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深亚微米IC互连降阶分析与优化技术研究
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摘要
深亚微米集成电路内互连线规模庞大,互连线之间的耦合众多,以至于互连线的等效电路系统规模通常达到数万至数十万阶,传统的电路模拟分析工具无法实现对如此大规模互连电路的有效仿真分析,因此大规模互连电路的快速分析,成为集成电路性能分析和优化需要解决的基本问题之一。同时互连寄生对集成电路性能有越来越大的影响,增加了集成电路设计的压力。互连性能优化技术,是解决互连问题的一种有效手段。因此本文主要从集成电路互连的模型降阶分析及互连性能优化技术两个方面进行研究。
     针对空间投影互连系统模型降阶方面的问题,分别提出了基于Krylov子空间广义逆降阶方法、基于群智能算法的结构保留降阶方法和基于广义结构保留的参数化降阶方法。在分析传统的正交投影降阶和斜投影降阶或Galerkin投影降阶和Petro-Galerkin投影降阶方法基础上,针对在给定Krylov投影矩阵V下如何找到最优的投影降阶状态变量问题,提出了Krylov子空间广义逆投影降阶方法,其满足最小范数最小二乘投影要求,在空间投影的意义上,这是相对较优的降阶结果。针对传统的结构保留降阶方法不能完全保留状态矩阵中电感关联矩阵子模块结构的问题,即有可能造成电感对地回路问题,提出基于群智能算法的结构保留降阶方法,其把互连系统结构保留降阶过程转化为固定结构的参数优化过程,通过现代粒子群优化算法进行优化降阶。在分析广义结构保留模型降阶方法特点和互连参数的局部均匀性特征的基础上,提出广义结构保留的参数化降阶方法,其利用通用的结构保留降阶方法有效的保留系统参数变化的概率特性。仿真结果证明了上述方法的正确性与有效性。最后,针对空间投影互连系统模型降阶的时域全局误差限问题,给出了4种时域误差限计算方法。
     针对正交函数近似互连系统模型降阶方面的问题,分别提出了加权自适应阈值小波插值点选择降阶方法和切比雪夫-小波降阶方法。在有理Krylov降阶方法基础上,针对传统固定阈值小波插值点选择方法的不足,提出加权自适应阈值小波插值点选择降阶方法,从仿真结果来看,其精度明显高于固定阈值小波插入点选择降阶方法。针对切比雪夫函数近似降阶方法局部精度不足和4阶B样条小波近似降阶方法速度过慢的缺点,提出了切比雪夫-小波函数近似降阶方法,其是充分利用了切比雪夫-小波函数的优点构造了一个兼顾降阶速度和降阶精度的正交函数近似降阶方法。从仿真结果来看,切比雪夫-小波降阶方法降阶速度明显高于4阶B样条小波降阶方法而与切比雪夫降阶方法相近,而精度方面明显优于切比雪夫降阶方法与4阶B样条小波降阶方法相近。
     针对互连系统电路级优化方面的问题,分别进行了参数变化下缓冲器插入和低功耗工艺变化不敏感电流模电路方面的研究。在参数变化下缓冲器插入方面,提出了基于高斯拟合的快速缓冲器插入方法,此方法主要采用高斯函数拟合插入互连线和插入缓冲器的联合概率密度函数,其有助于联合概率密度函数的求解和优化解方案的选取。仿真结果证明了这种方法的正确性和有效性。在电路层面还提出了一种替代缓冲器插入的低功耗工艺变化不敏感的电流模电路,此电路的核心为一个自偏置结构的偏置电路,其主要通过变化补偿的思想抑制工艺变化的影响,同时通过减少静态直流通路个数而降低自身功耗消耗。仿真与测试结果表明延时受工艺变化的影响很小,同时功耗得到有效降低。
     针对互连系统结构与系统级优化方面的问题,提出了一种基于数据总线特点的FV-BI总线编码电路,其能有效改善FV编码所不能改善的连续两次传递未编码数据总线上的开关活动。此编码电路主要采用时分复用和寄存器共用技术,有效降低FV-BI编码电路的额外电路开销,而很大程度地改善数据总线开关活动,在随机数据下相比FV总线编码能降低总线开关活动的26.4%。同时提出了一个可用于系统级时序分析优化的缓冲器模型和一种系统级互连时序快速分析优化方法,其不但能用于不变参数系统互连时序分析与优化,而且也能用于工艺变化下互连系统时序分析与优化,仿真结果表明其正确性与有效性。
Interconnect system in VLSI is complexity, and the mutual coupling is large.So, the equivalent circuit of interconnect wire scale usually reaches tens ofthousands to hundreds of thousands orders. Tranditional circuit simulation tools cannot achieve the effective analysis on such a large interconnect circuit. Thus,It is thefundamental problem of performance analysis and optimization of IC to solve rapidanalysis of large-scale interconnect circuit. Moreover, interconnect parasitics haveincreasing influence on integrated circuit performance, which increases the ICdesign pressure. Interconnect optimization techniques are a kind of effective meanto solve the problem of interconnection. Hence, this thesis mainly studies twoaspects those are the integrated circuit interconnect model order reduction (MOR)analysis and interconnect performance optimizaiton technology.
