MPI和混合MPI+OpenMP编程范式在多核处理器集群上的性能评价

Rajkumar Sharma, P. Kanungo
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引用次数: 9

摘要

处理器设计现在转向多核架构,朝着最小化能耗的方向发展。十年前,如果没有额外的普通冷却,cpu的速度就无法加速,因此遇到了时钟速度的障碍。引入多核架构是为了通过更多CPU内核提供硬件并行性来提高计算性能,每个CPU内核都具有限制的时钟速度。这是高性能计算(HPC)的一个突破。虽然更多的处理器内核提供了有效的执行结果,但多核技术为编程问题带来了额外的复杂性。为了利用多核环境中的每个核,应用软件应该通过使用多线程进行优化。由于时钟速度的降低,多核处理器甚至会降低单线程应用程序的性能。在本文中,我们使用MPI和混合MPI+OpenMP方法比较了多线程细粒度和粗粒度计算问题的性能,并根据问题的性质评估了多核集群的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance evaluation of MPI and hybrid MPI+OpenMP programming paradigms on multi-core processors cluster
Processors design is now switched to multi-core architecture in a direction that minimizes energy consumption. A decade ago CPUs speed could not accelerate without extra ordinary cooling and consequently hit a clock speed barrier. The multi-core architecture is introduced to improve computing performance by providing hardware parallelism through more CPU cores, each having restrained clock speed. This has been a break through in High Performance Computing (HPC). While more processor cores rendered effective execution results, multi-core technology inaugurated an extra layer of complexity for programming issues. To exploit each core in a multi-core environment, application software should be optimized by using multithreading. Multi-core processors can even degrade the performance for single threaded application due to reduction in clock speed. In this paper we compare performance of multithreading fine-grained and course-grained computational problems further flavored as computation-intensive and data-intensive problems by using MPI and hybrid MPI+OpenMP approach and evaluate suitability of multi-core cluster depending on the nature of the problems.
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