Introduction to the Intel® Math Kernel Library

Use the Intel Math Kernel Library (Intel MKL) when you need to perform computations with high performance. Intel MKL offers highly-optimized and extensively threaded routines which implement many types of operations.

Optimization Notice
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Notice revision #20110804

Optimization Notice

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804

Linear Algebra	Fast Fourier Transforms	Summary Statistics	Data Fitting	Other Components
BLAS LAPACK/ScaLAPACK PARDISO* Iterative sparse solvers	Multidimensional (up to 7D) FFTs FFTW interfaces Cluster FFT	Kurtosis Variation coefficient Quantiles, order statistics Min/max Variance/covariance ...	Splines Interpolation Cell search	Vector Math Trigonometric Hyperbolic Exponential, Logarithmic Power/Root Rounding Vector Random Number Generators Congruential Recursive Wichmann-Hill Mersenne Twister Sobol Niederreiter RDRAND-based Poisson Solvers Optimization Solvers

Exploring Basic Linear Algebra Subprograms (BLAS)

One key area is the Basic Linear Algebra Subprograms (BLAS), which perform a variety of vector and matrix operations. This tutorial uses the dgemm routine to demonstrate how to perform matrix multiplication as efficiently as possible.