     In space projection MOR aspect, we have proposed MOR method basedgeneralized inverse in Krylov sub-space, MOR method based swarm intelligencealgorithm, and parameterized MOR method based general structure preservingtechniques. On the basis of traditional orthogonal projection and oblique projectionor Galerkin space projection and Petro-Galerkin projection, we proposepseudo-inverse projection method in Krylov subspace, which satisfies minimumnorm least squares projection condition that is relative optimal reduced order resultin the sense of space projection reduced order. For traditonal structure preservingMOR problem that do not maintain the structure of inductance incidence matrix inreduced order process, we propose a MOR method based a swarm intelligencealgorithm that turns structure preserving reduced order process into parameteroptimiztion process and then optimizes it. On the basis of local uniformitycharacteristics of interconnect wire, we propose a parameterized MOR methodbased on general structure preserving techniques that can effectively retain theprobability characteristics of parameterized interconnect system. Simulation resultsprove the correctness and effectiveness of all above methods. Finally, For the globalerror bound prolem of space projection reduced order methods, we propose fourtypes of error bound calculation methods in time domain.
     In orthogonal funciton approximation reduced order aspect, we have proposeda weighted self-adaptive threshold wavelet for interpolation point selection MORmethod and a Chebyshe-Wavelet reduced order method. Weighted self-adaptivethreshold wavelet for interpolation point selection MOR method is on the basis ofrational Krylov MOR by weighted self-adaptive threshold wavelet method to selectrational frequency interpolation points. From simulation results, the precision of MOR based weighted self-adaptive threshold method is higher than man-madethreshold method. For Chebyshev function approximation reduced order precisionlimitation in local approximation and4-order B spline wavelet reduced ordermethod speed problem,we propose a Chebyshev-Wavelet MOR method that makesthe fullest use of Chebyshev-Wavelet function to construct wavelet functionexpansion MOR method, which considers reduced order speed and precision. Fromexperiment results, the speed of Chebyshev-Wavelet method is highe than4-order Bspline wavelet method and is same with Chebyshev method. While the precision ofChebyshev-Wavelet method is highe than Chebyshev method and is same as4-orderB spline wavelet method.
     For the circuit level optimization aspect of interconnect system, we havestudied a buffer insertion method in parameter variation condition and low powerprocess variation-insensitive current-mode signaling scheme respectively. Inparameter variation buffer insertion fact, we have propsed a probability methodbased on Gaussian fitting, which mainly used Gaussian function fitting the jointprobability density of inserting wire and buffer. From simulation results, we canprove the correctiveness and effectiveness of the method. In the low power andprocess variation-insensitive current-mode signaling scheme, we have proposed anew current-mode circuit that mainly used a biasing circuit based on self-biasstructure to maintain process variation robust by compensation strategy. Fromsimulation and testing results, we can prove that interconnect system delay onlychanges very little due to process variations, while the power of current-modecircuit is reduced effectively.
     For the structure and system level optimization aspect of interocnnect system,we have proposed a time division multiplexing FV-BI bus coder based on data buscharacteristics. FV-BI coder can effectively improve the switching activity of thecase that is consecutive transmiting two uncoding data in data bus. Due to usingtime-divison multiplexing technology, it only need to introduce one additionalsignal line. Moreover, it can employ small area and consume less power by usingregister sharing technology. From simulation results, we can conclude that FV-BIcan improve26.4%switching activity in random data than FV coder. Meanwhile,we also propose a system level buffer model and a fast speed timing analysisoptimization method which can be used in system level timing analysis andoptimizaiton in normal condition and process parameter variation condition.Simulaiton results prove the correctiveness and effectiveness of it.
引文
[1] ITRS. International Technology Roadmap for Semiconductors [EB/OL].(2009)
    [2013-10-06]. http://www.itrs.net/Links/2009ITRS/Home2009.htm
    [2] ITRS. International Technology Roadmap for Semiconductors
    [EB/OL].(2011)[2013-10-06].http://www.itrs.net/Links/2011ITRS/2011Chapters/2011Design.pdf
    [3] Brian B. The Need for a Scalable Verification Methodology to Overcome theLimitations of Current Verification Approaches [EB/OL].(2013)[2013-10-06].http://www.mentor.com/techpapers/fulfillment/upload/mentorpaper_22780.pdf
    [4] Cheng C K, Lillis J, Lin S, Chang N. Interconnect Analysis and Syntehsis[M].New York: Wiley,2000:153-159.
    [5] Schiilders H A. The Need for Novel Model Order Reduction Techniques inThe Electronics Industry[C]. Workshop Model Reduction for CircuitSimulation, Hambur, Germany,2008:3-23.
    [6] Schilders W. Introduction to Model Order Reduction[C]. Model OrderReduction Coupled Problems and Optimization Workshop, Leiden,Netherlands,2005:3-32.
