量化负载流行为

S. Sair, T. Sherwood, B. Calder
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引用次数: 22

摘要

处理器和内存之间越来越大的性能差距将迫使未来的架构投入大量资源来消除和隐藏内存延迟。用于解决这一日益扩大的差距的两个主要体系结构特性是缓存和预取。在本文中,我们对Olden基准测试、SPEC 2000基准测试和一系列基于指针的应用程序的缓存缺失模式进行了详细的量化。我们根据访问模式的类型将未命中分类为四类之一。它们是下一行转换、跨步转换、相同对象转换(最近访问的对象发生的额外丢失)或基于指针的转换。然后,我们提出并评估硬件分析体系结构,以正确识别所看到的访问模式类型。这种访问模式标识可用于帮助指导和分配预取资源,并为反馈导向的优化提供信息。本文的第二个目标是确定一套具有挑战性的基于指针的基准,这些基准可用于集中开发新的软件和硬件预取算法,并确定使用新指标为这些应用程序执行预取时面临的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying load stream behavior
The increasing performance gap between processors and memory will force future architectures to devote significant resources towards removing and hiding memory latency. The two major architectural features used to address this growing gap are caches and prefetching. In this paper we perform a detailed quantification of the cache miss patterns for the Olden benchmarks, SPEC 2000 benchmarks, and a collection of pointer based applications. We classify misses into one of four categories corresponding to the type of access pattern. These are next-line, stride, same-object (additional misses that occur to a recently accessed object), or pointer-based transitions. We then propose and evaluate a hardware profiling architecture to correctly identify which type of access pattern is being seen. This access pattern identification could be used to help guide and allocate prefetching resources, and provide information to feedback-directed optimizations. A second goal of this paper is to identify a suite of challenging pointer-based benchmarks that can be used to focus the development of new software and hardware prefetching algorithms, and identify the challenges in performing prefetching for these applications using new metrics.
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