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International Journal of Parallel Programming

Erschienen in:

01.02.2016

A Phase Behavior Aware Dynamic Cache Partitioning Scheme for CMPs

verfasst von: Xiaofei Liao, Rentong Guo, Danping Yu, Hai Jin, Li Lin

Erschienen in: International Journal of Parallel Programming | Ausgabe 1/2016

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Abstract

In multi-program environment, cache contention among processors can significantly degrade system performance. Cache partitioning served as an effective measure has been widely studied, especially for dynamic cache partitioning. However, it is difficult to decide the best cache quota which should be allocated to co-scheduled programs and the best time when a cache adjusting should be performed in dynamic cache partitioning scheme. This paper presents a novel dynamic cache partitioning mechanism based on the phase behavior of programs. It uses the performance monitoring units of modern processors and detects the phase behavior of programs to guide the cache partitioning at run-time. Since programs have recurring phase behavior during the whole execution time, on one hand, we can adjust the cache quota when a phase change occurs, on the other hand, we can make cache partitioning policy with higher accuracy and lower overhead by classifying phases. The method proposed in this work is validated in the measured results for applications from SPEC CPU 2006 benchmark suite. Compared with the performance of shared cache scheme, our method can achieve a speedup up to 1.214 for co-scheduled applications.

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Titel: A Phase Behavior Aware Dynamic Cache Partitioning Scheme for CMPs
verfasst von: Xiaofei Liao
Rentong Guo
Danping Yu
Hai Jin
Li Lin
Publikationsdatum: 01.02.2016
Verlag: Springer US
Erschienen in: International Journal of Parallel Programming / Ausgabe 1/2016
Print ISSN: 0885-7458
Elektronische ISSN: 1573-7640
DOI: https://doi.org/10.1007/s10766-014-0334-5

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