    [7] ITRS. International Technology Roadmap for Semiconductors [EB/OL].(2004)[2013-10-06]. http://www.itrs.net/Links/2004ITRS/Home2004.htm
    [8] ITRS. International Technology Roadmap for Semiconductors [EB/OL].(1997)[2013-10-06]. http://www.itrs.net/Links/1997ITRS/Home1997.htm
    [9] Chandra G, Kapur P, and Saraswat K C. Scaling Trends for the on Chip PowerDissipation[C]. IEEE International Interconnect Technology Conference,Burlingame, USA,2002:170-172.
    [10] Kapur P, Mcvittie J P, and Saraswat K C. Technology and ReliabilityConstrained Future Copper Interconnects-Part I: Resistance Modeling[J].IEEE Transactions on Electron Devices,2002,49(4):590-597.
    [11] Lanczos C. A Iteration Method for the Solution of the Eigenvalue Problem ofLinear Differential and Integral Operators[J]. J. Res. Nat. Bur. Standards,1950,45(2):225-289.
    [12] Lanczos C. Solution of Systems of Linear Equation by Minimized Iteration[J].J. Res. Nat. Bur. Standards,1952,9(1):33-53.
    [13] Arnoldi W E. The Principle Minimized Iteration in the Solution of the MatrixEigenproblem[J]. Quart. Appl. Math.,1951,9(1):17-29.
    [14] Freund R W. Krylov-Subspace Methods for Reduced-Order Modeling inCircuit Simulation[J]. Journal of Computational and Applied Mathematics,1999,123(2):395-421.
    [15] Pillage L T, Rohrer R A. Asymptotic Waveform Evaluation for TimingAnalysis[J]. IEEE Trans. On Computer-Aided Design of Integrated Circuitsand Systems,1990,9(4):352-366.
    [16] Feldmann P, Freund R W. Efficient Linear Circuit Analysis by PadeApproximation via the Lanczos Process[J]. IEEE Trans. On Computer-AidedDesign of Integrated Circuits and Systems,1995,14(5):639-649.
    [17] Freund R W and Feldmann P. Reduced-Order Modeling of Large LinearPassive Multi-Terminal Circuit Using Matrix-Pade Approximation[C]. DATEConf, Paris, France,1998:530-537.
    [18] Salimbahrami B, Lohmann B, Bechtold T, and Korvink J. A Two-SidedArnoldi-Algorithm with Stopping Criterion and an Application in OrderReduction of MEMS[J]. Mathematical and Computer Modelling of DynamicalSystems,2005,11(1):79-93.
    [19] Odabasioglu A, Celik M, Pileggi L. PRIMA: Passive Reduced-OrderInterconnect Macromodeling Algorithm[J]. IEEE Trans. On Computer-AidedDesign of Integrated Circuits and Systems,1999,17(8):645-654.
    [20] Kerns K J, Yang A T. Stable and Efficient Reduction of Large, Multiport RCNetwork by Pole Analysis via Congruence Transformations[J]. IEEE Trans. onComputer-Aided Design of Integrated Circuits and Systems,1998,16(4):734-744.
    [21] Mi N, Yan B, Tan S X-D, Fan J and Yu H. General Block Structure-PreservingReduced Order Modeling of Linear Dynamic Circuits[C]. InternationalSymposium on Quality Electronic Design, San Jose, USA,2007:633-638.
    [22] Bai Z, Li R, Su Y, A Unified Krylov Projection Framework forStructure-Preserving Model Reduction[M]. Model Order Reduction: Theory,Research Aspects and Applications, Springer-Verlag, Berlin, Herlberg,2008:100-140.
    [23] Cillena J F, Schilder W H A, Silveira L M. Block Oriented Model OrderReduction of Interconnected System[J]. International Journal NumericalModelling: Electr. Neetw. Dev. And Fields,2009,8(2):1-19.
    [24] Freund R W. SPRIM: Stucture-Preserving Reduced-Order InterconnectMacromodeling[C]. International Conference on Computer Aided Design, SanJose, USA,2004:80-87.
    [25] Sheehan B N. ENOR: Model Order Reduction of RLC Circuits Using NodalEquations for Efficient Factorization[C]. Design Automation Conference,New Orleans, USA,1999:17-21.
    [26] Su Y, Wang J, Zeng X, et al. SAPOR: Second-order Arnoldi Method forPassive Order Reduction of RCS Circuits[C]. International on ComputerAided Design, San Jose, USA,2004:74-79.
    [27] Bai Z, Slone R D, Smith W T, and Ye Q. Error Bound for Reduced SystemModel by Pade Approximation via the Lanczos Process[J]. IEEE Trans.Computer-Aided Design of ICs and Systems,1999,18(1):133-141.
    [28] Besselink B, Tabak U, Lutowska A. A Compairson of Model ReductionTechniques from Structural Dynamic, Numerical Mathematics and Systemsand Control[J]. Journal of Sound and Vibration,2013,332(19):4403-4422.
