Intel Math Kernel Library (Intel MKL) is a library of highly optimized, extensively threaded math routines for science, engineering, and financial applications that require maximum performance. Core math functions include BLAS, LAPACK, ScaLAPACK, Sparse Solvers, Fast Fourier Transforms, Vector Math, and more. Offering performance optimizations for Intel processors, it includes improved integration with Microsoft Visual Studio, Eclipse, and XCode. Intel MKL allows for full integration of the Intel compatibility OpenMP run-time library for greater Linux cross-platform compatibility.
Outstanding performance on Intel processors
Achieve leadership performance from the math library that is highly optimized for, Intel Xeon, Intel Core, Intel Itanium, and Intel Pentium 4 processor-based systems. Special attention has been paid to optimizing multithreaded performance for the Intel Xeon Quadcore processors and the Intel Core i7 Quad-Core processors. Intel MKL strives for performance, competitive with that of other math software packages on non-Intel processors.
Excellent scaling on multi-core and multiprocessor systems: Use the built-in parallelism of Intel MKL to automatically obtain excellent scaling on multi-core and multiprocessors including Intel Xeon 5500 and the latest dual and quad-core systems. Intel MKL BLAS, Fast Fourier transforms, and Vector Math, among many other routines are threaded using OpenMP. Thread-Safety: all Intel MKL functions are thread-safe, a non-threaded sequential version of Intel MKL is also provided.
Performance improvements cover several key math routines including LINPACK, Out-of-core PARDISO, BLAS, and FFT. In addition, Intel AVX (Advanced Vector Extensions) support is included for advanced vectorization being introduced in upcoming Intel architecture processors. This provides support for 256-bit vector operations, in many cases doubling performance. These are provided earlier to test and develop forward scaling in your applications.