- 论坛徽章:
- 24
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如果有需要也可以用这个: https://sourceforge.net/projects/viennacl/
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)
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