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Meshed Bluetree: Time-Predictable Multimemory Interconnect for Multicore Architectures

机译:网状bluetree:多核架构的时间可预测的多重互连

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Multicore architectures are widely adopted in the emerging real-time applications, such as autonomous vehicles and robotics, where latency is required to be both bounded in the worst case (i.e., time predictability) and low. With the number of processors growing, the conventional memory interconnects, i.e., shared bus, crossbar, and network-on-chip (NoC), suffer high latency due to the increasing logic size of their centralized arbiter, which is deployed for time predictability. In this article, we introduce a novel distributed multimemory interconnect, Meshed Bluetree, and explain its operation. Constructed by coupling a router network with multiple Bluetree-based memory architectures in parallel, Meshed Bluetree allows simultaneous access to multiple memory modules. We present the analysis for the predictable timing behavior of memory access to bound the worst case. The evaluation of FPGA with synthetic memory workloads and real-world benchmarks demonstrates the effectiveness of our work, i.e., as the number of memory modules increases, the latency is reduced with the same scale. This work reports the first time-predictable distributed multimemory interconnect, significantly contributing to multicore real-time systems.
机译:多核架构在新兴的实时应用中广泛采用,例如自主车辆和机器人,其中延迟是在最坏情况下界定(即时间可预测性)和低。利用生长的处理器数量,传统的存储器互连,即共享总线,横杆和片上网(NOC),由于其集中仲裁器的逻辑大小增加,因此部署了时间可预测性。在本文中,我们介绍了一种新颖的分布式多重互连,网状蓝色互联网,并解释其操作。通过并行地耦合具有多​​个蓝色的基于存储器架构的路由器网络,网状蓝色蓝色允许同时访问多个存储器模块。我们介绍了内存访问的可预测时序行为的分析,以绑定最坏情况。 FPGA与合成内存工作负载和现实世界基准的评估展示了我们工作的有效性,即,随着内存模块的数量增加,延迟以相同的比例降低。这项工作报告了第一个时间可预测的分布式多重互连,显着贡献了多核实时系统。

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