Tag Archives: C++

Overview of Parallel STL Implementation in Intel® Parallel Studio XE 2018 Beta

The Parallel STL implementation is a part of Intel® Parallel Studio XE 2018 Beta.  It offers efficient support for both parallel and vectorized execution of algorithms on Intel® processors. Under the hood, it uses an available implementation of the C++ standard library for sequential execution, Intel® Threading Building Blocks (Intel® TBB) for parallelism with par and […]

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Parallel STL: Boosting Performance of C++ STL Code

C++ and the Evolution Toward Parallelism Computing systems have evolved rapidly from single-threaded SISD architectures to modern multi- and many-core SIMD architectures, which are used in various fields and form factors. C++ is a general-purpose, performance-oriented language widely used on these modern systems. However, until recently, it didn’t provide any standardized instruments to fully utilize […]

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Code Modernization – The Importance of Cache Awareness

Thirty years ago in a simpler 8 bit world, I spent a few years developing games in 6502 and Z80 assembler. Life was simpler then with processors running at 1 MHz frequency and instructions being 2-3 words long. These Instructions took typically 2-3 clock cycles to execute but could be slower. So a maximum of […]

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Get More From Heterogeneous Computing with Threading Building Blocks (TBB)

TBB, Meet Heterogeneous Computing Computing platforms are becoming increasingly heterogeneous with the combination of CPUs, GPUs, FPGAs, co-processors, and more, but programming to take advantage of these heterogeneous environments in a single application remains a challenge. Watch this webinar to hear Jackson Marusarz of the Intel Developer Product Division present a brief overview of Intel® […]

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OpenMP: Past the Basics

So, you’ve started tinkering with OpenMP to help parallelize your code. Now what?  This video by Slashdot Media Contributing Editor Rick Leinecker points OpenMP newbies in the right direction to go beyond parallelizing for loops, and demonstrates how to avoid data race conditions while you’re doing it.  

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Using Intel Math Kernel Library: Random Number Generators

Practical application of the Intel MKL to get random All random number generators are not created equal, and having tools like the Intel Math Kernel Library makes a big difference, as demonstrated by Slashdot Media Contributing Editor David Bolton Random Number Generation with Intel MKL Not all random number generators (RNGs) are equal. If you […]

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Timing C++ Execution: Do Compilers Matter?

Execution speed can be impacted by choice of language AND compiler In this instructional video, Slashdot Media Contributing Editor David Bolton show us how to get the most performance out of C++ code by paying attention to compiler features that are in tune with hardware features.

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C++ Accelerated Massive Parallelism: CPU, GPU And Your Code

Are GPUs poised to replace general purpose CPUs? GPUs have evolved into a role far beyond their beginning as graphics co-processors. Slashdot Media Contributing Editor David Bolton looks at massively parallel constructs and how to apply GPU muscle to them The rise of the GPU (Graphical Processing Unit) to help with general purpose computing has […]

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Intel C++ and Latency: How Fast is Fast?

Have modern processor caches and new compilers solved latency in multicore/multiprocessor environments? As the limits of Moore’s law are put to the test, processors strive to drive latency down and performance up. Here, Slashdot Media Contributing Editor David Bolton takes a hard look at the numbers and shares his results. Modern processors execute instructions very […]

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Using Data Analysis Acceleration Library (DAAL) to Speed Taxi Scheduling

Part 1 of 2 – Collecting data from London’s famed Taxis to optimize routes Is “the Knowledge” enough to keep London taxis on track? In the first part of this two part series, Slashdot Media Contributing Editor David Bolton looks at London’s famous taxis, and collects data from the taxi service that will be parsed […]

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