未知缓存大小的协同缓存

Xiaoming Gu
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引用次数: 0

摘要

已经建立或提出了许多硬件系统来为影响缓存管理的软件提供接口。这种软硬件结合的解决方案被称为协同缓存。我们之前的工作表明,从理论上讲,LRU和MRU的协同缓存可以使程序最优地管理缓存。在这项工作中,我们首先提出了一个优先级的LRU模型。对于每次内存访问,程序为所有缓存大小指定一个优先级,即所访问数据的目标缓存位置。我们证明了优先级LRU具有包含性。另外,我们描述了一种基于相关优先级的动态缓存控制方案。消除了LRU-MRU协同缓存工作中知道缓存大小的限制。
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Collaborative Caching for Unknown Cache Sizes
A number of hardware systems have been built or proposed to provide an interface for software to influence cache management. The combined software-hardware solution is called collaborative caching. Our previous work showed that in theory collaborative caching with LRU and MRU may enable a program to manage cache optimally. In this work we first present a prioritized LRU model. For each memory access, a program specifies a priority, the target cache position for the accessed datum, for all cache sizes. We have proved that the prioritized LRU holds inclusion property. Alternatively, we describe a dynamic cache control scheme based on the associated priority. The limitation of knowing cache size in our LRU-MRU collaborative caching work is removed.
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