Improved method for SNR prediction in machine-learning-based test

This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach, the dynamic parameters can be predicted by using the signature results. However, it can only estimate the SNR accurately within a certain range. In order to overcome this limitation, an improved method based on work is applied in this work. It is validated on the Labview model of a 12-bit 80 Ms/s pipelined ADC with a pulse- wave input signal of 3 LSB noise and 7-bit nonlinear rising and falling edges

redicting dynamic specifications of ADCs with a low-quality digital input signal

A new method is presented to test dynamic parameters of Analogue-to-Digital Converters (ADC). A noisy and nonlinear pulse is applied as the test stimulus, which is suitable for a multi-site test environment. The dynamic parameters are predicted using a machine-learning-based approach. A training step is required in order to build the mapping function using alternate signatures and the conventional test parameters, all measured on a set of converters. As a result, for industrial testing, only a simple signature-based test is performed on the Devices-Under-Test (DUTs). The signature measurements are provided to the mapping function that is used to predict the conventional dynamic parameters. The method is validated by simulation on a 12-bit 80 Ms/s pipelined ADC with a pulse wave input signal of 3 LSB noise and 7-bit nonlinear rising and falling edges. The final results show that the estimated mean error is less than 4% of the full range of the dynamic specifications

Asynchronous Circuit Stacking for Simplified Power Management

As digital integrated circuits (ICs) continue to increase in complexity, new challenges arise for designers. Complex ICs are often designed by incorporating multiple power domains therefore requiring multiple voltage converters to produce the corresponding supply voltages. These converters not only take substantial on-chip layout area and/or off-chip space, but also aggregate the power loss during the voltage conversions that must occur fast enough to maintain the necessary power supplies. This dissertation work presents an asynchronous Multi-Threshold NULL Convention Logic (MTNCL) “stacked” circuit architecture that alleviates this problem by reducing the number of voltage converters needed to supply the voltage the ICs operate at. By stacking multiple MTNCL circuits between power and ground, supplying a multiple of VDD to the entire stack and incorporating simple control mechanisms, the dynamic range fluctuation problem can be mitigated. A 130nm Bulk CMOS process and a 32nm Silicon-on-Insulator (SOI) CMOS process are used to evaluate the theoretical effect of stacking different circuitry while running different workloads. Post parasitic physical implementations are then carried out in the 32nm SOI process for demonstrating the feasibility and analyzing the advantages of the proposed MTNCL stacking architecture

The test ability of an adaptive pulse wave for ADC testing

In the conventional ADC production test method, a high-quality analogue sine wave is applied to the Analogue-to-Digital Converter (ADC), which is expensive to generate. Nowadays, an increasing number of ADCs are integrated into a system-on-chip (SoC) platform design, which usually contains a digital embedded processor. In such a platform, a digital pulse wave is obviously less expensive to generate than an accurate analogue sine wave. As a result, the usage of a digital pulse wave has been investigated to test ADCs as the test stimulus. In this paper, the ability of a digital adaptive pulse wave for ADC testing is presented via the measurement results. Instead of the conventional FFT analysis, a time-domain analysis is exploited for post-processing, from which a signature result can be obtained. This signature can distinguish between faulty devices and the fault-free devices. It is also used in the machine-learning-based test method to predict the dynamic specifications of the ADC. The experimental results of a 12-bit 80 M/s pipelined ADC are shown to evaluate the sensitivity and accuracy of using a pulse wave to test an ADC

Electron Spin for Classical Information Processing: A Brief Survey of Spin-Based Logic Devices, Gates and Circuits

