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BSfactor(3)
Compute the incomplete factor of a matrix
BSsetup_factor(3)
Set up the communication for factorization
HPL_pdfact(3)
recursive panel factorization
HPL_pdgesv0(3)
Factor an N x N+1 matrix
HPL_pdgesvK1(3)
Factor an N x N+1 matrix
HPL_pdgesvK2(3)
Factor an N x N+1 matrix
HPL_pdpancrN(3)
Crout panel factorization
HPL_pdpancrT(3)
Crout panel factorization
HPL_pdpanllN(3)
Left-looking panel factorization
HPL_pdpanllT(3)
Left-looking panel factorization
HPL_pdpanrlN(3)
Right-looking panel factorization
HPL_pdpanrlT(3)
Right-looking panel factorization
HPL_pdrpancrN(3)
Crout recursive panel factorization
HPL_pdrpancrT(3)
Crout recursive panel factorization
HPL_pdrpanllN(3)
Left-looking recursive panel factorization
HPL_pdrpanllT(3)
Left-looking recursive panel factorization
HPL_pdrpanrlN(3)
Right-looking recursive panel factorization
HPL_pdrpanrlT(3)
Right-looking recursive panel factorization
PS_rotate(3)
Sets rotation factor
PS_scale(3)
Sets scaling factor
SoHandleBoxManip(3iv)
transform node with 3D Interface for Editing ScaleFactor and Translation
cdbtf2(l), CDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
cdbtrf(l), CDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
cdttrf(l), CDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
clanv2(l), CLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
cscout(1)
C code analyzer and refactoring browser
ddbtf2(l), DDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
ddbtrf(l), DDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
ddttrf(l), DDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
ecm(1)
integer factorization using ECM, P-1 or P+1
gfactor(1), factor(1)
factor numbers
glPixelZoom(3), "glPixelZoom(3)
specify the pixel zoom factors
login_duo(8)
second-factor authentication via Duo login service
mouse_setscale(3)
sets a mouse scale factor
pcdbtrf(l), PCDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pcdttrf(l), PCDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pcgbtrf(l), PCGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pcgecon(l), PCGECON(l)
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
pcgelq2(l), PCGELQ2(l)
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(l), PCGELQF(l)
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
pcgeql2(l), PCGEQL2(l)
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(l), PCGEQLF(l)
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(l), PCGEQPF(l)
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(l), PCGEQR2(l)
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(l), PCGEQRF(l)
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
pcgerq2(l), PCGERQ2(l)
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(l), PCGERQF(l)
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
pcgesvx(l), PCGESVX(l)
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(l), PCGETF2(l)
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(l), PCGETRF(l)
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(l), PCGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PCGETRF
pcgetrs(l), PCGETRS(l)
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(l), PCGGQRF(l)
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(l), PCGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pclaqge(l), PCLAQGE(l)
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(l), PCLAQSY(l)
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
pclarft(l), PCLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pclarzt(l), PCLARZT(l)
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
pclauu2(l), PCLAUU2(l)
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(l), PCLAUUM(l)
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)
pcpbtrf(l), PCPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pcpocon(l), PCPOCON(l)
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
pcposvx(l), PCPOSVX(l)
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),
pcpotf2(l), PCPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pcpotrf(l), PCPOTRF(l)
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(l), PCPOTRI(l)
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
pcpttrf(l), PCPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pddbtrf(l), PDDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pddttrf(l), PDDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pdgbtrf(l), PDGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
pdgecon(l), PDGECON(l)
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
pdgelq2(l), PDGELQ2(l)
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(l), PDGELQF(l)
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
pdgeql2(l), PDGEQL2(l)
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(l), PDGEQLF(l)
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(l), PDGEQPF(l)
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(l), PDGEQR2(l)
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(l), PDGEQRF(l)
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
pdgerq2(l), PDGERQ2(l)
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(l), PDGERQF(l)
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
pdgesvx(l), PDGESVX(l)
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),
pdgetf2(l), PDGETF2(l)
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(l), PDGETRF(l)
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(l), PDGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PDGETRF
pdgetrs(l), PDGETRS(l)
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(l), PDGGQRF(l)
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(l), PDGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pdlaqge(l), PDLAQGE(l)
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(l), PDLAQSY(l)
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
pdlarft(l), PDLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pdlarzt(l), PDLARZT(l)
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
pdlauu2(l), PDLAUU2(l)
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(l), PDLAUUM(l)
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)
pdpbtrf(l), PDPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pdpocon(l), PDPOCON(l)
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
pdposvx(l), PDPOSVX(l)
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(l), PDPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pdpotrf(l), PDPOTRF(l)
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(l), PDPOTRI(l)
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
pdpttrf(l), PDPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pixilate(1)
parses an input file containing Cisco PIX 6.2x - PIX 6.3x (normal mask) or Cisco IOS (inverted mask) access-list entries and generates the corresponding packets. For information on writing PIX access lists, see http://www.cisco.com/univercd/cc/td/doc/product/iaabu/pix/pix_62/cmdref/ab.htm#xtocid7 and http://www.cisco.com/warp/public/707/confaccesslists.html#intro for Cisco IOS access-lists. is currently capable of generating TCP/UDP/ICMP (various ICMP types), and IGMP utilizing the Libnet 1.1.x library available from http://www.packetfactory.net. NOTE: Libnet 1.0.x is NOT compatible."
