不同片上缓存一致性策略的端到端延迟界分析:基于网络演算的方法

X. Lai, Zhiying Wang, Quanyou Feng
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引用次数: 0

摘要

分析和比较不同缓存一致性策略的端到端延迟边界将为NoC设计提供有益的指导。然而,这并不是一件容易的事情,因为1)缓存一致性事件产生的数据包流不符合泊松过程,传统的队列定理无法应用于支持缓存一致性的noc的性能分析;2)广播或组播操作会复制缓存一致性数据包,使分析变得更加复杂。为了解决这些问题,在本文中,我们使用随机网络演算来分析不同缓存一致性策略的端到端延迟边界。具体来说,我们利用markov调制的On-Off (MMOO)流来模拟缓存一致性事件的到达过程,然后推导出不同缓存一致性策略的一般端到端延迟界限。此外,为了处理广播或组播操作中的数据包重复问题,我们建立了一个基于缩放函数的分析模型来研究它们对端到端延迟界的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
End-to-End Delay Bounds Analysis of Different On-chip Cache Coherence Policies: A Network Calculus-Based Approch
To analyze and compare end-to-end delay bounds of different cache coherence policies will provide beneficial guidelines for NoC design. However, it is not an easy task, because 1) packet flows generated by cache coherence events do not conform to the Poisson process, traditional queue theorem can't be applied to the performance analyzing for the NoCs that support cache coherence, 2) broadcast or multicast operations, which will duplicate the cache coherence packets, makes the analysis much more complicated. To address these challenges, in this paper, we use the stochastic network calculus to analyze the end-to-end delay bounds of different cache coherence policies. Specifically, we utilize Markov-modulated On-Off (MMOO) flow to model the arrival process of cache coherence events, and then deduce the general end-to-end delay bounds for different cache coherence policies. Furthermore, to deal with packet duplication issues in broadcast or multicast operations, we develop an analytical model based on scaling functions to study their impacts on end-to-end delay bounds.
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