ViennaCL

ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects.

Features

Three computing backends: CUDA, OpenCL, OpenMP
Iterative Solvers: Conjugate Gradient, Stabilized BiConjugate Gradient, Generalized Minimum Residual
Preconditioners: ICHOL, ILUT, ILU0, Block-ILU, AMG, (F)SPAI, Jacobi
BLAS Level 1, Level 2 and Level 3 routines on GPUs and multi-core CPUs
Fast sparse matrix-vector and sparse matrix-matrix products
Convenient C++ wrappers for common linear algebra operations
Fast Fourier transform
C++ Interface is mostly uBLAS compatible
Interfaces for uBLAS, Armadillo, Eigen and MTL 4
Iterative Solvers can directly be used with uBLAS, Armadillo, Eigen and MTL4 objects
Structured matrices: Circulant, Hankel, Toeplitz, Vandermonde
OpenCL Kernel optimization environment for optimal performance on the target device
Header-only library
MATLAB interface for the iterative solvers (separate download)
Python interface (PyViennaCL)

Project Activity

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License

MIT License

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ViennaCL Web Site

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matusi143 Posted 2014-06-03

Great project and team.

Additional Project Details

Operating Systems

BSD, Linux, Mac, Windows

Intended Audience

Engineering, Science/Research

Programming Language

C++

Related Categories

C++ Algorithms, C++ Mathematics Software, C++ Libraries

Registered

2010-05-12

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