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An analytical model for software-only main memory compression

机译:仅软件主存压缩的分析模型

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Many applications with large data spaces that cannot run on a typical workstation (due to page faults) call for techniques to expand the effective memory size. One such technique is memory compression.Understanding what applications under what conditions can benefit from main memory compression is complicated due to various tradeoffs and the dynamic characteristics of applications. For instance, a large area to store compressed data increases the effective memory size considerably but also decreases the amount of memory that can hold uncompressed data.This paper presents an analytical model that states the conditions for a compressed-memory system to yield performance improvements. Parameters of the model are the compression algorithm efficiency, the amount of data being compressed, and the application memory access pattern. Such a model can be used by an operating system to compute the size of the compressed-memory level that can improve an application's performance.
机译:许多具有大数据空间的应用程序(由于页面错误)无法在典型的工作站上运行,因此需要使用技术来扩展有效内存大小。一种这样的技术是内存压缩。由于各种折衷和应用程序的动态特性,要了解在什么条件下哪些应用程序可以从主内存压缩中受益是很复杂的。例如,大面积存储压缩数据会大大增加有效内存大小,但也会减少可以保存未压缩数据的内存量。本文提出了一个分析模型,该模型阐明了压缩内存系统产生性能改进的条件。该模型的参数是压缩算法效率,要压缩的数据量以及应用程序内存访问模式。操作系统可以使用这种模型来计算压缩内存级别的大小,从而可以提高应用程序的性能。

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