Intel® Threading Building Blocks

Joint lifetime and access synchronization algorithm for shared dynamic objects

Modern programming practices and computer languages (like .NET) tend to dynamically create and destroy objects at run-time, but how does it correlate with multi-core-enabled programming? A parallel program may need to synchronize both lifetime of- and access to- an object in shared memory.

Graduate Intern at Intel - Parallel Ray-Tracing

Submitted by dcfrogle on

Ray-tracing is a classic example of an embarrassingly parallel algorithm; since each pixel is typically independent of the rest, theoretically every pixel can be done in parallel (given enough cores). However, practically speaking the algorithm is usually parallelized on significantly fewer cores and the work is shared and distributed among them because the amount of time to render can differ greatly between pixels.

Intel® Threading Building Blocks: Scalable Programming for Multi-Core

Intel’s new parallel programming model is a new set of Libraries developed by Intel Software and Solutions Group in order to help developers write scalable code without worrying about managing threads.
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Beginner
  • Intel® Parallel Composer
  • Intel® Threading Building Blocks
  • Intel® Parallel Studio
  • Intel® Parallel Studio XE
  • Threading Building Blocks
  • Parallel Computing

    • Introducing...Concurrent Collections for distributed memory systems (distCnC)

    Intel has just released Intel® Concurrent Collections for C++ update 0.5. One of the interesting features in this update is an optional extension/plugin to the “normal” runtime system that allows the CnC graph to be executed on distributed memory systems. This article shows you how to enable your CnC program to run on a distributed memory system.

    More Parallelism: Congratulations to Microsoft on their Visual Studio 2010 launch

    Microsoft's Visual Studio 2010 development environment has, for the first time, several new parallelism capabilities built-in.  Combined with Intel® Parallel Studio, I think it is reasonable to say that Windows has the richest and most complete set of tools for multicore programming.  Microsoft has worked with Intel and others, to help tools from both companies interoperate well, and provide a well conceived set of key capabilities for other tools as well.

    Разработка примера использования библиотеки Intel® Threading Building Blocks

    Статья содержит описание работы по подбору оптимальной архитектуры взаимодействия библиотеки Intel® Threading Building Blocks и библиотеки асинхронного ввода/вывода boost::asio. Рассмотрены возможные проблемы полученных решений, проведено их сравнение.
  • Developers
  • Intel® Threading Building Blocks
  • summer school

    • Task - tree sum

    Submitted by (not verified) on

    Introduction

    This is a simple example that sums values in a tree. The example exhibits some speedup, but not a lot, because it quickly saturates the system bus on a multiprocessor. For good speedup, there needs to be more computation cycles per memory reference. The point of the example is to teach how to use the raw task interface, so the computation is deliberately trivial.

    SerialSumTree.cpp

    ==============================================================================

    Copyright 2005-2006 Intel Corporation. All Rights Reserved.

  • Intel® Threading Building Blocks
  • Threading Building Blocks
  • Multi-thread apps for Multi-Core
  • Threaded Code examples
  • Parallel Computing

    • Pages

    Subscribe to Intel® Threading Building Blocks