3 Library functions

pz

• pzdbsv solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzdbtrf compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
• pzdbtrs solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzdbtrsv solve a banded triangular system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzdrscl multiplie an N-element complex distributed vector sub( X ) by the real scalar 1/a
• pzdtsv solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzdttrf compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
• pzdttrs solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzdttrsv solve a tridiagonal triangular system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzgbsv solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzgbtrf compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
• pzgbtrs solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzgebd2 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 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 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 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 reduce a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation
• pzgehrd reduce a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation
• pzgelq2 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 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 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 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 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 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 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 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 improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions
• pzgerq2 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 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 compute the solution to a complex system of linear equations sub( A ) * X = sub( B ),
• pzgesvx use the LU factorization to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
• pzgetf2 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 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 compute the inverse of a distributed matrix using the LU factorization computed by PZGETRF
• pzgetrs 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 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 compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
• pzheevx compute selected eigenvalues and, optionally, eigenvectors of a complex hermitian matrix A by calling the recommended sequence of ScaLAPACK routines
• pzhegs2 reduce a complex Hermitian-definite generalized eigenproblem to standard form
• pzhegst reduce a complex Hermitian-definite generalized eigenproblem to standard form
• pzhegvx compute all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem
• pzhetd2 reduce a complex Hermitian matrix sub( A ) to Hermitian tridiagonal form T by an unitary similarity transformation
• pzhetrd reduce a complex Hermitian matrix sub( A ) to Hermitian tridiagonal form T by an unitary similarity transformation
• pzlabrd 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 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 estimate the 1-norm of a square, complex distributed matrix A
• pzlacp2 copie all or part of a distributed matrix A to another distributed matrix B
• pzlacpy copie all or part of a distributed matrix A to another distributed matrix B
• pzlaevswp 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 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 return the value of the one norm, or the Frobenius norm,
• pzlanhe return the value of the one norm, or the Frobenius norm,
• pzlanhs return the value of the one norm, or the Frobenius norm,
• pzlansy return the value of the one norm, or the Frobenius norm,
• pzlantr return the value of the one norm, or the Frobenius norm,
• pzlapiv 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 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 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 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 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 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 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 generate a complex elementary reflector H of order n, such that H * sub( X ) = H * ( x(iax,jax) ) = ( alpha ), H' * H = I
• pzlarft 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 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 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 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 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 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 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 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 return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,
• pzlaswp perform a series of row or column interchanges on the distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
• pzlatra compute the trace of an N-by-N distributed matrix sub( A ) denoting A( IA:IA+N-1, JA:JA+N-1 )
• pzlatrd 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 solve a triangular system
• pzlatrz 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 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 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)
• pzmax1 compute the global index of the maximum element in absolute value of a distributed vector sub( X )
• pzpbsv solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzpbtrf compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
• pzpbtrs solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzpbtrsv solve a banded triangular system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzpocon 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 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 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 compute the solution to a complex system of linear equations sub( A ) * X = sub( B ),
• pzposvx use the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
• pzpotf2 compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
• pzpotrf 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 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 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 solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzpttrf compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
• pzpttrs solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzpttrsv solve a tridiagonal triangular system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
• pzstein compute the eigenvectors of a symmetric tridiagonal matrix in parallel, using inverse iteration
• pztrcon 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 provide error bounds and backward error estimates for the solution to a system of linear equations with a triangular coefficient matrix
• pztrti2 compute the inverse of a complex upper or lower triangular block matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
• pztrtri compute the inverse of a upper or lower triangular distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
• pztrtrs 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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'