    [29] Wang H, Yu H, Tan X.-D. Fast Timing Analysis of Clock NetworksConsidering Environmental Uncertainty[J]. Integration, the VLSI Journal,2012,45(4):430-440.
    [30] Thomas W, Herko P, and Boris L. Gramian-Based Error Bound in ModelReduction by Krylov Subspace Methods[C]. International Federation ofAutomatic Control World Congress, Milano, Italy,2011:3587-3592.
    [31] Moore B. Principle Component Analysis in Linear Systems: Controllability,and Observability, and Model Reduction[J]. IEEE Trans. Automat. Contr.,1981,26(1):17-32.
    [32] Desai U, Pal D. A Transformation Approach to Stochastic Model Reduction[J].IEEE Trans. Automat. Contr.,1984,29(5):1097-1100.
    [33] Nahvi S A, Nabi M, Janardhanan S. Nonlinearrity-Aware Sub-ModelCombination in Trajectory Based Methods for Nonlinear MOR[J].Mathematics and Computers in Simulation,2013,94(8):127-144.
    [34] Sorensen D C, Antoulas A C. The Sylvester Equation and ApproximateBalanced Reduction[J]. Linear Algebra and Its Application,2002,351(4):671-700.
    [35] Knockaert L, Dhaene T, Ferranti F Zutter D D. Model Order Reduction withPreservation of Passivity, Non-Exapnsivity and Markov Moments[J]. Systems&Control Letters,2011,60(1):53-61.
    [36] Phillips J R, Silveira L M. Poor man’ TBR: A Simple Model ReductionScheme[J]. IEEE Trans. on Compter-Aided Design of Integrated Circuits andSystems,2005,24(1):43-55.
    [37] Ghosh S, Senroy N. Balanced Truncation Based Reduced Order Modeling ofWind Farm[J]. International Journal of Electrical Power&Energy Systems,2013,53(11):649-655.
    [38] David B, Chen X. Coupled Electrothermal-Mechanical Analysis for MEMSvia Model Order Reduction[J]. Finite Elements in Analysis and Design,2010,46(12):1068-1076.
    [39] Yan B, Tan S X-D, Liu P, and et al. SBPOR: Second-Order BalancedTruncation for Passive Model Order Reduction of RCL Circuit[C]. DesignAutomation Conference, San Jose, USA,2007:158-161.
    [40] Serkan G. An Iterative SVD-Krylov Based Method for Model Reduction ofLarge-Scale Dynamical Systems[J]. Linear Algrbra and Its Applications,2008,428(2008):1964-1986.
    [41] Tan S X-D. Advanced Model Order Reduction Techniques in VLSI[M], NewYork: Cambridge University Press,2007:57-62.
    [42] Antoulas A C. Approximation of Large-Scale Dynamical Systems[M],Philadelphia: SAIM,2005:235-240.
    [43] Peter B, Michael H, Jan E, Maten W T. Model Reduction for CircuitSimulation[M]. Hamburg: Germany,2011:53-83.
    [44] Jiang Y L and Chen H B. Time-Domain Model-Order Reduction of GeneralOrthogonal Polynomials for Linear Input-Output Systems[J]. IEEE Trans.Auto. Control,2012,57(2):330-343.
    [45] Rudy E and Boris L. Moment Matching Model Order Reduction in TimeDomain via Laguerre Series[C]. Proceeding of the17th world Congress TheInternational Federation of Automatic Control, Seoul, Korea,2008:3198-3203.
    [46] Wang J M, Yu Q, and Kuh E S. Passive Model Order Reduction AlgorithmBased on Chebychev Expansion of Impulse Response of InterconnectNetworks[C]. Design Automation Conference, San Jose, USA,2000:520-524.
    [47] Chen Y, Balakrishnan V, Koh C K, and Roy K. Model Reduction in TimeDomain using Laguerre Polynomial and Krylov Methods[C]. Design,Automation and Test in Europe, Grenoble, France,2002:931-935.
    [48] Eid R, Salimbahrami B, and Lohmann B. Equivalence of Laguerre-BasedModel Order Reduction and Moment Matching[J]. IEEE Trans. on AutomaticControl,2007,52(6):1104-1108.
    [49] Vrudhula S, Wang J M, and Ghanta P. Hermite Polynomial Based InterconnectAnalysis in the Presence of Process Variation[J]. IEEE Trans. Computer-AidedDesign,2006,25(10):2001-2011.
    [50] Zeng X, Feng L, Su Y, Cai W, Zhou D, Chiang C. Time Domain ModelReduction by Wavelet Collocation Method[C]. The Design, Automation andTest in Europe Conference, Grenoble, France,2006:1-6.
    [51] Wang J M, Ghanta P, Vrudhula S. Stochastic Analysis of InterconnectPerformance in the Presence of Process Variations[C]. IEEE/ACMInternational Conference on Computer Aided Design, San Jose, USA,2004:880-886.
    [52]李鑫,Wang J M,张瑛,等.工艺随机扰动下非均匀RLC互连线串扰的谱域方法分析[J].电子学报,2009,37(2):398-403.
