缓存过滤技术,以减少无用的推测内存引用对处理器性能的负面影响

O. Mutlu, Hyesoon Kim, D. N. Armstrong, Y. Patt
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引用次数: 15

摘要

高性能处理器采用积极的推测和预取技术来提高性能。这些技术引起的推测性内存引用有时会将正确执行不需要的数据放入缓存中。本文建议使用第一级缓存作为过滤器来预测推测内存引用的有用性。使用建议的技术,推测性内存引用仅将数据放入第一级缓存,而不是缓存层次结构中的所有级别。处理器监视第一级缓存中缓存块的使用情况,并根据缓存块的有用性决定在缓存层次结构中保留哪些块。结果表明,这种技术的简单实现通常优于当今处理器常用的包容性和排他性基线缓存层次结构,并且在SPEC2000整数基准测试中使IPC性能提高高达9.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cache filtering techniques to reduce the negative impact of useless speculative memory references on processor performance
High-performance processors employ aggressive speculation and prefetching techniques to increase performance. Speculative memory references caused by these techniques sometimes bring data into the caches that are not needed by correct execution. This paper proposes the use of the first-level caches as filters that predict the usefulness of speculative memory references. With the proposed technique, speculative memory references bring data only into the first-level caches rather than all levels in the cache hierarchy. The processor monitors the use of the cache blocks in the first-level caches and decides which blocks to keep in the cache hierarchy based on the usefulness of cache blocks. It is shown that a simple implementation of this technique usually outperforms inclusive and exclusive baseline cache hierarchies commonly used by today's processors and results in IPC performance improvements of up to 9.2% on the SPEC2000 integer benchmarks.
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