Implementation of well-known numerical methods.
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Updated
Aug 8, 2021 - Python
Implementation of well-known numerical methods.
Numerical Analysis
OpenACC GPU parallelization for various numerical methods and miscellaneous problems using FORTRAN
OpenMP parallelization for various numerical methods and miscellaneous problems using C
A sort of functions in Scilab so as to execute the iterative methods for sparse linear systems.
GaussSeidelIteration-Implementation is a project that demonstrates the implementation of the Gauss-Seidel iterative numerical method in the C programming language. This method is used to solve systems of linear equations and is known for its convergence properties and efficiency.
MPI parallelization for various numerical methods and miscellaneous problems using FORTRAN
OpenMP parallelization for various numerical methods and miscellaneous problems using FORTRAN
OpenACC GPU parallelization for various numerical methods and miscellaneous problems using C
An command-line app to solve systems of equations (3x3 only) using the iterative Gauss-Seidel Method, with user-specified decimal accuracy.
This repository contains a Python implementation of the Gauss-Seidel Elimination method for solving systems of linear equations. The code reads coefficients from an Excel file (`data.xls`), performs Gauss-Seidel iteration with relaxation, and saves the results in a new Excel file. The method also includes error checking and verifies the results.
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