基于云自适应遗传算法的NoC映射研究

NoC映射是NoC设计中的重要步骤,映射结果的优劣对NoC的QoS约束和通信功耗有着很大的影响。提出一种采用云自适应遗传算法实现NoC映射的方案,该算法利用云模型对传统遗传算法加以改进,以此新方法自动调整遗传算法过程中的交叉概率和变异概率,从而达到优化遗传算法的目的。结合NoC映射中的具体问题,在功耗和延时约束的限制条件下,建立了延时约束下的NoC映射功耗数学模型。实验表明,该方法在NoC映射中取得了良好的效果,降低了通信功耗。     

改进量子算法的片上网络映射研究

片上网络（NoC）是解决片上系统（SoC）之间各个IP核通信的主要方法。其中NoC的映射是整个NoC设计过程中最为关键的步骤之一。采用一种改进的方法解决NoC映射问题,该方法基于量子进化算法,并在算法中采用一种改进的更新方法,之后引入精英策略,让所有中间过程的解都参与到迭代中,选择其中最好的解作为每次迭代的NoC映射最终解。使用该方法建立在延时约束下的NoC映射功耗数学模型,实验表明,该方法在NoC映射中能达到降低通信功耗的目的。     

延迟优化的片上网络低功耗映射*

片上网络（NoC）是解决传统基于总线的片上系统（SoC）所面临的功耗、延迟、同步和信号完整性等挑战的有效解决方案。功耗和延迟是NoC设计中的重要约束和性能指标,在设计的各个阶段都存在着优化空间。基于蚁群优化算法,通过通信链路上并发通信事件的均匀分布来降低NoC映射阶段的功耗和延迟。仿真实验表明,与链路通信量负载均衡的方法相比,该方案能进一步在拓扑映射阶段优化功耗和延迟。     

片上网络的低功耗自适应数据保护

针对片上网络(NoC)提出了一种低功耗自适应数据保护机制。根据不同的片上网络通信链路错误数目自适应选择，在路由节点之间进行数据保护的跳距，保证了系统芯片功耗效率最优化。实验结果证明，在同样的可靠约束条件下，采用自适应数据保护，其功耗低于节点到节点，端到端的数据保护，特别是对需要高可靠性的NoC通信结构，自适应数据保护机制表现得更为有效。     

不规则IP模块到2维NoC结构的映射方法研究

提出了一种新的基于NoC(Network on Chip)的不规则IP模块映射方法.其基本思想是把较大的IP模块分解成几个小的IP虚模型,或把几个较小的IP模块组合成一个IP虚模型,使得每个IP虚模型能映射到NoC结构的一个资源节点上.通过计算曼哈顿距离和输入/输出度,可以确定每个通信节点中缓冲区的大小.根据计算的通信代价可以对初始映射结果进行调整,从而可以避免通信拥塞,降低系统的功耗.     

NoC低功耗技术研究综述

当前在高性能SoC设计中,功耗约束已成为NoC设计所面临的重要问题。本文着重阐述了NoC低功耗优化技术的相关内容,在分析现有NoC模拟器和功耗模型的基础上,从物理逻辑设计、软件编译优化、网络拓扑结构低功耗映射等方面评述了当前NoC低功耗关键技术。最后,对未来NoC低功耗技术研究的方向做出了预测。     

基于蚁群优化算法的NoC映射

功耗问题正逐渐成为NoC领域的研究热点,很多研究人员都在研究NoC功耗最小化的设计技术。文章采用一种有效的蚁群优化算法实现了NoC映射：在自动映射处理单元的同时,尽可能地减少了系统的通讯功耗。实验结果表明采用蚁群优化算法可以很快地收敛;针对不同的应用,可以减少25％-70％通讯功耗。     

