ohonen神经网络在时延驱动布局听应用

本文提出一个基于Ｋｏｈｏｎｅｎ自组织神经网络的以关键路径时延最小为优化目标的时延我动布局算法，算法的关键是建立面向线网的样本矢量，与面向单元的样本矢量相比，面向一网的样本矢量不仅可以直接处理多端线网，而且地延信息，实验结果表明，审一种有效的方法。     

用神经网络求解时延、功耗和连线三重驱动的布局问题

本文应用Ｋｏｈｏｎｅｎ自组织神经网络求解时延、功耗和连线三重驱动的门阵列布局问题．算法用自组织学习算法和分配算法确定关键单元的位置,用迭代改善的方法确定非关键单元的位置,从而获得关键线网最短、散热大的单元离得尽可能远并且单元连线总长尽可能短的布局．本文还介绍了面向线网和功耗的样本矢量的概念,与面向单元的样本矢量相比,面向线网和功耗的样本矢量不仅可以直接处理多端线网,而且能够描述时延信息和热信息．实验表明这是一种有效的方法     

精确时延模型下满足时延约束的缓冲器数目最小化的算法

提出了在精确时延模型下,满足时延约束的缓冲器数目最小化的算法.给出一个两端线网,该算法可以求出满足时延约束的最小缓冲器数目.运用高阶时延模型计算互连线的时延,运用基于查找表的非线性时延模型计算缓冲器的时延.实验结果证明此算法有效地优化了缓冲器插入数目和线网的时延,在二者之间取得了较好的折中.算法的运行时间也是令人满意的     

精确时延模型下满足时延约束的缓冲器数目最小化的算法

提出了在精确时延模型下,满足时延约束的缓冲器数目最小化的算法.给出一个两端线网,该算法可以求出满足时延约束的最小缓冲器数目.运用高阶时延模型计算互连线的时延,运用基于查找表的非线性时延模型计算缓冲器的时延.实验结果证明此算法有效地优化了缓冲器插入数目和线网的时延,在二者之间取得了较好的折中.算法的运行时间也是令人满意的.     

时延驱动的整平面整体布线算法

本文结出了一个新的时延驱动的整体布线算法．算法采用了整平面布线技术，从而具有快速求解的特点且无网序问题的困扰．算法优化的目标是使所有线网的最大时延之和最小，尤其是在关键路径上的线网实际电路的布线结果表明该算法可有效地改善关键路径上线网的时延．     

互连线网时延估算的一种有效算法

本文提出一种基于传递函数递推和系数匹配的互连线网时延估算法,该算法用二极点模型逼近互连线网的传递函数,仅通过计算某一频率点上的传递函数,就可利用导出的解析公式或拟合的经验公式进行快速时延估算,不必进行复杂的分量计算,算例表明,对于各个门限值,其计算结果均与ｓｐｉｃｅ计算的时延值发接近,计算量也比通常基于高阶分量计算的算法大为减少,在计算效率和模拟精度两方面得到较好折衷,对于互连线网时延估算具有实用     

基于Sakurai模型的时延驱动Steiner树算法

时延驱动的Ｓｔｅｉｎｅｒ树构造算法是时延驱动总体布线的基础．本文首先简介了求解最佳Ｓｔｅｉｎｅｒ树的Ｄｒｅｙｆｕｓ－Ｗａｇｎｅｒ算法．随后通过引入Ｓａｋｕｒａｉ时延模型,提出了直接基于Ｓａｋｕｒａｉ模型的提高线网时延性能的时延驱动ＤＷ算法．当集成电路工艺的特征宽度较小时,该算法求得的Ｓｔｅｉｎｅｒ树中关键点的时延值,明显小于ＩＤＷ和ＣＦＤ算法的结果．     

树的遍历在总体布线中的应用

把RLC模型的互连线网存储于一种树形链表结构,通过此种树形链表遍历RLC线网树的各节点,实现指定两点间的时延计算。把此种运算运用于一种新的总体布线算法中,进行布线算法的研究和实现。     

