Net-Ordering for Optimal Circuit Timing in Nanometer Interconnect Design

1. Net-Ordering for Optimal Circuit Timing in Nanometer Interconnect Design M. Sc. work by Moiseev Konstantin Supervisors: Dr. Shmuel Wimer, Dr. Avinoam Kolodny

2. Ri-1 Ri Ri+1 Vcc Si Si+1 Vcc L Wi-1 Wi Wi+1 Ci-1 Ci Ci+1 Problem formulation • Minimize bus timing by ordering of wires and allocation of wire widths and inter-wire spaces • Total width of interconnect structure is given constant A • All wires have equal length L A

3. Motivation • Cross-capacitances between wires in interconnect structures have a major effect on circuit timing Wires 10 years ago – area capacitance was dominant Wires today – cross capacitance is dominant

4. Weak driver Case A Case B Strong driver Capacitive load Motivation • Relative order of wire drivers in a bus influences circuit timing Circuit timing is better in case B !

5. Delay model • Elmore approximation for delay together with - model equivalent circuit for wire • Miller factor assumed 1 for all wires • More general case will be discussed later Q: Is Elmore delay model good enough for state-of-the-art technology? A: Fitted Elmore Delay model gives up to 2% error in delay estimation

6. Objective functions Total sum of delays: Worst wire delay: Worst wire slack:

7. Agenda • Solution for total sum of delays objective function • Solution for worst delay objective function • Optimization of total sum of delays with cross talk • Delay uncertainty issue

8. Solution for total sum of delays caseconstant wire width • Differentiating function with respect to and area constraint and equating derivatives to zero, obtain: • Now assume all wires have predefined constant width and get: This property is preserved in all kinds of optimizations discussed

9. Solution for total sum of delays caseconstant wire width • Substitute obtained relations for spaces to objective function, simplify and obtain: Order-independent part Order-dependent part Order of wires is influenced by values of driver resistances only ! Question: Does optimal order exist ???

10. BMI order • Take wires sorted in descending order of drivers and put alternately to the left and right sides of the bus channel • Obtained permutation of wires called Balanced Monotonic Interleaved(BMI) order BMI order 7 6 5 4 3 2 1 BMI order provides best sharing of inter-wire spaces

11. Optimal order theorem • Define , where - non-decreasing monotonic function and - some permutation of -values • Theorem (optimal order):given a bus whose wires are of uniform width , the BMI order of signals in the bus yields minimum total sum of delays. • Proof : • Order-dependent part of is special case of -sum • Prove by induction that -sums are minimized by BMI permutation

12. Impedance matching • Balance the resistance of the driver and resistance of the driven line • Mathematically: • BMI still holds • Simple but practical case:

13. Solution for general case • In general case, wire widths are optimization variables • Derivatives with respect to : • Theorem (existence): For given set of wires , if for each pair of wires and with drivers and loads and respectively holds and , then optimal order of this set of wires is BMI, under total sum of wire delays objective function. • One special case: if all load capacitances are equal, then optimal order is always BMI

14. Generate all permutations of wires For each permutation solve sizing problem Find permutation giving minimum delay Complexity: exponential Number of optimization variables: Perform impedance matching by function with parameters (if needed) Arrange wires in BMI order Solve sizing problem Complexity: linear Number of optimization variables: or Minimizing total sum of delays - summary Straight forward solution : Our heuristic:

15. Results: total sum minimizationproblem demonstration on random problem instances • 20 sets of 5 wires • Rdr: [0.1 ÷ 2] KΩ (random) • Cl: [10 ÷ 200] fF (random) • Bus length: 600 μm • Bus width: 12 μm • Technology: 90 nm

16. Results: total sum minimizationbus width influence • Set of 6 wires • Rdr: [0.1 ÷ 2] KΩ (random) • Cl: 10 fF • Bus length: 600 μm • Technology: 90 nm

17. Results: total sum minimizationinterleaved bus • Set of 7 wires • Rdr: 0.1KΩ and 1.9 KΩ • Cl: 50 fF and 5 fF • Bus length: 600 μm • Bus width: 15 μm • Technology: 90 nm

18. Results: total sum minimizationcomparison of heuristics on random problem instances Exhaustive search best delay Exhaustive search worst delay 16.54% 0.63% 100% 0.76% 12.60% 0.63% 16.39% 0.07% 11.28% 9.60% 0.21% 14.10% 0.20% 1st heuristic 0.42% 14.10% Average: 2nd heuristic

