Comprehensive multisite efficiency equation for semiconductor test equipment

Multisite efficiency (MSE) determines the effectiveness of improving multisite testing throughput, which ultimately affects the cost of tests. As indicated by International Technology Roadmap for Semiconductors 2.0 2015 Edition a decrease of the MSE relative to the test site increment has a negative effect on the testing throughput improvement. However, calculating the MSE accurately needs to consider all related variables such as test time, unit indexing time, tray exchange sequence time, testing yield, jam rate, and production capacity. The MSE equations identified from the previous literature are inaccurate and do not reflect the actual MSE situation. This study develops an equation which incorporates all the relevant variables for better prediction of testing throughput and the cost of test

Energy Efficient Computing with Time-Based Digital Circuits

University of Minnesota Ph.D. dissertation. May 2019. Major: Electrical Engineering. Advisor: Chris Kim. 1 computer file (PDF); xv, 150 pages.Advancements in semiconductor technology have given the world economical, abundant, and reliable computing resources which have enabled countless breakthroughs in science, medicine, and agriculture which have improved the lives of many. Due to physics, the rate of these advancements is slowing, while the demand for the increasing computing horsepower ever grows. Novel computer architectures that leverage the foundation of conventional systems must become mainstream to continue providing the improved hardware required by engineers, scientists, and governments to innovate. This thesis provides a path forward by introducing multiple time-based computing architectures for a diverse range of applications. Simply put, time-based computing encodes the output of the computation in the time it takes to generate the result. Conventional systems encode this information in voltages across multiple signals; the performance of these systems is tightly coupled to improvements in semiconductor technology. Time-based computing elegantly uses the simplest of components from conventional systems to efficiently compute complex results. Two time-based neuromorphic computing platforms, based on a ring oscillator and a digital delay line, are described. An analog-to-digital converter is designed in the time domain using a beat frequency circuit which is used to record brain activity. A novel path planning architecture, with designs for 2D and 3D routes, is implemented in the time domain. Finally, a machine learning application using time domain inputs enables improved performance of heart rate prediction, biometric identification, and introduces a new method for using machine learning to predict temporal signal sequences. As these innovative architectures are presented, it will become clear the way forward will be increasingly enabled with time-based designs

The design and use of a digital radio telemetry system for measuring internal combustion engine piston parameters.

During the course of this project, a digital radio telemetry system has been designed and shown to be capable of measuring parameters from the piston of an internal combustion engine, under load. The impetus for the work stems from the need to sample the appropriate data required for oil degradation analysis and the unavailability of system to perform such sampling. The prototype system was designed for installation within a small Norton Villiers C-30 industrial engine. This choice of engine presented significant design challenges due to the small size of the engine (components and construction) and the crankcase environment. These challenges were manifest in the choice of carrier frequency, antenna size and location, modulation scheme, data encoding scheme, signal attenuation, error checking and correction, choice of components, manufacturing techniques and physical mounting to reciprocating parts. In order to overcome these challenges detailed analysis of the radio frequency spectrum was undertaken in order to minimise attenuation from mechanisms such as, absorption, reflection, motion, spatial arrangement and noise. Another aspect of the project concerned the development of a flexible modus operandi in order to facilitate a number of sampling regimes. In order to achieve such flexibility a two-way communication protocol was implemented enabling the sampling system to be programmed into a particular mode of operation, while in use. Additionally the system was designed to accommodate the range of signals output from most transducer devices. The sampling capabilities of the prototype system were extended by enabling the system to support multiple transducers providing a mixture of output signals; for example both analogue and digital signals have been sampled. Additionally, a facility to sample data in response to triggering stimuli has been tested; specifically a sampling trigger may be derived from the motion of the piston via an accelerometer. Ancillary components, such as interface hardware and software, have been developed which are suitable for the recording of data accessed by the system. This work has demonstrated that multi-transducer, mixed signal monitoring of piston parameters, (such as temperature, acceleration etc.) using a two-way, programmable, digital radio frequency telemetry system is not only possible but provides a means for more advanced instrumentation

