基于分时复用的生物启发网络片上容错算法

M. A. J. Sethi, F. Hussin, N. H. Hamid
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引用次数: 3

摘要

受生物学启发的解决方案是解决复杂和现实世界问题的一种新方法。由于先进的纳米制造工艺和加工元件通信要求的复杂性,NoC上出现了各种各样的故障。由于设备的异构性,NoC的复杂性和通信要求也有所增加。为了支持NoC的复杂性,减小了物理设备的尺寸,导致了故障的发生。文献中提出了各种容错技术来解决临时故障。但这些算法在自适应性和鲁棒性方面都存在不足。利用时分复用技术(TDM)的仿生NoC是基于生物大脑的特性。该技术是容错的,因为它可以检测和绕过错误的互连。在TDM的帮助下,可以在多个源和多个目的地之间建立多个连接,从而有效地利用pe之间的NoC带宽。据我们所知,基于TDM的生物激励NoC算法是第一个利用TDM方法解决容错问题的算法,在故障恢复过程中,平均数据包延迟增加了2.45%,平均带宽和吞吐量分别减少了1.86%和14.05%。同时,该技术的可接受流量(飞行/周期/节点)比传统容错技术提高了68.45%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biologically inspired network on chip fault tolerant algorithm using time division multiplexing
Biologically inspired solutions are a novel way of solving the complex and real world problems. Due to the advanced nanoscale manufacturing processes and the complex communication requirements of the processing elements (PEs) various faults have occurred on NoC. The complexity and communication requirement of the NoC has also increased due to the heterogeneous devices. To support the complexity of NoC, the physical device sizes are scaled down, which have contributed to faults. Various fault tolerant techniques have been proposed in the literature to address the temporary faults. But all these algorithms have drawbacks in terms of adaptiveness and robustness. Bio-inspired NoC using Time division multiplexing (TDM) is based on the characteristics of biological brain. The technique is fault tolerant as it detects and bypass the faulty interconnects. With the help of TDM, multiple connections are possible between multiple sources and multiple destinations, which efficiently utilize the NoC bandwidth between PEs. To the best of our knowledge, TDM based bio-inspired NoC is the first algorithm to address the fault tolerance using the TDM approach as the average packet latency is increased by 2.45%, while the average bandwidth and throughput is reduced by 1.86% and 14.05% respectively during the recovery of faults. Also, the accepted traffic (flit/cycle/node) of the proposed bio-inspired technique is better than traditional fault tolerant techniques by 68.45%.
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