- pcdttrsv
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solve a tridiagonal triangular system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
- pcgbsv
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solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
- pcgbtrf
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compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
- pcgbtrs
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solve a system of linear equations A(1:N, JA:JA+N-1) * X = B(IB:IB+N-1, 1:NRHS)
- pcgebd2
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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
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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
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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
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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
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reduce a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation
- pcgehrd
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reduce a complex general distributed matrix sub( A ) to upper Hessenberg form H by an unitary similarity transformation
- pcgelq2
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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
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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
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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
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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
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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
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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
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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
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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
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improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solutions
- pcgerq2
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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
-
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
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compute the solution to a complex system of linear equations sub( A ) * X = sub( B ),
- pcgesvx
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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),
- pcgetf2
-
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
-
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
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compute the inverse of a distributed matrix using the LU factorization computed by PCGETRF
- pcgetrs
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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
-
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
-
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
- pcheevx
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compute selected eigenvalues and, optionally, eigenvectors
of a complex hermitian matrix A by calling the recommended sequence
of ScaLAPACK routines
- pchegs2
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reduce a complex Hermitian-definite generalized eigenproblem to standard form
- pchegst
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reduce a complex Hermitian-definite generalized eigenproblem to standard form
- pchegvx
-
compute all the eigenvalues, and optionally,
the eigenvectors of a complex generalized Hermitian-definite eigenproblem
- pchetd2
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reduce a complex Hermitian matrix sub( A ) to Hermitian tridiagonal form T by an unitary similarity transformation
- pchetrd
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reduce a complex Hermitian matrix sub( A ) to Hermitian tridiagonal form T by an unitary similarity transformation
- pclabrd
-
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
-
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
-
estimate the 1-norm of a square, complex distributed matrix A
- pclacp2
-
copie all or part of a distributed matrix A to another distributed matrix B
- pclacpy
-
copie all or part of a distributed matrix A to another distributed matrix B
- pclaevswp
-
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
-
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
-
return the value of the one norm, or the Frobenius norm,
- pclanhe
-
return the value of the one norm, or the Frobenius norm,
- pclanhs
-
return the value of the one norm, or the Frobenius norm,
- pclansy
-
return the value of the one norm, or the Frobenius norm,
- pclantr
-
return the value of the one norm, or the Frobenius norm,
- pclapiv
-
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
-
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
-
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