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Scope Oriented Programming

There is a long discussion talking about the advantages of Procedural Programming vs. the advantages of Object Oriented Programming.

Автор: Последнее обновление: 23.06.2019 - 19:00
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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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Introduction to OpenMP* on YouTube*

Tim Mattson (Intel) has authored an extensive series of excellent videos as in introduction to OpenMP*.

Автор: Mike P. (Intel) Последнее обновление: 04.07.2019 - 19:51
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Reduce Boilerplate Code in Parallelized Loops with C++11 Lambda Expressions

Parallelize loops with Intel® Threading Building Blocks using Intel® C++ Compiler for lambda expressions.
Автор: gaston-hillar (Blackbelt) Последнее обновление: 12.12.2018 - 18:00
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Doctor Fortran in "Eighteen is the New Fifteen"

When the international Fortran standards committee (WG5) met in 2012 to set a schedule for the next standard revision, the informal name of the standard was set to be "Fortran 2015". The schedule changed over the subsequent years, but the name stayed the same. The current schedule has the standard being published in the second half of 2018, which caused a question to be asked: "Should we perhaps...
Автор: Steve Lionel (Ret.) (Blackbelt) Последнее обновление: 12.12.2018 - 18:00
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Intel® Data Analytics Acceleration Library

The Intel® Data Analytics Acceleration Library (Intel® DAAL) helps speed big data analytics by providing highly optimized algorithmic building blocks for all data analysis stages (Pre-processing, Transformation, Analysis, Modeling, Validation, and Decision Making) for offline, streaming and distributed analytics usages. It’s designed for use with popular data platforms including Hadoop*, Spark*,...
Автор: James R. (Blackbelt) Последнее обновление: 27.08.2019 - 13:50
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英特尔® 数据分析加速库

The Intel® Data Analytics Acceleration Library (Intel® DAAL) helps speed big data analytics by providing highly optimized algorithmic building blocks for all data analysis stages (Pre-processing, Transformation, Analysis, Modeling, Validation, and Decision Making) for offline, streaming and distributed analytics usages. It’s designed for use with popular data platforms including Hadoop*, Spark*,...
Автор: James R. (Blackbelt) Последнее обновление: 27.08.2019 - 13:50
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Advanced Computer Concepts for the (Not So) Common Chef: The Multi-core Industrial Kitchen

This is going to be a short blog as there is no new material to discuss, just a simple extension of the earlier blogs (see

Автор: Последнее обновление: 15.10.2019 - 15:30
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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).

Автор: Sharmila C. (Intel) Последнее обновление: 15.10.2019 - 18:16
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Exploring Intel® Transactional Synchronization Extensions with Intel® Software Development Emulator

Intel® Transactional Synchronization Extensions (Intel® TSX) is perhaps one of the most non-trivial extensions of instruction set architecture introduced in the 4th generation Intel® Cor

Автор: Roman Dementiev (Intel) Последнее обновление: 15.10.2019 - 19:10