• 520

#### 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)
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)
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,