Courseware - Software Processes

  • Software life-cycle and process models
  • Software process capability maturity models
  • Approaches to process improvement
  • Process assessment models
  • Software process measurements



CSE445/598 Project on Multithreading and Multi-Core Processing (ASU)



Material Type:

  • 教授
  • 学生
  • OpenMP*
  • Software Engineering
  • Software Processes
  • multicore
  • distributed
  • Service
  • WSDL
  • soap
  • xml
  • distributed software development
  • SOA
  • Services
  • database
  • workflow
  • Textbook
  • Web Computing
  • web service
  • 并行计算
  • 线程
  • 云计算
  • OpenMP not using all processors

    I am trying to use MKL libraries and OpenMP in a MSVS C++ application on Windows7. The application shows affinity for all 24 processors (2 nodes, 6 processors, HyperThreaded). omp_get_num_procs() also shows 24 processors.  When I run the program only 1 node and 6 processors are accessed. This is confirmed  when I use "KMP_AFFINITY=verbose,none". It ouputs "OMP: Info #179: KMP_AFFINITY: 1 packages x 6 cores/pkg x 1 threads/core (6 total cores)".  I get no compiler or linker complaints.

    Intel® Parallel Studio XE 2015 Update 2 Cluster Edition Readme

    The Intel® Parallel Studio XE 2015 Update 2 Cluster Edition for Linux* and Windows* combines all Intel® Parallel Studio XE and Intel® Cluster Tools into a single package. This multi-component software toolkit contains the core libraries and tools to efficiently develop, optimize, run, and distribute parallel applications for clusters with Intel processors.  This package is for cluster users who develop on and build for IA-32 and Intel® 64 architectures on Linux* and Windows*, as well as customers running over the Intel® Xeon Phi™ coprocessor on Linux*. It contains:

  • Apple OS X*
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 8.x
  • 服务器
  • C/C++
  • Fortran
  • 英特尔® Parallel Studio XE Cluster Edition
  • 消息传递接口 (MPI)
  • OpenMP*
  • 云计算
  • Performance comparison between Intel TBB task_list, openMP task and parallel for

    I am planning on parallelizing a hotspot in a project. And I would like to know your opinion between the performance evaluation between parallel for, omp single followed by task and intel TBB task_list, under ideal conditions where number of threads are equal to computation items and when computation are much greater than available threads to see scheduling overhead(in order to evaluate the most efficient scheduler). I will also, be writing some sample test programs to evaluate myself but I also wanted to know if anybody had previously made these evaluations.

    Thanks in advance.

    英特尔® 至强™ 处理器和英特尔® 至强融核™ 协处理器上的 miniGhost


    本文可为针对英特尔® 至强™ 处理器和英特尔® 至强融核™ 协处理器上运行的 miniGhost 代码提供代码访问、构建和运行说明。


    miniGhost 是一种有限差分方法,可用于在同构三维域中实施差分模板。

    - 模板选项计算,
    - 进程间边界 (halo, ghost) 交换,
    - 网格值全局总和。

    miniGhost 主要用于研究计算环境中 BSPMA 配置的性能特征,这些计算广泛应用于各种不同的科学算法。

    在 BSPMA(带有消息聚合功能的整体同步并行) 模型中,针对每个变量的面部数据(face data)被聚合至用户托管的缓冲区内。 然后,缓冲区被传送至(最多)6 个相邻的进程,并针对每个变量应用所选模板的计算。 另外一种模型是 SVAF(单变量,聚合面部数据),但本文仅讨论 BSMPA 模型。

    miniGhost 可作为来自 Sandia 的 CTH (Shock Physics) 代码的代理(或 miniapp)。

  • Linux*
  • 服务器
  • C/C++
  • miniGhost
  • OpenMP*
  • Intel® Many Integrated Core Architecture
  • 订阅 OpenMP*