VLSI版图设计中的一种优化总体布线方法

本文针对国际上已有的多种BBL总体布线方法进行了研究,提出了一种更有效的基于多子图定向合并生成的布线算法,并在国家重点工程“熊猫系统中实现.实验结果比较表明:我们的总体布线优化技术优于已有的BBL总体布线工具.     

基于标准单元布图模式的电源线/地线网络设计、优化和验证集成工具

介绍了一个基于标准单元布图模式的电源线/地线网络的辅助设计集成工具.它应用了一系列高效的算法,为用户提供了电源线/地线网络的设计、优化和验证的功能.非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分.用户可以选择使用非线性规划的方法或者几种分枝定界方法来满足他们对于精度和速度方面的不同需求.实验结果表明,文中所提供的算法可以在很快的运行速度下实现更低的布线资源占用.因此,在这些有效算法基础上实现的辅助设计工具具有处理大规模电路的能力.     

基于标准单元布图模式的电源线/地线网络设计、优化和验证集成工具

介绍了一个基于标准单元布图模式的电源线 /地线网络的辅助设计集成工具 .它应用了一系列高效的算法 ,为用户提供了电源线 /地线网络的设计、优化和验证的功能 .非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分 .用户可以选择使用非线性规划的方法或者几种分枝定界方法来满足他们对于精度和速度方面的不同需求 .实验结果表明 ,文中所提供的算法可以在很快的运行速度下实现更低的布线资源占用 .因此 ,在这些有效算法基础上实现的辅助设计工具具有处理大规模电路的能力.     

基于不完全分解预优共轭梯度法的电源和地线网络求解器

在超大规模集成电路的电源和地线网络的设计中,求解由该网络上每个节点的电压和每条边上的电流是最基本的运算,它对电源和地线网络拓扑结构设计和线宽优化算法的质量具有直接的影响.针对电源和地线网络的特殊性,提出了一个高效的电源和地线网络求解器,包括电路网络中树结构的合并与恢复和用不完全分解的预优共轭梯度法来求解节点电压方程.该求解器的运算速度很快,所耗费的内存很小,同时具有很强的鲁棒性.     

基于不完全分解预优共轭梯度法的电源和地线网络求解器

在超大规模集成电路的电源和地线网络的设计中 ,求解由该网络上每个节点的电压和每条边上的电流是最基本的运算 ,它对电源和地线网络拓扑结构设计和线宽优化算法的质量具有直接的影响 .针对电源和地线网络的特殊性 ,提出了一个高效的电源和地线网络求解器 ,包括电路网络中树结构的合并与恢复和用不完全分解的预优共轭梯度法来求解节点电压方程 .该求解器的运算速度很快 ,所耗费的内存很小 ,同时具有很强的鲁棒性     

最小面积电源和地线网络的设计

本文讨论了集成电路芯片中单一压焊块树形结构电源／地线网络的线宽设计给定电源（地）线的布线拓扑结构，在满足最大可允许电压降、最小工艺线宽和金属电迁移等约束的条件下使整个电源（地）网络所占用的布线面积最小本文采用拉格朗日乘子算法实现了这个目标，不仅取得比较小的电源布线面积，同时取得了比其它同类算法快得多的运行速度     

基于可靠性及噪声约束的电源／ 地线优化设计

电源/地线(P/G)拓扑结构的优化设计是超大规模集成电路(VLSl)中直接影响芯片性能的一个非常重要的问题.通过对考虑可靠性及噪声的各项约束条件的分析,提出了一种时间复杂度为O(N2m)基于最小代价生成树(MST)和改进的Prim算法的快速构造算法.实验结果表明,该算法在满足同样的性能约束条件下能有效地减小布线面积.     

