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 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 IC and/or high-performance MCM/PCB designs. In particular, we apply...

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...

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.