实时优先级感知网络的缓冲空间分配

H. Kashif, Hiren D. Patel
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引用次数: 20

摘要

在这项工作中,我们解决了在优先级感知网络的最坏延迟分析中纳入缓冲空间约束的挑战。优先级感知网络是一种虫洞交换的片上网络,每个优先级都有不同的虚拟通道。先前的最坏情况延迟分析假设路由器有无限的缓冲空间分配给虚拟通道。这个假设使得这些分析在考虑实际部署时变得不切实际。这是因为优先级感知网络的实现对应用程序施加了缓冲区约束。这些约束可能导致通信上的反压力,这是分析必须考虑的。因此,我们扩展了优先级感知网络的最坏情况延迟分析,以包括缓冲空间约束。我们为这些扩展提供了理论依据,并证明了它们的正确性。我们在大量的综合基准测试上进行了实验,并证明我们可以在具有优先级感知的网络上部署应用程序,其虚拟通道的大小只有两个flits。此外,我们提出了一个多项式时间缓冲空间分配算法。该算法在调度目标优先级感知网络上的应用程序集时,将虚拟通道所需的缓冲区空间最小化。我们的经验评估表明,所提出的算法将虚拟通道中的缓冲空间需求平均减少了约85%。
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Buffer Space Allocation for Real-Time Priority-Aware Networks
In this work, we address the challenge of incorporating buffer space constraints in worst-case latency analysis for priority-aware networks. A priority-aware network is a wormhole-switched network-on-chip with distinct virtual channels per priority. Prior worst-case latency analyses assume that the routers have infinite buffer space allocated to the virtual channels. This assumption renders these analyses impractical when considering actual deployments. This is because an implementation of the priority-aware network imposes buffer constraints on the application. These constraints can result in back pressure on the communication, which the analyses must incorporate. Consequently, we extend a worst- case latency analysis for priority-aware networks to include buffer space constraints. We provide the theory for these extensions and prove their correctness. We experiment on a large set of synthetic benchmarks, and show that we can deploy applications on priority-aware networks with virtual channels of sizes as small as two flits. In addition, we propose a polynomial time buffer space allocation algorithm. This algorithm minimizes the buffer space required at the virtual channels while scheduling the application sets on the target priority-aware network. Our empirical evaluation shows that the proposed algorithm reduces buffer space requirements in the virtual channels by approximately 85% on average.
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