Software developers wanting to enjoy the performance benefits of Intel® Math Kernel Library (Intel® MKL) in C++ environments can use popular open source C++ template libraries and link them with Intel MKL. These higher-level libraries enable users to leverage abstracted C++ classes to perform vector math, BLAS, LAPACK and some sparse computations while also achieving performance similar to what Intel MKL library provides.
To discover more about the C++ libraries available, refer to the documentation available at the links below.
C++ math library
Supported MKL functionality
BLAS (level 2, 3)
LAPACK(LU, Cholesky, QR, SVD, Eigvalues, Shur)
BLAS (dot, gemv, gemm)
LAPACK (LU, Cholesky, QR, SVD, Eigvalues)
together with BOOST numeric bindings
Issues found in the C++ libraries listed in the table above should be reported to the open source library owners. Any issues determined to be caused by Intel MKL should be reported on the Intel MKL forum or Online Service Center