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Attaché: Towards Ideal Memory Compression by Mitigating Metadata Bandwidth Overheads

机译:附件:通过减轻元数据带宽开销来实现理想的记忆压缩

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Memory systems are becoming bandwidth constrained and data compression is seen as a simple technique to increase their effective bandwidth. However, data compression requires accessing Metadata which incurs additional bandwidth overheads. Even after using a Metadata-Cache, the bandwidth overheads of Metadata can reduce the benefits of compression. This paper proposes Attaché, a framework that reduces the overheads of Metadata accesses. The Attaché framework consists of two components. The first component, called the Blended Metadata Engine (BLEM), enables data and its Metadata to be accessed together. BLEM incurs additional Metadata accesses only 0.003% times and removes almost all Metadata bandwidth overheads. The second component, called theCompression Pre-dictor(COPR), predicts if the memory block is compressed. TheCOPR predictor uses a fine-grained line-level predictor, a coarse-grained page-level predictor, and a global indicator. This enables Attaché to predict the compressibility of the memory block before sending a memory read request. We implement Attaché on a memory system that uses Sub-Ranking. On average, Attaché achieves 15.3% speedup (ideal 17%) and saves 22% energy consumption (ideal 23%) when compared to a baseline system that does not employ data compression. Attaché is completely hardware-based and uses only 368KB of SRAM.
机译:内存系统正在变为带宽约束,并且数据压缩被视为提高其有效带宽的简单技术。但是,数据压缩需要访问引起额外带宽开销的元数据。即使在使用元数据缓存之后,元数据的带宽开销也可以降低压缩的好处。本文提出了ActaTé,这是一种减少元数据访问的开销的框架。附件框架由两个组成部分组成。第一个组件,称为混合元数据引擎(BLEM),使得能够一起访问数据及其元数据。 BLEM引起其他元数据仅访问0.003%次数,并删除几乎所有元数据带宽开销。第二组件,称为Thecupple预测(COPR),预测存储块是否被压缩。 TheCopre Predictor使用细粒度的线级预测器,粗粒度的页面级预测器和全局指示器。这使得ATTIVEASE能够在发送存储器读取请求之前预测存储器块的可压缩性。我们在使用子排名的内存系统上实现Attice。平均而言,与不采用数据压缩的基线系统相比,Attaché达到15.3%的加速(理想的17%)并节省22%的能耗(理想23%)。 Attaché完全基于硬件,仅使用368KB的SRAM。

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