In electronics, information has been traditionally stored, processed and communicated using an electron's charge. This paradigm is increasingly turning out to be energy-inefficient, because movement of charge within an information-processing device invariably causes current flow and an associated dissipation. Replacing charge with the "spin" of an electron to encode information may eliminate much of this dissipation and lead to more energy-efficient "green electronics". This realization has spurred significant research in spintronic devices and circuits where spin either directly acts as the physical variable for hosting information or augments the role of charge. In this review article, we discuss and elucidate some of these ideas, and highlight their strengths and weaknesses. Many of them can potentially reduce energy dissipation significantly, but unfortunately are error-prone and unreliable. Moreover, there are serious obstacles to their technological implementation that may be difficult to overcome in the near term. This review addresses three constructs: (1) single devices or binary switches that can be constituents of Boolean logic gates for digital information processing, (2) complete gates that are capable of performing specific Boolean logic operations, and (3) combinational circuits or architectures (equivalent to many gates working in unison) that are capable of performing universal computation.Comment: Topical Revie

Circuit design and analysis for on-FPGA communication systems

On-chip communication system has emerged as a prominently important subject in Very-Large- Scale-Integration (VLSI) design, as the trend of technology scaling favours logics more than interconnects. Interconnects often dictates the system performance, and, therefore, research for new methodologies and system architectures that deliver high-performance communication services across the chip is mandatory. The interconnect challenge is exacerbated in Field-Programmable Gate Array (FPGA), as a type of ASIC where the hardware can be programmed post-fabrication. Communication across an FPGA will be deteriorating as a result of interconnect scaling. The programmable fabrics, switches and the specific routing architecture also introduce additional latency and bandwidth degradation further hindering intra-chip communication performance. Past research efforts mainly focused on optimizing logic elements and functional units in FPGAs. Communication with programmable interconnect received little attention and is inadequately understood. This thesis is among the first to research on-chip communication systems that are built on top of programmable fabrics and proposes methodologies to maximize the interconnect throughput performance. There are three major contributions in this thesis: (i) an analysis of on-chip interconnect fringing, which degrades the bandwidth of communication channels due to routing congestions in reconfigurable architectures; (ii) a new analogue wave signalling scheme that significantly improves the interconnect throughput by exploiting the fundamental electrical characteristics of the reconfigurable interconnect structures. This new scheme can potentially mitigate the interconnect scaling challenges. (iii) a novel Dynamic Programming (DP)-network to provide adaptive routing in network-on-chip (NoC) systems. The DP-network architecture performs runtime optimization for route planning and dynamic routing which, effectively utilizes the in-silicon bandwidth. This thesis explores a new horizon in reconfigurable system design, in which new methodologies and concepts are proposed to enhance the on-FPGA communication throughput performance that is of vital importance in new technology processes

Memory-Based High-Level Synthesis Optimizations Security Exploration on the Power Side-Channel

High-level synthesis (HLS) allows hardware designers to think algorithmically and not worry about low-level, cycle-by-cycle details. This provides the ability to quickly explore the architectural design space and tradeoffs between resource utilization and performance. Unfortunately, security evaluation is not a standard part of the HLS design flow. In this article, we aim to understand the effects of memory-based HLS optimizations on power side-channel leakage. We use Xilinx Vivado HLS to develop different cryptographic cores, implement them on a Spartan-6 FPGA, and collect power traces. We evaluate the designs with respect to resource utilization, performance, and information leakage through power consumption. We have two important observations and contributions. First, the choice of resource optimization directive results in different levels of side-channel vulnerabilities. Second, the partitioning optimization directive can greatly compromise the hardware cryptographic system through power side-channel leakage due to the deployment of memory control logic. We describe an evaluation procedure for power side-channel leakage and use it to make best-effort recommendations about how to design more secure architectures in the cryptographic domain

