1 / 18

An Impulse-Response Based Methodology for Modeling Complex Interconnect Networks

Investigate the response of on-chip interconnect networks to RF interference and internal coupling using an impulse-response based methodology. The methodology combines unit-cell simulation with linear time-invariant systems to model complex networks. It offers computational advantages and flexibility for exploring different input distributions.

hollyhenry
Télécharger la présentation

An Impulse-Response Based Methodology for Modeling Complex Interconnect Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. An Impulse-Response Based Methodology for Modeling Complex Interconnect Networks Zeynep Dilli, Neil Goldsman, Akın Aktürk Dept. of Electrical and Computer Eng. University of Maryland, College Park ISDRS 2005

  2. Interconnect Network Modeling • Objective: Investigate the response of a complex on-chip interconnect network to external RF interference or internal coupling between different chip regions • Full-chip electromagnetic simulation: Too computationally-intensive • Full-wave simulation possible for small “unit cell”s: Simple seed structures of single and coupled interconnects, combined to form the network. • We have developed a methodology to solve for the response of such a network composed of unit cells with random inputs. Sample unit cells for a two-metal process

  3. Interconnect Network Modeling • On-chip interconnects on lossy substrates: capacitively and inductively coupled to each other • Characterized with S-parameter measurements • Equivalent circuit models found by parameter-fitting • For small interconnect unit cells, create an equivalent circuit model from EM simulation results/S-parameters.

  4. Interconnect Network Modeling • The interconnect network is a linear time invariant system: It is straightforward to calculate the output to any input distribution in space and time from the impulse responses.

  5. Response to a General Input from Impulse Responses f[x,t] 1, x=xi [x-xi]= Define the unit impulse at point xi: 0, else We calculate the system’s impulse response: hi[x,t] [x-xi][t] Let an input f[x,t] be applied to the system. This input can be written as the superposition of time-varying input components fi[t]=f[xi,t] applied to each point xi: We can write these input components fi[t] as Writing fi[t] as the sum of a series of time-impulses marching in time:

  6. Response to a General Input from Impulse Responses f[x,t] Let Fi[x,t] be the system’s response to this input applied to xi: fi[t] Fi[x,t] For a time-invariant system we can use the impulse response to find Fi[x,t] : Then, since

  7. Response to a General Input from Impulse Responses

  8. The Computational Advantage • Choose a spatial mesh and a time period • Calculate the impulse response over all the period to impulse inputs at possible input nodes (might be all of them) • The input values at discrete points in space and time can be selected randomly, depending on the characteristics of the interconnect network (coupling, etc.) and of the interference. Let • Then we can calculate the response to any such random input distribution αijby only summation and time shifting • We can explore different random input distributions easily, more flexible than experimentation

  9. A Demonstration • Goal: Simulate response at Point F3 to a discrete-time input given by the sum of two impulses at Point 2 and two at Point 5:

  10. A Demonstration • Theoretically, the response at point F3 to this input is obtainable by the time-shifted sum of scaled impulse responses: • Calculate this analytically from the simulated impulse responses and compare with simulation result

  11. A Demonstration

  12. A Demonstration

  13. Sample 2-D and 3-D Networks Only 5x5 mesh shown for simplicity. All nodes connected resistively to neighbors and with an R//C to ground. Only 5x5x2 mesh shown for simplicity. Not all vertical connections shown. All nodes on the same level connected resistively to neighbors. All nodes on lowest level are connected with an R//C to ground. All nodes in intermediary levels are connected with an R//C to neighbors above and below.

  14. Impulse Response Solver Solves for the response over the mesh using a system of differential equations derived from KCL equations. Given here: Results for a 11x11x5 mesh. Input points:(1,1,1) (bottom southwest corner), (6,6,3) (exact center), (11,11,5) (top northeast corner). Sample output points(4,4,2) (2nd layer, southwest of center); (8,8,4) (4th layer, northeast of center).

  15. Impulse Response Solver Impulse response over all five layers: Impulse at (1,1,1) Impulse at (6,6,3)

  16. Impulse Response Solver Impulse response vs. time at output points (4,4,2) and (8,8,4).

  17. Impulse Response Solver Input waveform (composite of three inputs) and output waveform (composite of timeshifted/summed impulse responses).

  18. Conclusion • Developing a method to model and investigate the response of a complex on-chip interconnect network to external RF interference or to internal coupling between different chip regions or subcircuits. • Computational advantages: • Impulse responses calculated once yield the system response to many inputs; • Impulse responses at only the desired points in the system need to be stored to calculate the output at those points for any input waveform; • The same unit cells can be combined for many interconnect layouts; • It is straightforward to expand the method to three-dimensional networks.

More Related