The following table lists links to the useful articles describing how Intel® Math Kernel Library (Intel® MKL) can be used with third-party libraries and applications.
| Topics | Description | Third Party Application/Tool |
|---|---|---|
| NumPy/SciPy with Intel® MKL | This article intends to help current NumPy/SciPy users to take advantage of Intel® Math Kernel Library (Intel® MKL). | Numpy/Scipy |
| Using Intel® MKL in R | This article shows how to configure R to use the optimized BLAS and LAPACK in the Intel® Math Kernel Library (Intel® MKL). | R |
| Using Intel® MKL in Gromacs | This article helps the current Gromacs* users get better performance by utilizing the Intel® Math Kernel Library (Intel® MKL). It explains how to build 64-bit Gromacs* with Intel MKL for Intel® 64 based applications. | Gromacs* |
| Using Intel® MKL in GNU Octave | This article helps the current GNU Octave* users to incorporate the latest versions of the Intel® Math Kernel Library (Intel® MKL) on Linux* platforms on Intel® Xeon® *processor-based systems. | Octave* |
| Using Intel MKL BLAS and LAPACK with PETSc | This article describes how to build the Portable Extensible Toolkit for Scientific Computation (PETSc) with the Intel® Math Kernel Library (Intel® MKL) BLAS and LAPACK. | PETSc |
| Performance hints for WRF on Intel® architecture | This article explains how to configure the Weather Research & Forecasting (WRF) run-time environment to achieve the best performance and scalability on Intel® architecture with Intel® software tools. | Weather Research & Forecasting (WRF) Application |
| • HPL application note | This guide helps the current HPL (High Performance LINPACK) users get better benchmark performance by utilizing Intel® Math Kernel Library (Intel® MKL) BLAS | High Performance Computing Challenge benchmarks |
| These guides help the Intel® Math Kernel Library (Intel® MKL) customers to use the latest version of Intel® MKL for Windows* OS with the MathWorks* MATLAB*. | MATLAB* | |
| Using Intel® MKL with IMSL* Fortran numerical library | This article explains how to use the latest version of the Intel® Math Kernel Library (Intel® MKL) with IMSL* Fortran Numerical Library Version 6.0.0 on Intel® architecture systems under Microsoft Windows* systems | IMSL* Fortran |
| Using Intel® MKL with the NAG* libraries | This article describes how to use the Intel® Math Kernel Library (Intel® MKL) with the NAG* libraries. Currently, Intel MKL is used for NAG's BLAS and LAPACK functionalities, with the addition of FFTs for NAG's Fortran SMP Libraries. | NAG* libraries |
| • Using Intel® MKL in your C# program • Some more additional tips "How to call MKL from your C# code" | These articles describe how to call and link the Intel® Math Kernel Library (Intel® MKL) functions from your C# code. Examples are provided for calling the BLAS, LAPACK, DFTI (the FFT interface), the PARDISO direct sparse solver, and the vector math library (VML). | C# |
| How do I use Intel® MKL with Java*? | The Intel® Math Kernel Library (Intel® MKL) package contains a set of examples that demonstrate the use of Intel MKL functions with Java*. The Java example set includes Java Native Interface (JNI) wrappers. These Java examples are intended for tutorial use only. | Java* |
| C++ template math libraries | This article provides information about existing high-level C++ APIs available to invoke MKL functionality. | |