Feedback-Driven Restructuring of Multi-threaded Applications for NUCA Cache Performance in CMPs

S. Bartolini, P. Foglia, M. Solinas, C. Prete
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引用次数: 13

Abstract

This paper addresses feedback-directed restructuring techniques tuned to Non Uniform Cache Architectures (NUCA) in CMPs running multi-threaded applications. Access time to NUCA caches depends on the location of the referred block, so the locality and cache mapping of the application influence the overall performance. We show techniques for altering the distribution of applications into the cache space as to achieve improved average memory access time. In CMPs running multi-threaded applications, the aggregated accesses (and locality) of the processors form the actual cache load and pose specific issues. We consider a number of Splash-2 and Parsec benchmarks on an 8 processor system and we show that a relatively simple remapping algorithm is able to improve the average Static-NUCA (SNUCA) cache access time by 5.5% and allows an SNUCA cache to surpass the performance of a more complex dynamic-NUCA (DNUCA) for most benchmarks. Then, we present a more sophisticated remapping algorithm, relying on cache geometry information and on the access distribution statistics from individual processors, that reduces the average cache access time by 10.2% and is very stable across all benchmarks.
基于反馈驱动的多线程应用程序重构在cmp中的NUCA缓存性能
本文讨论了在运行多线程应用程序的cmp中针对非统一缓存架构(NUCA)调整的反馈导向重构技术。对NUCA缓存的访问时间取决于所引用块的位置,因此应用程序的位置和缓存映射会影响整体性能。我们展示了一些技术,可以改变应用程序在缓存空间中的分布,从而提高平均内存访问时间。在运行多线程应用程序的cmp中,处理器的聚合访问(和局部性)构成了实际的缓存负载,并带来了特定的问题。我们考虑了8处理器系统上的许多Splash-2和Parsec基准测试,我们表明,相对简单的重新映射算法能够将平均静态nuca (SNUCA)缓存访问时间提高5.5%,并允许SNUCA缓存在大多数基准测试中超过更复杂的动态nuca (DNUCA)的性能。然后,我们提出了一种更复杂的重映射算法,该算法依赖于缓存几何信息和来自单个处理器的访问分布统计数据,该算法将平均缓存访问时间减少了10.2%,并且在所有基准测试中都非常稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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