MatrixGold

MatrixGold

MatrixGold is open source software for matrix calculations and linear algebra. It offers efficient implementations of matrix operations and solves systems of linear equations.
Science & Math Mathematics
MatrixGold image
matrix linear-algebra calculations
MatrixGold alternatives ➤

MatrixGold: Open Source Matrix Calculations

Efficient matrix operations and system of linear equations solver, MatrixGold is open source software for matrix calculations and linear algebra.

What is MatrixGold?

MatrixGold is an open source software library focused on numeric linear algebra calculations using matrices and vectors. It provides efficient implementations of fundamental matrix operations like addition, subtraction, multiplication, transposition, inversion, decomposition, solving linear systems, computing eigenvalues, etc.

Some key features of MatrixGold include:

  • Implemented in C++ for performance and portability
  • Supports dense and sparse matrices
  • Multi-threaded parallel execution using OpenMP
  • BLAS and LAPACK integration for some operations
  • A MATLAB-like API for ease of use
  • Cross-platform support including Linux, Windows, and macOS
  • Liberal open source MIT license

MatrixGold enables fast prototyping and development of applications that need to perform large scale matrix calculations like scientific computing, machine learning, data analysis, image processing, and more. Its simple API makes it easy to add matrix capabilities to existing applications.

By building on top of established libraries like BLAS, LAPACK, and OpenMP, MatrixGold is able to achieve high performance across various hardware platforms. The code is modular and extensible to add new capabilities over time.

MatrixGold Features

Features

  1. Performs matrix calculations and linear algebra operations
  2. Implements matrix decomposition methods like LU, QR, SVD
  3. Solves systems of linear equations
  4. Provides matrix factorization algorithms
  5. Supports sparse matrices
  6. Has Python and MATLAB APIs
  7. Open source with C++ and Python implementations

Pricing

  • Open Source

Pros

Efficient and optimized algorithms

Flexible APIs for integration

Free and open source

Supports both dense and sparse matrices

Active development community

Cons

Limited documentation and examples

Not as full featured as commercial alternatives like MATLAB

Sparse matrix support could be improved

Python API needs more development

Not ideal for non technical users

Official Links

Official Website
https://www.gemvision.com/matrixgold

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