psdbtrf(l), PSDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
psdttrf(l), PSDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
psgbtrf(l), PSGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
psgecon(l), PSGECON(l)
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
psgelq2(l), PSGELQ2(l)
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(l), PSGELQF(l)
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
psgeql2(l), PSGEQL2(l)
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(l), PSGEQLF(l)
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(l), PSGEQPF(l)
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(l), PSGEQR2(l)
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(l), PSGEQRF(l)
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
psgerq2(l), PSGERQ2(l)
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(l), PSGERQF(l)
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
psgesvx(l), PSGESVX(l)
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(l), PSGETF2(l)
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(l), PSGETRF(l)
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(l), PSGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PSGETRF
psgetrs(l), PSGETRS(l)
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(l), PSGGQRF(l)
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(l), PSGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pslaqge(l), PSLAQGE(l)
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(l), PSLAQSY(l)
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
pslarft(l), PSLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pslarzt(l), PSLARZT(l)
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
pslauu2(l), PSLAUU2(l)
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(l), PSLAUUM(l)
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)
pspbtrf(l), PSPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pspocon(l), PSPOCON(l)
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
psposvx(l), PSPOSVX(l)
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(l), PSPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pspotrf(l), PSPOTRF(l)
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(l), PSPOTRI(l)
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
pspttrf(l), PSPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pzdbtrf(l), PZDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pzdttrf(l), PZDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pzgbtrf(l), PZGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pzgecon(l), PZGECON(l)
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
pzgelq2(l), PZGELQ2(l)
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(l), PZGELQF(l)
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
pzgeql2(l), PZGEQL2(l)
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(l), PZGEQLF(l)
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(l), PZGEQPF(l)
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(l), PZGEQR2(l)
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(l), PZGEQRF(l)
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
pzgerq2(l), PZGERQ2(l)
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(l), PZGERQF(l)
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
pzgesvx(l), PZGESVX(l)
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(l), PZGETF2(l)
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(l), PZGETRF(l)
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(l), PZGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PZGETRF
pzgetrs(l), PZGETRS(l)
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(l), PZGGQRF(l)
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(l), PZGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pzlaqge(l), PZLAQGE(l)
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(l), PZLAQSY(l)
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
pzlarft(l), PZLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pzlarzt(l), PZLARZT(l)
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
pzlauu2(l), PZLAUU2(l)
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(l), PZLAUUM(l)
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)
pzpbtrf(l), PZPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pzpocon(l), PZPOCON(l)
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
pzposvx(l), PZPOSVX(l)
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(l), PZPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pzpotrf(l), PZPOTRF(l)
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(l), PZPOTRI(l)
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
pzpttrf(l), PZPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
sc_Integral(3), sc::Integral(3)
The Integral abstract class acts as a factory to provide objects that compute one and two electron integrals
sc_MOIntsTransformFactory(3), sc::MOIntsTransformFactory(3)
MOIntsTransformFactory is a factory that produces MOIntsTransform objects
sc_MOPairIterFactory(3), sc::MOPairIterFactory(3)
This class produces MOPairIter objects
sc_SCMatrixKit(3), sc::SCMatrixKit(3)
The SCMatrixKit abstract class acts as a factory for producing matrices
sdbtf2(l), SDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
sdbtrf(l), SDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
sdttrf(l), SDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
zdbtf2(l), ZDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
zdbtrf(l), ZDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
zdttrf(l), ZDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
zlanv2(l), ZLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
BSfactor(3)
Compute the incomplete factor of a matrix
BSsetup_factor(3)
Set up the communication for factorization
HPL_pdfact(3)
recursive panel factorization
HPL_pdgesv0(3)
Factor an N x N+1 matrix
HPL_pdgesvK1(3)
Factor an N x N+1 matrix
HPL_pdgesvK2(3)
Factor an N x N+1 matrix
HPL_pdpancrN(3)
Crout panel factorization
HPL_pdpancrT(3)
Crout panel factorization
HPL_pdpanllN(3)
Left-looking panel factorization
HPL_pdpanllT(3)
Left-looking panel factorization
HPL_pdpanrlN(3)
Right-looking panel factorization
HPL_pdpanrlT(3)
Right-looking panel factorization
HPL_pdrpancrN(3)
Crout recursive panel factorization
HPL_pdrpancrT(3)
Crout recursive panel factorization
HPL_pdrpanllN(3)
Left-looking recursive panel factorization
HPL_pdrpanllT(3)
