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Data Access Type Aware Replacement Policy for Cache Clustering Organization of Chip Multiprocessors

机译:数据访问类型感知芯片多处理器的缓存聚类组织的替换策略

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Chip multiprocessors (CMPs) are becoming the trend of mainstream computing platforms. The design of an efficient on-chip memory hierarchy is one of the key challenges in computer architecture. Tiled architecture and non-uniform cache architecture (NUCA) is commonly adopted in modern CMPs. Previous efforts on cache replacement policy usually assume an unified last-level cache or running multiprogrammed workloads. However, few researches focus on the replacement policy of cache clustering scheme running parallel workloads. Cache clustering scheme can improve the system performance on parallel performance, which is a tradeoff between shared cache organization and private cache organization which adopts cache replication. In cache clustering scheme, cache blocks in last-level cache can be subdivided into eight types. In this work we propose Data access Type Aware Replacement Policy (DTARP) for cache clustering organization, DTARP classifies data blocks in last-level cache into different access types, and designs the insertion and the victim selection policies according to different data access types based on traditional LRU policy. The global shared data will be kept in last-level cache longer than before. Simulation results show that DTARP can improve the system performance of cluster scheme using LRU policy by 10.9% on average.
机译:芯片多处理器(CMPS)正在成为主流计算平台的趋势。有效的片上存储层级的设计是计算机架构中的关键挑战之一。瓷砖架构和非统一缓存架构(NUCA)通常在现代CMP中采用。以前关于缓存替换策略的努力通常假设统一的最后一级缓存或运行的多程序编程工作负载。但是,很少有研究专注于运行并行工作负载的缓存聚类方案的替换策略。缓存聚类方案可以提高并行性能的系统性能,这是共享缓存组织与采用缓存复制的私人缓存组织之间的权衡。在缓存群集方案中,上次缓存中的缓存块可以细分为八种类型。在这项工作中,我们提出了数据访问类型感知替换策略(DTARP)用于缓存群集组织,DTARP将最后级别缓存中的数据块分类为不同的访问类型,并根据基于的不同数据访问类型设计插入和受害者选择策略传统的LRU政策。全局共享数据将在比以前更长的时间更长的缓存。仿真结果表明,DTARP可以平均使用LRU策略提高集群方案的系统性能10.9%。

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