Article

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.

作者: 最后更新时间: 2019/07/06 - 10:52
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PGO: Let It Go (PHP)

We can hope that companies like Intel® will come along with a faster processor. (And this does tend to happen every year). Or we can improve our compilers to produce better machine code. Or we can analyze our own code and change it to run more optimally. For PHP, we do all three: We partner with the processor architects to improve the way they execute PHP; we look for changes we can make to the...
作者: David S. (Blackbelt) 最后更新时间: 2019/07/03 - 20:08
Article

如何安装 Python* 版英特尔® 数据分析加速库(英特尔® 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.
作者: Gennady F. (Blackbelt) 最后更新时间: 2018/07/13 - 14:32
Article

The Inside Scoop on How We Accelerated NumPy Umath Functions

NumPy UMath Optimizations

作者: Andres G. (Intel) 最后更新时间: 2018/05/30 - 07:08
Article

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.
作者: Gennady F. (Blackbelt) 最后更新时间: 2019/08/27 - 14:30
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Celebrating a Decade of Parallel Programming with Intel® Threading Building Blocks (Intel® TBB)

This year marks the tenth anniversary of Intel® Threading Building Blocks (Intel® TBB).

作者: Sharmila C. (Intel) 最后更新时间: 2019/10/15 - 18:16
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Doubling the Performance of OpenStack Swift* with No Code Changes

My current gig is mostly about performance. I manage a group of software engineers dedicated to the languages becoming really important to the cloud and the datacenter.

作者: David S. (Blackbelt) 最后更新时间: 2019/10/15 - 19:31
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The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
作者: David S. (Blackbelt) 最后更新时间: 2019/10/15 - 19:42
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Core Challenge In Speeding Up Python, PHP, HHVM, Node.js...

A traditional compiler translates a high-level computer program into machine code for the CPU you want to run it on. An interpreted language translates a high-level language into the machine code for some imaginary CPU. For historical reasons, this imaginary CPU is called a "virtual machine" and its instructions are called "byte code." One advantage of this approach is development speed: creating...
作者: David S. (Blackbelt) 最后更新时间: 2019/10/15 - 19:43
博客

Dynamic Languages Take Over the Internet

The server world has really embraced Python in a big way. For example, the OpenStack project is a very popular Infrastructure as a Service offering, and most of it is written in Python. This makes Python a leader for Software Defined Infrastructure (SDI), Software Defined Storage (SDS) and Software Defined Networking (SDN).
作者: David S. (Blackbelt) 最后更新时间: 2019/10/15 - 19:44