首页> 外文期刊>Journal of systems architecture >Design and analysis of static memory management policies for CC-NUMA multiprocessors
【24h】

Design and analysis of static memory management policies for CC-NUMA multiprocessors

机译:CC-NUMA多处理器的静态内存管理策略的设计和分析

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

In this paper, we characterize the performance of three existing memory management techniques, namely, buddy, round-robin, and first-touch policies. With existing memory management schemes, we find several cases where requests from different processors arrive at the same memory simultaneously. To alleviate this problem, we present two improved memory management policies called skew-mapping and prime-mapping policies. By utilizing the properties of skewing and prime, the improved memory management designs considerably improve the application performance of cache coherent non-uniform memory access multiprocessors. We also re-evaluate the performance of a multistage interconnection network using these existing and improved memory management policies. Our results effectively present the performance benefits of different memory management techniques based on the sharing patterns of applications. Applications with a low degree of sharing benefit from the data locality provided by first-touch. However, several applications with significant sharing degrees as well as those with single processor initialization routines benefit highly from the intelligent distribution of data provided by skew-mapping and prime-mapping schemes. Improvements due to the new schemes are found to be as high as 35% in stall time.
机译:在本文中,我们描述了三种现有内存管理技术的性能,即伙伴,轮循和首次接触策略。利用现有的内存管理方案,我们发现了几种情况,其中来自不同处理器的请求会同时到达同一内存。为了缓解此问题,我们提出了两种改进的内存管理策略,分别称为偏斜映射和素数映射策略。通过利用偏斜和素数的属性,改进的内存管理设计可显着提高缓存一致性非均匀内存访问多处理器的应用程序性能。我们还使用这些现有的和改进的内存管理策略来重新评估多级互连网络的性能。我们的结果基于应用程序的共享模式有效地展示了不同内存管理技术的性能优势。共享程度低的应用程序会受益于第一触式提供的数据局部性。但是,具有显着共享度的几个应用程序以及具有单处理器初始化例程的应用程序都将从偏斜映射和质数映射方案提供的数据智能分发中受益匪浅。发现新方案带来的改进使停顿时间高达35%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号