分布式协同缓存

E. Herrero, José González, R. Canal
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引用次数: 48

摘要

本文提出了分布式协同缓存,一种可扩展且节能的芯片多处理器(CMP)缓存资源管理方案。提议的配置基于协作缓存框架[3],但它是为大规模cmp设计的。集中式和分布式配置都具有将私有缓存和共享缓存的优点结合起来的优点。在我们的建议中,连贯性引擎已被重新设计,以允许其分区,从而消除所有标签重复所施加的大小限制。同时,增加了一个全局替换机制来改进缓存空间的使用。我们的框架使用了几个分布在所有节点上的分布式一致性引擎来提高可伸缩性。该分布允许在整个芯片上更好地平衡网络流量,避免瓶颈,并使32核CMP的性能比传统共享内存配置提高21%,比协作缓存方案提高57%。此外,我们还通过使用不同的标签分配方法和减少每个请求比较的标签数量来降低整个系统的功耗。对于32核CMP,分布式协作式缓存框架提供的功率/性能关系(MIPS3/W)比传统共享内存配置平均提高3.66倍,比协作式缓存平均提高4.30倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Cooperative Caching
This paper presents the Distributed Cooperative Caching, a scalable and energy-efficient scheme to manage chip multiprocessor (CMP) cache resources. The proposed configuration is based in the Cooperative Caching framework [3] but it is intended for large scale CMPs. Both centralized and distributed configurations have the advantage of combining the benefits of private and shared caches. In our proposal, the Coherence Engine has been redesigned to allow its partitioning and thus, eliminate the size constraints imposed by the duplication of all tags. At the same time, a global replacement mechanism has been added to improve the usage of cache space. Our framework uses several Distributed Coherence Engines spread across all the nodes to improve scalability. The distribution permits a better balance of the network traffic over the entire chip avoiding bottlenecks and increasing performance for a 32-core CMP by 21% over a traditional shared memory configuration and by 57% over the Cooperative Caching scheme. Furthermore, we have reduced the power consumption of the entire system by using a different tag allocation method and by reducing the number of tags compared on each request. For a 32-core CMP the Distributed Cooperative Caching framework provides an average improvement of the power/performance relation (MIPS3/W) of 3.66× over a traditional shared memory configuration and 4.30× over Cooperative Caching.
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