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A Communication Probability-Based Mapping Algorithm for Mesh-Based Network-on-Chip Systems

机译:基于网格的片上网络系统中基于通信概率的映射算法

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Network-on-chip (NoC) mapping algorithms significantly affect NoC system performance in terms of communication cost and energy consumption. For a specific application represented by a task graph, this paper proposes an energy-efficient mapping algorithm that searches for the mapping decision with best communication locality and therefore lowest energy consumption. To this end, we formulate the concerned mapping problem as an optimization model, and propose an effective meta-heuristic algorithm to solve the formulated optimization model. During the mapping procedure, we employ a simulation-free, communication probability-based energy model to evaluate the quality of each candidate mapping. By iteratively updating the best explored mapping decision using a meta-heuristic search strategy, the mapping procedure can eventually identify an mapping decision with optimal energy efficiency in the search space. The proposed mapping algorithm has been verified on NoC systems of different sizes using a variety of benchmark applications. Simulation results demonstrate that the mapping decision produced by this algorithm achieves an up to 23% energy reduction compared with the traditional round-robin strategy.
机译:片上网络(NoC)映射算法在通信成本和能耗方面会严重影响NoC系统性能。对于以任务图表示的特定应用,本文提出了一种节能映射算法,该算法搜索具有最佳通信局部性并因此具有最低能耗的映射决策。为此,我们将相关的映射问题公式化为优化模型,并提出了一种有效的元启发式算法来解决所制定的优化模型。在映射过程中,我们采用了基于通信概率的无模拟能量模型来评估每个候选映射的质量。通过使用元启发式搜索策略迭代更新最佳探索的映射决策,映射过程最终可以在搜索空间中标识具有最佳能源效率的映射决策。使用各种基准测试应用程序,已在不同大小的NoC系统上对提出的映射算法进行了验证。仿真结果表明,与传统的轮询策略相比,该算法产生的映射决策最多可减少23%的能量。

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