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Superlearnmath The City Super Learn Math Math Kernel Library from Intel - Intel® Software Network

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2D FFT on desktop processor

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3D FFT on desktop processor

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2D FFT on server processor

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3D FFT on server processor

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Fast Fourier Transforms and Cluster FFT

Intel MKL Fast Fourier Transforms (FFT) are highly optimized and provide significant performance gains on both desktop and server processor based systems compared with alternative libraries for medium and large transform sizes. FFTW interface wrappers are included. Support for distributed memory systems (clusters) is included with Cluster FFT.





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Optimized LINPACK, Improved Performance
The Intel MKL computing math library package includes an optimized implementation of the LINPACK benchmark, which is easy to run on any Intel® architecture platform. It provides the best performance on the latest Intel® processors, getting close to the maximum Gflops supported by the underlying platform.

 

 



Vector Random Number Generators
Intel MKL Vector Statistical Library (VSL) is a collection of nine random number generators and 22 probability distributions that deliver significant performance improvements in physics, chemistry, and financial analysis.



Vector Math Library

Intel MKL provides vector implementations of computationally intensive core mathematical functions.




To learn more about Intel Math Kernel Library, download the product brief ›

What's new in Intel® Math Kernel Library 10.3


Support for Intel® Advanced Vector Extensions (Intel® AVX) to SSE

  • Faster floating point operations in BLAS, LAPACK, FFTs, VML and VSL functional domains on the upcoming Sandy Bridge processor

C interfaces for LAPACK and PARDISO for easier use by C developers

  • C LAPACK interfaces supporting row-major ordering and support for c-style (zero-based) array indexing for PARDISO arrays

New Intel® Summary Statistics Library

  • New domain covering a broad range of statistics functions

Dynamic accuracy control for VML

  • New interfaces for all VML functions that include parameters for setting accuracy mode

Additional optimizations for BLAS, LAPACK, PARDISO, FFTs, and VSL

  • Delivers increased performance for many algorithms

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