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Using Data Compression to Increase Energy Savings in Multi-bank Memories

机译:使用数据压缩来提高多银行记忆中的节能

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New DRAM technologies such as SDRAMs, RDRAMs, EDRAMs, CDRAMs and others are vying to be the next standard in DRAMs and improve upon bandwidth limit of conventional DRAMs. With proliferation of power-aware systems, banked DRAM architecture has emerged as a promising candidate for reducing power. Prior work on optimizing applications in a banked memory environment has exclusively focused on uncompressed data. While this may be preferable from a performance viewpoint, it is not necessarily the best strategy as far as memory space utilization is considered. This is because compressing data in memory may reduce the number of memory banks it occupies and this, in turn, may enable a better use of low-power operating modes. In this paper, we explore the possibility of compressing infrequently used data for increasing effectiveness of low-power operating modes in banked DRAMs. Our experiments with five highly parallel array-based embedded applications indicate significant savings in memory energy over a technique that exploits low-power modes but does not use data compression/decompression.
机译:新的DRAM技术,如SDRAM的,RDRAM的,EDRAMs,CDRAMs和其他人争先恐后地在DRAM中的一个标准,提高在传统的DRAM的带宽限制。随着电力感知系统的扩散,库存的DRAM架构已经成为用于降低功耗的有希望的候选。就在一部分存储环境中优化应用程序之前的工作专注于未压缩的数据。虽然这可能是从性能的角度考虑,优选,它不一定是尽可能存储空间利用率被认为是最好的策略。这是因为在内存中的数据压缩可能会降低其占用的存储体的数量,这反过来,可以使更好地利用低功耗工作模式。在本文中,我们探索了用于增加库存的DRAM中的低功率操作模式的有效性压缩不经常使用的数据的可能性。我们的具有五个高度并行的基于阵列的嵌入式应用试验表明在它利用低功率模式,但不使用数据压缩/解压缩的技术,存储器的能量显著节省。

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