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Intel® PCM Column Names Decoder Ring

When Intel Performance Counter Monitor (Intel PCM) is generating csv files as output, short names are used

Autor Thomas Willhalm (Intel) Última actualización 04/07/2019 - 19:37
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New optimizations for X86 in upcoming GCC 5.0

 

Autor Evgeny Stupachenko (Intel) Última actualización 24/01/2018 - 12:12
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Null Pointer Dereferencing Causes Undefined Behavior

I have unintentionally raised a large debate recently concerning the question if it is legal in C/C++ to use the &P->m_foo expression with P being a null pointer.

Autor Andrey Karpov (Blackbelt) Última actualización 30/05/2018 - 07:08
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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).

Autor Sharmila C. (Intel) Última actualización 15/10/2019 - 18:16
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The Last Line Effect

Autor Andrey Karpov (Blackbelt) Última actualización 20/11/2019 - 08:19
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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...
Autor David S. (Blackbelt) Última actualización 09/12/2019 - 12:20
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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).
Autor David S. (Blackbelt) Última actualización 09/12/2019 - 12:20
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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...
Autor David S. (Blackbelt) Última actualización 09/12/2019 - 12:20