摘要
传统翻译缓存分区管理系统的翻译块miss率与异常指令定位时间均较高,导致缓存分区管理性能较差,因此设计一种基于模糊聚类分析的单词翻译缓存分区管理系统。在系统硬件设计中主要集成了内容寻址存储器,为数据存储提供空间以及翻译缓存包分区提供地址搜索上的便利;在软件设计中,使用模糊聚类算法完成数据挖掘算法的优化,并详细设计了模糊聚类算法的执行流程,建立单词翻译缓存分区管理模型,将缓存空间划分出子区域,实现二级管理,完成系统设计。系统性能测试结果表明,本文系统与传统系统相比,miss率与异常指令定位时间均能保持在较低水平,实际应用效果好。
Traditional translation cache partition management system has high translation block miss rate and abnormal instruction location time,which results in poor performance of cache partition management.Therefore,a word translation cache partition management system based on fuzzy clustering analysis is designed.In the hardware design of the system,the content addressing memory is mainly integrated to provide space for data storage and the convenience of address search in the partition of translation cache package.In the software design,the fuzzy clustering algorithm is used to optimize the data mining algorithm,and the implementation process of the fuzzy clustering algorithm is designed in detail,and the word translation cache partition management model is established to partition the cache space.The sub area is divided out to realize the secondary management and complete the system design.The system performance test results show that,compared with the traditional system,the miss rate and abnormal instruction location time can be kept at a lower level,and the actual application effect is good.
作者
许培红
XU Pei-hong(Basic Teaching Department,Anhui Vocational and Technical College,Hefei 230001,China)
出处
《齐齐哈尔大学学报（自然科学版）》
2021年第5期26-30,共5页
Journal of Qiqihar University(Natural Science Edition)
基金
安徽省教育厅质量工程项目“教学资源库项目旅游英语专业教学资源库”(2019ZYK36)
安徽省教育厅质量工程项目“大规模在线开放课程(MOOC)公共英语”(2018MOOC006)。
关键词
模糊聚类分析
单词翻译
缓存
分区管理
fuzzy clustering analysis
word translation
cache
partition management
