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Program-Counter-Based Pattern Classification in Buffer Caching

机译:缓冲区缓存中基于程序计数器的模式分类

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摘要

Program-counter-based (PC-based) prediction techniques have been shown to be highly effective and are widely used in computer architecture design. In this paper, we explore the opportunity and viability of applying PC-based prediction to operating systems design, in particular, to optimize buffer caching. We propose a Program-Counter-based Classification (PCC) technique for use in pattern-based buffer caching that allows the operating system to correlate the I/O operations with the program context in which they are issued via the program counters of the call instructions that trigger the I/O requests. This correlation allows the operating system to classify I/O access pattern on a per-PC basis which achieves significantly better accuracy than previous per-file or per-application classification techniques. PCC also performs classification more quickly as per-PC pattern just needs to be learned once. We evaluate PCC via trace-driven simulations and an implementation in Linux, and compare it to UBM, a state-of-the-art pattern-based buffer replacement scheme. The performance improvements are substantial: the hit ratio improves by as much as 29.3% (with an average of 13.8%), and the execution time is reduced by as much as 29.0% (with an average of 13.7%).
机译:基于程序计数器(基于PC)的预测技术已被证明是非常有效的,并广泛用于计算机体系结构设计中。在本文中,我们探索了将基于PC的预测应用于操作系统设计的机会和可行性,特别是优化缓冲区缓存。我们提出一种用于基于模式的缓冲区缓存的基于程序计数器的分类(PCC)技术,该技术允许操作系统将I / O操作与通过调用指令的程序计数器在其中发出它们的程序上下文相关联触发I / O请求。这种相关性允许操作系统在每台PC的基础上对I / O访问模式进行分类,与以前的按文件或按应用程序分类的技术相比,其准确性要高得多。 PCC还可以更快地执行分类,因为每个PC模式仅需要学习一次。我们通过跟踪驱动的仿真和Linux中的实现对PCC进行评估,并将其与UBM(一种基于模式的最新缓冲区替换方案)进行比较。性能上的改进非常明显:命中率提高了29.3%(平均为13.8%),执行时间减少了29.0%(平均为13.7%)。

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