensional inverse FFT of a double complex sequence.
`ZFFTD2`	`DFFT2I` `DFFT2B`	Initialize the trigonometric weight and factor tables or compute the two-dimensional inverse FFT of a two-dimensional double complex array.
`ZFFTD3` (P)	`DFFT3I` `DFFT3B`	Initialize the trigonometric weight and factor tables or compute the three-dimensional inverse FFT of three-dimensional double complex array.
`ZFFTDM`	`VDFFTI` `VDFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional inverse FFT of a set of data sequences stored in a two-dimensional double complex array.
`ZFFTZ` (P)	`ZFFTI` `ZFFTF` (P) `ZFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward or inverse FFT of a double complex sequence.
`ZFFTZ2` (P)	`ZFFT2I` `ZFFT2F` (P) `ZFFT2B` (P)	Initialize the trigonometric weight and factor tables or compute the two-dimensional forward or inverse FFT of a two-dimensional double complex array.
`ZFFTZ3` (P)	`ZFFT3I` `ZFFT3F` (P) `ZFFT3B` (P)	Initialize the trigonometric weight and factor tables or compute the three-dimensional forward or inverse FFT of three-dimensional double complex array.
`ZFFTZM` (P)	`VZFFTI` `VZFFTF` (P) `VZFFTB` (P)	Initialize the trigonometric weight and factor tables or compute the one-dimensional forward or inverse FFT of a set of data sequences stored in a two-dimensional double complex array.

Fast Cosine and Sine Transforms

Sun Performance Library fast cosine and sine transform routines are based on the routines contained in FFTPACK (http://www.netlib.org/fftpack/). Routines with a V prefix are vectorized routines that are based on the routines contained in VFFTPACK (http://www.netlib.org/vfftpack/).

TABLE A-8 lists the Sun Performance Library sine and cosine transform routines.

TABLE A-8 Sine and Cosine Transform Routines
Routine	Function
`COSQB`, `DCOSQB`, `VCOSQB`, `VDCOSQB`	Cosine quarter-wave synthesis.
`COSQF`, `DCOSQF`, `VCOSQF`, `VDCOSQF`	Cosine quarter-wave transform.
`COSQI`, `DCOSQI`, `VCOSQI`, `VDCOSQI`	Initialize cosine quarter-wave transform and synthesis.
`COST`, `DCOST`, `VCOST,` `VDCOST`	Cosine even-wave transform.
`COSTI`, `DCOSTI`, `VCOSTI`, `VDCOSTI`	Initialize cosine even-wave transform.
`SINQB`, `DSINQB`, `VSINQB`, `VDSINQB`	Sine quarter-wave synthesis.
`SINQF`, `DSINQF`, `VSINQF`, `VDSINQF`	Sine quarter-wave transform.
`SINQI`, `DSINQI`, `VSINQI`, `VDSINQI`	Initialize sine quarter-wave transform and synthesis.
`SINT`, `DSINT`, `VSINT`, `VDSINT`	Sine odd-wave transform.
`SINTI`, `DSINT`, `VSINTI`, `VDSINTI`	Initialize sine odd-wave transform.

Convolution and Correlation Routines

TABLE A-9 lists the Sun Performance Library convolution and correlation routines.

TABLE A-9 Convolution and Correlation Routines
Routines	Function
x`CNVCOR`	Computes convolution or correlation
x`CNVCOR2`	Computes two-dimensional convolution or correlation

Miscellaneous Signal Processing Routines

TABLE A-10 lists the miscellaneous Sun Performance Library signal processing routines.

TABLE A-10 Convolution and Correlation Routines
Routines	Function
`RFFTOPT`, `DFFTOPT`, `CFFTOPT`, `ZFFTOPT`	Compute the length of the closest FFT
`SWIENER` or `DWEINER`	Performs Wiener deconvolution of two signals
x`TRANS`	Transposes array

Interval BLAS (IBLAS) Routines

Sun Performance Library includes the interval BLAS routines listed in TABLE A-11, which operate on interval scalars, interval vectors, and interval matrices (dense, banded, symmetric, and triangular).

