Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s10766-014-0334-5 | International Journal of Parallel Programming |
Keywords | Field | DocType |
Cache contention, Dynamic cache partitioning, Phase behavior, Multi-program | Cache,Computer science,Parallel computing,Cache contention | Journal |
Volume | Issue | ISSN |
44 | 1 | 1573-7640 |
Citations | PageRank | References |
3 | 0.38 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaofei Liao | 1 | 1145 | 120.57 |
| Rentong Guo | 2 | 21 | 3.19 |
| Danping Yu | 3 | 3 | 0.38 |
| Hai Jin | 4 | 6544 | 644.63 |
| Li Lin | 5 | 34 | 3.63 |