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Making Data Prefetch Smarter: Adaptive Prefetching on POWER7

机译:使数据预取更加智能:POWER7上的自适应预取

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Hardware data prefetch engines are integral parts of many general purpose server-class microprocessors in the field today. Some prefetch engines allow the user to change some of their parameters. The prefetcher, however, is usually enabled in a default configuration during system bring-up and dynamic reconfiguration of the prefetch engine is not an autonomic feature of current machines. Conceptually, however, it is easy to infer that commonly used prefetch algorithms, when applied in a fixed mode will not help performance in many cases. In fact, they may actually degrade performance due to useless bus bandwidth consumption and cache pollution. In this paper, we present an adaptive prefetch scheme that dynamically modifies the prefetch settings in order to adapt to the workload requirements. We implement and evaluate adaptive prefetching in the context of an existing, commercial processor, namely the IBM P0WER7. Our adaptive prefetch mechanism improves performance with respect to the default prefetch setting up to 2.7X and 30% for single-threaded and multiprogrammed workloads, respectively.
机译:硬件数据预取引擎是当今该领域许多通用服务器级微处理器的组成部分。一些预取引擎允许用户更改其某些参数。但是,通常在系统启动期间以默认配置启用预取器,并且预取引擎的动态重新配置不是当前计算机的自主功能。但是,从概念上讲,很容易推断出,当以固定模式应用时,常用的预取算法在许多情况下都不会提高性能。实际上,由于无用的总线带宽消耗和缓存污染,它们实际上可能降低性能。在本文中,我们提出了一种自适应预取方案,该方案可以动态修改预取设置以适应工作负载要求。我们在现有的商用处理器(即IBM P0WER7)的环境中实现和评估自适应预取。我们的自适应预取机制相对于默认的预取设置将性能提高了,默认的预取设置分别为单线程和多程序工作负载的2.7X和30%。

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