As the IC devices is scaled into nanometer dimen- sions and operates in giga-hertz frequencies, interconnect design and optimization have become critical in determining the system performance and reliability.

This paper presents an efficient approach to perform global interconnect sizing and spacing (GISS) for multiple nets to minimize interconnect delays with consideration of coupling capacitance, in addition to area and fringing capacitances. We introduce the formulation of symmetric and asymmetric wire sizing and spacing. We prove two important results on the symmetric and asymmetric effective-fringing properties which leadtoavery effective bound computation algorithm to compute the upper and lower bounds of the optimal wire sizing and spacing solution for all nets under consideration. Our experiments show that in most cases the upper and lower bounds meet quickly after a few iterations and we actually obtain the optimal solution. To our knowledge, this is the first in-depth study of global wire sizing and spacing for multiple nets with consideration of coupling capacitance. Experimental results show that our GISS solutions lead to substantial delay reduction than existing single net wire-sizing solutions without consideration of coupling capacitance.

This paper presents a set of interconnect performance estimation models for design planning with consideration of various effective interconnect layout optimization techniques, including optimal wire sizing, simultaneous driver and wire sizing, and simultaneous buffer insertion/sizing and wire sizing. These models are extremely efficient, yet provide high degree of accuracy. They have been tested on a wide range of parameters and shown to have over 90% accuracy on average compared to running best-available interconnect layout optimization algorithms directly. As a result, these fast yet accurate models can be used efficiently during high-level design space exploration, interconnect-driven design planning/synthesis, and timing-driven placement to ensure design convergence for deep submicrometer designs.

In this paper, we formulated a new class of optimization problem, named the general CH-posynomial program, which is more general than the simple and bounded-variation CH-posynomial programs in [1]. We revealed the general dominance property so that an efficient and unified algorithm based on the local refinement (LR) operation can be used to optimize the simple, bounded-variation and general CH-posynomial programs. We applied the LR-based optimization algorithm to solve the device sizing problem using accurate table-based model, and the wire sizing and spacing problem with consideration of coupling between multiple nets. Both problems are solved in the context of simultaneous device and wire sizing optimization for deep submicron designs. Experiments show that our LR-based optimization algorithm is very effective and extremely efficient. Up to 16.5% delay reduction is observed when compared with previous work based on the simple device model [1], and up to 31% delay reduction and 100x speedup is observed when compared the global interconnect sizing and spacing work [2]. We believe that our general CH-posynomial formulation and LR-based algorithm can also be applied to other optimization problems in the CAD field.

In this paper we formulate three classes of optimization problems: the simple, monotonically constrained, and bounded Cong-He (CH)-programs. We reveal the dominance property under the local refinement (LR) operation for the simple CH-program, as well as the general dominance property under the pseudo-LR operation for the monotonically constrained CH-program and the extended-LR operation for the bounded CH-program. These properties enable a very efficient polynomial-time algorithm, using different types of LR operations to compute tight lower and upper bounds of the exact solution to any CH-program. We show that the algorithm is capable of solving many layout optimization problems in deep submicron iterative circuit and/or high-performance multichip module (MCM) and printed circuit board (PCB) designs. In particular, we apply the algorithm to the simultaneous transistor and interconnect sizing problem, and to the global interconnect sizing and spacing problem considering the coupling cap...

In this paper, we study wire width planning for interconnect performance optimization in an interconnect-centric design flow. We first propose some simplified, yet near-optimal wire sizing schemes, using only one or two discrete wire widths. Our sensitivity study on wire sizing optimization further suggests that there exists a small set of "globally" optimal wire widths for a range of interconnects. We develop general and efficient methods for computing such a "globally" optimal wire width design and show rather surprisingly that using only two "predesigned" widths for each metal layer, we are still able to achieve close to optimal performance compared with that by using many possible widths, not only for one fixed length, but also for all wire lengths assigned at each metal layer. Our wire width planning can consider different design objectives and wire length distributions. Moreover, our method has a predictable small amount of errors compared with optimal solutions. We expect that our simplified wire sizing schemes and wire width planning methodology will be very useful for better design convergence and simpler routing architectures.

As very large scale integrated (VLSI) circuits move into the era of deepsubmicron (DSM) technology and gigahertz frequency, the system performance has increasingly become dominated by the interconnect delay. This dissertation presents five related research topics on interconnect layout optimization, and interconnect extraction and modeling: the multi-source wire sizing (MSWS) problem, the simultaneous transistor and interconnect sizing (STIS) problem, the global interconnect sizing and spacing (GISS) problem, the interconnect capacitance extraction problem, and the interconnect inductance extraction problems. Given a routing tree with multiple sources, the MSWS problem determines the optimal widths of the wire segments such that the delay is minimized. We reveal several interesting properties for the optimal MSWS solution, of which the most important is the bundled refinement property. Based on this property, we propose a polynomial time algorithm, which uses iterative bundled refinement operations to compute lower and upper bounds of an optimal solution. Since the algorithm often achieves identical lower and upper bounds in experiments, the optimal solution is obtained simply by the bound computation. Furthermore, this algorithm can be used for single-source wire sizing problem and runs 100x xxi faster than previous methods. It has replaced previous single-source wire sizing methods in practice.