Intel® Cilk™ Plus

New Intel Cilk Plus runtime sources and SDK is now available

New Intel Cilk Plus runtime sources and SDK were just released and are available for download now.

  • Intel Cilk Plus runtime sources build 4420 contains minor scheduler improvements and community-contributed Raspberry Pi* port
  • Intel Cilk Plus SDK build 4421 contains support for the latest Linux*, Windows*, and Mac OS X* operating systems

More information can be found at https://www.cilkplus.org/download.

Intel C++ Compiler 16.0 is now available in Intel Parallel Studio XE 2016

The new version Intel C++ Compiler 16.0 is now available in Intel Parallel Studio XE 2016 that has launched early this week. If your support license is current you can download and install this at no additional charge from the Intel Registration Center

You will find some blog postings about some new features and new free tools.

Vector of reducers that are not cache aligned

I am using Cilk and a custom reducer as described here: https://software.intel.com/en-us/node/522608. In the example, they use the reducer for append operation in a linked list.

Now, I want to create a vector of reducers (using std::vector); however, I get the following runtime error: 

Reducer should be cache aligned. Please see comments following this assertion for explanation and fixes.

Hybrid Parallelism: A MiniFE* Case Study

This case study examines the situation where the problem decomposition is the same for threading as it is for Message Passing Interface* (MPI); that is, the threading parallelism is elevated to the same level as MPI parallelism.
  • Profissional
  • Professores
  • Estudantes
  • Linux*
  • Modernização de código
  • Servidor
  • C/C++
  • Intermediário
  • Compilador C++ Intel®
  • Intel® Cilk™ Plus
  • Biblioteca MPI Intel®
  • MiniFE*
  • MPI (Message Passing Interface - Interface de transferência de mensagens)
  • OpenMP*
  • Acadêmico
  • Computação de cluster
  • Arquitetura Intel® Many Integrated Core
  • Otimização
  • Computação paralela
  • Thread
  • 整理您的数据和代码: 数据和布局 - 第 2 部分

    Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
  • Estudantes
  • Modernização de código
  • Servidor
  • Windows*
  • C/C++
  • Fortran
  • Intermediário
  • Intel® Advisor
  • Intel® Cilk™ Plus
  • Módulos de sub-rotinas Intel®
  • Intel® Advanced Vector Extensions
  • OpenMP*
  • Arquitetura Intel® Many Integrated Core
  • Otimização
  • Computação paralela
  • Thread
  • Vetorização
  • CILK PLUS w/ VxWorks 7

    Hi,

    I'm trying to load the Cilk Plus test code as documented in "GETTING STARTED WITH INTEL CILK PLUS WITH VXWORKS 7" as a downloadable kernel module (DKM) but I am getting the following undefined symbols:

    __cilkrts_hyper_destroy.

    __cilkrts_hyper_create.

    __cilkrts_cilk_for_32.

    __cilkrts_hyper_lookup.

    I have built the VxWorks 7 kernel w/ CILK support and was able to successfully execute the test code when it is linked directly into my VIP project.  Any ideas why I'm seeing issues when the test program is built as a DKM ? Thanks.

    Improve Performance with Vectorization

    This article focuses on the steps to improve software performance with vectorization. Included are examples of full applications along with some simpler cases to illustrate the steps to vectorization.
  • Profissional
  • Estudantes
  • Modernização de código
  • Servidor
  • C/C++
  • Fortran
  • Intermediário
  • Intel® Cilk™ Plus
  • Intel® Advanced Vector Extensions
  • Arquitetura Intel® Many Integrated Core
  • Otimização
  • Computação paralela
  • Vetorização
  • tracking clang updates

    I recently downloaded, from the git repo, and built the Cilk Plus/LLVM stuff.

    Playing with the generated Clang using -v, it claims to be 3.9. Surprising since 3.9 isn't really available yet, and notes about Cilk Plus/LLVM suggest it's made from a branch in February 2016. The git repo doesn't show any updates since February either.

    What's going on?

    Thanks

     

    Cilk algorithm slower than the scalar counterpart

    Hello everyone,

    I am writing a greyscale both in cilk and scalar as a project for university to compare cilk with "normal" code. Each pixel is represented as RGB (floats), as the title already states my issue is that the cilk is slower than the scalar part which i don't really understand so maybe could maybe take a look and tell me if i am doing something wrong and what would be the correct approach to implement such an algorithm in Cilk. 

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