Left-looking recursive panel factorization
HPL_pdrpanrlN(3)
Right-looking recursive panel factorization
HPL_pdrpanrlT(3)
Right-looking recursive panel factorization
PS_rotate(3)
Sets rotation factor
PS_scale(3)
Sets scaling factor
SoHandleBoxManip(3iv)
transform node with 3D Interface for Editing ScaleFactor and Translation
cdbtf2(l), CDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
cdbtrf(l), CDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
cdttrf(l), CDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
clanv2(l), CLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
cscout(1)
C code analyzer and refactoring browser
ddbtf2(l), DDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
ddbtrf(l), DDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
ddttrf(l), DDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
ecm(1)
integer factorization using ECM, P-1 or P+1
gfactor(1), factor(1)
factor numbers
glPixelZoom(3), "glPixelZoom(3)
specify the pixel zoom factors
login_duo(8)
second-factor authentication via Duo login service
mouse_setscale(3)
sets a mouse scale factor
pcdbtrf(l), PCDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pcdttrf(l), PCDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pcgbtrf(l), PCGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pcgecon(l), PCGECON(l)
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
pcgelq2(l), PCGELQ2(l)
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(l), PCGELQF(l)
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
pcgeql2(l), PCGEQL2(l)
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(l), PCGEQLF(l)
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(l), PCGEQPF(l)
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(l), PCGEQR2(l)
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(l), PCGEQRF(l)
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
pcgerq2(l), PCGERQ2(l)
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(l), PCGERQF(l)
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
pcgesvx(l), PCGESVX(l)
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(l), PCGETF2(l)
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(l), PCGETRF(l)
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(l), PCGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PCGETRF
pcgetrs(l), PCGETRS(l)
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(l), PCGGQRF(l)
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(l), PCGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pclaqge(l), PCLAQGE(l)
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(l), PCLAQSY(l)
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
pclarft(l), PCLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pclarzt(l), PCLARZT(l)
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
pclauu2(l), PCLAUU2(l)
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(l), PCLAUUM(l)
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)
pcpbtrf(l), PCPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pcpocon(l), PCPOCON(l)
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
pcposvx(l), PCPOSVX(l)
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),
pcpotf2(l), PCPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pcpotrf(l), PCPOTRF(l)
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(l), PCPOTRI(l)
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
pcpttrf(l), PCPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pddbtrf(l), PDDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pddttrf(l), PDDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pdgbtrf(l), PDGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
pdgecon(l), PDGECON(l)
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
pdgelq2(l), PDGELQ2(l)
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(l), PDGELQF(l)
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
pdgeql2(l), PDGEQL2(l)
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(l), PDGEQLF(l)
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(l), PDGEQPF(l)
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(l), PDGEQR2(l)
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(l), PDGEQRF(l)
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
pdgerq2(l), PDGERQ2(l)
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(l), PDGERQF(l)
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
pdgesvx(l), PDGESVX(l)
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),
pdgetf2(l), PDGETF2(l)
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(l), PDGETRF(l)
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(l), PDGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PDGETRF
pdgetrs(l), PDGETRS(l)
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(l), PDGGQRF(l)
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(l), PDGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pdlaqge(l), PDLAQGE(l)
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(l), PDLAQSY(l)
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
pdlarft(l), PDLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pdlarzt(l), PDLARZT(l)
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
pdlauu2(l), PDLAUU2(l)
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(l), PDLAUUM(l)
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)
pdpbtrf(l), PDPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pdpocon(l), PDPOCON(l)
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
pdposvx(l), PDPOSVX(l)
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(l), PDPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pdpotrf(l), PDPOTRF(l)
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(l), PDPOTRI(l)
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
pdpttrf(l), PDPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pixilate(1)
parses an input file containing Cisco PIX 6.2x - PIX 6.3x (normal mask) or Cisco IOS (inverted mask) access-list entries and generates the corresponding packets. For information on writing PIX access lists, see http://www.cisco.com/univercd/cc/td/doc/product/iaabu/pix/pix_62/cmdref/ab.htm#xtocid7 and http://www.cisco.com/warp/public/707/confaccesslists.html#intro for Cisco IOS access-lists. is currently capable of generating TCP/UDP/ICMP (various ICMP types), and IGMP utilizing the Libnet 1.1.x library available from http://www.packetfactory.net. NOTE: Libnet 1.0.x is NOT compatible."
