共享内存多处理器系统中缓存问题的知识状态

W. Bein, L. Larmore, R. Reischuk
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引用次数: 4

摘要

具有全局共享内存的多处理器系统提供逻辑上统一的数据访问。为了隐藏访问全局内存时的延迟,每个处理器都使用私有缓存。一个数据项的多个副本可以并发地存在于系统中。为了保证更新项时的一致性,处理器必须使该项在其他私有缓存中的副本失效。为了排除经典分页错误的影响,假设每个处理器都知道自己的数据访问顺序,但不知道其他处理器请求的未来失效顺序。使用竞争分析,可以根据理论上的全知处理器的最佳行为来衡量具有此限制的处理器的性能。针对该问题,提出了一种4/3竞争随机在线算法。该算法是借助于一个叫做知识状态的新概念推导出来的。我们还证明了一个匹配的下界,因此这种在线算法是最好的。最后,显示了较大缓存大小的竞争力的3/2的下界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge states for the caching problem in shared memory multiprocessor systems
Multiprocessor systems with a global shared memory provide logically uniform data access. To hide latencies when accessing global memory each processor makes use of a private cache. Several copies of a data item may exist concurrently in the system. To guarantee consistency when updating an item a processor must invalidate copies of the item in other private caches. To exclude the effect of classical paging faults, one assumes that each processor knows its own data access sequence, but does not know the sequence of future invalidations requested by other processors. Performance of a processor with this restriction can be measured against the optimal behavior of a theoretical omniscient processor, using competitive analysis. A 4/3 competitive randomized online algorithm for this problem for cache size 2 is presented. This algorithm is derived with the help of a new concept we call knowledge states. We also prove a matching lower bound, thus this online algorithm is best possible. Finally, a lower bound of 3/2 on the competitiveness for larger cache sizes is shown.
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