📦 scalapack-doc

548 pages · page 2 of 3

P (continued)

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 =…✨
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 =…✨
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 =…✨
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 =…✨
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…✨
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 ),✨
pdposvx(3)use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),✨
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✨
pdsyev(3)compute all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A by calling the recommended sequence of ScaLAPACK routines.✨
pdsyevx(3)compute selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix A by calling the recommended sequence of ScaLAPACK routines✨
pdsygs2(3)reduce a real symmetric-definite generalized eigenproblem to standard form✨
pdsygst(3)reduce a real symmetric-definite generalized eigenproblem to standard form✨
pdsygvx(3)compute all the eigenvalues, and optionally, the eigenvectors of a real generalized SY-definite eigenproblem✨
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✨
psgesvx(3)use the LU factorization to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),✨
psgetf2(3)compute an LU factorization of a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges✨
psgetrf(3)compute an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges✨
psgetri(3)compute the inverse of a distributed matrix using the LU factorization computed by PSGETRF✨
psgetrs(3)solve a system of distributed linear equations op( sub( A ) ) * X = sub( B ) with a general N-by-N distributed matrix sub( A ) using the LU factorization computed by PSGETRF✨
psggqrf(3)compute a generalized QR factorization of an N-by-M matrix sub( A ) = A(IA:IA+N-1,JA:JA+M-1) and an N-by-P matrix sub( B ) = B(IB:IB+N-1,JB:JB+P-1)✨
psggrqf(3)compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)✨
pslabad(3)take as input the values computed by PSLAMCH for underflow and overflow, and returns the square root of each of these values if the log of LARGE is sufficiently large✨
pslabrd(3)reduce the first NB rows and columns of a real general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper or lower bidiagonal form by an orthogonal transformation Q' * A * P,✨
pslacon(3)estimate the 1-norm of a square, real distributed matrix A✨
pslaconsb(3)look for two consecutive small subdiagonal elements by seeing the effect of starting a double shift QR iteration given by H44, H33, & H43H34 and see if this would make a subdiagonal negligible✨
pslacp2(3)copie all or part of a distributed matrix A to another distributed matrix B✨
pslacp3(3)i an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa✨
pslacpy(3)copie all or part of a distributed matrix A to another distributed matrix B✨
pslaevswp(3)move the eigenvectors (potentially unsorted) from where they are computed, to a ScaLAPACK standard block cyclic array, sorted so that the corresponding eigenvalues are sorted✨
pslahqr(3)i an auxiliary routine used to find the Schur decomposition and or eigenvalues of a matrix already in Hessenberg form from cols ILO to IHI✨
pslahrd(3)reduce the first NB columns of a real general N-by-(N-K+1) distributed matrix A(IA:IA+N-1,JA:JA+N-K) so that elements below the k- th subdiagonal are zero✨
pslamch(3)determine single precision machine parameters✨
pslange(3)return the value of the one norm, or the Frobenius norm,✨
pslanhs(3)return the value of the one norm, or the Frobenius norm,✨
pslansy(3)return the value of the one norm, or the Frobenius norm,✨
pslantr(3)return the value of the one norm, or the Frobenius norm,✨
pslapiv(3)applie either P (permutation matrix indicated by IPIV) or inv( P ) to a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1), resulting in row or column pivoting✨
pslapv2(3)applie either P (permutation matrix indicated by IPIV) or inv( P ) to a M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1), resulting in row or column pivoting✨
pslaqge(3)equilibrate a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using the row and scaling factors in the vectors R and C✨
pslaqsy(3)equilibrate a symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the scaling factors in the vectors SR and SC✨
pslared1d(3)redistribute a 1D array It assumes that the input array, BYCOL, is distributed across rows and that all process column contain the same copy of BYCOL✨
pslared2d(3)redistribute a 1D array It assumes that the input array, BYROW, is distributed across columns and that all process rows contain the same copy of BYROW✨
pslarf(3)applie a real elementary reflector Q (or Q**T) to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), from either the left or the right✨
pslarfb(3)applie a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1)✨
pslarfg(3)generate a real elementary reflector H of order n, such that H * sub( X ) = H * ( x(iax,jax) ) = ( alpha ), H' * H = I✨
pslarft(3)form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors✨
pslarz(3)applie a real elementary reflector Q (or Q**T) to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), from either the left or the right✨
pslarzb(3)applie a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1)✨
pslarzt(3)form the triangular factor T of a real block reflector H of order > n, which is defined as a product of k elementary reflectors as returned by PSTZRZF✨
pslascl(3)multiplie the M-by-N real distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) by the real scalar CTO/CFROM✨
pslase2(3)initialize an M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) to BETA on the diagonal and ALPHA on the offdiagonals✨
pslaset(3)initialize an M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) to BETA on the diagonal and ALPHA on the offdiagonals✨
pslasmsub(3)look for a small subdiagonal element from the bottom of the matrix that it can safely set to zero✨
pslassq(3)return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,✨
pslaswp(3)perform a series of row or column interchanges on the distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)✨
pslatra(3)compute the trace of an N-by-N distributed matrix sub( A ) denoting A( IA:IA+N-1, JA:JA+N-1 )✨
pslatrd(3)reduce NB rows and columns of a real symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) to symmetric tridiagonal form by an orthogonal similarity transformation Q' * sub( A ) * Q,✨
pslatrs(3)solve a triangular system✨
pslatrz(3)reduce the M-by-N ( M<=N ) real upper trapezoidal matrix sub( A ) = [ A(IA:IA+M-1,JA:JA+M-1) A(IA:IA+M-1,JA+N-L:JA+N-1) ] to upper triangular form by means of orthogonal transformations✨
pslauu2(3)compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)✨
pslauum(3)compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)✨
pslawil(3)get the transform given by H44,H33, & H43H34 into V starting at row M✨
psorg2l(3)generate an M-by-N real distributed matrix Q denoting A(IA:IA+M-1,JA:JA+N-1) with orthonormal columns, which is defined as the last N columns of a product of K elementary reflectors of order M Q =…✨
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 =…✨
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 =…✨
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 =…✨
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…✨
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 ),✨
psposvx(3)use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),✨
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✨
pssyev(3)compute all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A by calling the recommended sequence of ScaLAPACK routines✨
pssyevx(3)compute selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix A by calling the recommended sequence of ScaLAPACK routines✨
pssygs2(3)reduce a real symmetric-definite generalized eigenproblem to standard form✨
pssygst(3)reduce a real symmetric-definite generalized eigenproblem to standard form✨
pssygvx(3)compute all the eigenvalues, and optionally, the eigenvectors of a real generalized SY-definite eigenproblem✨
pssytd2(3)reduce a real symmetric matrix sub( A ) to symmetric tridiagonal form T by an orthogonal similarity transformation✨