GMRES algorithm to numerically solve matrices. Made with a custom CRS / sparse matrix lib.
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Updated
Mar 20, 2017 - Python
GMRES algorithm to numerically solve matrices. Made with a custom CRS / sparse matrix lib.
C# inplementation of generalized minimal residual method (GMRES) based on Math.NET Numerics library.
ITerative SOLvers package
A simple C++ library of Krylov subspace methods for solving linear systems
a matrix library for solving linear equations based on c++17.
Presentazione sul metodo generalizzato dei minimi residui applicabile in un sottospazio di Krylov per la soluzione numerica di equazioni lineari non simmetriche.
Implementation of a Krylov-subspace-like solver for systems of shifted linear problems.
Core part of HPL-AI implementation based on HPL-2.3. For the complete version of our HPL-AI benchmark, please go to the following site.
Trabalho da disciplina de Programação Científica da UFF, período 2020.1.
An implementation of HPL-AI Mixed-Precision Benchmark based on hpl-2.3
Compilation of the assignments of the course of COL726: Numerical Algorithms (Spring 2021) and their solutions
GMRES for large and sparse linear system
Scientific Computing exercises with tensors in MATLAB
RBF Meshless Method for Incompressible Flow
Intro algorithms to iterative Krylov methods for solving large sparse systems
A Matlab implementation of a revisited version of the MINRES for solving sparse and big linear systems arising from the KKT system of a quadratic MCF problem
MATLAB package of iterative regularization methods and large-scale test problems. This software is described in the paper "IR Tools: A MATLAB Package of Iterative Regularization Methods and Large-Scale Test Problems" that will be published in Numerical Algorithms, 2018.
modification of GMRES adapted from JuliaLinearAlgebra/IterativeSolvers.jl
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