FLENS 2007-07-13

FLENS is:
- a C++ interface for BLAS and LAPACK
- an extremely convenient C++ interface for BLAS and LAPACK
- an extremely efficient C++ interface to BLAS and LAPACK:
- There is no run-time overhead compared to directly calling BLAS and LAPACK.
- There are no obscure side-effects like internal creation of temporary objects
FLENS is NOT:
- just a C++ interface for BLAS and LAPACK! It is more than that:
- it is extendable: e.g. easy integration of user-defined matrix/vector types.
- it is flexible: e.g. generic programming of numerical algorithms.
FLENS is DEFINITELY NOT:
- ... a replacement for Matlab. While FLENS adopted some nice notations it has a completely different intension. Ok, Matlab uses BLAS and LAPACK just like FLENS. But it uses only a subset. Matlab basically has only two data types and these are general matrices and sparse matrices. If you have matrices with band structure Matlab will not use those BLAS and LAPACK routines that exploit this structure.
- Just to make sure you get us right: We do not want to bash Matlab. It is a great tool. But you have to figure out whats the right tool for your job. Matlab is a great tool because it is very easy to use and it allows rapid prototyping. For many people the performance of Matlab is Ok. For those people there might be absolutely no reason to even consider using FLENS.
- FLENS gives you full control about whats going on behind the scene. It provides (for example) general, triangular, symmetric and hermitian matrix types. Elements of these matrices can be stored in different formats: full storage (store all m x n elements), band storage (store only diagonals of a banded matrix), packed storage (store only the upper or lower triangular part).
- FLENS implements a view concept: You can define that a vector references a row, column or diagonal of a matrix. You can define, that elements of a triangular matrix are those stored in the upper triangular part of a general matrix,...
Enhancements:
- This release adds sparse matrix types.
- There are two types for general and symmetric matrices.
- For element storage, the "compressed row storage" format is used: the elements can be initialized in random (i.e. arbitrary) order.
- The tutorial slides have been extended with a demonstration of how to use sparse matrices, more details about how linear algebra expression are evaluated by FLENS, and an example on how to extend FLENS with new matrix/vector types.