Tutorial

  • 327357-009
  • 04/15/2019
  • Public Content
  • Download as PDF

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
Operation
Routine
Linear Algebra
  • BLAS
  • LAPACK/ScaLAPACK
  • PARDISO*
  • Iterative sparse solvers
Fast Fourier Transforms
  • Multidimensional (up to 7D) FFTs
  • FFTW interfaces
  • Cluster FFT
Summary Statistics
  • Kurtosis
  • Variation coefficient
  • Quantiles, order statistics
  • Min/max
  • Variance/covariance
  • ...
Data Fitting
  • Splines
  • Interpolation
  • Cell search
Other Components
  • 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

Explore 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.

Product and Performance Information

1

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