    [53] Homescu C, Petzold L R, and Seban R. Error Estimation for Reduced-OrderModels of Dynamical Systems[J]. SAIM Review,2007,49(2):277-299.
    [54] Lin W Z, Zhang Y J, and Li E P. Proper Orthogonal Decomposition in theGeneration of Reduced Order Models for Interconnects[J]. IEEE Trans. onAdvanced Packaging,2008,31(3):627-636.
    [55] Mijakovic S. Using Frequency Response Coherent Structures for Model-OrderReduction in Microwave Application[J]. IEEE Trans. Microwave TheoryTech.,2004,52(9):2292-2297.
    [56] Lam K M. Application of POD Analysis to Concerntration Field of a JetFlow[J]. Journal Hydro-Environment Research,2013,7(3):174-181.
    [57] Gad E. Circuit-Based Analysis of Electromagnetic Field Coupling withNonuniform Transmission Lines. IEEE Trans. on ElectromagneticCompatibility,2008,50(1):149-165.
    [58] Chen C Z, Gad E, Nakhla M Archar R. Analysis of Frequency-DependentInterconnects Using Integrated Congruence Transform[J]. IEEE Trans. onComputer-Aided Design of Integrated Circuits and Systems,2007,26(6):1139-1149.
    [59] Wang Q, Zhong T, Wong N. Hilber-Schmidt-Hankel Norm Model Reductionfor Matrix Secon-Order Linear Systems[J]. Journal of Control Theory andApplications,2011,9(4):571-578.
    [60] Zhou K, Doyle J C, and Glover K. Robust and Optimal Control[M]. NewJersey: Precntice-Hall,1996:432-540.
    [61] Sou K C, Megretski A, and Daniel L. A Quasi-Convex Optimization Approachto Parameterized Model Order Reduction[J]. IEEE Trans. on Computer-AidedDesign of Integrated Circuits and Systems,2008,27(3):456-469.
    [62] Eid R. Time Domain Model Reduction by Moment Matching[D]. PhD thesis,Institute of Automatic Control, Technische University Munchen,2009:20-30.
    [63] Beyene W. and Schutt-Aine. Efficient Transient Simulation of High-SpeedInterconnect Characterized by Sampled Data[J]. IEEE Trans. Compon.,Package, Manuf. Technol. B,1998,21(1):105-114.
    [64] Ferranti F, Dirk D, Luc K, Tom D. Data-Driven Parameterized Model OrderReduction Using z-Domain Multivariate Orthonormal Vector FittingTechnique [M]. Model Reduction for Circuit Simulation,2011:141-148.
    [65] Coelho C., Phillips J, and Silveira L. A Convex Programming Approach toPositive Real Rational Approximation[C]. IEEE ICCAD, San Jose, USA,2001:4-8.
    [66] Boyd S, Ghaoui L E, and Balakrishnan V. Linear Matrix Inequalitities inSystem and Control Theory[M]. New York: SIAM,1994:130-140.
    [67] Kubalinska D. Optimal Interpolation-Based Model Reduction[D]. PhD thesis,University of Bremen,2008:32-43.
    [68] Feldmann P. Model Order Reduction Techniques for Linear Systems withLarge Number of Terminals[C]. In Proceedings of the Design, Automation andTest in Europe Conference, Grenoble, France,2004:44-47.
    [69] Feldmann P and Liu F. Sparse and Efficient Reduced Order Modeling ofLinear Subcircuits with Large Number of Terminals[C]. InternationalConference on Computer-Aided Design, San Jose, USA,2004:88-92.
    [70] Peng L and Shi W. Model Order Reduction of Linear Networks with MassivePorts via Frequency-Dependent Port Packing[C]. In Proceedings Conferenceon Design Automation, San Jose, USA,2006:267-272.
    [71] Benner P, Feng L, and Rudnyi E B. Using the Superposition Property forModel Reduction of Linear Systems with a Large Number of Inputs[C]. InProceedings of the18th International Symposium on Mathematical Theory ofNetworks and Systems,2008:3-11.
    [72] Yang F, Zeng X, Su Y, and Zhou D. RLCSYN: RLC Equivalent CircuitSynthesis for Structure-Preserved Reduced-order Model of Interconnect[C].IEEE International Symposium on Circuits and Systems, New Orleans, LA,USA,2007:2710-2713.
    [73] Stefan G. Rational Krylov Methods for Operator Function[D]. TechnischenUniversitat Bergakademie Freiberg,2010:27-34.
    [74] Robert H H, James A H. High-Performance Interconnect: An IntegrationOverview[J]. Proceedings of the IEEE,2001,89(5):586-601.
    [75] Jeffrey A D and James D M. Interconnect Technology and Design forGigascale Integration[M]. Netherland: Kluwer Academic,2003:215-218.
    [76] Das A. Matt S. Nikos H, Gokhan M, and Alok C. Dynamic Directories: AMechanism for Reducing on-Chip Interconnect Power in Multicores[C].DATE, Dresden, Germanny,2012:479-484.
