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An Efficient Data Access Policy in shared Last Level Cache

机译:共享的末级缓存中的有效数据访问策略

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Future multi-core systems will execute massive memory intensive applications with significant data sharing. On chip memory latency further increases as more cores are added since diameter of most on chip networks increases with increase in number of cores, which makes it difficult to implement caches with single uniform access latency, leading to non-uniform cache architectures (NUCA). Data movement and their management further impacts memory access latency and consume power. We observed that previous D-NUCA design have used a costly data access scheme to search data in the NUCA cache in order to obtain significant performance benefits. In this paper, we propose an efficient and implementable data access algorithm for D-NUCA design using a set of pointers with each bank. Our scheme relies on low-overhead and highly accurate in-hardware pointers to reduce miss latency and on-chip network contention. Using simulations of 8-core multi-core, we show that our proposed data search mechanism in D-NUCA design reduces 40% dynamic energy consumed per memory request and outperforms multicast access policy by an average performance speedup of 6%.
机译:未来的多核系统将执行具有大量数据共享功能的大量内存密集型应用程序。随着更多核的增加,片上存储器的等待时间进一步增加,这是因为大多数片上网络的直径随核数的增加而增加,这使得难以通过单一的统一访问等待时间来实现高速缓存,从而导致非统一的高速缓存体系结构(NUCA)。数据移动及其管理进一步影响内存访问延迟并消耗功率。我们观察到,以前的D-NUCA设计已经使用了昂贵的数据访问方案来搜索NUCA缓存中的数据,以获得显着的性能优势。在本文中,我们为D-NUCA设计提出了一种高效且可实现的数据访问算法,该算法使用每个存储体都有一组指针。我们的方案依靠低开销和高精度的硬件内指针来减少未命中延迟和片上网络竞争。通过对8核多核的仿真,我们证明了我们在D-NUCA设计中提出的数据搜索机制将每个内存请求的动态能耗降低了40%,并且比多播访问策略的平均性能提升了6%。

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