Man Pages in scalapack-doc

Section 3: Library calls

cdttrf.3

Compute an lu factorization of a complex tridiagonal matrix a using elimination without partial pivoting

cdttrsv.3

Solve one of the systems of equations l * x = b, l**t * x = b, or l**h * x = b,

cpttrsv.3

Solve one of the triangular systems l * x = b, or l**h * x = b,

ddttrf.3

Compute an lu factorization of a complex tridiagonal matrix a using elimination without partial pivoting

ddttrsv.3

Solve one of the systems of equations l * x = b, l**t * x = b, or l**h * x = b,

dlamsh.3

Send multiple shifts through a small (single node) matrix to see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulges that can be sent through

dlaref.3

Applie one or several householder reflectors of size 3 to one or two matrices (if column is specified) on either their rows or columns

dlasorte.3

Sort eigenpairs so that real eigenpairs are together and complex are together

dlasrt2.3

The numbers in d in increasing order (if id = 'i') or in decreasing order (if id = 'd' )

dpttrsv.3

Solve one of the triangular systems l**t* x = b, or l * x = b,

dstein2.3

Compute the eigenvectors of a real symmetric tridiagonal matrix t corresponding to specified eigenvalues, using inverse iteration

dsteqr2.3

I a modified version of lapack routine dsteqr

pcdbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcdbtrf.3

Compute a lu factorization of an n-by-n complex banded diagonally dominant-like distributed matrix with bandwidth bwl, bwu

pcdbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcdbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcdtsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcdttrf.3

Compute a lu factorization of an n-by-n complex tridiagonal diagonally dominant-like distributed matrix a(1:n, ja:ja+n-1)

pcdttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcdttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcgbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcgbtrf.3

Compute a lu factorization of an n-by-n complex banded distributed matrix with bandwidth bwl, bwu

pcgbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcgebd2.3

Reduce a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an unitary transformation

pcgebrd.3

Reduce a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an unitary transformation

pcgecon.3

Estimate the reciprocal of the condition number of a general distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by pcgetrf

pcgeequ.3

Compute row and column scalings intended to equilibrate an m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number

pcgehd2.3

Reduce a complex general distributed matrix sub( a ) to upper hessenberg form h by an unitary similarity transformation

pcgehrd.3

Reduce a complex general distributed matrix sub( a ) to upper hessenberg form h by an unitary similarity transformation

pcgelq2.3

Compute a lq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pcgelqf.3

Compute a lq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pcgels.3

Solve overdetermined or underdetermined complex linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1),

pcgeql2.3

Compute a ql factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pcgeqlf.3

Compute a ql factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pcgeqpf.3

Compute a qr factorization with column pivoting of a m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pcgeqr2.3

Compute a qr factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pcgeqrf.3

Compute a qr factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pcgerfs.3

Improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions

pcgerq2.3

Compute a rq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pcgerqf.3

Compute a rq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pcgesv.3

Compute the solution to a complex system of linear equations sub( a ) * x = sub( b ),

pcgetf2.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pcgetrf.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pcgetri.3

Compute the inverse of a distributed matrix using the lu factorization computed by pcgetrf

pcgetrs.3

Solve a system of distributed linear equations op( sub( a ) ) * x = sub( b ) with a general n-by-n distributed matrix sub( a ) using the lu factorization computed by pcgetrf

pcggqrf.3

Compute a generalized qr factorization of an n-by-m matrix sub( a ) = a(ia:ia+n-1,ja:ja+m-1) and an n-by-p matrix sub( b ) = b(ib:ib+n-1,jb:jb+p-1)

pcggrqf.3

Compute a generalized rq factorization of an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pchegs2.3

Reduce a complex hermitian-definite generalized eigenproblem to standard form

pchegst.3

Reduce a complex hermitian-definite generalized eigenproblem to standard form

pchetd2.3

Reduce a complex hermitian matrix sub( a ) to hermitian tridiagonal form t by an unitary similarity transformation

pchetrd.3

Reduce a complex hermitian matrix sub( a ) to hermitian tridiagonal form t by an unitary similarity transformation

pclabrd.3

Reduce the first nb rows and columns of a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an unitary transformation q' * a * p, and returns the matrices x and y which are needed to apply the transfor- mation to the unreduced part of sub( a )

pclacgv.3

Conjugate a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if incx = descx( m_ ) and x(ix:ix+n-1,jx) if incx = 1, and notes ===== each global data object is described by an associated description vector

pclacon.3

Estimate the 1-norm of a square, complex distributed matrix a

pclacp2.3

Copie all or part of a distributed matrix a to another distributed matrix b

pclacpy.3

Copie all or part of a distributed matrix a to another distributed matrix b

pclaevswp.3

Move the eigenvectors (potentially unsorted) from where they are computed, to a scalapack standard block cyclic array, sorted so that the corresponding eigenvalues are sorted

pclahrd.3

Reduce the first nb columns of a complex general n-by-(n-k+1) distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero

pclange.3

Return the value of the one norm, or the frobenius norm,

pclanhe.3

Return the value of the one norm, or the frobenius norm,

pclanhs.3

Return the value of the one norm, or the frobenius norm,

pclansy.3

Return the value of the one norm, or the frobenius norm,

pclantr.3

Return the value of the one norm, or the frobenius norm,

pclapiv.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pclapv2.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pclaqge.3