19. Agenda • Solution for total sum of delays objective function • Solution for worst delay objective function • Optimization of total sum of delays with cross talk • Delay uncertainty issue

20. Solution for minmax case • The goal: minimizing maximum wire delay (or slack) • Function is not differentiable • All wires have the same delay (S. Michaely et al.) • Assumptions: • wire width is convex monotonic decreasing in driver resistance (impedance matching) • Drivers and loads satisfy existence theorem

21. Solution for minmax case • Supposition: In minimization of maximum wire delay, optimal order of wires is BMI • Under assumptions of previous slide delay expression can be written as: • Edge effects (S. Michaely et. al) can break down optimality of BMI

22. Results: minmax optimizationbus width influence • 20 sets of 5 wires • Rdr: [0.1 ÷ 2] KΩ (random) • Cl: [10 ÷ 200] fF (random) • Bus length: 600 μm • Technology: 90 nm

23. 20 sets of 5 wires Rdr: [0.1 ÷ 2] KΩ (random) Cl: [10 ÷ 200] fF (random) Bus width: 12 μm Technology: 90 nm Results: minmax optimizationbus length influence

24. Results: minmax optimizationinterleaved bus • Set of 7 wires • Rdr: 0.1KΩ and 1.9 KΩ • Cl: 50 fF and 5 fF • Bus length: 600 μm • Bus width: 15 μm • Technology: 90 nm

25. Agenda • Solution for total sum of delays objective function • Solution for worst delay objective function • Optimization of total sum of delays with cross talk • Delay uncertainty issue

26. Crosstalk issue • So far: we assumed Miller factor 1 • In practice: can be 0, 1 or 2 • Introducing Miller factor changes wire delay equation: • The solution will be different according to three cases: • Miller factor is equal for all pairs of wires • Miller factor different only near walls • Each pair of wires has its own different Miller factor

27. 1st case: uniform Miller factor • The order-dependent part of objective function is given as: • When all Miller coefficients are equal, above expression changes to: • Conclusion: • Uniform Miller factor doesn’t affect functional form of delay function and therefore optimal order will be BMI • Impact of wire ordering emphasized even more

28. 2nd case: almost uniform Miller factor • All Miller coefficients in internal inter-wire spaces are equal to • Miller coefficients near the walls are • Order-dependent part of objective function can be written as: • BMI order remains optimal if • In other cases order is monotonic but not always BMI • Minmax optimization gives the same results

29. 3rd case: non-uniform Miller factor Miller coefficients can be presented by the matrix Minimization problem then is equivalent to : Where and • Proved to be NP-complete (A. Vittal et al.)

30. Agenda • Solution for total sum of delays objective function • Solution for worst delay objective function • Optimization of total sum of delays with cross talk • Delay uncertainty issue

31. Peak noise Delay uncertainty Delay uncertainty issue • Due to difference in arrival times of signals transmitted by neighbor wires, crosstalk noise is created • Crosstalk noise is characterized by two main parameters: peak noise and delay uncertainty • Maximum delay uncertainty for a signal in a bus can be expressed as follows: (A. Vittal et al., T. Sato et al.)

32. Minimization of delay uncertainty • Define new objective functions: • Total sum of delay uncertainties: • Worst delay uncertainty: • Experiments show that BMI order leads to minimizing both and

33. Results: minimization of delay uncertainty Total sum • 20 sets of 5 wires • Rdr: [0.1 ÷ 2] KΩ (random) • Cl: [10 ÷ 200] fF (random) • Bus length: 600 μm • Bus width: 15 μm • Technology: 90 nm Minmax • Average improvement: • Total sum of delay uncertainties: about 27 % • Worst delay uncertainty: about 43%

34. Monotony in ordering optimizations • Monotony is most important property of solutions of ordering optimization problems • Total sum of delays: optimal order is monotonic, BMI • Maximum delay: optimal order is monotonic, BMI • Optimization with crosstalk: optimal order is monotonic • Delay uncertainty optimization: optimal order is monotonic, BMI • Generally, all above problems can be solved on cyclic bus and obtained optimal order will be monotonic • BMI and other monotonic orders are special cases and defined by edge conditions only

35. Conclusions • Problem of optimal simultaneous wire sizing and ordering was presented and solved • Effects of crosstalk on nominal delays and delay uncertainty are examined • Monotonic ordering according to driver strength is shown to be advantageous for the various objective functions • Examples for 90-nanometer technology are analyzed and discussed