TABLE A-11 Interval BLAS Routines
Routine	Function
`amax_val_i`	Max absolute value and location.
`amin_val_i`	Min absolute value and location.
`axpby_i`	Scaled vector accumulation.
`cancel_i`	Scaled cancellation.
`constructv_i`	Constructs an interval vector.
`copy_i`	Interval vector copy.
`disjv_i`	Checks if two interval vectors disjoint.
`dot_i`	Scaled dot product of two interval vectors.
`emptyelev_i`	Empty entry and its location.
`encv_i`	Check if an interval vector is enclosed in another.
`fpinfo_i`	Environmental enquiry.
`gbmv_i`	Interval matrix-vector multiplication.
`gb_acc_i`	General band matrix accumulation and scale.
`gb_add_i`	General band matrix add and scale.
`gb_constructm_i`	Constructs an interval matrix from two floating point matrices.
`gb_copy_i`	General band interval matrix copy.
`gb_diag_scale_i`	Diagonal scaling of an interval matrix.
`gb_disjm_i`	If two interval matrices are disjoint.
`gb_emptyelem_i`	Empty entry and its location.
`gb_encm_i`	If an interval matrix is enclosed in another.
`gb_hullm_i`	Convex hull of two interval matrices.
`gb_infm_i`	Left endpoint of an interval matrix.
`gb_interiorm_i`	If an interval matrix is in interior of another.
`gb_interm_i`	Intersection of two interval matrices.
`gb_lrscale_i`	Two-sided diagonal scaling.
`gb_midm_i`	Midpoint matrix of an interval matrix.
`gb_norm_i`	General band interval matrix norms.
`gb_supm_i`	Right endpoint of an interval matrix.
`gb_whullm_i`	Convex hull of two interval matrices.
`gb_widthm_i`	Elementwise width of an interval matrix.
`gb_winterm_i`	Intersection of two interval matrices.
`gemm_i`	General interval matrix product.
`gemv_i`	General interval matrix and vector multiplication.
`ger_i`	Rank one update.
`ge_acc_i`	General matrix accumulation and scale.
`ge_add_i`	General interval matrix add and scale.
`ge_constructm_i`	Constructs an interval matrix from two floating point matrices.
`ge_copy_i`	General interval matrix copy.
`ge_diag_scale_i`	Diagonal scaling an interval matrix.
`ge_disjm_i`	If two interval matrices are disjoint.
`ge_emptyelem_i`	Empty entry and its location.
`ge_encm_i`	If an interval matrix is enclosed in another.
`ge_hullm_i`	Convex hull of two interval matrices.
`ge_infm_i`	Left endpoint of an interval matrix.
`ge_interiorm_i`	If an interval matrix is in interior of another.
`ge_interm_i`	Intersection of two interval matrices.
`ge_lrscale_i`	Two-sided diagonal scaling.
`ge_midm_i`	Midpoint matrix of an interval matrix.
`ge_norm_i`	General interval matrix norms.
`ge_permute_i`	Permute an general interval matrix.
`ge_supm_i`	Right endpoint of an interval matrix.
`ge_trans_i`	Matrix transposition.
`ge_whullm_i`	Convex hull of two interval matrices.
`ge_widthm_i`	Elementwise width of an interval matrix.
`ge_winterm_i`	Intersection of two interval matrices.
`hullv_i`	Convex hull of an interval vector with another.
`infv_i`	The left endpoint of an interval vector.
`interiorv_i`	If an interval vector is in the interior of another.
`interv_i`	Intersection of an interval vector with another.
`midv_i`	The approximate midpoint of an interval vector.
`norm_i`	Interval vector norms.
`permute_i`	Permute interval vector.
`rscale_i`	Reciprocal scale of an interval vector.
`sbmv_i`	Interval symmetric matrix vector product.
`sb_acc_i`	Symmetric band matrix accumulation and scale.
`sb_add_i`	Symmetric band matrix add and scale.
`sb_constructm_i`	Constructs an interval matrix from two floating point matrices.
`sb_copy_i`	Symmetric band interval matrix copy.
`sb_disjm_i`	If two interval matrices are disjoint.
`sb_emptyelem_i`	Empty entry and its location.
`sb_encm_i`	If an interval matrix is enclosed in another.
`sb_hullm_i`	Convex hull of two interval matrices.
`sb_infm_i`	Left endpoint of an interval matrix.
`sb_interiorm_i`	If an interval matrix is in interior of another.
`sb_interm_i`	Intersection of two interval matrices.
`sb_lrscale_i`	Two-sided diagonal scaling.
`sb_midm_i`	Midpoint matrix of an interval matrix.
`sb_norm_i`	Symmetric band interval matrix norms.
`sb_supm_i`	Right endpoint of an interval matrix.
`sb_whullm_i`	Convex hull of two interval matrices.
`sb_widthm_i`	Elementwise width of an interval matrix.
`sb_winterm_i`	Intersection of two interval matrices.
`spmv_i`	Interval symmetric matrix vector product.
`spr_i`	Symmetric rank one update.
`sp_acc_i`	Symmetric packed matrix accumulation and scale.
`sp_add_i`	Symmetric packed matrix add and scale.
`sp_constructm_i`	Constructs an interval matrix from two floating point matrices.
`sp_copy_i`	Symmetric packed interval matrix copy.
`sp_disjm_i`	If two interval matrices are disjoint.
`sp_emptyelem_i`	Empty entry and its location.
`sp_encm_i`	If an interval matrix is enclosed in another.
`sp_hullm_i`	Convex hull of two interval matrices.
`sp_infm_i`	Left endpoint of an interval matrix.
`sp_interiorm_i`	If an interval matrix is in interior of another.
`sp_interm_i`	Intersection of two interval matrices.
