Optimization techniques for high-performance digital circuits

The relentless push for high performance in custom dig-ital circuits has led to renewed emphasis on circuit opti-mization or tuning. The parameters of the optimization are typically transistor and interconnect sizes. The de-sign metrics are not just delay, transition times, power and area, but also signal integrity and manufacturability. This tutorial paper discusses some of the recently pro-posed methods of circuit optimization, with an emphasis on practical application and methodology impact. Circuit optimization techniques fall into three broad categories. The rst is dynamic tuning, based on time-domain simulation of the underlying circuit, typically combined with adjoint sensitivity computation. These methods are accurate but require the specication of in-put signals, and are best applied to small data- ow cir-cuits and \cross-sections " of larger circuits. Ecient sensitivity computation renders feasible the tuning of cir-cuits with a few thousand transistors. Second, static tuners employ static timing analysis to evaluate the per-formance of the circuit. All paths through the logic are simultaneously tuned, and no input vectors are required. Large control macros are best tuned by these methods. However, in the context of deep submicron custom de-sign, the inaccuracy of the delay models employed by these methods often limits their utility. Aggressive dy-namic or static tuning can push a circuit into a precip-itous corner of the manufacturing process space, which is a problem addressed by the third class of circuit op-timization tools, statistical tuners. Statistical techniques are used to enhance manufacturability or maximize yield. In addition to surveying the above techniques, topics such as the use of state-of-the-art nonlinear optimization methods and special considerations for interconnect siz-ing, clock tree optimization and noise-aware tuning will be brie y considered.

Transistor Sizing of Energy-Delay-Efficient Circuits

This paper studies the problem of transistor sizing of CMOS circuits optimized for energy-delay efficiency, i.e., for optimal Et^n where E is the energy consumption and t is the delay of the circuit, while n is a fixed positive optimization index that reflects the chosen trade-off between energy and delay. We propose a set of analytical formulas that closely approximate the optimal transistor sizes. We then study an efficient iteration procedure that can further improve the original analytical solution. Based on these results, we introduce a novel transistor sizing algorithm for energy-delay efficiency

Delay Extraction Based Equivalent Elmore Model For RLC On-Chip Interconnects

As feature sizes for VLSI technology is shrinking, associated with higher operating frequency, signal integrity analysis of on-chip interconnects has become a real challenge for circuit designers. For this purpose, computer-aided-design (CAD) tools are necessary to simulate signal propagation of on-chip interconnects which has been an active area for research. Although SPICE models exist which can accurately predict signal degradation of interconnects, they are computationally expensive. As a result, more effective and analytic models for interconnects are required to capture the response at the output of high speed VLSI circuits. This thesis contributes to the development of efficient and closed form solution models for signal integrity analysis of on-chip interconnects. The proposed model uses a delay extraction algorithm to improve the accuracy of two-pole Elmore based models used in the analysis of on-chip distributed RLC interconnects. In the proposed scheme, the time of fight signal delay is extracted without increasing the number of poles or affecting the stability of the transfer function. This algorithm is used for both unit step and ramp inputs. From the delay rational approximation of the transfer function, analytic fitted expressions are obtained for the 50% delay and rise time for unit step input. The proposed algorithm is tested on point to point interconnections and tree structure networks. Numerical examples illustrate improved 50% delay and rise time estimates when compared to traditional Elmore based two-pole models

Simultaneous Driver and Wire Sizing for Performance and Power Optimization

In this paper, we study the simultaneous driver and wire sizing (SDWS) problem under two objective functions: (i) delay minimization only, or (ii) combined delay and power dissipation minimization. We present general formulations of the SDWS problem under these two objectives based on the distributed Elmore delay model with consideration of both capacitive power dissipation and short-circuit power dissipation. We show several interesting properties of the optimal SDWS solutions under the two objectives, including an important result (Theorem 5) which reveals the relationship between driver sizing and optimal wire sizing. These results lead to polynomial time algorithms for computing the lower and upper bounds of optimal SDWS solutions under the two objectives, and efficient algorithms for computing optimal SDWS solutions under the two objectives. We have implemented these algorithms and compared them with existing design methods for driver sizing only or independent driver and wire siz..

Simultaneous Driver and Wire Sizing for Performance and Power Optimization

In this paper, we study the simultaneous driver and wire sizing (SDWS) problem under two objective functions: (i) delay minimization only, or (ii) combined delay and power dissipation minimization. We present general formulations of the SDWS problem under these two objectives based on the distributed Elmore delay model with consideration of both capacitive power dissipation and short-circuit power dissipation. We show several interesting properties of the optimal SDWS solutions under the two objectives, including an important result (Theorem 3) which reveals the relationship between driver sizing and optimal wire sizing. These results lead to polynomial time algorithms for computing the lower and upper bounds of optimal SDWS solutions under the two objectives, and efficient algorithms for computing optimal SDWS solutions under the two objectives. We have implemented these algorithms and compared them with existing design methods for driver sizing only or independent driver and wire sizing. Accurate SPICE simulation shows that our methods reduce the delay by up to 11%-47% and power dissipation by 26%-63% compared with existing design methods