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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.
Authored by Gennady F. (Blackbelt) Last updated on 06/23/2019 - 18:50
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Analyzing Intel® SDE's TSX-related log data for capacity aborts

Starting with version 7.12.0, Intel® SDE has Intel® TSX-related instruction and memory access logging features which can be useful for debugging Intel® TSX's capacity aborts.

Authored by Last updated on 07/06/2019 - 10:52
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How to Get Intel® Math Kernel Library, Intel® Integrated Performance Primitives, or Intel® Data Analytics Acceleration Library

This page provides links to the current ways to get the Intel® Performance Libraries: Intel® Math Kernel Library (Intel® MKL), Intel® Integrated Performance Primitives (Intel® IPP), or Intel® Data

Authored by Ying H. (Intel) Last updated on 07/03/2019 - 15:43
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The Inside Scoop on How We Accelerated NumPy Umath Functions

NumPy UMath Optimizations

Authored by Andres G. (Intel) Last updated on 05/30/2018 - 07:08
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Open Source Project: Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel has created a data analytics acceleration project on github, to help accelerate data analytic

Authored by James R. (Blackbelt) Last updated on 08/27/2019 - 13:50
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How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel® Data Analytics Acceleration Library (Intel® DAAL) is a software solution that offers building blocks covering all the stages of data analytics, from preprocessing to decision making. The beta version of Intel DAAL 2017 provides support for the Python* language.
Authored by Gennady F. (Blackbelt) Last updated on 08/27/2019 - 14:30
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Intel® Performance Counter Monitor - A Better Way to Measure CPU Utilization

The Intel® Performance Counter Monitor provides sample C++ routines and utilities to estimate the internal resource utilization of the latest Intel® Xeon® and Core™ processors and gain a significant performance boost.
Authored by Thomas Willhalm (Intel) Last updated on 10/01/2019 - 15:30
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MeshCentral - Introduction & Overview

 
Authored by Ylian S. (Blackbelt) Last updated on 10/08/2019 - 18:20