Skip to content
#

matrix-computation

Star

Here are 6 public repositories matching this topic...

Language: All
Filter by language
All 6 C++ 1 Cuda 1 Go 1 Python 1 R 1
LSQR-solver-course

SENATOROVAI / LSQR-solver-course

Star 16

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

Add this topic to your repo

To associate your repository with the matrix-computation topic, visit your repo's landing page and select "manage topics."

Learn more