Techniques of Energy-Efficient VLSI Chip Design for High-Performance Computing

How to implement quality computing with the limited power budget is the key factor to move very large scale integration (VLSI) chip design forward. This work introduces various techniques of low power VLSI design used for state of art computing. From the viewpoint of power supply, conventional in-chip voltage regulators based on analog blocks bring the large overhead of both power and area to computational chips. Motivated by this, a digital based switchable pin method to dynamically regulate power at low circuit cost has been proposed to make computing to be executed with a stable voltage supply. For one of the widely used and time consuming arithmetic units, multiplier, its operation in logarithmic domain shows an advantageous performance compared to that in binary domain considering computation latency, power and area. However, the introduced conversion error reduces the reliability of the following computation (e.g. multiplication and division.). In this work, a fast calibration method suppressing the conversion error and its VLSI implementation are proposed. The proposed logarithmic converter can be supplied by dc power to achieve fast conversion and clocked power to reduce the power dissipated during conversion. Going out of traditional computation methods and widely used static logic, neuron-like cell is also studied in this work. Using multiple input floating gate (MIFG) metal-oxide semiconductor field-effect transistor (MOSFET) based logic, a 32-bit, 16-operation arithmetic logic unit (ALU) with zipped decoding and a feedback loop is designed. The proposed ALU can reduce the switching power and has a strong driven-in capability due to coupling capacitors compared to static logic based ALU. Besides, recent neural computations bring serious challenges to digital VLSI implementation due to overload matrix multiplications and non-linear functions. An analog VLSI design which is compatible to external digital environment is proposed for the network of long short-term memory (LSTM). The entire analog based network computes much faster and has higher energy efficiency than the digital one

Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally

A Charge-Recycling Scheme and Ultra Low Voltage Self-Startup Charge Pump for Highly Energy Efficient Mixed Signal Systems-On-A-Chip

The advent of battery operated sensor-based electronic systems has provided a pressing need to design energy-efficient, ultra-low power integrated circuits as a means to improve the battery lifetime. This dissertation describes a scheme to lower the power requirement of a digital circuit through the use of charge-recycling and dynamic supply-voltage scaling techniques. The novel charge-recycling scheme proposed in this research demonstrates the feasibility of operating digital circuits using the charge scavenged from the leakage and dynamic load currents inherent to digital design. The proposed scheme efficiently gathers the “ground-bound” charge into storage capacitor banks. This reclaimed charge is then subsequently recycled to power the source digital circuit. The charge-recycling methodology has been implemented on a 12-bit Gray-code counter operating at frequencies of less than 50 MHz. The circuit has been designed in a 90-nm process and measurement results reveal more than 41% reduction in the average energy consumption of the counter. The total energy savings including the power consumed for the generation of control signals aggregates to an average of 23%. The proposed methodology can be applied to an existing digital path without any design change to the circuit but with only small loss to the performance. Potential applications of this scheme are described, specifically in wide-temperature dynamic power reduction and as a source for energy harvesters. The second part of this dissertation deals with the design and development of a self-starting, ultra-low voltage, switched-capacitor (SC) DC-DC converter that is essential to an energy harvesting system. The proposed charge-pump based SC-converter operates from 125-mV input and thus enables battery-less operation in ultra-low voltage energy harvesters. The charge pump does not require any external components or expensive post-fabrication processing to enable low-voltage operation. This design has been implemented in a 130-nm CMOS process. While the proposed charge pump provides significant efficiency enhancement in energy harvesters, it can also be incorporated within charge recycling systems to facilitate adaptable charge-recycling levels. In total, this dissertation provides key components needed for highly energy-efficient mixed signal systems-on-a-chip

