📦 scalapack-doc

548 pages · page 3 of 3

P (continued)

  • 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…✨
  • 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 ),✨
  • pzgesvx(3)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(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)✨
  • pzheevx(3)compute selected eigenvalues and, optionally, eigenvectors of a complex hermitian matrix A by calling the recommended sequence of ScaLAPACK routines✨
  • pzhegs2(3)reduce a complex Hermitian-definite generalized eigenproblem to standard form✨
  • pzhegst(3)reduce a complex Hermitian-definite generalized eigenproblem to standard form✨
  • pzhegvx(3)compute all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem✨
  • 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…✨
  • 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…✨
  • 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…✨
  • 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)✨
  • pzmax1(3)compute the global index of the maximum element in absolute value of a distributed vector sub( X )✨
  • 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…✨
  • 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…✨
  • 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 ),✨
  • pzposvx(3)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(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 =…✨
  • 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…✨
  • 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 =…✨
  • 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…✨
  • 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)'…✨
  • 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)'…✨
  • 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'✨

S

  • sdbtf2(3)✨
  • sdbtrf(3)✨
  • 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…✨
  • 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✨

Z

  • zdbtf2(3)✨
  • zdbtrf(3)✨
  • 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,✨