Equilibrate a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using the row and scaling factors in the vectors r and c

pclaqsy.3

Equilibrate a symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the scaling factors in the vectors sr and sc

pclarf.3

Applie a complex elementary reflector q to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pclarfb.3

Applie a complex block reflector q or its conjugate transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right

pclarfc.3

Applie a complex elementary reflector q**h to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1),

pclarfg.3

Generate a complex elementary reflector h of order n, such that h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i

pclarft.3

Form the triangular factor t of a complex block reflector h of order n, which is defined as a product of k elementary reflectors

pclarz.3

Applie a complex elementary reflector q to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pclarzb.3

Applie a complex block reflector q or its conjugate transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right

pclarzc.3

Applie a complex elementary reflector q**h to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1),

pclarzt.3

Form the triangular factor t of a complex block reflector h of order n, which is defined as a product of k elementary reflectors as returned by pctzrzf

pclascl.3

Multiplie the m-by-n complex distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom

pclase2.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pclaset.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pclassq.3

Return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,

pclaswp.3

Perform a series of row or column interchanges on the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pclatra.3

Compute the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 )

pclatrd.3

Reduce nb rows and columns of a complex hermitian distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) to complex tridiagonal form by an unitary similarity transformation q' * sub( a ) * q, and returns the matrices v and w which are needed to apply the transformation to the unreduced part of sub( a )

pclatrs.3

Solve a triangular system

pclatrz.3

Reduce the m-by-n ( m=n ) complex upper trapezoidal matrix sub( a ) = [a(ia:ia+m-1,ja:ja+m-1) a(ia:ia+m-1,ja+n-l:ja+n-1)]

pclauu2.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pclauum.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pcpbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcpbtrf.3

Compute a cholesky factorization of an n-by-n complex banded symmetric positive definite distributed matrix with bandwidth bw

pcpbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcpbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcpocon.3

Estimate the reciprocal of the condition number (in the 1-norm) of a complex hermitian positive definite distributed matrix using the cholesky factorization a = u**h*u or a = l*l**h computed by pcpotrf

pcpoequ.3

Compute row and column scalings intended to equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm)

pcporfs.3

Improve the computed solution to a system of linear equations when the coefficient matrix is hermitian positive definite and provides error bounds and backward error estimates for the solutions

pcposv.3

Compute the solution to a complex system of linear equations sub( a ) * x = sub( b ),

pcpotf2.3

Compute the cholesky factorization of a complex hermitian positive definite distributed matrix sub( a )=a(ia:ia+n-1,ja:ja+n-1)

pcpotrf.3

Compute the cholesky factorization of an n-by-n complex hermitian positive definite distributed matrix sub( a ) denoting a(ia:ia+n-1, ja:ja+n-1)

pcpotri.3

Compute the inverse of a complex hermitian positive definite distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the cholesky factorization sub( a ) = u**h*u or l*l**h computed by pcpotrf

pcpotrs.3

Solve a system of linear equations sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+nrhs-1)

pcptsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcpttrf.3

Compute a cholesky factorization of an n-by-n complex tridiagonal symmetric positive definite distributed matrix a(1:n, ja:ja+n-1)

pcpttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcpttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pcsrscl.3

Multiplie an n-element complex distributed vector sub( x ) by the real scalar 1/a

pcstein.3

Compute the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration

pctrcon.3

Estimate the reciprocal of the condition number of a triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm

pctrrfs.3

Provide error bounds and backward error estimates for the solution to a system of linear equations with a triangular coefficient matrix

pctrti2.3

Compute the inverse of a complex upper or lower triangular block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pctrtri.3

Compute the inverse of a upper or lower triangular distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pctrtrs.3

Solve a triangular system of the form sub( a ) * x = sub( b ) or sub( a )**t * x = sub( b ) or sub( a )**h * x = sub( b ),

pctzrzf.3

Reduce the m-by-n ( m=n ) complex upper trapezoidal matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper triangular form by means of unitary transformations

pcung2l.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pcung2r.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pcungl2.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)'

pcunglq.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)'

pcungql.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pcungqr.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pcungr2.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1)' h(2)'

pcungrq.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1)' h(2)'

pcunm2l.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunm2r.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmbr.3

Vect = 'q', pcunmbr overwrites the general complex distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmhr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunml2.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmlq.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmql.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmqr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmr2.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmr3.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmrq.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmrz.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pcunmtr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pddbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pddbtrf.3

Compute a lu factorization of an n-by-n real banded diagonally dominant-like distributed matrix with bandwidth bwl, bwu

pddbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pddbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pddtsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pddttrf.3

Compute a lu factorization of an n-by-n real tridiagonal diagonally dominant-like distributed matrix a(1:n, ja:ja+n-1)

pddttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pddttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdgbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdgbtrf.3