Adiabatic Approach for Low-Power Passive Near Field Communication Systems

This thesis tackles the need of ultra-low power electronics in the power limited passive Near Field Communication (NFC) systems. One of the techniques that has proven the potential of delivering low power operation is the Adiabatic Logic Technique. However, the low power benefits of the adiabatic circuits come with the challenges due to the absence of single opinion on the most energy efficient adiabatic logic family which constitute appropriate trade-offs between computation time, area and complexity based on the circuit and the power-clocking schemes. Therefore, five energy efficient adiabatic logic families working in single-phase, 2-phase and 4-phase power-clocking schemes were chosen. Since flip-flops are the basic building blocks of any sequential circuit and the existing flip-flops are MUX-based (having more transistors) design, therefore a novel single-phase, 2-phase and 4-phase reset based flip-flops were proposed. The performance of the multi-phase adiabatic families was evaluated and compared based on the design examples such as 2-bit ring counter, 3-bit Up-Down counter and 16-bit Cyclic Redundancy Check (CRC) circuit (benchmark circuit) based on ISO 14443-3A standard. Several trade-offs, design rules, and an appropriate range for the supply voltage scaling for multi-phase adiabatic logic are proposed. Furthermore, based on the NFC standard (ISO 14443-3A), data is frequently encoded using Manchester coding technique before transmitting it to the reader. Therefore, if Manchester encoding can be implemented using adiabatic logic technique, energy benefits are expected. However, adiabatic implementation of Manchester encoding presents a challenge. Therefore, a novel method for implementing Manchester encoding using adiabatic logic is proposed overcoming the challenges arising due to the AC power-clock. Other challenges that come with the dynamic nature of the adiabatic gates and the complexity of the 4-phase power-clocking scheme is in synchronizing the power-clock v phases and the time spent in designing, validation and debugging of errors. This requires a specific modelling approach to describe the adiabatic logic behaviour at the higher level of abstraction. However, describing adiabatic logic behaviour using Hardware Description Languages (HDLs) is a challenging problem due to the requirement of modelling the AC power-clock and the dual-rail inputs and outputs. Therefore, a VHDL-based modelling approach for the 4-phase adiabatic logic technique is developed for functional simulation, precise timing analysis and as an improvement over the previously described approaches

Adiabatic Circuits for Power-Constrained Cryptographic Computations

This thesis tackles the need for ultra-low power operation in power-constrained cryptographic computations. An example of such an application could be smartcards. One of the techniques which has proven to have the potential of rendering ultra-low power operation is ‘Adiabatic Logic Technique’. However, the adiabatic circuits has associated challenges due to high energy dissipation of the Power-Clock Generator (PCG) and complexity of the multi-phase power-clocking scheme. Energy efficiency of the adiabatic system is often degraded due to the high energy dissipation of the PCG. In this thesis, nstep charging strategy using tank capacitors is considered for the power-clock generation and several design rules and trade-offs between the circuit complexity and energy efficiency of the PCG using n-step charging circuits have been proposed. Since pipelining is inherent in adiabatic logic design, careful selection of architecture is essential, as otherwise overhead in terms of area and energy due to synchronization buffers is induced specifically, in the case of adiabatic designs using 4-phase power-clocking scheme. Several architectures for the Montgomery multiplier using adiabatic logic technique are implemented and compared. An architecture which constitutes an appropriate trade-off between energy efficiency and throughput is proposed along with its methodology. Also, a strategy to reduce the overhead due to synchronization buffers is proposed. A modification in the Montgomery multiplication algorithm is proposed. Furthermore, a problem due to the application of power-clock gating in cascade stages of adiabatic logic is identified. The problem degrades the energy savings that would otherwise be obtained by the application of power-clock gating. A solution to this problem is proposed. Cryptographic implementations also present an obvious target for Power Analysis Attacks (PAA). There are several existing secure adiabatic logic designs which are proposed as a countermeasure against PAA. Shortcomings of the existing logic designs are identified, and two novel secure adiabatic logic designs are proposed as the countermeasures against PAA and improvement over the existing logic designs

Asynchrobatic logic for low-power VLSI design

In this work, Asynchrobatic Logic is presented. It is a novel low-power design style that combines the energy saving benefits of asynchronous logic and adiabatic logic to produce systems whose power dissipation is reduced in several different ways. The term “Asynchrobatic” is a new word that can be used to describe these types of systems, and is derived from the concatenation and shortening of Asynchronous, Adiabatic Logic. This thesis introduces the concept and theory behind Asynchrobatic Logic. It first provides an introductory background to both underlying parent technologies (asynchronous logic and adiabatic logic). The background material continues with an explanation of a number of possible methods for designing complex data-path cells used in the adiabatic data-path. Asynchrobatic Logic is then introduced as a comparison between asynchronous and Asynchrobatic buffer chains, showing that for wide systems, it operates more efficiently. Two more-complex sub-systems are presented, firstly a layout implementation of the substitution boxes from the Twofish encryption algorithm, and secondly a front-end only (without parasitic capacitances, resistances) simulation that demonstrates a functional system capable of calculating the Greatest Common Denominator (GCD) of a pair of 16-bit unsigned integers, which under typical conditions on a 0.35μm process, executed a test vector requiring twenty-four iterations in 2.067μs with a power consumption of 3.257nW. These examples show that the concept of Asynchrobatic Logic has the potential to be used in real-world applications, and is not just theory without application. At the time of its first publication in 2004, Asynchrobatic Logic was both unique and ground-breaking, as this was the first time that consideration had been given to operating large-scale adiabatic logic in an asynchronous fashion, and the first time that Asynchronous Stepwise Charging (ASWC) had been used to drive an adiabatic data-path