一个以时延优化为目标的力指向Steiner树算法

本文提出了一种用于总体布线的以时延优化为目标的力指向Ｓｔｅｉｎｅｒ树算法．它在构造Ｓｔｅｉｎｅｒ树时同时考虑使线网总长和从源点到漏点的路径长度最小，以期得到时延最小的Ｓｔｅｉｎｅｒ树．文中首先给出多端线网连线延迟模型，并导出其上界．基于这个时延模型，提出了力指向Ｓｔｅｉｎｅｒ树算法．算法已用Ｃ语言在Ｓｕｎ工作站上实现，并用于以性能优化为目标的总体布线中．实验表明，算法十分有效．     

一种基于敏感度的时延驱动快速布局算法

 本文提出了一种基于敏感度的时延驱动的快速布局算法.该算法在解方程和单元扩散这两个阶段同时优化关键线网时延.其中基于敏感度的线网权重模型用于解方程阶段,基于关键路径的启发式单元优化算法用于单元扩散阶段.静态时延分析工具Astro分析结果表明:与FastPlace相比,最小负松弛量(worst negative slack)平均提高了25.82%,负松弛量总和(total negative slack)平均提高了20.53%,同时总线长仅平均增加3.14%且运行时间没有明显增加.     

Scheduling of semiconductor test facility via Petri nets and hybridheuristic search

This paper proposes and evaluates two Petri net-based hybrid heuristic search strategies and their applications to semiconductor test facility scheduling. To reduce the setup time, such as the time spent to bring the test facilities to the required temperatures, scheduling multiple lots for each job type together is desirable. Petri nets can concisely model multiple lot sizes for each job, the strict precedence constraints, multiple kinds of resources, concurrent activities and flexible routes. To cope with the complexities for multiple lots scheduling, this paper presents two Petri net-based hybrid heuristic search strategies. They combine the heuristic best-first strategy with the controlled back tracking strategy based on the execution of the Petri nets. The obtained scheduling results are compared and analyzed through a small-size test facility. The better algorithm is also applied to a more sizable facility containing types of resources with a total of 79 pieces and 30 jobs. The future work includes the real-time implementation of the proposed method and scheduling results in real industrial settings     

流场可视化中的运动矢量估计方法

本文提出了一种新的运动矢量估计的方法,其基本思想是先对流体图象进行了处理,再采用贯相似性检测算法快速得到像素精度的位移量,最后再在像素范围内使用相位拟合算法快速且方便地估计出亚像素的位移精度。虽然本方法是基于流体运动分析的数字粒子图像测速,但基本原理可广泛地用于一般的运动矢量估计。     

基于归一化方法的协同过滤推荐算法

针对传统的协同过滤推荐算法没有考虑用户向量维度以及评价值差异的问题,提出了一种基于归一化方法的协同过滤推荐算法。算法在计算用户或项目相似度之前首先将用户对每一项目的评分值归一化到一个统一的值域范围,然后再计算用户向量空间的相似性并进行预测推荐。实验结果显示该算法能够准确地找到相似的邻居用户或项目,预测及推荐测性能有较大提高。     

融合TextRank算法的中文短文本相似度计算

传统的VSM向量空间模型忽略了文本语义,构建的文本特征矩阵具有稀疏性。基于深度学习词向量技术,文中提出一种融合改进TextRank算法的相似度计算方法。该方法利用词向量嵌入的技术来构建文本向量空间,使得构建的向量空间模型具有了语义相关性,同时采用改进的TextRank算法提取文本关键字,增强了文本特征的表达并消除了大量冗余信息,降低了文本特征矩阵的稀疏性,使文本相似度的计算更加高效。不同模型的仿真实验结果表明,融合改进的TextRank算法与Bert词向量技术的方法具有更好的文本相似度计算性能。     

LSI版图设计中的一种P／G网布线法

本文提出了一种有效的P/G网布线算法和在积木块式布图系统中实现的策略。与以往算法比较,此算法允许每条电源网具有多个馈电脚存在。其策略包括四个部分:(1)一种有效的层次式自上而下的P/G网平面性分析和拓扑路径分配算法;(2)P/G网线宽的确定;(3)总体压缩和再布线后P/G网布线信息的动态修改;(4)与信号网一起的平面性无网格电源网通道详细嵌入。实验结果表明我们的P/G网布线方法可获得令人满意的布线结果。     

A New Algorithm for the Selection of Control Cells in Boundary-Scan Interconnect Test

This paper presents an algorithm for the generation of the values to be loaded in the control cells of a Boundary-Scan (BS) chain during an interconnect test. The algorithm selects several groups of control cells while avoiding that two or more drivers excite the same net at the same time, allowing every net to be active for every test vector and testing every driver after the execution of the overall test process. It allows for 100% detection of short, open, stuck-at and driver transition faults on fully controllable and observable BS nets on virtually any BS board. In fact, only two minor requirements are imposed: (1) the sets of nets affected by two different control cells must be disjoint or one of them must be included in the other; (2) every net of a set affected by a control cell must have the same number of drivers. In addition, the algorithm can be implemented very easily, avoiding the need to explore all the possible combinations of values to be loaded in the control cells.     