psdbtrf(l), PSDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
psdttrf(l), PSDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
psgbtrf(l), PSGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
psgecon(l), PSGECON(l)
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
psgelq2(l), PSGELQ2(l)
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(l), PSGELQF(l)
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
psgeql2(l), PSGEQL2(l)
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(l), PSGEQLF(l)
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(l), PSGEQPF(l)
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(l), PSGEQR2(l)
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(l), PSGEQRF(l)
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
psgerq2(l), PSGERQ2(l)
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(l), PSGERQF(l)
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
psgesvx(l), PSGESVX(l)
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(l), PSGETF2(l)
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(l), PSGETRF(l)
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(l), PSGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PSGETRF
psgetrs(l), PSGETRS(l)
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(l), PSGGQRF(l)
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(l), PSGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pslaqge(l), PSLAQGE(l)
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(l), PSLAQSY(l)
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
pslarft(l), PSLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pslarzt(l), PSLARZT(l)
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
pslauu2(l), PSLAUU2(l)
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(l), PSLAUUM(l)
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)
pspbtrf(l), PSPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pspocon(l), PSPOCON(l)
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
psposvx(l), PSPOSVX(l)
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(l), PSPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pspotrf(l), PSPOTRF(l)
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(l), PSPOTRI(l)
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
pspttrf(l), PSPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pzdbtrf(l), PZDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pzdttrf(l), PZDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pzgbtrf(l), PZGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pzgecon(l), PZGECON(l)
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
pzgelq2(l), PZGELQ2(l)
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(l), PZGELQF(l)
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
pzgeql2(l), PZGEQL2(l)
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(l), PZGEQLF(l)
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(l), PZGEQPF(l)
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(l), PZGEQR2(l)
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(l), PZGEQRF(l)
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
pzgerq2(l), PZGERQ2(l)
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(l), PZGERQF(l)
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
pzgesvx(l), PZGESVX(l)
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(l), PZGETF2(l)
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(l), PZGETRF(l)
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(l), PZGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PZGETRF
pzgetrs(l), PZGETRS(l)
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(l), PZGGQRF(l)
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(l), PZGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pzlaqge(l), PZLAQGE(l)
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(l), PZLAQSY(l)
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
pzlarft(l), PZLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pzlarzt(l), PZLARZT(l)
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
pzlauu2(l), PZLAUU2(l)
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(l), PZLAUUM(l)
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)
pzpbtrf(l), PZPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pzpocon(l), PZPOCON(l)
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
pzposvx(l), PZPOSVX(l)
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(l), PZPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pzpotrf(l), PZPOTRF(l)
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(l), PZPOTRI(l)
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
pzpttrf(l), PZPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
sc_Integral(3), sc::Integral(3)
The Integral abstract class acts as a factory to provide objects that compute one and two electron integrals
sc_MOIntsTransformFactory(3), sc::MOIntsTransformFactory(3)
MOIntsTransformFactory is a factory that produces MOIntsTransform objects
sc_MOPairIterFactory(3), sc::MOPairIterFactory(3)
This class produces MOPairIter objects
sc_SCMatrixKit(3), sc::SCMatrixKit(3)
The SCMatrixKit abstract class acts as a factory for producing matrices
sdbtf2(l), SDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
sdbtrf(l), SDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
sdttrf(l), SDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
zdbtf2(l), ZDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
zdbtrf(l), ZDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
zdttrf(l), ZDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
zlanv2(l), ZLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
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