Power Reductions with Energy Recovery Using Resonant Topologies

The problem of power densities in system-on-chips (SoCs) and processors has become more exacerbated recently, resulting in high cooling costs and reliability issues. One of the largest components of power consumption is the low skew clock distribution network (CDN), driving large load capacitance. This can consume as much as 70% of the total dynamic power that is lost as heat, needing elaborate sensing and cooling mechanisms. To mitigate this, resonant clocking has been utilized in several applications over the past decade. An improved energy recovering reconfigurable generalized series resonance (GSR) solution with all the critical support circuitry is developed in this work. This LC resonant clock driver is shown to save about 50% driver power (\u3e40% overall), on a 22nm process node and has 50% less skew than a non-resonant driver at 2GHz. It can operate down to 0.2GHz to support other energy savings techniques like dynamic voltage and frequency scaling (DVFS). As an example, GSR can be configured for the simpler pulse series resonance (PSR) operation to enable further power saving for double data rate (DDR) applications, by using de-skewing latches instead of flip-flop banks. A PSR based subsystem for 40% savings in clocking power with 40% driver active area reduction xii is demonstrated. This new resonant driver generates tracking pulses at each transition of clock for dual edge operation across DVFS. PSR clocking is designed to drive explicit-pulsed latches with negative setup time. Simulations using 45nm IBM/PTM device and interconnect technology models, clocking 1024 flip-flops show the reductions, compared to non-resonant clocking. DVFS range from 2GHz/1.3V to 200MHz/0.5V is obtained. The PSR frequency is set \u3e3× the clock rate, needing only 1/10th the inductance of prior-art LC resonance schemes. The skew reductions are achieved without needing to increase the interconnect widths owing to negative set-up times. Applications in data circuits are shown as well with a 90nm example. Parallel resonant and split-driver non-resonant configurations as well are derived from GSR. Tradeoffs in timing performance versus power, based on theoretical analysis, are compared for the first time and verified. This enables synthesis of an optimal topology for a given application from the GSR

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.