用NS2评估片上网络体系结构的性能

随着SoC复杂度的不断提高,总线互连结构面临着越来越严峻的挑战,因此,以网络互连为特点的NoC应运而生。分析了影响NoC性能的几项重要指标,并用网络仿真软件NS2对几种常用拓扑结构的几项性能参数进行了评估,得出了在进行NoC设计时的指导性结论：结合具体的设计,对传输延迟、吞吐量、面积、功耗和可重用性等性能参数进行折衷考虑后选取合适的体系结构。     

一种面向通信特征的3D NoC体系结构设计

三维集成电路(three dimensional integrated circuit, 3D IC)和片上网络(network on chip, NoC)是集成电路设计发展的两个趋势.将两者结合的三维片上网络(three dimensional networks on chip, 3D NoC)是当前研究的热点之一.针对现有3D NoC的研究没有充分关注硅片内与硅片间的异构通信特征.提出了面向通信特征的硅片间单跳步(single hop inter dies, SHID)体系结构,该结构采用异构拓扑结构和硅片间扩展路由器(express inter dies router, EIDR).通过实验数据的分析表明,与3D-Mesh和NoC-Bus这两种已有的3D NoC结构相比,SHID结构有以下特点：1)延迟较低,4层堆叠时比3D-Mesh低15.1%,比NoC-Bus低11.5%;2)功耗与NoC-Bus相当,比3D-Mesh低10%左右;3)吞吐率随堆叠层数增加下降缓慢,16层堆叠时吞吐率比3D-Mesh高66.98%,比NoC-Bus高314.49%.SHID体系结构同时具备性能和可扩展性的优势,是未来3D NoC体系结构良好设计选择.     

NoC节点编码及路由算法的研究

NoC的设计和实现受到芯片的面积、功耗、深亚微米效应的限制.将拓扑结构和节点编码相结合,提出一种基于约翰逊码的二维平面编码.该编码隐含了Torus网络拓扑结构以及网络节点之间的连接关系并且有很好的扩展性,能够简化Torus拓扑结构上路由算法的实现和降低硬件成本.基于此编码和利用X-Y路由的路由确定性特点,提出改进X-Y路由,在中间节点只需要3或5个逻辑运算,降低路由的计算复杂性和硬件成本.最后,进行了节点结构设计.提出的编码不仅用于NoC的路由方面而且在NoC任务映射方面有重要应用.     

Improving performance of multi-core NUCA coherent systems using NoC-assisted mechanisms

The significant speed-gap between processor and memory makes last-level cache performance crucial for multi-core architectures (MCA). Non-uniform cache architecture (NUCA) has been proposed to overcome the performance limitations of MCA for many embedded applications. The cache is partitioned into sub-banks, with each sub-bank being an independently accessible entity connected with a fast on-chip network (NoC). This paper presents two NoC-assisted mechanisms to improve the performance and power consumption of NUCA coherence. The first mechanism provides priority-based communication based on the wormhole routing architecture to support NUCA coherence. High-priority coherent packets are transmitted first to save time. The second mechanism offers multicasting communication based on the proposed priority-based NoC to provide efficient cache coherency for NUCA. We dispatch and collect coherence packets at the collecting nodes (CN) to further decrease the number of coherent messages flowing in the NoC. Experimental results show that the priority-based transmission can improve performance by approximately 10?%. The proposed multicasting mechanism can further improve performance and decrease power consumption of the NoC in NUCA by approximately 15?%. The two proposed mechanisms can together enhance the performance by 25?% averagely.     

Performance-driven assignment and mapping for reliable networks-on-chips

Network-on-chip （NoC） communication architectures present promising solutions for scalable communication requests in large system-on-chip （SoC） designs. Intellectual property （IP） core assignment and mapping are two key steps in NoC design, significantly affecting the quality of NoC systems. Both are NP-hard problems, so it is necessary to apply intelligent algorithms. In this paper, we propose improved intelligent algorithms for NoC assignment and mapping to overcome the draw-backs of traditional intelligent algorithms. The aim of our proposed algorithms is to minimize power consumption, time, area, and load balance. This work involves multiple conflicting objectives, so we combine multiple objective optimization with intelligent algorithms. In addition, we design a fault-tolerant routing algorithm and take account of reliability using comprehensive performance indices. The proposed algorithms were implemented on embedded system synthesis benchmarks suite （E3S）. Experimental results show the improved algorithms achieve good performance in NoC designs, with high reliability.     

