Compiling for Locality in Advanced Scientific Computations

在现代处理器体系结构中，程序只有在拥有足够的数据局部性来利用片上缓存时才能获得良好的性能。 本研究的重点是开发和evaluatingsoftware支持，以提高先进的scientifapplications的顺序和并行机的本地化。 基本前提是编译时分析和复杂的运行时系统都是必要的。 运行时系统是必要的，因为许多程序是不可静态分析的。嵌入式支持是至关重要的，无论是插入接口的运行时系统，并直接应用程序transformationwherenable.This建议调查本地优化所需的三个功能，发现在先进的科学应用程序（3D数组，不规则的访问，指针）。 它侧重于扩展局部优化，以处理多个数据之间的缓存冲突，深层内存层次结构（多级缓存和TLB），硬件和软件预取，非线性内存布局，并行和集群架构，以及内存性能工具。 局部优化将应用于代表性的程序，并在先进的计算机系统上进行实验评估，这项研究的结果将有助于提高计算密集型科学应用的性能。 由于计算机体系结构的发展趋势，所吸取的经验教训也很可能对图像处理和高性能数据库等应用领域有用。

With modern processor architectures, programs can achieve goodperformance only if they possess sufficient data locality to exploiton-chip caches. This research focuses on developing and evaluatingsoftware support for improving locality for advanced scientificapplications for both sequential and parallel machines. The basicpremise is that both compile-time analyses and sophisticated run-timesystems are necessary. Run-time systems are needed because manyprograms are not analyzable statically. Compiler support is crucialboth for inserting interfaces to the run-time system and for directlyapplying program transformations where possible.This proposal investigates locality optimizations needed for threefeatures found in advanced scientific applications (3D arrays,irregular accesses, and pointers). It focuses on extendinglocality optimizations to handle cache conflicts between multipledata, deep memory hierarchies (multi-level caches and TLBs), hardwareand software prefetching, nonlinear memory layouts, parallel andcluster architectures, and memory performance tools. Localityoptimizations will be applied to representative programs andexperimentally evaluated on advanced computer systems.The results of this research should help improve the performanceof computationally intensive scientific applications. Becauseof trends in computer architectures, lessons learned are alsolikely to be useful for application domains such as imageprocessing and high-performance databases.