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 SCSL User's Guide
(document number: 007-4325-001 / published: 2003-12-30)    table of contents  |  additional info  |  download
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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

Prev Table of Contents 
Glossary   

SCSL User's Guide
(document number: 007-4325-001 / published: 2003-12-30)    table of contents  |  additional info  |  download

    Front Matter
    About This Guide
    Chapter 1. Introduction
    Chapter 2. Basic Linear Algebra Subprogram (BLAS) Routines
    Chapter 3. LAPACK
    Chapter 4. Using Sparse Linear Equation Solvers
    Chapter 5. Signal Processing Routines
    Appendix A. Supported SCSL Routines
    Glossary
    Index


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