Scalable network-on-chip architecture for configurable neural networks

Providing highly flexible connectivity is a major architectural challenge for hardware implementation of reconfigurable neural networks. We perform an analytical evaluation and comparison of different configurable interconnect architectures (mesh NoC, tree, shared bus and point-to-point) emulating variants of two neural network topologies (having full and random configurable connectivity). We derive analytical expressions and asymptotic limits for performance (in terms of bandwidth) and cost (in terms of area and power) of the interconnect architectures considering three communication methods (unicast, multicast and broadcast). It is shown that multicast mesh NoC provides the highest performance/cost ratio and consequently it is the most suitable interconnect architecture for configurable neural network implementation. Routing table size requirements and their impact on scalability were analyzed. Modular hierarchical architecture based on multicast mesh NoC is proposed to allow large scale neural networks emulation. Simulation results successfully validate the analytical models and the asymptotic behavior of the network as a function of its size.     

片上通信结构——共享总线和NoC的分析与比较

采用模块化方法对集中式仲裁共享总线和二维网格片上网络(Network on Chip,NoC)的硬件开销和延迟进行了数学上的分析。在此基础上,通过可综合Verilog代码对这两种片上通信结构在RTL级进行描述,并建立了这两种通信方式的周期准确级的功能验证和性能分析环境。结果表明,在同样工艺条件下,共享总线的面积与NoC相比相当小;但对于大规模片上系统通信,NoC的吞吐效率及带宽明显优于共享总线。     

Modern architecture for photonic networks-on-chip

Development in photonic integrated circuits (PICs) provides a promising solution for on-chip optical computation and communication. PICs provides the best alternative to traditional networks-on-chip (NoC) circuits which face serious challenges such as bandwidth, latency and power consumption. Integrated optics have substantiated the ability to accomplish low-power communication and low-power data processing at ultra-high speeds. In this work, we propose a new architecture for NoC, which might improve overall on-chip network performance by reducing its power consumption, providing large channel capacity for communication, decreasing latency among nodes and reducing hop count. Some of the key features of the proposed architecture are to reduce the waveguide network for communication among nodes, and this architecture can be used as a brick to construct other architectures. In this architecture, we use micro-ring resonator (MRR) and it is used to provide a high bandwidth connection among nodes with a lesser number of waveguide networks. Furthermore, results show that this architecture of PICs provides better performance in terms of low communication latency, low power consumption, high bandwidth. It also provides acceptable FSR value, FWHR value, finesse value and Q-factor of micro-ring resonators used for the design of MRR in this architecture.

     

A multi-application approach for synthesizing custom network-on-chips

Execution of multiple applications on Multi-Processor System-on-Chips (MPSoCs) significantly boosts performance and energy efficiency. Although various researchers have suggested Network-on-Chip (NoC) architectures for MPSoCs, the problem still needs more investigations for the case of multi-application MPSoCs. In this paper, we propose a fully automated synthesis flow in five steps for the design of custom NoC fabrics for multi-application MPSoCs. The steps include: preprocessing, core to router allocation, voltage island merging, floorplanning, and router to router connection. The proposed flow finds design solutions that satisfy the performance, bandwidth, and power constraints of all input applications. If the user decides, the proposed synthesis adds network-level reconfiguration to improve the efficiency of the obtained design solutions. With the reconfiguration option, the proposed flow comes up with adaptive NoC architectures that satisfy each application’s communication requirements while power-gate idle resources, e.g., router ports and links. If reconfiguration option is not set by the user, the proposed flow considers the top communication requirements among the applications in finding design solutions. We have used the proposed synthesis flow to design custom NoCs for several combined graphs of real-world applications and synthetic graphs. Results show that the reconfiguration option can save up to 98% in the energy-delay product (EDP) of the ultimate designs.

