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A Methodology for Interconnect Dimension Determination. By: Jeff Cobb Rajesh Garg Sunil P Khatri Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX-77840. Outline. Introduction Previous Work Objective Approach Cross-bar Bandwidth (CBB)
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A Methodology for Interconnect Dimension Determination By: Jeff Cobb Rajesh Garg Sunil P Khatri Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX-77840
Outline • Introduction • Previous Work • Objective • Approach • Cross-bar Bandwidth (CBB) • Power-adjusted CBB • Experimental Results • Conclusions
Introduction • New fabrication process development • Width • Spacing • Height • Inter-layer heights • Traditionally, fabrication team determines these values, and design team uses the values • This may lead to sub-optimal design
Introduction • Minimum dimension wires lead to increased scale of integration. However… • This leads to a large number of wires • Inter-wire parasitic capacitance may increase • Overall circuit speed may decrease • Increasing inter-layer dielectric heights • Reduces capacitance between wires • Increases via resistance and reduces via reliability • Recently, wire delay dominates the logic delay • Hence the problem of interconnect sizing is important
Introduction • Design team would provide several sets of acceptable wiring dimensions • Fabrication team selects the set which maximizes both yield and manufacturability • This process may be iterated. • Designers need some metrics to come up with the sets of wiring dimensions • We propose two metrics to guide the process of selecting wiring dimensions
Previous Work • Analytical Methods • Simplifying assumptions need to be made • Deodhar et. al. assume that grounding wires on present on either side of an interconnect • Davis et. al. considered stochastic interconnect distribution to compute interconnect sizing which minimizes power consumption • Li et. al. proposed metrics only for global interconnect optimization • Only wire width and spacing are considered
Objective • Optimal wiring configuration depends upon several non-linear parameters • A closed form model is not feasible • Want to develop metrics that model delay and power of any interconnect configuration • Cross-bar bandwidth (CBB) • Power-adjusted cross-bar bandwidth (PCBB) • Should be applicable to any interconnect layer
Approach - overview • Define two metrics -- CBB and PCBB • Extract resistance and capacitance for various wiring configurations • Evaluate CBB and PCBB for different wiring configurations • Vary wire height, width, spacing and inter-layer dielectric in a feasible range • Select the optimal wiring configuration empirically
Approach • Cross-bar bandwidth • Bandwidth of a wire times the number of wires in an average size rectangle • Higher CBB value implies higher maximum data transfer rate • Power-adjusted CBB • Weighted sum of CBB and power consumption of interconnects in a rectangular area • We perform sizing of METAL1 through METAL4 conductors • However, this approach can be used for any metal layer
Approach • Interconnect dimensions used in our study
Approach • Wiring configuration for METAL1 and METAL2 • Similar configuration is used for METAL3 and METAL4
Approach • To evaluate CBB or PCBB for any metal layer i, we need their average length li • Placed and routed several MCNC circuits • Average length li
Cross-bar Bandwidth • Consider a rectangle of size l1 by l2 • Via resistance: • Elmore delay where: c1 & c2 are extracted per unit length capacitances • CBB
Power-adjusted CBB • Charging current • Assume • Total power consumption • PCBB
CBB & PCBB with Rdriver • Including driver resistance Rdriver • Elmore delay • CBB with driver included • PCBB with driver included
Experimental Results • Extracted wire capacitances for 70nm process using SPACE 3D-capacitance extractor • Computed CBB and PCBB (for a = 0.4) for several wiring configurations METAL1 and METAL2 Parameters METAL3 and METAL4 Parameters
METAL1 & METAL2 - CBB • CBB for all parameter variation • Order of variation: • w12 • s12 • L2 • L1 • h 12 L1 has no effect on CBB therefore, select its lowest value i.e. 200nm
METAL1 & METAL2 - CBB • Varying: • w12 • s12 • L2 For L1=200nm Optimal Values w12 = 140nm s12 = 100nm CBB is maximum for w12 = 140nm CBB is maximum for s12 = 100nm
METAL1 & METAL2 - CBB • Vary h12 for optimal values of w12, s12 and L1 and a fixed value of L2 CBB is maximum for h12 = 300nm
METAL1 & METAL2 - CBB • Vary L2 for optimal values of w12 , s12,L1 and h12 • Optimal value of L2 is 200nm CBB is maximized for smallest value of L2
METAL1 & METAL2 - PCBB • For a = 0.4 PCBB is maximum
Optimal Sizing • For METAL1 and METAL2 • For METAL3 and METAL4
CBB and PCBB Improvement • For METAL1 and METAL2 optimal sizing yield • 12.94% increase in CBB • 19.29% in PCBB • METAL3 and METAL4 • 16.5% increase in CBB • 17.15% increase in PCBB
Optimal Sizing • For METAL1 and METAL2 with driver resistance • For METAL3 and METAL4 with driver resistance
CBB and PCBB Improvement • For METAL1 and METAL2 with driver resistance • For METAL3 and METAL4 with driver resistance • For 300 ohm drivers, the improvements are 31.7% and 68.9% (CBBdriver and PCBBdriver respectively) • Improvements for other resistance values are similar, and reported in the paper.
Conclusions • Optimal wiring configuration depends upon several parameters therefore, closed form model is not feasible • We proposed 2 metrics for wire sizing i.e. CBB and PCBB which account for delay and power • Without considering driver resistance, our approach yields up to 16% improvement in CBB and 19% improvement in PCBB • With driver resistance, the percent improvement is even higher