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Lagrangian relaxation based topology synthesis for Application-Specific Network-on-Chips

机译:基于拉格朗日松弛的拓扑合成,用于特定于应用的片上网络

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Application-Specific Network-on-Chip (ASNoC) has been proposed as a promising solution for addressing the global communication challenges in nanoscale System-on-Chips. However, with the number of cores on chip increasing, the power consumption and communication latency impose the major challenges for designing ASNoCs. In this paper, we propose an efficient latency-aware ASNoC low power synthesis algorithm. Firstly, considering the communication requirements and latency constraints between the cores, we integrate the floorplanning and clustering to explore the optimal clustering of cores. After the switches and network interfaces are inserted into the floorplan, a path allocation method based on the Lagrangian relaxation is proposed for routing traffic flows with minimization of power consumption subject to the latency constraints. Experimental results show that the proposed method is highly efficient and the success rate for meeting the latency constraints of the traffic flows is up to 100%.
机译:特定应用的片上网络(ASNoC)已被提出作为解决纳米级片上系统中的全球通信挑战的有前途的解决方案。但是,随着芯片上内核数量的增加,功耗和通信延迟给设计ASNoC带来了主要挑战。在本文中,我们提出了一种有效的可感知延迟的ASNoC低功耗综合算法。首先,考虑到核心之间的通信需求和延迟约束,我们将布局规划和集群集成在一起,以探索核心的最佳集群。在将交换机和网络接口插入到平面图中之后,提出了一种基于拉格朗日松弛的路径分配方法,该方法用于路由通信流,并在等待时间限制的情况下将功耗降至最低。实验结果表明,该方法是高效的,满足交通流时延约束的成功率高达100%。

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