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Performance and RLC Crosstalk Driven Global Routing

Performance and RLC Crosstalk Driven Global Routing. Ling Zhang, Tong Jing, Xianlong Hong, Jingyu Xu Jinjun Xiong, Lei He Dept. of CST, Tsinghua Univ Dept. of EE, UC, Los Angeles. Speaker: Xianlong Hong. Outline. Introduction & Previous Work

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Performance and RLC Crosstalk Driven Global Routing

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  1. Performance and RLC Crosstalk Driven Global Routing Ling Zhang, Tong Jing, Xianlong Hong, Jingyu Xu Jinjun Xiong, Lei He Dept. of CST, Tsinghua Univ Dept. of EE, UC, Los Angeles Speaker: Xianlong Hong

  2. Outline • Introduction & Previous Work • Problem Formulations • Our Algorithm: PO-GR • Experimental Results & Discussions • Conclusions ISCAS 2004, Vancouver, Canada

  3. Introduction • Device size shrinking and clock frequency increasing • Coupling capacitance and inductance could not be ignored • Longer delay and crosstalk caused by coupling effects • Global routing with performance optimization becomes more important. ISCAS 2004, Vancouver, Canada

  4. Previous Work(1) • Noise modeling • Sakurai model (T. Sakurai, C. Kobayashi, M. Node, 1993) • LSK model for calculating coupling inductance (L. He, K. M. Lepak, 2000) • Model for calculating noise voltage (K. M. Lepak, I. Luwandi, L. He, 2001) ISCAS 2004, Vancouver, Canada

  5. Previous Work(2) • Noise minimization • Spacing in detailed routing phase (K. Chaudhary, A. Onozawa et al, 1993) • Track permutation in detailed routing phase (T. Gao, C. L. Liu, 1996) • Wire perturbation in detailed routing phase (P. Saxena, C. L. Liu, 1999) • Crosstalk reduction after global routing phase (T. X. Xue, E. S. Kuh, D. F. Wang, 1997) (J. J. Xiong, J. Chen, J. Ma, L. He, 2002) • Coupling capacitance crosstalk reduction in global routing phase (J. Y. Xu, T. Jing, X. L. Hong, L. Zhang, 2004, ASP-DAC) ISCAS 2004, Vancouver, Canada

  6. Major Contributions • An efficient crosstalk elimination algorithm based on Tabu search and shielding technology is proposed. • Timing performance and routability are simultaneously considered at global routing level. • By using LSK model, we take coupling inductance into consideration. ISCAS 2004, Vancouver, Canada

  7. Outline • Introduction & Previous Work • Problem Formulations • Our Algorithm: PO-GR • Experimental Results & Discussions • Conclusions ISCAS 2004, Vancouver, Canada

  8. e GRC 1 GRG v v 1 2 Problem Formulations(1)—Global Routing Problem Fig.1 Global Routing Graph(GRG) ISCAS 2004, Vancouver, Canada

  9. K 1 g(j) kij f(i) Wire order Nj gr gl Ni Problem Formulations(2)—LSK Model Accurate calculation: Simplified calculation in LSK model: Kit for segment of net i in region t: (for all j sensitive to i) LSK, the total K value for net i: (for all t occupied by net i) Fig.2 LSK Model ISCAS 2004, Vancouver, Canada

  10. Problem Formulations(3)—Tabu Search Outline: Step1. Select an initial solution xnow, and set Tabu list H=empty; Step2.While not meet the stop conditions do Generate a candidate list Can_N(xnow) from the neighborhood N(xnow,H) of xnow that doesn’t conflict with H; Select the best solution from Can_N(xnow):xnext; xnow=xnext; Update Tabu list H; End While Key factors: neighborhood Tabu object & Tabu length aspiration rule How to search efficiently How to choose properly How to set the reasonably ISCAS 2004, Vancouver, Canada

  11. Outline • Introduction & Previous Work • Problem Formulations • Our Algorithm: PO-GR • Experimental Results & Discussions • Conclusions ISCAS 2004, Vancouver, Canada

  12. Our Algorithm: PO-GR—(1) • Part 1: timing performance and routability • Part 2: Crosstalk estimation and elimination • Part 1 firstly generates an initial routing solution considering congestion and timing optimization • Then, Part 2 eliminates the crosstalk from the solution by inserting shields and gets a mid-result • Finally, regard the mid-result as input and send it to Part 1 for iterations ISCAS 2004, Vancouver, Canada

