文章研究了使用OpenMP进行并行编程，比较冒泡排序、快速排序和归并排序的串行与并行性能。在8和16个虚拟CPU的服务器上测试，结果显示并行冒泡排序在大数据集上更高效，而并行快速排序和归并排序显著减少了大数据集的执行时间。超线程技术在大工作负载下提升性能，但对小数据集效果有限。性能提升依赖于数据集大小和算法特性。

Brett Estrade在TPRC 2024上成功演讲，介绍了使用OpenMP并行化Perl/C代码的方法。OpenMP是一种简单的方法，可以在Inline::C代码中并行化代码。结合Many Core Engine（MCE）和OpenMP，Perl用户可以提高硬件性能。Killing It With Perl开始了关于Perl/C并行应用编程的博客系列，第一篇文章介绍了对OpenMP环境的基本控制。

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A bit more than a year ago, we gave an update about recent changes in apt.llvm.org. Since then, we noticed an important increase of the usage of the service. Just last month, we saw more than...

OpenMP support in Clang compiler is completed! Every pragma and clause from 3.1 version of the standard is supported in full, including combined directives (like ‘#pragma omp parallel for’ and...

I am extremely glad to announce that Intel has decided to provide a copy of our Intel® open-source OpenMP* runtime as an LLVM sub-project (and the LLVM project has been kind enough to accept our...