    [77] Moiseev K, Kolodny A, and Wimer S. Interconnect Power and DelayOptimization by Dynamic Programming in Gridded Design Rules[C]. ISPD,San Francisco, USA,2010:1-8.
    [78] Jeon J, Kim D, Shin D, and Choi K. High-Level Synthesis Under Multi-CycleInterconnect Delay[C]. Proceedings of the ASP-DAC, Yokohama, Japan,2001:662-667.
    [79] Xue L, Shi F, Ji W, Khan H U R.3D Floorplanning of Low-Power andArea-Efficient Network-on-Chip Architecture[J]. Microprocessors andMicrosystems,2011,35(5):484-495.
    [80] Stammennann A, Helms D, Schulte M, Schulz A, and Nebe W. BindingAllocation and Floorplanning in Low Power High-Level Synthesis[C].International Conference on Computer Aided Design, San Jose, USA,2003:544-550.
    [81] Lin Z and Niraj K J. Interconnect-Aware High-Level Synthesis for LowPower[C]. International Conference on Computer Aided Design San Jose,USA,2002:110-117.
    [82] Saraju P M, Ranganathan N, and Sunil K C. Simultaneous Peak and AveragePower Minimization During Datapath Scheduling[J]. IEEE Trans. on Circuitsand Systems,2005,52(2005):1157-1165.
    [83] Liu Z P, Bian J N, Zhou Q, and Dai H. Interconnect Delay and PowerOptimization by Module Duplication for Integration of High Level Synthesisand Floorplan[C]. IEEE Computer Society Annual Symposium on VLSI, PortoAlegre, Brazi,2007:279-284.
    [84] ITRS. International Technology Roadmap for Semiconductors [EB/OL].(2005)[2013-10-06]. http://www.itrs.net/Links/2005ITRS/Home2005.htm
    [85] Catalan G, Seidel J, Ramesh R, Scott J F. Domain Wall Nanoelectronics[J].Physical Review X,2012,84(1):119-156.
    [86] Ruby A. Reduction of Transimission Line Losses Using VLSI Interconnect [J].Procedia Engineering,2012,30(1):10-19.
    [87] Wimer S, Michaely S, Moiseev K, and Kolodny A. Optimal Bus Sizing inMigration of Processor Design[J]. IEEE Trans. Circuits and Systems-I,2006,53(5):1089-1100.
    [88] Macii E, Poncino M, and Salerno S. Combining Wire Swapping Spacing forLow-Power Deep-Submicron Buses[C]13th ACM Great lakes Symp. OnVLSI, Washington, DC, USA,2003:198-202.
    [89] Moiseev K, Wimer S, Klodny A. Power-Delay Optimization in VLSIMicroprocessors by Wire Spacing[J]. ACM Trans. Design Automation ofElectronic Systems,2009,14(4):5-14
    [90] Chen R and Zhou H. An Efficient Data Structure for Maxplus Merge inDynamic Programming[J]. IEEE Trans. Computer-aided Design of IntegratedCircuits and Systems,2005,25(12):3004-3009.
    [91] Rabey J M, Chandrakasan A, and Nikolic B. Digital Integrated Circuits: ADesign Perspective[M]. New Jersey: Prentice Hall,2003:156-326.
    [92] Gupta R, Tutuianu B, Pileggi L T. The Elmore Delay as a Bound for RC Treeswith Generalized Input Signals[J]. IEEE Trans. Computer-Aided Design ofIntegrated Circuits and Systems,1997,16(1):95-104.
    [93] Yan S, Sarin V, Shi W. Fast3-D Capacitance Extraction by InexactFactorization and Reduction[J]. IEEE Trans. Computer-Aided Design ofIntegrated Circuits and Systems,2006,30(10):2282-2286.
    [94] Nabors K, White J. FastCap: A Multipole Accelerated3-D CapacitanceExtraction Program[J]. IEEE Trans. Computer-Aided Design of IntegratedCircuits and Systems,1991,10(11):1447-1459.
    [95] Cao Y, Wang G. A Wideband and Scalable Model of Spiral Inductors UsingSpace-Mapping Neural Network[J]. IEEE Trans. Microwave Theory andTechniques,2007,55(12):2473-2480.
    [96]朱恒亮.纳米工艺集成电路的互连线寄生参数提取[D].复旦大学,2009:47-79.
    [97] L.P.P.P. van Ginneken. Buffer Placement in Distributed RC-tree Network forMinimal Elmore Delay[C].In Proceeding of IEEE International Symposium onCircuits and Systems, New Orleans, USA,1990:865-868.
    [98] Lillis J, Cheng C K, Lin T T Y. Optimal Wire Sizing and Buffer Insertion forLow Power and a Generalized Delay Model[J]. IEEE Journal of Solid-StateCircuits,1996,31(3):437-447.
    [99] Li Z, Sze C N, Alpert C J, Hu J and Shi W. Making Fast Buffer Insertion EvenFaster via Approximation Techniques[C]. Asia and South Pacific DesignAutomation Conference, Shanghai, China,2005:13-18.
