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An Introduction to the Cilk Screen Race Detector

One of the pitfalls of parallel programming is the need to consider whether your code modifies a memory location in two parallel strands.

Автор: Barry Tannenbaum (Intel) Последнее обновление: 25.05.2018 - 15:30
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The switch() statement isn't really evil, right?

In my current position, I work to optimize and parallelize codes that deal with genomic data, e.g., DNA, RNA, proteins, etc.

Автор: Clay B. (Blackbelt) Последнее обновление: 04.07.2019 - 10:46
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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.

Автор: Andrey Karpov (Blackbelt) Последнее обновление: 30.05.2018 - 07:08
Article

Using Intel® MKL and Intel® TBB in the same application

Intel MKL 11.3 has introduced Intel TBB support.

Автор: Gennady F. (Blackbelt) Последнее обновление: 01.08.2019 - 09:22
Article

Intel® Math Kernel Library - Introducing Vectorized Compact Routines

Introduction     
Автор: Gennady F. (Blackbelt) Последнее обновление: 04.07.2019 - 21:35
Article

Intel® Data Analytics Acceleration Library - Decision Trees

Decision trees method is one of most popular approaches in machine learning. They can easily be used to solve different classification and regression tasks.
Автор: Gennady F. (Blackbelt) Последнее обновление: 17.09.2019 - 16:25
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The Last Line Effect

Автор: Andrey Karpov (Blackbelt) Последнее обновление: 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...
Автор: David S. (Blackbelt) Последнее обновление: 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...
Автор: David S. (Blackbelt) Последнее обновление: 09.12.2019 - 12:20