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matrix-computation

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LSQR-solver-course

SENATOROVAI / LSQR-solver-course

Star 17

LSQR is an iterative method for solving large, sparse, linear systems of equations and linear least-squares problems, including under- or over-determined and rank-deficient systems. It uses the Lanczos bidiagonalization process to provide a robust alternative to conjugate gradients, offering better numerical stability. Solver

python optimization solver least-squares scientific-computing iterative-methods sparse-linear-solver lsqr large-scale-optimizations numerical-linear-algebra large-scale-optimization lsqr-solver matrix-computation senatorov lsqr-python-implementation lsqr-algorithm solver-lsqr
  • Updated Mar 17, 2026
  • Python

rbga / CPU-vs-GPU-Matrix-Operation

Star 6

A performance comparison of standard matrix functions between CPU and GPU using Nvidia CUDA on Visual Studio using C++

visual-studio cpp parallel-computing cuda matrix-functions matrix-multiplication gpu-acceleration gpu-computing matrix-transpose performance-comparison nvidia-cuda matrix-addition cuda-programming cpu-vs-gpu cuda-kernel matrix-subtraction matrix-operation matrix-implementation matrix-computation matrix-performance
  • Updated Jul 29, 2023
  • Cuda

mehdihbgi3 / High-Performance-Iterative-Solvers

Star 0

High-performance C++ implementations of iterative methods for solving large sparse linear systems and computing eigenvalues, including Conjugate Gradient, Preconditioned CG, Jacobi, Arnoldi, and QR-based solvers, optimized for memory efficiency and numerical stability.

cpp computational-mathematics scientific-computing high-performance-computing finite-difference sparse-linear-systems numerical-methods conjugate-gradient sparse-matrix poisson-equation numerical-linear-algebra qr-algorithm iterative-solvers power-iteration eigenvalue-algorithms matrix-computation pde-solvers rayleigh-quotient krylov-subspace arnoldi-method
  • Updated Mar 8, 2026
  • C++

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