Compute a lu factorization of an n-by-n real banded distributed matrix with bandwidth bwl, bwu

pdgbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdgebd2.3

Reduce a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an orthogonal transformation

pdgebrd.3

Reduce a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an orthogonal transformation

pdgecon.3

Estimate the reciprocal of the condition number of a general distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by pdgetrf

pdgeequ.3

Compute row and column scalings intended to equilibrate an m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number

pdgehd2.3

Reduce a real general distributed matrix sub( a ) to upper hessenberg form h by an orthogonal similarity transforma- tion

pdgehrd.3

Reduce a real general distributed matrix sub( a ) to upper hessenberg form h by an orthogonal similarity transforma- tion

pdgelq2.3

Compute a lq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pdgelqf.3

Compute a lq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pdgels.3

Solve overdetermined or underdetermined real linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1),

pdgeql2.3

Compute a ql factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pdgeqlf.3

Compute a ql factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pdgeqpf.3

Compute a qr factorization with column pivoting of a m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pdgeqr2.3

Compute a qr factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pdgeqrf.3

Compute a qr factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pdgerfs.3

Improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions

pdgerq2.3

Compute a rq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pdgerqf.3

Compute a rq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pdgesv.3

Compute the solution to a real system of linear equations sub( a ) * x = sub( b ),

pdgesvd.3

Compute the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or right singular vectors

pdgetf2.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pdgetrf.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pdgetri.3

Compute the inverse of a distributed matrix using the lu factorization computed by pdgetrf

pdgetrs.3

Solve a system of distributed linear equations op( sub( a ) ) * x = sub( b ) with a general n-by-n distributed matrix sub( a ) using the lu factorization computed by pdgetrf

pdggqrf.3

Compute a generalized qr factorization of an n-by-m matrix sub( a ) = a(ia:ia+n-1,ja:ja+m-1) and an n-by-p matrix sub( b ) = b(ib:ib+n-1,jb:jb+p-1)

pdggrqf.3

Compute a generalized rq factorization of an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pdlabad.3

Take as input the values computed by pdlamch for underflow and overflow, and returns the square root of each of these values if the log of large is sufficiently large

pdlabrd.3

Reduce the first nb rows and columns of a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an orthogonal transformation q' * a * p,

pdlacon.3

Estimate the 1-norm of a square, real distributed matrix a

pdlaconsb.3

Look for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible

pdlacp2.3

Copie all or part of a distributed matrix a to another distributed matrix b

pdlacp3.3

I an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa

pdlacpy.3

Copie all or part of a distributed matrix a to another distributed matrix b

pdlaevswp.3

Move the eigenvectors (potentially unsorted) from where they are computed, to a scalapack standard block cyclic array, sorted so that the corresponding eigenvalues are sorted

pdlahqr.3

I an auxiliary routine used to find the schur decomposition and or eigenvalues of a matrix already in hessenberg form from cols ilo to ihi

pdlahrd.3

Reduce the first nb columns of a real general n-by-(n-k+1) distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero

pdlamch.3

Determine double precision machine parameters

pdlange.3

Return the value of the one norm, or the frobenius norm,

pdlanhs.3

Return the value of the one norm, or the frobenius norm,

pdlansy.3

Return the value of the one norm, or the frobenius norm,

pdlantr.3

Return the value of the one norm, or the frobenius norm,

pdlapiv.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pdlapv2.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pdlaqge.3

Equilibrate a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using the row and scaling factors in the vectors r and c

pdlaqsy.3

Equilibrate a symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the scaling factors in the vectors sr and sc

pdlared1d.3

Redistribute a 1d array it assumes that the input array, bycol, is distributed across rows and that all process column contain the same copy of bycol

pdlared2d.3

Redistribute a 1d array it assumes that the input array, byrow, is distributed across columns and that all process rows contain the same copy of byrow

pdlarf.3

Applie a real elementary reflector q (or q**t) to a real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pdlarfb.3

Applie a real block reflector q or its transpose q**t to a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1)

pdlarfg.3

Generate a real elementary reflector h of order n, such that h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i

pdlarft.3

Form the triangular factor t of a real block reflector h of order n, which is defined as a product of k elementary reflectors

pdlarz.3

Applie a real elementary reflector q (or q**t) to a real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pdlarzb.3

Applie a real block reflector q or its transpose q**t to a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1)

pdlarzt.3

Form the triangular factor t of a real block reflector h of order n, which is defined as a product of k elementary reflectors as returned by pdtzrzf

pdlascl.3

Multiplie the m-by-n real distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom

pdlase2.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pdlaset.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pdlasmsub.3

Look for a small subdiagonal element from the bottom of the matrix that it can safely set to zero

pdlassq.3

Return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,

pdlaswp.3

Perform a series of row or column interchanges on the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pdlatra.3

Compute the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 )

pdlatrd.3

Reduce nb rows and columns of a real symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) to symmetric tridiagonal form by an orthogonal similarity transformation q' * sub( a ) * q,

pdlatrs.3

Solve a triangular system

pdlatrz.3

Reduce the m-by-n ( m=n ) real upper trapezoidal matrix sub( a ) = [ a(ia:ia+m-1,ja:ja+m-1) a(ia:ia+m-1,ja+n-l:ja+n-1) ] to upper triangular form by means of orthogonal transformations

pdlauu2.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pdlauum.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pdlawil.3

