Intel® MKL with NumPy, SciPy, MATLAB, C#, Python, NAG and More

The following article explains on using Intel® MKL with NumPy/SciPy, Matlab, C#, Java, Python, NAG, Gromacs, Gnu Octave, PETSc, HPL, HPCC, IMSL etc.
作者: Gennady F. (Blackbelt) 最后更新时间: 2019/06/23 - 18:50

Using Intel® MKL with R


作者: TODD R. (Intel) 最后更新时间: 2019/03/27 - 10:00

Extending R with Intel MKL


作者: TODD R. (Intel) 最后更新时间: 2019/03/27 - 13:20

Build R-3.4.2 with Intel® C++ and Fortran Compilers and Intel® MKL on Linux*

R is a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. This guide will show how to build R with the Intel® C++ and Fortran Compilers and BLAS and LAPACK libraries within Intel® Math Kernel...
作者: Devorah H. (Intel) 最后更新时间: 2018/06/19 - 18:22

Performance Comparison of OpenBLAS* and Intel® Math Kernel Library in R

Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
作者: Nguyen, Khang T (Intel) 最后更新时间: 2019/07/06 - 16:40