Subthreshold and gate leakage current analysis and reduction in VLSI circuits

CMOS technology has scaled aggressively over the past few decades in an effort to enhance functionality, speed and packing density per chip. As the feature sizes are scaling down to sub-100nm regime, leakage power is increasing significantly and is becoming the dominant component of the total power dissipation. Major contributors to the total leakage current in deep submicron regime are subthreshold and gate tunneling leakage currents. The leakage reduction techniques developed so far were mostly devoted to reducing subthreshold leakage. However, at sub-65nm feature sizes, gate leakage current grows faster and is expected to surpass subthreshold leakage current. In this work, an extensive analysis of the circuit level characteristics of subthreshold and gate leakage currents is performed at 45nm and 32nm feature sizes. The analysis provides several key observations on the interdependency of gate and subthreshold leakage currents. Based on these observations, a new leakage reduction technique is proposed that optimizes both the leakage currents. This technique identifies minimum leakage vectors for a given circuit based on the number of transistors in OFF state and their position in the stack. The effectiveness of the proposed technique is compared to most of the mainstream leakage reduction techniques by implementing them on ISCAS89 benchmark circuits. The proposed leakage reduction technique proved to be more effective in reducing gate leakage current than subthreshold leakage current. However, when combined with dual-threshold and variable-threshold CMOS techniques, substantial subthreshold leakage current reduction was also achieved. A total savings of 53% for subthreshold leakage current and 26% for gate leakage current are reported

Dynamic Power Management for Neuromorphic Many-Core Systems

This work presents a dynamic power management architecture for neuromorphic many core systems such as SpiNNaker. A fast dynamic voltage and frequency scaling (DVFS) technique is presented which allows the processing elements (PE) to change their supply voltage and clock frequency individually and autonomously within less than 100 ns. This is employed by the neuromorphic simulation software flow, which defines the performance level (PL) of the PE based on the actual workload within each simulation cycle. A test chip in 28 nm SLP CMOS technology has been implemented. It includes 4 PEs which can be scaled from 0.7 V to 1.0 V with frequencies from 125 MHz to 500 MHz at three distinct PLs. By measurement of three neuromorphic benchmarks it is shown that the total PE power consumption can be reduced by 75%, with 80% baseline power reduction and a 50% reduction of energy per neuron and synapse computation, all while maintaining temporary peak system performance to achieve biological real-time operation of the system. A numerical model of this power management model is derived which allows DVFS architecture exploration for neuromorphics. The proposed technique is to be used for the second generation SpiNNaker neuromorphic many core system

Designing energy-efficient sub-threshold logic circuits using equalization and non-volatile memory circuits using memristors

The very large scale integration (VLSI) community has utilized aggressive complementary metal-oxide semiconductor (CMOS) technology scaling to meet the ever-increasing performance requirements of computing systems. However, as we enter the nanoscale regime, the prevalent process variation effects degrade the CMOS device reliability. Hence, it is increasingly essential to explore emerging technologies which are compatible with the conventional CMOS process for designing highly-dense memory/logic circuits. Memristor technology is being explored as a potential candidate in designing non-volatile memory arrays and logic circuits with high density, low latency and small energy consumption. In this thesis, we present the detailed functionality of multi-bit 1-Transistor 1-memRistor (1T1R) cell-based memory arrays. We present the performance and energy models for an individual 1T1R memory cell and the memory array as a whole. We have considered TiO2- and HfOx-based memristors, and for these technologies there is a sub-10% difference between energy and performance computed using our models and HSPICE simulations. Using a performance-driven design approach, the energy-optimized TiO2-based RRAM array consumes the least write energy (4.06 pJ/bit) and read energy (188 fJ/bit) when storing 3 bits/cell for 100 nsec write and 1 nsec read access times. Similarly, HfOx-based RRAM array consumes the least write energy (365 fJ/bit) and read energy (173 fJ/bit) when storing 3 bits/cell for 1 nsec write and 200 nsec read access times. On the logic side, we investigate the use of equalization techniques to improve the energy efficiency of digital sequential logic circuits in sub-threshold regime. We first propose the use of a variable threshold feedback equalizer circuit with combinational logic blocks to mitigate the timing errors in digital logic designed in sub-threshold regime. This mitigation of timing errors can be leveraged to reduce the dominant leakage energy by scaling supply voltage or decreasing the propagation delay. At the fixed supply voltage, we can decrease the propagation delay of the critical path in a combinational logic block using equalizer circuits and, correspondingly decrease the leakage energy consumption. For a 8-bit carry lookahead adder designed in UMC 130 nm process, the operating frequency can be increased by 22.87% (on average), while reducing the leakage energy by 22.6% (on average) in the sub-threshold regime. Overall, the feedback equalization technique provides up to 35.4% lower energy-delay product compared to the conventional non-equalized logic. We also propose a tunable adaptive feedback equalizer circuit that can be used with sequential digital logic to mitigate the process variation effects and reduce the dominant leakage energy component in sub-threshold digital logic circuits. For a 64-bit adder designed in 130 nm our proposed approach can reduce the normalized delay variation of the critical path delay from 16.1% to 11.4% while reducing the energy-delay product by 25.83% at minimum energy supply voltage. In addition, we present detailed energy-performance models of the adaptive feedback equalizer circuit. This work serves as a foundation for the design of robust, energy-efficient digital logic circuits in sub-threshold regime

