Effect of Temperature of Electrolyte Solution On Cu/Ni Layer On Low-Temperature Voltage Range Measurement Performance

The electroplating method is considered an economical way in coating manufacture. However, this method is more widely used to treat chemical waste management and material properties engineering. The purpose of this research is to make a low-temperature sensor Cu/Ni film using an electroplating method assisted by an external magnetic field. The materials used are nickel (Ni) and copper (Cu), placed as anode and cathode. The electrolyte solution used is made from a mixture of H3BO3 (40 g/L), NiSO4 (260 g/L), and NiCl2 (60 g/L). The deposition process is carried out using an external magnetic field of 200 G and installed perpendicular to the deposition current, 120 s deposition time, and 3 Volt voltage. Preparation of Cu/Ni layer sensor samples is done by changing the electrolyte solution's temperature by varying the temperature between 30 ºC to 70 ºC with intervals of 10 ºC. The results of the research show that in testing the performance of the low-temperature sensor, each Cu/Ni layer sample has been able to offer its character as a low-temperature sensor. The character is indicated by changes in the output voltage's value following changes in the thermocouple value. Each sample at variations in the temperature of the electrolyte solution shows that the measured voltage range varies with the most extensive voltage range the sample has with deposition at 60 ºC.Keywords: Electrolyte Solution Temperature, Voltage Range, Cu/Ni layer, Low-Temperature Sensor, Electroplating

DynOR: A 32-bit Microprocessor in 28 nm FD-SOI with Cycle-By-Cycle Dynamic Clock Adjustment

This paper presents DynOR, a 32-bit 6-stage OpenRISC microprocessor with dynamic clock adjustment. To alleviate the issue of unused dynamic timing margins, the clock period of the processor is adjusted on a cycle-by-cycle level, based on the instruction types currently in flight in the pipeline. To this end, we employ a custom designed clock generation unit, capable of immediate glitch-free adjustments of the clock period over a wide range with fine granularity. Our chip measurements in 28nm FD-SOI technology show that DynOR provides an average speedup of 19% in program execution over a wide range of operating conditions, with a peak speedup for certain applications of up to 41%. Furthermore, this speedup can be traded off against energy, to reduce the chip power consumption for a typical die by up to 15%, compared to a static clocking scheme based on worst case excitation

Predictable GPUs Frequency Scaling for Energy and Performance

Dynamic voltage and frequency scaling (DVFS) is an important solution to balance performance and energy consumption, and hardware vendors provide management libraries that allow the programmer to change both memory and core frequencies. The possibility to manually set these frequencies is a great opportunity for application tuning, which can focus on the best applicationdependent setting. However, this task is not straightforward because of the large set of possible configurations and because of the multi-objective nature of the problem, which minimizes energy consumption and maximizes performance. This paper proposes a method to predict the best core and memory frequency configurations on GPUs for an input OpenCL kernel. Our modeling approach, based on machine learning, first predicts speedup and normalized energy over the default frequency configuration. Then, it combines the two models into a multi-objective one that predicts a Pareto-set of frequency configurations. The approach uses static code features, is built on a set of carefully designed microbenchmarks, and can predict the best frequency settings of a new kernel without executing it. Test results show that our modeling approach is very accurate on predicting extrema points and Pareto set for ten out of twelve test benchmarks, and discover frequency configurations that dominate the default configuration in either energy or performance.DFG, 360291326, CELERITY: Innovative Modellierung für Skalierbare Verteilte Laufzeitsystem

Synthesis constraint optimization for near-threshold voltage design

Near-threshold voltage (NTV) design is a viable solution to many embedded systems which require high energy efficiencies and low performances, but it makes them vulnerable to process variation. Increasing the size of devices and/or decreasing the operating frequencies of the systems can be the solutions, but these methods decrease the energy efficiencies which is cancelling out the benefit from NTV. In this work, we test multiple logic synthesis options on openMSP430 microcontroller with TSMC 65nm technology library and suggest the optimal design points to the future IC designers. We find synthesizing the microcontroller with the minimum design constraint gives us the best performance and energy consumption. We also run Monte Carlo simulation to show the estimated yield rate of the suggested design points

A survey of system level power management schemes in the dark-silicon era for many-core architectures

