LA is a library that provides a C vector and matrix class with an interface to LAPACK and BLAS linear algebra libraries and a few additional features. Templates (including some simple template metaprogramming) are employed in order to achieve generic applicability of the algorithms.
In particular, iterative methods suitable for sparse matrices can be applied to your custom matrix class, which does not need to provide any explicit storage of the matrix elements (only matrix times vector operation has to be implemented).
What's New in This Release: [ read full changelog ]
· This version adds support for GPU computing on NVIDIA CUDA (Fermi Tesla) cards using a transparent interface to the CUBLAS library.
· Documentation generated via Doxygen is now available (although not covering the whole library yet).