    [100] Li Z and Shi W. An O(bn2) Time Algorithm for Optimal Buffer Insertion withb Buffer types[J]. IEEE Trans. Comp.-Aided Design of Integrated Circuits andSystems,2006,25(3):484-489.
    [101] Anahita B, Nasser M. Reducing Expected Delay and Power in FPGAs UsingBuffer Insertion in Single-Driver Wires[J]. Microelectronics Journal,2012,43(12):1038-1045.
    [102] Jiang Z, Hu S, Hu J, Li Z and Shi W. A New RLC Buffer InsertionAlgorithm[C]. IEEE International Conference on Computer Aided-Design,San Jose, USA,2006:553-557.
    [103] Khandelwal V, Davoodi A, Nanavati A, and Srivastava A. A ProbabilisticApproach to Buffer Insertion[C]. International Conference on Computer AidedDesign, San Jose, CA, USA,2003:560-567.
    [104] Tsai S H, Li M Y, Huang C Y. A Semi-Formal Min-Cost Buffer InsertionTechnique Considering Multi-Mode Timing Constraints[C]. DesignAutomation Conference Asia and South Pacific, Sydney, Austrilian,2012:505-510.
    [105] Wason V and Banerjee K. A Probabilistic Framework for Power-OptimalRepeater Insertion in Global Interconnects under Parameter Variations[C]. Int.Symp. Low Power Electron. Des., San Diego, USA,2005:131-136.
    [106] Mahalingam V and Ranganathan N. A Fuzzy Approach for Variation AwareBuffer Insertion and Driver Sizing[C]. IEEE Computer Society AnnualSymposium on VLSI, Montpellier, France,2008:329-334.
    [107] Xiong J and He L. Fast Buffer Insertion Considering Process Variations[C]. InProceedings of the2006international symposium on Physical design, SanJose, USA,2006:128-135.
    [108] Nalamalpu A, Srinivasan S, and Burleson W P. Booster for Driving Longon-Chip Interconnects: Design Issues, Interconnect Synthesis, andComparison with Repeaters[J]. IEEE Trans. on Computer-Aided Design ofIntegrated Circuits and Systems,2002,21(1):50-62.
    [109] Kusse E. Analysis and Circuit Design for Low Power Programmable LogicModules[D]. M.S. Thesis, UC Berkeley,1997:15-30.
    [110] Nakagome Y. Sub-1-V Swing Internal Bus Architecture for Future Low-PowerULSI[J]. IEEE Journal Solid-State Circuits,1993,28(4):414-419.
    [111] Colshan R and Jaroun B. A Novel Reduced Swing CMOS Bus InterfaceCircuit for High Speed Low Power VLSI Systems[C]. IEEE InternationalSymposium on Circuits and Systems, London, UK,1994:351-354.
    [112] Nor M M, Gordon R, Chester E. Design and Analysis of Low-Swing DriverScheme for Long Interconnects[J]. Microelectronics Journal,2011,42(9):1039-1048.
    [113] Paci G, Bertozzi D, Benini L. Effectiveness of Adaptive Supply Voltage andBody Bias as Post-Pilicon Variability Compensation Techniques forFull-Swing and Low-Swing on-Chip Communication Channels[C]. Design,Automation&Test in Europe Conference&Exhibition, Nice, France,2009:1404-1409.
    [114] Venkatraman V and Burleson W. An Energy-Efficient Multi-Bit QuaternaryCurrent Mode Signaling for on-Chip Interconnects[C]. Proc. Custom Integr.Circuits Conference, San Jose, USA,2007:301-304.
    [115] Dave M, Shojai M, and Sharma D. Energy-Efficient Current-Mode SignalingScheme for on-Chip Interconnects[C]. Asian Solid-State Conference, Beijing,China,2010:1-4
    [116] Katoch A, Ceendrick H, and Seevinck E. High Speed Current-Mode SignalingCircuits for on-Chip Wires[C]. IEEE Int. Symp. Circuits Syst., Kobe, Japan,2005:4138-4141.
    [117] Tabrizi M M, Masoumi N, Deilami M M. High Speed Current-ModesSiganling for Interconnects Considering Transmission Line and CrosstalkEffects[C]. Midwest Symp. on Circuits and Systems, Montreal, Canada,2007:17-20.
    [118] Cong J. An Interconnect-Centric Design Flow for Nanometer Technologies[J].Proceedings of the IEEE,2001,89(4):505-528.
    [119] Chou C, Marculescu R. FARM: Fault-Aware Resource Management inNoC-Based Multiprocessor Platforms[C]. Design, Automation&Test inEurope Conference&Exhibition, Grenoble, France,2011:1-6.
    [120] Wang C, Hu W, Lee S, Nader B. Area and Power-Efficient InnovativeCongestion-Aware Network-on-Chip Architecture[J]. Journal of SystemsArchitecture,2011,57(1):24-38.
    [121] Stan M R and Burelson W P. Bus Invert Coding for Low Power I/O[J]. IEEETrans. VLSI Systems,1995,3(1):49-58.
