General MEX Implementation of Thomas' Algorithm

Version 2.7.0.2 (18.7 KB) by oreoman
MEX (C/C++) Implementation of Thomas Algorithm (or Tridiagonal Matrix Algorithm) for real and complex data.
0.0
(0)
80 Downloads
Updated 10 Mar 2020
View License on GitHub

MLDIVIDE has a great tridiagonal matrix solver for sparse matrices, and there are other implementations of Thomas' algorithm out there (see below), but I needed a faster way to solve tridiagonal systems for complex data; this seems to do the trick. On my system (and R2018b), this is about four times faster than MLDIVIDE or a straight up implementation in MATLAB.

This does use interleaved complex numbers with AVX instructions for complex operations, so to compile for use just put it on your path, type "mex -R2018a 'CFLAGS=-mavx' tdma.c" and it should work.

For a MEX implementation that works on REAL data, please see:
https://www.mathworks.com/matlabcentral/fileexchange/38640-implementation-of-thomas-algorithm--mex

For a MATLAB implementation that works on all data, please see:
https://www.mathworks.com/matlabcentral/fileexchange/40722-tridiag-m

Cite As

oreoman (2024). General MEX Implementation of Thomas' Algorithm (https://github.com/michael-nix/MATLAB-MEX-Thomas-Algorithm), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2018b
Compatible with R2018a and later releases
Platform Compatibility
Windows macOS Linux
Categories
Find more on Code Generation, GPU, and Third-Party Support in Help Center and MATLAB Answers
Acknowledgements

Inspired by: Implementation of Thomas algorithm, mex, tridiag.m

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
2.7.0.2

Connecting to GitHub...
2.7.0.1

Of course I forgot a few important comments on how to compile the MEX thread pool stuff so... fixed.
2.7.0

Added in a version that includes use of new persistent Thread Pool code for multi-threading, greatly speeding up smaller 2D and 3D problems.
2.6.5.0

Fixed a stupid logic error for 3D problems.
2.6.0.0

Added additional error checking, and updated some notes on multi-threading performance.
2.5.0.0

Added in limited multi-threading support, with underwhelming results.
2.0.0.0

Updated to include real data too, and to handle multi-dimensional problems without the need for permutation and reshaping of inputs / outputs.
1.0.0.0

Added in some error checks so things don't just crash MATLAB if you're off by a little bit.

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.