Net-based force-directed macrocell placement for wirelength optimization

We propose a net-based hierarchical macrocell placement such that "net placement" dictates the cell placement. The proposed approach has four phases. 1) Net clustering and net-level floorplanning phase: a weighted net dependency graph is built from the input register-transfer-level netlist. Clusters of nets are then formed by clique partitioning and a net-cluster level floorplan is obtained by simulated annealing. The floorplan defines the regions where the nets in each cluster must be routed. 2) Force-directed net placement phase: a force-directed net placement is performed which yields a coarse net-level placement without consideration for the cell placement. 3) Iterative net terminal and cell placement phase: a force-directed net and cell placement is performed iteratively. The terminals of a net are free to move under the influence of forces in the quest for optimal wire length. The cells with high net length cost may "jump" out of local minima by ignoring the rejection forces. The overlaps are reduced by employing electrostatic rejection forces. 4) Overlap removal and input/output (I/O) pin assignment phase: Overlap removal is performed by a grid-based heuristic. I/O pin assignment is performed by minimum-weight bipartite matching. Placements generated by the proposed approach are compared with those generated by Cadence Silicon Ensemble and the O-tree floorplanning algorithm. On average, the proposed approach improves both the total wire length and longest wire length by 18.9% and 28.3%, respectively, with an average penalty of 5.6% area overhead.     

基于区域最大相似度的快速图像分割算法

针对基于区域最大相似度图像分割(MSRM)算法中利 用颜色直方图描述符计算相邻区域之间相似度存 在着计算量大和描述能力的不足,提出改用基于局部二值模式(LBP)纹理描述符计 算相邻区域相似度的改进MSRM(IMSRM)算法。LBP描述符通过对像素点之间局 部微结构进行编码实 现了对其空间关系的描述,有效提高了对区域特征的描述能力,并且所获得的特征矢量维数 远小于颜色直 方图,区域之间的相似度计算效率大幅度得到提高。与MSRM算法对比实验表明,IMSRM算法 可以从各种复杂背景中有效提取待分割对象的轮廓,所提取的轮廓边缘细节上更优,算法执 行效率能够提高50%左右。     

Research on calculation method of text similarity based on smooth inverse frequency

In order to improve the accuracy of text similarity calculation, this paper presents a text similarity function part of speech and word order-smooth inverse frequency (PO-SIF) based on sentence vector, which optimizes the classical SIF calculation method in two aspects: part of speech and word order. The classical SIF algorithm is to calculate sentence similarity by getting a sentence vector through weighting and reducing noise. However, the different methods of weighting or reducing noise would affect the efficiency and the accuracy of similarity calculation. In our proposed PO-SIF, the weight parameters of the SIF sentence vector are first updated by the part of speech subtraction factor, to determine the most crucial words. Furthermore, PO-SIF calculates the sentence vector similarity taking into the account of word order, which overcomes the drawback of similarity analysis that is mostly based on the word frequency. The experimental results validate the performance of our proposed PO-SIF on improving the accuracy of text similarity calculation.     

融合矢量量化与LBP的图像检索算法

基于内容的图像检索算法一直是图像领域研究的热门课题,因此提出一种新的融合矢量量化与LBP的图像检索算法。首先,将彩色图像转化到HSI颜色空间,进行矢量量化编码,统计图像码字出现的频数,形成颜色直方图,完成颜色特征的提取;然后,再将彩色图像转化成灰度图像,利用局部二进制模式(LBP)算法提取纹理特征;最后,相似度计算采用颜色特征和纹理特征相似度加权平均,并且改变颜色特征和纹理特征的权值,多次实验,得到使查准率最高的权值。实验结果表明,算法能有效地提升图像检索性能。