Get the transform given by h44,h33, & h43h34 into v starting at row m

pdorg2l.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pdorg2r.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pdorgl2.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)

pdorglq.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)

pdorgql.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pdorgqr.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pdorgr2.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1) h(2)

pdorgrq.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1) h(2)

pdorm2l.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdorm2r.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormbr.3

Vect = 'q', pdormbr overwrites the general real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormhr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdorml2.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormlq.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormql.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormqr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormr2.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormr3.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormrq.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormrz.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdormtr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pdpbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdpbtrf.3

Compute a cholesky factorization of an n-by-n real banded symmetric positive definite distributed matrix with bandwidth bw

pdpbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdpbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdpocon.3

Estimate the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matrix using the cholesky factorization a = u**t*u or a = l*l**t computed by pdpotrf

pdpoequ.3

Compute row and column scalings intended to equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm)

pdporfs.3

Improve the computed solution to a system of linear equations when the coefficient matrix is symmetric positive definite and provides error bounds and backward error estimates for the solutions

pdposv.3

Compute the solution to a real system of linear equations sub( a ) * x = sub( b ),

pdpotf2.3

Compute the cholesky factorization of a real symmetric positive definite distributed matrix sub( a )=a(ia:ia+n-1,ja:ja+n-1)

pdpotrf.3

Compute the cholesky factorization of an n-by-n real symmetric positive definite distributed matrix sub( a ) denoting a(ia:ia+n-1, ja:ja+n-1)

pdpotri.3

Compute the inverse of a real symmetric positive definite distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the cholesky factorization sub( a ) = u**t*u or l*l**t computed by pdpotrf

pdpotrs.3

Solve a system of linear equations sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+nrhs-1)

pdptsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdpttrf.3

Compute a cholesky factorization of an n-by-n real tridiagonal symmetric positive definite distributed matrix a(1:n, ja:ja+n-1)

pdpttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdpttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pdrscl.3

Multiplie an n-element real distributed vector sub( x ) by the real scalar 1/a

pdstebz.3

Compute the eigenvalues of a symmetric tridiagonal matrix in parallel

pdstein.3

Compute the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration

pdsygs2.3

Reduce a real symmetric-definite generalized eigenproblem to standard form

pdsygst.3

Reduce a real symmetric-definite generalized eigenproblem to standard form

pdsytd2.3

Reduce a real symmetric matrix sub( a ) to symmetric tridiagonal form t by an orthogonal similarity transformation

pdsytrd.3

Reduce a real symmetric matrix sub( a ) to symmetric tridiagonal form t by an orthogonal similarity transformation

pdtrcon.3

Estimate the reciprocal of the condition number of a triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm

pdtrrfs.3

Provide error bounds and backward error estimates for the solution to a system of linear equations with a triangular coefficient matrix

pdtrti2.3

Compute the inverse of a real upper or lower triangular block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pdtrtri.3

Compute the inverse of a upper or lower triangular distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pdtrtrs.3

Solve a triangular system of the form sub( a ) * x = sub( b ) or sub( a )**t * x = sub( b ),

pdtzrzf.3

Reduce the m-by-n ( m=n ) real upper trapezoidal matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper triangular form by means of orthogonal transformations

pdzsum1.3

Return the sum of absolute values of a complex distributed vector sub( x ) in asum,

pscsum1.3

Return the sum of absolute values of a complex distributed vector sub( x ) in asum,

psdbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psdbtrf.3

Compute a lu factorization of an n-by-n real banded diagonally dominant-like distributed matrix with bandwidth bwl, bwu

psdbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psdbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psdtsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psdttrf.3

Compute a lu factorization of an n-by-n real tridiagonal diagonally dominant-like distributed matrix a(1:n, ja:ja+n-1)

psdttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psdttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psgbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psgbtrf.3

Compute a lu factorization of an n-by-n real banded distributed matrix with bandwidth bwl, bwu

psgbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psgebd2.3

Reduce a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an orthogonal transformation

psgebrd.3

Reduce a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an orthogonal transformation

psgecon.3

Estimate the reciprocal of the condition number of a general distributed real matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by psgetrf

psgeequ.3

Compute row and column scalings intended to equilibrate an m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number

psgehd2.3

Reduce a real general distributed matrix sub( a ) to upper hessenberg form h by an orthogonal similarity transforma- tion

psgehrd.3

Reduce a real general distributed matrix sub( a ) to upper hessenberg form h by an orthogonal similarity transforma- tion

psgelq2.3

Compute a lq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

psgelqf.3

Compute a lq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

psgels.3

Solve overdetermined or underdetermined real linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1),

psgeql2.3

Compute a ql factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

psgeqlf.3

Compute a ql factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

psgeqpf.3

Compute a qr factorization with column pivoting of a m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

