The LA library provides a C++ vector and matrix class with an interface to BLAS and LAPACK 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).

Operating Systems

Recent releases

  •  08 Sep 2010 16:40

    Release Notes: This release 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).

    •  13 Nov 2009 15:32

      Release Notes: The library has been enclosed in the namespace "LA" to prevent name clashes; add 'using namespace LA' to your code. A new class template SparseSMat for sparse symmetric matrices has been implemented, particularly to facilitate computations of exp(iH) with H real, symmetric. Further minor improvements and bugfixes were made. In particular, you can enable/disable optimization and debugging at the ./configure level.

      •  07 Oct 2009 15:43

        Release Notes: Now users should be able to enjoy easy installation via ./configure;make.

        •  13 Sep 2009 19:25

          Release Notes: This release has minor enhancements (particularly for work with complex matrices) and bugfixes.

          •  26 Nov 2008 16:52

            Release Notes: This release contains minor bugfixes in various routines and has been checked to compile with gcc-4.3.2.


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