基于簇的COMA多处理器中共享吸引存储器的效率研究

A. Landin, Mattias Karlgren
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引用次数: 4

摘要

彗差多处理器的性能在很大程度上取决于大节点缓存和吸引存储器的效率。当多个处理器共享一个吸引内存时,它的行为就会改变。通过程序驱动仿真实验,我们发现聚类可以显著提高吸引力记忆的性能。交通减少,失分率是共同吸引记忆的动力。然而,聚类可能会引入对吸引记忆的争夺,这可能会破坏从增加的吸引记忆命中率中获得的任何潜在性能收益。提供了足够的本地带宽,应用程序。在集群系统中,与具有单处理器节点的系统相比,在更高的内存压力下,执行可以保持效率。在非常高的内存压力下,一些应用程序会改变行为并开始遭受集群的困扰。这是由于共同吸引记忆的联想性相对较低而导致的冲突缺失造成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study of the efficiency of shared attraction memories in cluster-based COMA multiprocessors
The performance of a COMA multiprocessor greatly depends on the efficiency of the large node caches, the attraction memories. When more than one processor share an attraction memory its behavior is changed. From experiments with program-driven simulation we have found that clustering may improve the performance of the attraction memory significantly. Traffic is reduced, and the miss rates are power for shared attraction memories. However clustering may introduce contention for the attraction memory that may ruin any potential performance gain from increased attraction memory hit rate. Provided enough local bandwidth, application. Execution can remain efficient at higher memory pressure in clustered systems than in systems with single processor nodes. At very high memory pressure some applications change behavior and start suffering from clustering. This is caused by conflict misses due to the relatively lower associativity of the shared attraction memory.
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