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Parallel Processing with Python and OpenMP

How to make Python “thread-safe” to increase performance, work around CPython challenges. The increasing popularity of Python for math and scientific programming presents some challenges for existing compilers. In this article, Slashdot Media Contributing Editor David Bolton demonstrates how to make your Python code “thread-safe” for use in today’s multicore …

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Python vs Fortran in Scientific Computing

An in-depth look at critical coding choices for today’s scientific and math problems Python is huge, free and open source, but FORTRAN is the oldest computer language still in common use. Which is better for today’s scientific and math programming tasks? Slashdot Media Contributing Editor David Bolton walks through the …

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Accelerating Python with Intel Math Kernel Library

New MKL speeds Python math, integrates with NumPy and SciPy to deliver blazing performance In this video, Intel Software evangelist James Reinders discusses the latest iteration of Intel’s Math Kernel Library which now includes support for Python and the new Xeon Phil processor, aka Knights Landings

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Getting Started with NumPy

Python instead of FORTRAN? NumPy can help get you there Many programmers are more familiar with Python than FORTRAN, but need to do higher maths. In this video, Slashdot Media Contributing Editor David Bolton shows how to get started with NumPy, a tool that gives Python some real numeric chops.

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Visual Studio Tips: Getting the most out of your Intel Systems

Choose the right settings and compiler to optimize your code for parallelization In this blog, Slashdot Media Contributing Editor Rick Leinecker demonstrates how to fine tune MS Visual Studio to ensure your code makes the most efficient use of the Intel processor designs. Visual Studio Tips Rick Leinecker, March 2016 …

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Benefits of Intel Xeon Phi Developers Program

Intel Expert discusses benefits of KNL offering You’ve probably heard lots about the second generation Intel Xeon Phi processor, known as Knights Landing (KNL). In this video, Intel Software Chief Evangelist James Reinders discusses the benefits of the new developers program focused on KNL.

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Intel Math Kernel Library (MKL) Functional Demo

Getting the most from Intel’s tools for accelerating math functions In this blog, Slashdot Media Contributing Editor David Bolton demonstrates the benefits of utilizing the Intel Math Kernel Library to accelerate the development and execution of maths functions of all types for parallel, sequential or clustered systems. Overview of Intel …

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Comparing C++ Compilers

Getting the most from Parallelized and Vectorized Code Does choice of C++ compiler make a difference when coding for parallelized and vectorized code? Slashdot Media Contributing Editor Rick Leinecker discusses the hows and whys of choosing your compiler For years I have been an advocate of the Microsoft development tools. …

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Programmer’s Guide to “Knights Landing”: Free Webinar on coding for new Xeon Phi

Experts from Colfax Research present developer-to-developer webinar on newly released Intel Xeon Phi Every developer who is or plans to code for the Intel Xeon Phi should attend this free webinar, presented by the experts at Colfax Research. This interactive event will be presented every Tuesday and Thursday in April. …

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New Intel Python Distribution Offers Substantial Performance Boost

Tech Preview leverages Intel Math Kernel Library, is free for download online. Python 2.7 and 3.5 users can expect from 2x to 90x+ increase in execution speed with the new Intel Distribution for Python, according to this brief by Slashdot Media Contributing Editor Wylie Wong Intel has introduced a beta …

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