A large scale non-linear optimization library

MATLAB implementations of a variety of nonlinear programming algorithms.

Quantum Lattice Model Simulator Package

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.

OptimKit: A blissfully ignorant Julia package for gradient optimization

Implementation of ConjugateGradients method using C and Nvidia CUDA

Library of High Precision Sparse Matrix Operations Accelerated by SIMD

PyTorch implementation of Hessian Free optimisation

PyTorch implementation of the Hessian-free optimizer

Improved version of real-time physics engine that couples FEM-based deformables and rigid body dynamics

Modern Fortran sparse linear systems solver

DirectX 11 Poisson solvers using Jacobi iteration, conjugate gradient, and multi-grid method respectively.

Sparse Spectrum Gaussian Process Regression

Density Functional Theory with plane waves basis, applied on a 'quantum dot'. Volumetric visualization of orbitals with VTK

Conjugate Gradient method (CG)

General Purpose Optimization in R using C++: provides a unified C++ wrapper to call functions of the algorithms underlying the optim() solver

Source code for the CPU-Free model - a fully autonomous execution model for multi-GPU applications that completely excludes the involvement of the CPU beyond the initial kernel launch.

A set of useful algebraic preconditioners for iterative numerical linear-algebraic methods.

Sparse matrix linear equation solver, using the Conjugate Gradient algorithm

The Conjugate Gradient (CG) method is an efficient iterative algorithm for solving large, sparse systems of linear equations where the matrix is symmetric and positive-definite. It finds the minimum of a quadratic function by generating conjugate search directions, ensuring convergence in at most steps for an matrix.Solver