NASA Space Engineering Research Center Symposium on VLSI Design

The NASA Space Engineering Research Center (SERC) is proud to offer, at its second symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories and the electronics industry. These featured speakers share insights into next generation advances that will serve as a basis for future VLSI design. Questions of reliability in the space environment along with new directions in CAD and design are addressed by the featured speakers

Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing

Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end of CMOS technology scaling, innovations are required to tackle the challenges in a radically different way. Inspired by the emerging understanding of the computing occurring in a brain and nanotechnology-enabled biological plausible synaptic plasticity, neuromorphic computing architectures are being investigated. Such a neuromorphic chip that combines CMOS analog spiking neurons and nanoscale resistive random-access memory (RRAM) using as electronics synapses can provide massive neural network parallelism, high density and online learning capability, and hence, paves the path towards a promising solution to future energy-efficient real-time computing systems. However, existing silicon neuron approaches are designed to faithfully reproduce biological neuron dynamics, and hence they are incompatible with the RRAM synapses, or require extensive peripheral circuitry to modulate a synapse, and are thus deficient in learning capability. As a result, they eliminate most of the density advantages gained by the adoption of nanoscale devices, and fail to realize a functional computing system. This dissertation describes novel hardware architectures and neuron circuit designs that synergistically assemble the fundamental and significant elements for brain-inspired computing. Versatile CMOS spiking neurons that combine integrate-and-fire, passive dense RRAM synapses drive capability, dynamic biasing for adaptive power consumption, in situ spike-timing dependent plasticity (STDP) and competitive learning in compact integrated circuit modules are presented. Real-world pattern learning and recognition tasks using the proposed architecture were demonstrated with circuit-level simulations. A test chip was implemented and fabricated to verify the proposed CMOS neuron and hardware architecture, and the subsequent chip measurement results successfully proved the idea. The work described in this dissertation realizes a key building block for large-scale integration of spiking neural network hardware, and then, serves as a step-stone for the building of next-generation energy-efficient brain-inspired cognitive computing systems

Data systems elements technology assessment and system specifications, issue no. 2

The ability to satisfy the objectives of future NASA Office of Applications programs is dependent on technology advances in a number of areas of data systems. The hardware and software technology of end-to-end systems (data processing elements through ground processing, dissemination, and presentation) are examined in terms of state of the art, trends, and projected developments in the 1980 to 1985 timeframe. Capability is considered in terms of elements that are either commercially available or that can be implemented from commercially available components with minimal development

The 1991 3rd NASA Symposium on VLSI Design

Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Digital System Design - Use of Microcontroller

Embedded systems are today, widely deployed in just about every piece of machinery from toasters to spacecraft. Embedded system designers face many challenges. They are asked to produce increasingly complex systems using the latest technologies, but these technologies are changing faster than ever. They are asked to produce better quality designs with a shorter time-to-market. They are asked to implement increasingly complex functionality but more importantly to satisfy numerous other constraints. To achieve the current goals of design, the designer must be aware with such design constraints and more importantly, the factors that have a direct effect on them.One of the challenges facing embedded system designers is the selection of the optimum processor for the application in hand; single-purpose, general-purpose or application specific. Microcontrollers are one member of the family of the application specific processors.The book concentrates on the use of microcontroller as the embedded system?s processor, and how to use it in many embedded system applications. The book covers both the hardware and software aspects needed to design using microcontroller.The book is ideal for undergraduate students and also the engineers that are working in the field of digital system design.Contents• Preface;• Process design metrics;• A systems approach to digital system design;• Introduction to microcontrollers and microprocessors;• Instructions and Instruction sets;• Machine language and assembly language;• System memory; Timers, counters and watchdog timer;• Interfacing to local devices / peripherals;• Analogue data and the analogue I/O subsystem;• Multiprocessor communications;• Serial Communications and Network-based interfaces