Power consumption in Complementary Metal Oxide Semiconductor (CMOS) technology has escalated to a point that only a fractional part of many-core chips can be powered-on at a time. Fortunately, this fraction can be increased at the expense of performance through the dark-silicon solution. However, with many-core integration set to be heading towards its thousands, power consumption and temperature increases per time, meaning the number of active nodes must be reduced drastically. Therefore, optimized techniques are demanded for continuous advancement in technology. Existing efforts try to overcome this challenge by activating nodes from different parts of the chip at the expense of communication latency. Other efforts on the other hand employ run-time power management techniques to manage the power performance of the cores trading-off performance for power. We found out that, for a significant amount of power to saved and high temperature to be avoided, focus should be on reducing the power consumption of all the on-chip components. Especially, the memory hierarchy and the interconnect. Power consumption can be minimized by, reducing the size of high leakage power dissipating elements, turning-off idle resources and integrating power saving materials

Robust Circuit Design for Low-Voltage VLSI.

Voltage scaling is an effective way to reduce the overall power consumption, but the major challenges in low voltage operations include performance degradation and reliability issues due to PVT variations. This dissertation discusses three key circuit components that are critical in low-voltage VLSI. Level converters must be a reliable interface between two voltage domains, but the reduced on/off-current ratio makes it extremely difficult to achieve robust conversions at low voltages. Two static designs are proposed: LC2 adopts a novel pulsed-operation and modulates its pull-up strength depending on its state. A 3-sigma robustness is guaranteed using a current margin plot; SLC inherently reduces the contention by diode-insertion. Improvements in performance, power, and robustness are measured from 130nm CMOS test chips. SRAM is a major bottleneck in voltage-scaling due to its inherent ratioed-bitcell design. The proposed 7T SRAM alleviates the area overhead incurred by 8T bitcells and provides robust operation down to 0.32V in 180nm CMOS test chips with 3.35fW/bit leakage. Auto-Shut-Off provides a 6.8x READ energy reduction, and its innate Quasi-Static READ has been demonstrated which shows a much improved READ error rate. A use of PMOS Pass-Gate improves the half-select robustness by directly modulating the device strength through bitline voltage. Clocked sequential elements, flip-flops in short, are ubiquitous in today’s digital systems. The proposed S2CFF is static, single-phase, contention-free, and has the same number of devices as in TGFF. It shows a 40% power reduction as well as robust low-voltage operations in fabricated 45nm SOI test chips. Its simple hold-time path and the 3.4x improvement in 3-sigma hold-time is presented. A new on-chip flip-flop testing harness is also proposed, and measured hold-time variations of flip-flops are presented.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111525/1/yejoong_1.pd

Design of energy-efficient high-speed wireline transceiver

Energy efficiency has become the most important performance metric of integrated circuits used in many applications ranging from mobile devices to high-performance processors. The power problem permeates both computing and communication systems alike. Especially in the era of Big Data, continuously growing demand for higher communication bandwidth is driving the need for energy-efficient high-speed I/O serial links. However, the rate at which the energy efficiency of serial links is improving is much slower than the rate at which the required data transfer bandwidth is increasing. This dissertation explores two design approaches for energy-efficient communication systems. The first design approach maximizes the energy efficiency of a transceiver without any performance loss, and as a prototype, a source-synchronous multi-Gb/s transceiver that achieves excellent energy efficiency lower than 0.3pJ/bit is presented. To this end, the proposed transceiver employs aggressive supply voltage scaling, and multiplexed transmitter and receiver synchronized by low-rate multi-phase clocks are adopted to achieve high data rate even at a supply voltage close to the device threshold voltage. Phase spacing errors resulting from device mismatches are corrected using a self-calibration scheme. The proposed phase calibration method uses a single digital delay-locked loop (DLL) for calibrating all the phases, which makes the calibration process insensitive to the supply voltage level. Thanks to this technique, the proposed multi-Gb/s transceiver operates robustly and energy-efficiently at a very low supply voltage. Fabricated in a 65nm CMOS process, the energy efficiency and data rate of the prototype transceiver vary from 0.29pJ/bit to 0.58pJ/bit and 1Gb/s to 6Gb/s, respectively, as the supply voltage is varied from 0.45V to 0.7V. In the second approach, observing that the data traffic in a real system is bursty, a full-rate burst-mode transceiver that achieves rapid on/off operation needed for energy-proportional systems is presented. By injecting input data edges into the oscillator embedded in a classical type-II digital clock and data recovery (CDR) circuit, the proposed receiver achieves instantaneous phase-locking and input jitter filtering simultaneously. In other words, the proposed CDR combines the advantages of conventional feed-forward and feedback architectures to achieve energy-proportional operation. By controlling the number of data edges injected into the oscillator, both the jitter transfer bandwidth and the jitter tolerance corner are accurately controlled. The feedback loop also corrects for any frequency error and helps improve the CDR's immunity to oscillator frequency drift during the power-on and -off states. This also improves the CDR's tolerance to consecutive identical digits present in the input data. Fabricated in a 90nm CMOS process, the prototype receiver instantaneously locks onto the very first data edge and consumes 6.1mW at 2.2Gb/s. Owing to its short power-on time, the overall transceiver's energy efficiency varies only from 5.4pJ/bit to 10.7pJ/bit when the effective data rate is varied from 2.2Gb/s to 0.22Gb/s

