Data Compression Techniques for Improving Memory Hierarchy Performance

用于提高内存层次结构性能的数据压缩技术

• 批准号: 0105355
• 负责人: Rajiv Gupta
• 金额: $ 27万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0105355&HistoricalAwards=false
• 关键词: Data; Compression; Techniques; Improving; Memory

Abstract:This project is aimed at developing data compression techniques forsubstantially reducing the data memory footprint of memory intensiveapplications. We will study the behavior of a wide range of applicationsto identify characteristics of data held in data structures by theseprograms that can be exploited in carrying out data compression. Wewill develop a suite of data compression transformations that will beimplemented by the compiler. Our goal is to develop data transformationsthat can be applied to partially compressible data structures, that is,data structures in which all the data is not compressible. This approachwill not only result in transformations that are widely applicable, butalso lead to techniques for applying them that are efficient. In particular,instead of relying on complex compile-time analysis for proving theirapplicability, we will be able to use simple value profiling techniquesto identify data structures that are mostly compressible and then applythe transformations to them. We will develop data compression extensions(DCX) to a RISC-style instruction set for efficiently manipulatingcompressed data. In addition, we will also address other low level codegeneration issues, such as impact of transformations on register pressureand instruction cache behavior, which can have a significant impact onperformance.

翻译后摘要：该项目的目的是开发数据压缩技术，大大减少内存密集型应用程序的数据内存足迹。我们将研究广泛的应用程序的行为，以识别这些程序在数据结构中保存的数据的特性，这些程序可以用于进行数据压缩。我们将开发一套由编译器实现的数据压缩转换。我们的目标是开发可应用于部分可压缩数据结构的数据转换，即所有数据都不可压缩的数据结构。这种方法不仅会产生广泛适用的转换，而且会产生有效的应用转换的技术。特别是，我们将能够使用简单的值分析技术来识别大多数可压缩的数据结构，然后对它们应用转换，而不是依赖于复杂的编译时分析来证明它们的可压缩性。 我们将开发数据压缩扩展（DCX）到RISC风格的指令集，以有效地处理压缩数据。此外，我们还将解决其他低级代码生成问题，例如转换对寄存器压力和指令缓存行为的影响，这可能对性能产生重大影响。