informs ® doi 10.1287/opre.1050.0254 © 2005 INFORMS This paper concerns a method for digital circuit optimization based on formulating the problem as a geometric program (GP) or generalized geometric program (GGP), which can be transformed to a convex optimization problem and then very efficiently solved. We start with a basic gate scaling problem, with delay modeled as a simple resistor-capacitor (RC) time constant, and then add various layers of complexity and modeling accuracy, such as accounting for differing signal fall and rise times, and the effects of signal transition times. We then consider more complex formulations such as robust design over corners, multimode design, statistical design, and problems in which threshold and power supply voltage are also variables to be chosen. Finally, we look at the detailed design of gates and interconnect wires, again using a formulation that is compatible with GP or GGP.

If current technology scaling trends hold, leakage power dissipation will soon become the dominant source of power consumption. Caches, due to the fact that they account for the largest fraction of on-chip transistors in most modern processors, are a primary candidate for attacking the leakage problem. While there has been a flurry of research in this area over the Last several years, a major question remains unanswered. What is the total potential of existing architectural and circuit techniques to address this important design concern? In this paper, we explore the limits in which existing circuit and architecture technologies may address this growing problem. We first formally propose a parameterized model that can determine the optimal leakage savings based on the perfect knowledge of the address trace. By carefully applying the sleep and drowsy modes, we find that the total leakage power from the L1 instruction cache, data cache, and a unified L2 cache may be reduced to mere 3.6%, 0.9%, and 2.3%, respectively, of the unoptimized case. We further study how such a model can be extended to obtain the optimal leakage power savings for different cache configurations.

With continued and aggressive scaling, using ultralow thickness SiO2 for the transistor gates, tunneling current has emerged as the major component of leakage in CMOS circuits. In this paper, we propose a new approach called dual dielectrics of dual thicknesses (DKDT) for the reduction of both ON and OFF state gate tunneling currents. We claim that the simultaneous utilization of SiON and SiO2 each with multiple thicknesses is a better approach for gate leakage reduction than the conventional one that uses a single gate dielectric, SiO2 , of multiple thicknesses. We develop an algorithm for the corresponding assignment of dual dielectric and dual thickness cells that minimizes the overall tunneling current for a circuit without compromising its performance. We performed extensive experiments on ISCAS'85 benchmarks using 45 nm technology which demonstrate that our approach can reduce the tunneling current by as much as 98.7% (on average 94.8%), without performance degradation.

Gate oxide direct tunneling current is the major component of static power dissipation of a CMOS circuit for low-end technology, where the gate dielectric (SiO 2 ) thickness is very low. This paper presents a novel direct tunneling current reduction method during behavioral synthesis of nanometer CMOS circuits. We provide analytical models to calculate the direct tunneling current and the propagation delay of behavioral level components. We then characterize those components for various gate oxide thicknesses. We also provide an algorithm for behavioral scheduling for minimizing the overall tunneling current dissipation of datapath circuits. The algorithm explores dual oxide thickness option for reducing direct tunneling current. We have carried out extensive experiments for various behavioral level benchmarks under various resource constraints and observed significant reductions in tunneling current.

Rising interest in the applications of wireless sensor networks has spurred research in the development of computing systems for lowthroughput, energy-constrained applications. Unlike traditional performance oriented applications, sensor network nodes are primarily constrained by operation lifetime, which is limited by power consumption. Advanced CMOS process technologies provide ever increasing transistor density and improved performance characteristics. However, shrinking feature size and decreasing threshold voltages also lead to significant increases in leakage current, which is especially troublesome for applications with significant idle times. This work investigates tradeoffs between leakage and active power for low-throughput applications. We study these issues across a range of process technologies on a computing architecture that provides explicit support for fine-grain leakage-control techniques such as Vdd-gating and adaptive body bias. We present a methodology for selecting design parameters, including choice of process technology, that makes the optimal tradeoff between active power and leakage power for a given workload. Our results show that leakage power will dominate the selection of process technology, and architectures that support advanced leakage control techniques at the circuit level will be essential. We argue that without advanced lowpower architectures future nano-scale process technologies will not be suited for sensor network applications.

Abstract — For a nanoCMOS of sub-65nm technology, where the gate oxide (SiO2) thickness is very low, the gate leakage is one of the major components of power dissipation. In this paper, we provide analytical models to describe the tunneling current and propagation delay of behavioral level components considering various physical effects in the absence of foundry data. Subsequently, we explore the use of multiple oxide thickness resources as a technique for the reduction of gate leakage. In particular, we introduce a behavioral datapath scheduler that maximizes the utilization of higher gate oxide thickness resources. We characterize behavioral components for both 65nm and 45nm technologies in order to study the trend of tunneling current as technology scales, and provide them as inputs to the scheduler. We carried out extensive experiments for several benchmarks and observed significant reduction in gate leakage. I.

Aggressive CMOS scaling results in low threshold voltage and thin oxide thickness for transistors manufactured in very deep submicron regime. As a result, reducing the subthreshold and gate-tunneling leakage currents has become one of the most important criteria in the design of VLSI circuits. This paper presents a method based on dual-V and dual-T ox assignment to reduce the total leakage power dissipation of SRAMs while maintaining their performance. The proposed method is based on the observation that the read and write delays of a memory cell in an SRAM block depend on the physical distance of the cell from the sense amplifier and the decoder. Thus, the idea is to deploy different types of sixtransistor SRAM cells corresponding to different threshold voltage and oxide thickness assignments for the transistors. Unlike other techniques for low-leakage SRAM design, the proposed technique incurs neither area nor delay overhead. In addition, it results in a minor change in the SRAM design flow. Simulation results with a 65nm process demonstrate that this technique can reduce the total leakage power dissipation of a 64Kb SRAM by more than 50%.

Optimum sleep transistor design and implementation are critical to a successful power-gating design. This paper describes a number of critical considerations for the sleep transistor design and implementation including header or footer switch selection, sleep transistor distribution choices and sleep transistor gate length, width and body bias optimization for area, leakage and efficiency.

Optimum power gating sleep transistor design and implementation are critical to a successful low-power design. This paper describes important considerations for the sleep transistor design and implementation including header or footer switch selection, sleep transistor distribution choices and sleep transistor gate length, width and body bias optimization for area, leakage and efficiency. It also investigated various power-on current rush control methods for the sleep transistor implementation.

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