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing

Exploiting Natural On-chip Redundancy for Energy Efficient Memory and Computing

Power density is currently the primary design constraint across most computing segments and the main performance limiting factor. For years, industry has kept power density constant, while increasing frequency, lowering transistors supply (Vdd) and threshold (Vth) voltages. However, Vth scaling has stopped because leakage current is exponentially related to it. Transistor count and integration density keep doubling every process generation (Moore’s Law), but the power budget caps the amount of hardware that can be active at the same time, leading to dark silicon. With each new generation, there are more resources available, but we cannot fully exploit their performance potential. In the last years, different research trends have explored how to cope with dark silicon and unlock the energy efficiency of the chips, including Near-Threshold voltage Computing (NTC) and approximate computing. NTC aggressively lowers Vdd to values near Vth. This allows a substantial reduction in power, as dynamic power scales quadratically with supply voltage. The resultant power reduction could be used to activate more chip resources and potentially achieve performance improvements. Unfortunately, Vdd scaling is limited by the tight functionality margins of on-chip SRAM transistors. When scaling Vdd down to values near-threshold, manufacture-induced parameter variations affect the functionality of SRAM cells, which eventually become not reliable. A large amount of emerging applications, on the other hand, features an intrinsic error-resilience property, tolerating a certain amount of noise. In this context, approximate computing takes advantage of this observation and exploits the gap between the level of accuracy required by the application and the level of accuracy given by the computation, providing that reducing the accuracy translates into an energy gain. However, deciding which instructions and data and which techniques are best suited for approximation still poses a major challenge. This dissertation contributes in these two directions. First, it proposes a new approach to mitigate the impact of SRAM failures due to parameter variation for effective operation at ultra-low voltages. We identify two levels of natural on-chip redundancy: cache level and content level. The first arises because of the replication of blocks in multi-level cache hierarchies. We exploit this redundancy with a cache management policy that allocates blocks to entries taking into account the nature of the cache entry and the use pattern of the block. This policy obtains performance improvements between 2% and 34%, with respect to block disabling, a technique with similar complexity, incurring no additional storage overhead. The latter (content level redundancy) arises because of the redundancy of data in real world applications. We exploit this redundancy compressing cache blocks to fit them in partially functional cache entries. At the cost of a slight overhead increase, we can obtain performance within 2% of that obtained when the cache is built with fault-free cells, even if more than 90% of the cache entries have at least a faulty cell. Then, we analyze how the intrinsic noise tolerance of emerging applications can be exploited to design an approximate Instruction Set Architecture (ISA). Exploiting the ISA redundancy, we explore a set of techniques to approximate the execution of instructions across a set of emerging applications, pointing out the potential of reducing the complexity of the ISA, and the trade-offs of the approach. In a proof-of-concept implementation, the ISA is shrunk in two dimensions: Breadth (i.e., simplifying instructions) and Depth (i.e., dropping instructions). This proof-of-concept shows that energy can be reduced on average 20.6% at around 14.9% accuracy loss