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Fast Configuration of MEMS-Based Storage Devices for Streaming Applications

机译:用于流式应用的MEMS的存储设备快速配置

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An exciting class of storage devices is emerging: the class of Micro-Electro-Mechanical storage Systems (MEMS). Properties of MEMS-based storage devices include high density, small form factor, and low power. The use of this type of devices in mobile infotainment systems, such as video cameras is not at all obvious. We must explore their configuration and assess their benefit with respect to existing devices, such as Flash. In this paper, we study the configuration of the data layout of MEMS-based storage devices for predominately streaming applications. The configuration targets: the timing performance, energy consumption, and the capacity. We show that formatting the data layout based on knowledge of the expected streaming workload results in devices that consume at least 22% less energy than Flash and perform comparably. We present a fast and effective configuration method to format the data layout. This method exploits the bimodal distribution of the request size in streaming applications. Using the fast method, we present a design rule for streaming environments: reducing the amount of prefetching of streaming data allows to reach configurations with small trade-offs between the design targets.
机译:兴奋的存储设备是出现的:微电机械存储系统(MEMS)的类。基于MEMS的存储装置的性质包括高密度,小形状因子和低功率。在移动信息娱乐系统中使用这种类型的设备,例如摄像机并不明显。我们必须探索他们的配置,并评估他们对现有设备(例如Flash)的福利。在本文中,我们研究了基于MEMS的存储设备的数据布局的配置,以实现主要流式传输应用程序。配置目标:定时性能,能耗和容量。我们表明,基于对预期流工作量的知识格式化数据布局,这些设备会导致比闪存的能量减少至少22%的设备。我们提出了一种快速有效的配置方法来格式化数据布局。此方法利用Repling应用程序中请求大小的双峰分布。使用快速方法,我们呈现了流环境的设计规则:减少流数据的预取量允许在设计目标之间达到具有小权衡的配置。

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