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Maze Routing with Buffer Insertion and Wire sizing. Minghorng Lai , D.F. Wong DAC 2000. Elmore delay model. Elmore delay model. R wire =1.2 C wire =2.4F. Elmore delay model. R wire =1.2 C wire =2.4F R buffer =0.2 C buffer =1F. t. s. Problem. Solution. Previously Proposed Methods
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Maze Routing with Buffer Insertion and Wire sizing Minghorng Lai , D.F. Wong DAC 2000
Elmore delay model Rwire=1.2 Cwire=2.4F
Elmore delay model Rwire=1.2 Cwire=2.4F Rbuffer=0.2 Cbuffer=1F
t s Problem
Solution • Previously Proposed Methods • Dynamic programming • Waste time and space • With wire sizing, the sizes of the sub-solution sets for dynamic programming increase significantly. • Proposed method • Shortest Path Formulation • Time :O(|V|2log(|V|)) • Space:O(|B|2|V|2)
u t sb-1 tb-1 s Graph G={V,E} SP Graph BG ={VBG,EBG} x v Shortest Path Formulation
Step 1.Compute shortest distance Step 2.Create new vertices and edges Step 3.Assign every edges’ weight Shortest Path Formulation Wire sizing Construct SP Graph Find the shortest path from source to sink
Step 1.Compute shortest distance Step 2.Create new vertices and edges Step 3.Assign every edges’ weight Shortest Path Formulation • Construct SP Graph
v u Shortest Path Formulation Step 2.Create new vertices & edges Buffer Library B={b0,b1} vb0 ub0 vb1 ub1
u s t bo bo bo bo bo b1 b1 b1 b1 b1 x v Shortest Path Formulation Step 2.Create new vertices & edges t u s v x Graph G={V,E}
sb-1 tb-1 Shortest Path Formulation Step 2.Create new vertices & edges • Add pseudo node sb-1 & tbi-1 SP Graph
Step 1.Compute shortest distance Step 2.Create new vertices and edges Step 3.Assign every edges’ weight Step 4.Find the shortest path from source to sink Shortest Path Formulation
h1 h2 bi bj h3 hn l1 l2 l3 ln Shortest Path Formulation Step 3.Assign every edges’ weight • C. Chu and D. F.Wong, “ A New Approach to Simultaneous Buffer Insertion and Wire Sizing," IEEE Trans. on CAD, 1997 • use (bi, bj, d(u, v)) as index to check look-up table d(u, v)
Step 1.Compute shortest distance Step 2.Create new vertices and edges Step 3.Assign every edges’ weight Shortest Path Formulation Step 4.Find the shortest path from source to sink
Shortest Path Formulation • Time Complexity • Shortest path O(|VGV|log|VGV|) • at most |B||V| new vertices are created in the BP-Graph • Space Complexity • O(|VBG|2)=>O(|B|2|V|2).
DP-Routing SP-Routing Name Memory(Mb) Time(s) Memory(Mb) Time(s) Experimental Results SRL1 SRL2 SRL3 SRL4 SRL5 SRL6 SRL7 SRL8 SRL9 SRL10 2.88 2.71 2. 3.09 3.08 2.69 2.82 2.88 2.85 3.48 741 919 827 1044 1306 961 969 767 868 1243 0.524 0.318 0.355 0.740 0.672 0.572 0.767 0.384 0.479 0.869 35.3 18.2 19.5 51.0 60.2 38.1 46.1 25.5 22.6 71.0
Conclusion • The lookup-table construction only needs to be done once and can be reused in multi-net maze routing. • congestion avoidance