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High Performance Dynamic Resource Allocation for Guaranteed Service in Network-on-Chips

机译:网络上网络中保证服务的高性能动态资源分配

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This paper proposes a dedicated connection allocation unit-the NoCManager-implementing the connection allocation functionality in circuit-switched network-on-chip (NoC) based on time-division-multiplexing (TDM). The NoCManager employs a novel trellis-search-algorithm (TESSA) that solves the allocation optimization problem by making use of dynamic programming approach. This enables to explore all possible paths between source-destination node pairs in order to determine the shortest available path. Three different trellis structures are proposed and analyzed for the purpose of different application scenarios. In contrast to previous TDM allocation approaches, the proposed method offers the following advantages: (1) hardware supported fast and high-throughput allocation mechanism; (2) improved success rate due to parallel multi-slot multi-path search mechanism; (3) selection of the contention-free shortest path with a guaranteed low latency; (4) general mathematical formulation allowing a variety of optimization ideas. The proposed method is compared to the state of the art centralized and distributed techniques under uniformly distributed random traffic as well as real-application traffic. The experimental results demonstrate two orders of magnitude improvement in allocation speed and tens of times higher success rate against the centralized software solutions, and 5 to 10 percent higher success rate against the centralized hardware solution. Moreover, it achieves up to 8x higher allocation speed and up to 29 percent higher success rate against recently proposed distributed solution.
机译:本文提出了一种专用连接分配单元 - 基于时分复用(TDM),基于时分复用(TDM)实现电路交换网络上(NOC)中的连接分配功能的NOCManager。 NOCManager采用新的网格搜索算法(TESSA),通过利用动态编程方法来解决分配优化问题。这使得能够探索源目标节点对之间的所有可能路径,以便确定最短可用路径。提出了三种不同的格子结构,并分析了不同的应用方案的目的。与先前的TDM分配方法相比,所提出的方法提供以下优点:(1)硬件支持快速和高通量分配机制; (2)由于并行多插槽多路径搜索机制,提高成功率; (3)选择无争用最短路径,保证低延迟; (4)允许各种优化思想的一般数学制定。将所提出的方法与均匀分布的随机交通和实际应用流量的艺术集中和分布式技术进行比较。实验结果表明,对集中软件解决方案的分配速度和数度较高的成功率,对集中硬件解决方案的成功率提高了两大数量级。此外,它可以实现高达8倍的分配速度,最近提出的分布式解决方案的成功率高达29%。

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