Mehboob Alam

Rice University, Houston, Texas, United States

Are you Mehboob Alam?

Claim your profile

Publications (6)0.79 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: The efficient modeling of integrated passive components and interconnects is vital for the realization of high performance mixed-signal systems. In this paper, we develop a dynamic multi-point rational interpolation method based on Krylov subspace techniques to generate reduced order models for passive components and interconnects that are accurate across a wide-range of frequencies. We dynamically select interpolation points by applying a cubic spline-based algorithm to detect complex regions in the system's frequency response. The results indicate that our method provides greater accuracy than techniques that apply uniform interpolation points.
    Analog Integrated Circuits and Signal Processing 01/2007; 50(3):273-277. · 0.55 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Model order reduction plays a key role in determining VLSI system performance and the optimization of intercon- nects. In this paper, we develop an accurate and provably passive method for model order reduction using adaptive wavelet-based frequency selective projection. The wavelet- based approach provides an automated means to generate low order models that are accurate in a particular range of frequencies. Theresults indicatethatourapproachprovides more accurate reduced order models than the spectral zero method with uniform interpolation points and the zero-shift and multi-shift Block Arnoldi-based techniques. In this paper, we develop an adaptive, passivity preserv- ing methodology for the selection of interpolation points in spectral zero-based model order reduction. We dynamically select expansion points by applying Haar wavelets to de- tect complex changes in the frequency points spanned by the spectral zeros of the system and select the dominant interpolation points. The adaptive scheme provides a low order realization with optimized matching of the system re- sponse for a given range of frequencies. The preservation of passivity is guaranteed by selecting interpolation points as a subset of the system's spectral zeros. The approximate low-order model can then be directly constructed from the projection matrices derived from these interpolants. In or- der to demonstrate the efficiency of the approach, we ap- ply our technique to an RLC network representing an in- terconnect wire. The results indicate that the wavelet-based method provides higher accuracy approximate models than techniques based on moment matching and uniform inter- polation point selection.
    8th International Symposium on Quality of Electronic Design (ISQED 2007), 26-28 March 2007, San Jose, CA, USA; 01/2007
  • [Show abstract] [Hide abstract]
    ABSTRACT: As process technology continues to scale into the nanoscale regime and the overall system complexity increases, the reduced order modeling of on-chip interconnect plays a crucial role in determining VLSI system performance. In this paper, we develop an adaptive wavelet interpolation method based on Krylov subspace techniques to generate reduced order interconnect models that are accurate across a wide-range of frequencies. We dynamically select interpolation points by applying an inexpensive Haar wavelet and performing irregular sampling in the frequency domain. The results indicate that our method provides greater accuracy than multi-shift Krylov subspace methods with uniform interpolation points.
    Journal of Circuits System and Computers 01/2007; 16:699-709. · 0.24 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In the paper, we develop a systematic methodology for modeling sampled interconnect frequency response data based on spline interpolation. Through piecewise polynomial interpola- tion, we are able to avoid the numerical problems associated with global polynomial fitting and generate higher order systems to model simulated or measured wideband frequency response data. We reduce the complexity of the generated systems using a data point pruning algorithm and by applying model order reduction based on balanced truncation. The methodology provides sub- stantially greater accuracy than global polynomial approximation while only having O(n) growth in model complexity.
    Proceedings of the 12th Conference on Asia South Pacific Design Automation, ASP-DAC 2007, Yokohama, Japan, January 23-26, 2007; 01/2007
  • [Show abstract] [Hide abstract]
    ABSTRACT: As process technology continues to scale into the nanoscale regime, interconnect plays an ever increasing role in determining VLSI system performance. As the complexity of these systems increases, reduced order modeling becomes critical. In this paper, we develop a new method for the model order reduction of interconnect using frequency restrictive selection of interpolation points based on the spectral-zeros of the RLC interconnect model's transfer function. The methodology uses the imaginary part of spectral zeros for frequency selective projection and provides stable as well as passive reduced order models for interconnect in VLSI systems. For large order interconnect models with realistic RLC parameters, the results indicate that our method provides more accurate approximations than techniques based on balanced truncation and moment matching with excellent agreement with the original system's transfer function.
    Proceedings of the 12th Conference on Asia South Pacific Design Automation, ASP-DAC 2007, Yokohama, Japan, January 23-26, 2007; 01/2007
  • [Show abstract] [Hide abstract]
    ABSTRACT: As process technology continues to scale into the nanoscale regime and overall system complexity increases, the reduced order modeling of on-chip interconnect plays a crucial role in characterizing VLSI system performance. In this paper, we develop a dynamic multi-point rational interpolation method based on Krylov subspace techniques to generate reduced order interconnect models that are accurate across a wide-range of frequencies. We dynamically select interpolation point by applying a cubic spline-based algorithm to detect complex regions in the system's frequency response. The results indicate that our method provides greater accuracy than techniques that apply multi-shift Krylov subspace methods with uniform interpolation points
    Design, Applications, Integration and Software, 2006 IEEE Dallas/CAS Workshop on; 11/2006