Built-in self-test and self-calibration for analog and mixed signal circuits

Analog-to-digital converters (ADC) are one of the most important components in modern electronic systems. In the mission-critical applications such as automotive, the reliability of the ADC is critical as the ADC impacts the system level performance. Due to the aging effect and environmental changes, the performance of the ADC may degrade and even fail to meet the accuracy requirement over time. Built-in self-test (BIST) and self-calibration are becoming the ultimate solution to achieve lifetime reliability. This dissertation introduces two ADC testing algorithms and two ADC built-in self-test circuit implementations to test the ADC integral nonlinearity (INL) and differential nonlinearity (DNL) on-chip. In the first testing algorithm, the ultrafast stimulus error removal and segmented model identification of linearity errors (USER-SMILE) is developed for ADC built-in self-test, which eliminates the need for precision stimulus and reduces the overall test time. In this algorithm, the ADC is tested twice with a nonlinear ramp, instead of using a linear ramp signal. Therefore, the stimulus can be easily generated on-chip in a low-cost way. For the two ramps, there is a constant voltage shift in between. As the input stimulus linearity is completely relaxed, there is no requirement on the waveform of the input stimulus as long as it covers the ADC input range. In the meantime, the high-resolution ADC linearity is modeled with segmented parameters, which reduces the number of samples required for achieving high-precision test, thus saving the test time. As a result, the USER-SMILE algorithm is able to use less than 1 sample/code nonlinear stimulus to test high resolution ADCs with less than 0.5 least significant bit (LSB) INL estimation error, achieving more than 10-time test time reduction. This algorithm is validated with both board-level implementation and on-chip silicon implementation. The second testing algorithm is proposed to test the INL/DNL for multi-bit-per-stages pipelined ADCs with reduced test time and better test coverage. Due to the redundancy characteristics of multi-bit-per-stages pipelined ADC, the conventional histogram test cannot estimate and calibrate the static linearity accurately. The proposed method models the pipelined ADC nonlinearity as segmented parameters with inter-stage gain errors using the raw codes instead of the final output codes. During the test phase, a pure sine wave is sent to the ADC as the input and the model parameters are estimated from the output data with the system identification method. The modeled errors are then removed from the digital output codes during the calibration phase. A high-speed 12-bit pipelined ADC is tested and calibrated with the proposed method. With only 4000 samples, the 12-bit ADC is accurately tested and calibrated to achieve less than 1 LSB INL. The ADC effective number of bits (ENOB) is improved from 9.7 bits to 10.84 bits and the spurious-free dynamic range (SFDR) is improved by more than 20dB after calibration. In the first circuit implementation, a low-cost on-chip built-in self-test solution is developed using an R2R digital-to-analog converter (DAC) structure as the signal generator and the voltage shift generator for ADC linearity test. The proposed DAC is a subradix-2 R2R DAC with a constant voltage shift generation capability. The subradix-2 architecture avoids positive voltage gaps caused by mismatches, which relaxes the DAC matching requirements and reduces the design area. The R2R DAC based BIST circuit is fabricated in TSMC 40nm technology with a small area of 0.02mm^2. Measurement results show that the BIST circuit is capable of testing a 15-bit ADC INL accurately with less than 0.5 LSB INL estimation error. In the second circuit implementation, a complete SAR ADC built-in self-test solution using the USER-SMILE is developed and implemented in a 28nm automotive microcontroller. A low-cost 12-bit resistive DAC with less than 12-bit linearity is used as the signal generator to test and calibrate a SAR ADC with a target linearity of 12 bits. The voltage shift generation is created inside the ADC with capacitor switching. The entire algorithm processing unit for USER-SMILE algorithm is also implemented on chip. The final testing results are saved in the memory for further digital calibration. Both the total harmonic distortion (THD) and the SFDR are improved by 20dB after calibration, achieving -84.5dB and 86.5dB respectively. More than 700 parts are tested to verify the robustness of the BIST solution

Concepts for on-board satellite image registration. Volume 3: Impact of VLSI/VHSIC on satellite on-board signal processing

Anticipated major advances in integrated circuit technology in the near future are described as well as their impact on satellite onboard signal processing systems. Dramatic improvements in chip density, speed, power consumption, and system reliability are expected from very large scale integration. Improvements are expected from very large scale integration enable more intelligence to be placed on remote sensing platforms in space, meeting the goals of NASA's information adaptive system concept, a major component of the NASA End-to-End Data System program. A forecast of VLSI technological advances is presented, including a description of the Defense Department's very high speed integrated circuit program, a seven-year research and development effort