psgeqr2.3

Compute a qr factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

psgeqrf.3

Compute a qr factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

psgerfs.3

Improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions

psgerq2.3

Compute a rq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

psgerqf.3

Compute a rq factorization of a real distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

psgesv.3

Compute the solution to a real system of linear equations sub( a ) * x = sub( b ),

psgesvd.3

Compute the singular value decomposition (svd) of an m-by-n matrix a, optionally computing the left and/or right singular vectors

psgetf2.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

psgetrf.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

psgetri.3

Compute the inverse of a distributed matrix using the lu factorization computed by psgetrf

psgetrs.3

Solve a system of distributed linear equations op( sub( a ) ) * x = sub( b ) with a general n-by-n distributed matrix sub( a ) using the lu factorization computed by psgetrf

psggqrf.3

Compute a generalized qr factorization of an n-by-m matrix sub( a ) = a(ia:ia+n-1,ja:ja+m-1) and an n-by-p matrix sub( b ) = b(ib:ib+n-1,jb:jb+p-1)

psggrqf.3

Compute a generalized rq factorization of an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pslabad.3

Take as input the values computed by pslamch for underflow and overflow, and returns the square root of each of these values if the log of large is sufficiently large

pslabrd.3

Reduce the first nb rows and columns of a real general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an orthogonal transformation q' * a * p,

pslacon.3

Estimate the 1-norm of a square, real distributed matrix a

pslaconsb.3

Look for two consecutive small subdiagonal elements by seeing the effect of starting a double shift qr iteration given by h44, h33, & h43h34 and see if this would make a subdiagonal negligible

pslacp2.3

Copie all or part of a distributed matrix a to another distributed matrix b

pslacp3.3

I an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa

pslacpy.3

Copie all or part of a distributed matrix a to another distributed matrix b

pslaevswp.3

Move the eigenvectors (potentially unsorted) from where they are computed, to a scalapack standard block cyclic array, sorted so that the corresponding eigenvalues are sorted

pslahqr.3

I an auxiliary routine used to find the schur decomposition and or eigenvalues of a matrix already in hessenberg form from cols ilo to ihi

pslahrd.3

Reduce the first nb columns of a real general n-by-(n-k+1) distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero

pslamch.3

Determine single precision machine parameters

pslange.3

Return the value of the one norm, or the frobenius norm,

pslanhs.3

Return the value of the one norm, or the frobenius norm,

pslansy.3

Return the value of the one norm, or the frobenius norm,

pslantr.3

Return the value of the one norm, or the frobenius norm,

pslapiv.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pslapv2.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pslaqge.3

Equilibrate a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using the row and scaling factors in the vectors r and c

pslaqsy.3

Equilibrate a symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the scaling factors in the vectors sr and sc

pslared1d.3

Redistribute a 1d array it assumes that the input array, bycol, is distributed across rows and that all process column contain the same copy of bycol

pslared2d.3

Redistribute a 1d array it assumes that the input array, byrow, is distributed across columns and that all process rows contain the same copy of byrow

pslarf.3

Applie a real elementary reflector q (or q**t) to a real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pslarfb.3

Applie a real block reflector q or its transpose q**t to a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1)

pslarfg.3

Generate a real elementary reflector h of order n, such that h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i

pslarft.3

Form the triangular factor t of a real block reflector h of order n, which is defined as a product of k elementary reflectors

pslarz.3

Applie a real elementary reflector q (or q**t) to a real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pslarzb.3

Applie a real block reflector q or its transpose q**t to a real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1)

pslarzt.3

Form the triangular factor t of a real block reflector h of order n, which is defined as a product of k elementary reflectors as returned by pstzrzf

pslascl.3

Multiplie the m-by-n real distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom

pslase2.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pslaset.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pslasmsub.3

Look for a small subdiagonal element from the bottom of the matrix that it can safely set to zero

pslassq.3

Return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,

pslaswp.3

Perform a series of row or column interchanges on the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pslatra.3

Compute the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 )

pslatrd.3

Reduce nb rows and columns of a real symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) to symmetric tridiagonal form by an orthogonal similarity transformation q' * sub( a ) * q,

pslatrs.3

Solve a triangular system

pslatrz.3

Reduce the m-by-n ( m=n ) real upper trapezoidal matrix sub( a ) = [ a(ia:ia+m-1,ja:ja+m-1) a(ia:ia+m-1,ja+n-l:ja+n-1) ] to upper triangular form by means of orthogonal transformations

pslauu2.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pslauum.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pslawil.3

Get the transform given by h44,h33, & h43h34 into v starting at row m

psorg2l.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

psorg2r.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

psorgl2.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)

psorglq.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)

psorgql.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

psorgqr.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

psorgr2.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1) h(2)

psorgrq.3

Generate an m-by-n real distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1) h(2)

psorm2l.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psorm2r.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormbr.3

Vect = 'q', psormbr overwrites the general real distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormhr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psorml2.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormlq.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormql.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormqr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormr2.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormr3.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormrq.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormrz.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

psormtr.3

Overwrite the general real m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pspbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pspbtrf.3