     

System design of full HD MVC decoding on mesh-based multicore NoCs

Future multimedia applications such as full HD (1920 × 1080) multiview video coding (MVC) present great challenges on computing architectures. Even if with the state-of-the-art ASIC technology which can process single view HD decoding, dealing with multiple views would require times of computation capacity in proportion to the number of views, which is difficult to achieve. In this paper, we explore the system-level design space for full HD MVC applications mapped onto mesh-based multicore Network-on-Chip (NoC) architectures. To this end, we establish a simulation framework capable of simulating the combination of communication networks with computing cores. We investigate two task assignment schemes: picture-level assignment and view-level assignment. With an eight-view MVC decoding, we explore the design options with respect to network size, single-core performance and link bandwidth under both task assignment schemes. Our studies show that, to achieve a certain decoding performance, the computation capability and communication capacity should be balanced in the system. Also, to realize the eight-view HD decoding, the system only requires twice or less than twice of the single-core processing capacity required by single view decoding, thanks to the parallel computation and communication enabled by the multicore NoC architectures. Our results exhibit feasibility and potential of efficiently implementing the full HD MVC decoding on multicore NoC architectures.     

拓扑结构感知的片上网络体系结构应用映射与优化

应用映射是片上网络体系结构研究的关键问题之一,映射结果的好坏会极大地影响体系结构的性能。现有的应用映射方法大多基于特定的网络结构,如2d-mesh、2d-torus等,研究NoC性能或功耗约束的应用映射与优化方法。本文提出了一种拓扑结构感知的基于高层代码转换的片上网络应用映射与优化方法。该方法采用多面体模型对应用的核心循环进行自动并行和局部性优化,并将网络拓扑结构抽象成带权重的有向图,使用该有向图对任务流图进行覆盖,以提高任务的并行性,降低任务间同步和通信开销。实验结果表明,采用优化的映射方法后任务节点间的并行性被充分利用,通信开销降低,整体上提高了片上网络系统性能。     

A novel 3D NoC architecture based on De Bruijn graph

Networks on Chip (NoC) and 3-Dimensional Integrated Circuits (3D IC) have been proposed as the solutions to the ever-growing communication problem in System on Chip (SoC). Most of contemporary 3D architectures are based on Mesh topology, which fails to achieve small latency and power consumption due to its inherent large network diameter. Moreover, the conventional XY routing lacks the ability of fault tolerance. In this paper, we propose a new 3D NoC architecture, which adopts De Bruijn graph as the topology in physical horizontal planes by leveraging its advantage of small latency, simple routing, low power, and great scalability. We employ an enhanced pillar structure for vertical interconnection. We design two shifting based routing algorithms to meet separate performance requirements in latency and computing complexity. Also, we use fault tolerant routing to guarantee reliable data transmission. Our simulation results show that the proposed 3D NoC architecture achieves better network performance and power efficiency than 3D Mesh and XNoTs topologies.     

3D floorplanning of low-power and area-efficient Network-on-Chip architecture

Network-on-Chip (NoC) architectures have been adopted by chip multi-processors (CMPs) as a flexible solution to the increasing delay in the deep sub-micron regime. However, the shrinking feature size limits the performance of NoCs due to power and area constraints. In this paper, we propose three 3D floorplanning methods for a Triplet-based Hierarchical Interconnection Network (THIN) which is a new high performance NoC. The proposed floorplanning methods use both Manhattan and Y-architecture routing architectures so as to improve the performance, reduce the power consumption and area requirement of THIN. A cycle accurate simulator was developed based on Noxim NoC simulator and ORION 2.0 energy model. The proposed floorplanning methods show up to 24.69% energy and 8.84% area reduction at best compared with 3D Mesh. Our analysis concludes that THIN is not only a feasible but also a low-power and area-efficient NoC at physical level.