Incomplete Cholesky Decomposition

Implementation of the Incomplete Cholesky Decomposition with Thresholding
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Aktualisiert 27. Feb 2022

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Sparse Incomplete Cholesky Decomposition

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Implementation of the Incomplete Cholesky Decomposition with few methods.
The project includes a C implementation with a MATLAB MEX wrapper.

The aim is to have 3 variants of the incomplete decomposition:

  1. Threshold (IC(\tau))
    Using a threshold, $ \tau $ to define which elements will be kept from the decomposition.
    It can be using global threshold or by a column.
    Implemented
  2. Pattern (IC(l))
    Filling elements which are up to l steps in the graph of the matrix A. For l = 0 called Zero Fill where filling zeros in elements not defined by the pattern.
    Also could be filled by a given pattern of sparsity (So given A as the pattern it matches l = 0).
    Not Implemented
  3. Number of Non Zero Elements (IC(p))
    Keeps the largest p elements per column.
    Not Implemented

Generating MATLAB MEX

  1. Download the repository.
  2. Run MakeMex in MATLAB with pre defined MATLAB MEX Compiler.
  3. Go through the Unit Tests and the Run Time Analysis.

The MEX Wrapper supports only Sparse Real Matrices of Type Double.

Performance

Comparing the performance with MATLAB's functions.

Decomposition

The MEX file and MATLAB's ICT were the most memory efficient.

Pre Conditioning (Solving the Linear System)

To Do

  • Move the array sorting related code to a dedicated repository with complete run time analysis.

References

Zitieren als

Royi Avital (2024). Incomplete Cholesky Decomposition (https://github.com/RoyiAvital/IncompleteCholeskyDecomposition), GitHub. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2021a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux

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Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version Veröffentlicht Versionshinweise
1.0.0

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.