存储能量优化数据压缩算法的硬件实现

L. Benini, D. Bruni, A. Macii, E. Macii
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引用次数: 5

摘要

本文描述了在基于处理器的系统中用于优化能耗的硬件压缩与解压缩单元(CDU)的实现细节。许多用于数据压缩的算法(例如,概要驱动的、自适应的、差分的)以前已经介绍过。在所有情况下,数据压缩和解压缩都是在缓存到内存的路径上实时执行的:未压缩的缓存罚款在写回主存之前被压缩,并在缓存重新填充时解压缩。本文通过具体解决硬件实现问题,为提出的压缩体系结构的可行性提供证据,从而完成并扩展了这些先前的贡献。CDU设计的目标是在缓存-总线-存储器子系统中实现能量最小化,并对性能有严格的约束。因此,在几个基准程序中评估的平均内存能耗减少约为24%,而没有性能损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hardware implementation of data compression algorithms for memory energy optimization
This paper describes implementation details of a hardware compression and decompression unit (CDU) for optimizing energy consumption in processor-based systems. Many algorithms for data compression (i.e., profile-driven, adaptive, differential) have previously been introduced. In all cases, data compression and decompression are performed on-the-fly on the cache-to-memory path: Uncompressed cache fines are compressed before they are written back to main memory, and decompressed when cache refills occur. This paper completes and extends these previous contributions by providing evidence on the feasibility of the proposed compression architectures by specifically addressing hardware implementation issues. CDU design is targeted towards energy minimization in the cache-bus-memory subsystem with a strict constraint on performance. As a result, average memory energy reductions evaluated on several benchmark programs are around 24%, at no performance penalty.
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