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Detecting the Eigen library

The code for this recipe is available at https://github.com/dev-cafe/cmake-cookbook/tree/v1.0/chapter-03/recipe-07 and has a C++ example. The recipe is valid with CMake version 3.9 (and higher) and has been tested on GNU/Linux, macOS, and Windows. In https://github.com/dev-cafe/cmake-cookbook/tree/v1.0/chapter-03/recipe-07, we also provide a C++ example compatible with CMake 3.5.

The BLAS library offers a standardized interface for common operations involving matrices and vectors. This interface was however standardized with the Fortran language in mind. While we have shown how these libraries can be used more or less directly from C++, it may be desirable to have a higher-level interface in modern C++ programs.

The header-only Eigen library uses template programming to offer such an interface. Its matrix and vector types are intuitive to use and even provide type checking at compile time, to ensure that incompatible matrix dimensions are not mixed. Dense and sparse matrix operations, such as matrix-matrix products, solvers for linear systems, and eigenvalue problems, are also implemented using expression templates for efficiency. From version 3.3, Eigen can be linked to the BLAS and LAPACK libraries, which provides the flexibility to offload certain operations to the implementation given in these libraries for additional performance.

This recipe will show how to find the Eigen library and to instruct it to use OpenMP parallelization and offload some of the work to the BLAS library.