Data Compression Techniques for Improving Memory Hierarchy Performance

摘要：该项目旨在开发数据压缩技术，以大幅减少内存密集型应用程序的数据内存占用。我们将研究广泛的应用程序的行为，以确定数据结构中保存的数据的特征，这些程序可用于执行数据压缩。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，即其中并非所有数据都不可压缩的数据结构。这种方法不仅将导致广泛适用的转换，而且还将导致有效应用它们的技术。特别是，我们不再依赖复杂的编译时分析来证明它们的适用性，而是能够使用简单的值剖析技术来识别大多数可压缩的数据结构，然后将转换应用于它们。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，这可能会对性能产生重大影响。

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.