Compute a cholesky factorization of an n-by-n real banded symmetric positive definite distributed matrix with bandwidth bw

pspbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pspbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pspocon.3

Estimate the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matrix using the cholesky factorization a = u**t*u or a = l*l**t computed by pspotrf

pspoequ.3

Compute row and column scalings intended to equilibrate a distributed symmetric positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm)

psporfs.3

Improve the computed solution to a system of linear equations when the coefficient matrix is symmetric positive definite and provides error bounds and backward error estimates for the solutions

psposv.3

Compute the solution to a real system of linear equations sub( a ) * x = sub( b ),

pspotf2.3

Compute the cholesky factorization of a real symmetric positive definite distributed matrix sub( a )=a(ia:ia+n-1,ja:ja+n-1)

pspotrf.3

Compute the cholesky factorization of an n-by-n real symmetric positive definite distributed matrix sub( a ) denoting a(ia:ia+n-1, ja:ja+n-1)

pspotri.3

Compute the inverse of a real symmetric positive definite distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the cholesky factorization sub( a ) = u**t*u or l*l**t computed by pspotrf

pspotrs.3

Solve a system of linear equations sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+nrhs-1)

psptsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pspttrf.3

Compute a cholesky factorization of an n-by-n real tridiagonal symmetric positive definite distributed matrix a(1:n, ja:ja+n-1)

pspttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pspttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

psrscl.3

Multiplie an n-element real distributed vector sub( x ) by the real scalar 1/a

psstebz.3

Compute the eigenvalues of a symmetric tridiagonal matrix in parallel

psstein.3

Compute the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration

pssygs2.3

Reduce a real symmetric-definite generalized eigenproblem to standard form

pssygst.3

Reduce a real symmetric-definite generalized eigenproblem to standard form

pssytd2.3

Reduce a real symmetric matrix sub( a ) to symmetric tridiagonal form t by an orthogonal similarity transformation

pssytrd.3

Reduce a real symmetric matrix sub( a ) to symmetric tridiagonal form t by an orthogonal similarity transformation

pstrcon.3

Estimate the reciprocal of the condition number of a triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm

pstrrfs.3

Provide error bounds and backward error estimates for the solution to a system of linear equations with a triangular coefficient matrix

pstrti2.3

Compute the inverse of a real upper or lower triangular block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pstrtri.3

Compute the inverse of a upper or lower triangular distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pstrtrs.3

Solve a triangular system of the form sub( a ) * x = sub( b ) or sub( a )**t * x = sub( b ),

pstzrzf.3

Reduce the m-by-n ( m=n ) real upper trapezoidal matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper triangular form by means of orthogonal transformations

pzdbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzdbtrf.3

Compute a lu factorization of an n-by-n complex banded diagonally dominant-like distributed matrix with bandwidth bwl, bwu

pzdbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzdbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzdrscl.3

Multiplie an n-element complex distributed vector sub( x ) by the real scalar 1/a

pzdtsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzdttrf.3

Compute a lu factorization of an n-by-n complex tridiagonal diagonally dominant-like distributed matrix a(1:n, ja:ja+n-1)

pzdttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzdttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzgbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzgbtrf.3

Compute a lu factorization of an n-by-n complex banded distributed matrix with bandwidth bwl, bwu

pzgbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzgebd2.3

Reduce a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an unitary transformation

pzgebrd.3

Reduce a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form b by an unitary transformation

pzgecon.3

Estimate the reciprocal of the condition number of a general distributed complex matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm, using the lu factorization computed by pzgetrf

pzgeequ.3

Compute row and column scalings intended to equilibrate an m-by-n distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja:ja+n-1) and reduce its condition number

pzgehd2.3

Reduce a complex general distributed matrix sub( a ) to upper hessenberg form h by an unitary similarity transformation

pzgehrd.3

Reduce a complex general distributed matrix sub( a ) to upper hessenberg form h by an unitary similarity transformation

pzgelq2.3

Compute a lq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pzgelqf.3

Compute a lq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = l * q

pzgels.3

Solve overdetermined or underdetermined complex linear systems involving an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1),

pzgeql2.3

Compute a ql factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pzgeqlf.3

Compute a ql factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * l

pzgeqpf.3

Compute a qr factorization with column pivoting of a m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pzgeqr2.3

Compute a qr factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pzgeqrf.3

Compute a qr factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = q * r

pzgerfs.3

Improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions

pzgerq2.3

Compute a rq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pzgerqf.3

Compute a rq factorization of a complex distributed m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) = r * q

pzgesv.3

Compute the solution to a complex system of linear equations sub( a ) * x = sub( b ),

pzgetf2.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pzgetrf.3

Compute an lu factorization of a general m-by-n distributed matrix sub( a ) = (ia:ia+m-1,ja:ja+n-1) using partial pivoting with row interchanges

pzgetri.3

Compute the inverse of a distributed matrix using the lu factorization computed by pzgetrf

pzgetrs.3

Solve a system of distributed linear equations op( sub( a ) ) * x = sub( b ) with a general n-by-n distributed matrix sub( a ) using the lu factorization computed by pzgetrf

pzggqrf.3

Compute a generalized qr factorization of an n-by-m matrix sub( a ) = a(ia:ia+n-1,ja:ja+m-1) and an n-by-p matrix sub( b ) = b(ib:ib+n-1,jb:jb+p-1)

pzggrqf.3

Compute a generalized rq factorization of an m-by-n matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pzhegs2.3

