位平面压缩:在多核架构中转换数据以获得更好的压缩

Jungrae Kim, Michael B. Sullivan, Esha Choukse, M. Erez
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引用次数: 73

摘要

随着关键应用程序变得更加数据密集,处理器的计算吞吐量增加,需要在现代内存子系统中传输的数据量也在增加。然而,由于严格的面积和能源限制,增加物理带宽以跟上需求增长是具有挑战性的。为了提高有效内存带宽,本文提出了一种新的轻量级压缩算法——位平面压缩(BPC)。BPC针对多核架构中普遍存在的同质类型内存块,并应用智能数据转换来提高固有的数据可压缩性并降低压缩硬件的复杂性。我们证明了BPC为整数基准测试提供了4.1:1的优越压缩比,并显着降低了内存带宽需求。
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Bit-Plane Compression: Transforming Data for Better Compression in Many-Core Architectures
As key applications become more data-intensive and the computational throughput of processors increases, the amount of data to be transferred in modern memory subsystems grows. Increasing physical bandwidth to keep up with the demand growth is challenging, however, due to strict area and energy limitations. This paper presents a novel and lightweight compression algorithm, Bit-Plane Compression (BPC), to increase the effective memory bandwidth. BPC aims at homogeneously-typed memory blocks, which are prevalent in many-core architectures, and applies a smart data transformation to both improve the inherent data compressibility and to reduce the complexity of compression hardware. We demonstrate that BPC provides superior compression ratios of 4.1:1 for integer benchmarks and reduces memory bandwidth requirements significantly.
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