Design and Analysis of an Adaptive Asynchronous System Architecture for Energy Efficiency

Power has become a critical design parameter for digital CMOS integrated circuits. With performance still garnering much concern, a central idea has emerged: minimizing power consumption while maintaining performance. The use of dynamic voltage scaling (DVS) with parallelism has shown to be an effective way of saving power while maintaining performance. However, the potency of DVS and parallelism in traditional, clocked synchronous systems is limited because of the strict timing requirements such systems must comply with. Delay-insensitive (DI) asynchronous systems have the potential to benefit more from these techniques due to their flexible timing requirements and high modularity. This dissertation presents the design and analysis of a real-time adaptive DVS architecture for paralleled Multi-Threshold NULL Convention Logic (MTNCL) systems. Results show that energy-efficient systems with low area overhead can be created using this approach

Design and modelling of variability tolerant on-chip communication structures for future high performance system on chip designs

The incessant technology scaling has enabled the integration of functionally complex System-on-Chip (SoC) designs with a large number of heterogeneous systems on a single chip. The processing elements on these chips are integrated through on-chip communication structures which provide the infrastructure necessary for the exchange of data and control signals, while meeting the strenuous physical and design constraints. The use of vast amounts of on chip communications will be central to future designs where variability is an inherent characteristic. For this reason, in this thesis we investigate the performance and variability tolerance of typical on-chip communication structures. Understanding of the relationship between variability and communication is paramount for the designers; i.e. to devise new methods and techniques for designing performance and power efficient communication circuits in the forefront of challenges presented by deep sub-micron (DSM) technologies. The initial part of this work investigates the impact of device variability due to Random Dopant Fluctuations (RDF) on the timing characteristics of basic communication elements. The characterization data so obtained can be used to estimate the performance and failure probability of simple links through the methodology proposed in this work. For the Statistical Static Timing Analysis (SSTA) of larger circuits, a method for accurate estimation of the probability density functions of different circuit parameters is proposed. Moreover, its significance on pipelined circuits is highlighted. Power and area are one of the most important design metrics for any integrated circuit (IC) design. This thesis emphasises the consideration of communication reliability while optimizing for power and area. A methodology has been proposed for the simultaneous optimization of performance, area, power and delay variability for a repeater inserted interconnect. Similarly for multi-bit parallel links, bandwidth driven optimizations have also been performed. Power and area efficient semi-serial links, less vulnerable to delay variations than the corresponding fully parallel links are introduced. Furthermore, due to technology scaling, the coupling noise between the link lines has become an important issue. With ever decreasing supply voltages, and the corresponding reduction in noise margins, severe challenges are introduced for performing timing verification in the presence of variability. For this reason an accurate model for crosstalk noise in an interconnection as a function of time and skew is introduced in this work. This model can be used for the identification of skew condition that gives maximum delay noise, and also for efficient design verification