Reduce a complex hermitian-definite generalized eigenproblem to standard form

pzhegst.3

Reduce a complex hermitian-definite generalized eigenproblem to standard form

pzhetd2.3

Reduce a complex hermitian matrix sub( a ) to hermitian tridiagonal form t by an unitary similarity transformation

pzhetrd.3

Reduce a complex hermitian matrix sub( a ) to hermitian tridiagonal form t by an unitary similarity transformation

pzlabrd.3

Reduce the first nb rows and columns of a complex general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper or lower bidiagonal form by an unitary transformation q' * a * p, and returns the matrices x and y which are needed to apply the transfor- mation to the unreduced part of sub( a )

pzlacgv.3

Conjugate a complex vector of length n, sub( x ), where sub( x ) denotes x(ix,jx:jx+n-1) if incx = descx( m_ ) and x(ix:ix+n-1,jx) if incx = 1, and notes ===== each global data object is described by an associated description vector

pzlacon.3

Estimate the 1-norm of a square, complex distributed matrix a

pzlacp2.3

Copie all or part of a distributed matrix a to another distributed matrix b

pzlacpy.3

Copie all or part of a distributed matrix a to another distributed matrix b

pzlaevswp.3

Move the eigenvectors (potentially unsorted) from where they are computed, to a scalapack standard block cyclic array, sorted so that the corresponding eigenvalues are sorted

pzlahrd.3

Reduce the first nb columns of a complex general n-by-(n-k+1) distributed matrix a(ia:ia+n-1,ja:ja+n-k) so that elements below the k-th subdiagonal are zero

pzlange.3

Return the value of the one norm, or the frobenius norm,

pzlanhe.3

Return the value of the one norm, or the frobenius norm,

pzlanhs.3

Return the value of the one norm, or the frobenius norm,

pzlansy.3

Return the value of the one norm, or the frobenius norm,

pzlantr.3

Return the value of the one norm, or the frobenius norm,

pzlapiv.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pzlapv2.3

Applie either p (permutation matrix indicated by ipiv) or inv( p ) to a m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1), resulting in row or column pivoting

pzlaqge.3

Equilibrate a general m-by-n distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) using the row and scaling factors in the vectors r and c

pzlaqsy.3

Equilibrate a symmetric distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the scaling factors in the vectors sr and sc

pzlarf.3

Applie a complex elementary reflector q to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pzlarfb.3

Applie a complex block reflector q or its conjugate transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right

pzlarfc.3

Applie a complex elementary reflector q**h to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1),

pzlarfg.3

Generate a complex elementary reflector h of order n, such that h * sub( x ) = h * ( x(iax,jax) ) = ( alpha ), h' * h = i

pzlarft.3

Form the triangular factor t of a complex block reflector h of order n, which is defined as a product of k elementary reflectors

pzlarz.3

Applie a complex elementary reflector q to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1), from either the left or the right

pzlarzb.3

Applie a complex block reflector q or its conjugate transpose q**h to a complex m-by-n distributed matrix sub( c ) denoting c(ic:ic+m-1,jc:jc+n-1), from the left or the right

pzlarzc.3

Applie a complex elementary reflector q**h to a complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1),

pzlarzt.3

Form the triangular factor t of a complex block reflector h of order n, which is defined as a product of k elementary reflectors as returned by pztzrzf

pzlascl.3

Multiplie the m-by-n complex distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) by the real scalar cto/cfrom

pzlase2.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pzlaset.3

Initialize an m-by-n distributed matrix sub( a ) denoting a(ia:ia+m-1,ja:ja+n-1) to beta on the diagonal and alpha on the offdiagonals

pzlassq.3

Return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,

pzlaswp.3

Perform a series of row or column interchanges on the distributed matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1)

pzlatra.3

Compute the trace of an n-by-n distributed matrix sub( a ) denoting a( ia:ia+n-1, ja:ja+n-1 )

pzlatrd.3

Reduce nb rows and columns of a complex hermitian distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) to complex tridiagonal form by an unitary similarity transformation q' * sub( a ) * q, and returns the matrices v and w which are needed to apply the transformation to the unreduced part of sub( a )

pzlatrs.3

Solve a triangular system

pzlatrz.3

Reduce the m-by-n ( m=n ) complex upper trapezoidal matrix sub( a ) = [a(ia:ia+m-1,ja:ja+m-1) a(ia:ia+m-1,ja+n-l:ja+n-1)]

pzlauu2.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pzlauum.3

Compute the product u * u' or l' * l, where the triangular factor u or l is stored in the upper or lower triangular part of the distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pzpbsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzpbtrf.3