基于可靠性及噪声约束的电源/地线优化设计

电源 /地线 ( P/G)拓扑结构的优化设计是超大规模集成电路 ( VLSI)中直接影响芯片性能的一个非常重要的问题 .通过对考虑可靠性及噪声的各项约束条件的分析 ,提出了一种时间复杂度为 O( N2m)基于最小代价生成树 ( MST)和改进的 Prim算法的快速构造算法 .实验结果表明 ,该算法在满足同样的性能约束条件下能有效地减小布线面积     

IO单元自动排布算法IOAP

提出了一种应用于芯片物理设计过程中IO单元自动排布的新算法。IO单元排布是芯片物理设计过程中长期依赖经验的环节。IO单元排布的优化对布线,电源网格和设计收敛性的优化有很大贡献。文章重点研究边缘IO单元排布,提出了IO单元自动排布算法(IOAP)。此算法及其相关软件直接应用于视频解码芯片和无线传感器网络处理器芯片(已流片成功)的物理设计流程中。结果表明,IOAP有效改善了芯片的电源网格,时序和布线结果,减少了布线努力,提高了设计收敛性。     

用户电路板中的抗干扰问题分析

用户电路板具有数字／模拟信号混合,电源种类多,地线种类多,元器件多密度大等特点,因而会带来一 系列干扰问题,正确合理的布局布线,对抑制其干扰起着重要作用。本文通过几个典型实例,分析其干扰现象和干扰原因,并给出了抑制其干扰的有效措施。最后提出了用户电路板中印制板电源,地线布线设计时应注意的问题。     

A novel multicast routing algorithm in sparse splitting WDM network with power attenuation constraint

With the increasing requirement for communication bandwidth, all-optical network has been more and more important owning to its large traffic capability. Multicasting is an important technology in wavelength division multiplexing (WDM) optical network, and has been studied in many works. In this paper, we consider the multicasting technology on all-optical metropolitan area network (MAN) with maximum power attenuation constraint. The objective is to minimize total cost of a multicasting request. This problem is NP-hard. We propose a heuristic, named Power-Constraint Fix-Destination-Path (PC-FDP) algorithm, to solve this maximal power-loss constrained minimizing cost multicasting problem. It means that, during the process of building a multicasting tree, when a destination is reached and its power satisfies the constraint, the path from source to it would be fixed in the tree. Simulation results show that, all multicasting trees building the proposed algorithm satisfy the power constraint, with slight increasing of the total cost.     

Approximation and Heuristic Algorithms for Minimum-Delay Application-Layer Multicast Trees

In this paper we investigate the problem of finding minimum-delay application-layer multicast trees, such as the trees constructed in overlay networks. It is accepted that shortest path trees are not a good solution for the problem since such trees can have nodes with very large degree, termed high-load nodes. The load on these nodes makes them a bottleneck in the distribution tree, due to computation load and access link bandwidth constraints. Many previous solutions limited the maximum degree of the nodes by introducing arbitrary constraints. In this work, we show how to directly map the node load to the delay penalty at the application host, and create a new model that captures the trade offs between the desire to select shortest path trees and the need to constrain the load on the hosts. In this model the problem is shown to be NP-hard. We therefore present an approximation algorithm and an alternative heuristic algorithm. Our heuristic algorithm is shown by simulations to be scalable for large group sizes, and produces results that are very close to optimal     

一种改进的Steiner树启发式算法

最小Steiner树问题是NP完全问题，关于Steiner问题的启发式算法的研究具有重要理论和实际意义。本文在MPH算法基础上，对于经过某些关键节点的短路径优先考虑，提出了KBMPH算法，从而实现更多链路的共享。在随机网络上的仿真结果表明，极大多数情况下，在准Steiner树的网络费用KBMPH算法优于MPH算法，KBMPH算法的复杂度为O（n^3）。     

加权的基于多播节点的多播路由算法

在许多多播应用中,降低多播树网络费用非常重要.本文提出了加权的基于多播节点的多播路由算法（WDDMC算法）.由于改变了DDMC（Destination-Driven routing for low-cost Multicast ）算法中的指示函数,适当降低了多播节点作为中间节点的优先级,提高非多播节点作为中间节点的优先级,从而使得多播树更接近最小Steiner树.在随机网络上的仿真结果表明,WDDMC算法的多播树网络费用优于DDMC算法.该算法的复杂度与DDMC算法完全相同.     

