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An adaptive page replacement scheme for scientific applications

机译：适用于科学应用的自适应页面替换方案

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Memory management is playing an increasingly important role in application performance owing to the rapid increase in the amount of data utilized in modern computing workloads and the slow growth in the capacity of the main memory devices. We also observe that recent scientific applications are processing huge amount of data never been seen before. Scientific applications show a tendency to repeat operations on intermediate data using loops, but such access patterns are hard to be appropriately handled by LRU, which is generally used as a page replacement policy in operating systems. In this paper, we propose an adaptive page replacement (APR) scheme, which deals with looping access patterns in scientific applications. APR detects various looping access patterns online and handles them while considering the resulting performance. It can be implemented using limited events or information (e.g., page faults and access bits) provided by the virtual memory subsystem of operating systems. We evaluate APR through trace-driven simulation with traces extracted from workloads in the SPLASH-2x benchmark. Throughout the comparison with multiple previous schemes, we demonstrate that APR successfully improves the performance over the previous schemes by avoiding their downsides.
机译：由于现代计算工作负载中使用的数据量迅速增加以及主存储设备容量的缓慢增长，因此内存管理在应用程序性能中扮演着越来越重要的角色。我们还观察到，最近的科学应用正在处理前所未有的海量数据。科学应用程序显示了使用循环对中间数据重复操作的趋势，但是这种访问模式很难由LRU适当地处理，LRU通常用作操作系统中的页面替换策略。在本文中，我们提出了一种自适应页面替换（APR）方案，该方案处理科学应用中的循环访问模式。 APR在线检测各种循环访问模式并在考虑最终性能的同时进行处理。可以使用操作系统的虚拟内存子系统提供的有限事件或信息（例如，页面错误和访问位）来实现该功能。我们通过跟踪驱动的仿真来评估APR，并使用SPLASH-2x基准测试中的工作负载提取跟踪。在与多个以前的方案进行比较的过程中，我们证明了APR通过避免它们的缺点，成功地提高了其性能。

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