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cyclic_reduction.html
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<html>
<head>
<title>
CYCLIC_REDUCTION - A Direct Solution Method for Tridiagonal Linear Systems.
</title>
</head>
<body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">
<h1 align = "center">
CYCLIC_REDUCTION <br> A Direct Solution Method for Tridiagonal Linear Systems.
</h1>
<hr>
<p>
<b>CYCLIC_REDUCTION</b>
is a C++ library which
applies the cyclic reduction method to solve a tridiagonal system of
linear equations A*x=b.
</p>
<p>
The matrix is assumed to be diagonally dominant - that is, for every row,
we require that the magnitude of the diagonal entry be at least as great
as the sum of the magnitudes of the two off-diagonal elements. This is
(just barely) true for the "-1, 2, -1" matrix, for instance.
</p>
<p>
Other methods for solving tridiagonal linear systems include:
<ul>
<li>
Gauss elimination with pivoting;
</li>
<li>
the Thomas algorithm, (Gauss elimination without pivoting);
</li>
<li>
the Jacobi, Gauss-Seidel, and SOR iterative methods;
</li>
</ul>
</p>
<p>
Cyclic reduction is a form of Gauss elimination. It proceeds by first
eliminating half of the variables simultaneously, then half of the remainder,
and so on. This amounts to more work, but the work in each elimination
step can be done in parallel. Thus, unlike the Gauss and Thomas algorithms,
cyclic reduction offers a procedure for the direct solution of a tridiagonal
linear system that can take advantage of parallelism.
</p>
<p>
Cyclic reduction can also be adapted to the block tridiagonal linear systems
that arise when Poisson's equation is discretized over a 2D region.
</p>
<h3 align = "center">
Licensing:
</h3>
<p>
The computer code and data files described and made available on this web page
are distributed under
<a href = "../../txt/gnu_lgpl.txt">the GNU LGPL license.</a>
</p>
<h3 align = "center">
Languages:
</h3>
<p>
<b>CYCLIC_REDUCTION</b> is available in
<a href = "../../c_src/cyclic_reduction/cyclic_reduction.html">a C version</a> and
<a href = "../../cpp_src/cyclic_reduction/cyclic_reduction.html">a C++ version</a> and
<a href = "../../f77_src/cyclic_reduction/cyclic_reduction.html">a FORTRAN77 version</a> and
<a href = "../../f_src/cyclic_reduction/cyclic_reduction.html">a FORTRAN90 version</a> and
<a href = "../../m_src/cyclic_reduction/cyclic_reduction.html">a MATLAB version</a>.
</p>
<h3 align = "center">
Related Data and Programs:
</h3>
<p>
<a href = "../../c_src/csparse/csparse.html">
CSPARSE</a>,
a C library which
carries out the direct solution of sparse linear systems.
</p>
<p>
<a href = "../../f_src/dlap/dlap.html">
DLAP</a>,
a FORTRAN90 library which
carries out the iterative solution of sparse linear systems.
</p>
<p>
<a href = "../../f77_src/lapack_examples/lapack_examples.html">
LAPACK_EXAMPLES</a>,
a FORTRAN77 program which
demonstrates the use of the LAPACK linear algebra library.
</p>
<p>
<a href = "../../c_src/linpack_d/linpack_d.html">
LINPACK_D</a>,
a C library which
factors and solves systems of linear equations in a variety of
formats and arithmetic types.
</p>
<p>
<a href = "../../cpp_src/linplus/linplus.html">
LINPLUS</a>,
a C++ library which
carries out simple manipulations of matrices in a variety of formats.
</p>
<p>
<a href = "../../c_src/mgmres/mgmres.html">
MGMRES</a>,
a C library which
applies the restarted GMRES algorithm to solve a sparse linear system.
</p>
<p>
<a href = "../../c_src/super_lu/super_lu.html">
SUPER_LU</a>,
a C library which
implements some very fast direct
solvers for systems of sparse linear equations.
</p>
<p>
<a href = "../../cpp_src/test_mat/test_mat.html">
TEST_MAT</a>,
a C++ library which
defines test matrices, some of
which have known determinants, eigenvalues and eigenvectors,
inverses and so on.
</p>
<h3 align = "center">
Reference:
</h3>
<p>
<ol>
<li>
Gene Golub, Charles VanLoan,<br>
Matrix Computations,<br>
Third Edition,<br>
Johns Hopkins, 1996,<br>
ISBN: 0-8018-4513-X,<br>
LC: QA188.G65.
</li>
<li>
Roger Hockney,<br>
A fast direct solution of Poisson's equation using Fourier Analysis,<br>
Journal of the ACM,<br>
Volume 12, Number 1, pages 95-113, January 1965.
</li>
</ol>
</p>
<h3 align = "center">
Source Code:
</h3>
<p>
<ul>
<li>
<a href = "cyclic_reduction.cpp">cyclic_reduction.cpp</a>, the source code.
</li>
<li>
<a href = "cyclic_reduction.hpp">cyclic_reduction.hpp</a>, the include file.
</li>
<li>
<a href = "cyclic_reduction.sh">cyclic_reduction.sh</a>,
commands to compile the source code.
</li>
</ul>
</p>
<h3 align = "center">
Examples and Tests:
</h3>
<p>
<ul>
<li>
<a href = "cyclic_reduction_prb.cpp">cyclic_reduction_prb.cpp</a>,
a sample calling program.
</li>
<li>
<a href = "cyclic_reduction_prb.sh">cyclic_reduction_prb.sh</a>,
commands to compile and run the sample program.
</li>
<li>
<a href = "cyclic_reduction_prb_output.txt">cyclic_reduction_prb_output.txt</a>,
the output file.
</li>
</ul>
</p>
<h3 align = "center">
List of Routines:
</h3>
<p>
<ul>
<li>
<b>I4_MAX</b> returns the maximum of two I4's.
</li>
<li>
<b>I4_MIN</b> returns the minimum of two I4's.
</li>
<li>
<b>R83_CR_FA</b> decomposes a real tridiagonal matrix using cyclic reduction.
</li>
<li>
<b>R83_CR_SL</b> solves a real linear system factored by R83_CR_FA.
</li>
<li>
<b>R83_GS_SL</b> solves a R83 system using Gauss-Seidel iteration.
</li>
<li>
<b>R83_MXV_NEW</b> multiplies a R83 matrix times a vector.
</li>
<li>
<b>R83_PRINT</b> prints a R83 matrix.
</li>
<li>
<b>R83_PRINT_SOME</b> prints some of a R83 matrix.
</li>
<li>
<b>R8MAT_PRINT</b> prints an R8MAT.
</li>
<li>
<b>R8MAT_PRINT_SOME</b> prints some of an R8MAT.
</li>
<li>
<b>R8VEC_INDICATOR_NEW</b> sets an R8VEC to the indicator vector {1,2,3...}.
</li>
<li>
<b>R8VEC_PRINT</b> prints an R8VEC.
</li>
<li>
<b>R8VEC_PRINT_SOME</b> prints "some" of an R8VEC.
</li>
<li>
<b>TIMESTAMP</b> prints the current YMDHMS date as a time stamp.
</li>
</ul>
</p>
<p>
You can go up one level to <a href = "../cpp_src.html">
the C++ source codes</a>.
</p>
<hr>
<i>
Last revised on 07 May 2010.
</i>
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