`sp_lrscale_i`	Two-sided diagonal scaling.
`sp_midm_i`	Midpoint matrix of an interval matrix.
`sp_norm_i`	Symmetric packed interval matrix norms.
`sp_supm_i`	Right endpoint of an interval matrix.
`sp_whullm_i`	Convex hull of two interval matrices.
`sp_widthm_i`	Elementwise width of an interval matrix.
`sp_winterm_i`	Intersection of two interval matrices.
`sumsq_i`	Sum of squares.
`sum_i`	Sum the entries of an interval vector.
`supv_i`	The right endpoint of an interval vector.
`swap_i`	Interval vector swap.
`symm_i`	Symmetric interval matrix product.
`symv_i`	Interval symmetric matrix vector product.
`syr_i`	Symmetric rank one update.
`sy_acc_i`	Symmetric interval matrix accumulation and scale.
`sy_add_i`	Symmetric matrix add and scale.
`sy_constructm_i`	Constructs an interval matrix from two floating point matrices.
`sy_copy_i`	Symmetric interval matrix copy.
`sy_disjm_i`	If two interval matrices are disjoint.
`sy_emptyelem_i`	Empty entry and its location.
`sy_encm_i`	If an interval matrix is enclosed in another.
`sy_hullm_i`	Convex hull of two interval matrices.
`sy_infm_i`	Left endpoint of an interval matrix.
`sy_interiorm_i`	If an interval matrix is in interior of another.
`sy_interm_i`	Intersection of two interval matrices.
`sy_lrscale_i`	Two-sided diagonal scaling.
`sy_midm_i`	Midpoint matrix of an interval matrix.
`sy_norm_i`	Symmetric interval matrix norms.
`sy_supm_i`	Right endpoint of an interval matrix.
`sy_whullm_i`	Convex hull of two interval matrices.
`sy_widthm_i`	Elementwise width of an interval matrix.
`sy_winterm_i`	Intersection of two interval matrices.
`tbmv_i`	Interval triangular matrix vector product.
`tbsv_i`	Interval triangular solve with a vector.
`tb_acc_i`	Matrix accumulation and scale.
`tb_add_i`	Triangular band matrix add and scale.
`tb_constructm_i`	Constructs an interval matrix from two floating point matrices.
`tb_copy_i`	Triangular band interval matrix copy.
`tb_disjm_i`	If two interval matrices are disjoint.
`tb_emptyelem_i`	Empty entry and its location.
`tb_encm_i`	If an interval matrix is enclosed in another.
`tb_hullm_i`	Convex hull of two interval matrices.
`tb_infm_i`	Left endpoint of an interval matrix.
`tb_interiorm_i`	If an interval matrix is in interior of another.
`tb_interm_i`	Intersection of two interval matrices.
`tb_midm_i`	Midpoint matrix of an interval matrix.
`tb_norm_i`	Triangular band interval matrix norms.
`tb_supm_i`	Right endpoint of an interval matrix.
`tb_whullm_i`	Convex hull of two interval matrices.
`tb_widthm_i`	Elementwise width of an interval matrix.
`tb_winterm_i`	Intersection of two interval matrices.
`tpmv_i`	Interval triangular matrix vector product.
`tpsv_i`	Interval triangular solve with a vector.
`tp_acc_i`	Matrix accumulation and scale.
`tp_add_i`	Triangular packed matrix add and scale.
`tp_constructm_i`	Constructs an interval matrix from two floating point matrices.
`tp_copy_i`	Triangular packed interval matrix copy.
`tp_disjm_i`	If two interval matrices are disjoint.
`tp_emptyelem_i`	Empty entry and its location.
`tp_encm_i`	If an interval matrix is enclosed in another.
`tp_hullm_i`	Convex hull of two interval matrices.
`tp_infm_i`	Left endpoint of an interval matrix.
`tp_interiorm_i`	If an interval matrix is in interior of another.
`tp_interm_i`	Intersection of two interval matrices.
`tp_midm_i`	Midpoint matrix of an interval matrix.
`tp_norm_i`	Triangular packed interval matrix norms.
`tp_supm_i`	Right endpoint of an interval matrix.
`tp_whullm_i`	Convex hull of two interval matrices.
`tp_widthm_i`	Elementwise width of an interval matrix.
`tp_winterm_i`	Intersection of two interval matrices.
`trmm_i`	Triangular interval matrix matrix product.
`trmv_i`	Interval triangular matrix vector product.
`trsm_i`	Interval triangular solve.
`trsv_i`	Interval triangular solve with a vector.
`tr_acc_i`	Matrix accumulation and scale.
`tr_add_i`	Triangular matrix add and scale.
`tr_constructm_i`	Constructs an interval matrix from two floating point matrices.
`tr_copy_i`	Triangular interval matrix copy.
`tr_disjm_i`	If two interval matrices are disjoint.
`tr_emptyelem_i`	Empty entry and its location.
`tr_encm_i`	If an interval matrix is enclosed in another.
`tr_hullm_i`	Convex hull of two interval matrices.
`tr_infm_i`	Left endpoint of an interval matrix.
`tr_interiorm_i`	If an interval matrix is in interior of another.
`tr_interm_i`	Intersection of two interval matrices.
`tr_midm_i`	Midpoint matrix of an interval matrix.
`tr_norm_i`	Triangular interval matrix norms.
`tr_supm_i`	Right endpoint of an interval matrix.
`tr_whullm_i`	Convex hull of two interval matrices.
`tr_widthm_i`	Elementwise width of an interval matrix.
`tr_winterm_i`	Intersection of two interval matrices.
`waxpby_i`	Scaled vector addition.
`wcancel_i`	Scaled cancellation.
`whullv_i`	Convex hull of an interval vector with another.
`widthv_i`	The elementwise width of an interval vector.
`winterv_i`	Intersection of an interval vector with another.

