https://github.com/miltiadiss/ceid_ny343-scientific-computing
This project consists of three tasks: 1) analyzing the execution time of chol(A) for Cholesky decomposition to verify cubic complexity. 2) working with sparse matrices stored efficiently using few vectors, similar to the LAPACK format, to solve tridiagonal systems, 3) implementing tensor operations with multidimensional arrays, such as ttt or ttv.
https://github.com/miltiadiss/ceid_ny343-scientific-computing
cholesky-decomposition lapack sparce-matrice tensor tensor-toolbox tridiagonal-system-solver
Last synced: about 1 year ago
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This project consists of three tasks: 1) analyzing the execution time of chol(A) for Cholesky decomposition to verify cubic complexity. 2) working with sparse matrices stored efficiently using few vectors, similar to the LAPACK format, to solve tridiagonal systems, 3) implementing tensor operations with multidimensional arrays, such as ttt or ttv.
- Host: GitHub
- URL: https://github.com/miltiadiss/ceid_ny343-scientific-computing
- Owner: miltiadiss
- Created: 2024-01-10T11:31:31.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-15T23:19:14.000Z (over 1 year ago)
- Last Synced: 2025-03-30T04:12:25.579Z (about 1 year ago)
- Topics: cholesky-decomposition, lapack, sparce-matrice, tensor, tensor-toolbox, tridiagonal-system-solver
- Language: MATLAB
- Homepage:
- Size: 698 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Overview
 This project is part of **Scientific Computing** compulsory course in Computer Engineering & Informatics Department of University of Patras for Winter Semester 2023 (Semester 7).