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首页> 外文期刊>Wireless personal communications: An Internaional Journal >P-NoC: Performance Evaluation and Design Space Exploration of NoCs for Chip Multiprocessor Architecture Using FPGA
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P-NoC: Performance Evaluation and Design Space Exploration of NoCs for Chip Multiprocessor Architecture Using FPGA

机译:P-NOC:使用FPGA的芯片多处理器架构NOC的性能评估和设计空间探索

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摘要

The network-on-chip (NoC) has emerged as an efficient and scalable communication fabric for chip multiprocessors (CMPs) and multiprocessor system on chips (MPSoCs). The NoC architecture, the routers micro-architecture and links influence the overall performance of CMPs and MPSoCs significantly. We propose P-NoC: an FPGA-based parameterized framework for analyzing the performance of NoC architectures based on various design decision parameters in this paper. The mesh and a multi-local port mesh (ML-mesh) topologies have been considered for the study. By fine-tuning various NoC parameters and synthesizing on the FPGA, identify that the performance of NoC architectures are influenced by the configuration of router parameters and the interconnect. Experiments show that the flit width, buffer depth, virtual channels parameters have a significant impact on the FPGA resources. We analyze the performance of the NoCs on six traffic patterns viz., uniform, bit shuffle, random permutation, transpose, bit complement and nearest neighbor. Configuring the router and the interconnect parameters, the ML-mesh topology yields 75% lesser utilization of FPGA resources compared to the mesh. The ML-mesh topology shows an improvement of 33.2% in network latency under localized traffic pattern. The mesh and ML-mesh topologies have 0.53x and 0.1x higher saturation throughput under nearest neighbor traffic compared to uniform random traffic.
机译:片上网络(NoC)已成为一种高效、可扩展的芯片多处理器(cmp)和多处理器片上系统(mpsoc)通信结构。NoC体系结构、路由器微体系结构和链路对CMP和MPSOC的整体性能有显著影响。本文提出了P-NoC:一种基于FPGA的参数化框架,用于分析基于各种设计决策参数的NoC架构的性能。研究中考虑了网格和多局部端口网格(ML mesh)拓扑。通过微调各种NoC参数并在FPGA上进行综合,确定NoC架构的性能受路由器参数配置和互连的影响。实验表明,flit宽度、缓冲区深度、虚拟通道参数对FPGA资源有显著影响。我们分析了NOC在六种业务模式下的性能,即:。,统一、位洗牌、随机排列、转置、位补码和最近邻。通过配置路由器和互连参数,ML mesh拓扑的FPGA资源利用率比mesh低75%。ML mesh拓扑显示,在局部流量模式下,网络延迟提高了33.2%。与均匀随机流量相比,mesh和ML mesh拓扑在最近邻流量下的饱和吞吐量分别高出0.53倍和0.1倍。

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