Since Eigen version 3.1 and later, users can benefit from built-in Intel® Math Kernel Library (MKL) optimizations with an installed copy of Intel MKL 10.3 (or later).
Intel MKL provides highly optimized multi-threaded mathematical routines for x86-compatible architectures. Intel MKL is available on Linux, Mac and Windows for both Intel64 and IA32 architectures.
Using Intel MKL through Eigen is easy:
EIGEN_USE_MKL_ALLmacro before including any Eigen's header
When doing so, a number of Eigen's algorithms are silently substituted with calls to Intel MKL routines. These substitutions apply only for Dynamic or large enough objects with one of the following four standard scalar types:
complex<double>. Operations on other scalar types or mixing reals and complexes will continue to use the built-in algorithms.
In addition you can choose which parts will be substituted by defining one or multiple of the following macros:
|Enables the use of external BLAS level 2 and 3 routines|
|Enables the use of external Lapack routines via the Lapacke C interface to Lapack|
|Same as |
This currently concerns only JacobiSVD which otherwise would be replaced by
|Enables the use of Intel VML (vector operations)|
Note that the BLAS and LAPACKE backends can be enabled for any F77 compatible BLAS and LAPACK libraries. See this page for the details.
The following table summarizes the list of functions covered by
|Code example||MKL routines|
In the examples, v1 and v2 are dense vectors.