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Remove obsolete bench/ and btl/ directories

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libeigen/eigen!2217

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
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Rasmus Munk Larsen
2026-02-25 20:19:45 -08:00
parent 6e2aff6b5d
commit a95440de17
220 changed files with 9 additions and 21383 deletions
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doc/SparseLinearSystems.dox
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@@ -176,7 +176,7 @@ x2 = solver.solve(b2);
For direct methods, the solution are computed at the machine precision. Sometimes, the solution need not be too accurate. In this case, the iterative methods are more suitable and the desired accuracy can be set before the solve step using \b setTolerance(). For all the available functions, please, refer to the documentation of the \link IterativeLinearSolvers_Module Iterative solvers module \endlink.
\section BenchmarkRoutine
Most of the time, all you need is to know how much time it will take to solve your system, and hopefully, what is the most suitable solver. In Eigen, we provide a benchmark routine that can be used for this purpose. It is very easy to use. In the build directory, navigate to `bench/spbench` and compile the routine by typing `make spbenchsolver`. Run it with `--help` option to get the list of all available options. Basically, the matrices to test should be in <a href="http://math.nist.gov/MatrixMarket/formats.html">MatrixMarket Coordinate format</a>, and the routine returns the statistics from all available solvers in Eigen.
Most of the time, all you need is to know how much time it will take to solve your system, and hopefully, what is the most suitable solver. You can benchmark solvers by timing them on matrices in <a href="http://math.nist.gov/MatrixMarket/formats.html">MatrixMarket Coordinate format</a>. See the `benchmarks/Sparse/` directory for example benchmarks.
To export your matrices and right-hand-side vectors in the matrix-market format, you can use the unsupported SparseExtra module:
\code