Index
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Index
banded matrix
Sparse Matrices
Basic Linear Algebra Subprogram (BLAS)
Basic Linear Algebra Subprogram (BLAS) Routines
BLAS routines
array storage
Array Storage (BLAS 2 and BLAS 3)
C interface
C Interface to the BLAS Routines
casts
C Interface to the BLAS Routines
C/C++ function prototypes
C Interface to the BLAS Routines
data types
Data Types
increment arguments
Increment Arguments
integer argument defaults
C Interface to the BLAS Routines
Level 1
Level 1 BLAS Routines
Level 2
Level 2 BLAS Routines
Level 3
Level 3 BLAS Routines
levels
Basic Linear Algebra Subprogram (BLAS) Routines
list of
BLAS Routines
man page names
Data Types
overview
Basic Linear Algebra Subprogram (BLAS) Routines
user-defined complex types
C Interface to the BLAS Routines
C interface
in BLAS routines
C Interface to the BLAS Routines
compiler options
Introduction
complex<double> data type
Data Types
computational routines
Types of Problems Solved by LAPACK
computing a simple bound
Use in Error Bounds
condition estimation
Condition Estimation
condition number
Condition Estimation
convolution routines
Convolution and Correlation Routines
correlation routines
Convolution and Correlation Routines
data types
BLAS routines
Data Types
diagonally dominant matrix
Sparse Matrices
direct solvers
Using Sparse Linear Equation Solvers
solution techniques
How Direct Solvers Work
DITERATIVE
Iterative Solvers
double precision complex data type
Data Types
double precision data type
Data Types
driver routines
Types of Problems Solved by LAPACK
Solving from the Factored Form
EISPACK
LAPACK
equilibration
Equilibration
error bounds
Use in Error Bounds
error bounds computations
Error Bounds
error codes
Error Codes
error conditions
Error Codes
examples
error conditions
Error Codes
LU factorization
Factoring a Matrix
orthogonal factorization
Orthogonal Factorizations
roundoff errors
Condition Estimation
symmetric indefinite matrix factorization
Factoring a Matrix
explicit form
Factoring a Matrix
factored form
Factoring a Matrix
Factoring a Matrix
factoring a matrix
Factoring a Matrix
factorization forms
Factoring a Matrix
Fast Fourier Transforms
FFT Routines
casts
Implementation Details
data types
Data Types
implementation details
Implementation Details
C/C++ function prototypes
Implementation Details
data types for variables
Implementation Details
integer argument defaults
Implementation Details
isys array
Implementation Notes:
isys
Parameter Array
scratch space
Implementation Notes: Scratch Space
work and table arrays
Implementation Notes:
work
and
table
arrays
include files
Data Types
supported routines
Supported Routines
user-defined complex types
Implementation Details
FFT routines
FFT Routines
list of
FFT Routines
Fortran type declarations
Level 1 BLAS
Level 1 BLAS Routines
Hilbert matrix
Iterative Refinement
Householder transformation
Orthogonal Factorizations
ILAENV
LAPACK and SCSL
LAPACK and SCSL
increment arguments
BLAS routines
Increment Arguments
introductory man pages
Introductory Man Pages
inverse of dense matrix
Inverting a Matrix
isys array
in FFT
Implementation Notes:
isys
Parameter Array
iterative refinement
Iterative Refinement
iterative solvers
Iterative Solvers
LAPACK
and tuning parameters
LAPACK and SCSL
computation types
Naming Scheme for Individual Routines
data types supported
LAPACK and SCSL
error codes
Error Codes
factoring a matrix
Factoring a Matrix
iterative refinement
Iterative Refinement
matrix types
Naming Scheme for Individual Routines
naming scheme
Naming Scheme for Individual Routines
orthogonal factorizations
Orthogonal Factorizations
overview
LAPACK
result comparisons
Comparing Answers
simple driver routines
Solving from the Factored Form
solving from the factored form
Solving from the Factored Form
solving linear systems
Solving Linear Systems
types of problems solved
Types of Problems Solved by LAPACK
types of routines
Types of Problems Solved by LAPACK
LAPACK routines
list of
LAPACK Routines
least squares problem
Types of Problems Solved by LAPACK
least squares problems
solving
Solving Least Squares Problems
Level 1 BLAS
Level 1 BLAS Routines
Fortran type declarations
Level 1 BLAS Routines
Level 2 BLAS
Level 2 BLAS Routines
Level 3 BLAS
Level 3 BLAS Routines
levels of BLAS routines
Basic Linear Algebra Subprogram (BLAS) Routines
linear system
Sparse Matrices
linear system solutions
Types of Problems Solved by LAPACK
linkage defaults
Introduction
LINPACK
LAPACK
list of supported routines
Supported SCSL Routines
LU factorization
Factoring a Matrix
man pages
introductory
Introductory Man Pages
matrix inversion
Inverting a Matrix
naming
LAPACK routines
Naming Scheme for Individual Routines
orthogonal factorizations
Orthogonal Factorizations
orthogonal matrix
generating
Generating the Orthogonal Matrix
multiplying by
Multiplying by the Orthogonal Matrix
overdetermined linear system
Types of Problems Solved by LAPACK
parallel processing
benefits
Parallel Processing Issues
common problems
Parallel Processing Issues
costs/benefits discussion
Parallel Processing Issues
discussions of
Parallel Processing Issues
overhead
Parallel Processing Issues
QR factorization
Orthogonal Factorizations
reciprocal condition number
Condition Estimation
roundoff errors
Condition Estimation
scratch space
in FFT
Implementation Notes: Scratch Space
SCSL
compiler options
Introduction
linkage defaults
Introduction
overview
Introduction
scsl_zomplex data type
Data Types
signal processing routines
Signal Processing Routines
convolution
Convolution and Correlation Routines
correlation
Convolution and Correlation Routines
FFT
FFT Routines
single precision complex data type
Data Types
single precision data type
Data Types
solution techniques
direct methods
Direct Methods
Glossary
direct solvers
How Direct Solvers Work
iterative methods
How Iterative Methods Work
sparse linear systems
Solution Techniques
solving dense linear systems
Solving from the Factored Form
solving linear systems
Solving Linear Systems
sparse linear solvers
Using Sparse Linear Equation Solvers
sparse linear systems
solution techniques
Solution Techniques
direct methods
Direct Methods
Glossary
iterative methods
How Iterative Methods Work
sparse matrices
banded matrix
Sparse Matrices
diagonally dominant matrix
Sparse Matrices
overview
Sparse Matrices
structurally symmetric matrix
Sparse Matrices
Symmetric Positive Definite matrix
Sparse Matrices
tridiagonal matrix
Sparse Matrices
types of
Sparse Matrices
structurally symmetric matrix
Sparse Matrices
supported routines
Supported SCSL Routines
BLAS routines
BLAS Routines
FFT routines
FFT Routines
LAPACK routines
LAPACK Routines
symmetric indefinite matrix factorization
Factoring a Matrix
Symmetric Positive Definite matrix
Sparse Matrices
table array
FFT
Implementation Notes:
work
and
table
arrays
throughput
Parallel Processing Issues
tridiagonal matrix
Sparse Matrices
Tuning parameters
LAPACK and SCSL
underdetermined linear system
Types of Problems Solved by LAPACK
Solving Least Squares Problems
user-defined complex types
C Interface to the BLAS Routines
Implementation Details
work array
in FFT
Implementation Notes:
work
and
table
arrays
XERBLA
Error Codes