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Application-specific topology generation algorithms for network-on-chip design

机译:片上网络设计的专用拓扑生成算法

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摘要

Network-on-chip (NoC) is an alternative approach to traditional communication methods for system-on-chip architectures. Irregular topologies are preferable for the application specific NoC designs as they offer huge optimisation space in contrast to their regular counterparts. Generating an application-specific topology as part of the synthesis flow of a NoC architecture is a challenging problem as there may be several topology alternatives, each of which may be superior to the others based on the different objective criteria. In this study, the authors tackle at this problem and propose a heuristic and a genetic algorithm-based methods. The heuristic method, called TopGen, is a two-phase application-specific topology generation algorithm aiming to minimise the energy consumption of the system. TopGen first decomposes the given application into clusters based on the communication traffic. It then maps the clusters onto the routers and connects them in such a way that the communication cost of the network is minimised. The second algorithm, called GA-based topology generation algorithm-based topology generation algorithm (GATGA), is based on a genetic algorithm, which initially creates a set of solutions and uses genetic operators to reproduce new topologies from them. The authors compared our algorithms with existing methods through several multimedia benchmarks and custom generated graphs. TopGen and GATGA obtained better results than previous methods with negligible area and link length overheads.
机译:片上网络(NoC)是片上系统体系结构的传统通信方法的替代方法。不规则拓扑对于特定应用的NoC设计是更可取的,因为与常规规则相比,它们提供了巨大的优化空间。作为NoC架构的综合流程的一部分,生成特定于应用程序的拓扑结构是一个具有挑战性的问题,因为可能存在多种拓扑结构替代方案,根据不同的客观标准,每种替代方案都可能优于其他拓扑。在这项研究中,作者解决了这个问题,并提出了一种启发式和基于遗传算法的方法。名为TopGen的启发式方法是一种两阶段的特定于应用程序的拓扑生成算法,旨在最小化系统的能耗。 TopGen首先根据通信流量将给定的应用程序分解为群集。然后将群集映射到路由器,并以使网络的通信成本最小化的方式连接它们。第二种算法称为基于GA的拓扑生成算法-基于拓扑的生成算法(GATGA),它是基于遗传算法的,该算法最初创建了一组解决方案,并使用遗传算子从这些解决方案中复制出新的拓扑。作者通过多个多媒体基准测试和自定义生成的图形将我们的算法与现有方法进行了比较。与以前的方法相比,TopGen和GATGA的面积和链路长度开销可忽略不计,因此获得了更好的结果。

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