Fault tolerance issues in nanoelectronics

The astonishing success story of microelectronics cannot go on indefinitely. In fact, once devices reach the few-atom scale (nanoelectronics), transient quantum effects are expected to impair their behaviour. Fault tolerant techniques will then be required. The aim of this thesis is to investigate the problem of transient errors in nanoelectronic devices. Transient error rates for a selection of nanoelectronic gates, based upon quantum cellular automata and single electron devices, in which the electrostatic interaction between electrons is used to create Boolean circuits, are estimated. On the bases of such results, various fault tolerant solutions are proposed, for both logic and memory nanochips. As for logic chips, traditional techniques are found to be unsuitable. A new technique, in which the voting approach of triple modular redundancy (TMR) is extended by cascading TMR units composed of nanogate clusters, is proposed and generalised to other voting approaches. For memory chips, an error correcting code approach is found to be suitable. Various codes are considered and a lookup table approach is proposed for encoding and decoding. We are then able to give estimations for the redundancy level to be provided on nanochips, so as to make their mean time between failures acceptable. It is found that, for logic chips, space redundancies up to a few tens are required, if mean times between failures have to be of the order of a few years. Space redundancy can also be traded for time redundancy. As for memory chips, mean times between failures of the order of a few years are found to imply both space and time redundancies of the order of ten

CIRCUITS AND ARCHITECTURE FOR BIO-INSPIRED AI ACCELERATORS

Technological advances in microelectronics envisioned through Moore’s law have led to powerful processors that can handle complex and computationally intensive tasks. Nonetheless, these advancements through technology scaling have come at an unfavorable cost of significantly larger power consumption, which has posed challenges for data processing centers and computers at scale. Moreover, with the emergence of mobile computing platforms constrained by power and bandwidth for distributed computing, the necessity for more energy-efficient scalable local processing has become more significant. Unconventional Compute-in-Memory architectures such as the analog winner-takes-all associative-memory and the Charge-Injection Device processor have been proposed as alternatives. Unconventional charge-based computation has been employed for neural network accelerators in the past, where impressive energy efficiency per operation has been attained in 1-bit vector-vector multiplications, and in recent work, multi-bit vector-vector multiplications. In the latter, computation was carried out by counting quanta of charge at the thermal noise limit, using packets of about 1000 electrons. These systems are neither analog nor digital in the traditional sense but employ mixed-signal circuits to count the packets of charge and hence we call them Quasi-Digital. By amortizing the energy costs of the mixed-signal encoding/decoding over compute-vectors with many elements, high energy efficiencies can be achieved. In this dissertation, I present a design framework for AI accelerators using scalable compute-in-memory architectures. On the device level, two primitive elements are designed and characterized as target computational technologies: (i) a multilevel non-volatile cell and (ii) a pseudo Dynamic Random-Access Memory (pseudo-DRAM) bit-cell. At the level of circuit description, compute-in-memory crossbars and mixed-signal circuits were designed, allowing seamless connectivity to digital controllers. At the level of data representation, both binary and stochastic-unary coding are used to compute Vector-Vector Multiplications (VMMs) at the array level. Finally, on the architectural level, two AI accelerator for data-center processing and edge computing are discussed. Both designs are scalable multi-core Systems-on-Chip (SoCs), where vector-processor arrays are tiled on a 2-layer Network-on-Chip (NoC), enabling neighbor communication and flexible compute vs. memory trade-off. General purpose Arm/RISCV co-processors provide adequate bootstrapping and system-housekeeping and a high-speed interface fabric facilitates Input/Output to main memory