  13. Our Algorithm: PO-GR—(2) CallPart 1to generate a minimum wire length initial solution X0without congestion and timing violation; CallPart 2to obtainX1 = CEE(X0); If no edge overflow inX1then go to4.; Else do go back to1.to generate a new solution; Call Part 1again to obtain congestion and timing optimized solutionX2from X1; 1. 2. CEE 3. 4. Fig.3 flow chart of PO-GR pseudo code of PO-GR ISCAS 2004, Vancouver, Canada

  14. Part 2—CEE partition the LSK bound at each sink of a net into the GRG edges belonging to the source-sink paths. Insert shield with specific method Check each net to eliminate possible remnant crosstalk and delete unnecessary shields to minimize total area. Fig.4 flow chart of CEE ISCAS 2004, Vancouver, Canada

  15. Crosstalk Elimination Based on Tabu Search(1) Simulated Annealing, or Tabu search? The runtime of Simulated Annealing could be very long, while with similar performance, Tabu search is much faster. ISCAS 2004, Vancouver, Canada

  16. xcur: current solution; xnew: candidate in neighborhood of xcur; xtmp: best candidate; xmin: best solution ever reached; Na: maximum iteration times with no improvement; Nb: number of candidates selected from neighborhood; Nc: maximum trying times for searching one candidate; randommove(x): method of generate a candidate in neighborhood of x; cost(x): evaluation of solution x; Set the global solution in one GRG edge as initial solution xcur; Set Tabu list H=empty; a=0; c=0; While( a < Na ) tmpcost = ; b = 0; While (b < Nb ) xnew = xcur; randommove ( xnew ); Ifcost (xnew) is in H c++; If c < Nc, then continue; Else c = 0; Ifcost (xnew) < tmpcost, then xtmp = xnew; tmpcost = cost (xnew); b++; End While Insert xcur into H; xcur= xtmp; Ifcost (xcur) < cost (xmin), thenxmin = xcur; a = 0; Else a++; UpdateH; End While ISCAS 2004, Vancouver, Canada

  17. Crosstalk Elimination Based on Tabu Search(2) cost(x)=w1*c1 + w2*c2 + w3*c3 + w4*c4 randommove(x): { swap two net randomly, move one net randomly, insert one shield randomly, remove one shield randomly } c1: total number of nets that are adjacent to their sensitive nets; c2: total number of shields in a GRG edge; c3: summation of (Keff- Kth) for all nets with Keff > Kthin a GRG edge; c4: total number of nets with (Keff > Kth) in a GRG edge. ISCAS 2004, Vancouver, Canada

  18. Outline • Introduction & Previous Work • Problem Formulations • Our Algorithm: PO-GR • Experimental Results & Discussions • Conclusions ISCAS 2004, Vancouver, Canada

  19. Benchmark Data Technology: 0.2um Sensitivity rate: 0.5 for all nets and sensitivity matrix is random. LSK bound:1000 at each sink ISCAS 2004, Vancouver, Canada

  20. Experimental Results(1) Comparison of runtime(s) between Tabu search and Simulate Annealing ISCAS 2004, Vancouver, Canada

  21. Experimental Results(2) Comparison of results between Tabu search and Simulated Annealing ISCAS 2004, Vancouver, Canada

  22. Experimental Results(3) Comparison of results between P1 and PO-GR ISCAS 2004, Vancouver, Canada

  23. Discussions • Tabu search sharply decreases the runtime of step2 in CEE(about 20x speedup), and doesn’t make any bad effects on step3 in CEE(its runtime slightly decreases too). • Tabu search can obtains similar results in routing area compared with SA method,while the shielding number only increases a little. • Tabu search achieve 2.5x wire length reduction compared with SA. • PO-GR keeps the effectiveness in timing optimization. ISCAS 2004, Vancouver, Canada

  24. Outline • Introduction & Previous Work • Problem Formulations • Our Algorithm: PO-GR • Experimental Results & Discussions • Conclusions ISCAS 2004, Vancouver, Canada

  25. Conclusions PO-GR is able to: • Take coupling inductance into consideration. • Tackle coupling noise, timing performance and routability simultaneously. • Efficiently eliminate crosstalk throughout the global routing phase by inserting shields and has little influence on wire length and timing performance. • Preserve the good routing result and greatly decrease the running time. ISCAS 2004, Vancouver, Canada

  26. THANK YOU ISCAS 2004, Vancouver, Canada

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