Compute a cholesky factorization of an n-by-n complex banded symmetric positive definite distributed matrix with bandwidth bw

pzpbtrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzpbtrsv.3

Solve a banded triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzpocon.3

Estimate the reciprocal of the condition number (in the 1-norm) of a complex hermitian positive definite distributed matrix using the cholesky factorization a = u**h*u or a = l*l**h computed by pzpotrf

pzpoequ.3

Compute row and column scalings intended to equilibrate a distributed hermitian positive definite matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) and reduce its condition number (with respect to the two-norm)

pzporfs.3

Improve the computed solution to a system of linear equations when the coefficient matrix is hermitian positive definite and provides error bounds and backward error estimates for the solutions

pzposv.3

Compute the solution to a complex system of linear equations sub( a ) * x = sub( b ),

pzpotf2.3

Compute the cholesky factorization of a complex hermitian positive definite distributed matrix sub( a )=a(ia:ia+n-1,ja:ja+n-1)

pzpotrf.3

Compute the cholesky factorization of an n-by-n complex hermitian positive definite distributed matrix sub( a ) denoting a(ia:ia+n-1, ja:ja+n-1)

pzpotri.3

Compute the inverse of a complex hermitian positive definite distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1) using the cholesky factorization sub( a ) = u**h*u or l*l**h computed by pzpotrf

pzpotrs.3

Solve a system of linear equations sub( a ) * x = sub( b ) a(ia:ia+n-1,ja:ja+n-1)*x = b(ib:ib+n-1,jb:jb+nrhs-1)

pzptsv.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzpttrf.3

Compute a cholesky factorization of an n-by-n complex tridiagonal symmetric positive definite distributed matrix a(1:n, ja:ja+n-1)

pzpttrs.3

Solve a system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzpttrsv.3

Solve a tridiagonal triangular system of linear equations a(1:n, ja:ja+n-1) * x = b(ib:ib+n-1, 1:nrhs)

pzstein.3

Compute the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration

pztrcon.3

Estimate the reciprocal of the condition number of a triangular distributed matrix a(ia:ia+n-1,ja:ja+n-1), in either the 1-norm or the infinity-norm

pztrrfs.3

Provide error bounds and backward error estimates for the solution to a system of linear equations with a triangular coefficient matrix

pztrti2.3

Compute the inverse of a complex upper or lower triangular block matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pztrtri.3

Compute the inverse of a upper or lower triangular distributed matrix sub( a ) = a(ia:ia+n-1,ja:ja+n-1)

pztrtrs.3

Solve a triangular system of the form sub( a ) * x = sub( b ) or sub( a )**t * x = sub( b ) or sub( a )**h * x = sub( b ),

pztzrzf.3

Reduce the m-by-n ( m=n ) complex upper trapezoidal matrix sub( a ) = a(ia:ia+m-1,ja:ja+n-1) to upper triangular form by means of unitary transformations

pzung2l.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pzung2r.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pzungl2.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)'

pzunglq.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the first m rows of a product of k elementary reflectors of order n q = h(k)'

pzungql.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the last n columns of a product of k elementary reflectors of order m q = h(k)

pzungqr.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal columns, which is defined as the first n columns of a product of k elementary reflectors of order m q = h(1) h(2)

pzungr2.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1)' h(2)'

pzungrq.3

Generate an m-by-n complex distributed matrix q denoting a(ia:ia+m-1,ja:ja+n-1) with orthonormal rows, which is defined as the last m rows of a product of k elementary reflectors of order n q = h(1)' h(2)'

pzunm2l.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunm2r.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmbr.3

Vect = 'q', pzunmbr overwrites the general complex distributed m-by-n matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmhr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunml2.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmlq.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmql.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmqr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmr2.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmr3.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmrq.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmrz.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

pzunmtr.3

Overwrite the general complex m-by-n distributed matrix sub( c ) = c(ic:ic+m-1,jc:jc+n-1) with side = 'l' side = 'r' trans = 'n'

sdttrf.3

Compute an lu factorization of a complex tridiagonal matrix a using elimination without partial pivoting

sdttrsv.3

Solve one of the systems of equations l * x = b, l**t * x = b, or l**h * x = b,

slamsh.3

Send multiple shifts through a small (single node) matrix to see how consecutive small subdiagonal elements are modified by subsequent shifts in an effort to maximize the number of bulges that can be sent through

slaref.3

Applie one or several householder reflectors of size 3 to one or two matrices (if column is specified) on either their rows or columns

slasorte.3

Sort eigenpairs so that real eigenpairs are together and complex are together

slasrt2.3

The numbers in d in increasing order (if id = 'i') or in decreasing order (if id = 'd' )

spttrsv.3

Solve one of the triangular systems l**t* x = b, or l * x = b,

sstein2.3

Compute the eigenvectors of a real symmetric tridiagonal matrix t corresponding to specified eigenvalues, using inverse iteration

ssteqr2.3

I a modified version of lapack routine ssteqr

zdttrf.3

Compute an lu factorization of a complex tridiagonal matrix a using elimination without partial pivoting

zdttrsv.3

Solve one of the systems of equations l * x = b, l**t * x = b, or l**h * x = b,

zpttrsv.3

Solve one of the triangular systems l * x = b, or l**h * x = b,