    [122] Hui G, Parameswaran S. Shifted Gray Encoding to Reduce InstructionMemory Address Bus Switching for Low-Power Embedded System[J]. Journalof Systems Architecture,2010,56(4):180-190.
    [123] Zhang Y, Lach J, Skadron K, and Stan M R. Odd/Even Bus Invert withTwo-Phase Transfer for Buses with Coupling[C]. Intl. Symp. On Low PowerElectronics and Design, Monterey, CA,2002:80-83.
    [124] Ji G, Hui G A. A Segmental Bus-Invert Coding Method for InstructionMemory Data Bus Power Efficiency[C]. Institute of Electircal and ElectronicsEngineers, Taipei, Taiwan,2009:137-140.
    [125] Benini L, Macii A, Macii E, Poncino M, and Scarsi R. Architectures andSynthesis Algorithms for Power-Efficient Bus Interfaces[J]. IEEE Trans. onComputer-Aided Design of Integrated Circuits and Systems,2000,19(9):969-980.
    [126] Satoshi K, Makoto I, and Kunihiro A. Bus Data Encoding with AdaptiveCode-Book Method for Low Power IP Base Desing[C]. InternationalWorkshop on IP Based Design and Synthesis, Grenoble, France,2000:77-81.
    [127] Babu G N, Brajesh K K, Anand B. Crosstalk Reduction Using Novel BusEncoders in Coupled RLC Modeled VLSI Interconnects[J]. Advances inComputer Science, Engineering&Applications,2012,166(5):735-744.
    [128] Yang J, Gupta R, and Zhang C. Frequent Value Encoding for Low Power DataBuses[J]. ACM Trans. on Design Automation of Electronic systems,2004,9(3):354-384.
    [129] Lv T, Wolf W, Henke J, and Lekatsas H. An Adaptive Dictionary EncodingScheme for SoS Data Buses[C]. Proceeding of DATE, Paris, France,2002:1059-1064.
    [130] Siamak M, Mahdi M, Rasul Y. Improved Weighted Code Mapping for Buseswith Non Unifrom Data Distribution[C]. International Design and TestWorkshop, Riyadh, Saudi Arabia,2009:1738-1742.
    [131] Shin Y, Choi K, and Chang Y H. Narrow Bus Encoding for Low Power DSPSystems[J]. IEEE Trans. on Very Large Scale Integration System,2001,9(5):656-660.
    [132] Brajesh K K, Verma S K, Balraj S. Encoding in VLSI Interconnects[M].Advances in Wireless, Mobile Networks and Application, Springer, Dubai,United Arab Emirates,2011:260-269.
    [133] Lekatsa H, and Henkel J. ETAM++: Extended Transition Activity Measure forLow Power Address Bus Designs[C]. ASP-DAC, Bangalore, India,2002:113-120.
    [134]北京大学数学系几何与代数教研室代数小组.高等代数第二版[M].北京:高等教育出版社,1988:296-305.
    [135] Golub G H and Can Loan C F. Matrix Computations[M]. Baltimore: JohnsHopkings Universtiy Press,2013:90-130.
    [136] Nigussie E E. Variation Tolerant on-Chip Interconnects[M]. New York:Spring-Verlag,2008:368-522.
    [137] Rosa C S, Boris L, Rudy E. Stability Preservation in Projection-based ModelOrder Reduction of Large Scale Systems[J]. European Journal of Control,2012,18(2):122-132.
    [138] Freund R W. Krylov-Subspace Methods for Reduced Order Modeling inCircuits Simulation[J]. Journal Comput. Appl. Math.,2000,123(2):395-421.
    [139] Weile D S, Michielssen E, Grimme E, Gallivan K. A Method for GeneratingRational Interpolant Reduced Order Models of Two-Parameter LinearSystems[J]. Appl. Math. Lett.,1999,12(5):93-102.
    [140] L. Daniel, O. C. Siong, L. S. Chay, K. H. Lee, J. White. A MultiparameterMoment-Matching Model Reduction Approach for Generating GeometricallyParameterized Interconnect Performance Models[J]. IEEE Trans. Comput.Aided Des. Integr. Circuits Syst.,2004,23(5):678-693.
    [141] Biazar J, Ebrahimi H. Chebyshev Wavelets Approach for Nonlinear System ofVolterra integral equation[J]. Computers&Mathematics with Applications,2012,63(2):608-616.
    [142] Altan and M. Celik, Practical Considerations For Passive Reduction of RLCCircuits[C]. IEEE/ACM International Conference on Computer-Aided Design,San Jose, USA,1999:214-219.
    [143] Xiong J, Tam K, and He L. Buffer Insertion Considering Process Variations[C].In Proceedings of the Design, Automation and Test in Europe Conference andExhibition, Munich, Germany,2005:970-975.
    [144] Dave M, Jain M, Baghini M S, and Sharma D. A Variation TolerantCurrent-Mode Signaling Scheme for On-Chip Interconnects[J]. IEEETransaction on VLSI Systems,2013,21(2):342-353.

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