| 引用本文: | 黄智濒,周锋,马华东,等.利用堆栈特征的片上末级缓存访问模式在线识别方法.[J].国防科技大学学报,2015,37(1):1-7.[点击复制] |
| HUANG Zhibin,ZHOU Feng,MA Huadong,et al.An online access pattern identification method based on the stack characteristic in the on-chip last-level-cache[J].Journal of National University of Defense Technology,2015,37(1):1-7[点击复制] |
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| 利用堆栈特征的片上末级缓存访问模式在线识别方法 |
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(1. 北京邮电大学 计算机学院，北京 100876;2.北京航空航天大学 软件开发环境国家重点实验室，北京 100191;3. 吉林师范大学 数学学院, 吉林 四平 136000)
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| 摘要: |
| 很多优化处理器缓存利用效率的方法依赖于对访问请求序列的特征的探测或识别，例如，预取和绕开等。如何在线有效识别访问请求序列的特征依然是一个开放的问题。通过对典型访问模式的深入分析，发现其堆栈距离频度的分布展示出鲜明的特征。而模拟实验数据表明访问请求序列的特征具有一定的持续性和稳定性，具有检测和预测的可行性。因而提出了一种基于堆栈直方图峰值的在线识别访问模式的机制和方法，空间和时间开销都较小。对SPEC CPU2000/2006的15个程序的实验表明，所提方法均可正确识别测试程序的访问模式。 |
| 关键词: 访问模式 识别 缓存 处理器 |
| DOI：10.11887/j.cn.201501001 |
| 投稿日期：2014-06-12 |
| 基金项目:中国博士后基金资助项目(2014M550662)；软件开发环境国家重点实验室资助项目（SKLSDE-2014KF-04） |
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| An online access pattern identification method based on the stack characteristic in the on-chip last-level-cache |
| HUANG Zhibin1,2, ZHOU Feng1, MA Huadong1, ZHU Mingfa3, TAO Yuan4 |
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(1. School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;2.
2. State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;3.2. State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;4.3. College of Mathematics, Jilin Normal University, Siping 136000, China)
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| Abstract: |
| Many methods optimizing the on-chip cache utilization are dependent on the profile or identification of the access sequence characteristics, for instance, prefetcher or bypass etc. How to identify these characteristics is still an open problem. Through a detailed theoretical analysis of typical access patterns, it is shown that the frequency of stack distance has obvious features. Furthermore, according to the results of the Simics simulation, these features present persistent and stable to a certain extent, therefore, they are feasible to be identified and predicted. An online method based on the peak value of the collected stack histogram attaching to each core is provided. In addition, the storage and time overhead is small. The experimental results based on 15 benchmarks from SPEC CPU2000/2006 show that it identifies all correctly. |
| Keywords: access pattern identification cache processor |
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