一种采用混合平衡准则的新功率控制算法

功率控制算法按准则可以分为基于功率平衡准则和基于SIR平衡准则两大主流。基于信干比平衡的功率控制算法存在正反馈问题。基于功率平衡和信干比平衡混合准则的功率控制算法可以解决正反馈问题,但复杂度较高,实现比较困难。提出了一种基于功率平衡和信干比平衡混合准则的功率控制算法。本算法在每次迭代中通过测试接收信号功率和接收信干比,只需要一次判决产生下一周期的发射功率,因此具有易于实现的优点。分析和仿真表明本算法是有效的。     

基于微动调制的梳状谱灵巧噪声压制干扰

针对目前相干压制干扰算法干扰面积不足、非相干压制干扰算法发射功率要求高等问题,本文在噪声卷积干扰及微动干扰算法的基础上,提出一种基于微动调制的梳状谱灵巧噪声压制干扰算法。该算法能够在距离向及方位向获得部分压缩增益,降低了对干扰机发射功率的需求,同时在压制干扰面积上优于其他干扰算法,可根据压制区域地物回波特性对干扰参数进行调整,达到干扰要求。此外,针对图像客观评估中没有考虑人眼主观因素影响的不足,本文采用了基于人眼视觉特性的主、客观结合的图像评估指标对干扰前后的图像进行评估。场景实测数据与干扰信号仿真数据结合后得到的图像评估结果表明,本文所提出的干扰算法能够在一片区域中形成有效的面状压制干扰,且适用场景广泛,可以实现对面目标的有效保护。     

基于MADDPG的无人机辅助通信功率分配算法

针对多无人机(unmanned aerial vehicle, UAV)作为空中基站辅助通信的吞吐量和公平性问题,提出了一种基于多智能体深度确定性策略梯度算法(multi-agent deep deterministic policy gradient algorithms, MADDPG)的功率分配算法,该算法通过联合优化UAV基站的功率分配和用户接入以提高系统吞吐量和公平性。本文首先构建了UAV基站为地面建立通信服务的三维场景,然后通过联合功率、用户关联和UAV位置约束,构建了吞吐量和公平性最大化的问题模型。考虑到该问题的复杂性,本文将所构建的优化问题建模为马尔科夫决策过程(Markov decision process, MDP),通过引入深度确定性策略梯度算法(deep deterministic policy gradient algorithm, DDPG)解决该问题。仿真结果表明,本文提出的基于MADDPG的UAV基站功率分配算法与其他算法相比,可以有效地提升系统的吞吐量和用户的公平性,提高通信的服务质量。     

Spanning trees set synthesis algorithm for custom VLSI global routing

In this paper, we study the problem of multi-terminal nets layout optimization. To solve the problem, we propose a polynomial-time algorithm, which first constructs minimum spanning tree and then generates spanning tree set. An algorithm for near-minimum spanning trees set with controllable length deviation from a minimum is proposed. Effective trees length deviation value and trees number are investigated.     

Prediction-based dynamic routing intelligent algorithm in power optical communication network

New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network ( POCN ) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path ( KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent ( P-DRI) algorithm can reduce the service blocking probability by 55.59% , and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.     

Nonconvex Optimization for Power Control in Wireless CDMA Networks

In this paper, we propose an efficient power control algorithm for the downlink wireless CDMA systems. The goal of our paper is to achieve the optimum and fair resource utilization by maximizing a weighted sum utility with the power constraint. In fact, the objective function in the power optimization problem is always nonconcave, which makes the problem difficult to solve. We make progress in solving this type of optimization problem using PSO (particle swarm optimization). PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. It’s proved that the proposed algorithm converges to the global optimal solutions in this paper. Numerical examples show that our algorithm can guarantee the fast convergence and fairness within a few iterations. It also demonstrates that our algorithm can efficiently solve the nonconvex optimization problems when we study the different utility functions in more realistic settings.