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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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Using Intel® IPP Threaded Static Libraries

Q: How to get Intel® Integrated Performance Primitives (Intel® IPP) Static threaded libraries?

Authored by Last updated on 06/23/2019 - 18:50
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Intel® System Studio Matrix Multiplication Sample

This is a "matrix multiplication" example that illustrates different features of Intel® System Studio on Microsoft* Visual Studio* IDE, Eclipse* IDE and on Yocto* Target System By Downloading or copying all or any part of the sample source code, you agree to the terms of the Intel® Sample Source Code License Agreement
Authored by Last updated on 06/23/2019 - 18:50
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OpenMP* and the Intel® IPP Library

How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Authored by Last updated on 06/23/2019 - 18:50
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Intel® IPP - Threading / OpenMP* FAQ

This page contains common questions and answers on multi-threading in the Intel IPP.
Authored by Last updated on 06/23/2019 - 18:50
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Developing Embedded application on Intel® Atom™ Processor E3800 (Formerly Bay Trail) using Intel® System Studio 2015

This article is about developing any type of embedded application on Intel® Atom™ 3800 processor using Intel® System Studio
Authored by Last updated on 06/23/2019 - 18:50
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Intel® VTune™ Amplifier XE - Profiling Windows* Services

Steps to profile Windows* services by Intel® VTune™ Amplifier XE
Authored by Kirill R. (Intel) Last updated on 06/23/2019 - 18:50
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Using Intel® Math Kernel Library and Intel® Integrated Performance Primitives in the Microsoft* .NET* Framework

This article is about calling intel® MKL and Intel® from .NET framework
Authored by Last updated on 06/23/2019 - 18:50
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Writing High Performance .NET Code

With Microsoft® .NET Framework, developers can now quickly build rich and robust business solutions. Because architecture and design of these solutions is not straightforward, developers must be aware of core performance issues. This paper discusses designing for performance as well as providing information about common mistakes.
Authored by Milind Hanchinmani (Intel) Last updated on 06/23/2019 - 18:50
File Wrapper

Parallel Universe Magazine - Issue 10, June 2012

Authored by admin Last updated on 06/23/2019 - 19:00