This paper briefly reviews the forces that caused the power problem, the solutions that were applied, and what the solutions tell us about the problem As systems became more power constrained, optimizing the power became more critical; viewing power reduction from an optimization perspective provides valuable insights Section III describes these insights in more detail, including why Vdd and Vth have stopped scaling Section IV describes some of the low power techniques that have been used in the past in the context of the optimization framework This framework also makes it easy to see the impact of variability, which is discussed in more detail in section V along with the adaptive mechanisms that have been proposed and deployed to minimize the energy cost Section VI describes possible strategies for dealing with the slowdown in gate energy scaling, and the final section concludes by discussing the implications of these strategies for device designers

Scaling, power, and the future of CMOS

This paper presents methods for efficient energy-performance optimization at the circuit and micro-architectural levels. The optimal balance between energy and performance is achieved when the sensitivity of energy to a change in performance is equal for all the design variables. The sensitivity-based optimizations minimize energy subject to a delay constraint. Energy savings of about 65% can be achieved without delay penalty with equalization of sensitivities to sizing, supply, and threshold voltage in a 64-bit adder, compared to the reference design sized for minimum delay. Circuit optimization is effective only in the region of about /spl plusmn/30% around the reference delay; outside of this region the optimization becomes too costly either in terms of energy or delay. Using optimal energy-delay tradeoffs from the circuit level and introducing more degrees of freedom, the optimization is hierarchically extended to higher abstraction layers. We focus on the micro-architectural optimization and demonstrate that the scope of energy-efficient optimization can be extended by the choice of circuit topology or the level of parallelism. In a 64-bit ALU example, parallelism of five provides a three-fold performance increase, while requiring the same energy as the reference design. Parallel or time-multiplexed solutions significantly affect the area of their respective designs, so the overall design cost is minimized when optimal energy-area tradeoff is achieved.

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Methods for true energy-performance optimization

A Digital Design Method which may be automated is for obtaining timing closure in the design of large, complex, high-performance digital integrated circuits. The methodincludes the use of a tuner on random logic macros that adjusts transistor sizes in a continuous domain. To accommodate this tuning, logic gates are mapped to parameterized cells for the tuning and then back to fixed gates after the tuning. Tuning is constrained in such a way as to minimize “binning errors” when the design is mapped back to fixed cells. Further, the critical sections of the circuit are marked in order to make the optimization more effective and to fit within the problem-size constraints of the tuner. A specially formulated objective function is employed during the tuning to promote faster global timing convergence, despite possibly incorrect initial timing budgets. The specially formulated objective function targets all paths that are failing timing, with appropriate weighting, rather than just targeting the most critical path. Finally, the addition of multiple threshold voltage gates allows for increased performance while limiting leakage power.

Method for tuning a digital design for synthesized random logic circuit macros in a continuous design space with optional insertion of multiple threshold voltage devices

In the mid 1980's the power growth that accompanied scaling forced the industry to focus on CMOS technology, and leave nMOS and bipolars for niche applications. Now 20 years later, CMOS technology is facing power issues of its own. After first reviewing the "cause" of the problem, it will become clear that there are not easy solutions this time - no new technology or simple system/circuit change will rescue us. Power, and not number of devices is now the primary limiter of chip performance, and the need to create power efficient designs is changing how we do design. This talk will review power optimized design methods and shows how power is strongly tied to performance and that variability aversely effects power efficiency. Projecting forward, it shows that unless die size shrinks, in future technologies most of the devices will need to be idle most of the time which has strong ramifications for the both the underlying device and system design.

Scaling, Power and the Future of CMOS

Power consumption has become a major constraint in the design of processors today. To optimize a processor for energy-efficiency requires an examination of energy-performance trade-offs in all aspects of the processor design space, including both architectural and circuit design choices. In this paper, we apply an integrated architecture-circuit optimization framework to map out energy-performance trade-offs of several different high-level processor architectures. We show how the joint architecture-circuit space provides a trade-off range of approximately 6.5x in performance for 4x energy, and we identify the optimal architectures for different design objectives. We then show that many of the designs in this space come at very high marginal costs. Our results show that, for a large range of design objectives, voltage scaling is effective in efficiently trading off performance and energy, and that the choice of optimal architecture and circuits does not change much during voltage scaling. Finally, we show that with only two designs--a dual-issue in-order design and a dual-issue out-of-order design, both properly optimized-a large part of the energy-performance trade-off space can be covered within 3% of the optimal energy-efficiency.

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Energy-performance tradeoffs in processor architecture and circuit design: a marginal cost analysis

This paper describes a method of optimally sizing digital circuits on a static-timing basis. All paths through the logic are considered simultaneously and no input patterns need be specified by the user. The method is unique in that it is based on gradient-based, nonlinear optimization and can accommodate transistor-level schematics without the need for pre-characterization. It employs efficient time-domain simulation and gradient computation for each channel-connected component. A large-scale, general-purpose, nonlinear optimization package is used to solve the tuning problem. A prototype tuner has been developed that accommodates combinational circuits consisting of parameterized library cells. Numerical results are presented.

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P. N. Strenski

Papers

Gradient-based optimization of custom circuits using a static-timing formulation