See the section 3P man pages for information on using each routine.

Sort Routines

TABLE A-12 lists the Sun Performance Library sort routines. (P) denotes routines that are parallelized on Solaris/SPARC platforms. All routines are single-threaded on Solaris/x86 platforms whether denoted by (P) or not.

TABLE A-12 Sort Routines
Routines	Function
`BLAS_DSORT` (P)	Sorts a real (double precision) vector X in increasing or decreasing order using quick sort algorithm.
`BLAS_DSORTV` (P)	Sorts a real (double precision) vector X in increasing or decreasing order using quick sort algorithm and overwrite P with the permutation vector.
`BLAS_DPERMUTE` (P)	Permutes a real (double precision) array in terms of the permutation vector P, output by `DSORTV`.
`BLAS_ISORT` (P)	Sorts an integer vector X in increasing or decreasing order using quick sort algorithm.
`BLAS_ISORTV` (P)	Sorts a real vector X in increasing or decreasing order using quick sort algorithm and overwrite P with the permutation vector.
`BLAS_IPERMUTE` (P)	Permutes an integer array in terms of the permutation vector P, output by `DSORTV.`
`BLAS_SSORT` (P)	Sorts a real vector X in increasing or decreasing order using quick sort algorithm.
`BLAS_SSORTV` (P)	Sorts a real vector X in increasing or decreasing order using quick sort algorithm and overwrite P with the permutation vector.
`BLAS_SPERMUTE` (P)	Permutes a real array in terms of the permutation vector P, output by `DSORTV`.